National Center For Research Resources Research Articles

175-OR: Pregnancy Intervention with a Closed-Loop System (PICLS) Study

We performed a parallel, two-site, randomized controlled trial of a commercially available hybrid closed-loop (HCL) system compared to sensor augmented pump therapy (SAPT) in pregnant women with type 1 diabetes (T1D). Participants started SAPT (Medtronic 670G) by 11 weeks gestation, were randomized at 14-18 weeks, and continued therapy until 6 weeks postpartum. The HCL group used assistive techniques, “fake carbohydrate” boluses, to optimize therapy. We performed linear mixed model regression to compare outcomes between groups, adjusted for clinic. There were 24 women randomized and 23 completers. At baseline there were no significant differences between groups (mean baseline A1C 6.8% at 8w5d [SAPT]/9w0d [HCL] enrollment). There were no episodes of severe hypoglycemia or diabetic ketoacidosis after randomization. Adverse skin reactions occurred in 6 participants (5 SAPT vs 1 HCL, p=0.1550) with a median (IQR) number of 1 (1-2) SAPT vs 4 (4-4) HCL (p=0.8774). A1C significantly decreased from baseline to 2nd trimester, and was different between groups in the 3rd trimester (Table 1). There were no differences in time below, within, or above range between groups during the study (Table 1) or in gestational health outcomes (Table 2). In a pilot cohort of pregnant women with T1D, assisted HCL therapy did not increase risk to mothers or fetuses compared to SAPT despite lack of a pregnancy-specific algorithm in the HCL system. Disclosure E.Buschur: Consultant; Beta Bionics, Inc., Research Support; Dexcom, Inc., JDRF, Leona M. and Harry B. Helmsley Charitable Trust. E.R.Nease: None. S.Polsky: Other Relationship; diaTribe, Research Support; Dexcom, Inc., Medtronic, Hemsley Charitable Trust, JDRF, NIH - National Institutes of Health. J.K.Snell-bergeon: None. L.Pyle: None. R.Garcetti: None. K.M.Dungan: Board Member; Elsevier, Consultant; Eli Lilly and Company, Dexcom, Inc., Other Relationship; UpToDate, Research Support; Dexcom, Inc., Abbott, ViaCyte, Inc., Sanofi, Speaker's Bureau; Academy for Continued Healthcare Learning, Cardiometabolic Health Congress, Medscape, Integritas. S.F.Thung: None. A.Bartholomew: None. T.Summerfield: None. T.Bloks: None. Funding JDRF (2-SRA-2018-666-M-R); Colorado Clinical and Translational Sciences Institute; Children’s Diabetes Foundation; National Center for Research Resources (UL1RR02578)

Brain Scans May Offer Clues About Depression Remission

Back to table of contents Previous article Next article Clinical & ResearchFull AccessBrain Scans May Offer Clues About Depression RemissionNick ZagorskiNick ZagorskiSearch for more papers by this authorPublished Online:23 Mar 2023https://doi.org/10.1176/appi.pn.2023.04.4.4AbstractMany brain imaging studies have looked at key differences between the brains of people with or without depression. An AJP study examined how the brain changes when patients with depression get better.People with depression who have been successfully treated with antidepressants exhibit distinct changes in the brain relative to those successfully treated with cognitive-behavioral therapy (CBT), according to a report in The American Journal of Psychiatry.“Despite the theorized differences in how antidepressants and CBT exert their effects, no controlled study has explored the impact on the brain of these two very different types of treatment,” said Boadie Dunlop, M.D., the lead author of the report. “There is a lot of interest in using brain imaging to identify differences between people with or without depression, but it is also important to understand what happens to the brain when it gets better.” Dunlop is an associate professor of psychiatry and director of the Mood and Anxiety Disorders Program at Emory University School of Medicine.Dunlop and colleagues used data collected as part of the Predictors of Remission in Depression to Individual and Combined Treatments (PReDICT) trial. For this trial, 344 adults aged 18 to 65 with major depressive disorder who had never been treated for the disorder were randomized to receive 12 weeks of escitalopram, duloxetine, or CBT. The subjects underwent a functional MRI (fMRI) scan before and after the 12-week study.Using the PReDICT data, Dunlop and colleagues in 2017 reported that they had identified baseline brain connectivity patterns that could reliably predict whether patients would respond to CBT or antidepressants. For the current study, the researchers examined data from 131 PReDICT participants who completed the 12-week trial and had two fMRI scans (one at baseline, one after 12 weeks) to identify changes in connectivity.In total, 49.5% of the participants who took medication and 47.5% who received CBT achieved remission—defined as a score of 7 or less on the 17-item Hamilton Depression Rating (HAM-D) Scale.The researchers observed a stark difference in the scans of the participants after they received 12 weeks of treatment. In general, people who achieved remission following use of antidepressants showed reduced connectivity (electrical activity) between certain brain regions compared with baseline. In contrast, people who achieved remission following CBT had increased connectivity between these same regions.These changes in brain connectivity did not occur in people who did not achieve remission, regardless of treatment. This suggests the changes are not simply due to receiving medication or therapy, but the individual’s response to it, Dunlop said.Notably, remission following CBT was associated with stronger connections between the brain regions that control executive function—the cognitive ability to process and prioritize information to complete a task—and attention. Executive function is often impaired in patients who are depressed, which can result in negative attitudes and beliefs being prioritized by the brain before positive ones, Dunlop explained. Cognitive training helps people to identify maladaptive thoughts and push these thoughts away.“To my knowledge, this is the first biological demonstration that the core target of CBT is activated in people who respond to therapy, and this activation is specific to CBT,” Dunlop said. He added that people who showed greater connectivity increases in the executive function network after 12 weeks also had greater improvements in HAM-D scores, supporting that this network is engaged during CBT.Depression-Movement ConnectionWhile the participants’ brain scans primarily showed that medications and CBT generally had opposite effects on connectivity, they had one change in common: People who achieved remission with either CBT or antidepressants showed reduced brain connectivity between the subcallosal cingulate cortex (a central hub for processing emotions) and the motor cortex (which controls movement).“When people are no longer depressed, they frequently report it is easier to initiate motor actions, such as getting out of bed or moving more quickly from one place to another,” Dunlop said. It’s possible that in depressed people, the extra burden of negative emotions processed by the subcallosal cingulate cortex may cause increased inhibition of the motor cortex, he continued. As depressive symptoms lessen, motor activity increases.“This is all speculation, though, since our data cannot tell us the direction of the information exchange,” Dunlop cautioned.Dunlop believes these findings provide neurological evidence to support the clinical practice of switching or combining treatment modalities if someone doesn’t respond to a first-line treatment. Since CBT and antidepressants are associated with distinct brain connectivity changes, a patient who doesn’t respond to one may be more likely to respond to the other.Dunlop’s team is now analyzing two-year follow-up data collected from the PReDICT participants to determine if there are clues in the fRMI images regarding patients who are most likely to experience depression relapse.“We need to improve the long-term management of this disorder,” he said. “Right now, it’s typical to keep people on maintenance antidepressant therapy, but not everyone needs that. If we can better predict who can stop treatment or should continue, that would meet an enormous public health need.”The PReDICT study and subsequent analyses were supported by multiple grants from the National Institute of Mental Health and National Center for Research Resources. Forest Laboratories and Eli Lilly donated the escitalopram and duloxetine, respectively, used in the trial. ■Resources“Shared and Unique Changes in Brain Connectivity Among Depressed Patients After Remission With Pharmacotherapy Versus Psychotherapy”“Functional Connectivity of the Subcallosal Cingulate Cortex And Differential Outcomes to Treatment With Cognitive-Behavioral Therapy or Antidepressant Medication for Major Depressive Disorder” ISSUES NewArchived

Reply Re: "Correlation of Automated Computed Tomography Volumetric Analysis Metrics With Motility Disturbances in Thyroid Eye Disease".

Accepted for publication December 17, 2022. The sponsor or funding organization had no role in the design or conduct of this research. Supported in part by an unrestricted grant to the Vanderbilt Eye Institute and Physician Scientist Award from Research to Prevent Blindness, New York, NY. This project was supported by NIH 1R03EB012461, 1R21EY024036, and the National Center for Research Resources, Grant UL1 RR024975-01 (now at the National Center for Advancing Translational Sciences, Grant 2 UL1 TR000445-06). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. This work was conducted in part using the resources of the Advanced Computing Center for Research and Education at Vanderbilt University, Nashville, TN. L.M. has been a consultant to Horizon Therapeutics. The other author has no financial or conflicts of interest to disclose. Correspondence: Louise Mawn, M.D., Vanderbilt Eye Institute, 2311 Pierce Avenue, Nashville, TN 37232 ([email protected])

1009-P: The Association between Patient Characteristics and the Efficacy of Remote Patient Monitoring and Messaging

In the Pilot 4T study (n=135) , remote patient monitoring (RPM) was associated with improved time in range (TIR) and lower A1c. Measuring differences in how patients respond to messages from the care team is essential for the design of effective, personalized care models. We analyzed electronic health record (EHR) and continuous glucose monitor (CGM) data to estimate the week-over-week impact of RPM messages on patients’ TIR. We applied statistical clustering methods to divide patients who received messages into two groups based on their changes in TIR and compared the characteristics of these groups. Receiving a message was associated with a greater mean week-to-week improvement in TIR after a low-TIR week [4.9 percentage points (pp) after a message vs. 2.5pp without a message; p < 0.001]. A patient’s TIR improvement after receiving a message is greater on average if the same patient’s TIR improved following previous messages. We identified two groups of patients with significantly different responses to messages. The group with greater mean TIR improvement after messages contains a larger proportion of non-white, non-English speaking, and publicly insured patients. We found that messages were associated with different magnitudes of TIR improvement across two clusters of patients. Identifying patients who benefit more from RPM could facilitate the personalization of management strategies. Disclosure J.Ferstad: None. P.Prahalad: None. D.M.Maahs: Advisory Panel; Abbott Diabetes, Eli Lilly and Company, Medtronic, Novo Nordisk, Sanofi, Consultant; Aditx Therapeutics, Inc., Biospex. E.Fox: None. R.Johari: None. D.Scheinker: None. Funding Helmsley Charitable Trust, ISPAD-JDRF Fellowship,NIH R18DK122422,Stanford Diabetes Research Center,LPCH Auxiliaries,Stanford Maternal and Child Health Research Institute, The Stanford REDCap platform (http://redcap.stanford.edu) is developed and operated by Stanford Medicine Research IT team. The REDCap platform services at Stanford are subsidized by a) Stanford School of Medicine Research Office, and b) the National Center for Research Resources and the National Center for Advancing Translational Sciences, National Institutes of Health, through grant UL1 TR001085.

888-P: A Model to Assess the Financial Feasibility of Telemedicine-Based Pediatric T1D Care in Value-Based Care and Fee-for-Service Settings

We previously examined a type 1 diabetes care model based on the use of a remote patient monitoring (RPM) tool that analyzes CGM data. The care model was associated with improved glucose management and reduced provider effort. We compare the financial feasibility of this care model in value-based care (VBC) and fee-for-service (FFS) settings. We set parameters based on the current deployment of the care model. In the FFS setting, we estimated Medicare reimbursement rates and labor costs for in-person diabetes education. We compared these to costs in a VBC setting where providers make prospective payments for RPM services. We evaluated the financial impact of the care model across a variety of parameters (Fig) . In a FFS setting, we estimated that in-person care incurs net costs of $1per patient. Under a VBC contract, we estimated that prospective payments are offset by reduced labor costs, incurring net costs of $65 per patient (i.e., 49% savings) . These results are sensitive to input parameters (Fig) . We identified financially viable payment models for an algorithm-enabled telemedicine-based care model associated with improved T1D glucose management. The analysis may inform operational planning at the clinic level as well as reimbursement policy design. Disclosure R.Leonard pei: None. P.Dupenloup: None. P.Prahalad: None. R.Johari: None. A.Addala: None. D.P.Zaharieva: Research Support; Insulet Corporation, International Society for Pediatric and Adolescent Diabetes, Leona M. and Harry B. Helmsley Charitable Trust. D.M.Maahs: Advisory Panel; Abbott Diabetes, Eli Lilly and Company, Medtronic, Novo Nordisk, Sanofi, Consultant; Aditx Therapeutics, Inc., Biospex. D.Scheinker: None. Funding Helmsley Charitable Trust.ISPAD-JDRF Fellowship.R18DK122422.SDRC.LPCH Auxiliaries.The Stanford REDCap platform (http://redcap.stanford.edu) is developed and operated by Stanford Medicine Research IT team. The REDCap platform services at Stanford are subsidized by a) Stanford School of Medicine Research Office, and b) the National Center for Research Resources and the National Center for Advancing Translational Sciences, National Institutes of Health, through grant UL1 TR001085.Stanford Maternal and Child Health Research Institute.

0676 Increased Depression Symptoms are Associated with Higher Nightmare Frequency within the Wisconsin Sleep Cohort

Abstract Introduction Nightmare frequency has been suggested as a strong clinical indicator of psychiatric disorders. Additionally, frequent nightmares are a possible underrepresented outcome of depression. As nightmares may increase the risk of negative health outcomes, such as suicide attempts, understanding possible sources of nightmare frequency is imperative. This study sought to examine the association between depression and anxiety on the incidence of high frequency of nightmares. Methods Using cross-sectional and longitudinal data from the Wisconsin Sleep Cohort, accessed through the National Sleep Research Resource, we conducted an analysis of demographics, co-occurring sleep disturbances, and mental health measures of participants experiencing ordinal frequencies of nightmares. The study sample included 758 Wisconsin state employees with a baseline and follow-up assessment (mean 4.46 years between visits; standard deviation 1.7). All participants were screened for depression and anxiety symptoms using the Zung Depression Scale (SDS), and the State-Trait Anxiety Inventory. Sleep disturbances, medication use, nightmares and insomnia were based on self-report. Nightmare frequency was categorized as high (≥2 per month) and low (<2 per month). Logistic regression was used to determine the association of baseline anxiety and depression scales (in the same model) with incidence of high nightmare frequency at follow-up, adjusted by age, sex, body mass index, hypertension medications, use of narcotics and caffeine. Results After adjusting for covariates, SDS scores at baseline were associated with an increased incidence of higher frequency of nightmares at follow-up (OR=1.05; 95%CI=1.01-1.10, p = 0.026), while anxiety at baseline was not (OR=1.03; 95%CI=0.99-1.07; p = 0.165). An increase in one unit of the SDS was associated with a 5% increase in the odds of presenting higher frequency nightmares at follow-up. Conclusion Participants with higher SDS scores had higher incidence of high frequency of nightmares upon follow up, however, those with anxiety did not. Further research should be targeted at gaining better understanding of the role of psychiatric conditions on the onset of nightmares. Support (If Any) NIH NHLBI (R01HL62252), NIA (R01AG036838, R01AG058680), and National Center for Research Resources (1UL1RR025011). The National Sleep Research Resource was supported by NIH-NHLBI (R24 HL114473, 75N92019R002).

0115 Discrepancies Between Actual and Ideal Bedtime are Associated with Cognitive Performance

Abstract Introduction Experimental studies have shown that acute sleep-circadian misalignment can lead to cognitive deficits. Additionally, chronic jetlag among pilots and long-term exposure to shiftwork are associated with worse cognitive performance. This study investigated whether small daily discrepancies in actual versus perceived ideal bedtime are associated with cognitive performance. Methods A subset of Wisconsin Sleep Cohort study participants (N=750; 58% male; mean[range] age 59 [38-78] years) participated in a neurocognitive test battery, provided a 6-night sleep diary, and completed questionnaires at the same study visit. The neurocognitive assessment included the Controlled Oral Word Association Test, Trails Making Test Part B, Grooved Pegboard Test, Auditory Verbal Learning Test, Digit Cancellation, and Symbol Digit Modalities Test. Weekday bedtimes from the sleep diary were averaged to represent “actual” bedtime. “Ideal” bedtime was represented by the answer to the question from the Horne-Ostberg Morningness-Eveningness Questionnaire: If you were free of any schedule and could go to bed at any time you wanted, what time would that be? Bedtime mismatch was represented as (ideal bedtime – actual bedtime). Cognitive performance was regressed on bedtime mismatch (separate models for each cognitive test) in linear regression models, adjusting for age, sex, BMI, sedative and stimulant use, average total sleep time, actual bedtime, smoking, caffeine consumption, and education level. Results There was a significant association between bedtime mismatch and performance on both the Grooved Pegboard (p=0.02) and Symbol Digit Modalities (p=0.02) tests, and a borderline significant association (p=0.09) with performance on the Oral Word test. On average, participants that had actual bedtimes that were later than ideal bedtimes demonstrated worse cognitive performance, while actual bedtimes that were earlier than ideal bedtimes were associated with better performance. No associations were found for the other 3 cognitive tests. Conclusion Going to bed at a time that is later than perceived ideal bedtime may be associated with cognitive deficits, even after accounting for actual bedtime and total sleep time. Support (If Any) This work was supported by the National Heart, Lung, and Blood Institute (R01HL62252), National Institute on Aging (R01AG058680) and the National Center for Research Resources (1UL1RR025011) at the US National Institutes of Health.

0030 Development and Validation of a Metabolomic Risk Score for Obstructive Sleep Apnea across Race/Ethnicities

Abstract Introduction Obstructive sleep apnea (OSA) is a common disorder characterized by recurrent episodes of upper airway obstruction during sleep resulting in oxygen desaturation and sleep fragmentation, and associated with increased risk of adverse health outcomes. Metabolites are being increasingly used for biomarker discovery and evaluation of disease processes and progression. We aimed to develop a metabolomic risk score (MRS) for OSA and identify individual metabolites associated with OSA to provide insights into the pathogenesis of OSA. Methods We studied 219 metabolites and their associations the apnea hypopnea index (AHI) and with OSA, defined as AHI , in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) (n=3507) using two methods: (1) association analysis of individual metabolites, and (2) least absolute shrinkage and selection operator (LASSO) regression to identify a subset of metabolites that are jointly associated with OSA, and develop an MRS. We then validated the results in Multi-Ethnic Study of Atherosclerosis (MESA) (n=475), an independent dataset. Results HCHS/SOL participants were 41.72 years old on average, 50.7% female, and 10.2% had OSA. MESA individuals were 68.45 years old on average, 56.2% females, and 46.7% had OSA. When assessing the associations between OSA/AHI and individual metabolites, we identified seven metabolites significantly and positively associated with OSA in HCHS/SOL (FDR p<0.05), of which four associations - glutamate, oleoyl-linoleoyl-glycerol (18:1/18:2) (DAG(36:3)), linoleoyl-linoleoyl-glycerol (18:2/18:2) (DAG(36:4)) and phenylalanine, replicated in MESA (one sided-p value<0.05). The OSA-MRS, composed of 14 metabolites, was associated with 52% increase of risk for moderate to severe OSA (OR=1.52 [95% CI: 1.23-1.87] per 1 SD of OSA-MRS, p<.001) in the discovery dataset of HCHS/SOL and 44% increased risk (OR=1.44 [95% CI: 1.03-2.03] per 1 SD of OSA-MRS, p=0.034) in the validation dataset of MESA, both adjusted for demographic, lifestyle, and comorbidities. Similar albeit less significant associations were observed for AHI modeled continuously. Conclusion We developed an MRS that replicated in an independent multi-ethnic dataset, demonstrating the robustness of metabolomic-based OSA risk score to population heterogeneity. Replicated metabolite associations may provide insights into OSA-related molecular and metabolic mechanisms. Support (If Any) Support for metabolomics data was graciously provided by the JLH Foundation (Houston, Texas). The Hispanic Community Health Study/Study of Latinos was carried out as a collaborative study supported by contracts from the National Heart, Lung, and Blood Institute (NHLBI) to the University of North Carolina (N01-HC65233), University of Miami (N01-HC65234), Albert Einstein College of Medicine (N01-HC65235), Northwestern University (N01-HC65236), and San Diego State University (N01-HC65237). The following Institutes/Centers/Offices contribute to the HCHS/SOL through a transfer of funds to the NHLBI: National Center on Minority Health and Health Disparities, the National Institute of Deafness and Other Communications Disorders, the National Institute of Dental and Craniofacial Research, the National Institute of Diabetes and Digestive and Kidney Diseases, the National Institute of Neurological Disorders and Stroke, and the Office of Dietary Supplements. The authors thank the staff and participants of HCHS/SOL for their important contributions. MESA and the MESA SHARe project are conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with MESA investigators. Support for MESA is provided by contracts HHSN268201500003I, N01-HC-95159, N01-HC-95160, N01-HC-95161, N01-HC-95162, N01-HC-95163, N01-HC-95164, N01-HC-95165, N01-HC-95166, N01-HC-95167, N01-HC-95168, N01-HC-95169, UL1-TR-000040, UL1-TR-001079, UL1-TR-001420. MESA Family is conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with MESA investigators. Support is provided by grants and contracts R01HL071051, R01HL071205, R01HL071250, R01HL071251, R01HL071258, R01HL071259, and by the National Center for Research Resources, Grant UL1RR033176. The provision of genotyping data was supported in part by the National Center for Advancing Translational Sciences, CTSI grant UL1TR001881, and the National Institute of Diabetes and Digestive and Kidney Disease Diabetes Research Center (DRC) grant DK063491 to the Southern California Diabetes Endocrinology Research Center. Molecular data for the Trans-Omics in Precision Medicine (TOPMed) program was supported by the National Heart, Lung and Blood Institute (NHLBI). ). Metabolomics for “NHLBI TOPMed: Multi-Ethnic Study of Atherosclerosis (MESA)” (phs001416) was performed at Broad Institute and Beth Israel Metabolomics Platform (HHSN268201600038I). Core support including centralized genomic read mapping and genotype calling, along with variant quality metrics and filtering were provided by the TOPMed Informatics Research Center (3R01HL-117626-02S1; contract HHSN268201800002I). Core support including phenotype harmonization, data management, sample-identity QC, and general program coordination were provided by the TOPMed Data Coordinating Center (R01HL-120393; U01HL-120393; contract HHSN268201800001I). We gratefully acknowledge the studies and participants who provided biological samples and data for TOPMed. This study was supported by NHLBI grant R35HL135818.

0414 Estimated Prevalence of Idiopathic Hypersomnia in the Wisconsin Sleep Cohort

Abstract Introduction Idiopathic hypersomnia (IH) is a neurologic condition characterized by chronic excessive daytime sleepiness despite normal sleep duration in which sleepiness is unexplained by other sleep disorders, behaviors, or other identifiable causes. Population-based prevalence estimates of IH are unavailable, though a recent analysis of a US insured population found ~1/10,000 persons were diagnosed with IH. Here we estimate IH prevalence in the Wisconsin Sleep Cohort (WSC). Methods The WSC is an epidemiology cohort recruited from a working population. To characterize IH we used measures of subjective (Epworth Sleepiness Scale, ESS) and objective sleepiness (Multiple Sleep Latency Tests, MSLT), polysomnography, sleep diaries, and extensive questionnaires. IH was defined as the union of: ESS>10; MSLT<8 minutes; <2 sleep-onset REM periods; apnea-hypopnea index (AHI)<15 (we also estimated prevalence using an AHI<5 cutpoint); >=6 hours habitual daily sleep; and non-shift worker. Other explanations for sleepiness were also investigated. Results Among 792 WSC participants (48% female, mean age=59 years [range=40-78 years]), we estimate an IH prevalence=3.8%, 95% CI=2.6-5.4%). We arrived at this estimate thusly: of n=792 participants, n=275 (35%) had ESS>10; of these, n=89 had MSLT<8 minutes; of these, n=71 had <2 sleep onset REM periods; of these, n=35 had an AHI<15; of these, n=33 slept >=6 hours/night; and, of these, n=30 were non-shift workers. Comparing the 30 so-defined “IH participants” to non-IH participants, respectively: 57% (IH) vs. 48% (non-IH) (NS) were female, mean age was 57 vs. 59 years (NS), mean AHI was 4.6 vs. 13.3 (by definition of IH, mean AHI was lower for IH participants), mean sleep duration was 7.6 vs. 7.7 hours (NS), and sedative use prevalence was 3% vs. 10% (NS). No IH participants reported a history of heart failure, heart attack or stroke. Prevalence of IH using an AHI cutpoint of 5 (i.e., IH only classified in participants with AHI<5), we find an IH prevalence of 2.4% (95% CI=1.5-3.7%). Conclusion Idiopathic hypersomnia may be more prevalent than previously assumed: approximately 2 to 4% of Wisconsin Sleep Cohort participants had evidence of hypersomnia that could not be explained by other sleep disorders, insufficient sleep, shift work or other examined factors. Support (If Any) This work was supported by the National Heart, Lung, and Blood Institute (NHLBI, R01HL62252), National Institute on Aging (NIA, R01AG058680) and the National Center for Research Resources (NCRR, 1UL1RR025011) at the US National Institutes of Health, as well as a grant from Jazz Pharmaceuticals.

How the Patient-clinician Relationship Influences Treatment Experiences and Outcomes in Chronic Pain Patients: An fMRI Hyperscan Study

The patient-clinician therapeutic alliance is a powerful modulator shaping patients' treatment experience and clinical outcomes. Before and after a 3-week electro-acupuncture intervention (6 sessions), fMRI hyper-scanning was applied to investigate the influence of either an Augmented (warm/attentive) or a Limited (neutral/business-like) clinician interaction style. Eighteen women with fibromyalgia (mean age=41.41, SD=12.20, each group N=9), randomly assigned to an Augmented or Limited patient-clinician dyadic interaction style (trained acupuncturists), underwent a simultaneously recorded fMRI hyper-scanning procedure with a video connection between two scanners and an evoked cuff pressure pain/treatment paradigm. Questionnaires were used to assess the patients' experience by targeting treatment-related changes such as clinical pain levels, therapeutic alliance, trust, the clinician's warmth and competence, and the probability of continuing the treatment with this clinician after study participation. As rated by patients, pooled therapeutic alliance and clinicians' warmth in the Augmented (mean_alliance=43.21, SD=2.40; mean_warmth=4.00, SD=0.0) were significantly higher than in the Limited group (mean_alliance=22.79, SD=13.15; mean_warmth=2.54, SD=1.10; t_alliance(16)=4.31, p<0.001; t_warmth(16)=3.74; p=0.002). Additionally, over the course of all 6 acupuncture treatment sessions, most patients experienced immediate clinical pain relief after each treatment session (p<0.001), irrespective of augmented or limited group assignment. Pain catastrophizing was significantly reduced after the intervention (t(16)=3.79; p=0.002) in the Augmented (∆-7.88) but not the Limited group (∆1.44). Importantly, only the Augmented group reported a high probability to continue with the treatment after the study as well as a high pain relief expectation for future acupuncture treatments even though both groups experienced similar pain relief treatment outcomes over the course of the study intervention. Brain imaging data analysis focused on social mirroring areas such as the temporo-parietal junction (TPJ). In summary, this study highlights the importance of investigating variable interaction quality during longitudinal clinical therapies and its influence on clinical outcomes, treatment compliance, and brain processing of nociceptive signaling. Grant support from NIH - National Center for Complementary and Integrative Health (NCCIH: R61-AT009306, R33-AT009306), Neuroimaging Pilot Funding Initiative at the Martinos Center for Biomedical imaging (MGH R90DA023427), Korea Institute of Oriental Medicine (KIOM), Foundation for the Science of the Therapeutic Encounter, National Center for Research Resources (P41RR14075; CRC 1 UL1 RR025758), Harvard Clinical and Translational Science Center, Martinos Computing facilities, and National Institutes of Health (Grant Nos. S10RR023401, S10RR019307, S10RR019254, and S10RR023043). The funders had no role in study design, data collection and/or interpretation of the results. Also, all authors declare no existence of competing conflicts of interest.

Structure guided engineering of selective HVEM mutants reveal distinct functions binding to LIGHT and BTLA/CD160

Abstract HVEM is a TNF (tumor necrosis factor) receptor contributing to a broad range of immune functions involving diverse cell types. It interacts with a TNF ligand, LIGHT, and immunoglobulin (Ig) superfamily members BTLA and CD160. Assessing the functional impact of HVEM binding to specific ligands in different settings has been complicated by the multiple interactions of HVEM and HVEM binding partners. To dissect the molecular basis for multiple functions, we determined crystal structures that reveal the distinct HVEM surfaces that engage LIGHT or BTLA/CD160, including the human HVEM–LIGHT–CD160 ternary complex, with HVEM interacting simultaneously with both binding partners. Based on these structures, we generated mouse HVEM mutants that selectively recognized either the TNF or Ig ligands in vitro. Knockin mice expressing these muteins maintain expression of all the proteins in the HVEM network, yet they demonstrate selective functions for LIGHT in the clearance of bacteria in the intestine and for the Ig ligands in the amelioration of liver inflammation. Supported grants from NIH (S10 OD020068, P30CA023100, P30 DK120515, S10RR027366, U01 AI125955, P01 DK46763), U.S. Department of Energy (DE-AC02-98CH10886, DE-AC02-06CH11357), National Center for Research Resources (P41RR012408), National Institute of General Medical Sciences (P41GM103473), Albert Einstein Cancer Center (P30CA013330), Eli Lilly Company, Albert Einstein Macromolecular Therapeutics Development Facility, Price Family Foundation, Albert Einstein Center for Experimental Therapeutics, Pamela and Edward S. Pantzer, and Academia Sinica, Taiwan.  

Differential Response of Dendritic Cells and Macrophages to Signals from Airway Epithelial Cells in Humans: Changes with Age

Abstract Advancing age significantly enhances the risk of respiratory diseases such as COPD, fibrosis etc. Immune response to respiratory viral infections is also impaired often leading to hospitalization. The underlying mechanisms are not well understood. Airway epithelial cells (AECs) and dendritic cells (DCs) and alveolar macrophages are the primary cells involved in respiratory immunity and tolerance. Since DCs and macrophages exist in close proximity to AECs, the function of both these cells is influenced by AECs. Using a 2D model to study the interaction of human primary bronchial epithelial cells (representative of AECs) with DCs we have recently demonstrated that AECs enhance the immune surveillance capacity of myeloid DCs (mDCs) from the circulation at homeostasis. Culture of mDCs with AECs resulted in the upregulation of pathogen recognition receptors (PRRs) and downstream signaling molecules. In contrast to circulatory mDCs, culture of macrophages with AECs led to a significant inhibition of LPS induced pro-inflammatory responses. More importantly, AECs induced the secretion of TGF-β and IL-10 from macrophages even in the absence of LPS stimulation. Thus, it seems AECs induce tolerance in macrophages but enhance the immunogenicity of mDCs suggesting a division of labor between DCs and macrophages in the respiratory mucosa. Investigation into the possible mechanisms for this differential response indicates that metabolites and growth factors from AECs may be responsible for inducing tolerance in macrophages and priming DCs. We also find that the crosstalk between AECs and macrophages and DCs is altered with age which may contribute to the increased susceptibility of elderly to respiratory diseases and infections. This study was supported by grant from the NIH AG045216 (to AA), and from the National Center for Research Resources and the National Center for Advancing Translational Sciences # UL1 TR000153.

Acne risk in transgender and gender diverse populations: A retrospective, comparative cohort study

To the Editor: Acne is a common dermatologic condition that may be particularly problematic for transgender and gender diverse (TGD) individuals.1Motosko C. Zakhem G. Pomeranz M. Hazen A. Acne: a side-effect of masculinizing hormonal therapy in transgender patients.Br J Dermatol. 2019; 180: 26-30Crossref PubMed Scopus (24) Google Scholar Both masculinizing gender-affirming hormone therapy (mGAHT [ie, testosterone]) and feminizing gender-affirming hormone therapy (fGAHT [ie, estrogen or antiandrogens]) have been linked to the worsening and improvement of acne, respectively, but existing studies have been limited by the size and lack of comparison groups.1Motosko C. Zakhem G. Pomeranz M. Hazen A. Acne: a side-effect of masculinizing hormonal therapy in transgender patients.Br J Dermatol. 2019; 180: 26-30Crossref PubMed Scopus (24) Google Scholar, 2Giltay E. Gooren L. Effects of sex steroid deprivation/administration on hair growth and skin sebum production in transsexual males and females.J Clin Endocrinol Metab. 2000; 85: 2913-2921Crossref PubMed Scopus (140) Google Scholar, 3Wierckx K. Van de Peer F. Verhaeghe E. et al.Short- and long-term clinical skin effects of testosterone treatment in trans men.J Sex Med. 2014; 11: 222-229https://doi.org/10.1111/jsm.12366Abstract Full Text Full Text PDF PubMed Scopus (82) Google Scholar, 4Thoreson N. Park J.A. Grasso C. et al.Incidence and factors associated with acne among transgender patients receiving masculinizing hormone therapy.JAMA Dermatol. 2021; 157: 290-295Crossref PubMed Scopus (9) Google Scholar In this study of 46,507 patients, we examined the overall prevalence and risk ratios of acne in TGD patients receiving mGAHT (TGD-mGAHT) or fGAHT (TGD-fGAHT) compared with those in cisgender men, cisgender women, and TGD patients not receiving gender-affirming hormone therapy who were assigned female or male at birth.We conducted a retrospective cohort study using electronic health records of all TGD and cisgender adults who had at least 1 medical visit at Fenway Health, a community health center in Boston, between August 2014 and August 2020. This study was determined to be exempted from review by the institutional review board of Fenway Institute of Health. We excluded patients without recorded gender identity, birth sex, or body mass index data; cisgender women prescribed testosterone; and cisgender men prescribed birth control or menopause medications. Acne was defined based on International Statistical Classification of Diseases, Ninth and Tenth Revisions, Clinical Modification codes for acne (706.1 and L70.x, respectively). The use of gender-affirming hormone therapy was elicited based on prescription data. We collected data on demographics and other clinical factors that affect acne (Table I). Prevalence was defined as the total number of acne cases, both new and pre-existing, identified based on the diagnostic codes at the time of analysis. Unadjusted risk ratios and adjusted risk ratios (aRRs) with 95% CIs for association with acne were calculated using log-binomial regression. Multivariate models included age, body mass index, diabetes, hyperlipidemia, hypertension, corticosteroid use, lithium or amoxapine use, and smoking status.Table IBaseline demographics and clinical characteristicsCharacteristicOverallTGD-fGAHTTGD-mGAHTCisgender menCisgender womenTGD-nGAHT, AFABTGD-nGAHT, AMABPatients, N46,5071394157625,59416,961535447Acne diagnosis, n (%)3517(7.6%)73(5.2%)415(26.3%)1345(5.3%)1621(9.6%)45(8.4%)18(4.0%)Age Median (IQR), y27(22-39)25(21-32)23(20-28)30(24-44)25(21-32)25(20-27)30(21-35) Range, y18-9518-7118-6618-9518-9318-7018-74BMI Median (IQR)25.3(22.6-29.0)25.3(22.0-30.1)26.6(22.9-32.3)25.9(23.4-29.1)24.2(21.6-28.4)28.8(22.8-33.2)26.4(21.8-29.3) Range(2.0,81.8)(2.1,68.1)(2.5,73.7)(2.0,67.6)(2.0,81.8)(5.3,57.0)(16.6,74.6) 18.5-24.9, n (%)20,762(44.6%)622(44.6%)608(38.6%)10,133(39.6%)8994(53.0%)182(34.0%)223(49.9%) <18.5, n (%)1038(2.2%)46(3.3%)36(2.3%)329(1.3%)600(3.5%)16(3.0%)11(47.7%) ≥25.0, n (%)24,707(51.1%)726(52.1%)932(59.1%)15,132(59.1%)7367(43.4%)337(63.0%)213(2.5%)Race, n (%) Caucasian/White30,972(66.6%)1014(72.7%)1295(76.5%)17,479(68.3%)10,557(62.2%)398(74.4%)319(71.4%) Asian4741(10.2%)64(4.6%)59(3.7%)2226(8.7%)2349(13.9%)22(4.1%)21(4.7%) Black3127(6.7%)64(4.6%)88(5.6%)1669(6.5%)1258(7.4%)23(4.3%)25(5.6%) Multiracial2296(4.9%)110(7.9%)126(8.0%)1187(4.6%)780(4.6%)61(11.4%)32(7.2%) Other1370(3.0%)40(2.9%)28(1.8%)709(2.8%)562(3.3%)17(3.2%)14(3.1%) Unknown or missing4001(8.6%)102(7.3%)70(4.4%)2324(9.1%)1455(8.6%)14(2.6%)36(8.1%)Smoking status, n (%) Current4491(9.7%)165(11.8%)182(11.6%)2945(11.5%)1101(6.5%)47(8.8%)51(11.4%) Past7448(16.0%)293(21.0%)303(19.2%)4746(18.5%)1935(11.4%)91(17.0%)80(17.9%) Never28,143(60.5%)854(61.3%)998(63.3%)14,597(57.0%)11,079(65.3%)337(63.0%)278(62.2%) Unknown or missing6425(13.8%)82(5.9%)93(5.9%)3306(12.9%)2846(16.8%)60(11.2%)38(8.5%)Comorbidities, n (%) Diabetes1660(3.6%)60(4.3%)41(2.6%)1115(4.4%)413(2.4%)12(2.2%)19(4.3%) Hyperlipidemia6978(15.0%)171(12.3%)224(14.2%)5088(19.9%)1414(8.3%)30(5.6%)51(11.4%) Hypertension6053(13.0%)113(8.1%)112(7.1%)4388(17.1%)1370(8.1%)27(5.1%)43(9.6%)Other medication use Oral corticosteroids7776(16.7%)207(13.1%)156(11.2%)4997(19.5%)2311(13.6%)51(9.5%)54(12.1%) Lithium or amoxapine529(1.1%)29(2.1%)46(2.9%)271(1.1%)154(0.9%)17(3.2%)12(2.7%)AFAB, Assigned female at birth; AMAB, assigned male at birth; BMI, body mass index; IQR, interquartile range; TGD-fGAHT, transgender/gender diverse patients receiving feminizing gender-affirming hormone therapy; TGD-mGAHT, transgender/gender diverse patients receiving masculinizing gender-affirming hormone therapy; TGD-nGAHT, transgender/gender diverse patients not undergoing gender-affirming hormone therapy. Open table in a new tab Both unadjusted and adjusted analyses revealed that TGD-mGAHT patients were significantly more likely to have acne than cisgender women (aRR = 2.41; 95% CI, 2.18-2.67), cisgender men (aRR = 4.09; 95% CI, 3.67-4.56), and TGD patients not receiving gender-affirming hormone therapy. TGD-fGAHT patients were not significantly less likely to have acne than cisgender men (aRR = 0.85; 95% CI, 0.66-1.09) but were significantly less likely to have acne than cisgender women (aRR = 0.51; 95% CI, 0.40-0.65) and TGD patients not receiving gender-affirming hormone therapy who were assigned female at birth (aRR = 0.56; 95% CI, 0.39-0.81) (Table II). Sensitivity analyses restricting the cisgender comparison groups to only those not receiving hormonal treatments—ie, testosterone, birth control, or menopause therapy—did not significantly affect these findings.Table IIUnadjusted, multivariate, and sensitivity analyses for acne∗aRR was adjusted for age by quartile, body mass index category, race, diabetes or hyperlipidemia, hypertension, corticosteroid or lithium or amoxapine use, and smoking status.Comparison groupCisgender womenCisgender menCisgender women†Only included cisgender women not receiving hormonal birth control or menopausal hormone therapy.Cisgender men‡Only included cisgender men not receiving testosterone therapy.TGD not receiving GAHT who were assigned female at birthTGD not receiving GAHT who were assigned male at birthExposed groupTGD receiving masculinizing GAHTRR95% CIRR95% CIRR95% CIRR95% CIRR95% CIRR95% CI2.76(2.51-3.03)5.01(4.54-5.52)3.59(3.23-4.00)5.03(4.56-5.55)3.13(2.34-4.19)6.54(4.13-10.36)aRR95% CIaRR§For the comparison between TGD patients receiving masculinizing GAHT versus cisgender men, we did not control for corticosteroid, lithium, or amoxapine use because convergence was unable to be achieved when this variable was included.95% CIaRR95% CIaRR§For the comparison between TGD patients receiving masculinizing GAHT versus cisgender men, we did not control for corticosteroid, lithium, or amoxapine use because convergence was unable to be achieved when this variable was included.95% CIaRR95% CIaRR95% CI2.41(2.18-2.67)4.09(3.67-4.56)2.89(2.57-3.25)4.11(3.69-4.56)2.70(2.02-3.62)6.64(3.94-11.20)TGD receiving feminizing GAHTRR95% CIRR95% CIRR95% CIRR95% CIRR95% CIRR95% CI0.55(0.44-0.69)1.00(0.79-1.25)0.71(0.57-0.90)1.00(0.80-1.26)0.62(0.44-0.89)1.30(0.79-2.12)aRR95% CIaRR95% CIaRR95% CIaRR95% CIaRR95% CIaRR95% CI0.51(0.40-0.65)0.85(0.66-1.09)0.62(0.48-0.80)0.86(0.67-1.11)0.56(0.39-0.81)1.32(0.75-2.32)aRR, Adjusted relative risk; GAHT, gender-affirming hormone therapy; RR, relative risk; TGD, transgender/gender diverse.∗ aRR was adjusted for age by quartile, body mass index category, race, diabetes or hyperlipidemia, hypertension, corticosteroid or lithium or amoxapine use, and smoking status.† Only included cisgender women not receiving hormonal birth control or menopausal hormone therapy.‡ Only included cisgender men not receiving testosterone therapy.§ For the comparison between TGD patients receiving masculinizing GAHT versus cisgender men, we did not control for corticosteroid, lithium, or amoxapine use because convergence was unable to be achieved when this variable was included. Open table in a new tab Prior studies examining acne among TGD patients have been limited in size and scope. Our large-cohort study expands upon existing literature, corroborates the association of mGAHT with increased acne, and helps establish the decreased risk of acne in TGD-fGAHT patients.1Motosko C. Zakhem G. Pomeranz M. Hazen A. Acne: a side-effect of masculinizing hormonal therapy in transgender patients.Br J Dermatol. 2019; 180: 26-30Crossref PubMed Scopus (24) Google Scholar,2Giltay E. Gooren L. Effects of sex steroid deprivation/administration on hair growth and skin sebum production in transsexual males and females.J Clin Endocrinol Metab. 2000; 85: 2913-2921Crossref PubMed Scopus (140) Google Scholar,4Thoreson N. Park J.A. Grasso C. et al.Incidence and factors associated with acne among transgender patients receiving masculinizing hormone therapy.JAMA Dermatol. 2021; 157: 290-295Crossref PubMed Scopus (9) Google Scholar Our study’s limitations include the inability to determine causation and the direction of association, lack of generalizability, and undercounting of cases, which were identified based only on the diagnostic codes and only included adults.Acne can be detrimental to well-being, especially for gender minority individuals who already experience discrimination. TGD patients starting mGAHT should be counseled about potentially increased acne risk and treatment options; however, fGAHT may decrease acne risk. To the Editor: Acne is a common dermatologic condition that may be particularly problematic for transgender and gender diverse (TGD) individuals.1Motosko C. Zakhem G. Pomeranz M. Hazen A. Acne: a side-effect of masculinizing hormonal therapy in transgender patients.Br J Dermatol. 2019; 180: 26-30Crossref PubMed Scopus (24) Google Scholar Both masculinizing gender-affirming hormone therapy (mGAHT [ie, testosterone]) and feminizing gender-affirming hormone therapy (fGAHT [ie, estrogen or antiandrogens]) have been linked to the worsening and improvement of acne, respectively, but existing studies have been limited by the size and lack of comparison groups.1Motosko C. Zakhem G. Pomeranz M. Hazen A. Acne: a side-effect of masculinizing hormonal therapy in transgender patients.Br J Dermatol. 2019; 180: 26-30Crossref PubMed Scopus (24) Google Scholar, 2Giltay E. Gooren L. Effects of sex steroid deprivation/administration on hair growth and skin sebum production in transsexual males and females.J Clin Endocrinol Metab. 2000; 85: 2913-2921Crossref PubMed Scopus (140) Google Scholar, 3Wierckx K. Van de Peer F. Verhaeghe E. et al.Short- and long-term clinical skin effects of testosterone treatment in trans men.J Sex Med. 2014; 11: 222-229https://doi.org/10.1111/jsm.12366Abstract Full Text Full Text PDF PubMed Scopus (82) Google Scholar, 4Thoreson N. Park J.A. Grasso C. et al.Incidence and factors associated with acne among transgender patients receiving masculinizing hormone therapy.JAMA Dermatol. 2021; 157: 290-295Crossref PubMed Scopus (9) Google Scholar In this study of 46,507 patients, we examined the overall prevalence and risk ratios of acne in TGD patients receiving mGAHT (TGD-mGAHT) or fGAHT (TGD-fGAHT) compared with those in cisgender men, cisgender women, and TGD patients not receiving gender-affirming hormone therapy who were assigned female or male at birth. We conducted a retrospective cohort study using electronic health records of all TGD and cisgender adults who had at least 1 medical visit at Fenway Health, a community health center in Boston, between August 2014 and August 2020. This study was determined to be exempted from review by the institutional review board of Fenway Institute of Health. We excluded patients without recorded gender identity, birth sex, or body mass index data; cisgender women prescribed testosterone; and cisgender men prescribed birth control or menopause medications. Acne was defined based on International Statistical Classification of Diseases, Ninth and Tenth Revisions, Clinical Modification codes for acne (706.1 and L70.x, respectively). The use of gender-affirming hormone therapy was elicited based on prescription data. We collected data on demographics and other clinical factors that affect acne (Table I). Prevalence was defined as the total number of acne cases, both new and pre-existing, identified based on the diagnostic codes at the time of analysis. Unadjusted risk ratios and adjusted risk ratios (aRRs) with 95% CIs for association with acne were calculated using log-binomial regression. Multivariate models included age, body mass index, diabetes, hyperlipidemia, hypertension, corticosteroid use, lithium or amoxapine use, and smoking status. AFAB, Assigned female at birth; AMAB, assigned male at birth; BMI, body mass index; IQR, interquartile range; TGD-fGAHT, transgender/gender diverse patients receiving feminizing gender-affirming hormone therapy; TGD-mGAHT, transgender/gender diverse patients receiving masculinizing gender-affirming hormone therapy; TGD-nGAHT, transgender/gender diverse patients not undergoing gender-affirming hormone therapy. Both unadjusted and adjusted analyses revealed that TGD-mGAHT patients were significantly more likely to have acne than cisgender women (aRR = 2.41; 95% CI, 2.18-2.67), cisgender men (aRR = 4.09; 95% CI, 3.67-4.56), and TGD patients not receiving gender-affirming hormone therapy. TGD-fGAHT patients were not significantly less likely to have acne than cisgender men (aRR = 0.85; 95% CI, 0.66-1.09) but were significantly less likely to have acne than cisgender women (aRR = 0.51; 95% CI, 0.40-0.65) and TGD patients not receiving gender-affirming hormone therapy who were assigned female at birth (aRR = 0.56; 95% CI, 0.39-0.81) (Table II). Sensitivity analyses restricting the cisgender comparison groups to only those not receiving hormonal treatments—ie, testosterone, birth control, or menopause therapy—did not significantly affect these findings. aRR, Adjusted relative risk; GAHT, gender-affirming hormone therapy; RR, relative risk; TGD, transgender/gender diverse. Prior studies examining acne among TGD patients have been limited in size and scope. Our large-cohort study expands upon existing literature, corroborates the association of mGAHT with increased acne, and helps establish the decreased risk of acne in TGD-fGAHT patients.1Motosko C. Zakhem G. Pomeranz M. Hazen A. Acne: a side-effect of masculinizing hormonal therapy in transgender patients.Br J Dermatol. 2019; 180: 26-30Crossref PubMed Scopus (24) Google Scholar,2Giltay E. Gooren L. Effects of sex steroid deprivation/administration on hair growth and skin sebum production in transsexual males and females.J Clin Endocrinol Metab. 2000; 85: 2913-2921Crossref PubMed Scopus (140) Google Scholar,4Thoreson N. Park J.A. Grasso C. et al.Incidence and factors associated with acne among transgender patients receiving masculinizing hormone therapy.JAMA Dermatol. 2021; 157: 290-295Crossref PubMed Scopus (9) Google Scholar Our study’s limitations include the inability to determine causation and the direction of association, lack of generalizability, and undercounting of cases, which were identified based only on the diagnostic codes and only included adults. Acne can be detrimental to well-being, especially for gender minority individuals who already experience discrimination. TGD patients starting mGAHT should be counseled about potentially increased acne risk and treatment options; however, fGAHT may decrease acne risk. Dr Dommasch reported serving as co-chair of the American Academy of Dermatology Expert Resource Group on Lesbian, Gay, Bisexual, Transgender, Queer/Sexual and Gender Minority Health. Dr Modest and Authors Gao and King have no conflicts of interest to declare. This work was conducted with support from Harvard Catalyst | The Harvard Clinical and Translational Science Center (National Center for Research Resources and the National Center for Advancing Translational Sciences, National Institutes of Health Award UL1 TR002541) and financial contributions from Harvard University and its affiliated academic health care centers. The content is solely the responsibility of the authors and does not necessarily represent the official views of Harvard Catalyst, Harvard University, and its affiliated academic health care centers or the National Institutes of Health.

Pathogenic and transcriptomic differences of emerging SARS-CoV-2 variants in the Syrian golden hamster model.

BackgroundFollowing the discovery of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its rapid spread throughout the world, new viral variants of concern (VOC) have emerged. There is a critical need to understand the impact of the emerging variants on host response and disease dynamics to facilitate the development of vaccines and therapeutics.MethodsSyrian golden hamsters are the leading small animal model that recapitulates key aspects of severe coronavirus disease 2019 (COVID-19). We performed intranasal inoculation of SARS-CoV-2 into hamsters with the ancestral virus (nCoV-WA1-2020) or VOC first identified in the United Kingdom (B.1.1.7, alpha) and South Africa (B.1.351, beta) and analyzed viral loads and host responses.FindingsSimilar gross and histopathologic pulmonary lesions were observed after infection with all three variants. Although differences in viral genomic copy numbers were noted in the lungs and oral swabs of challenged animals, infectious titers in the lungs were comparable between the variants. Antibody neutralization capacities varied, dependent on the original challenge virus and cross-variant protective capacity. Transcriptional profiling of lung samples 4 days post-challenge (DPC) indicated significant induction of antiviral pathways in response to all three challenges with a more robust inflammatory signature in response to B.1.1.7 infection. Furthermore, no additional mutations in the spike protein were detected at 4 DPC.InterpretationsAlthough disease severity and viral shedding were not significantly different, the emerging VOC induced distinct humoral responses and transcriptional profiles compared to the ancestral virus. These observations suggest potential differences in acute early responses or alterations in immune modulation by VOC.FundingIntramural Research Program, NIAID, NIH; National Center for Research Resources, NIH; National Center for Advancing Translational Sciences, NIH.

An End-to-End Integrated Clinical and CT Based Radiomics Nomogram for Predicting Disease Severity and Need for Ventilator Support in COVID-19 Patients: A Large Multi-Site Retrospective Study

Objective: The disease COVID-19 has caused a widespread global pandemic with ~3.93 million deaths worldwide. In this work, we present three models- Radiomics (MRM), Clinical (MCM), and combined Clinical-Radiomics (MRCM) nomogram to predict COVID-19 positive patients who will end up needing invasive mechanical ventilation from the baseline CT scans.  Method: We performed a retrospective multicohort study of individuals with COVID-19 positive findings for a total of 980 patients from 2 different institutions (Renmin hospital of Wuhan University, D1 =787 and University Hospitals, US D2 = 110). The patients from institution-1 were divided into 60% training, D1 T (N=473), and 40% test set D1 V (N=314). The patients from institution-2 were used for an independent validation test set D2 V(N=110). A U-Net-based neural network (CNN) was trained to automatically segment out the COVID consolidation regions on the CT scans. The segmented regions from the CT scans were used for extracting first-order and higher-order Radiomic textural features. The top Radiomic and clinical features were selected using the Least Absolute Shrinkage and Selection Operator (LASSO) with an optimal binomial regression model within D1 T. Results: The 3 out of the top 5 features identified using D1 T were higher-order textural features (GLCM, GLRLM, GLSZM), whereas the last two features included the total infection size on the CT scan and the total intensity of the COVID consolidations. The Radiomics Model (MRM ) was constructed using the Radiomic Score built using the coefficients obtained from the LASSO logistic model used within the linear regression (LR) classifier. The MRM yielded an area under the receiver operating characteristic curve (AUC) of 0.754 [0.709-0.799] on D1 T, 0.836 on D1 V, and 0.748 D2 V. The top prognostic clinical factors identified in the analysis were dehydrogenase (LDH), age, and albumin (ALB). The clinical model had an AUC of 0.784 [0.743-0.825] on D1 T, 0.813 on D1 V, and 0.723 on D2 V. Finally, the combined model, MRCM integrating Radiomic Score, age, LDH and ALB, yielded an AUC of 0.814 [0.774-0.853] on D1 T, 0.847 on D1 V, and 0.772 on D2 V. The MRCM had an overall improvement in the performance of ~3.77% (D1 T: p = 0.0003; D1 V p= 0.0165; D2 V : p = 0.024) over MCM Conclusion: The novel integrated imaging and clinical model (MRCM) outperformed both models (MRM) and (MCM). Our results across multiple sites suggest that the integrated nomogram could help identify COVID-19 patients with more severe disease phenotype and potentially requiring mechanical ventilation. Funding: National Cancer Institute of the US National Institutes of Health, National Center for Research Resources, US Department of Veterans Affairs Biomedical Laboratory Research and Development Service, Department of Defense, National Institute of Diabetes and Digestive and Kidney Diseases, Wallace H Coulter Foundation, Case Western Reserve University, and Dana Foundation. Declaration of Interest: AM reports grants from National Cancer Institute of the National Institutes of Health, grants from National Center for Research Resources, grants from VA Merit Review Award, grants from DOD Cancer Investigator-Initiated Translational Research Award, during the conduct of the study; grants from DOD Prostate Cancer Idea Development Award, grants from DOD Peer Reviewed Cancer Research Program, grants from National Institute of Diabetes and Digestive and Kidney Diseases , grants from the Ohio Third Frontier Technology Validation Fund, grants from the Wallace H. Coulter Foundation Program in the Department of Biomedical Engineering and the Clinical and Translational Science Award Program (CTSA) at Case Western Reserve University, grants from Department of Defense Peer Reviewed Cancer Research Program (PRCRP) Career Development Award, grants from Dana Foundation David Mahoney Neuroimaging Program. Ethical Approval: The study conformed to HIPAA guidelines was approved by University Hospitals, Cleveland (STUDY20200463), and the Ethics committee of the Renmin Hospital of Wuhan University (ethics number: V1.0).

A prognostic and predictive computational pathology image signature for added benefit of adjuvant chemotherapy in early stage non-small-cell lung cancer.

We developed and validated a prognostic and predictive computational pathology risk score (CoRiS) using H&E stained tissue images from patients with early-stage non-small cell lung cancer (ES-NSCLC). 1330 patients with ES-NSCLC were acquired from 3 independent sources and divided into four cohorts D1-4. D1 comprised 100 surgery treated patients and was used to identify prognostic features via an elastic-net Cox model to predict overall and disease-free survival. CoRiS was constructed using the Cox model coefficients for the top features. The prognostic performance of CoRiS was evaluated on D2 (N=331), D3 (N=657) and D4 (N=242). Patients from D2 and D3 which comprised surgery+chemotherapy were used to validate CoRiS as predictive of added benefit to adjuvant chemotherapy (ACT) by comparing survival between different CoRiS defined risk groups. CoRiS was found to be prognostic on univariable analysis, D2 (hazard ratio (HR)=1.41, adjusted (adj.) P=.01) and D3 (HR=1.35, adj. P < .001). Multivariable analysis showed CoRiS was independently prognostic, D2 (HR=1.41, adj. P < .001) and D3 (HR=1.35, adj. P < .001), after adjusting for clinico-pathologic factors. CoRiS was also able to identify high-risk patients who derived survival benefit from ACT D2 (HR=0.42, adj. P=.006) and D3 (HR=0.46, adj. P=.08). CoRiS is a tissue non-destructive, quantitative and low-cost tool that could potentially help guide management of ES-NSCLC patients. Data collection, anlaysis, and computation resources of the research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under award numbers: 1U24CA199374-01, R01CA202752-01A1, R01CA208236-01A1, R01 CA216579-01A1, R01 CA220581-01A1, 1U01 CA239055-01. National Center for Research Resources under award number 1 C06 RR12463-01. VA Merit Review Award IBX004121A from the United States Department of Veterans Affairs Biomedical Laboratory Research and Development Service, the DOD Prostate Cancer Idea Development Award (W81XWH-15-1-0558), the DOD Lung Cancer Investigator-Initiated Translational Research Award (W81XWH-18-1-0440), the DOD Peer Reviewed Cancer Research Program (W81XWH-16-1-0329), the Ohio Third Frontier Technology Validation Fund, the Wallace H. Coulter Foundation Program in the Department of Biomedical Engineering and the Clinical and Translational Science Award Program (CTSA) at Case Western Reserve University.

67-OR: Oral Minimal Model Testing Reveals Early Impairment of Insulin Sensitivity in Type 1 Diabetes Autoantibody Positive, Nonobese, Nondysglycemic Youth

Background: Clinical onset of type 1 diabetes (Stage 3 T1D) is preceded by a pre-symptomatic phase characterized by multiple islet autoimmunity with normal glucose tolerance (Stage 1 T1D), followed by dysglycemia (Stage 2). The metabolic phenotypes of beta-cell function and insulin sensitivity were explored in normoglycemic youth with stage 1 T1D and compared to healthy non-related peers during a 3-h oral glucose tolerance test (OGTT). Methods: Participants were recruited from TrialNet (cases) and Yale University (controls). Twenty-eight lean youth with at least two islet autoantibody (cases) and 32 healthy controls underwent a 3-hour 9-point OGTT with measurement of glucose, C-peptide and insulin. The oral minimal model was used to quantitate beta-cell responsivity (Phitotal) and insulin sensitivity (SI), allowing assessment of beta-cell function by the disposition index, DI=Phitotal x SI. Subjects with impaired fasting glucose, impaired glucose tolerance or any OGTT glucose concentration >200mg/dL were excluded. Results: Cases (10.5y[8, 15]) exhibited reduced DI (p Conclusion: Pre-symptomatic stage 1 T1D is associated with both reduced insulin sensitivity and lower beta cell responsiveness in youth. Disclosure A. Galderisi: None. A. Moran: Advisory Panel; Self; Dompe, Novo Nordisk, Research Support; Self; Abbott Diabetes, Intrexon, Provention Bio, Inc. C. Evans-molina: Advisory Panel; Self; Provention Bio, Inc., Consultant; Self; Dompe, Other Relationship; Self; Bristol-Myers Squibb Company, Nimbus Pharmaceuticals, Pfizer Inc. M. Martino: None. N. Santoro: None. S. Caprio: None. C. Cobelli: None. Funding Eunice Kennedy Shriver National Institute of Child Health and Human Development (R01HD40787, R01DK111038, R01HD28016, R01DK114504); National Center for Research Resources (UL1RR0249139); National Institute of Diabetes and Digestive and Kidney Diseases (R01DK111038); Diabetes Research Center (P30DK045735, R01DK114504-01A, K12AWDA10768, GR103182); National Institutes of Health (U01DK085476, UL1TR002494, U01DK085505); Fondazione Cassa di Risparmio di Padova e Rovigo (2018); European Commission (EU951933)

DASH Diet Concordance Among Adults in the Mediators of Atherosclerosis in South Asians Living in America (MASALA) Study (2010–2013)

Abstract Objectives South Asian Americans have a disproportionately higher risk of atherosclerotic cardiovascular disease (ASCVD) and risk factors, such as hypertension compared to non-Hispanic whites and other Asian American groups. Our objective was to investigate adherence to Dietary Approaches to Stop Hypertension (DASH), an established dietary pattern to reduce blood pressure, and association with sociodemographic, body composition, and ASCVD risk factors. Methods Baseline data from 893 adults (40–83y, 47% female) recruited between 2010–2013 for the MASALA Study were used in these analyses. We computed a DASH concordance score from the validated 163-item Study of Health Assessment and Risk in Ethnic groups food frequency questionnaire (FFQ), using an established method. We scored concordance based on 8 components: high intake of 1) fruit, 2) vegetables, 3) nuts/legumes, 4) low-fat dairy products, and 5) whole grains, and low intake of 6) sodium, 7) sugar-sweetened beverages, and 8) red/processed meats. The theoretical DASH score may range from 8 (low concordance) to 40 (high concordance). Results The DASH score in MASALA participants ranged 12–35 (mean ± SD, 24.4 ± 4.4). The average score was higher among women (25.4 ± 4.1) than men (23.6 ± 4.5; P &amp;lt; 0.001), higher among adults 65 and older than those ≤50 (24.9 ± 4.3 vs. 23.9 ± 4.6, P = 0.015), and higher among participants who had lived less than 50% of their life in the U.S. (24.9 ± 4.4 vs. 23.9 ± 4.4, p-0.0014). The score was also higher among participants who had a Bachelor's degree or greater (P = 0.0064), but there was no difference in the score based on annual family income (P = 0.07). The score was higher among vegetarians than non-vegetarians (26.7 ± 3.5 vs. 23 ± 4.4; P &amp;lt; 0.001). It was also inversely associated with indicators of central adiposity including waist circumference (P = 0.001) and waist-to-hip ratio (P &amp;lt; 0.001). Conclusions Our results indicate that adherence to the DASH dietary pattern is associated with select sociodemographic factors and body composition among South Asians in the U.S. The computed DASH score will be utilized in forthcoming analyses to determine its associations with risk factors for hypertension, central adiposity, and ASCVD among participants in the MASALA cohort. Funding Sources NHLBI, National Center for Research Resources, National Center for Advancing Translational Sciences, NIH, via UCSF-CTSI.

79-LB: Pharmacokinetics and Pharmacodynamics of Avexitide (Exendin 9-39) in Neonates and Infants with Congenital Hyperinsulinism

Congenital hyperinsulinism (HI) is an ultra-rare pediatric disease with high unmet medical need. Avexitide, a first-in-class GLP-1 receptor antagonist, has been shown to reduce hyperinsulinemic hypoglycemia in children and adolescents with HI. Among neonates, maintenance of euglycemia often depends on high glucose infusion rates (GIR) by central lines. Those whose GIR exceeds 10 mg/kg/min frequently require subtotal pancreatectomy, leading to prolonged hospitalization, life-threatening complications, and induction of insulin-dependent diabetes. In this Phase 2 trial, 13 neonates and infants ages 11 days to 5 months with diazoxide-unresponsive HI were randomized to single ascending doses of avexitide and placebo by continuous IV infusion for up to 12 hours on two days in crossover design. Plasma glucose was monitored with GIR adjusted to maintain euglycemia. The primary endpoint was GIR. Relationships between avexitide exposure and absolute difference in GIR during avexitide vs. placebo were evaluated. A pharmacokinetic (PK) simulation of avexitide following subcutaneous (SC) injection in neonates was performed based on a modified PopPK model previously established with inclusion of weight-based allometric scaling. Relative to placebo, avexitide significantly reduced GIR when evaluated across dose levels (p=0.0087) with dose-dependent improvements observed. On average, avexitide infused at 100, 200 and 1000 pmol/kg/min demonstrated 1.3 (15%), 2.9 (24%), and 4.3 (56%) mg/kg/min reductions in GIR relative to placebo and entirely abolished glucose requirements in 50% of patients at the top dose. PK/PD analysis demonstrated an exposure-response relationship best described by an Emax model. PK simulation indicated that avexitide dosed by SC injection may achieve adequate steady-state exposure to lower GIR requirements. Subcutaneous avexitide may represent a promising therapeutic approach for treatment of neonates and infants with HI. Disclosure C. Craig: Consultant; Self; Eiger BioPharmaceuticals. D. D. De leon: Advisory Panel; Self; Zealand Pharma A/S, Consultant; Self; Hanmi Pharmaceutical, Heptares Therapeutics, Poxel SA, Soleno Therapeutics, Inc., Employee; Spouse/Partner; Merck &amp; Co., Inc., Research Support; Self; Crinetics Pharmaceuticals, Tiburio, Zealand Pharma A/S. Funding National Institute of Diabetes and Digestive and Kidney Diseases (1R56DK083670); Clifford and Katherine Goldsmith Foundation; National Center for Research Resources (UL1RR024134); Eiger BioPharmaceuticals

Reduced Plasma Short-Chain Fatty Acid (SCFA) Concentrations Are Not Associated With Markers of Muscle Health in Non-Small Cell Lung Cancer

Abstract Objectives Cancer patients were shown to have an altered intestinal microbiota composition and lower fecal concentrations of the bacterial metabolites short-chain fatty acids (SCFA), which among others serve as energy source to muscle. We previously described an association between reduced plasma SCFA concentrations and muscle dysfunction in chronic wasting diseases and now examined whether this relationship exists in non-small cell lung cancer (NSCLC) patients. Methods We recruited 13 male patients with advanced NSCLC (stage 3–4) without anticancer therapy or surgery in the previous 4 weeks (age: 65.8 [62.2, 69.5] yo, BMI: 27.7 [25.2, 30.2] kg/m2), and 11 healthy male, age-matched controls (age: 68.5 [64.0, 73.0] yo, BMI: 26.5 [24.0, 28.9] kg/m2). Venous plasma was collected in the postabsorptive state to determine SCFA concentrations (in μM) by GC-MS. Nutritional depletion was assessed by unintended weight loss &amp;gt;5% in the past 3 months, muscle mass by DXA, handgrip strength and endurance by dynamometry, and maximal expiratory and inspriratory pressure using a hand-held mouth pressure device. Statistics are by ANCOVA and Pearson's correlation adjusting for age and BMI. Data are mean [95% CI]. Results Acetate (−54.1 [−105.0, −3.1] μmol/L, P = 0.039), propionate (−0.72 [−1.29, −0.16] μmol/L, P = 0.015), and butyrate (−0.52 [−0.92, −0.12] μmol/L, P = 0.014) concentrations were reduced in NSCLC compared to controls. While a higher propionate concentration correlated with a higher life expectancy (P = 0.037), SCFA concentrations were not associated with disease severity (stage 3 vs. 4), presence of nutritional depletion, or cancer type (adenocarcinoma vs. squamous cell carcinoma) (all P &amp;gt; 0.05). We observed no differences in muscle mass, strength or endurance between cancer and healthy participants and SCFA concentrations did not correlate with muscle function and endurance in NSCLC patients (all P &amp;gt; 0.05). Conclusions Our data suggest that the reduced SCFA play a role in overall outcome but not in muscle health in NSCLC patients. Funding Sources AICR, NIH, National Center for Research Resources, Sydney and J.L. Huffines Institute for Sports Medicine and Human Performance.