The recent rapid expansion of multidrug resistant Ural lineage Mycobacterium tuberculosis in Moldova

The projected trajectory of multidrug resistant tuberculosis (MDR-TB) epidemics depends on the reproductive fitness of circulating strains of MDR M. tuberculosis (Mtb). Previous efforts to characterize the fitness of MDR Mtb have found that Mtb strains of the Beijing sublineage (Lineage 2.2.1) may be more prone to develop resistance and retain fitness in the presence of resistance-conferring mutations than other lineages. Using Mtb genome sequences from all culture-positive cases collected over two years in Moldova, we estimate the fitness of Ural (Lineage 4.2) and Beijing strains, the two lineages in which MDR is concentrated in the country. We estimate that the fitness of MDR Ural strains substantially exceeds that of other susceptible and MDR strains, and we identify several mutations specific to these MDR Ural strains. Our findings suggest that MDR Ural Mtb has been transmitting efficiently in Moldova and poses a substantial risk of spreading further in the region.

Dopamine and serotonin in human substantia nigra track social context and value signals during economic exchange

Dopamine and serotonin are hypothesized to guide social behaviours. In humans, however, we have not yet been able to study neuromodulator dynamics as social interaction unfolds. Here, we obtained subsecond estimates of dopamine and serotonin from human substantia nigra pars reticulata during the ultimatum game. Participants, who were patients with Parkinson's disease undergoing awake brain surgery, had to accept or reject monetary offers of varying fairness from human and computer players. They rejected more offers in the human than the computer condition, an effect of social context associated with higher overall levels of dopamine but not serotonin. Regardless of the social context, relative changes in dopamine tracked trial-by-trial changes in offer value-akin to reward prediction errors-whereas serotonin tracked the current offer value. These results show that dopamine and serotonin fluctuations in one of the basal ganglia's main output structures reflect distinct social context and value signals.

Dynamic associations between glucose and ecological momentary cognition in Type 1 Diabetes

Type 1 diabetes (T1D) is a chronic condition characterized by glucose fluctuations. Laboratory studies suggest that cognition is reduced when glucose is very low (hypoglycemia) and very high (hyperglycemia). Until recently, technological limitations prevented researchers from understanding how naturally-occurring glucose fluctuations impact cognitive fluctuations. This study leveraged advances in continuous glucose monitoring (CGM) and cognitive ecological momentary assessment (EMA) to characterize dynamic, within-person associations between glucose and cognition in naturalistic environments. Using CGM and EMA, we obtained intensive longitudinal measurements of glucose and cognition (processing speed, sustained attention) in 200 adults with T1D. First, we used hierarchical Bayesian modeling to estimate dynamic, within-person associations between glucose and cognition. Consistent with laboratory studies, we hypothesized that cognitive performance would be reduced at low and high glucose, reflecting cognitive vulnerability to glucose fluctuations. Second, we used data-driven lasso regression to identify clinical characteristics that predicted individual differences in cognitive vulnerability to glucose fluctuations. Large glucose fluctuations were associated with slower and less accurate processing speed, although slight glucose elevations (relative to person-level means) were associated with faster processing speed. Glucose fluctuations were not related to sustained attention. Seven clinical characteristics predicted individual differences in cognitive vulnerability to glucose fluctuations: age, time in hypoglycemia, lifetime severe hypoglycemic events, microvascular complications, glucose variability, fatigue, and neck circumference. Results establish the impact of glucose on processing speed in naturalistic environments, suggest that minimizing glucose fluctuations is important for optimizing processing speed, and identify several clinical characteristics that may exacerbate cognitive vulnerability to glucose fluctuations.

Effect of mobile food environments on fast food visits

Poor diets are a leading cause of morbidity and mortality. Exposure to low-quality food environments saturated with fast food outlets is hypothesized to negatively impact diet. However, food environment research has predominantly focused on static food environments around home neighborhoods and generated mixed findings. In this work, we leverage population-scale mobility data in the U.S. to examine 62M people's visits to food outlets and evaluate how food choice is influenced by the food environments people are exposed to as they move through their daily routines. We find that a 10% increase in exposure to fast food outlets in mobile environments increases individuals' odds of visitation by 20%. Using our results, we simulate multiple policy strategies for intervening on food environments to reduce fast-food outlet visits. This analysis suggests that optimal interventions are informed by spatial, temporal, and behavioral features and could have 2x to 4x larger effect than traditional interventions focused on home food environments.

Depression and cognition are associated with lipid dysregulation in both a multigenerational study of depression and the National Health and Nutrition Examination Survey

Chronic dysregulation of peripheral lipids has been found to be associated with depression and cognition, but their interaction has not been investigated. Growing evidence has highlighted the association between peripheral lipoprotein levels with depression and cognition with inconsistent results. We assessed the association between peripheral lipids, depression, and cognition while evaluating their potential interactions using robust clinically relevant predictors such as lipoprotein levels and chronic medical disorders that dysregulate lipoproteins. We report an association between peripheral lipids, depression, and cognition, suggesting a common underlying biological mechanism driven by lipid dysregulation in two independent studies. Analysis of a longitudinal study of a cohort at high or low familial risk for major depressive disorder (MDD) (n = 526) found metabolic diseases, including diabetes, hypertension, and other cardiovascular diseases, were associated with MDD and cognitive outcomes. Investigating a cross-sectional population survey of adults in the National Health and Nutrition Examination Survey 2011-2014 (NHANES) (n = 2377), depression was found to be associated with high density lipoprotein (HDL) and cognitive assessments. In the familial risk study, medical conditions were found to be associated with chronic lipid dysregulation and were significantly associated with MDD using the structural equation model. A positive association between chronic lipid dysregulation and cognitive scores was found in an exploratory analysis of the familial risk study. In a complementary study, analysis of NHANES revealed a positive association of HDL levels with cognition. Further analysis of the NHANES cohort indicated that depression status mediated the interaction between HDL levels and cognitive tests. Importantly, the protective effect of HDL on cognition was absent in those with depressive symptoms, which may ultimately result in worse outcomes leading to cognitive decline. These findings highlight the potential for the early predictive value of medical conditions with chronic lipid dyshomeostasis for the risk of depression and cognitive decline.

Genome-matched treatments and patient outcomes in the Maine Cancer Genomics Initiative (MCGI)

Genomic tumor testing (GTT) is an emerging technology aimed at identifying variants in tumors that can be targeted with genomically matched drugs. Due to limited resources, rural patients receiving care in community oncology settings may be less likely to benefit from GTT. We analyzed GTT results and observational clinical outcomes data from patients enrolled in the Maine Cancer Genomics Initiative (MCGI), which provided access to GTTs; clinician educational resources; and genomic tumor boards in community practices in a predominantly rural state. 1603 adult cancer patients completed enrollment; 1258 had at least one potentially actionable variant identified. 206 (16.4%) patients received a total of 240 genome matched treatments, of those treatments, 64% were FDA-approved in the tumor type, 27% FDA-approved in a different tumor type and 9% were given on a clinical trial. Using Inverse Probability of Treatment Weighting to adjust for baseline characteristics, a Cox proportional hazards model demonstrated that patients who received genome matched treatment were 31% less likely to die within 1 year compared to those who did not receive genome matched treatment (HR: 0.69; 95% CI: 0.52-0.90; p-value: 0.006). Overall, GTT through this initiative resulted in levels of genome matched treatment that were similar to other initiatives, however, clinical trials represented a smaller share of treatments than previously reported, and "off-label" treatments represented a greater share. Although this was an observational study, we found evidence for a potential 1-year survival benefit for patients who received genome matched treatments. These findings suggest that when disseminated and implemented with a supportive infrastructure, GTT may benefit cancer patients in rural community oncology settings, with further work remaining on providing genome-matched clinical trials.

Trans-lesion synthesis and mismatch repair pathway crosstalk defines chemoresistance and hypermutation mechanisms in glioblastoma

Almost all Glioblastoma (GBM) are either intrinsically resistant to the chemotherapeutical drug temozolomide (TMZ) or acquire therapy-induced mutations that cause chemoresistance and recurrence. The genome maintenance mechanisms responsible for GBM chemoresistance and hypermutation are unknown. We show that the E3 ubiquitin ligase RAD18 (a proximal regulator of TLS) is activated in a Mismatch repair (MMR)-dependent manner in TMZ-treated GBM cells, promoting post-replicative gap-filling and survival. An unbiased CRISPR screen provides an aerial map of RAD18-interacting DNA damage response (DDR) pathways deployed by GBM to tolerate TMZ genotoxicity. Analysis of mutation signatures from TMZ-treated GBM reveals a role for RAD18 in error-free bypass of O6mG (the most toxic TMZ-induced lesion), and error-prone bypass of other TMZ-induced lesions. Our analyses of recurrent GBM patient samples establishes a correlation between low RAD18 expression and hypermutation. Taken together we define molecular underpinnings for the hallmark tumorigenic phenotypes of TMZ-treated GBM.

Low-calorie diets for people with isolated impaired fasting glucose

Thirunavukkarasu et al. discuss how standard lifestyle interventions prove ineffective in preventing type 2 diabetes in individuals with isolated impaired fasting glucose, a highly prevalent prediabetes phenotype globally. They propose low-calorie diets as a promising strategy for diabetes prevention in this high-risk population.

Multimodal imaging risk factors predictive of small choroidal melanocytic lesion growth to melanoma: An educational study and pictorial guide

BACKGROUND

Risk factors for small choroidal melanocytic lesion growth to melanoma have been redefined using multimodal imaging. We explored provider ability to recognize risk factors for small choroidal melanocytic lesion growth to melanoma before and after image-based education and with and without multimodal imaging.

METHODS

Providers were invited to participate in a survey assessing ability to identify risk factors for small choroidal melanocytic lesion growth to melanoma using either fundus imaging or multimodal imaging. Risk factors included thickness >2 mm on ultrasonography, subretinal fluid on optical coherence tomography, presence of orange pigment by autofluorescence, acoustic hollowness by ultrasonography, and diameter >5 mm by fundus imaging. Performance was assessed before and after reviewing an educational PowerPoint providing pictorial examples of risk factors. Comparison between groups was conducted using two-tailed Fisher's exact test.

RESULTS

Thirty and 26 providers completed the pre-education and post-education assessments, respectively. Post-education participants were more accurate within ±1 risk factor for lesions with zero risk factors (77% vs. 100%, p = 0.01) or two risk factors (79% vs. 91%, p = 0.03). Following education, participants presented with multimodal imaging more often correctly identified lesions with four (12% vs. 42%, p = 0.03) or five (4% vs. 39%, p = 0.004) risk factors, demonstrated lower mean level of concern for lesions with zero risk factors (2.0 vs. 1.4, p < 0.001), and expressed higher level of concern for lesions with 5 risk factors (2.4 vs. 3.6, p < 0.001).

CONCLUSION

Use of multimodal imaging may be more beneficial than education itself to improve accuracy of risk factor identification for small choroidal melanocytic lesions.

Rapid genomic sequencing for genetic disease diagnosis and therapy in intensive care units: a review

Single locus (Mendelian) diseases are a leading cause of childhood hospitalization, intensive care unit (ICU) admission, mortality, and healthcare cost. Rapid genome sequencing (RGS), ultra-rapid genome sequencing (URGS), and rapid exome sequencing (RES) are diagnostic tests for genetic diseases for ICU patients. In 44 studies of children in ICUs with diseases of unknown etiology, 37% received a genetic diagnosis, 26% had consequent changes in management, and net healthcare costs were reduced by $14,265 per child tested by URGS, RGS, or RES. URGS outperformed RGS and RES with faster time to diagnosis, and higher rate of diagnosis and clinical utility. Diagnostic and clinical outcomes will improve as methods evolve, costs decrease, and testing is implemented within precision medicine delivery systems attuned to ICU needs. URGS, RGS, and RES are currently performed in <5% of the ~200,000 children likely to benefit annually due to lack of payor coverage, inadequate reimbursement, hospital policies, hospitalist unfamiliarity, under-recognition of possible genetic diseases, and current formatting as tests rather than as a rapid precision medicine delivery system. The gap between actual and optimal outcomes in children in ICUs is currently increasing since expanded use of URGS, RGS, and RES lags growth in those likely to benefit through new therapies. There is sufficient evidence to conclude that URGS, RGS, or RES should be considered in all children with diseases of uncertain etiology at ICU admission. Minimally, diagnostic URGS, RGS, or RES should be ordered early during admissions of critically ill infants and children with suspected genetic diseases.

Cortical signatures of sleep are altered following effective deep brain stimulation for depression

Deep brain stimulation (DBS) of the subcallosal cingulate cortex (SCC) is an experimental therapy for treatment-resistant depression (TRD). Chronic SCC DBS leads to long-term changes in the electrophysiological dynamics measured from local field potential (LFP) during wakefulness, but it is unclear how it impacts sleep-related brain activity. This is a crucial gap in knowledge, given the link between depression and sleep disturbances, and an emerging interest in the interaction between DBS, sleep, and circadian rhythms. We therefore sought to characterize changes in electrophysiological markers of sleep associated with DBS treatment for depression. We analyzed key electrophysiological signatures of sleep-slow-wave activity (SWA, 0.5-4.5 Hz) and sleep spindles-in LFPs recorded from the SCC of 9 patients who responded to DBS for TRD. This allowed us to compare the electrophysiological changes before and after 24 weeks of therapeutically effective SCC DBS. SWA power was highly correlated between hemispheres, consistent with a global sleep state. Furthermore, SWA occurred earlier in the night after chronic DBS and had a more prominent peak. While we found no evidence for changes to slow-wave power or stability, we found an increase in the density of sleep spindles. Our results represent a first-of-its-kind report on long-term electrophysiological markers of sleep recorded from the SCC in patients with TRD, and provides evidence of earlier NREM sleep and increased sleep spindle activity following clinically effective DBS treatment. Future work is needed to establish the causal relationship between long-term DBS and the neural mechanisms underlying sleep.

Multivalent cytomegalovirus glycoprotein B nucleoside modified mRNA vaccines did not demonstrate a greater antibody breadth

Human cytomegalovirus (HCMV) remains the most common congenital infection and infectious complication in immunocompromised patients. The most successful HCMV vaccine to date, an HCMV glycoprotein B (gB) subunit vaccine adjuvanted with MF59, achieved 50% efficacy against primary HCMV infection. A previous study demonstrated that gB/MF59 vaccinees were less frequently infected with HCMV gB genotype strains most similar to the vaccine strain than strains encoding genetically distinct gB genotypes, suggesting strain-specific immunity accounted for the limited efficacy. To determine whether vaccination with multiple HCMV gB genotypes could increase the breadth of anti-HCMV gB humoral and cellular responses, we immunized 18 female rabbits with monovalent (gB-1), bivalent (gB-1+gB-3), or pentavalent (gB-1+gB-2+gB-3+gB-4+gB-5) gB lipid nanoparticle-encapsulated nucleoside-modified RNA (mRNA-LNP) vaccines. The multivalent vaccine groups did not demonstrate a higher magnitude or breadth of the IgG response to the gB ectodomain or cell-associated gB compared to that of the monovalent vaccine. Also, the multivalent vaccines did not show an increase in the breadth of neutralization activity and antibody-dependent cellular phagocytosis against HCMV strains encoding distinct gB genotypes. Interestingly, peripheral blood mononuclear cell-derived gB-2-specific T-cell responses elicited by multivalent vaccines were of a higher magnitude compared to that of monovalent vaccinated animals against a vaccine-mismatched gB genotype at peak immunogenicity. Yet, no statistical differences were observed in T cell response against gB-3 and gB-5 variable regions among the three vaccine groups. Our data suggests that the inclusion of multivalent gB antigens is not an effective strategy to increase the breadth of anti-HCMV gB antibody and T cell responses. Understanding how to increase the HCMV vaccine protection breadth will be essential to improve the vaccine efficacy.

Contribution of climate change to the spatial expansion of West Nile virus in Europe

West Nile virus (WNV) is an emerging mosquito-borne pathogen in Europe where it represents a new public health threat. While climate change has been cited as a potential driver of its spatial expansion on the continent, a formal evaluation of this causal relationship is lacking. Here, we investigate the extent to which WNV spatial expansion in Europe can be attributed to climate change while accounting for other direct human influences such as land-use and human population changes. To this end, we trained ecological niche models to predict the risk of local WNV circulation leading to human cases to then unravel the isolated effect of climate change by comparing factual simulations to a counterfactual based on the same environmental changes but a counterfactual climate where long-term trends have been removed. Our findings demonstrate a notable increase in the area ecologically suitable for WNV circulation during the period 1901-2019, whereas this area remains largely unchanged in a no-climate-change counterfactual. We show that the drastic increase in the human population at risk of exposure is partly due to historical changes in population density, but that climate change has also been a critical driver behind the heightened risk of WNV circulation in Europe.

Improving polygenic risk prediction in admixed populations by explicitly modeling ancestral-differential effects via GAUDI

Polygenic risk scores (PRS) have shown successes in clinics, but most PRS methods focus only on participants with distinct primary continental ancestry without accommodating recently-admixed individuals with mosaic continental ancestry backgrounds for different segments of their genomes. Here, we develop GAUDI, a novel penalized-regression-based method specifically designed for admixed individuals. GAUDI explicitly models ancestry-differential effects while borrowing information across segments with shared ancestry in admixed genomes. We demonstrate marked advantages of GAUDI over other methods through comprehensive simulation and real data analyses for traits with associated variants exhibiting ancestral-differential effects. Leveraging data from the Women's Health Initiative study, we show that GAUDI improves PRS prediction of white blood cell count and C-reactive protein in African Americans by > 64% compared to alternative methods, and even outperforms PRS-CSx with large European GWAS for some scenarios. We believe GAUDI will be a valuable tool to mitigate disparities in PRS performance in admixed individuals.

Examining the association between posttraumatic stress disorder and disruptions in cortical networks identified using data-driven methods

Posttraumatic stress disorder (PTSD) is associated with lower cortical thickness (CT) in prefrontal, cingulate, and insular cortices in diverse trauma-affected samples. However, some studies have failed to detect differences between PTSD patients and healthy controls or reported that PTSD is associated with greater CT. Using data-driven dimensionality reduction, we sought to conduct a well-powered study to identify vulnerable networks without regard to neuroanatomic boundaries. Moreover, this approach enabled us to avoid the excessive burden of multiple comparison correction that plagues vertex-wise methods. We derived structural covariance networks (SCNs) by applying non-negative matrix factorization (NMF) to CT data from 961 PTSD patients and 1124 trauma-exposed controls without PTSD. We used regression analyses to investigate associations between CT within SCNs and PTSD diagnosis (with and without accounting for the potential confounding effect of trauma type) and symptom severity in the full sample. We performed additional regression analyses in subsets of the data to examine associations between SCNs and comorbid depression, childhood trauma severity, and alcohol abuse. NMF identified 20 unbiased SCNs, which aligned closely with functionally defined brain networks. PTSD diagnosis was most strongly associated with diminished CT in SCNs that encompassed the bilateral superior frontal cortex, motor cortex, insular cortex, orbitofrontal cortex, medial occipital cortex, anterior cingulate cortex, and posterior cingulate cortex. CT in these networks was significantly negatively correlated with PTSD symptom severity. Collectively, these findings suggest that PTSD diagnosis is associated with widespread reductions in CT, particularly within prefrontal regulatory regions and broader emotion and sensory processing cortical regions.

Interplay between ATRX and IDH1 mutations governs innate immune responses in diffuse gliomas

Stimulating the innate immune system has been explored as a therapeutic option for the treatment of gliomas. Inactivating mutations in ATRX, defining molecular alterations in IDH-mutant astrocytomas, have been implicated in dysfunctional immune signaling. However, little is known about the interplay between ATRX loss and IDH mutation on innate immunity. To explore this, we generated ATRX-deficient glioma models in the presence and absence of the IDH1R132H mutation. ATRX-deficient glioma cells are sensitive to dsRNA-based innate immune agonism and exhibit impaired lethality and increased T-cell infiltration in vivo. However, the presence of IDH1R132H dampens baseline expression of key innate immune genes and cytokines in a manner restored by genetic and pharmacological IDH1R132H inhibition. IDH1R132H co-expression does not interfere with the ATRX deficiency-mediated sensitivity to dsRNA. Thus, ATRX loss primes cells for recognition of dsRNA, while IDH1R132H reversibly masks this priming. This work reveals innate immunity as a therapeutic vulnerability of astrocytomas.

Revisiting the Plasmodium sporozoite inoculum and elucidating the efficiency with which malaria parasites progress through the mosquito

Malaria is initiated when infected anopheline mosquitoes inoculate sporozoites as they probe for blood. It is thought that all infected mosquitoes are equivalent in terms of their infectious potential, with parasite burden having no role in transmission success. In this study, using mosquitoes harboring the entire range of salivary gland sporozoite loads observed in the field, we demonstrate a strong and highly significant correlation between mosquito parasite burden and inoculum size. We then link the inoculum data to oocyst counts, the most commonly-used metric to assess mosquito infection in the field, and determine the efficiency with which oocyst sporozoites enter mosquito salivary glands. Taken together our data support the conclusion that mosquitoes with higher parasite burdens are more likely to initiate infection and contribute to onward transmission. Overall these data may account for some of the unexplained heterogeneity in transmission and enable more precise benchmarks for transmission-blocking interventions.

Digital and precision clinical trials: innovations for testing mental health medications, devices, and psychosocial treatments

Mental health treatment advances - including neuropsychiatric medications and devices, psychotherapies, and cognitive treatments - lag behind other fields of clinical medicine such as cardiovascular care. One reason for this gap is the traditional techniques used in mental health clinical trials, which slow the pace of progress, produce inequities in care, and undermine precision medicine goals. Newer techniques and methodologies, which we term digital and precision trials, offer solutions. These techniques consist of (1) decentralized (i.e., fully-remote) trials which improve the speed and quality of clinical trials and increase equity of access to research, (2) precision measurement which improves success rate and is essential for precision medicine, and (3) digital interventions, which offer increased reach of, and equity of access to, evidence-based treatments. These techniques and their rationales are described in detail, along with challenges and solutions for their utilization. We conclude with a vignette of a depression clinical trial using these techniques.

Temporal dynamics of neurobehavioral hormone sensitivity in a scaled-down experimental model of early pregnancy and parturition

The hormonal changes of pregnancy and parturition can trigger robust changes in affective state, particularly among patients with a history of postpartum depression. However, more work is needed to elucidate the temporal dynamics of symptom emergence. The current study explored how quickly hormone-sensitive (HS+) individuals can be differentiated from hormone-insensitive (HS-) controls in the context of a tightly controlled experimental hormone manipulation, and which symptoms demonstrate the most rapid, consistent, and largest response during this protocol. Participants were female, non-pregnant, and euthymic, with a history of DSM-5 major depressive episode with peripartum onset (n = 15) or parous healthy controls with no psychiatric history (n = 15). Perinatal hormonal changes were simulated by inducing hypogonadism, adding back estradiol (E2) and progesterone (P4) to reach first-trimester levels for 8 weeks, and then subsequently withdrawing both hormones. Those reporting a 30% or greater increase during addback or withdrawal on select subscales of the Inventory of Depression and Anxiety Symptoms (IDAS) were identified as HS+. Participants provided daily ratings of symptoms throughout the study via the Daily Record of Severity of Problems. Results indicated that HS+ participants could be differentiated from HS- participants early in the hormone protocol, with many symptoms showing significantly greater change from baseline within the first week of addback. Notably, the most rapid symptom increases were observed for Anger/Irritability, Mood Swings, Overwhelm, Lethargy, Increased Appetite, Joint and Muscle Pain, and Breast Tenderness, reaching 50% of peak group contrast within the first week of hormone addback. The largest group effects were observed for Anger/Irritability, followed by Fatigue and Anxiety, and the most consistent group effects were observed for Anger/Irritability, Interpersonal Conflict, Overwhelm, and Hopelessness. Findings support the role of reproductive hormones in the onset of perinatal affective disorders. The rapid emergence of anger and irritability in HS+ participants suggests that these symptoms may be early indicators of perinatal hormone sensitivity.

Prediction of atrial fibrillation from at-home single-lead ECG signals without arrhythmias

Early identification of atrial fibrillation (AF) can reduce the risk of stroke, heart failure, and other serious cardiovascular outcomes. However, paroxysmal AF may not be detected even after a two-week continuous monitoring period. We developed a model to quantify the risk of near-term AF in a two-week period, based on AF-free ECG intervals of up to 24 h from 459,889 patch-based ambulatory single-lead ECG (modified lead II) recordings of up to 14 days. A deep learning model was used to integrate ECG morphology data with demographic and heart rhythm features toward AF prediction. Observing a 1-day AF-free ECG recording, the model with deep learning features produced the most accurate prediction of near-term AF with an area under the curve AUC = 0.80 (95% confidence interval, CI = 0.79-0.81), significantly improving discrimination compared to demographic metrics alone (AUC 0.67; CI = 0.66-0.68). Our model was able to predict incident AF over a two-week time frame with high discrimination, based on AF-free single-lead ECG recordings of various lengths. Application of the model may enable a digital strategy for improving diagnostic capture of AF by risk stratifying individuals with AF-negative ambulatory monitoring for prolonged or recurrent monitoring, potentially leading to more rapid initiation of treatment.

Post-diagnosis weight trajectories and mortality among women with breast cancer

Weight gain after breast cancer diagnosis is associated with adverse health outcomes. Yet, few studies have characterized post-diagnosis weight change in the modern treatment era or populations most at risk for weight changes. Among women diagnosed with stages I-III breast cancer in the Smilow Care Network (2013-2019; N = 5441), we abstracted demographic and clinical characteristics from electronic health records and survival data from tumor registries. We assessed if baseline characteristics modified weight trajectories with nonlinear multilevel mixed-effect models. We evaluated body mass index (BMI) at diagnosis and weight change 1-year post-diagnosis in relation to all-cause and breast cancer-specific mortality with Cox proportional hazard models. Women had 34.4 ± 25.5 weight measurements over 3.2 ± 1.8 years of follow-up. Weight gain was associated with ER/PR-, HER2+ tumors, BMI ≤ 18.5 kg/m2, and age ≤ 45 years (+4.90 kg (standard error [SE] = 0.59), +3.24 kg (SE = 0.34), and +1.75 kg (SE = 0.10), respectively). Weight loss was associated with BMI ≥ 35 kg/m2 and age ≥ 70 years (-4.50 kg (SE = 0.08) and -4.34 kg (SE = 0.08), respectively). Large weight loss (≥10%), moderate weight loss (5-10%), and moderate weight gain (5-10%) 1-year after diagnosis were associated with higher all-cause mortality (hazard ratio [HR] = 2.93, 95% confidence interval [CI] = 2.28-3.75, HR = 1.32, 95% CI = 1.02-1.70 and HR = 1.39, 95% CI = 1.04-1.85, respectively). BMI ≥ 35 kg/m2 or BMI ≤ 18.5 kg/m2 at diagnosis were also associated with higher all-cause mortality. Weight change after a breast cancer diagnosis differed by demographic and clinical characteristics highlighting subgroups at-risk for weight change during a 5-year period post-diagnosis. Monitoring and interventions for weight management early in clinical care are important.

Adopting and expanding ethical principles for generative artificial intelligence from military to healthcare

In 2020, the U.S. Department of Defense officially disclosed a set of ethical principles to guide the use of Artificial Intelligence (AI) technologies on future battlefields. Despite stark differences, there are core similarities between the military and medical service. Warriors on battlefields often face life-altering circumstances that require quick decision-making. Medical providers experience similar challenges in a rapidly changing healthcare environment, such as in the emergency department or during surgery treating a life-threatening condition. Generative AI, an emerging technology designed to efficiently generate valuable information, holds great promise. As computing power becomes more accessible and the abundance of health data, such as electronic health records, electrocardiograms, and medical images, increases, it is inevitable that healthcare will be revolutionized by this technology. Recently, generative AI has garnered a lot of attention in the medical research community, leading to debates about its application in the healthcare sector, mainly due to concerns about transparency and related issues. Meanwhile, questions around the potential exacerbation of health disparities due to modeling biases have raised notable ethical concerns regarding the use of this technology in healthcare. However, the ethical principles for generative AI in healthcare have been understudied. As a result, there are no clear solutions to address ethical concerns, and decision-makers often neglect to consider the significance of ethical principles before implementing generative AI in clinical practice. In an attempt to address these issues, we explore ethical principles from the military perspective and propose the "GREAT PLEA" ethical principles, namely Governability, Reliability, Equity, Accountability, Traceability, Privacy, Lawfulness, Empathy, and Eutonomy, for generative AI in healthcare. Furthermore, we introduce a framework for adopting and expanding these ethical principles in a practical way that has been useful in the military and can be applied to healthcare for generative AI, based on contrasting their ethical concerns and risks. Ultimately, we aim to proactively address the ethical dilemmas and challenges posed by the integration of generative AI into healthcare practice.

Regenerating human skeletal muscle forms an emerging niche in vivo to support PAX7 cells

Skeletal muscle stem and progenitor cells including those derived from human pluripotent stem cells (hPSCs) offer an avenue towards personalized therapies and readily fuse to form human-mouse myofibres in vivo. However, skeletal muscle progenitor cells (SMPCs) inefficiently colonize chimeric stem cell niches and instead associate with human myofibres resembling foetal niches. We hypothesized competition with mouse satellite cells (SCs) prevented SMPC engraftment into the SC niche and thus generated an SC ablation mouse compatible with human engraftment. Single-nucleus RNA sequencing of SC-ablated mice identified the absence of a transient myofibre subtype during regeneration expressing Actc1. Similarly, ACTC1+ human myofibres supporting PAX7+ SMPCs increased in SC-ablated mice, and after re-injury we found SMPCs could now repopulate into chimeric niches. To demonstrate ACTC1+ myofibres are essential to supporting PAX7 SMPCs, we generated caspase-inducible ACTC1 depletion human pluripotent stem cells, and upon SMPC engraftment we found a 90% reduction in ACTC1+ myofibres and a 100-fold decrease in PAX7 cell numbers compared with non-induced controls. We used spatial RNA sequencing to identify key factors driving emerging human niche formation between ACTC1+ myofibres and PAX7+ SMPCs in vivo. This revealed that transient regenerating human myofibres are essential for emerging niche formation in vivo to support PAX7 SMPCs.

Cross species systems biology discovers glial DDR2, STOM, and KANK2 as therapeutic targets in progressive supranuclear palsy

Progressive supranuclear palsy (PSP) is a neurodegenerative parkinsonian disorder characterized by cell-type-specific tau lesions in neurons and glia. Prior work uncovered transcriptome changes in human PSP brains, although their cell-specificity is unknown. Further, systematic data integration and experimental validation platforms to prioritize brain transcriptional perturbations as therapeutic targets in PSP are currently lacking. In this study, we combine bulk tissue (n = 408) and single nucleus RNAseq (n = 34) data from PSP and control brains with transcriptome data from a mouse tauopathy and experimental validations in Drosophila tau models for systematic discovery of high-confidence expression changes in PSP with therapeutic potential. We discover, replicate, and annotate thousands of differentially expressed genes in PSP, many of which reside in glia-enriched co-expression modules and cells. We prioritize DDR2, STOM, and KANK2 as promising therapeutic targets in PSP with striking cross-species validations. We share our findings and data via our interactive application tool PSP RNAseq Atlas ( https://rtools.mayo.edu/PSP_RNAseq_Atlas/ ). Our findings reveal robust glial transcriptome changes in PSP, provide a cross-species systems biology approach, and a tool for therapeutic target discoveries in PSP with potential application in other neurodegenerative diseases.

Use of term reference infants in assessing the developmental outcome of extremely preterm infants: lessons learned in a multicenter study

OBJECTIVE

Extremely preterm (EP) impairment rates are likely underestimated using the Bayley III norm-based thresholds scores and may be better assessed relative to concurrent healthy term reference (TR) infants born in the same hospital.

STUDY DESIGN

Blinded, certified examiners in the Neonatal Research Network (NRN) evaluated EP survivors and a sample of healthy TR infants recruited near the 2-year assessment age.

RESULTS

We assessed 1452 EP infants and 183 TR infants. TR-based thresholds showed higher overall EP impairment than Bayley norm-based thresholds (O.R. = 1.86; [95% CI 1.56-2.23], especially for severe impairment (36% vs. 24%; p ≤ 0.001). Difficulty recruiting TR patients at 2 years extended the study by 14 months and affected their demographics.

CONCLUSION

Impairment rates among EP infants appear to be substantially underestimated from Bayley III norms. These rates may be best assessed by comparison with healthy term infants followed with minimal attrition from birth in the same centers.

CLINICALTRIALS

GOV ID

Term Reference (under the Generic Database Study): NCT00063063.

Novel scoring tool of hypoxemic respiratory failure and pulmonary hypertension for defining severity of persistent pulmonary hypertension of newborn

OBJECTIVE

To obtain preliminary validity data for a hypoxemic respiratory failure/pulmonary hypertension (HRF/PH) score for classifying persistent pulmonary hypertension of the newborn (PPHN).

STUDY DESIGN

Retrospective chart review of 100 consecutive neonates admitted to a Children's hospital from 2016-2021 with PPHN, gestational age ≥34 weeks, and echocardiograms in the first week. We assessed the correlation between HRF/PH score and short-term outcomes using linear and logistic regressions.

RESULTS

HRF/PH scores ranged 2-12 (mean 8.5), and were classified mild (0-5), moderate (6-10), and severe (11-15), with 6%, 77% and 17% infants in respective categories. HRF/PH score category correlated with invasive ventilation, nitric oxide, high frequency ventilation, vasoactive infusions, extracorporeal life support and death. HRF/PH score category did not correlate with duration of support or length of stay.

CONCLUSION

The HRF/PH score offers a promising representation of disease severity for PPHN. The tool requires further validation in prospective studies and evaluation for long-term outcomes.

Exploiting the fibroblast growth factor receptor-1 vulnerability to therapeutically restrict the MYC-EZH2-CDKN1C axis-driven proliferation in Mantle cell lymphoma

Mantle cell lymphoma (MCL) is a lethal hematological malignancy with a median survival of 4 years. Its lethality is mainly attributed to a limited understanding of clinical tumor progression and resistance to current therapeutic regimes. Intrinsic, prolonged drug treatment and tumor-microenvironment (TME) facilitated factors impart pro-tumorigenic and drug-insensitivity properties to MCL cells. Hence, elucidating neoteric pharmacotherapeutic molecular targets involved in MCL progression utilizing a global "unified" analysis for improved disease prevention is an earnest need. Using integrated transcriptomic analyses in MCL patients, we identified a Fibroblast Growth Factor Receptor-1 (FGFR1), and analyses of MCL patient samples showed that high FGFR1 expression was associated with shorter overall survival in MCL patient cohorts. Functional studies using pharmacological intervention and loss of function identify a novel MYC-EZH2-CDKN1C axis-driven proliferation in MCL. Further, pharmacological targeting with erdafitinib, a selective small molecule targeting FGFRs, induced cell-cycle arrest and cell death in-vitro, inhibited tumor progression, and improved overall survival in-vivo. We performed extensive pre-clinical assessments in multiple in-vivo model systems to confirm the therapeutic potential of erdafitinib in MCL and demonstrated FGFR1 as a viable therapeutic target in MCL.

A virus-like particle-based bivalent PCSK9 vaccine lowers LDL-cholesterol levels in non-human primates

Elevated low-density lipoprotein cholesterol (LDL-C) is an important risk factor in the development of atherosclerotic cardiovascular disease (ASCVD). Inhibitors of proprotein convertase subtilisin/kexin type 9 (PCSK9), a negative regulator of LDL-C metabolism, have emerged as promising approaches for reducing elevated LDL-C levels. Here, we evaluated the cholesterol-lowering efficacy of virus-like particle (VLP) based vaccines that target epitopes found within the LDL receptor (LDL-R) binding domain of PCSK9. In both mice and non-human primates, a bivalent VLP vaccine targeting two distinct epitopes on PCSK9 elicited strong and durable antibody responses and lowered cholesterol levels. In macaques, a VLP vaccine targeting a single PCSK9 epitope was only effective at lowering LDL-C levels in combination with statins, whereas immunization with the bivalent vaccine lowered LDL-C without requiring statin co-administration. These data highlight the efficacy of an alternative, vaccine-based approach for lowering LDL-C.

Behavioral and neurocognitive factors distinguishing post-traumatic stress comorbidity in substance use disorders

Significant trauma histories and post-traumatic stress disorder (PTSD) are common in persons with substance use disorders (SUD) and often associate with increased SUD severity and poorer response to SUD treatment. As such, this sub-population has been associated with unique risk factors and treatment needs. Understanding the distinct etiological profile of persons with co-occurring SUD and PTSD is therefore crucial for advancing our knowledge of underlying mechanisms and the development of precision treatments. To this end, we employed supervised machine learning algorithms to interrogate the responses of 160 participants with SUD on the multidimensional NIDA Phenotyping Assessment Battery. Significant PTSD symptomatology was correctly predicted in 75% of participants (sensitivity: 80%; specificity: 72.22%) using a classification-based model based on anxiety and depressive symptoms, perseverative thinking styles, and interoceptive awareness. A regression-based machine learning model also utilized similar predictors, but failed to accurately predict severity of PTSD symptoms. These data indicate that even in a population already characterized by elevated negative affect (individuals with SUD), especially severe negative affect was predictive of PTSD symptomatology. In a follow-up analysis of a subset of 102 participants who also completed neurocognitive tasks, comorbidity status was correctly predicted in 86.67% of participants (sensitivity: 91.67%; specificity: 66.67%) based on depressive symptoms and fear-related attentional bias. However, a regression-based analysis did not identify fear-related attentional bias as a splitting factor, but instead split and categorized the sample based on indices of aggression, metacognition, distress tolerance, and interoceptive awareness. These data indicate that within a population of individuals with SUD, aberrations in tolerating and regulating aversive internal experiences may also characterize those with significant trauma histories, akin to findings in persons with anxiety without SUD. The results also highlight the need for further research on PTSD-SUD comorbidity that includes additional comparison groups (i.e., persons with only PTSD), captures additional comorbid diagnoses that may influence the PTSD-SUD relationship, examines additional types of SUDs (e.g., alcohol use disorder), and differentiates between subtypes of PTSD.

Human liver single nuclear RNA sequencing implicates BMPR2, GDF15, arginine, and estrogen in portopulmonary hypertension

Portopulmonary hypertension (PoPH) is a type of pulmonary vascular disease due to portal hypertension that exhibits high morbidity and mortality. The mechanisms driving disease are unknown, and transcriptional characteristics unique to the PoPH liver remain unexplored. Here, we apply single nuclear RNA sequencing to compare cirrhotic livers from patients with and without PoPH. We identify characteristics unique to PoPH in cells surrounding the central hepatic vein, including increased growth differentiation factor signaling, enrichment of the arginine biosynthesis pathway, and differential expression of the bone morphogenic protein type II receptor and estrogen receptor type I genes. These results provide insight into the transcriptomic characteristics of the PoPH liver and mechanisms by which PoPH cellular dysfunction might contribute to pulmonary vascular remodeling.

Ablative radiotherapy improves survival but does not cure autochthonous mouse models of prostate and colorectal cancer

BACKGROUND

Genetically engineered mouse models (GEMMs) of cancer are powerful tools to study mechanisms of disease progression and therapy response, yet little is known about how these models respond to multimodality therapy used in patients. Radiation therapy (RT) is frequently used to treat localized cancers with curative intent, delay progression of oligometastases, and palliate symptoms of metastatic disease.

METHODS

Here we report the development, testing, and validation of a platform to immobilize and target tumors in mice with stereotactic ablative RT (SART). Xenograft and autochthonous tumor models were treated with hypofractionated ablative doses of radiotherapy.

RESULTS

We demonstrate that hypofractionated regimens used in clinical practice can be effectively delivered in mouse models. SART alters tumor stroma and the immune environment, improves survival in GEMMs of primary prostate and colorectal cancer, and synergizes with androgen deprivation in prostate cancer. Complete pathologic responses were achieved in xenograft models, but not in GEMMs.

CONCLUSIONS

While SART is capable of fully ablating xenografts, it is unable to completely eradicate disease in GEMMs, arguing that resistance to potentially curative therapy can be modeled in GEMMs.

Impact of misclassified defective proviruses on HIV reservoir measurements

Most proviruses persisting in people living with HIV (PWH) on antiretroviral therapy (ART) are defective. However, rarer intact proviruses almost always reinitiate viral rebound if ART stops. Therefore, assessing therapies to prevent viral rebound hinges on specifically quantifying intact proviruses. We evaluated the same samples from 10 male PWH on ART using the two-probe intact proviral DNA assay (IPDA) and near full length (nfl) Q4PCR. Both assays admitted similar ratios of intact to total HIV DNA, but IPDA found ~40-fold more intact proviruses. Neither assay suggested defective proviruses decay over 10 years. However, the mean intact half-lives were different: 108 months for IPDA and 65 months for Q4PCR. To reconcile this difference, we modeled additional longitudinal IPDA data and showed that decelerating intact decay could arise from very long-lived intact proviruses and/or misclassified defective proviruses: slowly decaying defective proviruses that are intact in IPDA probe locations (estimated up to 5%, in agreement with sequence library based predictions). The model also demonstrates how misclassification can lead to underestimated efficacy of therapies that exclusively reduce intact proviruses. We conclude that sensitive multi-probe assays combined with specific nfl-verified assays would be optimal to document absolute and changing levels of intact HIV proviruses.

NICU sensory experiences associated with positive outcomes: an integrative review of evidence from 2015-2020

To inform changes to the Supporting and Enhancing NICU Sensory Experiences (SENSE) program, studies investigating sensory-based interventions in the NICU with preterm infants born ≤32 weeks were identified. Studies published between October 2015 to December 2020, and with outcomes related to infant development or parent well-being, were included in this integrative review. The systematic search used databases including MEDLINE, Cumulative Index to Nursing and Allied Health Literature, the Cochrane Library, and Google Scholar. Fifty-seven articles (15 tactile, 9 auditory, 5 visual, 1 gustatory/olfactory, 5 kinesthetic, and 22 multimodal) were identified. The majority of the sensory interventions that were identified within the articles were reported in a previous integrative review (1995-2015) and already included in the SENSE program. New evidence has led to refinements of the SENSE program, notably the addition of position changes across postmenstrual age (PMA) and visual tracking starting at 34 weeks PMA.

Sequential intrahost evolution and onward transmission of SARS-CoV-2 variants

Persistent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections have been reported in immune-compromised individuals and people undergoing immune-modulatory treatments. Although intrahost evolution has been documented, direct evidence of subsequent transmission and continued stepwise adaptation is lacking. Here we describe sequential persistent SARS-CoV-2 infections in three individuals that led to the emergence, forward transmission, and continued evolution of a new Omicron sublineage, BA.1.23, over an eight-month period. The initially transmitted BA.1.23 variant encoded seven additional amino acid substitutions within the spike protein (E96D, R346T, L455W, K458M, A484V, H681R, A688V), and displayed substantial resistance to neutralization by sera from boosted and/or Omicron BA.1-infected study participants. Subsequent continued BA.1.23 replication resulted in additional substitutions in the spike protein (S254F, N448S, F456L, M458K, F981L, S982L) as well as in five other virus proteins. Our findings demonstrate not only that the Omicron BA.1 lineage can diverge further from its already exceptionally mutated genome but also that patients with persistent infections can transmit these viral variants. Thus, there is, an urgent need to implement strategies to prevent prolonged SARS-CoV-2 replication and to limit the spread of newly emerging, neutralization-resistant variants in vulnerable patients.

Systems immunology-based drug repurposing framework to target inflammation in atherosclerosis

The development of new immunotherapies to treat the inflammatory mechanisms that sustain atherosclerotic cardiovascular disease (ASCVD) is urgently needed. Herein, we present a path to drug repurposing to identify immunotherapies for ASCVD. The integration of time-of-flight mass cytometry and RNA sequencing identified unique inflammatory signatures in peripheral blood mononuclear cells stimulated with ASCVD plasma. By comparing these inflammatory signatures to large-scale gene expression data from the LINCS L1000 dataset, we identified drugs that could reverse this inflammatory response. Ex vivo screens, using human samples, showed that saracatinib-a phase 2a-ready SRC and ABL inhibitor-reversed the inflammatory responses induced by ASCVD plasma. In Apoe-/- mice, saracatinib reduced atherosclerosis progression by reprogramming reparative macrophages. In a rabbit model of advanced atherosclerosis, saracatinib reduced plaque inflammation measured by [18F] fluorodeoxyglucose positron emission tomography-magnetic resonance imaging. Here we show a systems immunology-driven drug repurposing with a preclinical validation strategy to aid the development of cardiovascular immunotherapies.

A pilot randomized controlled trial of ketamine in Borderline Personality Disorder

This study is the first randomized controlled trial to test the effects of ketamine in Borderline Personality Disorder (BPD). BPD remains undertreated in the community and no medication has FDA approval for this indication. People with BPD experience chronic mood disturbances with depressed mood, suicidal ideation, and severe social difficulties. In this double-blind, randomized controlled pilot study, we tested the effects of one infusion of ketamine (0.5 mg/kg, n = 10) or the psychoactive comparator drug midazolam (0.04 mg/kg, n = 12) in adults with BPD. Infusions were well tolerated in both groups. Dissociative symptoms during infusion were more intense with ketamine than midazolam (t(12.3) = 3.61, p = 0.01), but they resolved by 40 min after infusion in both groups. Post-infusion adverse events were at the expected low levels in both groups. For our primary outcome measure of suicidal ideation and our secondary outcome measure of depression, we found numerical reduction but not significant group or group x timepoint difference (p > 0.05). For our secondary outcome measures of anxiety and BPD symptoms, we did not observe group or group x timepoint differences. There was a group x timepoint effect for socio-occupational functioning (F(1,20.12) = 5.16, p = 0.03, at Day 14, ketamine group showed more improvement than midazolam group). An exploratory analysis revealed that improvement in socio-occupational functioning was correlated with improvement in depression in the ketamine group (r(8) = 0.65, p = 0.04) but not midazolam group (r(9) = 0.41, p = 0.216). This pilot study provides the first randomized controlled evidence of the effects of antidepressant-dosed ketamine in people with BPD. Our results provide reason for optimism that antidepressant-dosed ketamine will be well-tolerated in larger studies and may provide clinical benefit for mood symptoms and related impairments in people with BPD.

Selenomonas sputigena acts as a pathobiont mediating spatial structure and biofilm virulence in early childhood caries

Streptococcus mutans has been implicated as the primary pathogen in childhood caries (tooth decay). While the role of polymicrobial communities is appreciated, it remains unclear whether other microorganisms are active contributors or interact with pathogens. Here, we integrate multi-omics of supragingival biofilm (dental plaque) from 416 preschool-age children (208 males and 208 females) in a discovery-validation pipeline to identify disease-relevant inter-species interactions. Sixteen taxa associate with childhood caries in metagenomics-metatranscriptomics analyses. Using multiscale/computational imaging and virulence assays, we examine biofilm formation dynamics, spatial arrangement, and metabolic activity of Selenomonas sputigena, Prevotella salivae and Leptotrichia wadei, either individually or with S. mutans. We show that S. sputigena, a flagellated anaerobe with previously unknown role in supragingival biofilm, becomes trapped in streptococcal exoglucans, loses motility but actively proliferates to build a honeycomb-like multicellular-superstructure encapsulating S. mutans, enhancing acidogenesis. Rodent model experiments reveal an unrecognized ability of S. sputigena to colonize supragingival tooth surfaces. While incapable of causing caries on its own, when co-infected with S. mutans, S. sputigena causes extensive tooth enamel lesions and exacerbates disease severity in vivo. In summary, we discover a pathobiont cooperating with a known pathogen to build a unique spatial structure and heighten biofilm virulence in a prevalent human disease.

Long COVID risk and pre-COVID vaccination in an EHR-based cohort study from the RECOVER program

Long COVID, or complications arising from COVID-19 weeks after infection, has become a central concern for public health experts. The United States National Institutes of Health founded the RECOVER initiative to better understand long COVID. We used electronic health records available through the National COVID Cohort Collaborative to characterize the association between SARS-CoV-2 vaccination and long COVID diagnosis. Among patients with a COVID-19 infection between August 1, 2021 and January 31, 2022, we defined two cohorts using distinct definitions of long COVID-a clinical diagnosis (n = 47,404) or a previously described computational phenotype (n = 198,514)-to compare unvaccinated individuals to those with a complete vaccine series prior to infection. Evidence of long COVID was monitored through June or July of 2022, depending on patients' data availability. We found that vaccination was consistently associated with lower odds and rates of long COVID clinical diagnosis and high-confidence computationally derived diagnosis after adjusting for sex, demographics, and medical history.

Ontologizing health systems data at scale: making translational discovery a reality

Common data models solve many challenges of standardizing electronic health record (EHR) data but are unable to semantically integrate all of the resources needed for deep phenotyping. Open Biological and Biomedical Ontology (OBO) Foundry ontologies provide computable representations of biological knowledge and enable the integration of heterogeneous data. However, mapping EHR data to OBO ontologies requires significant manual curation and domain expertise. We introduce OMOP2OBO, an algorithm for mapping Observational Medical Outcomes Partnership (OMOP) vocabularies to OBO ontologies. Using OMOP2OBO, we produced mappings for 92,367 conditions, 8611 drug ingredients, and 10,673 measurement results, which covered 68-99% of concepts used in clinical practice when examined across 24 hospitals. When used to phenotype rare disease patients, the mappings helped systematically identify undiagnosed patients who might benefit from genetic testing. By aligning OMOP vocabularies to OBO ontologies our algorithm presents new opportunities to advance EHR-based deep phenotyping.

Reversal of the diabetic bone signature with anabolic therapies in mice

The mechanisms underlying the bone disease induced by diabetes are complex and not fully understood; and antiresorptive agents, the current standard of care, do not restore the weakened bone architecture. Herein, we reveal the diabetic bone signature in mice at the tissue, cell, and transcriptome levels and demonstrate that three FDA-approved bone-anabolic agents correct it. Diabetes decreased bone mineral density (BMD) and bone formation, damaged microarchitecture, increased porosity of cortical bone, and compromised bone strength. Teriparatide (PTH), abaloparatide (ABL), and romosozumab/anti-sclerostin antibody (Scl-Ab) all restored BMD and corrected the deteriorated bone architecture. Mechanistically, PTH and more potently ABL induced similar responses at the tissue and gene signature levels, increasing both formation and resorption with positive balance towards bone gain. In contrast, Scl-Ab increased formation but decreased resorption. All agents restored bone architecture, corrected cortical porosity, and improved mechanical properties of diabetic bone; and ABL and Scl-Ab increased toughness, a fracture resistance index. Remarkably, all agents increased bone strength over the healthy controls even in the presence of severe hyperglycemia. These findings demonstrate the therapeutic value of bone anabolic agents to treat diabetes-induced bone disease and suggest the need for revisiting the approaches for the treatment of bone fragility in diabetes.

ctDNA and residual cancer burden are prognostic in triple-negative breast cancer patients with residual disease

Triple-negative breast cancer (TNBC) patients with residual disease (RD) after neoadjuvant systemic therapy (NAST) are at high risk for recurrence. Biomarkers to risk-stratify patients with RD could help individualize adjuvant therapy and inform future adjuvant therapy trials. We aim to investigate the impact of circulating tumor DNA (ctDNA) status and residual cancer burden (RCB) class on outcomes in TNBC patients with RD. We analyze end-of-treatment ctDNA status in 80 TNBC patients with residual disease who are enrolled in a prospective multisite registry. Among 80 patients, 33% are ctDNA positive (ctDNA+) and RCB class distribution is RCB-I = 26%, RCB-II = 49%, RCB-III = 18% and 7% unknown. ctDNA status is associated with RCB status, with 14%, 31%, and 57% of patients within RCB-I, -II, and -III classes demonstrating ctDNA+ status (P = 0.028). ctDNA+ status is associated with inferior 3-year EFS (48% vs. 82%, P < 0.001) and OS (50% vs. 86%, P = 0.002). ctDNA+ status predicts inferior 3-year EFS among RCB-II patients (65% vs. 87%, P = 0.044) and shows a trend for inferior EFS among RCB-III patients (13% vs. 40%, P = 0.081). On multivariate analysis accounting for T stage and nodal status, RCB class and ctDNA status independently predict EFS (HR = 5.16, P = 0.016 for RCB class; HR = 3.71, P = 0.020 for ctDNA status). End-of-treatment ctDNA is detectable in one-third of TNBC patients with residual disease after NAST. ctDNA status and RCB are independently prognostic in this setting.

Association between adherence to radiation therapy quality metrics and patient reported outcomes in prostate cancer

BACKGROUND

Prior studies have shown significant variability in the quality of prostate cancer care in the US with questionable associations between quality measures and patient reported outcomes. We evaluated the impact of compliance with nationally recognized radiation therapy (RT) quality measures on patient-reported health-related quality of life (HRQOL) outcomes in the Comparative Effectiveness Analysis of Surgery and Radiation (CEASAR) cohort.

METHODS

CEASAR is a population-based, prospective cohort study of men with localized prostate cancer from which we identified 649 who received primary RT and completed HRQOL surveys for inclusion. Eight quality measures were identified based on national guidelines. We analyzed the impact of compliance with these measures on HRQOL assessed by the 26-item Expanded Prostate Index Composite at pre-specified intervals up to 5 years after treatment. Multivariable analysis was performed controlling for demographic and clinicopathologic features.

RESULTS

Among eligible participants, 566 (87%) patients received external beam radiation therapy and 83 (13%) received brachytherapy. Median age was 69 years (interquartile range: 64-73), 33% had low-, 43% intermediate-, and 23% high-risk disease. 28% received care non-compliant with at least one measure. In multivariable analyses, while some statistically significant associations were identified, there were no clinically significant associations between compliance with evaluated RT quality measures and patient reported urinary irritative, urinary incontinence, bowel, sexual or hormonal function.

CONCLUSIONS

Compliance with RT quality measures was not meaningfully associated with patient-reported outcomes after prostate cancer treatment. Further work is needed to identify patient-centered quality measures of prostate cancer care.

Cross-platform normalization enables machine learning model training on microarray and RNA-seq data simultaneously

Large compendia of gene expression data have proven valuable for the discovery of novel biological relationships. Historically, most available RNA assays were run on microarray, while RNA-seq is now the platform of choice for many new experiments. The data structure and distributions between the platforms differ, making it challenging to combine them directly. Here we perform supervised and unsupervised machine learning evaluations to assess which existing normalization methods are best suited for combining microarray and RNA-seq data. We find that quantile and Training Distribution Matching normalization allow for supervised and unsupervised model training on microarray and RNA-seq data simultaneously. Nonparanormal normalization and z-scores are also appropriate for some applications, including pathway analysis with Pathway-Level Information Extractor (PLIER). We demonstrate that it is possible to perform effective cross-platform normalization using existing methods to combine microarray and RNA-seq data for machine learning applications.

Developing a standardized but extendable framework to increase the findability of infectious disease datasets

Biomedical datasets are increasing in size, stored in many repositories, and face challenges in FAIRness (findability, accessibility, interoperability, reusability). As a Consortium of infectious disease researchers from 15 Centers, we aim to adopt open science practices to promote transparency, encourage reproducibility, and accelerate research advances through data reuse. To improve FAIRness of our datasets and computational tools, we evaluated metadata standards across established biomedical data repositories. The vast majority do not adhere to a single standard, such as Schema.org, which is widely-adopted by generalist repositories. Consequently, datasets in these repositories are not findable in aggregation projects like Google Dataset Search. We alleviated this gap by creating a reusable metadata schema based on Schema.org and catalogued nearly 400 datasets and computational tools we collected. The approach is easily reusable to create schemas interoperable with community standards, but customized to a particular context. Our approach enabled data discovery, increased the reusability of datasets from a large research consortium, and accelerated research. Lastly, we discuss ongoing challenges with FAIRness beyond discoverability.

Multi-center retrospective cohort study applying deep learning to electrocardiograms to identify left heart valvular dysfunction

BACKGROUND

Aortic Stenosis and Mitral Regurgitation are common valvular conditions representing a hidden burden of disease within the population. The aim of this study was to develop and validate deep learning-based screening and diagnostic tools that can help guide clinical decision making.

METHODS

In this multi-center retrospective cohort study, we acquired Transthoracic Echocardiogram reports from five Mount Sinai hospitals within New York City representing a demographically diverse cohort of patients. We developed a Natural Language Processing pipeline to extract ground-truth labels about valvular status and paired these to Electrocardiograms (ECGs). We developed and externally validated deep learning models capable of detecting valvular disease, in addition to considering scenarios of clinical deployment.

RESULTS

We use 617,338 ECGs paired to transthoracic echocardiograms from 123,096 patients to develop a deep learning model for detection of Mitral Regurgitation. Area Under Receiver Operating Characteristic curve (AUROC) is 0.88 (95% CI:0.88-0.89) in internal testing, and 0.81 (95% CI:0.80-0.82) in external validation. To develop a model for detection of Aortic Stenosis, we use 617,338 Echo-ECG pairs for 128,628 patients. AUROC is 0.89 (95% CI: 0.88-0.89) in internal testing, going to 0.86 (95% CI: 0.85-0.87) in external validation. The model's performance increases leading up to the time of the diagnostic echo, and it performs well in validation against requirement of Transcatheter Aortic Valve Replacement procedures.

CONCLUSIONS

Deep learning based tools can increase the amount of information extracted from ubiquitous investigations such as the ECG. Such tools are inexpensive, can help in earlier disease detection, and potentially improve prognosis.

Ultra-long-acting in-situ forming implants with cabotegravir protect female macaques against rectal SHIV infection

Ultra-long-acting delivery platforms for HIV pre-exposure prophylaxis (PrEP) may increase adherence and maximize public health benefit. We report on an injectable, biodegradable, and removable in-situ forming implant (ISFI) that is administered subcutaneously and can release the integrase inhibitor cabotegravir (CAB) above protective benchmarks for more than 6 months. CAB ISFIs are well-tolerated in female mice and female macaques showing no signs of toxicity or chronic inflammation. In macaques, median plasma CAB concentrations exceed established PrEP protection benchmarks within 3 weeks and confer complete protection against repeated rectal SHIV challenges. Implant removal via a small incision in 2 macaques at week 12 results in a 7- to 48-fold decrease in plasma CAB levels within 72 hours. Modeling to translate CAB ISFI dosing suggests that a 3 mL injection would exceed protective benchmarks in humans for over 5 months post administration. Our results support the clinical advancement of CAB ISFIs for ultra-long-acting PrEP in humans.

Loss of alcohol dehydrogenase 1B in cancer-associated fibroblasts: contribution to the increase of tumor-promoting IL-6 in colon cancer

BACKGROUND

Increases in IL-6 by cancer-associated fibroblasts (CAFs) contribute to colon cancer progression, but the mechanisms involved in the increase of this tumor-promoting cytokine are unknown. The aim of this study was to identify novel targets involved in the dysregulation of IL-6 expression by CAFs in colon cancer.

METHODS

Colonic normal (N), hyperplastic, tubular adenoma, adenocarcinoma tissues, and tissue-derived myo-/fibroblasts (MFs) were used in these studies.

RESULTS

Transcriptomic analysis demonstrated a striking decrease in alcohol dehydrogenase 1B (ADH1B) expression, a gene potentially involved in IL-6 dysregulation in CAFs. ADH1B expression was downregulated in approximately 50% of studied tubular adenomas and all T1-4 colon tumors, but not in hyperplastic polyps. ADH1B metabolizes alcohols, including retinol (RO), and is involved in the generation of all-trans retinoic acid (atRA). LPS-induced IL-6 production was inhibited by either RO or its byproduct atRA in N-MFs, but only atRA was effective in CAFs. Silencing ADH1B in N-MFs significantly upregulated LPS-induced IL-6 similar to those observed in CAFs and lead to the loss of RO inhibitory effect on inducible IL-6 expression.

CONCLUSION

Our data identify ADH1B as a novel potential mesenchymal tumor suppressor, which plays a critical role in ADH1B/retinoid-mediated regulation of tumor-promoting IL-6.

Cholinergic neurons in the basal forebrain are involved in behavioral abnormalities associated with Cul3 deficiency: Role of prefrontal cortex projections in cognitive deficits

Loss-of-function mutations of the gene Cul3 have been identified as a risk factor for autism-spectrum disorder (ASD), but the pathogenic mechanisms are not well understood. Conditional Cul3 ablation in cholinergic neurons of mice (ChatCRECul3F/+) recapitulated ASD-like social and sensory gating phenotypes and caused significant cognitive impairments, with diminished activity of cholinergic neurons in the basal forebrain (BF). Chemogenetic inhibition of BF cholinergic neurons in healthy mice induced similar social and cognitive deficits. Conversely, chemogenetic stimulation of BF cholinergic neurons in ChatCRECul3F/+ mice reversed abnormalities in sensory gating and cognition. Cortical hypofunction was also found after ChAT-specific Cul3 ablation and stimulation of cholinergic projections from the BF to the prefrontal cortex (PFC) mitigated cognitive deficits. Overall, we demonstrate that cholinergic dysfunction due to Cul3 deficiency is involved in ASD-like behavioral abnormalities, and that BF cholinergic neurons are particularly critical for cognitive component through their projections to the PFC.