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Background: Clinical trials in patients with COVID-19 have exclusively used self- or proxy-reporting to characterize alcohol consumption. The aim of this study was to measure an objective biomarker of recent alcohol use in patients hospitalized with severe COVID-19-associated respiratory failure who were enrolled in an investigational clinical trial to determine the prevalence of alcohol misuse, and to explore the relationship of alcohol use with outcomes., Methods: We conducted a substudy of patients enrolled in the multicenter, phase 2, adaptive platform design, Investigation of Serial Studies to Predict Your Therapeutic Response with Imaging And molecular Analysis in COVID-19 trial (ClinicalTrials.gov: NCT04488081), conducted at 20 hospital systems across the United States. Three hundred and fifty-five patients with available red blood cell (RBC) samples and 60-day follow-up assessments were included. RBCs were utilized to measure phosphatidylethanol (PEth). Prespecified thresholds of PEth were utilized to stratify patients into groups: low/no alcohol use (PEth < 20 ng/mL), significant alcohol use (PEth 20-200 ng/mL), and heavy alcohol use (PEth ≥ 200 ng/mL)., Results: In this cohort, 17% of patients met criteria for significant alcohol use, while 4% met criteria for heavy alcohol use. Alcohol misuse was associated with diminished odds for home discharge, though this finding did not achieve statistical significance., Conclusions: In a cohort of patients with severe COVID-19 enrolled in a clinical trial, alcohol consumption of two or more standard drinks per day was present among 21%, approximating the proportion of patients with diabetes, and raising the possibility that alcohol consumption alters risk for severe viral pneumonia. Undetected alcohol misuse among clinical trial participants has the potential to influence study outcomes or contribute to adverse events., (© 2024 Research Society on Alcohol.)

Purpose: The purpose of this study was to evaluate the correlation between longitudinal monitoring of donor-derived cell free DNA (dd-cfDNA) in lung transplant recipients and a "gold standard" of existing tools (pulmonary function testing, radiographic imaging, laboratory and bronchoscopy data, clinical judgment) to assess allograft function., Methods: 24 consecutive transplant recipients were prospectively enrolled in this study measuring dd-cfDNA levels monthly in the first year after bilateral lung transplant. Blinded clinical adjudications were performed at the same timepoints to categorize allograft function as stable (FEV1 within 10% of prior value or when compared to best two averaged post-transplant values) or unstable. When deemed unstable, etiology of unstable graft function was elicited based on available clinical data. We then evaluated the association between dd-cfDNA and the clinical impression of allograft function using linear mixed models which adjusted for patient-level covariates and time since transplant., Results: Unstable allografts were associated with 54.4% higher measures of dd-cfDNA, controlling for time since transplant and demographic covariates [ adjusted mean ratio (aMR)  = 1.54, 95% CI: 1.25-1.91]. Females tended to have higher measures of dd-cfDNA ( aMR  = 1.90 95%CI: 1.14-3.16). A two-fold increase in dd-cfDNA was associated with declines in FEV1 and FVC of 0.047 and 0.066 L, respectively, controlling for time since transplant and demographic covariates ( slope: -0.047 95%CI: -0.076 to -0.019, and slope: -0.066 95%CI: -0.097 to -0.035, respectively). Discussion: Donor derived cell free DNA presents a potential additional minimally invasive clinical tool in lung transplant allograft monitoring within the first year of transplant, with unstable allografts correlating with higher dd-cfDNA values., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2024 Smith, Peterson, Pomponio, Steele and Gray.)

Background: Brain ageing is highly heterogeneous, as it is driven by a variety of normal and neuropathological processes. These processes may differentially affect structural and functional brain ageing across individuals, with more pronounced ageing (older brain age) during midlife being indicative of later development of dementia. Here, we examined whether brain-ageing heterogeneity in unimpaired older adults related to neurodegeneration, different cognitive trajectories, genetic and amyloid-beta (Aβ) profiles, and to predicted progression to Alzheimer's disease (AD)., Methods: Functional and structural brain age measures were obtained for resting-state functional MRI and structural MRI, respectively, in 3460 cognitively normal individuals across an age range spanning 42-85 years. Participants were categorised into four groups based on the difference between their chronological and predicted age in each modality: advanced age in both (n = 291), resilient in both (n = 260) or advanced in one/resilient in the other (n = 163/153). With the resilient group as the reference, brain-age groups were compared across neuroimaging features of neuropathology (white matter hyperintensity volume, neuronal loss measured with Neurite Orientation Dispersion and Density Imaging, AD-specific atrophy patterns measured with the Spatial Patterns of Abnormality for Recognition of Early Alzheimer's Disease index, amyloid burden using amyloid positron emission tomography (PET), progression to mild cognitive impairment and baseline and longitudinal cognitive measures (trail making task, mini mental state examination, digit symbol substitution task)., Findings: Individuals with advanced structural and functional brain-ages had more features indicative of neurodegeneration and they had poor cognition. Individuals with a resilient brain-age in both modalities had a genetic variant that has been shown to be associated with age of onset of AD. Mixed brain-age was associated with selective cognitive deficits., Interpretation: The advanced group displayed evidence of increased atrophy across all neuroimaging features that was not found in either of the mixed groups. This is in line with biomarkers of preclinical AD and cerebrovascular disease. These findings suggest that the variation in structural and functional brain ageing across individuals reflects the degree of underlying neuropathological processes and may indicate the propensity to develop dementia in later life., Funding: The National Institute on Aging, the National Institutes of Health, the Swiss National Science Foundation, the Kaiser Foundation Research Institute and the National Heart, Lung, and Blood Institute., Competing Interests: Declaration of interests TB has received investigator-initiated research awards from the NIH, the Alzheimer’s Association, the Foundation at Barnes-Jewish Hospital, Siemens Healthineers, Hyperfine and Avid Radiopharmaceuticals (a wholly-owned subsidiary of Eli Lilly and Company). She participates as a site investigator in clinical trials sponsored by Eli Lilly and Company, Biogen, Eisai, Jaansen, and Roche. She has served as a paid and unpaid consultant to Eisai, Siemens, Biogen, Janssen, Hyperfine, Merck Lilly, and Bristol-Myers Squibb. JCM has served as a paid consultant to the Barcelona Brain Research Center and the Native Alzheimer Disease-related Resource Center in Minority Aging Research. He also received payments for presentations at the AAIM meeting, Longer Life Foundation and the International Brain Health Symposium. JCM has received travel support to attend meetings including: AAIM, DIAN, AD/PD, ATRI/ADNI, ADRC, ADC, the International conference on Health Aging & Biomarkers and the International Brain Health Symposium. He has served on the advisory board for the Cure Alzheimer’s Fund and LEADS at Indiana University. IMN has received payments from Premier, Inc for participating in an advisory board, from Peerview for an educational talk, and from Subtle Medical, Inc for consulting. DW has served as a paid consultant to Qynapse, Beckman Coulter and Eli Lilly. He also received grants from the NIH and Biogen paid to his institution and received travel support from the Alzheimer's Association. SR is an NIA IRP employee and has served on the advisory board of Dementia Platforms, UK, the Canadian Consortium on Neurodegeneration in Aging and the Adult Aging Brain Connectome. She has received travel support from the McKnight Foundation to attend an annual meeting., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Objectives: To describe U.S. practice regarding administration of sedation and analgesia to patients on noninvasive ventilation (NIV) for acute respiratory failure (ARF) and to determine the association of this practice with odds of intubation or death., Design: A retrospective multicenter cohort study., Setting: A total of 1017 hospitals contributed data between January 2010 and September 2020 to the Premier Healthcare Database, a nationally representative healthcare database in the United States., Patients: Adult (≥ 18 yr) patients admitted to U.S. hospitals requiring NIV for ARF., Interventions: None., Measurements and Main Results: We identified 433,357 patients on NIV of whom (26.7% [95% CI] 26.3%-27.0%) received sedation or analgesia. A total of 50,589 patients (11.7%) received opioids only, 40,646 (9.4%) received benzodiazepines only, 20,146 (4.6%) received opioids and benzodiazepines, 1.573 (0.4%) received dexmedetomidine only, and 2,639 (0.6%) received dexmedetomidine in addition to opioid and/or benzodiazepine. Of 433,357 patients receiving NIV, 50,413 (11.6%; 95% CI, 11.5-11.7%) patients underwent invasive mechanical ventilation on hospital days 2-5 or died on hospital days 2-30. Intubation was used in 32,301 patients (7.4%; 95% CI, 7.3-7.6%). Further, death occurred in 24,140 (5.6%; 95% CI, 5.5-5.7%). In multivariable analysis adjusting for relevant covariates, receipt of any medication studied was associated with increased odds of intubation or death. In inverse probability weighting, receipt of any study medication was also associated with increased odds of intubation or death (average treatment effect odds ratio 1.38; 95% CI, 1.35-1.40)., Conclusions: The use of sedation and analgesia during NIV is common. Medication exposure was associated with increased odds of intubation or death. Further investigation is needed to confirm this finding and determine whether any subpopulations are especially harmed by this practice., Competing Interests: This article was supported by an Institutional National Research Service Award (T32) funded by the National Institute of Health, National Heart, Lung, and Blood Institute (T32 HL007085). Dr. Ho disclosed government work. Dr. Sottile’s institution received funding from the National Heart, Lung, and Blood Institute; he received support for article research from the National Institutes of Health. The remaining authors have disclosed that they do not have any potential conflicts of interest., (Copyright © 2024 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.)

Background: Cognitive load theory asserts that learning and performance degrade when cognitive load exceeds working memory capacity. This is particularly relevant in the learning environment of ICU rounds, when multidisciplinary providers integrate complex decision-making and teaching in a noisy, high-stress environment prone to cognitive distractions., Research Question: What features of ICU rounds correlate with high provider cognitive load?, Study Design and Methods: This was an observational, multisite study of multidisciplinary providers during ICU rounds. Investigators recorded rounding characteristics and hourly extraneous cognitive load events during rounds (defined as distractions, episodes of split-attention or repetition, and deviations from standard communication format). After rounds, investigators measured each provider's cognitive load using the provider task load (PTL), an instrument derived from the National Aeronautics and Space Administration Task Load Index survey that assesses perceived workload associated with complex tasks. Relationships between rounding characteristics, extraneous load, and PTL score were evaluated using mixed-effects modeling., Results: A total of 76 providers were observed during 32 rounds from December 2020 to May 2021. The mean rounding census ± SD was 12.5 ± 2.9 patients. The mean rounding time ± SD was 2 h 17 min ± 49 min. The mean extraneous load ± SD was 20.5 ± 4.5 events per hour, or one event every 2 min 51 s. This included 8.6 ± 3.4 distractions, 8.2 ± 4.2 communication deviations, 1.9 ± 1.4 repetitions, and 1.8 ± 1.3 episodes of split-attention per hour. Controlling for covariates, the hourly extraneous load events, number of new patients, and number of higher acuity patients were each associated with increased PTL score (slope, 2.40; 95% CI, 0.76-4.04; slope, 5.23; 95% CI, 2.02-8.43; slope, 3.35; 95% CI, 1.34-5.35, respectively)., Interpretation: Increased extraneous load, new patients, and patient acuity were associated with higher cognitive load during ICU rounds. These results can help direct how the ICU rounding structure may be modified to reduce workload and optimize provider learning and performance., Competing Interests: Financial/Nonfinancial Disclosures None declared., (Copyright © 2024 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.)

Importance: Brain aging elicits complex neuroanatomical changes influenced by multiple age-related pathologies. Understanding the heterogeneity of structural brain changes in aging may provide insights into preclinical stages of neurodegenerative diseases., Objective: To derive subgroups with common patterns of variation in participants without diagnosed cognitive impairment (WODCI) in a data-driven manner and relate them to genetics, biomedical measures, and cognitive decline trajectories., Design, Setting, and Participants: Data acquisition for this cohort study was performed from 1999 to 2020. Data consolidation and harmonization were conducted from July 2017 to July 2021. Age-specific subgroups of structural brain measures were modeled in 4 decade-long intervals spanning ages 45 to 85 years using a deep learning, semisupervised clustering method leveraging generative adversarial networks. Data were analyzed from July 2021 to February 2023 and were drawn from the Imaging-Based Coordinate System for Aging and Neurodegenerative Diseases (iSTAGING) international consortium. Individuals WODCI at baseline spanning ages 45 to 85 years were included, with greater than 50 000 data time points., Exposures: Individuals WODCI at baseline scan., Main Outcomes and Measures: Three subgroups, consistent across decades, were identified within the WODCI population. Associations with genetics, cardiovascular risk factors (CVRFs), amyloid β (Aβ), and future cognitive decline were assessed., Results: In a sample of 27 402 individuals (mean [SD] age, 63.0 [8.3] years; 15 146 female [55%]) WODCI, 3 subgroups were identified in contrast with the reference group: a typical aging subgroup, A1, with a specific pattern of modest atrophy and white matter hyperintensity (WMH) load, and 2 accelerated aging subgroups, A2 and A3, with characteristics that were more distinct at age 65 years and older. A2 was associated with hypertension, WMH, and vascular disease-related genetic variants and was enriched for Aβ positivity (ages ≥65 years) and apolipoprotein E (APOE) ε4 carriers. A3 showed severe, widespread atrophy, moderate presence of CVRFs, and greater cognitive decline. Genetic variants associated with A1 were protective for WMH (rs7209235: mean [SD] B = -0.07 [0.01]; P value = 2.31 × 10-9) and Alzheimer disease (rs72932727: mean [SD] B = 0.1 [0.02]; P value = 6.49 × 10-9), whereas the converse was observed for A2 (rs7209235: mean [SD] B = 0.1 [0.01]; P value = 1.73 × 10-15 and rs72932727: mean [SD] B = -0.09 [0.02]; P value = 4.05 × 10-7, respectively); variants in A3 were associated with regional atrophy (rs167684: mean [SD] B = 0.08 [0.01]; P value = 7.22 × 10-12) and white matter integrity measures (rs1636250: mean [SD] B = 0.06 [0.01]; P value = 4.90 × 10-7)., Conclusions and Relevance: The 3 subgroups showed distinct associations with CVRFs, genetics, and subsequent cognitive decline. These subgroups likely reflect multiple underlying neuropathologic processes and affect susceptibility to Alzheimer disease, paving pathways toward patient stratification at early asymptomatic stages and promoting precision medicine in clinical trials and health care.

Background: Alcohol misuse is overlooked frequently in hospitalized patients, but is common among patients with pneumonia and acute hypoxic respiratory failure. Investigations in hospitalized patients rely heavily on self-report surveys or chart abstraction, which lack sensitivity. Therefore, our understanding of the prevalence of alcohol misuse before and during the COVID-19 pandemic is limited., Research Question: In critically ill patients with respiratory failure, did the proportion of patients with alcohol misuse, defined by the direct biomarker phosphatidylethanol, vary over a period including the COVID-19 pandemic?, Study Design and Methods: Patients with acute hypoxic respiratory failure receiving mechanical ventilation were enrolled prospectively from 2015 through 2019 (before the pandemic) and from 2020 through 2022 (during the pandemic). Alcohol use data, including Alcohol Use Disorders Identification Test (AUDIT)-C scores, were collected from electronic health records, and phosphatidylethanol presence was assessed at ICU admission. The relationship between clinical variables and phosphatidylethanol values was examined using multivariable ordinal regression. Dichotomized phosphatidylethanol values (≥ 25 ng/mL) defining alcohol misuse were compared with AUDIT-C scores signifying misuse before and during the pandemic, and correlations between log-transformed phosphatidylethanol levels and AUDIT-C scores were evaluated and compared by era. Multiple imputation by chained equations was used to handle missing phosphatidylethanol data., Results: Compared with patients enrolled before the pandemic (n = 144), patients in the pandemic cohort (n = 92) included a substantially higher proportion with phosphatidylethanol-defined alcohol misuse (38% vs 90%; P < .001). In adjusted models, absence of diabetes, positive results for COVID-19, and enrollment during the pandemic each were associated with higher phosphatidylethanol values. The correlation between health care worker-recorded AUDIT-C score and phosphatidylethanol level was significantly lower during the pandemic., Interpretation: The higher prevalence of phosphatidylethanol-defined alcohol misuse during the pandemic suggests that alcohol consumption increased during this period, identifying alcohol misuse as a potential risk factor for severe COVID-19-associated respiratory failure. Results also suggest that AUDIT-C score may be less useful in characterizing alcohol consumption during high clinical capacity.

Background: Targeting receptor-interacting serine/threonine protein kinase 1 could mitigate the devastating sequelae of the hyperinflammatory state observed in severe cases of COVID-19. This study explored the immunomodulatory and clinical effects of the receptor-interacting serine/threonine protein kinase 1 inhibitor SAR443122 (eclitasertib) in patients with severe COVID-19., Methods: In this Phase 1b, double-blinded, placebo-controlled study (NCT04469621) a total of 82 patients were screened, of whom 68 patients were eligible and randomized (2:1) to receive eclitasertib 600 mg (300 mg twice daily) or placebo up to 14 days. Primary outcome was relative change in C-reactive protein from baseline to Day 7. Time to clinical improvement using 7-point ordinal scale, ventilator/respiratory failure-free days, change in SpO 2 /FiO 2 ratio, and biomarkers of severe COVID-19 were explored., Results: Geometric mean ratio (point estimate [90% confidence interval]) of the relative change from baseline in C-reactive protein with eclitasertib vs. placebo on Day 7 was 0.85 (0.49-1.45; p = 0.30). Median time to 50% decrease in C-reactive protein from baseline was 3 days vs. 5 days (p = 0.056) with eclitasertib vs. placebo. Median time to ≥ 2-point improvement on 7-point clinical symptoms scale was 8 days vs. 10 days with eclitasertib vs. placebo (p = 0.38). Mean ventilator/respiratory failure-free days, change in baseline-adjusted SpO 2 /FiO 2 ratio, and clinical biomarkers showed consistent numerical improvements with eclitasertib vs. placebo. The most frequently reported treatment-emergent adverse events were gastrointestinal disorders and condition aggravated/worsened COVID-19 pneumonia., Conclusions: Eclitasertib was well tolerated with consistent trends toward more rapid resolution of inflammatory biomarkers and clinical improvement in severe COVID-19 patients than placebo., Gov Identifier: NCT04469621, first posted on clinicaltrials.gov on July 14, 2020., (© 2024. The Author(s).)

SAR439459, a 'second-generation' human anti-transforming growth factor-beta (TGFβ) monoclonal antibody, inhibits all TGFβ isoforms and improves the antitumor activity of anti-programmed cell death protein-1 therapeutics. This study reports the pharmacodynamics (PD) and biomarker results from phase I/Ib first-in-human study of SAR439459 ± cemiplimab in patients with advanced solid tumors (NCT03192345). In dose-escalation phase (Part 1), SAR439459 was administered intravenously at increasing doses either every 2 weeks (Q2W) or every 3 weeks (Q3W) with cemiplimab IV at 3 mg/kg Q2W or 350 mg Q3W, respectively, in patients with advanced solid tumors. In dose-expansion phase (Part 2), patients with melanoma received SAR439459 IV Q3W at preliminary recommended phase II dose (pRP2D) of 22.5/7.5 mg/kg or at 22.5 mg/kg with cemiplimab 350 mg IV Q3W. Tumor biopsy and peripheral blood samples were collected for exploratory biomarker analyses to assess target engagement and PD, and results were correlated with patients' clinical parameters. SAR439459 ± cemiplimab showed decreased plasma and tissue TGFβ, downregulation of TGFβ-pathway activation signature, modulation of peripheral natural killer (NK) and T cell expansion, proliferation, and increased secretion of CXCL10. Conversion of tumor tissue samples from 'immune-excluded' to 'immune-infiltrated' phenotype in a representative patient with melanoma SAR439459 22.5 mg/kg with cemiplimab was observed. In paired tumor and plasma, active and total TGFβ1 was more consistently elevated followed by TGFβ2, whereas TGFβ3 was only measurable (lower limit of quantitation ≥2.68 pg/mg) in tumors. SAR439459 ± cemiplimab showed expected peripheral PD effects and TGFβ alteration. However, further studies are needed to identify biomarkers of response., (© 2024 The Authors. Clinical and Translational Science published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

SAR443820 (DNL788) is a selective, orally bioavailable, brain penetrant inhibitor of receptor-interacting serine/threonine protein kinase 1 (RIPK1). This phase I first-in-human healthy participant study (NCT05795907) was comprised of three parts: randomized, double-blind, placebo-controlled single ascending dose (SAD; part 1a); 14-day multiple ascending dose (MAD; part 2) parts that evaluated safety, tolerability, pharmacokinetics (PK), and pharmacodynamics of SAR443820; and a separate open-label, single-dose part 1b (PK-cerebrospinal fluid [CSF]) to assess SAR443820 levels in CSF. SAR443820 was well-tolerated in healthy participants, and no treatment discontinuation related to an adverse event (AE) occurred. Most common AEs were dizziness and headache. No clinically meaningful changes were noted in laboratory values, vital signs, or electrocardiogram parameters. SAR443820 had a favorable PK profile, with plasma half-lives (geometric mean) ranged between 5.7-8.0 h and 7.2-8.9 h after single and repeated doses, respectively. There were no major deviations from dose proportionality for maximum concentration and area under the curve across SAR443820 doses. Mean CSF-to-unbound plasma concentration ratio ranged from 0.8 to 1.3 over time (assessed up to 10 h postdose), indicating high brain penetrance. High levels of inhibition of activated RIPK1, as measured by decrease in pS166-RIPK1, were achieved in both SAD and MAD parts, with a maximum median inhibition from baseline close to 90% at predose (C trough ) after multiple dosing in MAD, reflecting a marked RIPK1 target engagement at the peripheral level. These results support further development of SAR443820 in phase II trials in amyotrophic lateral sclerosis (NCT05237284) and multiple sclerosis (NCT05630547)., (© 2023 Sanofi and The Authors. Clinical and Translational Science published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Addressing housing insecurity contributes to health care programs as stable housing has positive health benefits. Home environmental hazards may reduce these potential health benefits and could increase morbidity for conditions such as asthma. This study examined housing and indoor air quality among urban low-income households in Colorado to inform housing-insecurity interventions. We conducted a community-engaged study among residents of motels, mobile homes, apartments, and single-family homes that included a survey on the home environment, health, and sociodemographic factors, spirometry, and indoor air quality measurement. We enrolled 60 households: 50% single-family homes, 37% apartments, and 13% residential motels. Perceived stress and depression were higher among motel residents compared with other housing types. We did not find differences in lung function by housing type. Indoor fine particulate matter (PM2.5) and black carbon concentrations were higher in motels than in other housing types. The differential health impacts of housing type support housing programs that jointly address security and quality.

To better understand the impact of the COVID-19 pandemic on the care of patients with pulmonary hypertension, we conducted a retrospective cohort study evaluating health insurance status, healthcare access, disease severity, and patient reported outcomes in this population. Using the Pulmonary Hypertension Association Registry (PHAR), we defined and extracted a longitudinal cohort of pulmonary arterial hypertension (PAH) patients from the PHAR's inception in 2015 until March 2022. We used generalized estimating equations to model the impact of the COVID-19 pandemic on patient outcomes, adjusting for demographic confounders. We assessed whether insurance status modified these effects via covariate interactions. PAH patients were more likely to be on publicly-sponsored insurance during the COVID-19 pandemic compared with prior, and did not experience statistically significant delays in access to medications, increased emergency room visits or nights in the hospital, or worsening of mental health metrics. Patients on publicly-sponsored insurance had higher healthcare utilization and worse objective measures of disease severity compared with privately insured individuals irrespective of the COVID-19 pandemic. The relatively small impact of the COVID-19 pandemic on pulmonary hypertension-related outcomes was unexpected but may be due to pre-established access to high quality care at pulmonary hypertension comprehensive care centers. Irrespective of the COVID-19 pandemic, patients who were on publicly-sponsored insurance seemed to do worse, consistent with prior studies highlighting outcomes in this population. We speculate that previously established care relationships may lessen the impact of an acute event, such as a pandemic, on patients with chronic illness., Competing Interests: The authors declare no conflict of interest., (© 2023 The Authors. Pulmonary Circulation published by John Wiley & Sons Ltd on behalf of Pulmonary Vascular Research Institute.)

Increasing evidence suggests that the presence and spatial localization and distribution pattern of tumor infiltrating lymphocytes (TILs) is associate with response to immunotherapies. Recent studies have identified TGF β activity and signaling as a determinant of T cell exclusion in the tumor microenvironment and poor response to PD-1/PD-L1 blockade. Here we coupled the artificial intelligence (AI)-powered digital image analysis and gene expression profiling as an integrative approach to quantify distribution of TILs and characterize the associated TGF β pathway activity. Analysis of T cell spatial distribution in the solid tumor biopsies revealed substantial differences in the distribution patterns. The digital image analysis approach achieves 74% concordance with the pathologist assessment for tumor-immune phenotypes. The transcriptomic profiling suggests that the TIL score was negatively correlated with TGF β pathway activation, together with elevated TGF β signaling activity observed in excluded and desert tumor phenotypes. The present results demonstrate that the automated digital pathology algorithm for quantitative analysis of CD8 immunohistochemistry image can successfully assign the tumor into one of three infiltration phenotypes: immune desert, immune excluded or immune inflamed. The association between "cold" tumor-immune phenotypes and TGF β signature further demonstrates their potential as predictive biomarkers to identify appropriate patients that may benefit from TGF β blockade., (© 2022 Chinese Pharmaceutical Association and Institute of Materia Medica, Chinese Academy of Medical Sciences. Production and hosting by Elsevier B.V.)

Community detection on graphs constructed from functional magnetic resonance imaging (fMRI) data has led to important insights into brain functional organization. Large studies of brain community structure often include images acquired on multiple scanners across different studies. Differences in scanner can introduce variability into the downstream results, and these differences are often referred to as scanner effects. Such effects have been previously shown to significantly impact common network metrics. In this study, we identify scanner effects in data-driven community detection results and related network metrics. We assess a commonly employed harmonization method and propose new methodology for harmonizing functional connectivity that leverage existing knowledge about network structure as well as patterns of covariance in the data. Finally, we demonstrate that our new methods reduce scanner effects in community structure and network metrics. Our results highlight scanner effects in studies of brain functional organization and provide additional tools to address these unwanted effects. These findings and methods can be incorporated into future functional connectivity studies, potentially preventing spurious findings and improving reliability of results., Competing Interests: Declaration of Competing Interest Authors declare that they have no conflict of interest., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Neuroimaging biomarkers that distinguish between changes due to typical brain ageing and Alzheimer's disease are valuable for determining how much each contributes to cognitive decline. Supervised machine learning models can derive multivariate patterns of brain change related to the two processes, including the Spatial Patterns of Atrophy for Recognition of Alzheimer's Disease (SPARE-AD) and of Brain Aging (SPARE-BA) scores investigated herein. However, the substantial overlap between brain regions affected in the two processes confounds measuring them independently. We present a methodology, and associated results, towards disentangling the two. T 1 -weighted MRI scans of 4054 participants (48-95 years) with Alzheimer's disease, mild cognitive impairment (MCI), or cognitively normal (CN) diagnoses from the Imaging-based coordinate SysTem for AGIng and NeurodeGenerative diseases (iSTAGING) consortium were analysed. Multiple sets of SPARE scores were investigated, in order to probe imaging signatures of certain clinically or molecularly defined sub-cohorts. First, a subset of clinical Alzheimer's disease patients ( n  = 718) and age- and sex-matched CN adults ( n  = 718) were selected based purely on clinical diagnoses to train SPARE-BA1 (regression of age using CN individuals) and SPARE-AD1 (classification of CN versus Alzheimer's disease) models. Second, analogous groups were selected based on clinical and molecular markers to train SPARE-BA2 and SPARE-AD2 models: amyloid-positive Alzheimer's disease continuum group ( n  = 718; consisting of amyloid-positive Alzheimer's disease, amyloid-positive MCI, amyloid- and tau-positive CN individuals) and amyloid-negative CN group ( n  = 718). Finally, the combined group of the Alzheimer's disease continuum and amyloid-negative CN individuals was used to train SPARE-BA3 model, with the intention to estimate brain age regardless of Alzheimer's disease-related brain changes. The disentangled SPARE models, SPARE-AD2 and SPARE-BA3, derived brain patterns that were more specific to the two types of brain changes. The correlation between the SPARE-BA Gap (SPARE-BA minus chronological age) and SPARE-AD was significantly reduced after the decoupling ( r  = 0.56-0.06). The correlation of disentangled SPARE-AD was non-inferior to amyloid- and tau-related measurements and to the number of APOE ε4 alleles but was lower to Alzheimer's disease-related psychometric test scores, suggesting the contribution of advanced brain ageing to the latter. The disentangled SPARE-BA was consistently less correlated with Alzheimer's disease-related clinical, molecular and genetic variables. By employing conservative molecular diagnoses and introducing Alzheimer's disease continuum cases to the SPARE-BA model training, we achieved more dissociable neuroanatomical biomarkers of typical brain ageing and Alzheimer's disease., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Guarantors of Brain.)

The proportion of aging populations affected by dementia is increasing. There is an urgent need to identify biological aging markers in mid-life before symptoms of age-related dementia present for early intervention to delay the cognitive decline and the onset of dementia. In this cohort study involving 1,676 healthy participants (mean age 40) with up to 15 years of follow up, we evaluated the associations between cognitive function and two classes of novel biological aging markers: blood-based epigenetic aging and neuroimaging-based brain aging. Both accelerated epigenetic aging and brain aging were prospectively associated with worse cognitive outcomes. Specifically, every year faster epigenetic or brain aging was on average associated with 0.19-0.28 higher (worse) Stroop score, 0.04-0.05 lower (worse) RAVLT score, and 0.23-0.45 lower (worse) DSST (all false-discovery-rate-adjusted p <0.05). While epigenetic aging is a more stable biomarker with strong long-term predictive performance for cognitive function, brain aging biomarker may change more dynamically in temporal association with cognitive decline. The combined model using epigenetic and brain aging markers achieved the highest accuracy (AUC: 0.68, p<0.001) in predicting global cognitive function status. Accelerated epigenetic age and brain age at midlife may aid timely identification of individuals at risk for accelerated cognitive decline and promote the development of interventions to preserve optimal functioning across the lifespan.

Recently, it was shown that patients with Parkinson's disease (PD) who exhibit an "Alzheimer's disease (AD)-like" pattern of brain atrophy are at greater risk for future cognitive decline. This study aimed to investigate whether this association is domain-specific and whether atrophy associated with brain aging also relates to cognitive impairment in PD. SPARE-AD, an MRI index capturing AD-like atrophy, and atrophy-based estimates of brain age were computed from longitudinal structural imaging data of 178 PD patients and 84 healthy subjects from the LANDSCAPE cohort. All patients underwent an extensive neuropsychological test battery. Patients diagnosed with mild cognitive impairment or dementia were found to have higher SPARE-AD scores as compared to patients with normal cognition and healthy controls. All patient groups showed increased brain age. SPARE-AD predicted impairment in memory, language and executive functions, whereas advanced brain age was associated with deficits in attention and working memory. Data suggest that SPARE-AD and brain age are differentially related to domain-specific cognitive decline in PD. The underlying pathomechanisms remain to be determined., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Importance: Meta-analyses of randomized clinical trials have indicated that improved hypertension control reduces the risk for cognitive impairment and dementia. However, it is unclear to what extent pathways reflective of Alzheimer disease (AD) pathology are affected by hypertension control., Objective: To evaluate the association of intensive blood pressure control on AD-related brain biomarkers., Design, Setting, and Participants: This is a substudy of the Systolic Blood Pressure Intervention Trial (SPRINT MIND), a multicenter randomized clinical trial that compared the efficacy of 2 different blood pressure-lowering strategies. Potential participants (n = 1267) 50 years or older with hypertension and without a history of diabetes or stroke were approached for a brain magnetic resonance imaging (MRI) study. Of these, 205 participants were deemed ineligible and 269 did not agree to participate; 673 and 454 participants completed brain MRI at baseline and at 4-year follow-up, respectively; the final follow-up date was July 1, 2016. Analysis began September 2019 and ended November 2020., Interventions: Participants were randomized to either a systolic blood pressure goal of less than 120 mm Hg (intensive treatment: n = 356) or less than 140 mm Hg (standard treatment: n = 317)., Main Outcomes and Measures: Changes in hippocampal volume, measures of AD regional atrophy, posterior cingulate cerebral blood flow, and mean fractional anisotropy in the cingulum bundle., Results: Among 673 recruited patients who had baseline MRI (mean [SD] age, 67.3 [8.2] years; 271 women [40.3%]), 454 completed the follow-up MRI at a median (interquartile range) of 3.98 (3.7-4.1) years after randomization. In the intensive treatment group, mean hippocampal volume decreased from 7.45 cm3 to 7.39 cm3 (difference, -0.06 cm3; 95% CI, -0.08 to -0.04) vs a decrease from 7.48 cm3 to 7.46 cm3 (difference, -0.02 cm3; 95% CI, -0.05 to -0.003) in the standard treatment group (between-group difference in change, -0.033 cm3; 95% CI, -0.062 to -0.003; P = .03). There were no significant treatment group differences for measures of AD regional atrophy, cerebral blood flow, or mean fractional anisotropy., Conclusions and Relevance: Intensive treatment was associated with a small but statistically significant greater decrease in hippocampal volume compared with standard treatment, consistent with the observation that intensive treatment is associated with greater decreases in total brain volume. However, intensive treatment was not associated with changes in any of the other MRI biomarkers of AD compared with standard treatment., Trial Registration: ClinicalTrials.gov Identifier: NCT01206062.

Introduction: Relationships between brain atrophy patterns of typical aging and Alzheimer's disease (AD), white matter disease, cognition, and AD neuropathology were investigated via machine learning in a large harmonized magnetic resonance imaging database (11 studies; 10,216 subjects)., Methods: Three brain signatures were calculated: Brain-age, AD-like neurodegeneration, and white matter hyperintensities (WMHs). Brain Charts measured and displayed the relationships of these signatures to cognition and molecular biomarkers of AD., Results: WMHs were associated with advanced brain aging, AD-like atrophy, poorer cognition, and AD neuropathology in mild cognitive impairment (MCI)/AD and cognitively normal (CN) subjects. High WMH volume was associated with brain aging and cognitive decline occurring in an ≈10-year period in CN subjects. WMHs were associated with doubling the likelihood of amyloid beta (Aβ) positivity after age 65. Brain aging, AD-like atrophy, and WMHs were better predictors of cognition than chronological age in MCI/AD., Discussion: A Brain Chart quantifying brain-aging trajectories was established, enabling the systematic evaluation of individuals' brain-aging patterns relative to this large consortium., (© 2020 the Alzheimer's Association.)

Deep learning has emerged as a powerful approach to constructing imaging signatures of normal brain ageing as well as of various neuropathological processes associated with brain diseases. In particular, MRI-derived brain age has been used as a comprehensive biomarker of brain health that can identify both advanced and resilient ageing individuals via deviations from typical brain ageing. Imaging signatures of various brain diseases, including schizophrenia and Alzheimer's disease, have also been identified using machine learning. Prior efforts to derive these indices have been hampered by the need for sophisticated and not easily reproducible processing steps, by insufficiently powered or diversified samples from which typical brain ageing trajectories were derived, and by limited reproducibility across populations and MRI scanners. Herein, we develop and test a sophisticated deep brain network (DeepBrainNet) using a large (n = 11 729) set of MRI scans from a highly diversified cohort spanning different studies, scanners, ages and geographic locations around the world. Tests using both cross-validation and a separate replication cohort of 2739 individuals indicate that DeepBrainNet obtains robust brain-age estimates from these diverse datasets without the need for specialized image data preparation and processing. Furthermore, we show evidence that moderately fit brain ageing models may provide brain age estimates that are most discriminant of individuals with pathologies. This is not unexpected as tightly-fitting brain age models naturally produce brain-age estimates that offer little information beyond age, and loosely fitting models may contain a lot of noise. Our results offer some experimental evidence against commonly pursued tightly-fitting models. We show that the moderately fitting brain age models obtain significantly higher differentiation compared to tightly-fitting models in two of the four disease groups tested. Critically, we demonstrate that leveraging DeepBrainNet, along with transfer learning, allows us to construct more accurate classifiers of several brain diseases, compared to directly training classifiers on patient versus healthy control datasets or using common imaging databases such as ImageNet. We, therefore, derive a domain-specific deep network likely to reduce the need for application-specific adaptation and tuning of generic deep learning networks. We made the DeepBrainNet model freely available to the community for MRI-based evaluation of brain health in the general population and over the lifespan., (© The Author(s) (2020). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Neurobiological heterogeneity in schizophrenia is poorly understood and confounds current analyses. We investigated neuroanatomical subtypes in a multi-institutional multi-ethnic cohort, using novel semi-supervised machine learning methods designed to discover patterns associated with disease rather than normal anatomical variation. Structural MRI and clinical measures in established schizophrenia (n = 307) and healthy controls (n = 364) were analysed across three sites of PHENOM (Psychosis Heterogeneity Evaluated via Dimensional Neuroimaging) consortium. Regional volumetric measures of grey matter, white matter, and CSF were used to identify distinct and reproducible neuroanatomical subtypes of schizophrenia. Two distinct neuroanatomical subtypes were found. Subtype 1 showed widespread lower grey matter volumes, most prominent in thalamus, nucleus accumbens, medial temporal, medial prefrontal/frontal and insular cortices. Subtype 2 showed increased volume in the basal ganglia and internal capsule, and otherwise normal brain volumes. Grey matter volume correlated negatively with illness duration in Subtype 1 (r = -0.201, P = 0.016) but not in Subtype 2 (r = -0.045, P = 0.652), potentially indicating different underlying neuropathological processes. The subtypes did not differ in age (t = -1.603, df = 305, P = 0.109), sex (chi-square = 0.013, df = 1, P = 0.910), illness duration (t = -0.167, df = 277, P = 0.868), antipsychotic dose (t = -0.439, df = 210, P = 0.521), age of illness onset (t = -1.355, df = 277, P = 0.177), positive symptoms (t = 0.249, df = 289, P = 0.803), negative symptoms (t = 0.151, df = 289, P = 0.879), or antipsychotic type (chi-square = 6.670, df = 3, P = 0.083). Subtype 1 had lower educational attainment than Subtype 2 (chi-square = 6.389, df = 2, P = 0.041). In conclusion, we discovered two distinct and highly reproducible neuroanatomical subtypes. Subtype 1 displayed widespread volume reduction correlating with illness duration, and worse premorbid functioning. Subtype 2 had normal and stable anatomy, except for larger basal ganglia and internal capsule, not explained by antipsychotic dose. These subtypes challenge the notion that brain volume loss is a general feature of schizophrenia and suggest differential aetiologies. They can facilitate strategies for clinical trial enrichment and stratification, and precision diagnostics., (© The Author(s) (2020). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

As medical imaging enters its information era and presents rapidly increasing needs for big data analytics, robust pooling and harmonization of imaging data across diverse cohorts with varying acquisition protocols have become critical. We describe a comprehensive effort that merges and harmonizes a large-scale dataset of 10,477 structural brain MRI scans from participants without a known neurological or psychiatric disorder from 18 different studies that represent geographic diversity. We use this dataset and multi-atlas-based image processing methods to obtain a hierarchical partition of the brain from larger anatomical regions to individual cortical and deep structures and derive age trends of brain structure through the lifespan (3-96 years old). Critically, we present and validate a methodology for harmonizing this pooled dataset in the presence of nonlinear age trends. We provide a web-based visualization interface to generate and present the resulting age trends, enabling future studies of brain structure to compare their data with this reference of brain development and aging, and to examine deviations from ranges, potentially related to disease., Competing Interests: Declaration of competing interest The authors declare that they have no competing interests., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

Pompe disease is an autosomal recessive lysosomal glycogen storage disorder, characterized by progressive muscle weakness. Deficiency of acid α-glucosidase (EC; 3.2.1.20/3) can be caused by numerous pathogenic variants in the GAA gene. The Pompe Disease Mutation Database at http://www.pompecenter.nl aims to list all variants and their effect. This update reports on 94 variants. We examined 35 novel and 34 known mutations by site-directed mutagenesis and transient expression in COS-7 cells or HEK293T cells. Each of these mutations was given a severity rating using a previously published system, based on the level of acid α-glucosidase activity in medium and transfected cells and on the quantity and quality of the different molecular mass species in the posttranslational modification and transport of acid α-glucosidase. This approach enabled to classify 55 missense mutations as pathogenic and 13 as likely nonpathogenic. Based on their nature and the use of in silico analysis (Alamut® software), 12 of the additional 25 novel mutations were predicted to be pathogenic including 4 splicing mutations, 6 mutations leading to frameshift, and 2 point mutations causing stop codons. Seven of the additional mutations were considered nonpathogenic (4 silent and 3 occurring in intron regions), and 6 are still under investigation., (© 2012 Wiley Periodicals, Inc.)

Pompe disease is a genetic disorder resulting from a deficiency of lysosomal acid alpha-glucosidase (GAA) that manifests as a clinical spectrum with regard to symptom severity and rate of progression. In this study, we used microarrays to examine gene expression from the muscle of two cohorts of infantile-onset Pompe patients to identify transcriptional differences that may contribute to the disease phenotype. We found strong similarities among the gene expression profiles generated from biceps and quadriceps, and identified a number of signaling pathways altered in both cohorts. We also found that infantile-onset Pompe patient muscle had a gene expression pattern characteristic of immature or regenerating muscle, and exhibited many transcriptional markers of inflammation, despite having few overt signs of inflammatory infiltrate. Further, we identified genes exhibiting correlation between expression at baseline and response to therapy. This combined dataset can serve as a foundation for biological discovery and biomarker development to improve the treatment of Pompe disease., (Copyright © 2012 Elsevier Inc. All rights reserved.)

The enzymatic defect in Pompe disease is insufficient lysosomal acid alpha-glucosidase (GAA) activity which leads to lysosomal glycogen accumulation. We recently introduced a simple and reliable method to measure GAA activity in dried blood spots using Acarbose, a highly selective alpha-glucosidase inhibitor, to eliminate isoenzyme interference. Here we demonstrate that this method efficiently detects late-onset Pompe patients who are frequently misdiagnosed by conventional methods due to residual GAA activity in other tissue types.

A CE method for metacycline (MTC) determination was investigated in an inter-laboratory experiment. Many problems were encountered in this study, most of which were related to the transfer of the method to different CE equipment. The reported problems could be classified into different categories: problems related to the precision, to the parameters in the protocol, and to the MTC peak shape. As the peak shape problem was partially responsible for the poor precision, a new CE method was developed in order to obtain a good MTC peak shape on all equipment. The precision of this new method for MTC determination was examined in an intermediate precision study, where the influence of the factors "time" and "equipment" was investigated. Although the new method could be transferred to different instruments, the precision remained poor mainly due to the contributions of the between-replicate and the between-injection variances.