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STUDY OBJECTIVES: To describe initial insomnia-related encounters among a national sample of Medicare beneficiaries, and to identify older adults at risk for potentially inappropriate prescription insomnia medication usage. METHODS: Our data source was a random 5% sample of Medicare administrative claims data (2006-2013). Insomnia was operationalized as International Classification of Disease, Ninth Revision, Clinical Modification diagnostic codes. Insomnia medications included FDA-approved insomnia-related medication classes and drugs. Logistic regression was employed to identify predictors of being prescribed only (i.e., being prescribed an insomnia medication without a corresponding insomnia diagnosis). RESULTS: A total of N = 60 362 beneficiaries received either an insomnia diagnosis or a prescription for an insomnia medication as their first sleep-related encounter during the study period. Of these, 55.1% (n = 33 245) were prescribed only, whereas 44.9% (n = 27 117) received a concurrent insomnia diagnosis. In a fully adjusted regression model, younger age (odds ratio (OR) 0.98; 95% confidence interval (CI) 0.98, 0.99), male sex (OR 1.15; 95% CI 1.11, 1.20), and several comorbid conditions (i.e., dementia [OR 1.21; 95% CI 1.15, 1.27] and anemia [OR 1.17; 95% CI 1.13, 1.22]) were positively associated with being prescribed only. Conversely, black individuals (OR 0.83; 95% CI 0.78, 0.89) and those of other race (OR 0.89; 95% CI 0.84, 0.94) were less likely to be prescribed only. Individuals who received care from a board-certified sleep medicine provider (BCSMP) were less likely to be prescribed only (OR 0.27; 95% CI 0.16, 0.46). CONCLUSIONS: Fewer than half of Medicare beneficiaries prescribed insomnia medications ever received a formal sleep-related diagnosis.

The purpose of the present study was to evaluate the impact of sleep disturbances on subsequent depressive symptomatology among a representative sample of patients following traumatic brain injury (TBI). Within a retrospective cohort design, our sample included 305 individuals from the Transforming Research and Clinical Knowledge in Traumatic Brain Injury Pilot (TRACK-TBI Pilot; NINDS-OD09-004) database. At 3-months post-TBI, symptoms of insomnia were reported by 34% of patients, and symptoms of hypersomnia were reported by 39% of patients. For the vast majority of individuals, sleep complaints were likely to persist through 6-month follow-up. Symptoms of hypersomnia but not insomnia at three months were associated with worsened depressive symptomatology at six months. These results highlight the importance of sleep disturbances in recovery from TBI and suggest targeted sleep treatments as a pathway to improve outcomes and quality of life following TBI.

Fibroblasts play critical roles in tissue homeostasis, but in pathologic states they can drive fibrosis, inflammation, and tissue destruction. Little is known about what regulates the homeostatic functions of fibroblasts. Here, we perform RNA sequencing and identify a gene expression program in healthy synovial fibroblasts characterized by enhanced fatty acid metabolism and lipid transport. We identify cortisol as the key driver of the healthy fibroblast phenotype and that depletion of adipocytes, which express high levels of Hsd11b1, results in loss of the healthy fibroblast phenotype in mouse synovium. Additionally, fibroblast-specific glucocorticoid receptor Nr3c1 deletion in vivo leads to worsened arthritis. Cortisol signaling in fibroblasts mitigates matrix remodeling induced by TNF and TGF-β1 in vitro, while stimulation with these cytokines represses cortisol signaling and adipogenesis. Together, these findings demonstrate the importance of adipocytes and cortisol signaling in driving the healthy synovial fibroblast state that is lost in disease.Fibroblasts play critical roles in tissue homeostasis, but in pathologic states they can drive fibrosis, inflammation, and tissue destruction. Here, Faust et al. find that healthy human synovial fibroblasts under the influence of adjacent adipocytes have altered lipid metabolism driven by cortisol signaling. Both adipocytes and these characteristics are lost in inflammatory arthritis. [ABSTRACT FROM AUTHOR]

It is well-known that older adults have poorer recovery following traumatic brain injury (TBI) relative to younger adults with similar injury severity. However, most older adults do recover well from TBI. Identifying those at increased risk of poor recovery could inform appropriate management pathways, facilitate discussions about palliative care or unmet needs, and permit targeted intervention to optimize quality of life or recovery. We sought to explore heterogeneity in recovery from TBI among older adults as measured by home time per month, a patient-centered metric defined as time spent at home and not in a hospital, urgent care, or other facility. Using data obtained from Medicare administrative claims data for years 2010-2018, group-based trajectory modeling was employed to identify unique trajectories of recovery among a sample of United States adults age 65 and older who were hospitalized with TBI. We next determined which patient-level characteristics discriminated poor from favorable recovery using logistic regression. Among 20,350 beneficiaries, four unique trajectories were identified: poor recovery (n = 1929; 9.5%), improving recovery (n = 2,793; 13.7%), good recovery (n = 13,512; 66.4%), and declining recovery (n = 2116; 10.4%). The strongest predictors of membership in the poor relative to the good recovery trajectory group were diagnosis of Alzheimer's disease and related dementias (ADRD; odd ratio [OR] 2.42; 95% confidence interval [CI] 2.16, 2.72) and dual eligibility for Medicaid, a proxy for economic vulnerability (OR 5.13; 95% CI 4.59, 5.74). TBI severity was not associated with recovery trajectories. In conclusion, this study identified four unique trajectories of recovery over one year following TBI among older adults. Two-thirds of older adults hospitalized with TBI returned to the community and stayed there. Recovery of monthly home time was complete for most by 3 months post injury. An important sub-group comprising 10% of patients who did not return home was characterized primarily by eligibility for Medicaid and diagnosis of ADRD. Future studies should seek to further characterize and investigate identified recovery groups to inform management and development of interventions to improve recovery. [ABSTRACT FROM AUTHOR]

Background/Objective: Dementia is estimated to affect over 150 million individuals by 2050. Individuals with dementia commonly suffer from other comorbid conditions which can affect quality of life and result in increased health care expenditures. We conducted this study to determine the frequency of comorbid conditions between representative samples of non-Hispanic Black and White US adults aged ≥65 with dementia. Methods: This cross-sectional study was conducted on non-Hispanic Black and White adults aged 65 and older with dementia whose data were retrieved from the National Hospital Ambulatory Medical Care Survey, 2016–2021, and the National Ambulatory Medical Care Survey, 2016, 2018, and 2019. Dementia was defined based on medical record abstraction. The exposure was Black vs. White race. The outcome was a sum of 13 comorbid conditions, including obesity, hypertension, cancer, cerebrovascular disease, congestive heart failure, and coronary artery disease, assessed in older adults with dementia. Results: A total of 1354 non-Hispanic (1175 White and 179 Black) participants were studied. The mean number of comorbid conditions, as well as the prevalence of obesity, cerebrovascular disease, congestive heart failure, and coronary artery disease, was significantly (p  <  0.01) higher in the Black vs. White study participants. The Black participants were more likely to have more than two comorbid conditions relative to those who were White (odds ratio 2.5; 95% confidence interval 1.6 to 3.7). Conclusions: A higher burden of comorbid conditions was observed among non-Hispanic Blacks compared to non-Hispanic White older adults with dementia. Future studies should examine the quality of life and health care utilization implications of this finding. [ABSTRACT FROM AUTHOR]

Objective: To estimate the impact of traumatic brain injury (TBI) on prevalence of posttraumatic stress disorder (PTSD), depression, and alcohol and substance use disorders. Setting: A random sample of Veteran's Health Administration data. Participants: A total of 14 116 veterans aged =55 with incident late-life TBI between October 1, 1999, and September 31, 2021, were matched 1:3 on age and TBI date to 42 678 veterans without TBI. Design: Retrospective cohort study. Main Measures: PTSD, depression, and alcohol and substance use disorders were identified using diagnostic codes. Participants were censored after the first diagnosis during the year before and the year after the TBI or matched date. Prevalence rates of PTSD, depression, alcohol, and substance use disorders were compared before and after incident TBI or matched date using Poisson regression. Results: Pre-TBI prevalence rates of disorders were higher among those with TBI relative to those without TBI. Pre-TBI PTSD prevalence rates (per 1000 person-years) were 126.3 (95% CI, 120.2-132.4) compared to 21.5 (95% CI, 20.1-22.9) in the non-TBI cohort. In adjusted models, TBI was not associated with an increase in the prevalence of any of the studied disorders. Conclusions: Prevalence rates of depression, PTSD, and alcohol and substance use disorders were 5 to 10 times higher among older veterans before incident TBI. We did not observe an increase in the prevalence of these disorders after incident TBI. Older veterans with these disorders may be at increased risk for TBI. [ABSTRACT FROM AUTHOR]

A rapidly expanding scientific literature supports the frequent co-occurrence of sleep and circadian disturbances following mild traumatic brain injury (mTBI). Although many questions remain unanswered, the preponderance of evidence suggests that sleep and circadian disorders can result from mTBI. Among those with mTBI, sleep disturbances and clinical sleep and circadian disorders contribute to the morbidity and long-term sequelae across domains of functional outcomes and quality of life. Specifically, along with deterioration of neurocognitive performance, insufficient and disturbed sleep can precede, exacerbate, or perpetuate many of the other common sequelae of mTBI, including depression, post-traumatic stress disorder, and chronic pain. Further, sleep and mTBI share neurophysiologic and neuroanatomic mechanisms that likely bear directly on success of rehabilitation following mTBI. For these reasons, focus on disturbed sleep as a modifiable treatment target has high likelihood of improving outcomes in mTBI. Here, we review relevant literature and present a research agenda to 1) advance understanding of the reciprocal relationships between sleep and circadian factors and mTBI sequelae and 2) advance rapidly the development of sleep-related treatments in this population.

Rheumatoid arthritis (RA) is a complex immune-mediated inflammatory disorder in which patients suffer from inflammatory-erosive arthritis. Recent advances on histopathology heterogeneity of RA synovial tissue revealed three distinct phenotypes based on cellular composition (pauci-immune, diffuse and lymphoid), suggesting that distinct etiologies warrant specific targeted therapy which motivates a need for cost effective phenotyping tools in preclinical and clinical settings. To this end, we developed an automated multi-scale computational pathotyping (AMSCP) pipeline for both human and mouse synovial tissue with two distinct components that can be leveraged together or independently: (1) segmentation of different tissue types to characterize tissue-level changes, and (2) cell type classification within each tissue compartment that assesses change across disease states. Here, we demonstrate the efficacy, efficiency, and robustness of the AMSCP pipeline as well as the ability to discover novel phenotypes. Taken together, we find AMSCP to be a valuable cost-effective method for both pre-clinical and clinical research. Automated pathotyping of synovial tissue in arthritis is a major unmet need. Here, the authors develop and demonstrate the efficacy of an automated tissue and cellular pathotyping tool for inflammatory arthritis. [ABSTRACT FROM AUTHOR]

Rheumatoid arthritis (RA) is an autoimmune disease involving antigen-specific T and B cells. Here, we perform single-cell RNA and repertoire sequencing on paired synovial tissue and blood samples from 12 seropositive RA patients. We identify clonally expanded CD4 + T cells, including CCL5+ cells and T peripheral helper (Tph) cells, which show a prominent transcriptomic signature of recent activation and effector function. CD8 + T cells show higher oligoclonality than CD4 + T cells, with the largest synovial clones enriched in GZMK+ cells. CD8 + T cells with possibly virus-reactive TCRs are distributed across transcriptomic clusters. In the B cell compartment, NR4A1+ activated B cells, and plasma cells are enriched in the synovium and demonstrate substantial clonal expansion. We identify synovial plasma cells that share BCRs with synovial ABC, memory, and activated B cells. Receptor-ligand analysis predicted IFNG and TNFRSF members as mediators of synovial Tph-B cell interactions. Together, these results reveal clonal relationships between functionally distinct lymphocyte populations that infiltrate the synovium of patients with RA. Activated B cells and T cells accumulate within joints of patients with rheumatoid arthritis. Here, the authors use single-cell transcriptome and repertoire profiling to identify clonally expanded synovial B cells and T cells and define their phenotypes and predicted cell-cell interactions. [ABSTRACT FROM AUTHOR]

Synovial tissue inflammation is a hallmark of rheumatoid arthritis (RA). Recent work has identified prominent pathogenic cell states in inflamed RA synovial tissue, such as T peripheral helper cells; however, the epigenetic regulation of these states has yet to be defined. Here, we examine genome-wide open chromatin at single-cell resolution in 30 synovial tissue samples, including 12 samples with transcriptional data in multimodal experiments. We identify 24 chromatin classes and predict their associated transcription factors, including a CD8 + GZMK+ class associated with EOMES and a lining fibroblast class associated with AP-1. By integrating with an RA tissue transcriptional atlas, we propose that these chromatin classes represent 'superstates' corresponding to multiple transcriptional cell states. Finally, we demonstrate the utility of this RA tissue chromatin atlas through the associations between disease phenotypes and chromatin class abundance, as well as the nomination of classes mediating the effects of putatively causal RA genetic variants. The epigenetic changes underlying the heterogeneity of RA disease presentation have been the subject of intense scrutiny. In this study, the authors use multiple single-cell sequencing datasets to define 'chromatin superstates' in patients with RA, which associate with distinct transcription factors and disease phenotypes. [ABSTRACT FROM AUTHOR]

Objective: Recent studies have uncovered diverse cell types and states in the rheumatoid arthritis (RA) synovium; however, limited data exist correlating these findings with patient‐level clinical information. Using the largest cohort to date with clinical and multicell data, we determined associations between RA clinical factors with cell types and states in the RA synovium. Methods: The Accelerated Medicines Partnership Rheumatoid Arthritis study recruited patients with active RA who were not receiving disease‐modifying antirheumatic drugs (DMARDs) or who had an inadequate response to methotrexate (MTX) or tumor necrosis factor inhibitors. RA clinical factors were systematically collected. Biopsies were performed on an inflamed joint, and tissue were disaggregated and processed with a cellular indexing of transcriptomes and epitopes sequencing pipeline from which the following cell type percentages and cell type abundance phenotypes (CTAPs) were derived: endothelial, fibroblast, and myeloid (EFM); fibroblasts; myeloid; T and B cells; T cells and fibroblasts (TF); and T and myeloid cells. Correlations were measured between RA clinical factors, cell type percentage, and CTAPs. Results: We studied 72 patients (mean age 57 years, 75% women, 83% seropositive, mean RA duration 6.6 years, mean Disease Activity Score‐28 C‐reactive Protein 3 [DAS28‐CRP3] score 4.8). Higher DAS28‐CRP3 correlated with a higher T cell percentage (P < 0.01). Those receiving MTX and not a biologic DMARD (bDMARD) had a higher percentage of B cells versus those receiving no DMARDs (P < 0.01). Most of those receiving bDMARDs were categorized as EFM (57%), whereas none were TF. No significant difference was observed across CTAPs for age, sex, RA disease duration, or DAS28‐CRP3. Conclusion: In this comprehensive screen of clinical factors, we observed differential associations between DMARDs and cell phenotypes, suggesting that RA therapies, more than other clinical factors, may impact cell type/state in the synovium and ultimately influence response to subsequent therapies. [ABSTRACT FROM AUTHOR]