Faculty Bibliography

OBJECTIVES/OBJECTIVE:To determine which in-hospital complications following the operative treatment of hip fractures are associated with increased inpatient, 30-day and 1 year mortality. METHODS:Design: Retrospective study. SETTING/METHODS:A single academic medical center and a Level 1 Trauma Center. PATIENT SELECTION CRITERIA/UNASSIGNED:All patients who were operatively treated for hip fractures (OTA/AO 31A, 31B and Vancouver A,B, and C periprosthetic fractures) at a single center between October, 2014 and June, 2023. OUTCOME MEASURES AND COMPARISONS/UNASSIGNED:Occurrence of an in-hospital complication was recorded. Cohorts were based upon mortality time points (during admission, 30-days and 1-year) and compared to patients who were alive at those time points to determine which in- hospital complications were most associated with mortality. Correlation analysis was performed between patients who died and those who were alive at each time point. RESULTS:A total of 3,134 patients (average age of 79.6 years, range 18-104 years and 66.6% female) met inclusion for this study. The overall mortality rate during admission, 30 days and 1 year were found to be 1.6%, 3.9% and 11.1%, respectively. Sepsis was the complication most associated with increased in-hospital mortality (OR: 7.79, 95% CI 3.22 - 18.82, p<0.001) compared to other in-hospital complications. Compared to other in-hospital complications, stroke was the complication most associated with 30-day mortality (OR: 7.95, 95% CI 1.82 - 34.68, p<0.001). Myocardial infarction was the complication most associated with 1-year mortality (OR: 2.86, 95% CI 1.21 - 6.77, p=0.017) compared to other in-hospital complications. CONCLUSIONS:Post-operative sepsis, stroke and myocardial infraction were the three complications most associated with mortality during admission, 30-day mortality and 1-year mortality, respectively, during the operative treatment of hip fractures. LEVEL OF EVIDENCE/METHODS:Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.

As efforts to study the mechanisms of melanoma metastasis and novel therapeutic approaches multiply, researchers need accurate, high-throughput methods to evaluate the effects on tumor burden resulting from specific interventions. We show that automated quantification of tumor content from whole slide images is a compelling solution to assess in vivo experiments. In order to increase the outflow of data collection from preclinical studies, we assembled a large dataset with annotations and trained a deep neural network for the quantitative analysis of melanoma tumor content on histopathological sections of murine models. After assessing its performance in segmenting these images, the tool obtained consistent results with an orthogonal method (bioluminescence) of measuring metastasis in an experimental setting. This AI-based algorithm, made freely available to academic laboratories through a web-interface called MetFinder, promises to become an asset for melanoma researchers and pathologists interested in accurate, quantitative assessment of metastasis burden.

Glucocorticoids (GCs) are the most prescribed anti-inflammatory and immunosuppressive drugs. However, their use is often limited by substantial side effects, such as GC-induced osteoporosis (GIO) with the underlying mechanisms still not fully understood. In this study, we identify Tau as a low-affinity binding receptor for GCs that plays a crucial role in GIO. Tau deficiency largely abolished bone loss induced by high-dose dexamethasone, a synthetic GC, in both inflammatory arthritis and GIO models. Furthermore, TRx0237, a Tau inhibitor identified from an FDA-approved drug library, effectively prevented GIO. Notably, combinatorial administration of TRx0237 and dexamethasone completely overcame the osteoporosis adverse effect of dexamethasone in treating inflammatory arthritis. These findings present Tau as a previously unrecognized GC receptor with low affinity, and provide potential strategies to mitigate a spectrum of GC-related adverse effects, particularly osteoporosis.

Hair follicle neogenesis (HFN) occurs following large skin excisions in mice, serving as a rare regenerative model in mammalian wound healing. Wound healing typically results in fibrosis in mice and humans. We previously showed small skin excisions in mice result in scarring devoid of HFN, displaying features of non-regenerative healing, and Hedgehog (Hh) activation in the dermis of such wounds can induce HFN. In this study, we sought to verify the role of dermal Wnt/β-catenin signaling in HFN, as this pathway is essential for HF development, but is also paradoxically well-characterized in fibrosis of adult wounds. By deletion of β-catenin in large wound myofibroblasts, we show Wnt/β-catenin signaling is required for endogenous mechanisms of HFN. Through utilizing a combined mouse model that simultaneously induces deletion of β-catenin and constitutive activation of Smoothened (Smo) in myofibroblasts, we also found β-catenin is required for Hh-driven DP formation. Transcriptome analysis confirms Wnt/β-catenin and Hh pathways are activated in dermal papilla (DP) cells. Our results indicate that Wnt-active fibrotic status may also create a permissive state for the regenerative function of Hh, suggesting that activation of both Wnt and Hh pathways in skin wound fibroblasts must be ensured in future strategies to promote HFN.

Estrogen deficiency is considered the most important cause of postmenopausal osteoporosis. However, the underlying mechanism is still not completely understood. In this study, progranulin (PGRN) was isolated as a key regulator of bone mineral density in postmenopausal women through high throughput proteomics screening. In addition, PGRN-deficient mice exhibited significantly lower bone mass than their littermates in an ovariectomy-induced osteoporosis model. Furthermore, estrogen-mediated inhibition of osteoclastogenesis and bone resorption as well as its protection against ovariectomy-induced bone loss largely depended on PGRN. Mechanistic studies revealed the existence of a positive feedback regulatory loop between PGRN and estrogen signaling. In addition, loss of PGRN led to the reduction of estrogen receptor α, the important estrogen receptor involved in estrogen regulation of osteoporosis, through enhancing its degradation via K48-linked ubiquitination. These findings not only provide a previously unrecognized interplay between PGRN and estrogen signaling in regulating osteoclastogenesis and osteoporosis but may also present a new therapeutic approach for the prevention and treatment of postmenopausal osteoporosis by targeting PGRN/estrogen receptor α.

BACKGROUND:Lipoprotein(a) [Lp(a)] is a driver of residual cardiovascular risk. Proprotein convertase subtilisin/kexin type 9 inhibitors (PCSK9i) decrease Lp(a) with significant heterogeneity in response. We investigated contributors to the heterogeneous response. METHODS:CHOlesterol Reduction and Residual Risk in Diabetes (CHORD) was a prospective study examining lipid lowering in participants with a low-density lipoprotein cholesterol (LDL-C) >100 mg/dL with and without diabetes (DM) on lipid lowering therapy (LLT) for 30-days with evolocumab 140 mg every 14 days combined with either atorvastatin 80 mg or ezetimibe 10 mg daily. Lp(a) level was measured by immunoturbidometry, and the apolipoprotein (a) [apo(a)] isoform size was measured by denaturing agarose gel electrophoresis and western blotting. We examined the change in Lp(a) levels from baseline to 30 days. RESULTS:Among 150 participants (mean age 50 years, 58% female, 50% non-White, 17% Hispanic, 50% DM), median (interquartile range) Lp(a) was 27.5 (8-75) mg/dL at baseline and 23 (3-68) mg/dL at 30 days, leading to a 10% (0-36) median reduction (P < 0.001). Among 73 (49%) participants with Lp(a) ≥30 mg/dL at baseline, there was a 15% (3-25) median reduction in Lp(a) (P < 0.001). While baseline Lp(a) level was not correlated with change in Lp(a) (r = 0.04, P = 0.59), apo(a) size directly correlated with Lp(a) reduction (P < 0.001). After adjustment for age, sex, race/ethnicity, DM, and type of LLT, apo(a) size remained positively associated with a reduction in Lp(a) (Beta 0.95, 95% confidence interval, 0.93-0.97, P < 0.001). CONCLUSION/CONCLUSIONS:Our data demonstrate variation in Lp(a) reduction with potent LLT. Change in Lp(a) was strongly associated with apo(a) isoform size.

For many rare diseases with no approved preventive interventions, promising interventions exist. However, it has proven difficult to conduct a pivotal phase 3 trial that could provide direct evidence demonstrating a beneficial effect of the intervention on the target disease outcome. When a promising putative surrogate endpoint(s) for the target outcome is available, surrogate-based provisional approval of an intervention may be pursued. Following the general Causal Roadmap rubric, we describe a surrogate endpoint-based provisional approval causal roadmap. Based on an observational study data set and a phase 3 randomized trial data set, this roadmap defines an approach to analyze the combined data set to draw a conservative inference about the treatment effect (TE) on the target outcome in the phase 3 study population. The observational study enrolls untreated individuals and collects baseline covariates, surrogate endpoints, and the target outcome, and is used to estimate the surrogate index-the regression of the target outcome on the surrogate endpoints and baseline covariates. The phase 3 trial randomizes participants to treated vs. untreated and collects the same data but is much smaller and hence very underpowered to directly assess TE, such that inference on TE is based on the surrogate index. This inference is made conservative by specifying 2 bias functions: one that expresses an imperfection of the surrogate index as a surrogate endpoint in the phase 3 study, and the other that expresses imperfect transport of the surrogate index in the untreated from the observational to the phase 3 study. Plug-in and nonparametric efficient one-step estimators of TE, with inferential procedures, are developed. The finite-sample performance of the estimators is evaluated in simulation studies. The causal roadmap is motivated by and illustrated with contemporary Group B Streptococcus vaccine development.