Sildenafil as a Candidate Drug for Alzheimer's Disease: Real-World Patient Data Observation and Mechanistic Observations from Patient-Induced Pluripotent Stem Cell-Derived Neurons.

Background: Alzheimer's disease (AD) is a chronic neurodegenerative disease needing effective therapeutics urgently. Sildenafil, one of the approved phosphodiesterase-5 inhibitors, has been implicated as having potential effect in AD. Objective: To investigate the potential therapeutic benefit of sildenafil on AD. Methods: We performed real-world patient data analysis using the MarketScan® Medicare Supplemental and the Clinformatics® databases. We conducted propensity score-stratified analyses after adjusting confounding factors (i.e., sex, age, race, and comorbidities). We used both familial and sporadic AD patient induced pluripotent stem cells (iPSC) derived neurons to evaluate the sildenafil's mechanism-of-action. Results: We showed that sildenafil usage is associated with reduced likelihood of AD across four new drug compactor cohorts, including bumetanide, furosemide, spironolactone, and nifedipine. For instance, sildenafil usage is associated with a 54% reduced incidence of AD in MarketScan® (hazard ratio [HR] = 0.46, 95% CI 0.32- 0.66) and a 30% reduced prevalence of AD in Clinformatics® (HR = 0.70, 95% CI 0.49- 1.00) compared to spironolactone. We found that sildenafil treatment reduced tau hyperphosphorylation (pTau181 and pTau205) in a dose-dependent manner in both familial and sporadic AD patient iPSC-derived neurons. RNA-sequencing data analysis of sildenafil-treated AD patient iPSC-derived neurons reveals that sildenafil specifically target AD related genes and pathobiological pathways, mechanistically supporting the beneficial effect of sildenafil in AD. Conclusions: These real-world patient data validation and mechanistic observations from patient iPSC-derived neurons further suggested that sildenafil is a potential repurposable drug for AD. Yet, randomized clinical trials are warranted to validate the causal treatment effects of sildenafil in AD.

Prevalence and trend of central nervous system-active medication polypharmacy among US commercially insured adults with vs without early-onset dementia: a multi-year cross-sectional study.

BACKGROUND: Limited data exist on the prevalence and trend of central nervous system (CNS)-active medication polypharmacy among adults with early-onset dementia (EOD) and whether these estimates differ for adults without EOD but with chronic pain, depression, or epilepsy, conditions managed by CNS-active medications. METHODS: A multi-year, cross-sectional study using 2012-2021 MarketScan Commercial Claims data was conducted among adults aged 30 to 64 years with EOD and those without EOD but having a diagnosis of chronic pain, depression, or epilepsy as comparison groups. For each disease cohort, the primary outcome was CNS-active medication polypharmacy defined as concurrent use of ≥ 3 CNS-active medications on the US Beers Criteria list that overlapped for > 30 consecutive days during 12 months following a randomly selected medical encounter with the disease diagnosis. A separate multivariate modified Poisson regression model was used to estimate time trends in CNS polypharmacy in each disease cohort. Differences in trend estimates between EOD and non-EOD disease cohorts were examined by an interaction between EOD status and yearly time. RESULTS: From 2013 to 2020, the annual crude prevalence of CNS polypharmacy was higher among adults with EOD (21.2%-25.0%) than adults with chronic pain (5.1%-5.9%), depression (14.8%-21.7%), or epilepsy (20.0%-22.3%). The adjusted annual prevalence of CNS polypharmacy among patients with EOD did not significantly change between 2013 and 2020 (adjusted prevalence rate ratio [aPRR], 0.94; 95% CI, 0.88-1.01), whereas a significant decreasing trend was observed among non-EOD cohorts with chronic pain (aPRR, 0.66; 95% CI, 0.63-0.69), depression (aPRR, 0.81; 95% CI, 0.77-0.85), and epilepsy (aPRR, 0.86; 95% CI, 0.83-0.89). The interaction analysis indicated that patients with epilepsy and depression (vs with EOD) had a decreasing probability of CNS-active medication polypharmacy over time (aPRR, 0.98 [95% CI, 0.98-0.99]; P < .001 for interaction for both conditions). CONCLUSIONS: The prevalence of CNS polypharmacy among US commercially insured adults with EOD (vs without) was higher and remained unchanged from 2013 to 2021. Medication reviews of adults with EOD and CNS polypharmacy are needed to ensure that benefits outweigh risks associated with combined use of these treatments.

Comparing super-utilizers and lower-utilizers among commercial- and Medicare-insured adults with sickle cell disease.

ABSTRACT: Sickle cell disease (SCD) is a rare but costly condition in the United States. Super-utilizers have been defined as a subset of the population with high health care encounters or expenditures. Although super-utilizers have been described in other disease states, little is known about super-utilizers among adults with SCD. This study aimed to characterize the differences in expenditures, overall health care encounters, and pain episode encounters between super-utilizers (top 10% expenditures) and lower-utilizers with SCD (high, top 10%-24.9%; moderate, 25%-49.9%; and low, bottom 50% expenditures). A retrospective longitudinal cohort of adults with SCD were identified using validated algorithms in MarketScan and Medicare claim databases from 2016 to 2020. Encounters and expenditures were analyzed from inpatient, outpatient, and emergency department settings. Differences in encounters and expenditures between lower-utilizers and super-utilizers were compared using logistic regression. Among super-utilizers, differences in encounters and expenditures were compared according to incidences of pain episode encounters. The study population included 5666 patients with commercial insurance and 8600 with Medicare. Adjusted total annual health care expenditure was 43.46 times higher for super-utilizers than for low-utilizers among commercial-insured and 13.37 times higher in Medicare-insured patients. Among super-utilizers, there were patients with few pain episode encounters who had higher outpatient expenditures than patients with a high number of pain episode encounters. Our findings demonstrate the contribution of expensive outpatient care among SCD super-utilizers, in which analyses of high expenditure have largely focused on short-term care. Future studies are needed to better understand super-utilizers in the SCD population to inform the effective use of preventive interventions and/or curative therapies.

Application of an Innovative Data Mining Approach Towards Safe Polypharmacy Practice in Older Adults.

INTRODUCTION: Polypharmacy is common and is associated with higher risk of adverse drug event (ADE) among older adults. Knowledge on the ADE risk level of exposure to different drug combinations is critical for safe polypharmacy practice, while approaches for this type of knowledge discovery are limited. The objective of this study was to apply an innovative data mining approach to discover high-risk and alternative low-risk high-order drug combinations (e.g., three- and four-drug combinations). METHODS: A cohort of older adults (≥ 65 years) who visited an emergency department (ED) were identified from Medicare fee-for-service and MarketScan Medicare supplemental data. We used International Classification of Diseases (ICD) codes to identify ADE cases potentially induced by anticoagulants, antidiabetic drugs, and opioids from ED visit records. We assessed drug exposure data during a 30-day window prior to the ED visit dates. We investigated relationships between exposure of drug combinations and ADEs under the case-control setting. We applied the mixture drug-count response model to identify high-order drug combinations associated with an increased risk of ADE. We conducted therapeutic class-based mining to reveal low-risk alternative drug combinations for high-order drug combinations associated with an increased risk of ADE. RESULTS: We investigated frequent high-order drug combinations from 8.4 million ED visit records (5.1 million from Medicare data and 3.3 million from MarketScan data). We identified 5213 high-order drug combinations associated with an increased risk of ADE by controlling the false discovery rate at 0.01. We identified 1904 high-order, high-risk drug combinations had potential low-risk alternative drug combinations, where each high-order, high-risk drug combination and its corresponding low-risk alternative drug combination(s) have similar therapeutic classes. CONCLUSIONS: We demonstrated the application of a data mining technique to discover high-order drug combinations associated with an increased risk of ADE. We identified high-risk, high-order drug combinations often have low-risk alternative drug combinations in similar therapeutic classes.

Modeling Path Importance for Effective Alzheimer's Disease Drug Repurposing.

Recently, drug repurposing has emerged as an effective and resource-efficient paradigm for AD drug discovery. Among various methods for drug repurposing, network-based methods have shown promising results as they are capable of leveraging complex networks that integrate multiple interaction types, such as protein-protein interactions, to more effectively identify candidate drugs. However, existing approaches typically assume paths of the same length in the network have equal importance in identifying the therapeutic effect of drugs. Other domains have found that same length paths do not necessarily have the same importance. Thus, relying on this assumption may be deleterious to drug repurposing attempts. In this work, we propose MPI (Modeling Path Importance), a novel network-based method for AD drug repurposing. MPI is unique in that it prioritizes important paths via learned node embeddings, which can effectively capture a network's rich structural information. Thus, leveraging learned embeddings allows MPI to effectively differentiate the importance among paths. We evaluate MPI against a commonly used baseline method that identifies anti-AD drug candidates primarily based on the shortest paths between drugs and AD in the network. We observe that among the top-50 ranked drugs, MPI prioritizes 20.0% more drugs with anti-AD evidence compared to the baseline. Finally, Cox proportional-hazard models produced from insurance claims data aid us in identifying the use of etodolac, nicotine, and BBB-crossing ACE-INHs as having a reduced risk of AD, suggesting such drugs may be viable candidates for repurposing and should be explored further in future studies.

Modeling Path Importance for Effective Alzheimer's Disease Drug Repurposing.

Recently, drug repurposing has emerged as an effective and resource-efficient paradigm for AD drug discovery. Among various methods for drug repurposing, network-based methods have shown promising results as they are capable of leveraging complex networks that integrate multiple interaction types, such as protein-protein interactions, to more effectively identify candidate drugs. However, existing approaches typically assume paths of the same length in the network have equal importance in identifying the therapeutic effect of drugs. Other domains have found that same length paths do not necessarily have the same importance. Thus, relying on this assumption may be deleterious to drug repurposing attempts. In this work, we propose MPI (Modeling Path Importance), a novel network-based method for AD drug repurposing. MPI is unique in that it prioritizes important paths via learned node embeddings, which can effectively capture a network's rich structural information. Thus, leveraging learned embeddings allows MPI to effectively differentiate the importance among paths. We evaluate MPI against a commonly used baseline method that identifies anti-AD drug candidates primarily based on the shortest paths between drugs and AD in the network. We observe that among the top-50 ranked drugs, MPI prioritizes 20.0% more drugs with anti-AD evidence compared to the baseline. Finally, Cox proportional-hazard models produced from insurance claims data aid us in identifying the use of etodolac, nicotine, and BBB-crossing ACE-INHs as having a reduced risk of AD, suggesting such drugs may be viable candidates for repurposing and should be explored further in future studies.

The Risk of Colorectal Polyps after Weight Loss Therapy Versus Obesity: A Propensity-Matched Nationwide Cohort Study.

BACKGROUND: A fundamental understanding of the impact of bariatric surgery (BRS) on mechanisms of colorectal carcinogenesis is limited. For instance, studies report a reduced risk of colorectal cancer in females but not in males after BRS. We examined whether this sex-specific difference existed at the earlier polyp development stage. METHODS: This retrospective cohort study included 281,417 adults from the 2012-2020 MarketScan database. We compared polyps rates on colonoscopy in four groups: post- vs. pre-BRS (treatment) to post- vs. pre-severe obesity (SO) diagnosis (control). We focused our main analysis on a propensity-matched sample that yielded a balanced distribution of covariates in our four groups (n = 9680 adults, 21.9% males). We also adjusted for important covariates. RESULTS: Metabolic syndrome parameters improved after bariatric surgery and worsened after severe obesity diagnosis (p < 0.05). The rate of polyps was 46.7% at a median of 0.5 years pre-BRS and 47.9% at a median of 0.6 years pre-SO diagnosis. The polyps rate was 45.4% at a median (range) of 3.2 (1.0-8.5) years post-BRS. Conversely, 53.8% of adults had polyps at 3.0 (1.0-8.6) years post-SO. There was no change in the risk of colorectal polyps in males or females post- vs. pre-BRS. However, the risk of polyps was higher in males (OR = 1.32, 95% CI: 1.02-1.70) and females (OR = 1.29, 95% CI: 1.13-1.47) post- vs. pre-SO. When compared to the control group (SO), the odds ratios for colorectal polyps were lower for males and females after bariatric surgery (OR = 0.63, 95% CI: 0.44-0.90, and OR = 0.79, 95% CI: 0.66-0.96, respectively). CONCLUSIONS: Obesity is associated with an increased risk of colorectal polyps, an effect that is ameliorated after bariatric surgery. These data are relevant for studies investigating colorectal carcinogenesis mechanisms.

Generalizability of machine learning methods in detecting adverse drug events from clinical narratives in electronic medical records.

We assessed the generalizability of machine learning methods using natural language processing (NLP) techniques to detect adverse drug events (ADEs) from clinical narratives in electronic medical records (EMRs). We constructed a new corpus correlating drugs with adverse drug events using 1,394 clinical notes of 47 randomly selected patients who received immune checkpoint inhibitors (ICIs) from 2011 to 2018 at The Ohio State University James Cancer Hospital, annotating 189 drug-ADE relations in single sentences within the medical records. We also used data from Harvard's publicly available 2018 National Clinical Challenge (n2c2), which includes 505 discharge summaries with annotations of 1,355 single-sentence drug-ADE relations. We applied classical machine learning (support vector machine (SVM)), deep learning (convolutional neural network (CNN) and bidirectional long short-term memory (BiLSTM)), and state-of-the-art transformer-based (bidirectional encoder representations from transformers (BERT) and ClinicalBERT) methods trained and tested in the two different corpora and compared performance among them to detect drug-ADE relationships. ClinicalBERT detected drug-ADE relationships better than the other methods when trained using our dataset and tested in n2c2 (ClinicalBERT F-score, 0.78; other methods, F-scores, 0.61-0.73) and when trained using the n2c2 dataset and tested in ours (ClinicalBERT F-score, 0.74; other methods, F-scores, 0.55-0.72). Comparison among several machine learning methods demonstrated the superior performance and, therefore, the greatest generalizability of findings of ClinicalBERT for the detection of drug-ADE relations from clinical narratives in electronic medical records.

Promotion of S-nitrosation of cysteine by a {Co(NO)2}10 complex.

S-Nitrosothiols (SNOs) serve as endogenous carriers and donors of NO within living cells, releasing nitrosonium ions (NO+), NO, or other nitroso derivatives. In this study, we present a bioinspired {Co(NO)2}10 complex 1 that achieved S-nitrosation towards Cys residues. The incorporation of a ferrocenyl group in 1 allowed for fine-tuning of the nitrosation reaction, taking advantage of the redox ability of Cys residues. Complex 1 was synthesized and characterized, demonstrating its NO translation reactivity. Furthermore, complex 1 successfully converted Cys into S-nitrosocysteine (Cys-SNO), as confirmed by UV-Vis, IR, and XAS spectroscopy. This study presents a promising approach for S-nitrosation of Cys residues for further exploration in the modification of Cys-containing peptides.

Versatile Synthesis of Symmetric and Unsymmetric Imines via Photoelectrochemical Catalysis: Application to N-Terminal Modification of Phenylalanine.

A strategy that combines electrochemical synthesis and photoredox catalysis was reported for the efficient synthesis of imines. This approach was demonstrated to be highly versatile in producing various types of imines, including symmetric and unsymmetric imines, by exploring the impact of different substituents on the benzene ring of the arylamine. Additionally, the method was specifically applied to modify N-terminal phenylalanine residues and was found to be successful in the photoelectrochemical cross-coupling reaction between NH2 -Phe-OMe and aryl methylamines, leading to the synthesis of phenylalanine-containing imines. Therefore, this technique would present a convenient and efficient platform for synthesizing imines, with promising applications in chemical biology, drug development, and organic synthesis.

The impact of surgical weight loss procedures on the risk of metachronous colorectal neoplasia: the differential effect of surgery type, sex, and anatomic location.

Patients with prior colorectal polyps are at high risk for metachronous colorectal neoplasia, especially in the presence of obesity. We assessed the impact of 2 common bariatric surgeries, vertical sleeve gastrectomy and roux-n-Y gastric bypass, on the risk of colorectal neoplasia recurrence. This nationally representative analysis included 1183 postbariatric adults and 3193 propensity score-matched controls, who all had prior colonoscopy with polyps and polypectomy. Colorectal polyps reoccurred in 63.8% of bariatric surgery patients and 71.7% of controls at a mean follow-up of 53.1 months from prior colonoscopy. There was a reduced odds of colorectal polyp recurrence after bariatric surgery compared with controls (odds ratio [OR] = 0.70, 95% confidence interval [CI] = 0.58 to 0.83). This effect was most pronounced in men (OR = 0.58, 95% CI = 0.42 to 0.79), and post roux-n-Y gastric bypass (OR = 0.57, 95% CI = 0.41 to 0.79). However, the risk of rectal polyps or colorectal cancer remained consistent between groups. This study is the first to our knowledge to show a reduction in risk of polyp recurrence following bariatric surgery.

A comprehensive assessment of statin discontinuation among patients who concurrently initiate statins and CYP3A4-inhibitor drugs; a multistate transition model.

AIMS: The aim of this study was to describe the 1-year direct and indirect transition probabilities to premature discontinuation of statin therapy after concurrently initiating statins and CYP3A4-inhibitor drugs. METHODS: A retrospective new-user cohort study design was used to identify (N = 160 828) patients who concurrently initiated CYP3A4 inhibitors (diltiazem, ketoconazole, clarithromycin, others) and CYP3A4-metabolized statins (statin DDI exposed, n = 104 774) vs. other statins (unexposed to statin DDI, n = 56 054) from the MarketScan commercial claims database (2012-2017). The statin DDI exposed and unexposed groups were matched (2:1) through propensity score matching techniques. We applied a multistate transition model to compare the 1-year transition probabilities involving four distinct states (start, adverse drug events [ADEs], discontinuation of CYP3A4-inhibitor drugs, and discontinuation of statin therapy) between those exposed to statin DDIs vs. those unexposed. Statistically significant differences were assessed by comparing the 95% confidence intervals (CIs) of probabilities. RESULTS: After concurrently starting stains and CYP3A, patients exposed to statin DDIs, vs. unexposed, were significantly less likely to discontinue statin therapy (71.4% [95% CI: 71.1, 71.6] vs. 73.3% [95% CI: 72.9, 73.6]) but more likely to experience an ADE (3.4% [95% CI: 3.3, 3.5] vs. 3.2% [95% CI: 3.1, 3.3]) and discontinue with CYP3A4-inhibitor therapy (21.0% [95% CI: 20.8, 21.3] vs. 19.5% [95% CI: 19.2, 19.8]). ADEs did not change these associations because those exposed to statin DDIs, vs. unexposed, were still less likely to discontinue statin therapy but more likely to discontinue CYP3A4-inhibitor therapy after experiencing an ADE. CONCLUSION: We did not observe any meaningful clinical differences in the probability of premature statin discontinuation between statin users exposed to statin DDIs and those unexposed.

Photoredox C-H functionalization leads the site-selective phenylalanine bioconjugation.

Site-selectively chemical bioconjugation of peptides and proteins can improve the therapeutic exploration of modified protein drugs. Only 3.8% natural abundance of phenylalanine in protein and nearly 90% of proteins contain at least one phenylalanine residue in their sequenced, showing the potential in biopharmaceutical utility of the phenylalanine bioconjugation. However, the covalent bioconjugation of native phenylalanine is one of the most challenging problems in protein modification. Herein, an approach to protein modification is described that relies on a photoredox method for the site-selective bioconjugation of phenylalanine. This methodology has been validated on peptides as well as protein insulin using a straightforward and mild condition. In addition, based on characterization by near-UV CD spectroscopy and small angle X-ray scattering (SAXS), this pyrazole labeling approach permitted the insulin hexamer to completely dissociate into the monomeric form, thus making it a potential candidate for use as rapid-acting insulin for the treatment of diabetes.

Incidence and Risk Factors for New-Onset Diabetes Mellitus After Surgical Resection of Pancreatic Cystic Lesions: A MarketScan Study.

OBJECTIVES: There is a paucity of literature evaluating new-onset diabetes mellitus (NODM) after resection of pancreatic cystic lesions (PCLs). We sought to characterize the incidence and risk factors associated with NODM after partial pancreatectomy for PCLs. METHODS: We utilized the IBM MarketScan Database (2012-2018) to identify all nondiabetic adults who underwent partial pancreatectomy for PCLs. Patients with any other pancreatic disease were excluded. We performed Kaplan-Meier analysis and multivariable Cox proportional hazards regression to define the incidence and risk factors of postoperative NODM. RESULTS: Among 311 patients, the overall risk (95% confidence interval) of NODM was 9.1% (6.3-12.9%), 15.1% (11.3-20.2%), and 20.2% (15.3-26.4%) at 6, 12 and 24 months, respectively. Multivariable analysis (adjusted hazard ratio; 95% confidence interval) revealed that older age (1.97; 1.04-3.72; 55-64 vs 18-54 years), obesity (2.63; 1.35-5.12), hypertension (1.79; 1.01-3.17), and cardiovascular disease (2.54; 1.02-6.28) were independent predictors of NODM. Rates of NODM were similar after distal pancreatectomy versus pancreaticoduodenectomy. CONCLUSIONS: Within 2 years, 1 in 5 patients without any other pancreatic disease will develop NODM after partial pancreatectomy for PCLs. Those with advanced age, metabolic syndrome features, and/or cardiovascular disease may benefit from preoperative counseling and intensive postoperative monitoring, education, and treatment for diabetes mellitus.

PhenoDEF: a corpus for annotating sentences with information of phenotype definitions in biomedical literature.

BACKGROUND: Adverse events induced by drug-drug interactions are a major concern in the United States. Current research is moving toward using electronic health record (EHR) data, including for adverse drug events discovery. One of the first steps in EHR-based studies is to define a phenotype for establishing a cohort of patients. However, phenotype definitions are not readily available for all phenotypes. One of the first steps of developing automated text mining tools is building a corpus. Therefore, this study aimed to develop annotation guidelines and a gold standard corpus to facilitate building future automated approaches for mining phenotype definitions contained in the literature. Furthermore, our aim is to improve the understanding of how these published phenotype definitions are presented in the literature and how we annotate them for future text mining tasks. RESULTS: Two annotators manually annotated the corpus on a sentence-level for the presence of evidence for phenotype definitions. Three major categories (inclusion, intermediate, and exclusion) with a total of ten dimensions were proposed characterizing major contextual patterns and cues for presenting phenotype definitions in published literature. The developed annotation guidelines were used to annotate the corpus that contained 3971 sentences: 1923 out of 3971 (48.4%) for the inclusion category, 1851 out of 3971 (46.6%) for the intermediate category, and 2273 out of 3971 (57.2%) for exclusion category. The highest number of annotated sentences was 1449 out of 3971 (36.5%) for the "Biomedical & Procedure" dimension. The lowest number of annotated sentences was 49 out of 3971 (1.2%) for "The use of NLP". The overall percent inter-annotator agreement was 97.8%. Percent and Kappa statistics also showed high inter-annotator agreement across all dimensions. CONCLUSIONS: The corpus and annotation guidelines can serve as a foundational informatics approach for annotating and mining phenotype definitions in literature, and can be used later for text mining applications.

Colorectal Cancer Risk Is Impacted by Sex and Type of Surgery After Bariatric Surgery.

PURPOSE: Sex differences exist in the associations between obesity and the risk of colorectal cancer (CRC). However, limited data exist on how sex affects CRC risk after bariatric surgery. MATERIALS AND METHODS: This retrospective cohort study used the 2012-2020 MarketScan database. We employed a propensity-score-matched analysis and precise coding to define CRC in this nationwide US study. Adjusted hazards ratio (HR) assessed CRC risk ≥ 6 months. In a restricted analysis, logistic regression with adjusted odds ratios (OR) examined CRC risk ≥ 3 years. RESULTS: Our sample included 327,734 controls with severe obesity and 88,630 patients with Roux-en-Y gastric bypass (RYGB) or sleeve gastrectomy (VSG). The odds of cessation of diabetes mellitus medications, a surrogate for diabetes remission, were higher post-surgery vs. controls, especially in RYGB and males. In females, CRC risk decreased post-RYGB compared to controls (HR = 0.40, 95%CI: 0.18-0.87, p = 0.02). However, VSG was not associated with lower CRC risk in females. Paradoxically, in males compared to controls, CRC risk trended toward an almost significant increase, especially after 3 years or more from surgery (OR = 2.18, 95%CI: 0.97-4.89, p = 0.06). Males had a higher risk of CRC, particularly rectosigmoid cancer, than females after bariatric surgery (HR = 2.69, 95% CI: 1.35-5.38, p < 0.001). Furthermore, diabetes remission was not associated with a lower CRC risk post-surgery. CONCLUSION: Our data suggest an increased risk of CRC in males compared to females after bariatric surgery. Compared to controls, there was a decrease in CRC risk in females' post-RYGB but not VSG. Mechanistic studies are needed to explain these differences.