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Choline is an essential nutrient for some mammals; it is used for membrane and neurotransmitter synthesis. We analyzed plasma samples, obtained periodically during TPN therapy, for choline concentration. Malnourished patients referred to a nutrition support service were prospectively assigned to be treated with daily infusions of amino acids with, and without, supplemental daily infusions of lipid emulsion for a period of 1 wk. After the first week, all subjects received intravenous lipid, and most were offered enteral food supplements. Initial plasma choline concentrations in the 25 malnourished patients were significantly lower than those measured in plasma samples from 23 hospitalized patients known to be eating well (6.5 ± 0.6 vs 9.7 ± 0.7 nmol/ml; mean ± SEM; p <0.001). During the first week of TPN therapy, plasma choline concentrations in the lipid-restricted group tended to decrease (from 7.3 ± 1.0 to 4.7 ± 0.5 nmol/ml; mean ± SEM; p <0.05), while in the lipid-supplemented group plasma choline tended to increase (from 5.6 ± 0.5 to 6.2 ± 0.7 nmol/ml; mean ± SEM; p <0.05). Plasma choline concentration increased during wk 2-4, when all patients were treated with lipid emulsions, and some were offered enteral foods. We conclude that malnourished humans who eat no choline have diminished stores of plasma (and possibly tissue) choline. [ABSTRACT FROM AUTHOR]

Aims Though statin therapy is known to slow coronary atherosclerosis progression and reduce cardiovascular (CV) events, significant CV risk still remains. In the REDUCE-IT study, icosapent ethyl (IPE) added to statin therapy reduced initial CV events by 25% and total CV events by 30%, but its effects on coronary atherosclerosis progression have not yet been fully investigated. Therefore, this study is to determine whether IPE 4 g/day will result in a greater change from baseline in plaque volume measured by serial multidetector computed tomography than placebo in statin-treated patients. Methods and results EVAPORATE is a randomized, double-blind, placebo-controlled trial. Patients had to have coronary atherosclerosis by coronary computed tomographic angiography (CCTA) (≥1 angiographic stenoses with ≥20% narrowing), on stable statin therapy with low-density lipoprotein cholesterol levels 40–115 mg/dL, and persistently high triglyceride levels (135–499 mg/dL). Patients underwent an interim scan at 9 months and were followed for an additional 9 months with CCTA at 0, 9, and 18 months. Here, we present the protocol-specified interim efficacy results. A total of 80 patients were enrolled, with 67 completing the 9-month visit and having interpretable CCTA at baseline and at 9 months (age = 57 ± 6 years, male = 36, 63%). At the 9-month interim analysis, there was no significant change in low attenuation plaque (LAP) between active and placebo groups (74% vs. 94%, P  = 0.469). However, there was slowing of total non-calcified plaque (sum of LAP, fibrofatty, and fibrous plaque) (35% vs. 43%, P  = 0.010), total plaque (non-calcified + calcified plaque) (15% vs. 26%, P  = 0.0004), fibrous plaque (17% vs. 40%, P  = 0.011), and calcified plaque (−1% vs. 9%, P  = 0.001), after adjustment by baseline plaque, age, sex, diabetes, baseline triglyceride levels, and statin use. Conclusion EVAPORATE is the first study using CCTA to evaluate the effects of IPE as an adjunct to statin therapy on atherosclerotic plaque characteristics in a high-risk CV population with persistently high triglyceride levels. It provides important mechanistic data in regards to the reduction in CV events in the REDUCE-IT clinical trial. ClinicalTrials. govIdentifier NCT029226027. [ABSTRACT FROM AUTHOR]

Background: Numerous studies demonstrate associations between serum concentrations of 25-hydroxyvitamin D (25[OH]D) and a variety of common disorders, including musculoskeletal, metabolic, cardiovascular, malignant, autoimmune, and infectious diseases. Although a causal link between serum 25(OH)D concentrations and many disorders has not been clearly established, these associations have led to widespread supplementation with vitamin D and increased laboratory testing for 25(OH)D in the general population. The benefit-risk ratio of this increase in vitamin D use is not clear, and the optimal vitamin D intake and the role of testing for 25(OH)D for disease prevention remain uncertain., Objective: To develop clinical guidelines for the use of vitamin D (cholecalciferol [vitamin D3] or ergocalciferol [vitamin D2]) to lower the risk of disease in individuals without established indications for vitamin D treatment or 25(OH)D testing., Methods: A multidisciplinary panel of clinical experts, along with experts in guideline methodology and systematic literature review, identified and prioritized 14 clinically relevant questions related to the use of vitamin D and 25(OH)D testing to lower the risk of disease. The panel prioritized randomized placebo-controlled trials in general populations (without an established indication for vitamin D treatment or 25[OH]D testing), evaluating the effects of empiric vitamin D administration throughout the lifespan, as well as in select conditions (pregnancy and prediabetes). The panel defined "empiric supplementation" as vitamin D intake that (a) exceeds the Dietary Reference Intakes (DRI) and (b) is implemented without testing for 25(OH)D. Systematic reviews queried electronic databases for publications related to these 14 clinical questions. The Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) methodology was used to assess the certainty of evidence and guide recommendations. The approach incorporated perspectives from a patient representative and considered patient values, costs and resources required, acceptability and feasibility, and impact on health equity of the proposed recommendations. The process to develop this clinical guideline did not use a risk assessment framework and was not designed to replace current DRI for vitamin D., Results: The panel suggests empiric vitamin D supplementation for children and adolescents aged 1 to 18 years to prevent nutritional rickets and because of its potential to lower the risk of respiratory tract infections; for those aged 75 years and older because of its potential to lower the risk of mortality; for those who are pregnant because of its potential to lower the risk of preeclampsia, intra-uterine mortality, preterm birth, small-for-gestational-age birth, and neonatal mortality; and for those with high-risk prediabetes because of its potential to reduce progression to diabetes. Because the vitamin D doses in the included clinical trials varied considerably and many trial participants were allowed to continue their own vitamin D-containing supplements, the optimal doses for empiric vitamin D supplementation remain unclear for the populations considered. For nonpregnant people older than 50 years for whom vitamin D is indicated, the panel suggests supplementation via daily administration of vitamin D, rather than intermittent use of high doses. The panel suggests against empiric vitamin D supplementation above the current DRI to lower the risk of disease in healthy adults younger than 75 years. No clinical trial evidence was found to support routine screening for 25(OH)D in the general population, nor in those with obesity or dark complexion, and there was no clear evidence defining the optimal target level of 25(OH)D required for disease prevention in the populations considered; thus, the panel suggests against routine 25(OH)D testing in all populations considered. The panel judged that, in most situations, empiric vitamin D supplementation is inexpensive, feasible, acceptable to both healthy individuals and health care professionals, and has no negative effect on health equity., Conclusion: The panel suggests empiric vitamin D for those aged 1 to 18 years and adults over 75 years of age, those who are pregnant, and those with high-risk prediabetes. Due to the scarcity of natural food sources rich in vitamin D, empiric supplementation can be achieved through a combination of fortified foods and supplements that contain vitamin D. Based on the absence of supportive clinical trial evidence, the panel suggests against routine 25(OH)D testing in the absence of established indications. These recommendations are not meant to replace the current DRIs for vitamin D, nor do they apply to people with established indications for vitamin D treatment or 25(OH)D testing. Further research is needed to determine optimal 25(OH)D levels for specific health benefits., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Endocrine Society. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com. See the journal About page for additional terms.)

Distinguishing between alcohol-associated hepatitis (AH) and alcohol-associated cirrhosis (AC) remains a diagnostic challenge. In this study, we used machine learning with transcriptomics and proteomics data from liver tissue and peripheral mononuclear blood cells (PBMCs) to classify patients with alcohol-associated liver disease. The conditions in the study were AH, AC, and healthy controls. We processed 98 PBMC RNAseq samples, 55 PBMC proteomic samples, 48 liver RNAseq samples, and 53 liver proteomic samples. First, we built separate classification and feature selection pipelines for transcriptomics and proteomics data. The liver tissue models were validated in independent liver tissue datasets. Next, we built integrated gene and protein expression models that allowed us to identify combined gene-protein biomarker panels. For liver tissue, we attained 90% nested-cross validation accuracy in our dataset and 82% accuracy in the independent validation dataset using transcriptomic data. We attained 100% nested-cross validation accuracy in our dataset and 61% accuracy in the independent validation dataset using proteomic data. For PBMCs, we attained 83% and 89% accuracy with transcriptomic and proteomic data, respectively. The integration of the two data types resulted in improved classification accuracy for PBMCs, but not liver tissue. We also identified the following gene-protein matches within the gene-protein biomarker panels: CLEC4M-CLC4M, GSTA1-GSTA2 for liver tissue and SELENBP1-SBP1 for PBMCs. In this study, machine learning models had high classification accuracy for both transcriptomics and proteomics data, across liver tissue and PBMCs. The integration of transcriptomics and proteomics into a multi-omics model yielded improvement in classification accuracy for the PBMC data. The set of integrated gene-protein biomarkers for PBMCs show promise toward developing a liquid biopsy for alcohol-associated liver disease., Competing Interests: The authors have declared that no competing interests exist., (Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.)

Background & Aims: Liver disease carries significant healthcare burden and frequently requires a combination of blood tests, imaging, and invasive liver biopsy to diagnose. Distinguishing between inflammatory liver diseases, which may have similar clinical presentations, is particularly challenging. In this study, we implemented a machine learning pipeline for the identification of diagnostic gene expression biomarkers across several alcohol-associated and non-alcohol-associated liver diseases, using either liver tissue or blood-based samples., Methods: We collected peripheral blood mononuclear cells (PBMCs) and liver tissue samples from participants with alcohol-associated hepatitis (AH), alcohol-associated cirrhosis (AC), non-alcohol-associated fatty liver disease, chronic HCV infection, and healthy controls. We performed RNA sequencing (RNA-seq) on 137 PBMC samples and 67 liver tissue samples. Using gene expression data, we implemented a machine learning feature selection and classification pipeline to identify diagnostic biomarkers which distinguish between the liver disease groups. The liver tissue results were validated using a public independent RNA-seq dataset. The biomarkers were computationally validated for biological relevance using pathway analysis tools., Results: Utilizing liver tissue RNA-seq data, we distinguished between AH, AC, and healthy conditions with overall accuracies of 90% in our dataset, and 82% in the independent dataset, with 33 genes. Distinguishing 4 liver conditions and healthy controls yielded 91% overall accuracy in our liver tissue dataset with 39 genes, and 75% overall accuracy in our PBMC dataset with 75 genes., Conclusions: Our machine learning pipeline was effective at identifying a small set of diagnostic gene biomarkers and classifying several liver diseases using RNA-seq data from liver tissue and PBMCs. The methodologies implemented and genes identified in this study may facilitate future efforts toward a liquid biopsy diagnostic for liver diseases., Lay Summary: Distinguishing between inflammatory liver diseases without multiple tests can be challenging due to their clinically similar characteristics. To lay the groundwork for the development of a non-invasive blood-based diagnostic across a range of liver diseases, we compared samples from participants with alcohol-associated hepatitis, alcohol-associated cirrhosis, chronic hepatitis C infection, and non-alcohol-associated fatty liver disease. We used a machine learning computational approach to demonstrate that gene expression data generated from either liver tissue or blood samples can be used to discover a small set of gene biomarkers for effective diagnosis of these liver diseases., Competing Interests: T.R.M. has received grant/research support from 10.13039/100006483AbbVie, 10.13039/100005564Gilead, Genfit, and 10.13039/100004334Merck. The remaining authors have nothing to disclose. Please refer to the accompanying ICMJE disclosure forms for further details., (© 2022 The Author(s).)

Introduction: Cost of generic medications has risen more in the past few years than any other time in history. While medical insurance covers much of these costs, health care professionals can better provide medications that have the longest duration of action when compared to placebo - treated controls. This will save health care costs and improve prescribing accuracy., Methods: Papers in PubMed were identified with keywords placebo. The study must be at least 2 years in length to evaluate the change in A1c over time. The primary endpoint was time to A1c neutrality (return of A1c to baseline at a maximum dose of single oral agent). A medication would be considered at neutrality if the 95% CI crossed baseline. Time to neutrality was averaged for each medication within the class and each summarized for class effect., Results: Effective therapy for the DPP-4 and sulfonylurea classes of medications are 3-4 years as compared to a 5-year time to A1c neutrality for metformin usage. In comparison, the projected time to A1c neutrality was approximately 6-8 years for rosiglitazone and pioglitazone. While only a few studies have been published in the SGLT-2 class of medication, the time to A1c neutrality was also 6-8 years with Canagliflozin and full dosage of Empagliflozin., Conclusion: Metformin appears to have a 5-year duration of effect before the A1c returns to baseline. The sulfonylureas and DPP-4 inhibitors class of medications have one of the shortest durability which ranges between 3.3 to 4.4 years. In contrast, the SGLT-2 class of medication and the TZD class of medications has a projected time to A1c neutrality from 6-8 years. Diabetic duration of therapy as compared to placebo should be listed with those medications tested so the provider can choose wisely.

Aim: To compare mortality risks associated with known diabetic patients to hyperglycemic non-diabetic patients., Methods: PubMed data base was searched for patients with sepsis, bacteremia, mortality and diabetes. Articles that also identified new onset hyperglycemia (NOH) (fasting blood glucose > 125 mg/dL or random blood glucose > 199 mg/dL) were identified and reviewed. Nine studies were evaluated with regards to hyperglycemia and hospital mortality and five of the nine were summarized with regards to intensive care unit (ICU) mortality., Results: Historically hyperglycemia has been believed to be equally harmful in known diabetic patients and non-diabetics patients admitted to the hospital. Unexpectedly, having a history of diabetes when admitted to the hospital was associated with a reduced risk of hospital mortality. Approximately 17% of patients admitted to hospital have NOH and 24% have diabetes mellitus. Hospital mortality was significantly increased in all nine studies of patients with NOH as compared to known diabetic patients (26.7% ± 3.4% vs 12.5% ± 3.4%, P < 0.05; analysis of variance). Unadjusted ICU mortality was evaluated in five studies and was more than doubled for those patients with NOH as compared to known diabetic patients (25.3% ± 3.3% vs 12.8% ± 2.6%, P < 0.05) despite having similar blood glucose concentrations. Most importantly, having NOH was associated with an increased ICU and a 2.7-fold increase in hospital mortality when compared to hyperglycemic diabetic patients. The mortality benefit of being diabetic is unclear but may have to do with adaptation to hyperglycemia over time. Having a history of diabetes mellitus and prior episodes of hyperglycemia may provide time for the immune system to adapt to hyperglycemia and result in a reduced mortality risk. Understanding why diabetic patients have a lower than expected hospital mortality rate even with bacteremia or acute respiratory distress syndrome needs further study., Conclusion: Having hyperglycemia without a history of previous diabetes mellitus is a major independent risk factor for ICU and hospital mortality.

Objective: To ascertain whether troglitazone, independent of control of diabetes, increases low-density lipoprotein (LDL) particle size., Methods: We administered 600 mg of troglitazone (a peroxisome proliferator-activated receptor-gamma agonist) daily for 8 weeks to 10 patients with type 2 diabetes (8 of whom completed the study). Then troglitazone therapy was discontinued, and alternative medication for diabetic control was used for another 4 weeks. The LDL, very-low-density lipoprotein (VLDL), and high-density lipoprotein (HDL) concentrations and subpopulations, as well as blood glucose and hemoglobin A1c (HbA1c), were determined at weeks 0, 4, 8, and 12 and analyzed statistically., Results: Small, dense LDL cholesterol is commonly seen in patients with diabetes and is thought to be associated with an increased risk for coronary artery disease. After both 4 and 8 weeks of troglitazone therapy, control of diabetes was significantly improved (mean HbA1c values at baseline, week 4, and week 8 were 8.0 +/- 0.7%, 7.4 +/- 0.5%, and 7.0 +/- 0.7%, respectively; P<0.05). HbA1c (6.5 +/- 0.6% at 12 weeks) and blood glucose levels (126 +/- 19 mg/dL at 8 weeks versus 145 +/- 9 mg/dL at 12 weeks) were not significantly different 4 weeks after troglitazone therapy was discontinued. Troglitazone treatment increased the large LDL particle at 4 and 8 weeks, a change that significantly (P<0.05) enlarged the LDL particle size (20.5 +/- 0.3 nm, 21.2 +/- 0.3 nm, and 21.3 +/- 0.2 nm at baseline, week 4, and week 8, respectively). After 8 weeks of troglitazone therapy, VLDL triglycerides were reduced (195 +/- 37 mg/dL versus 136 +/- 28 mg/dL; P<0.05) and HDL was increased (31.6 +/- 2.4 mg/dL versus 35.5 +/- 2.9 mg/dL; P<0.05). This greater HDL value was due to an increase in the small HDL particles. A decrease in the larger VLDL particles (V5 and V6) resulted in a reduction in the mean VLDL particle size (59 +/- 3 nm versus 46 +/- 2 nm; P<0.05). Despite the fact that control of diabetes remained significantly improved after troglitazone therapy was discontinued, the LDL particle size decreased to the baseline value. This change was due to a reduction in the large LDL cholesterol particle (L3)., Conclusion: This study shows that troglitazone therapy increases LDL particle size, reduces VLDL particle size, and increases small HDL particles. These changes may lower the risk for coronary artery disease.