Curcumin Supplementation and Human Disease: A Scoping Review of Clinical Trials.

Medicinal properties of turmeric (Curcuma longa L.), a plant used for centuries as an anti-inflammatory, are attributed to its polyphenolic curcuminoids, where curcumin predominates. Although "curcumin" supplements are a top-selling botanical with promising pre-clinical effects, questions remain regarding biological activity in humans. To address this, a scoping review was conducted to assess human clinical trials reporting oral curcumin effects on disease outcomes. Eight databases were searched using established guidelines, yielding 389 citations (from 9528 initial) that met inclusion criteria. Half focused on obesity-associated metabolic disorders (29%) or musculoskeletal disorders (17%), where inflammation is a key driver, and beneficial effects on clinical outcomes and/or biomarkers were reported for most citations (75%) in studies that were primarily double-blind, randomized, and placebo-controlled trials (77%, D-RCT). Citations for the next most studied disease categories (neurocognitive [11%] or gastrointestinal disorders [10%], or cancer [9%]), were far fewer in number and yielded mixed results depending on study quality and condition studied. Although additional research is needed, including systematic evaluation of diverse curcumin formulations and doses in larger D-RCT studies, the preponderance of current evidence for several highly studied diseases (e.g., metabolic syndrome, osteoarthritis), which are also clinically common, are suggestive of clinical benefits.

Dietary Supplement Use in Women Diagnosed with Breast Cancer.

BACKGROUND: Vitamins, minerals, and natural product (NP)-derived dietary supplements are commonly used among women with breast cancer, where interactions with treatments and the disease are possible, emphasizing the importance for health care providers to be aware of supplement use. OBJECTIVES: The study aimed to investigate current vitamin/mineral (VM) and NP supplement use among those diagnosed with breast cancer, including usage based on tumor type or concurrent breast cancer treatments and primary information sources for specific supplements. METHODS: Social media recruiting to complete an online questionnaire self-reporting current VM and NP use and breast cancer diagnosis and treatment information primarily attracted US participants. Analyses, including multivariate logistic regression, were performed on 1271 women who self-reported breast cancer diagnosis and completed the survey. RESULTS: Most participants reported current VM (89.5%) and NP (67.7%) use, with 46.5% (VM) and 26.7% (NP) using at least 3 products concurrently. Top-reported (>15% prevalence) products were vitamin D, calcium, multivitamin, and vitamin C for VM and probiotics, turmeric, fish oil/omega-3 fatty acids, melatonin, and cannabis for NP. Overall, VM or NP use was higher among those with hormone receptor-positive tumors. Although overall NP use did not differ according to current breast cancer treatments, VM use was significantly less common among those currently undergoing chemotherapy or radiation, but higher with current endocrine therapy. Among current chemotherapy users, specific VM and NP supplements with possible adverse effects were still used by 23% of respondents. Medical providers were the primary information source for VM, whereas NP information sources were more varied. CONCLUSIONS: Because women diagnosed with breast cancer commonly reported concurrent use of multiple VM and NP supplements, including those with known or underexplored risks (or benefits) in breast cancer, it is important for health care providers to inquire about and facilitate discussions regarding supplement use in this population.

A Microbial Signature Identifies Advanced Fibrosis in Patients with Chronic Liver Disease Mainly Due to NAFLD.

The presence of advanced fibrosis is an important measure of the severity of chronic liver disease. Prior works that have examined the gut microbiome as a novel biomarker for advanced fibrosis have only examined patients with nonalcoholic fatty liver disease. Therefore, our goal was to examine the gut microbiome across varying etiologies of liver disease to create a predictive model for liver fibrosis based upon a microbial signature. Stool samples were obtained from patients with chronic liver disease (n = 50) undergoing FibroScan (ultrasound elastography) at the VA Greater Los Angeles Healthcare System. Healthy control patients (n = 25) were also recruited as a reference population. Fecal samples underwent 16S ribosomal RNA sequencing. Using differentially abundant microbes, a random forest classifier model was created to distinguish advanced fibrosis from mild/moderate fibrosis. The findings were then validated in a separate cohort of chronic liver disease patients (n = 37). Etiologies for liver disease included non-alcoholic liver disease (58.0%), hepatitis C (26.0%), hepatitis B (10.0%), and alcohol (6.0%). Microbiome composition was distinct in liver patients with advanced fibrosis compared to those with minimal fibrosis and healthy controls (p = 0.003). In multivariate negative binomial modeling, 26 bacterial taxa were differentially abundant in patients with advanced fibrosis as compared to those with minimal/moderate fibrosis (q-value < 0.05). A random forests classifier based on these taxa had an AUROC of 0.90 to predict advanced fibrosis. Prevotella copri, which was enriched in patients with advanced fibrosis, was the most strongly predictive microbe in the classifier. The classifier had an AUROC of 0.82 for advanced fibrosis in the validation cohort and Prevotella copri remained the strongest predictive microbe for advanced fibrosis. There is a distinct microbial signature for patients with advanced fibrosis independent of liver disease etiology and other comorbidities. These results suggest that microbial profiles can be used as a non-invasive marker for advanced fibrosis and support the hypothesis that microbes and their metabolites contribute to hepatic fibrosis.

Metformin alters the duodenal microbiome and decreases the incidence of pancreatic ductal adenocarcinoma promoted by diet-induced obesity.

Pancreatic ductal adenocarcinoma (PDAC)'s growing incidence has been linked to the rise in obesity and type 2 diabetes mellitus. In previous work, we have shown that metformin can prevent the increased incidence of PDAC in a KrasG12D mouse model subjected to a diet high in fat and calories (HFCD). One potential way that metformin can affect the host is through alterations in the gut microbiome. Therefore, we investigated microbial associations with PDAC development and metformin use in the same mouse model. Lox-Stop-Lox Kras G12D/+ (LSL-Kras G12D/+); p48-Cre (KC) mice were given control diet, HFCD, or HFCD with 5 mg/mL metformin in drinking water for 3 mo. At the end of the 3 mo, 16S rRNA sequencing was performed to characterize microbiome composition of duodenal mucosal, duodenal luminal, and cecal luminal samples. KC mice on an HFCD demonstrated depletion of intact acini and formation of advanced pancreatic intraepithelial neoplasia. This effect was completely abrogated by metformin treatment. HFCD was associated with significant changes in microbial composition and diversity in the duodenal mucosa and lumen, much of which was prevented by metformin. In particular, Clostridium sensu stricto was negatively correlated with percent intact acini and seemed to be inhibited by the addition of metformin while on an HFCD. Administration of metformin eliminated PDAC formation in KC mice. This change was associated with significant microbial changes in both the mucosal and luminal microbiome of the duodenum. This suggests that the microbiome may be a potential mediator of the chemopreventive effects of metformin.NEW & NOTEWORTHY Pancreatic ductal adenocarcinoma (PDAC)'s growing incidence has been linked to the rise in obesity and type 2 diabetes mellitus. Administration of metformin eliminated PDAC formation in KC mice with diet-induced obesity. This change was associated with significant microbial changes in both the mucosal and luminal microbiome of the duodenum. This suggests that the microbiome may be a potential mediator of the chemopreventive effects of metformin.

Machine Learning-based Development and Validation of a Scoring System for Screening High-Risk Esophageal Varices.

BACKGROUND & AIMS: Many patients with cirrhosis who undergo esophagogastroduodenoscopy (EGD) screening for esophageal varices (EVs) are found to have no or only small EVs. Endoscopic screening for EVs is therefore a potentially deferrable procedure that increases patient risk and healthcare cost. We developed and validated a scoring system, based on readily-available data, to reliably identify patients with EVs that need treatment. METHODS: We collected data from 238 patients with cirrhosis undergoing screening EGD from January 2016 through December 2017 at 3 separate hospitals in Los Angeles (training cohort). We abstracted data on patient sex, age, race/ethnicity, platelet counts, and levels of hemoglobin, serum sodium, aspartate aminotransferase, alanine aminotransferase, total bilirubin, international normalized ratio, albumin, urea nitrogen, and creatinine. We also included etiology of cirrhosis, presence of ascites, and presence of hepatic encephalopathy. We used a random forest algorithm to identify factors significantly associated with the presence of EVs and varices needing treatment (VNT) and calculated area under the receiver operating characteristic curve (AUROC). We called the resulting formula the EVendo score. We tested the accuracy of EVendo in a prospective study of 109 patients undergoing screening EGDs at the same medical centers from January 2018 through December 2018 (validation cohort). RESULTS: We developed an algorithm that identified patients with EVs and VNT based on international normalized ratio, level of aspartate aminotransferase, platelet counts, urea nitrogen, hemoglobin, and presence of ascites. The EVendo score identified patients with EVs in the training set with an AUROC of 0.84, patients with EVs in the validation set with and AUROC of 0.82, and EVs in patients with cirrhosis Child-Turcotte-Pugh class A (n = 235) with an AUROC of 0.81. The score identified patients with VNT in the training set with an AUROC of 0.74, VNT in the validation set with and AUROC of 0.75, and VNT in patients with cirrhosis Child-Turcotte-Pugh class A with and AUROC of 0.75. An EVendo score below 3.90 would have spared 30.5% patients from EGDs, missing only 2.8% of VNT. The same cutoff would have spared 40.0% of patients with Child-Turcotte-Pugh class A cirrhosis from EGDs, missing only 1.1% of VNT. CONCLUSIONS: We algorithmically developed a formula, called the EVendo score, that can be used to predict EVs and VNT based on readily available data in patients with cirrhosis. This score could help patients at low risk for VNT avoid unnecessary EGDs.