Metformin: A Promising Antidiabetic Medication for Cancer Treatment.

Metformin is a widely used drug in patients with type 2 diabetes mellitus. Metformin inhibits hepatic gluconeogenesis and increases glucose utilization in peripheral tissues. In recent years, several studies have shown that metformin is a potential therapeutic agent against cancer, alone or combined with other anticancer treatments. Metformin mainly activates the AMPK complex and regulates intracellular energy status, inhibiting the mitochondrial respiratory chain complex I and reducing the production of reactive oxygen species. Other anticancer targets of metformin are specific transcription factors inhibiting cell proliferation, promoting apoptosis and reducing drug resistance. In addition, metformin modulates tumor cells' response to anticancer treatments, favoring the activity of T cells. In diabetic patients, metformin reduces the occurrence of cancer and improves the prognosis and efficacy of anticancer treatments. In this review, we provided a comprehensive perspective of metformin as an anticancer drug.

The Potential Therapeutic Role of Metformin in Diabetic and Non-Diabetic Bone Impairment.

Metformin is a widely-used anti-diabetic drug in patients with type 2 diabetic mellitus (T2DM) due to its safety and efficacy in clinical. The classic effect of metformin on lowering blood glucose levels is to inhibit liver gluconeogenesis that reduces glucose production as well as increases peripheral glucose utilization. However, the factors such as hyperglycemia, insulin deficiency, reduced serum levels of insulin-like growth factor-1 (IGF-1) and osteocalcin, accumulation of advanced glycation end products (AGEs), especially in collagen, microangiopathy, and inflammation reduced bone quality in diabetic patients. However, hyperglycemia, insulin deficiency, reduced levels of insulin-like growth factor-1 (IGF-1) and osteocalcin in serum, accumulation of advanced glycation end products (AGEs) in collagen, microangiopathy, and inflammation, reduce bone quality in diabetic patients. Furthermore, the imbalance of AGE/RAGE results in bone fragility via attenuating osteogenesis. Thus, adequate glycemic control by medical intervention is necessary to prevent bone tissue alterations in diabetic patients. Metformin mainly activates adenosine 5' -monophosphate-activated protein kinase (AMPK), and inhibits mitochondrial respiratory chain complex I in bone metabolism. In addition, metformin increases the expression of transcription factor runt-related transcription factor2 (RUNX2) and Sirtuin protein to regulate related gene expression in bone formation. Until now, there are a lot of preclinical or clinical findings on the application of metformin to promote bone repair. Taken together, metformin is considered as a potential medication for adjuvant therapy in bone metabolic disorders further to its antidiabetic effect. Taken together, as a conventional hypoglycemia drug with multifaceted effects, metformin has been considered a potential adjuvant drug for the treatment of bone metabolic disorders.

Prospective Validation of a Rapid Host Gene Expression Test to Discriminate Bacterial From Viral Respiratory Infection.

Importance: Bacterial and viral causes of acute respiratory illness (ARI) are difficult to clinically distinguish, resulting in the inappropriate use of antibacterial therapy. The use of a host gene expression-based test that is able to discriminate bacterial from viral infection in less than 1 hour may improve care and antimicrobial stewardship. Objective: To validate the host response bacterial/viral (HR-B/V) test and assess its ability to accurately differentiate bacterial from viral infection among patients with ARI. Design, Setting, and Participants: This prospective multicenter diagnostic study enrolled 755 children and adults with febrile ARI of 7 or fewer days' duration from 10 US emergency departments. Participants were enrolled from October 3, 2014, to September 1, 2019, followed by additional enrollment of patients with COVID-19 from March 20 to December 3, 2020. Clinical adjudication of enrolled participants identified 616 individuals as having bacterial or viral infection. The primary analysis cohort included 334 participants with high-confidence reference adjudications (based on adjudicator concordance and the presence of an identified pathogen confirmed by microbiological testing). A secondary analysis of the entire cohort of 616 participants included cases with low-confidence reference adjudications (based on adjudicator discordance or the absence of an identified pathogen in microbiological testing). Thirty-three participants with COVID-19 were included post hoc. Interventions: The HR-B/V test quantified the expression of 45 host messenger RNAs in approximately 45 minutes to derive a probability of bacterial infection. Main Outcomes and Measures: Performance characteristics for the HR-B/V test compared with clinical adjudication were reported as either bacterial or viral infection or categorized into 4 likelihood groups (viral very likely [probability score <0.19], viral likely [probability score of 0.19-0.40], bacterial likely [probability score of 0.41-0.73], and bacterial very likely [probability score >0.73]) and compared with procalcitonin measurement. Results: Among 755 enrolled participants, the median age was 26 years (IQR, 16-52 years); 360 participants (47.7%) were female, and 395 (52.3%) were male. A total of 13 participants (1.7%) were American Indian, 13 (1.7%) were Asian, 368 (48.7%) were Black, 131 (17.4%) were Hispanic, 3 (0.4%) were Native Hawaiian or Pacific Islander, 297 (39.3%) were White, and 60 (7.9%) were of unspecified race and/or ethnicity. In the primary analysis involving 334 participants, the HR-B/V test had sensitivity of 89.8% (95% CI, 77.8%-96.2%), specificity of 82.1% (95% CI, 77.4%-86.6%), and a negative predictive value (NPV) of 97.9% (95% CI, 95.3%-99.1%) for bacterial infection. In comparison, the sensitivity of procalcitonin measurement was 28.6% (95% CI, 16.2%-40.9%; P < .001), the specificity was 87.0% (95% CI, 82.7%-90.7%; P = .006), and the NPV was 87.6% (95% CI, 85.5%-89.5%; P < .001). When stratified into likelihood groups, the HR-B/V test had an NPV of 98.9% (95% CI, 96.1%-100%) for bacterial infection in the viral very likely group and a positive predictive value of 63.4% (95% CI, 47.2%-77.9%) for bacterial infection in the bacterial very likely group. The HR-B/V test correctly identified 30 of 33 participants (90.9%) with acute COVID-19 as having a viral infection. Conclusions and Relevance: In this study, the HR-B/V test accurately discriminated bacterial from viral infection among patients with febrile ARI and was superior to procalcitonin measurement. The findings suggest that an accurate point-of-need host response test with high NPV may offer an opportunity to improve antibiotic stewardship and patient outcomes.

Inhibition of the deubiquitinating enzyme USP47 as a novel targeted therapy for hematologic malignancies expressing mutant EZH2.

Activating mutations in EZH2, the catalytic component of PRC2, promote cell proliferation, tumorigenesis, and metastasis through enzymatic or non-enzymatic activity. The EZH2-Y641 gain-of-function mutation is one of the most significant in diffuse large B-cell lymphoma (DLBCL). Although EZH2 kinase inhibitors, such as EPZ-6438, provide clinical benefit, certain cancer cells are resistant to the enzymatic inhibition of EZH2 because of the inability to functionally target mutant EZH2, or because of cells' dependence on the non-histone methyltransferase activity of EZH2. Consequently, destroying mutant EZH2 protein may be more effective in targeting EZH2 mutant cancers that are dependent on the non-catalytic activity of EZH2. Here, using extensive selectivity profiling, combined with genetic and animal model studies, we identified USP47 as a novel regulator of mutant EZH2. Inhibition of USP47 would be anticipated to block the function of mutated EZH2 through induction of EZH2 degradation by promoting its ubiquitination. Moreover, targeting of USP47 leads to death of mutant EZH2-positive cells in vitro and in vivo. Taken together, we propose targeting USP47 with a small molecule inhibitor as a novel potential therapy for DLBCL and other hematologic malignancies characterized by mutant EZH2 expression.

Novel polymer-based system for intrauterine delivery of everolimus for anti-cancer applications.

Non-surgical treatment options for low-grade endometrial cancer and precancerous lesions are a critical unmet need for women who wish to preserve fertility or are unable to undergo hysterectomy. The PI3K/AKT/mTOR pathway is frequently activated in endometrial cancers and has been associated with resistance to endocrine therapy, making it a compelling target for early stage disease. Oral everolimus, an inhibitor against mTORC1, has shown clinical benefit in advanced or recurrent disease but has severe adverse effects that may lead to treatment interruption or dose reduction. To overcome this, we developed a polymer-based intrauterine delivery system to achieve persistent, local delivery of everolimus without systemic exposure. In vivo studies, using a rat model, showed that a poly(propylene fumarate)-based rod loaded with everolimus achieved everolimus delivery to the endometrium with levels similar to oral administration, but with limited systemic exposure and up to 84 days of release. Biological activity of everolimus delivered with this system was confirmed, measured by reduced lumen epithelial cell height and PI3K pathway biomarkers. This study shows a promising new delivery approach for anti-cancer drugs for non-surgical treatment of low-grade endometrial cancer.

Genome Sequence Analysis of the Fungal Pathogen Fusarium graminearum Using Oxford Nanopore Technology.

Fusarium graminearum is a plant pathogen of global importance which causes not only significant yield loss but also crop spoilage due to mycotoxins that render grain unsafe for human or livestock consumption. Although the full genome of several F. graminearum isolates from different parts of the world have been sequenced, there are no similar studies of isolates originating from China. The current study sought to address this by sequencing the F. graminearum isolate FG-12, which was isolated from the roots of maize seedlings exhibiting typical symptoms of blight growing in the Gansu province, China, using Oxford Nanopore Technology (ONT). The FG-12 isolate was found to have a 35.9 Mb genome comprised of five scaffolds corresponding to the four chromosomes and mitochondrial DNA of the F. graminearum type strain, PH-1. The genome was found to contain an approximately 2.23% repetitive sequence and encode 12,470 predicted genes. Additional bioinformatic analysis identified 437 genes that were predicted to be secreted effectors, one of which was confirmed to trigger a hypersensitive responses (HR) in the leaves of Nicotiana benthamiana during transient expression experiments utilizing agro-infiltration. The F. graminearum FG-12 genome sequence and annotation data produced in the current study provide an extremely useful resource for both intra- and inter-species comparative analyses as well as for gene functional studies, and could greatly advance our understanding of this important plant pathogen.

Network pharmacology study on the mechanism of Qiangzhifang in the treatment of panic disorder.

BACKGROUND: Panic disorder (PD) is a kind of mental illness characterized by the symptom of recurring panic attacks. Qiangzhifang (QZF) is a novel decoction developed by Professor Zhaojun Yan based on a unique system of syndrome differentiation and clinical experience. It has achieved remarkable results after long-term clinical practice, but its mechanism of action is still unclear. This study aims to use network pharmacology and molecular docking to explore the mechanism of QZF in the treatment of PD. METHODS: We used the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), a literature search, and Encyclopedia of Traditional Chinese Medicine (ETCM) to find active ingredients and targets of QZF. We searched for PD targets in GeneCards, Online Mendelian Inheritance in Man (OMIM), the Comparative Toxicogenomics Database (CTD), and DrugBank. We established a PD target database, constructed a protein-protein interaction (PPI) network, and performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis in order to screen possible pathways of action and analyze the mechanism. RESULTS: This study identified 84 effective components of QZF, 691 potential targets, 357 PD targets, and 97 intersectional targets. Enrichment analysis using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) showed that QZF was associated with 118 biological processes (BPs), 18 cellular components (CCs), 35 molecular functions (MFs) [false discovery rate (FDR) <0.01], and 62 pathways (FDR <0.01). QZF mainly acts on its targets AKT1, FOS, and APP through active ingredients such as quercetin, ß-sitosterol, 4-(4'-hydroxybenzyloxy)benzyl methyl ether, harmine, 1,7-dimethoxyxanthone, and 1-hydroxy-3,7-dimethoxyxanthone to regulate serotonin, gamma-aminobutyric acid (GABA), cyclic adenosine monophosphate (cAMP), and other signal pathways to treat PD. CONCLUSIONS: Through network pharmacology and molecular docking technology, we predicted the possible mechanism of QZF in the treatment of PD, revealed the interaction targets and potential value of QZF, and provided a basis for its clinical application.

The protective impact of Trans-Cinnamaldehyde (TCA) against the IL-1b induced inflammation in in vitro osteoarthritis model by regulating PI3K/AKT pathways.

INTRODUCTION: Osteoarthritis (OA) is a severe joint degeneration disease in elderly people described by the advanced degradation of articular cartilage, which ultimately leads to chronic pain. Trans-cinnamaldehyde (TCA) exerted its anti-inflammatory function in numerous disease syndromes; however, its role in the pathogenesis of OA remains unknown. The current research aimed to explore the potential protective impact of TCA in the progression of osteoarthritis in vitro. MATERIAL AND METHODS: Human knee articular chondrocytes were treated with 10 ng/ml IL-1b alone for 24 h or in a combination in a pretreatment with TCA at different concentrations (2, 5, 10 µg/mL, 24 h). The viability and cell apoptosis were determined by CCK-8 assay and flow cytometry methods. The protein levels of IL-8, PGE2, and TNF-a and the levels of phosphorylated AKT and PI3K were evaluated using ELISA assay. Moreover, RT-qPCR was used to measure the relative mRNA expression of MMP-13, iNOS, COX-2, and ADAMTS-5 in IL-1b-induced chondrocytes. RESULTS: Our results revealed that the treatment with TCA had no effect on chondrocytes' proliferation and apoptosis. Moreover, the protein levels of IL-8, TNF-a, and PGE2 were considerably reduced in IL-1b-induced chondrocytes treated with different concentrations of TCA. Furthermore, the mRNA expression of MMP-13, iNOS, COX-2, and ADAMTS-5 and the phosphorylation of AKT and PI3K were markedly reduced in IL-1b-induced chondrocytes with the increase in the concentration of TCA. CONCLUSIONS: Trans-cinnamaldehyde inhibited the inflammation induced by IL-1b in chondrocytes through the PI3K/AKT pathway, which suggests that TCA might serve as a potential therapeutic agent for osteoarthritis treatment.

De novo variants in the Helicase-C domain of CHD8 are associated with severe phenotypes including autism, language disability and overgrowth.

CHD8, which encodes Chromodomain helicase DNA-binding protein 8, is one of a few well-established Autism Spectrum Disorder (ASD) genes. Over 60 mutations have been reported in subjects with variable phenotypes, but little is known concerning genotype-phenotype correlations. We have identified four novel de novo mutations in Chinese subjects: two nonsense variants (c.3562C>T/p.Arg1188X, c.2065C>A/p.Glu689X), a splice site variant (c.4818-1G>A) and a missense variant (c.3502T>A/p.Tyr1168Asn). Three of these were identified from a 445-member ASD cohort by ASD gene panel sequencing of the 96 subjects who remained negative after molecular testing for copy number variation, Rett syndrome, FragileX and tuberous sclerosis complex (TSC). The fourth (p.Glu689X) was detected separately by diagnostic trio exome sequencing. We used diagnostic instruments and a comprehensive review of phenotypes, including prenatal and postnatal growth parameters, developmental milestones, and dysmorphic features to compare these four subjects. In addition to autism, they also presented with prenatal onset macrocephaly, intellectual disability, overgrowth during puberty, sleep disorder, and dysmorphic features, including broad forehead with prominent supraorbital ridges, flat nasal bridge, telecanthus and large ears. For further comparison, we compiled a comprehensive list of CHD8 variants from the literature and databases, which revealed constitutive and somatic truncating variants in the HELIC (Helicase-C) domain in ASD and in cancer patients, respectively, but not in the general population. Furthermore, HELIC domain mutations were associated with a severe phenotype defined by a greater number of clinical features, lower verbal IQ, and a prominent, consistent pattern of overgrowth as measured by weight, height and head circumference. Overall, this study adds to the ASD-associated loss-of-function mutations in CHD8 and highlights the clinical importance of the HELIC domain of CHD8.

Variable selection methods for identifying predictor interactions in data with repeatedly measured binary outcomes.

INTRODUCTION: Identifying predictors of patient outcomes evaluated over time may require modeling interactions among variables while addressing within-subject correlation. Generalized linear mixed models (GLMMs) and generalized estimating equations (GEEs) address within-subject correlation, but identifying interactions can be difficult if not hypothesized a priori. We evaluate the performance of several variable selection approaches for clustered binary outcomes to provide guidance for choosing between the methods. METHODS: We conducted simulations comparing stepwise selection, penalized GLMM, boosted GLMM, and boosted GEE for variable selection considering main effects and two-way interactions in data with repeatedly measured binary outcomes and evaluate a two-stage approach to reduce bias and error in parameter estimates. We compared these approaches in real data applications: hypothermia during surgery and treatment response in lupus nephritis. RESULTS: Penalized and boosted approaches recovered correct predictors and interactions more frequently than stepwise selection. Penalized GLMM recovered correct predictors more often than boosting, but included many spurious predictors. Boosted GLMM yielded parsimonious models and identified correct predictors well at large sample and effect sizes, but required excessive computation time. Boosted GEE was computationally efficient and selected relatively parsimonious models, offering a compromise between computation and parsimony. The two-stage approach reduced the bias and error in regression parameters in all approaches. CONCLUSION: Penalized and boosted approaches are effective for variable selection in data with clustered binary outcomes. The two-stage approach reduces bias and error and should be applied regardless of method. We provide guidance for choosing the most appropriate method in real applications.

An Ectopic Chemokine Expression Model for Testing Macrophage Recruitment In Vivo.

Zebrafish are widely used in basic and biomedical research. Many zebrafish transgenic lines are currently available to label various types of cells. Owing to the transparent embryonic body of zebrafish, it is convenient for us to study the effect of one chemokine on the behavior of a certain type of cells in vivo. Here we provided a workflow to investigate the function of a chemokine on macrophage migration in vivo. We constructed a tissue-specific overexpression plasmid to overexpress IL-34 and injected the plasmid into one-cell stage transgenic fish embryos whose macrophages were specifically labeled by a fluorescent protein. We then used whole mount fluorescent in situ hybridization and immunostaining to detect the pattern of the chemokine expression and the number or location of macrophages. The injected WT embryos were raised to generate a stable transgenic line. Finally, we used confocal live imaging to directly observe macrophage behavior in the stable transgenic fish to study the function of IL-34 on macrophages in vivo.

[Biocatalytic strategies in producing ginsenoside by glycosidase-a review].

Panax ginseng is a traditional Chinese medicine with significant pharmaceutical effects and wide application. Through orientational modification and transformation of ginsenoside glycosyl, rare ginsenosides with high antitumor activities can be generated. Traditional chemical methods cannot be applied in clinic. because of extremely complex preparation technologies and very high cost Transformations using microorganisms and their enzymatic systems provide the most feasible methods for solving the main problems. At present, the key problems in enzymatic synthesis of ginsenosides include low specific enzyme activities, identity of enzymes involved in the enzymatic synthesis, and their catalytic mechanisms, as well as nonsystematic studies on structural bioinformatics; specificity of enzymatic hydrolysis for saponin glycosyl has been rarely studied. Many reviews have been reported on glycosidase molecular recognition, immobilization, and biotransformation in ionic liquids (ILs), whereas ginsenoside transformation and application have not been systematically studied. To evaluate theoretical and applied studies on ginsenoside-oriented biotransformation, by reviewing the latest developments in related fields and evaluating the widely applied biocatalytic strategy, this review aims to evaluate the ginsenoside-oriented transformation method with improved product specificity, increased biocatalytic efficiency, and industrial application prospect based on the designed transformations of enzyme and solvent engineering of ILs. Therefore, useful theoretical and experimental evidence can be obtained for the development of ginsenoside anticancer drugs, large-scale preparation, and clinical applications in cancer therapy.

Screening and identification of novel specific markers of breast cancer stem cells.

Breast cancer is the leading cause of death among women worldwide. Until recent years, triple negative breast cancer could be divided into 6 types according to different biomarkers with the development of sequence and microarray technology. However, these results rarely have therapeutic impact and still lack validation with the string criteria of clinical studies. Therefore, the present study aimed to screen novel markers of breast cancer stem cells and to verify the specificity in vitro and in vivo. In the present study, screening for phages specifically binding to breast cancer stem cells was performed, positive phage DNAs were extracted, and polypeptides were synthesized and labeled with FITC. The specificity of the polypeptides was identified in vitro and in vivo. Breast cancer stem cells were cultured and identified by flow cytometry. A phage random-peptide library was amplified and screened by culturing with breast cancer cells and breast cancer stem cells. The positive phage was identified by ELISA, and positive phage DNA was extracted. The DNA pellet was isolated and sent for external sequencing with the primer -96 gIII. Based on the sequencing results, a polypeptide was synthesized and labeled with FITC. The specificity to breast cancer stem cells was identified in vivo and vitro. Following three rounds of screening, the phage was enriched ~200-fold. Immunofluorescence demonstrated that two randomly selected phage clones, B8 and A3, had specific affinity to breast cancer stem cells. The results of the present study indicated that phage polypeptides that specifically bind to breast cancer stem cells were successfully screened through stem cell enrichment and phage display technology, which may be beneficial for targeted therapy and further study of breast cancer stem cells.

Interval Estimation for Age-Adjusted Rate Ratios Using Bayesian Convolution Model.

Spatial correlation raises challenges in estimating confidence intervals for region specific event rates and rate ratios between geographic units that are nested. Methods have been proposed to incorporate spatial correlation by assuming various distributions for the structure of autocorrelation patterns. However, the derivation of these statistics based on approximation may have to condition on the distributional assumption underlying the data generating process, which may not hold for certain situations. This paper explores the feasibility of utilizing a Bayesian convolution model (BCM), which includes an uncorrelated heterogeneity (UH) and a conditional autoregression (CAR) component to accommodate both uncorrelated and correlated spatial heterogeneity, to estimate the 95% confidence intervals for age-adjusted rate ratios among geographic regions with existing spatial correlations. A simulation study is conducted and a BCM method is applied to two cancer incidence datasets to calculate age-adjusted rate/ratio for the counties in the State of Kentucky relative to the entire state. In comparison to three existing methods, without and with spatial correlation, the Bayesian convolution model-based estimation provides moderate shrinkage effect for the point estimates based on the neighbor structure across regions and produces a wider interval due to the inclusion of uncertainty in the spatial autocorrelation parameters. The overall spatial pattern of region incidence rate from BCM approach appears to be like the direct estimates and other methods for both datasets, even though "smoothing" occurs in some local regions. The Bayesian Convolution Model allows flexibility in the specification of risk components and can improve the accuracy of interval estimates of age-adjusted rate ratios among geographical regions as it considers spatial correlation.

Ectopically Expressed IL-34 Can Efficiently Induce Macrophage Migration to the Liver in Zebrafish.

Interleukin-34 (IL-34) is a known cytokine that plays an important role in the survival, proliferation, and differentiation of macrophages. In previous studies, IL-34 can induce macrophage migration through syndecan-1 or focal adhesion kinase and extracellular signal-related kinase 1 and 2 pathway. These studies mainly focused on in vitro experiments, but the effect of IL-34 on macrophage migration in vivo is less understood. In our study, we artificially induced macrophage, but not neutrophil, enrichment in the skin or liver by overexpressing IL-34 in epidermal cells or hepatocytes in zebrafish. Live imaging showed that the enrichment of macrophages in the liver is due to the direct attraction of macrophages by IL-34. Our results demonstrated that ectopically expressed IL-34 can induce macrophage migration to liver in vivo.

Socioeconomic Status and Morbidity Rate Inequality in China: Based on NHSS and CHARLS Data.

Previous studies have shown there are no consistent and robust associations between socioeconomic status and morbidity rates. This study focuses on the relationship between the socioeconomic status and the morbidity rates in China, which helps to add new evidence for the fragmentary relationship between socioeconomic status and morbidity rates. The National Health Services Survey (NHSS) and China Health and Retirement Longitudinal Study (CHARLS) data are used to examine whether the association holds in both all-age cohorts and in older only cohorts. Three morbidity outcomes (two-week incidence rate, the prevalence of chronic diseases, and the number of sick days per thousand people) and two socioeconomic status indicators (income and education) are mainly examined. The results indicate that there are quadratic relationships between income per capita and morbidities. This non-linear correlation is similar to the patterns in European countries. Meanwhile, there is no association between education years and the morbidity in China, i.e., either two-week incidence rate or prevalence rate of chronic diseases has no statistically significant relationship with the education level in China.

The Return of Actionable Variants Empirical (RAVE) Study, a Mayo Clinic Genomic Medicine Implementation Study: Design and Initial Results.

OBJECTIVES: To identify clinically actionable genetic variants from targeted sequencing of 68 disease-related genes, estimate their penetrance, and assess the impact of disclosing results to participants and providers. PATIENTS AND METHODS: The Return of Actionable Variants Empirical (RAVE) Study investigates outcomes following the return of pathogenic/likely pathogenic (P/LP) variants in 68 disease-related genes. The study was initiated in December 2016 and is ongoing. Targeted sequencing was performed in 2533 individuals with hyperlipidemia or colon polyps. The electronic health records (EHRs) of participants carrying P/LP variants in 36 cardiovascular disease (CVD) genes were manually reviewed to ascertain the presence of relevant traits. Clinical outcomes, health care utilization, family communication, and ethical and psychosocial implications of disclosure of genomic results are being assessed by surveys, telephone interviews, and EHR review. RESULTS: Of 29,208 variants in the 68 genes, 1915 were rare (frequency <1%) and putatively functional, and 102 of these (60 in 36 CVD genes) were labeled P/LP based on the American College of Medical Genetics and Genomics framework. Manual review of the EHRs of participants (n=73 with P/LP variants in CVD genes) revealed that 33 had the expected trait(s); however, only 6 of 45 participants with non-familial hypercholesterolemia (FH) P/LP variants had the expected traits. CONCLUSION: Expected traits were present in 13% of participants with P/LP variants in non-FH CVD genes, suggesting low penetrance; this estimate may change with additional testing performed as part of the clinical evaluation. Ongoing analyses of the RAVE Study will inform best practices for genomic medicine.