Anthropometric Measures and Risk of Cardiovascular Disease: Is there an Opportunity for Non-Traditional Anthropometric Assessment? A Review

Background: Several anthropometric measurements are used to assess cardiovascular risk and progress during clinical treatment. Most commonly used anthropometric measurements include total body weight and body mass index (BMI), with several other simple anthropometric measures typically underused in clinical practice. Herein, we review the evidence on the relationship between different anthropometric measurements and cardiovascular risk in patients with and without cardiovascular disease (CVD). Methods: Data for this review were identified by searches in PubMed, the Web of Science, Google Scholar, and references from relevant articles by using appropriate and related terms. The last search was performed on June 22, 2022. Articles published in English and Spanish were reviewed and included, if appropriate. We included studies detailing the relationship between skinfolds thickness, waist-to-hip ratio (WHR) and Conicity index with cardiovascular risk in adults with/without CVD. Results: In patients from the general population, elevated subscapular and triceps skinfolds showed a positive relationship with the development of hypertension, diabetes mellitus, hypercholesterolemia, cardiovascular mortality, and all-cause mortality. A higher subscapular skinfold was also associated with increased risk of coronary artery disease and stroke. A higher WHR, as well as other less common anthropometric measurements such as the Conicity index, was associated with an increased risk of myocardial infarction, incident CVD, major adverse cardiovascular events, and mortality in both patients with and without previous CVD. Conclusions: Non-traditional anthropometric measurements including skinfolds and WHR seem to improve the prediction of cardiovascular risk in the general population, and recurrent events in patients with previous CVD. Use of additional anthropometric techniques according to an objective and standardized method, may aid cardiovascular risk stratification in patients from the general population and the evaluation of therapeutic interventions for patients with CVD

Combined proteome and transcriptome analyses for the discovery of urinary biomarkers for urothelial carcinoma

Background: Proteomic discovery of cancer biomarkers in body fluids is challenging because of their low abundance in a complex background. Altered gene expression in tumours may not reflect protein levels in body fluids. We have tested combining gene expression profiling of tumours with proteomic analysis of cancer cell line secretomes as a strategy to discover urinary biomarkers for bladder cancer. Methods: We used shotgun proteomics to identify proteins secreted by three bladder cancer cell lines. Secreted proteins with high mRNA levels in bladder tumours relative to normal urothelium were assayed by ELISA in urine samples from 642 patients. Results: Midkine and HAI-1 were significantly increased in bladder cancer patients, with the highest levels in invasive disease (area under the receiver operating characteristic curve 0.89 vs non-cancer). The urinary concentration of both proteins was too high to be explained by bladder cancer associated haematuria and most likely arises by direct tumour secretion. Conclusions: This ‘dual-omic’ strategy identified tumour secreted proteins whose urine concentrations are increased significantly by bladder cancer. Combined secretome-transcriptome analysis may be more useful than direct proteomic analysis of body fluids for biomarker discovery in both bladder cancer and other tumour type

Protein shedding in urothelial bladder cancer: Prognostic implications of soluble urinary EGFR and EpCAM

Background: Better biomarkers must be found to develop clinically useful urine tests for bladder cancer. Proteomics can be used to identify the proteins released by cancer cell lines and generate candidate markers for developing such tests. Methods: We used shotgun proteomics to identify proteins released into culture media by eight bladder cancer cell lines. These data were compared with protein expression data from the Human Protein Atlas. Epidermal growth factor receptor (EGFR) was identified as a candidate biomarker and measured by ELISA in urine from 60 noncancer control subjects and from 436 patients with bladder cancer and long-term clinical follow-up. Results: Bladder cancer cell lines shed soluble EGFR ectodomain. Soluble EGFR is also detectable in urine and is highly elevated in some patients with high-grade bladder cancer. Urinary EGFR is an independent indicator of poor bladder cancer-specific survival with a hazard ratio of 2.89 (95% CI 1.81-4.62, P<0.001). In multivariable models including both urinary EGFR and EpCAM, both biomarkers are predictive of bladder cancer-specific survival and have prognostic value over and above that provided by standard clinical observations. Conclusions: Measuring urinary EGFR and EpCAM may represent a simple and useful approach for fast-tracking the investigation and treatment of patients with the most aggressive bladder cancers