Proteomics for prediction of disease progression and response to therapy in diabetic kidney disease

The past decade has resulted in multiple new findings of potential proteomic biomarkers of diabetic kidney disease (DKD). Many of these biomarkers reflect an important role in the (patho)physiology and biological processes of DKD. Situations in which proteomics could be applied in clinical practice include the identification of individuals at risk of progressive kidney disease and those who would respond well to treatment, in order to tailor therapy for those at highest risk. However, while many proteomic biomarkers have been discovered, and even found to be predictive, most lack rigorous external validation in sufficiently powered studies with renal endpoints. Moreover, studies assessing short-term changes in the proteome for therapy-monitoring purposes are lacking. Collaborations between academia and industry and enhanced interactions with regulatory agencies are needed to design new, sufficiently powered studies to implement proteomics in clinical practice

Clinical review: Biomarkers of acute kidney injury: where are we now?

The recognition that acute kidney injury (AKI) is a significant independent risk factor for morbidity and mortality has resulted in a substantial number of publications over the past 5 years or more. In no small part these have, to a degree, highlighted the inadequacy of conventional markers of renal insufficiency in the acute setting. Much effort has been invested in the identification of early, specific AKI markers in order to aid early diagnosis of AKI and hopefully improve outcome. The search for a 'biomarker' of AKI has seen early promise replaced by a degree of pessimism due to the lack of a clear candidate molecule and variability of results. We outline the major studies described to date as well as discuss potential reasons for the discrepancies observed and suggest that evolution of the field may result in success with ultimately an improvement in patient outcomes

Verification, Analytical Validation, and Clinical Validation (V3): The Foundation of Determining Fit-for-Purpose for Biometric Monitoring Technologies (BioMeTs)

Digital medicine is an interdisciplinary field, drawing together stakeholders with expertize in engineering, manufacturing, clinical science, data science, biostatistics, regulatory science, ethics, patient advocacy, and healthcare policy, to name a few. Although this diversity is undoubtedly valuable, it can lead to confusion regarding terminology and best practices. There are many instances, as we detail in this paper, where a single term is used by different groups to mean different things, as well as cases where multiple terms are used to describe essentially the same concept. Our intent is to clarify core terminology and best practices for the evaluation of Biometric Monitoring Technologies (BioMeTs), without unnecessarily introducing new terms. We focus on the evaluation of BioMeTs as fit-for-purpose for use in clinical trials. However, our intent is for this framework to be instructional to all users of digital measurement tools, regardless of setting or intended use. We propose and describe a three-component framework intended to provide a foundational evaluation framework for BioMeTs. This framework includes (1) verification, (2) analytical validation, and (3) clinical validation. We aim for this common vocabulary to enable more effective communication and collaboration, generate a common and meaningful evidence base for BioMeTs, and improve the accessibility of the digital medicine field

Urinary Kininogen-1 and Retinol binding protein-4 respond to Acute Kidney Injury: Predictors of patient prognosis?

Implementation of therapy for acute kidney injury (AKI) depends on successful prediction of individual patient prognosis. Clinical markers as serum creatinine (sCr) have limitations in sensitivity and early response. The aim of the study was to identify novel molecules in urine which show altered levels in response to AKI and investigate their value as predictors of recovery. Changes in the urinary proteome were here investigated in a cohort of 88 subjects (55 AKI patients and 33 healthy donors) grouped in discovery and validation independent cohorts. Patients'urine was collected at three time points: within the first 48 h after diagnosis(T1), at 7 days of follow-up(T2) and at discharge of Nephrology(T3). Differential gel electrophoresis was performed and data were confirmed by Western blot (WB), liquid chromatography/mass spectrometry (LC-MS/MS) and enzyme-linked immunosorbent assay (ELISA). Retinol binding protein 4 (RBP4) and kininogen-1 (KNG1) were found significantly altered following AKI. RBP4 increased at T1, and progressively decreased towards normalization. Maintained decrease was observed for KNG1 from T1. Individual patient response along time revealed RBP4 responds to recovery earlier than sCr. In conclusion, KNG1 and RBP4 respond to AKI. By monitoring RBP4, patient's recovery can be anticipated pointing to a role of RBP4 in prognosis evaluation.Funding: from Instituto de Salud Carlos III: FIS PI11/01401, PI13/01873, FIS IF08/3667-1, CP09/00229, PI13/00047, PI10/00624, ISCIII-RETIC REDinREN RD012/0021. FEDER funds, Comunidad de Madrid/CIFRA S2010/BMD-2378, Programa Intensificación Actividad Investigadora (ISCIII/Agencia Laín-Entralgo/CM) to AO, IDCSalud (3371/002) and Fundación Conchita Rábago de Jiménez Díaz, Proteomic Facility from Universidad Complutense de Madrid-Fundación Parque Científico de Madrid (UCM-FPCM), Spain, a member of ProteoRed-ISCIII Network member of ProteoRed- ISCIII Networ

Design and Validation of a Wearable, Continuous, and Non-Invasive Hydration Monitor that uses Ultrasonic Pulses to Detect Changes in Tissue Hydration Status

Chronic dehydration is an endemic problem for many population groups. Current methods of monitoring hydration status are invasive, time consuming, cannot be performed while exercising, and require lab resources. A proposed solution is a wearable, continuous, and non-invasive device that uses harm-free ultrasonic pulses to detect changes in tissue hydration status over time. Customer and engineering requirements were defined and used to guide the design process. Literature reviews were performed to identify essential information on dehydration, assess current methods, discover state of the art devices, and describe ultrasonic theory. Market research was performed to identify athletes as the target population group. An adjustable elastic nylon bicep band prototype was manufactured and the integration of more advanced components was proposed. The theoretical signal processing method used to detect hydration status was validated through initial tests with a prototype electrical system composed of a Teensy 3.1 board, two 18 kHz piezoceramic disc elements, and an Arduino/LabVIEW interface. Tests with aluminum, rubber, and sponge materials were performed to compare the signal response to propagation through materials with different acoustic properties and water contents. Finally, tests performed with dehydrated bovine muscle tissue revealed a statistically significant difference between hydrated and dehydrated tissue, a promising indication for future device refinement

Computational Models for Transplant Biomarker Discovery.

Translational medicine offers a rich promise for improved diagnostics and drug discovery for biomedical research in the field of transplantation, where continued unmet diagnostic and therapeutic needs persist. Current advent of genomics and proteomics profiling called "omics" provides new resources to develop novel biomarkers for clinical routine. Establishing such a marker system heavily depends on appropriate applications of computational algorithms and software, which are basically based on mathematical theories and models. Understanding these theories would help to apply appropriate algorithms to ensure biomarker systems successful. Here, we review the key advances in theories and mathematical models relevant to transplant biomarker developments. Advantages and limitations inherent inside these models are discussed. The principles of key -computational approaches for selecting efficiently the best subset of biomarkers from high--dimensional omics data are highlighted. Prediction models are also introduced, and the integration of multi-microarray data is also discussed. Appreciating these key advances would help to accelerate the development of clinically reliable biomarker systems

Consumption of Pomegranate Juice Attenuates Exercise-Induced Oxidative Stress, Blood Pressure and Urinary Cortisol/Cortisone Ratio in Human Adults

Oxidative stress is exacerbated in overweight and obese individuals after acute exercise compared with their non-obese counterparts. Antioxidant supplementation of the diet may be one intervention to reduce exercise-induced oxidative stress in this vulnerable population. The aim of this study was to investigate whether polyphenol-rich pomegranate juice attenuates post-exercise oxidative stress and contributors to oxidative stress (glucocorticoids) and blood pressure in healthy overweight subjects. Healthy male and female subjects participated in a randomized placebo controlled parallel pilot-study (mean BMI: 26.7 ± 6.6 kg/m2). Two groups of participants (n=12) received either 500 ml/day of pomegranate juice (containing 1685 mg GAE) or placebo (matched for total energy). Participants completed two standardized 30 min treadmill tests (50% Wmax) at baseline and after one week of the intervention. Exercise-induced lipid peroxidation (MDA) was significantly lower following pomegranate juice consumption compared with placebo (31.2 ± 10.6 to 26.5 ± 9.8 MDA μmole/day) (p=0.035). Urinary free cortisol was reduced from 179.4 ± 53.2 to 125.6 ± 43.5 nmole/24h which was significant (p=0.042). In addition, there was an increase in urinary free cortisone from 112.2 ± 40.4 to 187.6 ± 90.2 nmole/24 h (p=0.045), and a significant decrease in the urinary free cortisol/cortisone ratio (p=0.009) from 1.6 ± 1.1 to 0.67 ± 0.55 following one week of pomegranate juice intake. Pomegranate juice consumption was also found to decrease systolic blood pressure pre-exercise (136.7 ± 11.7 to 131.8 ± 8.8 mmHg (p=0.007), and post-exercise from 158.8 ± 15.8 to 148.1 ± 12.3 mmHg (p<0.01) and diastolic blood pressure (86.3 ± 10.6 to 82.5 ± 6.8 mmHg (p=0.04) and 103.1 ± 12.5 to 93.9 ± 11.5 mmHg (p=0.001), pre and post exercise, respectively. Correlation between the change in cortisol/cortisone ratio with the effect on blood pressure showed a negative significant association post pomegranate juice intake (p=0.028 for systolic and p=0.008 for diastolic BP). There were no changes in lipid peroxidation or blood pressure following placebo treatment. In conclusion, these findings suggest that pomegranate juice consumption prior to an acute bout of moderate intensity exercise may help to alleviate exercise-induced oxidative stress, and lower blood pressure in the overweight and obese population