2nd International Consensus Report on Gaps & Opportunities for the Clinical Translation of Precision Diabetes Medicine

Precision medicine is part of the logical evolution of contemporary evidence-based medicine that seeks to reduce errors and optimize outcomes when making medical decisions and health recommendations. Diabetes affects hundreds of millions worldwide, many of whom will develop life-threatening complications and die prematurely. Precision medicine can potentially address this enormous problem by accounting for the heterogeneous etiology, clinical presentation, and pathogenesis of common forms of diabetes and risk of complications. This 2nd International Consensus Report on Precision Diabetes Medicine summarize the findings from a systematic evidence review across the key pillars of precision medicine (prevention, diagnosis, treatment, prognosis) in four recognized forms of diabetes (monogenic, gestational, type 1, type 2). These reviews address key questions about translation of precision medicine research into practice. Although not complete, owing to the vast literature on this topic, they revealed opportunities for the immediate or near-term clinical implementation of precision diabetes medicine; further, we expose important gaps in knowledge, focusing on the need to obtain new clinically relevant evidence. Gaps include the need for common standards for clinical readiness, including consideration of cost-effectiveness, health equity, predictive accuracy, liability, and accessibility. Key milestones are outlined for the broad clinical implementation of precision diabetes medicine

Association of N-terminal pro-brain natriuretic peptide with cognitive function and depression in elderly people with type 2 diabetes

<p>Background: Type 2 diabetes mellitus is associated with risk of congestive heart failure (CHF), cognitive dysfunction and depression. CHF itself is linked both to poor cognition and depression. The ventricular N-terminal pro-brain natriuretic peptide (NT-proBNP) is a marker of CHF, suggesting potential as a marker for cognitive impairment and/or depression. This was tested in the Edinburgh Type 2 Diabetes Study (ET2DS).</p> <p>Methodology and Principal Findings: Cross-sectional analysis of 1066 men and women aged 60–75 with type 2 diabetes. Results from seven neuropsychological tests were combined in a standardised general cognitive ability factor, ‘g’. A vocabulary-based test estimated pre-morbid cognitive ability. The Hospital Anxiety and Depression Scale (HADS) assessed possible depression. After adjustment for age and sex, raised plasma NT-proBNP was weakly associated with lower ‘g’ and higher depression scores (ß −0.09, 95% CI −0.13 to −0.03, p = 0.004 and ß 0.08, 95% CI 0.04 to 0.12, p<0.001, respectively). Comparing extreme quintiles of NT-proBNP, subjects in the highest quintile were more likely to have reduced cognitive ability (within the lowest tertile of ‘g’) and ‘possible’ depression (HADS depression ≥8) (OR 1.80; 95% CI: 1.20, 2.70; p = 0.005 and OR 2.18; 95% CI: 1.28, 3.71; p = 0.004, respectively). Associations persisted when pre-morbid ability was adjusted for, but as expected were no longer statistically significant following the adjustment for diabetes-related and vascular co-variates (β −0.02, 95% CI −0.07 to 0.03, p>0.05 for ‘g’; β 0.03, 95% CI −0.02 to 0.07, p>0.05 for depression scores).</p> <p>Conclusion: Raised plasma NT-proBNP was weakly but statistically significantly associated with poorer cognitive function and depression. The prospective phases of the ET2DS will help determine whether or not NT-proBNP can be considered a risk marker for subsequent cognitive impairment and incident depression and whether it provides additional information over and above traditional risk factors for these conditions.</p&gt

Aging effects on airflow dynamics and lung function in human bronchioles

Background and objective The mortality rate for patients requiring mechanical ventilation is about 35% and this rate increases to about 53% for the elderly. In general, with increasing age, the dynamic lung function and respiratory mechanics are compromised, and several experiments are being conducted to estimate these changes and understand the underlying mechanisms to better treat elderly patients. Materials and methods Human tracheobronchial (G1 ~ G9), bronchioles (G10 ~ G22) and alveolar sacs (G23) geometric models were developed based on reported anatomical dimensions for a 50 and an 80-year-old subject. The aged model was developed by altering the geometry and material properties of the model developed for the 50-year-old. Computational simulations using coupled fluid-solid analysis were performed for geometric models of bronchioles and alveolar sacs under mechanical ventilation to estimate the airflow and lung function characteristics. Findings The airway mechanical characteristics decreased with aging, specifically a 38% pressure drop was observed for the 80-year-old as compared to the 50-year-old. The shear stress on airway walls increased with aging and the highest shear stress was observed in the 80-year-old during inhalation. A 50% increase in peak strain was observed for the 80-year-old as compared to the 50-year-old during exhalation. The simulation results indicate that there is a 41% increase in lung compliance and a 35%-50% change in airway mechanical characteristics for the 80-year-old in comparison to the 50-year-old. Overall, the airway mechanical characteristics as well as lung function are compromised due to aging. Conclusion Our study demonstrates and quantifies the effects of aging on the airflow dynamics and lung capacity. These changes in the aging lung are important considerations for mechanical ventilation parameters in elderly patients. Realistic geometry and material properties need to be included in the computational models in future studies

Targeting metabolic health promotion to optimise maternal and offspring health

There is an increase in maternal metabolic burden due to the rise in pregnancies complicated by obesity, gestational diabetes, type 2 diabetes and polycystic ovary syndrome. Metabolic dysfunction during pregnancy is associated with increased risks of long-term morbidity and mortality for women and their offspring. Lifestyle interventions in pregnancy in women at risk of metabolic dysfunction have demonstrated short-term improvements such as reduced gestational weight gain and lowered risk of gestational diabetes. It is not known whether these interventions lead to sustained improvements in the metabolic health of the mother and baby. Pharmacological interventions have also shown benefits for the mother and baby in pregnancy, including improvements in glycaemic control, reduction in gestational weight gain and reduction in large for gestational age infants; however, there remains uncertainty over long-term outcomes for mother and child. Existing studies on interventions targeting metabolic health are limited to selected populations in the preconception and postpartum periods and lack follow-up beyond delivery of the intervention. The COVID-19 pandemic has refocused our attention on the effects of maternal metabolic ill-health that play a role in contributing to premature morbidity and mortality. There is an urgent need for strategies to accurately identify the growing number of women and offspring at risk of long-term adverse metabolic health. Strategies which focus on early identification and risk stratification using individualised risk scores in the pre and inter-conception periods must take priority if we are to target and improve the metabolic health of women and their offspring who are at highest risk