Periodontal complications of hyperglycemia/diabetes mellitus: Epidemiologic complexity and clinical challenge

This report provides a comprehensive overview of the adverse effects of hyperglycemia on the periodontium. It combines data from literature reviews of original data from two large, population‐based epidemiologic studies with comprehensive periodontal health assessment. Emphasis is placed on the exploration of hitherto sparsely reported effects of prediabetes and poorly controlled (uncontrolled) diabetes, in contrast to the umbrella term “diabetes.” This stems from the realization that it is not simply having a diagnosis of diabetes that may adversely affect periodontal health. Rather, it is the level (severity) of hyperglycemia that is the determining factor, not the case definition of the diagnosis of diabetes or the type of diabetes in question. Importantly, based on existing evidence this paper also attempts to estimate the improvements in periodontal probing depth and clinical attachment level that can be expected upon successful nonsurgical periodontal treatment in people with chronic periodontitis, with and without diabetes, respectively. This exploration includes the implentation of new systematic reviews and meta‐analyses that allow comparison of such intervention outcomes between hyperglycemic and normoglycemic subjects. Based on both existing literature and original analyses of population‐based studies, we try to answer questions such as: Is there a glycated hemoglobin concentration threshold for periodontitis risk? Does short‐term periodontal probing depth reduction and clinical attachment level gain after scaling and root planing depend on glycemic control in type 2 diabetes? Are short‐term scaling and root planing outcomes in people with hyperglycemia/diabetes inferior to those in people without diabetes? Do periodontitis patients with diabetes benefit more from the use of adjuvant antibiotics with nonsurgical periodontal treatment than people without diabetes? Does hyperglycemia lead to greater tooth loss in patients in long‐term post‐periodontal treatment maintenance programs? Throughout this review, we compare our new findings with previous data and report whether the results of these new analyses corroborate, or are in discord with, similar scientific reports in the literature. We also explore the potential role of dental health‐care professionals in helping patients control the risk factors that are identical for periodontitis and diabetes. Finally, we suggest various topics that still need exploration in future research.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/146293/1/prd12235.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146293/2/prd12235_am.pd

A Biomarker for Alzheimer’s Disease Based on Patterns of Regional Brain Atrophy

Introduction: It has been shown that Alzheimer’s disease (AD) is accompanied by marked structural brain changes that can be detected several years before clinical diagnosis via structural magnetic resonance (MR) imaging. In this study, we developed a structural MR-based biomarker for in vivo detection of AD using a supervised machine learning approach. Based on an individual’s pattern of brain atrophy a continuous AD score is assigned which measures the similarity with brain atrophy patterns seen in clinical cases of AD. Methods: The underlying statistical model was trained with MR scans of patients and healthy controls from the Alzheimer’s Disease Neuroimaging Initiative (ADNI-1 screening). Validation was performed within ADNI-1 and in an independent patient sample from the Open Access Series of Imaging Studies (OASIS-1). In addition, our analyses included data from a large general population sample of the Study of Health in Pomerania (SHIP-Trend). Results: Based on the proposed AD score we were able to differentiate patients from healthy controls in ADNI-1 and OASIS-1 with an accuracy of 89% (AUC = 95%) and 87% (AUC = 93%), respectively. Moreover, we found the AD score to be significantly associated with cognitive functioning as assessed by the Mini-Mental State Examination in the OASIS-1 sample after correcting for diagnosis, age, sex, age·sex, and total intracranial volume (Cohen’s f2 = 0.13). Additional analyses showed that the prediction accuracy of AD status based on both the AD score and the MMSE score is significantly higher than when using just one of them. In SHIP-Trend we found the AD score to be weakly but significantly associated with a test of verbal memory consisting of an immediate and a delayed word list recall (again after correcting for age, sex, age·sex, and total intracranial volume, Cohen’s f2 = 0.009). This association was mainly driven by the immediate recall performance. Discussion: In summary, our proposed biomarker well differentiated between patients and healthy controls in an independent test sample. It was associated with measures of cognitive functioning both in a patient sample and a general population sample. Our approach might be useful for defining robust MR-based biomarkers for other neurodegenerative diseases, too

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements