Genetic Predisposition to Coronary Artery Disease in Type 2 Diabetes Mellitus

This work was supported by the European Union Framework Programme 7 (FP7/2007-2013) for the Innovative Medicine Initiative (IMI) under grant agreement n° IMI/115006 (the SUMMIT [Surrogate Markers for Micro- and Macro-Vascular Hard End Points for Innovative Diabetes Tools] consortium); Aarno Koskelo Foundation; Academy of Finland (no. 263401; no. 2676882); American Heart Association (13SDG14330006); AstraZeneca; AtheroSysMed (Systems medicine of coronary heart disease and stroke); British Heart Foundation Centre of Research Excellence at Oxford; ERC269045-Gene Target T2D grant; Estonian Research Council (IUT20-60, PUT1660 and PUT1665P); Estonian Center of Genomics/Roadmap II (project No. 2014-2020.4.01.16-0125); European Union (no. 692145; no. 633589; no. 313010; LSHM-CT-2007-037273; no. 201668; 2014-2020.4.01.15-0012;QLG1-CT-2002-00896; EU/QLRT-2001-01254; QLG2-CT-2002-01254 HEALTH-F2-2013-601456); Finnish Foundation for Cardiovascular research; Gentransmed - Centre of Excellence for Genomics and Translational Medicine; German Ministry of Education and Research (no. 01ZX1313A-K); Helsinki University Central Hospital special government funds (TYH7215, TKK2012005, TYH2012209, TYH2014312); Juvenile Diabetes Research Foundation (JDRF, 2-SRA-2014-276-Q-R); National Institute of Diabetes and Digestive and Kidney diseases (NIDDK, 5R01DK106236; U01-DK066134; U01-DK105535; R01DK101478); National Heart, Lung and Blood Institute (NLHBI, R01HL103866); National Institute for Health Research (NIHR); Personalized diagnostics and treatment of high risk coronary artery disease patients (RiskyCAD; 305739); Sigrid Juselius Foundation; Finnish Academy (no. 269517); Finnish Foundation for Cardiovascular Research; Foundation for Strategic Research and Stockholm County Council (560283; 592229); Juho Vainio Foundation; Knut and Alice Wallenberg Foundation; Ministry for Higher Education; Strategic Cardiovascular and Diabetes Programmes of Karolinska Institutet and Stockholm County Council; Swedish Foundation for Strategic Research (SSF; ICA08-0047); Swedish Heart-Lung Foundation; Swedish Research Council (project 8691; 2015-02558; 2016-00598; M-2005-1112 and 2009-2298); Torsten and Ragnar Söderberg Foundation; W.W. Smith Charitable Trust (H1201); Wellcome Trust Institutional strategic support fund; Yrjö Jahnsson Foundation. Publisher Copyright: © 2020 Lippincott Williams and Wilkins. All rights reserved.Background: Coronary artery disease (CAD) is accelerated in subjects with type 2 diabetes mellitus (T2D). Methods: To test whether this reflects differential genetic influences on CAD risk in subjects with T2D, we performed a systematic assessment of genetic overlap between CAD and T2D in 66 643 subjects (27 708 with CAD and 24 259 with T2D). Variants showing apparent association with CAD in stratified analyses or evidence of interaction were evaluated in a further 117 787 subjects (16 694 with CAD and 11 537 with T2D). Results: None of the previously characterized CAD loci was found to have specific effects on CAD in T2D individuals, and a genome-wide interaction analysis found no new variants for CAD that could be considered T2D specific. When we considered the overall genetic correlations between CAD and its risk factors, we found no substantial differences in these relationships by T2D background. Conclusions: This study found no evidence that the genetic architecture of CAD differs in those with T2D compared with those without T2D.Peer reviewe

Skillful Multi‐Month Predictions of Ecosystem Stressors in the Surface and Subsurface Ocean

Abstract Anthropogenic carbon emissions and associated climate change are driving rapid warming, acidification, and deoxygenation in the ocean, which increasingly stress marine ecosystems. On top of long‐term trends, short term variability of marine stressors can have major implications for marine ecosystems and their management. As such, there is a growing need for predictions of marine ecosystem stressors on monthly, seasonal, and multi‐month timescales. Previous studies have demonstrated the ability to make reliable predictions of the surface ocean physical and biogeochemical state months to years in advance, but few studies have investigated forecast skill of multiple stressors simultaneously or assessed the forecast skill below the surface. Here, we use the Community Earth System Model (CESM) Seasonal to Multiyear Large Ensemble (SMYLE) along with novel observation‐based biogeochemical and physical products to quantify the predictive skill of dissolved inorganic carbon (DIC), dissolved oxygen, and temperature in the surface and subsurface ocean. CESM SMYLE demonstrates high physical and biogeochemical predictive skill multiple months in advance in key oceanic regions and frequently outperforms persistence forecasts. We find up to 10 months of skillful forecasts, with particularly high skill in the Northeast Pacific (Gulf of Alaska and California Current Large Marine Ecosystems) for temperature, surface DIC, and subsurface oxygen. Our findings suggest that dynamical marine ecosystem prediction could support actionable advice for decision making

National Sleep Foundation’s sleep time duration recommendations:methodology and results summary

Objective: The objective was to conduct a scientifically rigorous update to the National Sleep Foundation’s sleep duration recommendations. Methods: The National Sleep Foundation convened an 18-member multidisciplinary expert panel, representing 12 stakeholder organizations, to evaluate scientific literature concerning sleep duration recommendations. We determined expert recommendations for sufficient sleep durations across the lifespan using the RAND/UCLA Appropriateness Method. Results: The panel agreed that, for healthy individuals with normal sleep, the appropriate sleep duration for newborns is between 14 and 17 hours, infants between 12 and 15 hours, toddlers between 11 and 14 hours, preschoolers between 10 and 13 hours, and school-aged children between 9 and 11 hours. For teenagers, 8 to 10 hours was considered appropriate, 7 to 9 hours for young adults and adults, and 7 to 8 hours of sleep for older adults. Conclusions: Sufficient sleep duration requirements vary across the lifespan and fromperson to person. The recommendations reported here represent guidelines for healthy individuals and those not suffering froma sleep disorder. Sleep durations outside the recommended range may be appropriate, but deviating far from thenormal range is rare. Individuals who habitually sleep outside the normal range may be exhibiting signs or symptoms of serious health problems or, if done volitionally,may be compromising their health and well-being

Genetic Predisposition to Coronary Artery Disease in Type 2 Diabetes Mellitus

BACKGROUND: Coronary artery disease (CAD) is accelerated in subjects with type 2 diabetes mellitus (T2D). METHODS: To test whether this reflects differential genetic influences on CAD risk in subjects with T2D, we performed a systematic assessment of genetic overlap between CAD and T2D in 66 643 subjects (27 708 with CAD and 24 259 with T2D). Variants showing apparent association with CAD in stratified analyses or evidence of interaction were evaluated in a further 117 787 subjects (16 694 with CAD and 11 537 with T2D). RESULTS: None of the previously characterized CAD loci was found to have specific effects on CAD in T2D individuals, and a genome-wide interaction analysis found no new variants for CAD that could be considered T2D specific. When we considered the overall genetic correlations between CAD and its risk factors, we found no substantial differences in these relationships by T2D background. CONCLUSIONS: This study found no evidence that the genetic architecture of CAD differs in those with T2D compared with those without T2D.Peer reviewe