Effects of asenapine on depressive symptoms in patients with bipolar I disorder experiencing acute manic or mixed episodes: a post hoc analysis of two 3-week clinical trials

<p>Abstract</p> <p>Background</p> <p>Asenapine demonstrated superiority over placebo for mania in bipolar I disorder patients experiencing acute current manic or mixed episodes in 2 randomized, placebo-and olanzapine-controlled trials. We report the results of exploratory pooled post hoc analyses from these trials evaluating asenapine's effects on depressive symptoms in patients from these trials with significant baseline depressive symptoms.</p> <p>Methods</p> <p>In the original trials (A7501004 [NCT00159744], A7501005 [NCT00159796]), 977 patients were randomized to flexible-dose sublingual asenapine (10 mg twice daily on day 1; 5 or 10 mg twice daily thereafter), placebo, or oral olanzapine 5-20 mg once daily for 3 weeks. Three populations were defined using baseline depressive symptoms: (1) Montgomery-Asberg Depression Rating Scale (MADRS) total score ≥20 (n = 132); (2) Clinical Global Impression for Bipolar Disorder-Depression (CGI-BP-D) scale severity score ≥4 (n = 170); (3) diagnosis of mixed episodes (n = 302) by investigative site screening. For each population, asenapine and olanzapine were independently compared with placebo using least squares mean change from baseline on depressive symptom measures.</p> <p>Results</p> <p>Decreases in MADRS total score were statistically greater with asenapine versus placebo at days 7 and 21 in all populations; differences between olanzapine and placebo were not significant. Decreases in CGI-BP-D score were significantly greater with asenapine versus placebo at day 7 in all categories and day 21 in population 1; CGI-BP-D score reductions were significantly greater with olanzapine versus placebo at day 21 in population 1 and day 7 in populations 2 and 3.</p> <p>Conclusions</p> <p>These post hoc analyses show that asenapine reduced depressive symptoms in bipolar I disorder patients experiencing acute manic or mixed episodes with clinically relevant depressive symptoms at baseline; olanzapine results appeared to be less consistent. Controlled studies of asenapine in patients with acute bipolar depression are necessary to confirm the generalizability of these findings.</p

Effects of asenapine, olanzapine, and risperidone on psychotomimetic-induced reversal-learning deficits in the rat

YesBackground: Asenapine is a new pharmacological agent for the acute treatment of schizophrenia and bipolar disorder. It has relatively higher affinity for serotonergic and α2-adrenergic than dopaminergic D2 receptors. We evaluated the effects of asenapine, risperidone, and olanzapine on acute and subchronic psychotomimetic-induced disruption of cued reversal learning in rats. Methods: After operant training, rats were treated acutely with D-amphetamine (0.75 mg/kg intraperitoneally [i.p.]) or phencyclidine (PCP; 1.5 mg/kg i.p.) or sub-chronically with PCP (2 mg/kg i.p. for 7 days). We assessed the effects of acute coadministration of asenapine, risperidone, or olanzapine on acute D-amphetamine– and PCP-induced deficits and the effects of long-term coadministration of these agents (for 28 additional days) on the deficits induced by subchronic PCP. Results: Deficits in reversal learning induced by acute D-amphetamine were attenuated by risperidone (0.2 mg/kg i.p.). Acute PCP-induced impairment of reversal learning was attenuated by acute asenapine (0.025 mg/kg subcutaneously [s.c.]), risperidone (0.2 mg/kg i.p.), and olanzapine (1.0 mg/kg i.p.). Subchronic PCP administration induced an enduring deficit that was attenuated by acute asenapine (0.075 mg/kg s.c.) and by olanzapine (1.5 mg/kg i.p.). Asenapine (0.075 mg/kg s.c.), risperidone (0.2 mg/kg i.p.), and olanzapine (1.0 mg/kg i.p.) all showed sustained efficacy with chronic (29 d) treatment to improve subchronic PCP-induced impairments. Conclusion: These data suggest that asenapine may have beneficial effects in the treatment of cognitive symptoms in schizophrenia. However, this remains to be validated by further clinical evaluation.This research was supported by Schering-Plough Corporation, now Merck & Co., Inc. and Pfizer Inc

Asenapine effects in animal models of psychosis and cognitive function

Asenapine, a novel psychopharmacologic agent in the development for schizophrenia and bipolar disorder, has high affinity for serotonergic, α-adrenergic, and dopaminergic receptors, suggesting potential for antipsychotic and cognitive-enhancing properties. The effects of asenapine in rat models of antipsychotic efficacy and cognition were examined and compared with those of olanzapine and risperidone. Amphetamine-stimulated locomotor activity (Amp-LMA; 1.0 or 3.0 mg/kg s.c.) and apomorphine-disrupted prepulse inhibition (Apo-PPI; 0.5 mg/kg s.c.) were used as tests for antipsychotic activity. Delayed non-match to place (DNMTP) and five-choice serial reaction (5-CSR) tasks were used to assess short-term spatial memory and attention, respectively. Asenapine doses varied across tasks: Amp-LMA (0.01–0.3 mg/kg s.c.), Apo-PPI (0.001–0.3 mg/kg s.c.), DNMTP (0.01–0.1 mg/kg s.c.), and 5-CSR (0.003–0.3 mg/kg s.c.). Asenapine was highly potent (active at 0.03 mg/kg) in the Amp-LMA and Apo-PPI assays. DNMTP or 5-CSR performance was not improved by asenapine, olanzapine, or risperidone. All agents (P &lt; 0.01) reduced DNMTP accuracy at short delays; post hoc analyses revealed that only 0.1 mg/kg asenapine and 0.3 mg/kg risperidone differed from vehicle. All active agents (asenapine, 0.3 mg/kg; olanzapine, 0.03–0.3 mg/kg; and risperidone, 0.01–0.1 mg/kg) significantly impaired 5-CSR accuracy (P &lt; 0.05). Asenapine has potent antidopaminergic properties that are predictive of antipsychotic efficacy. Asenapine, like risperidone and olanzapine, did not improve cognition in normal rats. Rather, at doses greater than those required for antipsychotic activity, asenapine impaired cognitive performance due to disturbance of motor function, an effect also observed with olanzapine and risperidone

Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

Background Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide.Methods A multimethods analysis was performed as part of the GlobalSurg 3 study-a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital.Findings Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3.85 [95% CI 2.58-5.75]; p&lt;0.0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63.0% vs 82.7%; OR 0.35 [0.23-0.53]; p&lt;0.0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer.Interpretation Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised

The trans-ancestral genomic architecture of glycemic traits

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 × 10−8), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution

Novel Blood Pressure Locus and Gene Discovery Using Genome-Wide Association Study and Expression Data Sets From Blood and the Kidney.

Elevated blood pressure is a major risk factor for cardiovascular disease and has a substantial genetic contribution. Genetic variation influencing blood pressure has the potential to identify new pharmacological targets for the treatment of hypertension. To discover additional novel blood pressure loci, we used 1000 Genomes Project-based imputation in 150 134 European ancestry individuals and sought significant evidence for independent replication in a further 228 245 individuals. We report 6 new signals of association in or near HSPB7, TNXB, LRP12, LOC283335, SEPT9, and AKT2, and provide new replication evidence for a further 2 signals in EBF2 and NFKBIA Combining large whole-blood gene expression resources totaling 12 607 individuals, we investigated all novel and previously reported signals and identified 48 genes with evidence for involvement in blood pressure regulation that are significant in multiple resources. Three novel kidney-specific signals were also detected. These robustly implicated genes may provide new leads for therapeutic innovation

Author Correction: Discovery and refinement of genetic loci associated with cardiometabolic risk using dense imputation maps

Correction to: Nature Genetics https://doi.org/10.1038/ng.3668, published online 26 September 2016. In the version of the article published, the surname of author Aaron Isaacs is misspelled as Issacs

Low-frequency and rare exome chip variants associate with fasting glucose and type 2 diabetes susceptibility.

Fasting glucose and insulin are intermediate traits for type 2 diabetes. Here we explore the role of coding variation on these traits by analysis of variants on the HumanExome BeadChip in 60,564 non-diabetic individuals and in 16,491 T2D cases and 81,877 controls. We identify a novel association of a low-frequency nonsynonymous SNV in GLP1R (A316T; rs10305492; MAF=1.4%) with lower FG (β=-0.09±0.01 mmol l(-1), P=3.4 × 10(-12)), T2D risk (OR[95%CI]=0.86[0.76-0.96], P=0.010), early insulin secretion (β=-0.07±0.035 pmolinsulin mmolglucose(-1), P=0.048), but higher 2-h glucose (β=0.16±0.05 mmol l(-1), P=4.3 × 10(-4)). We identify a gene-based association with FG at G6PC2 (pSKAT=6.8 × 10(-6)) driven by four rare protein-coding SNVs (H177Y, Y207S, R283X and S324P). We identify rs651007 (MAF=20%) in the first intron of ABO at the putative promoter of an antisense lncRNA, associating with higher FG (β=0.02±0.004 mmol l(-1), P=1.3 × 10(-8)). Our approach identifies novel coding variant associations and extends the allelic spectrum of variation underlying diabetes-related quantitative traits and T2D susceptibility.CHARGE: Funding support for ‘Building on GWAS for NHLBI-diseases: the U.S. CHARGE consortium’ was provided by the NIH through the American Recovery and Reinvestment Act of 2009 (ARRA) (5RC2HL102419). Sequence data for ‘Building on GWAS for NHLBI-diseases: the U.S. CHARGE consortium’ was provided by Eric Boerwinkle on behalf of the Atherosclerosis Risk in Communities (ARIC) Study, L. Adrienne Cupples, principal investigator for the Framingham Heart Study, and Bruce Psaty, principal investigator for the Cardiovascular Health Study. Sequencing was carried out at the Baylor Genome Center (U54 HG003273). Further support came from HL120393, ‘Rare variants and NHLBI traits in deeply phenotyped cohorts’ (Bruce Psaty, principal investigator). Supporting funding was also provided by NHLBI with the CHARGE infrastructure grant HL105756. In addition, M.J.P. was supported through the 2014 CHARGE Visiting Fellow grant—HL105756, Dr Bruce Psaty, PI. ENCODE: ENCODE collaborators Ben Brown and Marcus Stoiber were supported by the LDRD# 14-200 (B.B. and M.S.) and 4R00HG006698-03 (B.B.) grants. AGES: This study has been funded by NIA contract N01-AG-12100 with contributions from NEI, NIDCD and NHLBI, the NIA Intramural Research Program, Hjartavernd (the Icelandic Heart Association) and the Althingi (the Icelandic Parliament). ARIC: The Atherosclerosis Risk in Communities (ARIC) Study is carried out as a collaborative study supported by National Heart, Lung, and Blood Institute (NHLBI) contracts (HHSN268201100005C, HHSN268201100006C, HHSN268201100007C, HHSN268201100008C, HHSN268201100009C, HHSN268201100010C, HHSN268201100011C and HHSN268201100012C), R01HL087641, R01HL59367 and R01HL086694; National Human Genome Research Institute contract U01HG004402; and National Institutes of Health contract HHSN268200625226C. We thank the staff and participants of the ARIC study for their important contributions. Infrastructure was partly supported by Grant Number UL1RR025005, a component of the National Institutes of Health and NIH Roadmap for Medical Research. CARDIA: The CARDIA Study is conducted and supported by the National Heart, Lung, and Blood Institute in collaboration with the University of Alabama at Birmingham (HHSN268201300025C & HHSN268201300026C), Northwestern University (HHSN268201300027C), University of Minnesota (HHSN268201300028C), Kaiser Foundation Research Institute (HHSN268201300029C), and Johns Hopkins University School of Medicine (HHSN268200900041C). CARDIA is also partially supported by the Intramural Research Program of the National Institute on Aging. Exome chip genotyping and data analyses were funded in part by grants U01-HG004729, R01-HL093029 and R01-HL084099 from the National Institutes of Health to Dr Myriam Fornage. This manuscript has been reviewed by CARDIA for scientific content. CHES: This work was supported in part by The Chinese-American Eye Study (CHES) grant EY017337, an unrestricted departmental grant from Research to Prevent Blindness, and the Genetics of Latinos Diabetic Retinopathy (GOLDR) Study grant EY14684. CHS: This CHS research was supported by NHLBI contracts HHSN268201200036C, HHSN268200800007C, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086; and NHLBI grants HL080295, HL087652, HL103612, HL068986 with additional contribution from the National Institute of Neurological Disorders and Stroke (NINDS). Additional support was provided through AG023629 from the National Institute on Aging (NIA). A full list of CHS investigators and institutions can be found at http://www.chs-nhlbi.org/pi.htm. The provision of genotyping data was supported in part by the National Center for Advancing Translational Sciences, CTSI grant UL1TR000124, and the National Institute of Diabetes and Digestive and Kidney Disease Diabetes Research Center (DRC) grant DK063491 to the Southern California Diabetes Endocrinology Research Center. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The CoLaus Study: We thank the co-primary investigators of the CoLaus study, Gerard Waeber and Peter Vollenweider, and the PI of the PsyColaus Study Martin Preisig. We gratefully acknowledge Yolande Barreau, Anne-Lise Bastian, Binasa Ramic, Martine Moranville, Martine Baumer, Marcy Sagette, Jeanne Ecoffey and Sylvie Mermoud for their role in the CoLaus data collection. The CoLaus study was supported by research grants from GlaxoSmithKline and from the Faculty of Biology and Medicine of Lausanne, Switzerland. The PsyCoLaus study was supported by grants from the Swiss National Science Foundation (#3200B0–105993) and from GlaxoSmithKline (Drug Discovery—Verona, R&D). CROATIA-Korcula: The CROATIA-Korcula study would like to acknowledge the invaluable contributions of the recruitment team in Korcula, the administrative teams in Croatia and Edinburgh and the people of Korcula. Exome array genotyping was performed at the Wellcome Trust Clinical Research Facility Genetics Core at Western General Hospital, Edinburgh, UK. The CROATIA-Korcula study on the Croatian island of Korucla was supported through grants from the Medical Research Council UK and the Ministry of Science, Education and Sport in the Republic of Croatia (number 108-1080315-0302). EFSOCH: We are extremely grateful to the EFSOCH study participants and the EFSOCH study team. The opinions given in this paper do not necessarily represent those of NIHR, the NHS or the Department of Health. The EFSOCH study was supported by South West NHS Research and Development, Exeter NHS Research and Development, the Darlington Trust, and the Peninsula NIHR Clinical Research Facility at the University of Exeter. Timothy Frayling, PI, is supported by the European Research Council grant: SZ-245 50371-GLUCOSEGENES-FP7-IDEAS-ERC. EPIC-Potsdam: We thank all EPIC-Potsdam participants for their invaluable contribution to the study. The study was supported in part by a grant from the German Federal Ministry of Education and Research (BMBF) to the German Center for Diabetes Research (DZD e.V.). The recruitment phase of the EPIC-Potsdam study was supported by the Federal Ministry of Science, Germany (01 EA 9401) and the European Union (SOC 95201408 05 F02). The follow-up of the EPIC-Potsdam study was supported by German Cancer Aid (70-2488-Ha I) and the European Community (SOC 98200769 05 F02). Furthermore, we thank Ellen Kohlsdorf for data management as well as the follow-up team headed by Dr Manuala Bergmann for case ascertainment. ERF: The ERF study was supported by grants from the Netherlands Organization for Scientific Research (NWO) and a joint grant from NWO and the Russian Foundation for Basic research (Pionier, 047.016.009, 047.017.043), Erasmus MC, and the Centre for Medical Systems Biology (CMSB; National Genomics Initiative). Exome sequencing analysis in ERF was supported by the ZonMw grant (91111025). For the ERF Study, we are grateful to all participants and their relatives, to general practitioners and neurologists for their contributions, to P. Veraart for her help in genealogy and to P. Snijders for his help in data collection. FamHS: The Family Heart Study (FamHS) was supported by NIH grants R01-HL-087700 and R01-HL-088215 (Michael A. Province, PI) from NHLBI; and R01-DK-8925601 and R01-DK-075681 (Ingrid B. Borecki, PI) from NIDDK. FENLAND: The Fenland Study is funded by the Medical Research Council (MC_U106179471) and Wellcome Trust. We are grateful to all the volunteers for their time and help, and to the General Practitioners and practice staff for assistance with recruitment. We thank the Fenland Study Investigators, Fenland Study Co-ordination team and the Epidemiology Field, Data and Laboratory teams. The Fenland Study is funded by the Medical Research Council (MC_U106179471) and Wellcome Trust. FHS: Genotyping, quality control and calling of the Illumina HumanExome BeadChip in the Framingham Heart Study was supported by funding from the National Heart, Lung and Blood Institute Division of Intramural Research (Daniel Levy and Christopher J. O’Donnell, Principle Investigators). A portion of this research was conducted using the Linux Clusters for Genetic Analysis (LinGA) computing resources at Boston University Medical Campus. Also supported by National Institute for Diabetes and Digestive and Kidney Diseases (NIDDK) R01 DK078616, NIDDK K24 DK080140 and American Diabetes Association Mentor-Based Postdoctoral Fellowship Award #7-09-MN-32, all to Dr Meigs, a Canadian Diabetes Association Research Fellowship Award to Dr Leong, a research grant from the University of Verona, Italy to Dr Dauriz, and NIDDK Research Career Award K23 DK65978, a Massachusetts General Hospital Physician Scientist Development Award and a Doris Duke Charitable Foundation Clinical Scientist Development Award to Dr Florez. FIA3: We are indebted to the study participants who dedicated their time and samples to these studies. We thank Åsa Ågren (Umeå Medical Biobank) for data organization and Kerstin Enquist and Thore Johansson (Västerbottens County Council) for technical assistance with DNA extraction. This particular project was supported by project grants from the Swedish Heart-Lung Foundation, Umeå Medical Research Foundation and Västerbotten County Council. The Genetics Epidemiology of Metabolic Syndrome (GEMS) Study: We thank Metabolic Syndrome GEMs investigators: Scott Grundy, Jonathan Cohen, Ruth McPherson, Antero Kesaniemi, Robert Mahley, Tom Bersot, Philip Barter and Gerard Waeber. We gratefully acknowledge the contributions of the study personnel at each of the collaborating sites: John Farrell, Nicholas Nikolopoulos and Maureen Sutton (Boston); Judy Walshe, Monica Prentice, Anne Whitehouse, Julie Butters and Tori Nicholls (Australia); Heather Doelle, Lynn Lewis and Anna Toma (Canada); Kari Kervinen, Seppo Poykko, Liisa Mannermaa and Sari Paavola (Finland); Claire Hurrel, Diane Morin, Alice Mermod, Myriam Genoud and Roger Darioli (Switzerland); Guy Pepin, Sibel Tanir, Erhan Palaoglu, Kerem Ozer, Linda Mahley and Aysen Agacdiken (Turkey); and Deborah A. Widmer, Rhonda Harris and Selena Dixon (United States). Funding for the GEMS study was provided by GlaxoSmithKline. GeneSTAR: The Johns Hopkins Genetic Study of Atherosclerosis Risk (GeneSTAR) Study was supported by NIH grants through the National Heart, Lung, and Blood Institute (HL58625-01A1, HL59684, HL071025-01A1, U01HL72518, HL112064, and HL087698) and the National Institute of Nursing Research (NR0224103) and by M01-RR000052 to the Johns Hopkins General Clinical Research Center. Genotyping services were provided through the RS&G Service by the Northwest Genomics Center at the University of Washington, Department of Genome Sciences, under U.S. Federal Government contract number HHSN268201100037C from the National Heart, Lung, and Blood Institute. GLACIER: We are indebted to the study participants who dedicated their time, data and samples to the GLACIER Study as part of the Västerbottens hälsoundersökningar (Västerbottens Health Survey). We thank John Hutiainen and Åsa Ågren (Northern Sweden Biobank) for data organization and Kerstin Enquist and Thore Johansson (Västerbottens County Council) for extracting DNA. We also thank M. Sterner, M. Juhas and P. Storm (Lund University Diabetes Center) for their expert technical assistance with genotyping and genotype data preparation. The GLACIER Study was supported by grants from Novo Nordisk, the Swedish Research Council, Påhlssons Foundation, The Heart Foundation of Northern Sweden, the Swedish Heart Lung Foundation, the Skåne Regional Health Authority, Umeå Medical Research Foundation and the Wellcome Trust. This particular project was supported by project grants from the Swedish Heart-Lung Foundation, the Swedish Research Council, the Swedish Diabetes Association, Påhlssons Foundation and Novo nordisk (all grants to P. W. Franks). GOMAP (Genetic Overlap between Metabolic and Psychiatric Disease): This work was funded by the Wellcome Trust (098051). We thank all participants for their important contribution. We are grateful to Georgia Markou, Laiko General Hospital Diabetes Centre, Maria Emetsidou and Panagiota Fotinopoulou, Hippokratio General Hospital Diabetes Centre, Athina Karabela, Dafni Psychiatric Hospital, Eirini Glezou and Marios Matzioros, Dromokaiteio Psychiatric Hospital, Angela Rentari, Harokopio University of Athens, and Danielle Walker, Wellcome Trust Sanger Institute. Generation Scotland: Scottish Family Health Study (GS:SFHS): GS:SFHS is funded by the Chief Scientist Office of the Scottish Government Health Directorates, grant number CZD/16/6 and the Scottish Funding Council. Exome array genotyping for GS:SFHS was funded by the Medical Research Council UK and performed at the Wellcome Trust Clinical Research Facility Genetics Core at Western General Hospital, Edinburgh, UK. We also acknowledge the invaluable contributions of the families who took part in the Generation Scotland: Scottish Family Health Study, the general practitioners and Scottish School of Primary Care for their help in recruiting them, and the whole Generation Scotland team, which includes academic researchers, IT staff, laboratory technicians, statisticians and research managers. The chief investigators of Generation Scotland are David J. Porteous (University of Edinburgh), Lynne Hocking (University of Aberdeen), Blair Smith (University of Dundee), and Sandosh Padmanabhan (University of Glasgow). GSK (CoLaus, GEMS, Lolipop): We thank the GEMS Study Investigators: Philip Barter, PhD; Y. Antero Kesäniemi, PhD; Robert W. Mahley, PhD; Ruth McPherson, FRCP; and Scott M. Grundy, PhD. Dr Waeber MD, the CoLaus PI’s Peter Vollenweider MD and Gerard Waeber MD, the LOLIPOP PI’s, Jaspal Kooner MD and John Chambers MD, as well as the participants in all the studies. The GEMS study was sponsored in part by GlaxoSmithKline. The CoLaus study was supported by grants from GlaxoSmithKline, the Swiss National Science Foundation (Grant 33CSCO-122661) and the Faculty of Biology and Medicine of Lausanne. Health ABC: The Health, Aging and Body Composition (HABC) Study is supported by NIA contracts N01AG62101, N01AG62103 and N01AG62106. The exome-wide association study was funded by NIA grant 1R01AG032098-01A1 to Wake Forest University Health Sciences and was supported in part by the Intramural Research Program of the NIH, National Institute on Aging (Z01 AG000949-02 and Z01 AG007390-07, Human subjects protocol UCSF IRB is H5254-12688-11). Portions of this study utilized the high-performance computational capabilities of the Biowulf Linux cluster at the National Institutes of Health, Bethesda, MD. (http:/biowulf.nih.gov). Health2008: The Health2008 cohort was supported by the Timber Merchant Vilhelm Bang’s Foundation, the Danish Heart Foundation (Grant number 07-10-R61-A1754-B838-22392F), and the Health Insurance Foundation (Helsefonden) (Grant number 2012B233). HELIC: This work was funded by the Wellcome Trust (098051) and the European Research Council (ERC-2011-StG 280559-SEPI). The MANOLIS cohort is named in honour of Manolis Giannakakis, 1978–2010. We thank the residents of Anogia and surrounding Mylopotamos villages, and of the Pomak villages, for taking part. The HELIC study has been supported by many individuals who have contributed to sample collection (including Antonis Athanasiadis, Olina Balafouti, Christina Batzaki, Georgios Daskalakis, Eleni Emmanouil, Chrisoula Giannakaki, Margarita Giannakopoulou, Anastasia Kaparou, Vasiliki Kariakli, Stella Koinaki, Dimitra Kokori, Maria Konidari, Hara Koundouraki, Dimitris Koutoukidis, Vasiliki Mamakou, Eirini Mamalaki, Eirini Mpamiaki, Maria Tsoukana, Dimitra Tzakou, Katerina Vosdogianni, Niovi Xenaki, Eleni Zengini), data entry (Thanos Antonos, Dimitra Papagrigoriou, Betty Spiliopoulou), sample logistics (Sarah Edkins, Emma Gray), genotyping (Robert Andrews, Hannah Blackburn, Doug Simpkin, Siobhan Whitehead), research administration (Anja Kolb-Kokocinski, Carol Smee, Danielle Walker) and informatics (Martin Pollard, Josh Randall). INCIPE: NIcole Soranzo’s research is supported by the Wellcome Trust (Grant Codes WT098051 and WT091310), the EU FP7 (EPIGENESYS Grant Code 257082 and BLUEPRINT Grant Code HEALTH-F5-2011-282510). Inter99: The Inter99 was initiated by Torben Jørgensen (PI), Knut Borch-Johnsen (co-PI), Hans Ibsen and Troels F. Thomsen. The steering committee comprises the former two and Charlotta Pisinger. The study was financially supported by research grants from the Danish Research Council, the Danish Centre for Health Technology Assessment, Novo Nordisk Inc., Research Foundation of Copenhagen County, Ministry of Internal Affairs and Health, the Danish Heart Foundation, the Danish Pharmaceutical Association, the Augustinus Foundation, the Ib Henriksen Foundation, the Becket Foundation and the Danish Diabetes Association. Genetic studies of both Inter99 and Health 2008 cohorts were funded by the Lundbeck Foundation and produced by The Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention and Care (LuCamp, www.lucamp.org ). The Novo Nordisk Foundation Center for Basic Metabolic Research is an independent Research Center at the University of Copenhagen partially funded by an unrestricted donation from the Novo Nordisk Foundation (www.metabol.ku.dk). InterAct Consortium: Funding for the InterAct project was provided by the EU FP6 programme (grant number LSHM_CT_2006_037197). We thank all EPIC participants and staff for their contribution to the study. We thank the lab team at the MRC Epidemiology Unit for sample management and Nicola Kerrison for data management. IPM BioMe Biobank: The Mount Sinai IPM BioMe Program is supported by The Andrea and Charles Bronfman Philanthropies. Analyses of BioMe data was supported in part through the computational resources and staff expertise provided by the Department of Scientific Computing at the Icahn School of Medicine at Mount Sinai. The Insulin Resistance Atherosclerosis Family Study (IRASFS): The IRASFS was conducted and supported by the National Institute of Diabetes and Digestive and Kidney Diseases (HL060944, HL061019, and HL060919). Exome chip genotyping and data analyses were funded in part by grants DK081350 and HG007112. A subset of the IRASFS exome chips were contributed with funds from the Department of Internal Medicine at the University of Michigan. Computing resources were provided, in part, by the Wake Forest School of Medicine Center for Public Health Genomics. The Insulin Resistance Atherosclerosis Study (IRAS): The IRAS was conducted and supported by the National Institute of Diabetes and Digestive and Kidney Diseases (HL047887, HL047889, HL047890 and HL47902). Exome chip genotyping and data analyses were funded in part by grants DK081350 and HG007112). Computing resources were provided, in part, by the Wake Forest School of Medicine Center for Public Health Genomics. JHS: The JHS is supported by contracts HHSN268201300046C, HHSN268201300047C, HHSN268201300048C, HHSN268201300049C, HHSN268201300050C from the National Heart, Lung and Blood Institute and the National Institute on Minority Health and Health Disparities. ExomeChip genotyping was supported by the NHLBI of the National Institutes of Health under award number R01HL107816 to S. Kathiresan. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The London Life Sciences Prospective Population (LOLIPOP) Study: We thank the co-primary investigators of the LOLIPOP study: Jaspal Kooner, John Chambers and Paul Elliott. The LOLIPOP study is supported by the National Institute for Health Research Comprehensive Biomedical Research Centre Imperial College Healthcare NHS Trust, the British Heart Foundation (SP/04/002), the Medical Research Council (G0700931), the Wellcome Trust (084723/Z/08/Z) and the National Institute for Health Research (RP-PG-0407-10371). MAGIC: Data on glycaemic traits were contributed by MAGIC investigators and were downloaded from www.magicinvestigators.org. MESA: The Multi-Ethnic Study of Atherosclerosis (MESA) and MESA SHARe project are conducted and supported by contracts N01-HC-95159 through N01-HC-95169 and RR-024156 from the National Heart, Lung, and Blood Institute (NHLBI). Funding for MESA SHARe genotyping was provided by NHLBI Contract N02-HL-6-4278. MESA Family is conducted and supported in collaboration with MESA investigators; support is provided by grants and co