Suchergebnisse

La Nouvelle-Zélande est souvent citée comme l'archétype du nouveau management public (NMP), car elle est allée « plus loin et plus vite » que d'autres pays en réformant radicalement son service public à la fin des années 1980. On a attribué à ces réformes des gains significatifs en termes d'efficacité et de réactivité, tout en introduisant de nouveaux défis. Les réformes successives des 30 dernières années ont retouché le modèle sans modifier fondamentalement le paradigme sous-jacent, si bien que certains auteurs parlent du « mythe du post-NMP en Nouvelle-Zélande ». En 2020, la Nouvelle-Zélande a abrogé et remplacé sa principale législation sur le service public. En analysant textuellement des documents gouvernementaux, cet article explore les différentes racines théoriques des réformes administratives en cours en Nouvelle-Zélande et examine de leur degré de cohérence théorique. La loi fait directement écho aux récents débats universitaires et s'en inspire, en s'appuyant sur une série de sources (telles que la nouvelle gouvernance publique, la gouvernance à l'ère du numérique et le nouveau service public). Remarque à l'intention des praticiens La Nouvelle-Zélande a longtemps été considérée comme l'exemple le plus pur du nouveau management public (NMP). La législation approuvée en 2020 a permis à la Nouvelle-Zélande d'adopter une série de réformes décrites dans la littérature comme « post-NMP », tout en réaffirmant les caractéristiques associées à l'administration publique traditionnelle (APT). Si la Nouvelle-Zélande s'est éloignée d'un modèle purement NMP et a adopté des caractéristiques associées au post-NMP, le post-NMP n'est pas une doctrine cohérente et les doctrines administratives ne peuvent peut-être être identifiées que rétrospectivement. Nous entrons peut-être dans une période de « nouvelle complexité publique », où les doctrines administratives se mélangent et se superposent.

New Zealand is frequently cited as the archetypical example of New Public Management (NPM), having gone 'further and faster' than other jurisdictions in radically reforming their public service in the late 1980s. These reforms have been credited with significant gains in efficiency and responsiveness, while introducing new challenges. Successive reforms over the past 30 years tinkered with the model without fundamentally altering the underlying paradigm, such that authors refer to the 'myth of post-NPM in New Zealand'. In 2020, New Zealand repealed and replaced its main public service legislation. By textually analysing government documents, this article explores the different theoretical roots of New Zealand's ongoing administrative reforms and debates the extent of their theoretical coherence. The Act directly dialogues with and draws inspiration from recent academic debates, drawing from a range of sources (such as New Public Governance, Digital Era Governance, and the New Public Service). Points for practitioners New Zealand has long been regarded as the purest example of New Public Management (NPM). Legislation passed in 2020 saw New Zealand adopt a range of reforms described in the literature as 'post-NPM', while also reaffirming features associated with Traditional Public Administration (TPA). While New Zealand has moved away from a pure NPM model and adopted features associated with Post-NPM, Post-NPM is not a coherent doctrine and it may only be possible to identify administrative doctrines retrospectively. We may be entering a period of 'New Public Complexity', where administrative doctrines are blended and layered.

Mental model change and mental model alignment are reported outcomes of group model building. Several explanations have been proposed for these changes. This paper explores the experiences of participants in group model building workshops where delayed evaluations suggested that lasting mental model change has occurred. Semi‐structured interviews were used to explore how participants believed that the workshops changed their thinking. The results are compared with proposed mechanisms for mental model change: operator logic, system archetypes, modelling as persuasion, and boundary objects. Although individuals typically possess incomplete insight into their own learning, understanding participants' recollections helps practitioners to better communicate with clients and potential clients. Interview results support the boundary object mechanism as most consistent with participants' own recollections. Copyright © 2014 John Wiley & Sons, Ltd.

AbstractGroup model building literature reports that participation causes mental model refinement and alignment, but no previous study appears to have examined whether these changes are enduring. This paper reports on a case study involving four groups using group model building tools that were evaluated immediately before, immediately after, and 12 months following a 3‐hour workshop. Each workshop used qualitative group model building to plan strategy implementation initiatives in a government department. A change of circumstances (merger and restructure) meant that the workshop conclusions were not implemented, providing a research opportunity to measure the enduring effects of group model building workshops. Statistical comparison of written responses suggests that participants' views on the workshop topic changed and became more alike through the workshop process, and that these changes were enduring even in the relative absence of reinforcing activities. Copyright © 2014 System Dynamics Society

Abstract

Background
The inactivation of tumor suppressor genes follows Alfred Knudson's 'two-hit' model: both alleles need to be inactivated by independent mutation events to trigger tumor formation. However, in a minority of tumor suppressor genes a single hit is sufficient to initiate tumorigenesis notwithstanding the presence of the wild-type allele, a condition known as haploinsufficiency. The SMAD4 gene is an intracellular mediator of the TGF-β and BMP signal transduction pathways and a tumor suppressor involved in pancreatic and colorectal tumorigenesis. In Smad4-mutant mouse models, haploinsufficiency characterizes the development of gastrointestinal polyps with initial retention of the wild-type allele and protein expression within the nascent tumors and in their direct microenvironment. Similarly, germline SMAD4 mutations are responsible for a subset of patients affected by juvenile polyposis syndrome, an autosomal dominant intestinal cancer syndrome. To date, the molecular and cellular consequences of SMAD4 haploinsufficiency on TGF-β and BMP signaling and on genome-wide gene expression have not been investigated.


Results
Here we show that, similar to previous observations in Smad4-mutant mouse models, haploinsufficiency characterizes a substantial fraction of the juvenile polyps arising in patients with germline SMAD4 mutations. Also, mouse embryonic and intestinal cells heterozygous for a targeted Smad4 null mutation are characterized by a corresponding 50% reduction of the Smad4 protein levels. Reporter assays revealed that mouse Smad4
+/- cells exert intermediate inhibitory effects on both TGF-β and BMP signaling. Genome-wide expression profiling analysis of Smad4
+/- and Smad4
-/- cells pinpointed a subset of dosage-dependent transcriptional target genes encompassing, among others, members of the TGF-β and Wnt signaling pathways. These SMAD4 dosage-dependent transcriptional changes were confirmed and validated in a subset of target genes in intestinal tissues from juvenile polyposis syndrome patients.


Conclusion

Smad4 haploinsufficiency is sufficient to significantly inhibit both TGF-β and BMP signal transduction and results in the differential expression of a broad subset of target genes likely to underlie tumor formation both from the mesenchymal and epithelial compartments. The results of our study, performed in normal rather than tumor cells where additional (epi-) genetic alterations may confound the analysis, are relevant for our understanding and elucidation of the initial steps underlying SMAD4-driven intestinal tumorigenesis.

AbstractConsiderable progress continues to be made with regards to the value and use of disease associated polygenic scores (PGS). PGS aim to capture a person's genetic liability to a condition, disease, or a trait, combining information across many risk variants and incorporating their effect sizes. They are already available for clinicians and consumers to order in Australasia. However, debate is ongoing over the readiness of this information for integration into clinical practice and population health. This position statement provides the viewpoint of the Human Genetics Society of Australasia (HGSA) regarding the clinical application of disease-associated PGS in both individual patients and population health. The statement details how PGS are calculated, highlights their breadth of possible application, and examines their current challenges and limitations. We consider fundamental lessons from Mendelian genetics and their continuing relevance to PGS, while also acknowledging the distinct elements of PGS. Use of PGS in practice should be evidence based, and the evidence for the associated benefit, while rapidly emerging, remains limited. Given that clinicians and consumers can already order PGS, their current limitations and key issues warrant consideration. PGS can be developed for most complex conditions and traits and can be used across multiple clinical settings and for population health. The HGSA's view is that further evaluation, including regulatory, implementation and health system evaluation are required before PGS can be routinely implemented in the Australasian healthcare system.

BACKGROUND: Insulinemia and type 2 diabetes (T2D) have been associated with endometrial cancer risk in numerous observational studies. However, the causality of these associations is uncertain. Here we use a Mendelian randomization (MR) approach to assess whether insulinemia and T2D are causally associated with endometrial cancer. METHODS: We used single nucleotide polymorphisms (SNPs) associated with T2D (49 variants), fasting glucose (36 variants), fasting insulin (18 variants), early insulin secretion (17 variants), and body mass index (BMI) (32 variants) as instrumental variables in MR analyses. We calculated MR estimates for each risk factor with endometrial cancer using an inverse-variance weighted method with SNP-endometrial cancer associations from 1287 case patients and 8273 control participants. RESULTS: Genetically predicted higher fasting insulin levels were associated with greater risk of endometrial cancer (odds ratio [OR] per standard deviation = 2.34, 95% confidence internal [CI] = 1.06 to 5.14, P = .03). Consistently, genetically predicted higher 30-minute postchallenge insulin levels were also associated with endometrial cancer risk (OR = 1.40, 95% CI = 1.12 to 1.76, P = .003). We observed no associations between genetic risk of type 2 diabetes (OR = 0.91, 95% CI = 0.79 to 1.04, P = .16) or higher fasting glucose (OR = 1.00, 95% CI = 0.67 to 1.50, P = .99) and endometrial cancer. In contrast, endometrial cancer risk was higher in individuals with genetically predicted higher BMI (OR = 3.86, 95% CI = 2.24 to 6.64, P = 1.2x10(-6)). CONCLUSION: This study provides evidence to support a causal association of higher insulin levels, independently of BMI, with endometrial cancer risk. ; This study was supported by MRC grant MC_UU_12015/1 and by the Innovative Medicines Initiative Joint Undertaking under EMIF grant agreement n° 115372 (contributions from the European Union's Seventh Framework Programme (FP7/2007-2013) and EFPIA companies). ANECS recruitment was supported by project grants from the National Health and Medical Research Council of Australia (ID#339435), The Cancer Council Queensland (ID#4196615) and Cancer Council Tasmania (ID#403031 and ID#457636). SEARCH recruitment was funded by a programme grant from Cancer Research UK [C490/A10124]. Case genotyping was supported by the National Health and Medical Research Council (ID#552402). Control data was generated by the Wellcome Trust Case Control Consortium (WTCCC), and a full list of the investigators who contributed to the generation of the data is available from the WTCCC website. We acknowledge use of DNA from the British 1958 Birth Cohort collection, funded by the Medical Research Council grant G0000934 and the Wellcome Trust grant 068545/Z/02. Funding for this project was provided by the Wellcome Trust under award 085475. Recruitment of the QIMR controls was supported by the National Health and Medical Research Council of Australia (NHMRC). The University of Newcastle, the Gladys M Brawn Senior Research Fellowship scheme, The Vincent Fairfax Family Foundation, the Hunter Medical Research Institute and the Hunter Area Pathology Service all contributed towards the costs of establishing the Hunter Community Study. K.T.N. was supported by the Gates Cambridge Trust. R.K.S. is supported by the Wellcome Trust (grant number WT098498). A.B.S. is supported by the National Health and Medical Research Council (NHMRC) Fellowship Scheme. D.F.E. is a Principal Research Fellow of Cancer Research UK. A.M.D is supported by the Joseph Mitchell Trust. ; This is the final version of the article. It first appeared from Oxford University Press via http://dx.doi.org/10.1093/jnci/djv178

HapMap imputed genome-wide association studies (GWAS) have revealed >50 loci at which common variants with minor allele frequency >5% are associated with kidney function. GWAS using more complete reference sets for imputation, such as those from The 1000 Genomes project, promise to identify novel loci that have been missed by previous efforts. To investigate the value of such a more complete variant catalog, we conducted a GWAS meta-analysis of kidney function based on the estimated glomerular filtration rate (eGFR) in 110,517 European ancestry participants using 1000 Genomes imputed data. We identified 10 novel loci with p-value < 5 × 10−8 previously missed by HapMap-based GWAS. Six of these loci (HOXD8, ARL15, PIK3R1, EYA4, ASTN2, and EPB41L3) are tagged by common SNPs unique to the 1000 Genomes reference panel. Using pathway analysis, we identified 39 significant (FDR < 0.05) genes and 127 significantly (FDR < 0.05) enriched gene sets, which were missed by our previous analyses. Among those, the 10 identified novel genes are part of pathways of kidney development, carbohydrate metabolism, cardiac septum development and glucose metabolism. These results highlight the utility of re-imputing from denser reference panels, until whole-genome sequencing becomes feasible in large samples. ; 3C. Three-City Study. The work was made possible by the participation of the control subjects, the patients, and their families. We thank Dr. Anne Boland (CNG) for her technical help in preparing the DNA samples for analyses. This work was supported by the National Foundation for Alzheimer's disease and related disorders, the Institut Pasteur de Lille and the Centre National de Génotypage. The 3C Study was performed as part of a collaboration between the Institut National de la Santé et de la Recherche Médicale (Inserm), the Victor Segalen Bordeaux II University and Sanofi-Synthélabo. The Fondation pour la Recherche Médicale funded the preparation and initiation of the study. The 3C Study was also funded by the Caisse Nationale Maladie des Travailleurs Salariés, Direction Générale de la Santé, MGEN, Institut de la Longévité, Agence Française de Sécurité Sanitaire des Produits de Santé, the Aquitaine and Bourgogne Regional Councils, Fondation de France and the joint French Ministry of Research/INSERM "Cohortes et collections de données biologiques" programme. Lille Génopôle received an unconditional grant from Eisai. AGES. Age, Gene/Environment Susceptibility-Reykjavik Study. This study has been funded by NIH contract N01-AG-1-2100, the NIA Intramural Research Program, Hjartavernd (the Icelandic Heart Association), and the Althingi (the Icelandic Parliament). The study is approved by the Icelandic National Bioethics Committee, VSN: 00-063. The researchers are indebted to the participants for their willingness to participate in the study. ARIC. Atherosclerosis Risk in Communities study. The ARIC study is carried out as a collaborative study supported by National Heart, Lung, and Blood Institute 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. The authors 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. This work as well as YL and AK were supported by the German Research Foundation (KO 3598/2-1, KO 3598/3-1 and CRC1140 A05 to AK). ASPS. Austrian Stroke Prevention Study. The research reported in this article was funded by the Austrian Science Fond (FWF) grant number P20545-P05 and P13180. The Medical University of Graz supports the databank of the ASPS. The authors thank the staff and the participants of the ASPS for their valuable contributions. We thank Birgit Reinhart for her long-term administrative commitment and Ing Johann Semmler for the technical assistance at creating the DNA-bank. BMES. Blue Mountains Eye Study. The BMES has been supported by the Australian RADGAC grant (1992- 94) and Australian National Health & Medical Research Council, Canberra Australia (Grant Nos: 974159, 211069, 991407, 457349). The GWAS studies of Blue Mountains Eye Study population are supported by the Australian National Health & Medical Research Council (Grant Nos: 512423, 475604, 529912) and the Wellcome Trust, UK (2008). EGH and JJW are funded by the Australian National Health & Medical Research Council Fellowship Schemes. CILENTO. Italian Network on Genetic Isolates – Cilento. We thank the populations of Cilento for their participation in the study. The study was supported by the Italian Ministry of Universities and CNR 36 (PON03PE_00060_7, Interomics Flagship Project), the Assessorato Ricerca Regione Campania, the Fondazione con il SUD (2011-PDR-13), and the Istituto Banco di Napoli - Fondazione to MC. COLAUS. The CoLaus authors thank Yolande Barreau, Mathieu Firmann, Vladimir Mayor, Anne-Lise Bastian, Binasa Ramic, Martine Moranville, Martine Baumer, Marcy Sagette, Jeanne Ecoffey and Sylvie Mermoud for data collection. The CoLaus study received financial contributions from GlaxoSmithKline, the Faculty of Biology and Medicine of Lausanne, the Swiss National Science Foundation (33CSCO- 122661, 3200BO-111361/2, 3100AO-116323/1, 310000-112552). The computations for CoLaus imputation were performed in part at the Vital-IT center for high performance computing of the Swiss Institute of Bioinformatics. We thank Vincent Mooser for his contribution to the CoLaus study. EGCUT. Estonian Genome Center University of Tartu. EGCUT received financing from FP7 grants (278913, 306031, 313010) and targeted financing from Estonian Government (SF0180142s08). EGCUT studies were covered from Infra-structure grant no. 3.2.0304.11-0312 funded mostly by the European Regional Development Fund, Center of Excellence in Genomics (EXCEGEN) and University of Tartu (SP1GVARENG). We acknowledge EGCUT technical personnel, especially Mr V. Soo and S. Smit. Data analyses were carried out in part in the High Performance Computing Center of the University of Tartu. FamHS. Family Heart Study. The FHS work was supported in part by NIH grants 5R01HL08770003, 5R01HL08821502 (Michael A. Province) from the NHLBI and 5R01DK07568102, 5R01DK06833603 from the NIDDK (I.B.B.). The authors thank the staff and participants of the FamHS for their important contributions. FHS. Framingham Heart Study. This research was conducted in part using data and resources from the Framingham Heart Study of the National Heart Lung and Blood Institute of the National Institutes of Health and Boston University School of Medicine. The analyses reflect intellectual input and resource development from the Framingham Heart Study investigators participating in the SNP Health Association Resource (SHARe) project. This work was partially supported by the National Heart, Lung and Blood Institute's Framingham Heart Study (Contract No. N01-HC-25195) and its contract with Affymetrix, Inc. for genotyping services (Contract No. N02-HL-6-4278). A portion of this research utilized the Linux Cluster for Genetic Analysis (LinGA-II) funded by the Robert Dawson Evans Endowment of the Department of Medicine at Boston University School of Medicine and Boston Medical Center. GENDIAN. GENetics of DIAbetic Nephropathy study. The support of the physicians, the patients, and the staff of the Diabetes Zentrum Mergentheim (Head: Prof. Dr. Thomas Haak), the diabetes outpatient clinic Dr Nusser - Dr Kreisel, the dialysis centers KfH Amberg, KfH Bayreuth, KfH Deggendorf, KfH Donauwörth, KfH Freising, KfH Freyung, KfH Fürth, KfH Hof, KfH Ingolstadt, KfH Kelheim, KfH München Elsenheimerstraße, KfH München-Schwabing, KfH Neumarkt, KfH Neusäß, KfH Oberschleißheim, KfH Passau, KfH Plauen, KfH Regensburg Günzstraße, KfH Regensburg Caritas-Krankenhaus, KfH Straubing, KfH Sulzbach-Rosenberg, KfH Weiden, Dialysezentrum Augsburg Dr. Kirschner, Dialysezentrum Bad Alexandersbad, KfH Bamberg, Dialysezentrum Emmering, Dialysezentrum Klinikum Landshut, Dialysezentrum Landshut, Dialysezentrum Pfarrkirchen, Dialysezentrum Schwandorf, Dr. Angela Götz, the medical doctoral student Johanna Christ and the Study Nurse Ingrid Lugauer. The expert technical assistance of Claudia Strohmeier is acknowledged. Phenotyping was funded by the Dr. Robert PflegerStiftung (Dr Carsten A. Böger), the MSD Stipend Diabetes (Dr Carsten A. Böger) and the University Hospital of Regensburg (intramural grant ReForM A to Dr. A. Götz, ReForM C to Dr. Carsten Böger). Genome-wide genotyping was funded by the KfH Stiftung Präventivmedizin e.V. (Dr. Carsten A. Böger, Dr. Jens Brüning), the Else Kröner-Fresenius-Stiftung (2012_A147 to Dr Carsten A. Böger and Dr Iris M. Heid) and the University Hospital Regensburg (Dr Carsten A. Böger). Data analysis was funded by the Else 37 Kröner-Fresenius Stiftung (Dr. Iris M. Heid and Dr. Carsten A. Böger: 2012_A147; Dr. Carsten A. Böger and Dr. Bernhard K. Krämer: P48/08//A11/08). GENDIAN Study Group: Mathias Gorski, Iris M. Heid, Bernhard K. Krämer, Myriam Rheinberger, Michael Broll, Alexander Lammert, Jens Brüning, Matthias Olden, Klaus Stark, Claudia Strohmeier, Simone Neumeier, Sarah Hufnagel, Petra Jackermeier, Emilia Ruff, Johanna Christ, Peter Nürnberg, Thomas Haak, Carsten A. Böger. HABC. Health Aging and Body Composition Study. The HABC study was funded by the National Institutes of Aging. This research was supported by NIA contracts N01AG62101, N01AG62103, and N01AG62106. The genome-wide association study was funded by NIA grant 1R01AG032098-01A1 to Wake Forest University Health Sciences and genotyping services were provided by the Center for Inherited Disease Research (CIDR). CIDR is fully funded through a federal contract from the National Institutes of Health to The Johns Hopkins University, contract number HHSN268200782096C. This research was supported in part by the Intramural Research Program of the NIH, National Institute on Aging. HCS. Hunter Community Study. The University of Newcastle provided $300,000 from its Strategic Initiatives Fund, and $600,000 from the Gladys M Brawn Senior Research Fellowship scheme; Vincent Fairfax Family Foundation, a private philanthropic trust, provided $195,000; The Hunter Medical Research Institute provided media support during the initial recruitment of participants; and Dr Anne Crotty, Prof. Rodney Scott and Associate Prof. Levi provided financial support towards freezing costs for the long-term storage of participant blood samples. The authors would like to thank the men and women participating in the HCS as well as all the staff, investigators and collaborators who have supported or been involved in the project to date. A special thank you should go to Alison Koschel and Debbie Quain who were instrumental in setting up the pilot study and initial phase of the project. HPFS. Health Professionals Follow-Up Study. The NHS/HPFS type 2 diabetes GWAS (U01HG004399) is a component of a collaborative project that includes 13 other GWAS (U01HG004738, U01HG004422, U01HG004402, U01HG004729, U01HG004726, U01HG004735, U01HG004415, U01HG004436, U01HG004423, U01HG004728, RFAHG006033; National Institute of Dental & Craniofacial Research: U01DE018993, U01DE018903) funded as part of the Gene Environment-Association Studies (GENEVA) under the NIH Genes, Environment and Health Initiative (GEI). Assistance with phenotype harmonization and genotype cleaning, as well as with general study coordination, was provided by the GENEVA Coordinating Center (U01HG004446). Assistance with data cleaning was provided by the National Center for Biotechnology Information. Genotyping was performed at the Broad Institute of MIT and Harvard, with funding support from the NIH GEI (U01HG04424), and Johns Hopkins University Center for Inherited Disease Research, with support from the NIH GEI (U01HG004438) and the NIH contract "High throughput genotyping for studying the genetic contributions to human disease"(HHSN268200782096C). Additional funding for the current research was provided by the National Cancer Institute (P01CA087969, P01CA055075), and the National Institute of Diabetes and Digestive and Kidney Diseases (R01DK058845). We thank the staff and participants of the NHS and HPFS for their dedication and commitment. INGI-CARLANTINO. Italian Network on Genetic Isolates – Carlantino. We thank Anna Morgan and Angela D'Eustacchio for technical support. We are grateful to the municipal administrators for their collaboration on the project and for logistic support. We thank all participants to this study. INGI-FVG. Italian Network on Genetic Isolates – Friuli Venezia-Giulia. We thank Anna Morgan and Angela D'Eustacchio for technical support. We are grateful to the municipal administrators for their collaboration on the project and for logistic support. We thank all participants to this study. 38 INGI-VAL BORBERA. Italian Network on Genetic Isolates – Val Borbera. We thank the inhabitants of the Val Borbera who made this study possible, the local administrations and the ASL-Novi Ligure (Al) for support. We also thank Clara Camaschella for data collection supervision and organization of the clinical data collection, Fiammetta Vigano` for technical help and Corrado Masciullo for building the analysis platform. The research was supported by funds from Compagnia di San Paolo, Torino, Italy; Fondazione Cariplo, Italy and Ministry of Health, Ricerca Finalizzata 2008 and 2011/2012, CCM 2010, PRIN 2009 and Telethon, Italy to DT. IPM. Mount Sinai BioMe Biobank Program. The Mount Sinai BioMe Biobank Program is supported by The Andrea and Charles Bronfman Philanthropies. KORA-F3 and F4. The genetic epidemiological work was funded by the NIH subcontract from the Children's Hospital, Boston, US, (H.E.W., I.M.H, prime grant 1 R01 DK075787-01A1), the German National Genome Research Net NGFN2 and NGFNplus (H.E.W. 01GS0823; WK project A3, number 01GS0834), the Munich Center of Health Sciences (MC Health) as part of LMUinnovativ, and by the Else KrönerFresenius-Stiftung (P48/08//A11/08; C.A.B., B.K.K; 2012_A147 to CAB and IMH.). The Genetic Epidemiology at the University of Regensburg received financial contributions from the BMBF (01ER1206 and 01ER1507). The kidney parameter measurements in F3 were funded by the Else Kröner-FreseniusStiftung (C.A.B., B.K.K.) and the Regensburg University Medical Center, Germany; in F4 by the University of Ulm, Germany (W.K.). Genome wide genotyping costs in F3 and F4 were in part funded by the Else Kröner-Fresenius-Stiftung (C.A.B., B.K.K.). De novo genotyping in F3 and F4 were funded by the Else Kröner-Fresenius-Stiftung (C.A.B., B.K.K.). The KORA research platform and the MONICA Augsburg studies were initiated and financed by the Helmholtz Zentrum München, German Research Center for Environmental Health, by the German Federal Ministry of Education and Research and by the State of Bavaria. Genotyping was performed in the Genome Analysis Center (GAC) of the Helmholtz Zentrum München. The LINUX platform for computation were funded by the University of Regensburg for the Department of Epidemiology and Preventive Medicine at the Regensburg University Medical Center. LIFELINES. The authors wish to acknowledge the services of the Lifelines Cohort Study, the contributing research centers delivering data to Lifelines, and all the study participants. Lifelines group authors: Behrooz Z Alizadeh1 , H Marike Boezen1 , Lude Franke2 , Pim van der Harst3 , Gerjan Navis4 , Marianne Rots5 , Harold Snieder1 , Morris Swertz2 , Bruce HR Wolffenbuttel6 and Cisca Wijmenga2 1. Department of Epidemiology, University of Groningen, University Medical Center Groningen, The Netherlands 2. Department of Genetics, University of Groningen, University Medical Center Groningen, The Netherlands 3. Department of Cardiology, University of Groningen, University Medical Center Groningen, The Netherlands 4. Department of Internal Medicine, Division of Nephrology, University of Groningen, University Medical Center Groningen, The Netherlands 5. Department of Medical Biology, University of Groningen, University Medical Center Groningen, The Netherlands 6. Department of Endocrinology, University of Groningen, University Medical Center Groningen, The Netherlands MESA. Multi-Ethnic Study of Atherosclerosis. University of Washington (N01-HC-95159),Regents of the University of California (N01-HC-95160), Columbia University (N01-HC-95161), Johns Hopkins University 39 (N01-HC-95162, N01-HC-95168), University of Minnesota (N01-HC-95163), Northwestern University (N01-HC-95164), Wake Forest University (N01-HC-95165), University of Vermont (N01-HC-95166), New England Medical Center (N01-HC-95167), Harbor-UCLA Research and Education Institute (N01-HC- 95169), Cedars-Sinai Medical Center (R01-HL-071205), University of Virginia (subcontract to R01-HL- 071205) MICROS. Microisolates in South Tyrol study. We owe a debt of gratitude to all participants. We thank the primary care practitioners R. Stocker, S. Waldner, T. Pizzecco, J. Plangger, U. Marcadent and the personnel of the Hospital of Silandro (Department of Laboratory Medicine) for their participation and collaboration in the research project. In South Tyrol, the study was supported by the Ministry of Health and Department of Educational Assistance, University and Research of the Autonomous Province of Bolzano, the South Tyrolean Sparkasse Foundation, and the European Union framework program 6 EUROSPAN project (contract no. LSHG-CT-2006-018947). NESDA. The Netherlands Study of Depression and Anxiety. The infrastructure for the NESDA study is funded through the Geestkracht programme of the Dutch Scientific Organization (ZON-MW, grant number 10-000-1002) and matching funds from participating universities and mental health care organizations. Genotyping in NESDA was funded by the Genetic Association Information Network (GAIN) of the Foundation for the US National Institutes of Health. NHS. Nurses' Health Study. The NHS/HPFS type 2 diabetes GWAS (U01HG004399) is a component of a collaborative project that includes 13 other GWAS (U01HG004738, U01HG004422, U01HG004402, U01HG004729, U01HG004726, U01HG004735, U01HG004415, U01HG004436, U01HG004423, U01HG004728, RFAHG006033; National Institute of Dental & Craniofacial Research: U01DE018993, U01DE018903) funded as part of the Gene Environment-Association Studies (GENEVA) under the NIH Genes, Environment and Health Initiative (GEI). Assistance with phenotype harmonization and genotype cleaning, as well as with general study coordination, was provided by the GENEVA Coordinating Center (U01HG004446). Assistance with data cleaning was provided by the National Center for Biotechnology Information. Genotyping was performed at the Broad Institute of MIT and Harvard, with funding support from the NIH GEI (U01HG04424), and Johns Hopkins University Center for Inherited Disease Research, with support from the NIH GEI (U01HG004438) and the NIH contract "High throughput genotyping for studying the genetic contributions to human disease"(HHSN268200782096C). The NHS renal function and albuminuria work was supported by DK66574. Additional funding for the current research was provided by the National Cancer Institute (P01CA087969, P01CA055075), and the National Institute of Diabetes and Digestive and Kidney Diseases (R01DK058845). We thank the staff and participants of the NHS and HPFS for their dedication and commitment. NSPHS. The Northern Swedish Population Health Study. The NSPHS was supported by grants from the Swedish Natural Sciences Research Council, the European Union through the EUROSPAN project (contract no. LSHG-CT-2006-018947), the Foundation for Strategic Research (SSF) and the Linneaus Centre for Bioinformatics (LCB). We are also grateful for the contribution of samples from the Medical Biobank in Umeå and for the contribution of the district nurse Svea Hennix in the Karesuando study. RS-I. The Rotterdam Study. The GWA study was funded by the Netherlands Organisation of Scientific Research NWO Investments (nr. 175.010.2005.011, 911-03-012), the Research Institute for Diseases in the Elderly (014-93-015; RIDE2), the Netherlands Genomics Initiative (NGI)/Netherlands Consortium for Healthy Aging (NCHA) project nr. 050-060-810. We thank Pascal Arp, Mila Jhamai, Dr Michael 40 Moorhouse, Marijn Verkerk, and Sander Bervoets for their help in creating the GWAS database. The Rotterdam Study is funded by Erasmus Medical Center and Erasmus University, Rotterdam, Netherlands Organization for the Health Research and Development (ZonMw), the Research Institute for Diseases in the Elderly (RIDE), the Ministry of Education, Culture and Science, the Ministry for Health, Welfare and Sports, the European Commission (DG XII), and the Municipality of Rotterdam. The authors are very grateful to the participants and staff from the Rotterdam Study, the participating general practitioners and the pharmacists. We would like to thank Dr. Tobias A. Knoch, Luc V. de Zeeuw, Anis Abuseiris, and Rob de Graaf as well as their institutions the Erasmus Computing Grid, Rotterdam, The Netherlands, and especially the national German MediGRID and Services@MediGRID part of the German D-Grid, both funded by the German Bundesministerium fuer Forschung und Technology under grants #01 AK 803 A-H and # 01 IG 07015 G, for access to their grid resources. Abbas Dehghan is supported by NWO grant (vici, 918-76-619). SAPALDIA. Swiss Study on Air Pollution and Lung Diseases in Adults. The SAPALDIA Team: Study directorate: T Rochat (p), NM Probst Hensch (e/g), N Künzli (e/exp), C Schindler (s), JM Gaspoz (c) Scientific team: JC Barthélémy (c), W Berger (g), R Bettschart (p), A Bircher (a), O Brändli (p), C Brombach (n), M Brutsche (p), L Burdet (p), M Frey (p), U Frey (pd), MW Gerbase (p), D Gold (e/c/p), E de Groot (c), W Karrer (p), R Keller (p), B Martin (pa), D Miedinger (o), U Neu (exp), L Nicod (p), M Pons (p), F Roche (c), T Rothe (p), E Russi (p), P Schmid-Grendelmeyer (a), A Schmidt-Trucksäss (pa), A Turk (p), J Schwartz (e), D. Stolz (p), P Straehl (exp), JM Tschopp (p), A von Eckardstein (cc), E Zemp Stutz (e). Scientific team at coordinating centers: M Adam (e/g), C Autenrieth (pa), PO Bridevaux (p), D Carballo (c), E Corradi (exp), I Curjuric (e), J Dratva (e), A Di Pasquale (s), E Dupuis Lozeron (s), E Fischer (e), M Germond (s), L Grize (s), D Keidel (s), S Kriemler (pa), A Kumar (g), M Imboden (g), N Maire (s), A Mehta (e), H Phuleria (exp), E Schaffner (s), GA Thun (g) A Ineichen (exp), M Ragettli (e), M Ritter (exp), T Schikowski (e), M Tarantino (s), M Tsai (exp) (a) allergology, (c) cardiology, (cc) clinical chemistry, (e) epidemiology, (exp) exposure, (g) genetic and molecular biology, (m) meteorology, (n) nutrition, (o) occupational health, (p) pneumology, (pa) physical activity, (pd) pediatrics, (s) statistics. Funding: The Swiss National Science Foundation (grants no 33CSCO-134276/1, 33CSCO-108796, 3247BO-104283, 3247BO-104288, 3247BO- 104284, 3247-065896, 3100-059302, 3200-052720, 3200-042532, 4026-028099), the Federal Office for Forest, Environment and Landscape, the Federal Office of Public Health, the Federal Office of Roads and Transport, the canton's government of Aargau, Basel-Stadt, Basel-Land, Geneva, Luzern, Ticino, Valais, and Zürich, the Swiss Lung League, the canton's Lung League of Basel Stadt/ Basel Landschaft, Geneva, Ticino, Valais and Zurich, SUVA, Freiwillige Akademische Gesellschaft, UBS Wealth Foundation, Talecris Biotherapeutics GmbH, Abbott Diagnostics, European Commission 018996 (GABRIEL), Wellcome Trust WT 084703MA. The study could not have been done without the help of the study participants, technical and administrative support and the medical teams and field workers at the local study sites. Local fieldworkers : Aarau: S Brun, G Giger, M Sperisen, M Stahel, Basel: C Bürli, C Dahler, N Oertli, I Harreh, F Karrer, G Novicic, N Wyttenbacher, Davos: A Saner, P Senn, R Winzeler, Geneva: F Bonfils, B Blicharz, C Landolt, J Rochat, Lugano: S Boccia, E Gehrig, MT Mandia, G Solari, B Viscardi, Montana: AP Bieri, C Darioly, M Maire, Payerne: F Ding, P Danieli A Vonnez, Wald: D Bodmer, E Hochstrasser, R Kunz, C Meier, J Rakic, U Schafroth, A Walder. Administrative staff: C Gabriel, R Gutknecht. SHIP and SHIP-TREND. The Study of Health in Pomerania. SHIP is part of the Community Medicine Research net of the University of Greifswald, Germany, which is funded by the Federal Ministry of Education and Research (grants no. 01ZZ9603, 01ZZ0103, and 01ZZ0403), the Ministry of Cultural Affairs as well as the Social Ministry of the Federal State of Mecklenburg-West Pomerania, and the network 41 'Greifswald Approach to Individualized Medicine (GANI_MED)' funded by the Federal Ministry of Education and Research (grant 03IS2061A). Genome-wide data have been supported by the Federal Ministry of Education and Research (grant no. 03ZIK012) and a joint grant from Siemens Healthcare, Erlangen, Germany and the Federal State of Mecklenburg- West Pomerania. The University of Greifswald is a member of the 'Center of Knowledge Interchange' program of the Siemens AG and the Caché Campus program of the InterSystems GmbH. The SHIP authors are grateful to Mario Stanke for the opportunity to use his Server Cluster for the SNP imputation as well as to Holger Prokisch and Thomas Meitinger (Helmholtz Zentrum München) for the genotyping of the SHIP-TREND cohort. TRAILS. TRacking Adolescents' Individual Lives. Trails is a collaborative project involving various departments of the University Medical Center and University of Groningen, the Erasmus University Medical Center Rotterdam, the University of Utrecht, the Radboud Medical Center Nijmegen, and the Parnassia Bavo group, all in the Netherlands. TRAILS has been financially supported by grants from the Netherlands Organization for Scientific Research NWO (Medical Research Council program grant GB-MW 940-38-011; ZonMW Brainpower grant 100-001-004; ZonMw Risk Behavior and Dependence grants 60- 60600-98-018 and 60-60600-97-118; ZonMw Culture and Health grant 261-98-710; Social Sciences Council medium-sized investment grants GB-MaGW 480-01-006 and GB-MaGW 480-07-001; Social Sciences Council project grants GB-MaGW 457-03-018, GB-MaGW 452-04-314, and GB-MaGW 452-06- 004; NWO large-sized investment grant 175.010.2003.005; NWO Longitudinal Survey and Panel Funding 481-08-013); the Sophia Foundation for Medical Research (projects 301 and 393), the Dutch Ministry of Justice (WODC), the European Science Foundation (EuroSTRESS project FP-006), and the participating universities. We are grateful to all adolescents, their parents and teachers who participated in this research and to everyone who worked on this project and made it possible. Statistical analyses were carried out on the Genetic Cluster Computer (http://www.geneticcluster.org), which is financially supported by the Netherlands Scientific Organization (NWO 480-05-003) along with a supplement from the Dutch Brain Foundation. WGHS. Women's Genome Health Study. The WGHS is supported by the National Heart, Lung, and Blood Institute (HL043851 and HL080467) and the National Cancer Institute (CA047988 and UM1CA182913), with collaborative scientific support and funding for genotyping provided by Amgen. YFS. Young Finns Study. The YFS has been financially supported by the Academy of Finland: grants 134309 (Eye), 126925, 121584, 124282, 129378 (Salve), 117787 (Gendi), and 41071 (Skidi), the Social Insurance Institution of Finland, Kuopio, Tampere and Turku University Hospital Medical Funds (grant 9M048 and 9N035 for TeLeht), Juho Vainio Foundation, Paavo Nurmi Foundation, Finnish Foundation of Cardiovascular Research and Finnish Cultural Foundation, Tampere Tuberculosis Foundation and Emil Aaltonen Foundation (T.L). The technical assistance in the statistical analyses by Ville Aalto and Irina Lisinen is acknowledged. ; Peer Reviewed

Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs. ; Novartis ; Eli Lilly and Company ; AstraZeneca ; AbbVie ; Pfizer UK ; Celgene ; Eisai ; Genentech ; Merck Sharp and Dohme ; Roche ; Cancer Research UK ; Government of Canada ; Array BioPharma ; Genome Canada ; National Institutes of Health ; European Commission ; Ministère de l'Économie, de l'Innovation et des Exportations du Québec ; Seventh Framework Programme ; Canadian Institutes of Health Research