272 research outputs found
Exercise Training Amount and Intensity Effects on Metabolic Syndrome (From Studies of a Targeted Risk Reduction Intervention through Defined Exercise)
Although exercise improves individual risk factors of the metabolic syndrome (MS), there is little research on the effect of exercise on MS as a whole. The objective of this study was to determine how much exercise is recommended to reduce the prevalence of MS. Of 334 subjects randomized, 227 finished and 171 (80 women, 91 men) had complete data for all 5 Adult Treatment Panel III- defined MS risk factors and were included in this analysis. Subjects were randomly assigned to a six-month control or 1 of 3 eight-month exercise training groups: 1) low-amount/moderate-intensity (equivalent to walking ~19 km/week); 2) low-amount/vigorous-intensity (equivalent to jogging ~19 km/week); 3) high-amount/vigorous-intensity (equivalent to jogging ~32 km/week). The low- amount/moderate-intensity exercise prescription improved MS relative to inactive controls (p<0.05). However, the same amount of exercise at a vigorous intensity was not significantly better than inactive controls, suggesting that lower intensity exercise may be more effective in improving MS. The high-amount/vigorous-intensity group improved MS relative to controls (p<0.0001), the low- amount/vigorous-intensity group (p=0.001), and the moderate intensity group (p=0.07), suggesting an exercise dose effect. In conclusion, a modest amount of moderate intensity exercise, in the absence of dietary changes, significantly improved MS and thus supports the recommendation that adults get 30 minutes of moderate intensity exercise every day. A higher amount of vigorous exercise was shown to have greater and more widespread benefits. Finally, there is an indication that moderate intensity may be better than vigorous intensity exercise for improving MS. Originally published American Journal of Cardiology, Vol. 100, No. 12, Dec 200
Mapping SF-36 onto the EQ-5D index: how reliable is the relationship?
<p>Abstract</p> <p>Background</p> <p>Mapping from health status measures onto generic preference-based measures is becoming a common solution when health state utility values are not directly available for economic evaluation. However the accuracy and reliability of the models employed is largely untested, and there is little evidence of their suitability in patient datasets. This paper examines whether mapping approaches are reliable and accurate in terms of their predictions for a large and varied UK patient dataset.</p> <p>Methods</p> <p>SF-36 dimension scores are mapped onto the EQ-5D index using a number of different model specifications. The predicted EQ-5D scores for subsets of the sample are compared across inpatient and outpatient settings and medical conditions. This paper compares the results to those obtained from existing mapping functions.</p> <p>Results</p> <p>The model including SF-36 dimensions, squared and interaction terms estimated using random effects GLS has the most accurate predictions of all models estimated here and existing mapping functions as indicated by MAE (0.127) and MSE (0.030). Mean absolute error in predictions by EQ-5D utility range increases with severity for our models (0.085 to 0.34) and for existing mapping functions (0.123 to 0.272).</p> <p>Conclusion</p> <p>Our results suggest that models mapping the SF-36 onto the EQ-5D have similar predictions across inpatient and outpatient setting and medical conditions. However, the models overpredict for more severe EQ-5D states; this problem is also present in the existing mapping functions.</p
In silico APC/C substrate discovery reveals cell cycle-dependent degradation of UHRF1 and other chromatin regulators
The anaphase-promoting complex/cyclosome (APC/C) is an E3 ubiquitin ligase and critical regulator of cell cycle progression. Despite its vital role, it has remained challenging to globally map APC/C substrates. By combining orthogonal features of known substrates, we predicted APC/C substrates in silico. This analysis identified many known substrates and suggested numerous candidates. Unexpectedly, chromatin regulatory proteins are enriched among putative substrates, and we show experimentally that several chromatin proteins bind APC/C, oscillate during the cell cycle, and are degraded following APC/C activation, consistent with being direct APC/C substrates. Additional analysis revealed detailed mechanisms of ubiquitylation for UHRF1, a key chromatin regulator involved in histone ubiquitylation and DNA methylation maintenance. Disrupting UHRF1 degradation at mitotic exit accelerates G1-phase cell cycle progression and perturbs global DNA methylation patterning in the genome. We conclude that APC/C coordinates crosstalk between cell cycle and chromatin regulatory proteins. This has potential consequences in normal cell physiology, where the chromatin environment changes depending on proliferative state, as well as in disease. Copyright
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Proceedings of the 3rd Biennial Conference of the Society for Implementation Research Collaboration (SIRC) 2015: advancing efficient methodologies through community partnerships and team science : Seattle, WA, USA. 24-26 September 2015.
Introduction to the 3rd Biennial Conference of the Society for Implementation Research Collaboration: advancing efficient methodologies through team science and community partnerships Cara Lewis, Doyanne Darnell, Suzanne Kerns, Maria Monroe-DeVita, Sara J. Landes, Aaron R. Lyon, Cameo Stanick, Shannon Dorsey, Jill Locke, Brigid Marriott, Ajeng Puspitasari, Caitlin Dorsey, Karin Hendricks, Andria Pierson, Phil Fizur, Katherine A. Comtois A1: A behavioral economic perspective on adoption, implementation, and sustainment of evidence-based interventions Lawrence A. Palinkas A2: Towards making scale up of evidence-based practices in child welfare systems more efficient and affordable Patricia Chamberlain A3: Mixed method examination of strategic leadership for evidence-based practice implementation Gregory A. Aarons, Amy E. Green, Mark. G. Ehrhart, Elise M. Trott, Cathleen E. Willging A4: Implementing practice change in Federally Qualified Health Centers: Learning from leaders’ experiences Maria E. Fernandez, Nicholas H. Woolf, Shuting (Lily) Liang, Natalia I. Heredia, Michelle Kegler, Betsy Risendal, Andrea Dwyer, Vicki Young, Dayna Campbell, Michelle Carvalho, Yvonne Kellar-Guenther A3: Mixed method examination of strategic leadership for evidence-based practice implementation Gregory A. Aarons, Amy E. Green, Mark. G. Ehrhart, Elise M. Trott, Cathleen E. Willging A4: Implementing practice change in Federally Qualified Health Centers: Learning from leaders’ experiences Maria E. Fernandez, Nicholas H. Woolf, Shuting (Lily) Liang, Natalia I. Heredia, Michelle Kegler, Betsy Risendal, Andrea Dwyer, Vicki Young, Dayna Campbell, Michelle Carvalho, Yvonne Kellar-Guenther A5: Efficient synthesis: Using qualitative comparative analysis and the Consolidated Framework for Implementation Research across diverse studies Laura J. Damschroder, Julie C. Lowery A6: Establishing a veterans engagement group to empower patients and inform Veterans Affairs (VA) health services research Sarah S. Ono, Kathleen F. Carlson, Erika K. Cottrell, Maya E. O’Neil, Travis L. Lovejoy A7: Building patient-practitioner partnerships in community oncology settings to implement behavioral interventions for anxious and depressed cancer survivors Joanna J. Arch, Jill L. Mitchell A8: Tailoring a Cognitive Behavioral Therapy implementation protocol using mixed methods, conjoint analysis, and implementation teams Cara C. Lewis, Brigid R. Marriott, Kelli Scott A9: Wraparound Structured Assessment and Review (WrapSTAR): An efficient, yet comprehensive approach to Wraparound implementation evaluation Jennifer Schurer Coldiron, Eric J. Bruns, Alyssa N. Hook A10: Improving the efficiency of standardized patient assessment of clinician fidelity: A comparison of automated actor-based and manual clinician-based ratings Benjamin C. Graham, Katelin Jordan A11: Measuring fidelity on the cheap Rochelle F. Hanson, Angela Moreland, Benjamin E. Saunders, Heidi S. Resnick A12: Leveraging routine clinical materials to assess fidelity to an evidence-based psychotherapy Shannon Wiltsey Stirman, Cassidy A. Gutner, Jennifer Gamarra, Dawne Vogt, Michael Suvak, Jennifer Schuster Wachen, Katherine Dondanville, Jeffrey S. Yarvis, Jim Mintz, Alan L. Peterson, Elisa V. Borah, Brett T. Litz, Alma Molino, Stacey Young McCaughanPatricia A. Resick A13: The video vignette survey: An efficient process for gathering diverse community opinions to inform an intervention Nancy Pandhi, Nora Jacobson, Neftali Serrano, Armando Hernandez, Elizabeth Zeidler- Schreiter, Natalie Wietfeldt, Zaher Karp A14: Using integrated administrative data to evaluate implementation of a behavioral health and trauma screening for children and youth in foster care Michael D. Pullmann, Barbara Lucenko, Bridget Pavelle, Jacqueline A. Uomoto, Andrea Negrete, Molly Cevasco, Suzanne E. U. Kerns A15: Intermediary organizations as a vehicle to promote efficiency and speed of implementation Robert P. Franks, Christopher Bory A16: Applying the Consolidated Framework for Implementation Research constructs directly to qualitative data: The power of implementation science in action Edward J. Miech, Teresa M. Damush A17: Efficient and effective scaling-up, screening, brief interventions, and referrals to treatment (SBIRT) training: a snowball implementation model Jason Satterfield, Derek Satre, Maria Wamsley, Patrick Yuan, Patricia O’Sullivan A18: Matching models of implementation to system needs and capacities: addressing the human factor Helen Best, Susan Velasquez A19: Agency characteristics that facilitate efficient and successful implementation efforts Miya Barnett, Lauren Brookman-Frazee, Jennifer Regan, Nicole Stadnick, Alison Hamilton, Anna Lau A20: Rapid assessment process: Application to the Prevention and Early Intervention transformation in Los Angeles County Jennifer Regan, Alison Hamilton, Nicole Stadnick, Miya Barnett, Anna Lau, Lauren Brookman-Frazee A21: The development of the Evidence-Based Practice-Concordant Care Assessment: An assessment tool to examine treatment strategies across practices Nicole Stadnick, Anna Lau, Miya Barnett, Jennifer Regan, Scott Roesch, Lauren Brookman-Frazee A22: Refining a compilation of discrete implementation strategies and determining their importance and feasibility Byron J. Powell, Thomas J. Waltz, Matthew J. Chinman, Laura Damschroder, Jeffrey L. Smith, Monica M. Matthieu, Enola K. Proctor, JoAnn E. Kirchner A23: Structuring complex recommendations: Methods and general findings Thomas J. Waltz, Byron J. Powell, Matthew J. Chinman, Laura J. Damschroder, Jeffrey L. Smith, Monica J. Matthieu, Enola K. Proctor, JoAnn E. Kirchner A24: Implementing prolonged exposure for post-traumatic stress disorder in the Department of Veterans Affairs: Expert recommendations from the Expert Recommendations for Implementing Change (ERIC) project Monica M. Matthieu, Craig S. Rosen, Thomas J. Waltz, Byron J. Powell, Matthew J. Chinman, Laura J. Damschroder, Jeffrey L. Smith, Enola K. Proctor, JoAnn E. Kirchner A25: When readiness is a luxury: Co-designing a risk assessment and quality assurance process with violence prevention frontline workers in Seattle, WA Sarah C. Walker, Asia S. Bishop, Mariko Lockhart A26: Implementation potential of structured recidivism risk assessments with justice- involved veterans: Qualitative perspectives from providers Allison L. Rodriguez, Luisa Manfredi, Andrea Nevedal, Joel Rosenthal, Daniel M. Blonigen A27: Developing empirically informed readiness measures for providers and agencies for the Family Check-Up using a mixed methods approach Anne M. Mauricio, Thomas D. Dishion, Jenna Rudo-Stern, Justin D. Smith A28: Pebbles, rocks, and boulders: The implementation of a school-based social engagement intervention for children with autism Jill Locke, Courtney Benjamin Wolk, Colleen Harker, Anne Olsen, Travis Shingledecker, Frances Barg, David Mandell, Rinad S. Beidas A29: Problem Solving Teletherapy (PST.Net): A stakeholder analysis examining the feasibility and acceptability of teletherapy in community based aging services Marissa C. Hansen, Maria P. Aranda, Isabel Torres-Vigil A30: A case of collaborative intervention design eventuating in behavior therapy sustainment and diffusion Bryan Hartzler A31: Implementation of suicide risk prevention in an integrated delivery system: Mental health specialty services Bradley Steinfeld, Tory Gildred, Zandrea Harlin, Fredric Shephard A32: Implementation team, checklist, evaluation, and feedback (ICED): A step-by-step approach to Dialectical Behavior Therapy program implementation Matthew S. Ditty, Andrea Doyle, John A. Bickel III, Katharine Cristaudo A33: The challenges in implementing muliple evidence-based practices in a community mental health setting Dan Fox, Sonia Combs A34: Using electronic health record technology to promote and support evidence-based practice assessment and treatment intervention David H. Lischner A35: Are existing frameworks adequate for measuring implementation outcomes? Results from a new simulation methodology Richard A. Van Dorn, Stephen J. Tueller, Jesse M. Hinde, Georgia T. Karuntzos A36: Taking global local: Evaluating training of Washington State clinicians in a modularized cogntive behavioral therapy approach designed for low-resource settings Maria Monroe-DeVita, Roselyn Peterson, Doyanne Darnell, Lucy Berliner, Shannon Dorsey, Laura K. Murray A37: Attitudes toward evidence-based practices across therapeutic orientations Yevgeny Botanov, Beverly Kikuta, Tianying Chen, Marivi Navarro-Haro, Anthony DuBose, Kathryn E. Korslund, Marsha M. Linehan A38: Predicting the use of an evidence-based intervention for autism in birth-to-three programs Colleen M. Harker, Elizabeth A. Karp, Sarah R. Edmunds, Lisa V. Ibañez, Wendy L. Stone A39: Supervision practices and improved fidelity across evidence-based practices: A literature review Mimi Choy-Brown A40: Beyond symptom tracking: clinician perceptions of a hybrid measurement feedback system for monitoring treatment fidelity and client progress Jack H. Andrews, Benjamin D. Johnides, Estee M. Hausman, Kristin M. Hawley A41: A guideline decision support tool: From creation to implementation Beth Prusaczyk, Alex Ramsey, Ana Baumann, Graham Colditz, Enola K. Proctor A42: Dabblers, bedazzlers, or total makeovers: Clinician modification of a common elements cognitive behavioral therapy approach Rosemary D. Meza, Shannon Dorsey, Shannon Wiltsey-Stirman, Georganna Sedlar, Leah Lucid A43: Characterization of context and its role in implementation: The impact of structure, infrastructure, and metastructure Caitlin Dorsey, Brigid Marriott, Nelson Zounlome, Cara Lewis A44: Effects of consultation method on implementation of cognitive processing therapy for post-traumatic stress disorder Cassidy A. Gutner, Candice M. Monson, Norman Shields, Marta Mastlej, Meredith SH Landy, Jeanine Lane, Shannon Wiltsey Stirman A45: Cross-validation of the Implementation Leadership Scale factor structure in child welfare service organizations Natalie K. Finn, Elisa M. Torres, Mark. G. Ehrhart, Gregory A. Aarons A46: Sustainability of integrated smoking cessation care in Veterans Affairs posttraumatic stress disorder clinics: A qualitative analysis of focus group data from learning collaborative participants Carol A. Malte, Aline Lott, Andrew J. Saxon A47: Key characteristics of effective mental health trainers: The creation of the Measure of Effective Attributes of Trainers (MEAT) Meredith Boyd, Kelli Scott, Cara C. Lewis A48: Coaching to improve teacher implementation of evidence-based practices (EBPs) Jennifer D. Pierce A49: Factors influencing the implementation of peer-led health promotion programs targeting seniors: A literature review Agathe Lorthios-Guilledroit, Lucie Richard, Johanne Filiatrault A50: Developing treatment fidelity rating systems for psychotherapy research: Recommendations and lessons learned Kevin Hallgren, Shirley Crotwell, Rosa Muñoz, Becky Gius, Benjamin Ladd, Barbara McCrady, Elizabeth Epstein A51: Rapid translation of alcohol prevention science John D. Clapp, Danielle E. Ruderman A52: Factors implicated in successful implementation: evidence to inform improved implementation from high and low-income countries Melanie Barwick, Raluca Barac, Stanley Zlotkin, Laila Salim, Marnie Davidson A53: Tracking implementation strategies prospectively: A practical approach Alicia C. Bunger, Byron J. Powell, Hillary A. Robertson A54: Trained but not implementing: the need for effective implementation planning tools Christopher Botsko A55: Evidence, context, and facilitation variables related to implementation of Dialectical Behavior Therapy: Qualitative results from a mixed methods inquiry in the Department of Veterans Affairs Sara J. Landes, Brandy N. Smith, Allison L. Rodriguez, Lindsay R. Trent, Monica M. Matthieu A56: Learning from implementation as usual in children’s mental health Byron J. Powell, Enola K. Proctor A57: Rates and predictors of implementation after Dialectical Behavior Therapy Intensive Training Melanie S. Harned, Marivi Navarro-Haro, Kathryn E. Korslund, Tianying Chen, Anthony DuBose, André Ivanoff, Marsha M. Linehan A58: Socio-contextual determinants of research evidence use in public-youth systems of care Antonio R. Garcia, Minseop Kim, Lawrence A. Palinkas, Lonnie Snowden, John Landsverk A59: Community resource mapping to integrate evidence-based depression treatment in primary care in Brazil: A pilot project Annika C. Sweetland, Maria Jose Fernandes, Edilson Santos, Cristiane Duarte, Afrânio Kritski, Noa Krawczyk, Caitlin Nelligan, Milton L. Wainberg A60: The use of concept mapping to efficiently identify determinants of implementation in the National Institute of Health--President’s Emergent Plan for AIDS Relief Prevention of Mother to Child HIV Transmission Implementation Science Alliance Gregory A. Aarons, David H. Sommerfeld, Benjamin Chi, Echezona Ezeanolue, Rachel Sturke, Lydia Kline, Laura Guay, George Siberry A61: Longitudinal remote consultation for implementing collaborative care for depression Ian M. Bennett, Rinad Beidas, Rachel Gold, Johnny Mao, Diane Powers, Mindy Vredevoogd, Jurgen Unutzer A62: Integrating a peer coach model to support program implementation and ensure long- term sustainability of the Incredible Years in community-based settings Jennifer Schroeder, Lane Volpe, Julie Steffen A63: Efficient sustainability: Existing community based supervisors as evidence-based treatment supports Shannon Dorsey, Michael D Pullmann, Suzanne E. U. Kerns, Nathaniel Jungbluth, Lucy Berliner, Kelly Thompson, Eliza Segell A64: Establishment of a national practice-based implementation network to accelerate adoption of evidence-based and best practices Pearl McGee-Vincent, Nancy Liu, Robyn Walser, Jennifer Runnals, R. Keith Shaw, Sara J. Landes, Craig Rosen, Janet Schmidt, Patrick Calhoun A65: Facilitation as a mechanism of implementation in a practice-based implementation network: Improving care in a Department of Veterans Affairs post-traumatic stress disorder outpatient clinic Ruth L. Varkovitzky, Sara J. Landes A66: The ACT SMART Toolkit: An implementation strategy for community-based organizations providing services to children with autism spectrum disorder Amy Drahota, Jonathan I. Martinez, Brigitte Brikho, Rosemary Meza, Aubyn C. Stahmer, Gregory A. Aarons A67: Supporting Policy In Health with Research: An intervention trial (SPIRIT) - protocol and early findings Anna Williamson A68: From evidence based practice initiatives to infrastructure: Lessons learned from a public behavioral health system’s efforts to promote evidence based practices Ronnie M. Rubin, Byron J. Powell, Matthew O. Hurford, Shawna L. Weaver, Rinad S. Beidas, David S. Mandell, Arthur C. Evans A69: Applying the policy ecology model to Philadelphia’s behavioral health transformation efforts Byron J. Powell, Rinad S. Beidas, Ronnie M. Rubin, Rebecca E. Stewart, Courtney Benjamin Wolk, Samantha L. Matlin, Shawna Weaver, Matthew O. Hurford, Arthur C. Evans, Trevor R. Hadley, David S. Mandell A70: A model for providing methodological expertise to advance dissemination and implementation of health discoveries in Clinical and Translational Science Award institutions Donald R. Gerke, Beth Prusaczyk, Ana Baumann, Ericka M. Lewis, Enola K. Proctor A71: Establishing a research agenda for the Triple P Implementation Framework Jenna McWilliam, Jacquie Brown, Michelle Tucker A72: Cheap and fast, but what is “best?”: Examining implementation outcomes across sites in a state-wide scaled-up evidence-based walking program, Walk With Ease Kathleen P Conte A73: Measurement feedback systems in mental health: Initial review of capabilities and characteristics Aaron R. Lyon, Meredith Boyd, Abigail Melvin, Cara C. Lewis, Freda Liu, Nathaniel Jungbluth A74: A qualitative investigation of case managers’ attitudes toward implementation of a measurement feedback system in a public mental health system for youth Amelia Kotte, Kaitlin A. Hill, Albert C. Mah, Priya A. Korathu-Larson, Janelle R. Au, Sonia Izmirian, Scott Keir, Brad J. Nakamura, Charmaine K. Higa-McMillan A75: Multiple pathways to sustainability: Using Qualitative Comparative Analysis to uncover the necessary and sufficient conditions for successful community-based implementation Brittany Rhoades Cooper, Angie Funaiole, Eleanor Dizon A76: Prescribers’ perspectives on opioids and benzodiazepines and medication alerts to reduce co-prescribing of these medications Eric J. Hawkins, Carol A. Malte, Hildi J. Hagedorn, Douglas Berger, Anissa Frank, Aline Lott, Carol E. Achtmeyer, Anthony J. Mariano, Andrew J. Saxon A77: Adaptation of Coordinated Anxiety Learning and Management for comorbid anxiety and substance use disorders: Delivery of evidence-based treatment for anxiety in addictions treatment centers Kate Wolitzky-Taylor, Richard Rawson, Richard Ries, Peter Roy-Byrne, Michelle Craske A78: Opportunities and challenges of measuring program implementation with online surveys Dena Simmons, Catalina Torrente, Lori Nathanson, Grace Carroll A79: Observational assessment of fidelity to a family-centered prevention program: Effectiveness and efficiency Justin D. Smith, Kimbree Brown, Karina Ramos, Nicole Thornton, Thomas J. Dishion, Elizabeth A. Stormshak, Daniel S. Shaw, Melvin N. Wilson A80: Strategies and challenges in housing first fidelity: A multistate qualitative analysis Mimi Choy-Brown, Emmy Tiderington, Bikki Tran Smith, Deborah K. Padgett A81: Procurement and contracting as an implementation strategy: Getting To Outcomes® contracting Ronnie M. Rubin, Marilyn L. Ray, Abraham Wandersman, Andrea Lamont, Gordon Hannah, Kassandra A. Alia, Matthew O. Hurford, Arthur C. Evans A82: Web-based feedback to aid successful implementation: The interactive Stages of Implementation Completion (SIC)TM tool Lisa Saldana, Holle Schaper, Mark Campbell, Patricia Chamberlain A83: Efficient methodologies for monitoring fidelity in routine implementation: Lessons from the Allentown Social Emotional Learning Initiative Valerie B. Shapiro, B.K. Elizabeth Kim, Jennifer L. Fleming, Paul A. LeBuffe A84: The Society for Implementation Research Collaboration (SIRC) implementation development workshop: Results from a new methodology for enhancing implementation science proposals Sara J. Landes, Cara C. Lewis, Allison L. Rodriguez, Brigid R. Marriott, Katherine Anne Comtois A85: An update on the Society for Implementation Research Collaboration (SIRC) Instrument Review Projec
Rare coding variants and X-linked loci associated with age at menarche.
More than 100 loci have been identified for age at menarche by genome-wide association studies; however, collectively these explain only ∼3% of the trait variance. Here we test two overlooked sources of variation in 192,974 European ancestry women: low-frequency protein-coding variants and X-chromosome variants. Five missense/nonsense variants (in ALMS1/LAMB2/TNRC6A/TACR3/PRKAG1) are associated with age at menarche (minor allele frequencies 0.08-4.6%; effect sizes 0.08-1.25 years per allele; P<5 × 10(-8)). In addition, we identify common X-chromosome loci at IGSF1 (rs762080, P=9.4 × 10(-13)) and FAAH2 (rs5914101, P=4.9 × 10(-10)). Highlighted genes implicate cellular energy homeostasis, post-transcriptional gene silencing and fatty-acid amide signalling. A frequently reported mutation in TACR3 for idiopathic hypogonatrophic hypogonadism (p.W275X) is associated with 1.25-year-later menarche (P=2.8 × 10(-11)), illustrating the utility of population studies to estimate the penetrance of reportedly pathogenic mutations. Collectively, these novel variants explain ∼0.5% variance, indicating that these overlooked sources of variation do not substantially explain the 'missing heritability' of this complex trait.UK sponsors (see article for overseas ones):
This work made use of data and samples generated by the 1958 Birth Cohort (NCDS). Access to these resources was enabled via the 58READIE Project funded by Wellcome Trust and Medical Research Council (grant numbers WT095219MA and G1001799). A full list of the financial, institutional and personal contributions to the development of the 1958 Birth Cohort Biomedical resource is available at http://www2.le.ac.uk/projects/birthcohort. Genotyping was undertaken as part of the Wellcome Trust Case-Control Consortium (WTCCC) under Wellcome Trust award 076113, and a full list of the investigators who contributed to the generation of the data is available at www.wtccc.org.uk
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The Fenland Study is funded by the Wellcome Trust and the Medical Research Council, as well as by the Support for Science Funding programme and CamStrad.
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SIBS - CRUK ref: C1287/A8459 SEARCH - CRUK ref: A490/A10124 EMBRACE is supported by Cancer Research UK Grants C1287/A10118, C1287/A16563 and C1287/A17523. Genotyping was supported by Cancer Research - UK grant C12292/A11174D
and C8197/A16565. Gareth Evans and Fiona Lalloo are supported by an NIHR grant to the Biomedical Research Centre, Manchester.
The Investigators at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust are supported by an NIHR grant to the Biomedical Research Centre at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust. Ros Eeles and Elizabeth Bancroft are supported by Cancer Research UK Grant C5047/A8385.
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Generation Scotland - Scottish Executive Health Department, Chief Scientist Office, grant number CZD/16/6. Exome array genotyping for GS:SFHS was funded by the Medical Research Council UK. 23andMe - This work was supported in part by NIH Award 2R44HG006981-02 from the National Human Genome Research Institute.This is the final version of the article. It first appeared from NPG via http://dx.doi.org/10.1038/ncomms875
Healthy Lifestyle and Leukocyte Telomere Length in U.S. Women
Context: Whether a healthy lifestyle may be associated with longer telomere length is largely unknown. Objectives: To examine healthy lifestyle practices, which are primary prevention measures against major age-related chronic diseases, in relation to leukocyte telomere length. Design and Setting: Cross-sectional analysis in the Nurses' Health Study (NHS). Participants: The population consisted of 5,862 women who participated in multiple prospective case-control studies within the NHS cohort. Z scores of leukocyte telomere length were derived within each case-control study. Based on prior work, we defined low-risk or healthy categories for five major modifiable factors assessed in 1988 or 1990: non-current smoking, maintaining a healthy body weight (body mass index in 18.5-24.9 kg/m(2)), engaging in regular moderate or vigorous physical activities (>= 150 minutes/week), drinking alcohol in moderation (1 drink/week to,2 drinks/day), and eating a healthy diet (Alternate Healthy Eating Index score in top 50%). We calculated difference (%) of the z scores contrasting low-risk groups with reference groups to evaluate the association of interest. Results: Although none of the individual low-risk factors was significantly associated with larger leukocyte telomere length z scores, we observed a significant, positive relationship between the number of low-risk factors and the z scores. In comparison with women who had zero low-risk factors (1.9% of the total population) and were, therefore, considered the least healthy group, the leukocyte telomere length z scores were 16.4%, 22.1%, 28.7%, 22.6%, and 31.2% (P for trend = 0.015) higher for women who had 1 to 5 low-risk factors, respectively. Conclusions: Adherence to a healthy lifestyle, defined by major modifiable risk factors, was associated with longer telomere length in leukocytes
Coding Variation in ANGPTL4, LPL, and SVEP1 and the Risk of Coronary Disease.
BACKGROUND: The discovery of low-frequency coding variants affecting the risk of coronary artery disease has facilitated the identification of therapeutic targets. METHODS: Through DNA genotyping, we tested 54,003 coding-sequence variants covering 13,715 human genes in up to 72,868 patients with coronary artery disease and 120,770 controls who did not have coronary artery disease. Through DNA sequencing, we studied the effects of loss-of-function mutations in selected genes. RESULTS: We confirmed previously observed significant associations between coronary artery disease and low-frequency missense variants in the genes LPA and PCSK9. We also found significant associations between coronary artery disease and low-frequency missense variants in the genes SVEP1 (p.D2702G; minor-allele frequency, 3.60%; odds ratio for disease, 1.14; P=4.2×10(-10)) and ANGPTL4 (p.E40K; minor-allele frequency, 2.01%; odds ratio, 0.86; P=4.0×10(-8)), which encodes angiopoietin-like 4. Through sequencing of ANGPTL4, we identified 9 carriers of loss-of-function mutations among 6924 patients with myocardial infarction, as compared with 19 carriers among 6834 controls (odds ratio, 0.47; P=0.04); carriers of ANGPTL4 loss-of-function alleles had triglyceride levels that were 35% lower than the levels among persons who did not carry a loss-of-function allele (P=0.003). ANGPTL4 inhibits lipoprotein lipase; we therefore searched for mutations in LPL and identified a loss-of-function variant that was associated with an increased risk of coronary artery disease (p.D36N; minor-allele frequency, 1.9%; odds ratio, 1.13; P=2.0×10(-4)) and a gain-of-function variant that was associated with protection from coronary artery disease (p.S447*; minor-allele frequency, 9.9%; odds ratio, 0.94; P=2.5×10(-7)). CONCLUSIONS: We found that carriers of loss-of-function mutations in ANGPTL4 had triglyceride levels that were lower than those among noncarriers; these mutations were also associated with protection from coronary artery disease. (Funded by the National Institutes of Health and others.).Supported by a career development award from the National Heart, Lung, and Blood Institute, National Institutes of Health (NIH) (K08HL114642 to Dr. Stitziel) and by the Foundation for Barnes–Jewish Hospital. Dr. Peloso is supported by the National Heart, Lung, and Blood Institute of the NIH (award number K01HL125751). Dr. Kathiresan is supported by a Research Scholar award from the Massachusetts General Hospital, the Donovan Family Foundation, grants from the NIH (R01HL107816 and R01HL127564), a grant from Fondation Leducq, and an investigator-initiated grant from Merck. Dr. Merlini was supported by a grant from the Italian Ministry of Health (RFPS-2007-3-644382). Drs. Ardissino and Marziliano were supported by Regione Emilia Romagna Area 1 Grants. Drs. Farrall and Watkins acknowledge the support of the Wellcome Trust core award (090532/Z/09/Z), the British Heart Foundation (BHF) Centre of Research Excellence. Dr. Schick is supported in part by a grant from the National Cancer Institute (R25CA094880). Dr. Goel acknowledges EU FP7 & Wellcome Trust Institutional strategic support fund. Dr. Deloukas’s work forms part of the research themes contributing to the translational research portfolio of Barts Cardiovascular Biomedical Research Unit, which is supported and funded by the National Institute for Health Research (NIHR). Drs. Webb and Samani are funded by the British Heart Foundation, and Dr. Samani is an NIHR Senior Investigator. Dr. Masca was supported by the NIHR Leicester Cardiovascular Biomedical Research Unit (BRU), and this work forms part of the portfolio of research supported by the BRU. Dr. Won was supported by a postdoctoral award from the American Heart Association (15POST23280019). Dr. McCarthy is a Wellcome Trust Senior Investigator (098381) and an NIHR Senior Investigator. Dr. Danesh is a British Heart Foundation Professor, European Research Council Senior Investigator, and NIHR Senior Investigator. Drs. Erdmann, Webb, Samani, and Schunkert are supported by the FP7 European Union project CVgenes@ target (261123) and the Fondation Leducq (CADgenomics, 12CVD02). Drs. Erdmann and Schunkert are also supported by the German Federal Ministry of Education and Research e:Med program (e:AtheroSysMed and sysINFLAME), and Deutsche Forschungsgemeinschaft cluster of excellence “Inflammation at Interfaces” and SFB 1123. Dr. Kessler received a DZHK Rotation Grant. The analysis was funded, in part, by a Programme Grant from the BHF (RG/14/5/30893 to Dr. Deloukas). Additional funding is listed in the Supplementary Appendix.This is the author accepted manuscript. The final version is available from the Massachusetts Medical Society via http://dx.doi.org/10.1056/NEJMoa150765
Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits
Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting for environment in genetic analyses. Our results suggest that tobacco smoking may alter the genetic susceptibility to overall adiposity and body fat distribution.Peer reviewe
Gene-Educational attainment interactions in a Multi-Population Genome-Wide Meta-Analysis Identify Novel Lipid Loci
Trans-ancestry meta-analyses identify rare and common variants associated with blood pressure and hypertension
High blood pressure is a major risk factor for cardiovascular disease and premature death. However, there is limited knowledge on specific causal genes and pathways. To better understand the genetics of blood pressure, we genotyped 242,296 rare, low-frequency and common genetic variants in up to ~192,000 individuals, and used ~155,063 samples for independent replication. We identified 31 novel blood pressure or hypertension associated genetic regions in the general population, including three rare missense variants in RBM47, COL21A1 and RRAS with larger effects (>1.5mmHg/allele) than common variants. Multiple rare, nonsense and missense variant associations were found in A2ML1 and a low-frequency nonsense variant in ENPEP was identified. Our data extend the spectrum of allelic variation underlying blood pressure traits and hypertension, provide new insights into the pathophysiology of hypertension and indicate new targets for clinical intervention
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