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Weight reduction continues to be first-line therapy in the treatment of hypertension (HTN). However, the long-term effect of bariatric malabsorptive surgical techniques such as Roux-en-Y Gastric Bypass (RYGB) surgery in the management of hypertension (HTN) is less clear. African Americans (AA) are disproportionately affected by obesity and hypertension and have inconsistent outcomes after bariatric surgery (BS). Despite a plethora of bariatric literature, data about characteristics of a predominantly AA bariatric hypertensive cohort including hypertension in obese (HIO) are scarce and underreported. The aims of this study were, (1) to describe the preoperative clinical characteristics of HIO with respect to HTN status and age, and (2) to identify predictors of HTN resolution one year after RYGB surgery in an AA bariatric cohort enrolled at the Howard University Center for Wellness and Weight Loss Surgery (HUCWWS). In the review of 169 AA bariatric patients, the average BMI was 48.50 kg/m2 and the average age was 43.86 years. Obese hypertensive patients were older (46 years vs. 37.89 years; p

Body composition is often altered in psychiatric disorders. Using genome-wide common genetic variation data, we calculate sex-specific genetic correlations amongst body fat %, fat mass, fat-free mass, physical activity, glycemic traits and 17 psychiatric traits (up to N = 217,568). Two patterns emerge: (1) anorexia nervosa, schizophrenia, obsessive-compulsive disorder, and education years are negatively genetically correlated with body fat % and fat-free mass, whereas (2) attention-deficit/hyperactivity disorder (ADHD), alcohol dependence, insomnia, and heavy smoking are positively correlated. Anorexia nervosa shows a stronger genetic correlation with body fat % in females, whereas education years is more strongly correlated with fat mass in males. Education years and ADHD show genetic overlap with childhood obesity. Mendelian randomization identifies schizophrenia, anorexia nervosa, and higher education as causal for decreased fat mass, with higher body fat % possibly being a causal risk factor for ADHD and heavy smoking. These results suggest new possibilities for targeted preventive strategies., Psychiatric disorders are often accompanied by alterations in BMI and body composition due to changes in eating behaviour and physical activity. Here, Hübel et al. study the genetic overlap between these traits and find that genetic correlations between psychiatric disorders and body composition are sex-specific and evident only in adulthood.

Thomas V Fungwe,1 Julius S Ngwa,2 Oyonumo E Ntekim,1 Joanne S Allard,3 Sheeba Nadarajah,4 Saba Wolday,5 Oludolapo O Ogunlana,5 Steven P Johnson,5 Kakra Hughes,6 Daniel Larbi,5 Richard F Gillum,7 Thomas O Obisesan5 1Department of Nutritional Sciences, School of Nursing and Allied Health Sciences, Howard University, Washington, DC, USA; 2Division of Cardiology, Department of Medicine, Howard University, Washington, DC, USA; 3Division of Cardiology, Department of Physiology and Biophysics, Howard University, Washington, DC, USA; 4Division of Nursing, College of Nursing and Allied Health Sciences, Howard University, Washington, DC, USA; 5Division of Geriatrics, Department of Medicine and Clinical, Howard University Hospital, Washington, DC, USA; 6Department of Surgery, Howard University College of Medicine, Washington, DC, USA; 7Department of Internal Medicine, Howard University Hospital, Washington, DC, USACorrespondence: Thomas O ObisesanDivision of Geriatrics, Department of Medicine and Clinical/Translational Science Program, Howard University Hospital, 2041 Georgia Ave NW, Washington, DC 20060, USATel +1 202 865 3397Fax +1 202 865 3777Email tobisesan@howard.eduPurpose: Poor cardiorespiratory fitness (CRF) is linked to cognitive deterioration, but its effects on lipid heterogeneity and functional properties in older African American (AA) subjects with mild cognitive impairment (MCI) need elucidation. This study determined whether exercise training-induced changes in blood lipid particle sizes (LPS) were associated with CRF determined by VO2Max in elderly AAs with MCI. Given the pivotal role of brain-derived neurotrophic factor (BDNF) on glucose metabolism, and therefore, “diabetic dyslipidemia”, we also determined whether changes in LPS were associated with the levels of serum BDNF.Methods: This analysis included 17 of the 29 randomized elderly AAs with MCI who had NMR data at baseline and after a 6-month training. We used Generalized Linear Regression (GLM) models to examine cardiorespiratory fitness (VO2Max) effects on training-induced change in LPS in the stretch and aerobic groups. Additionally, we determined whether the level of BDNF influenced change in LPS.Results: Collectively, mean VO2Max (23.81±6.17) did not differ significantly between aerobic and stretch groups (difference=3.17±3.56, P=0.495). Training-related changes in very low-density lipoprotein, chylomicrons, and total low-density lipoprotein (LDL) particle sizes correlated significantly with VO2Max, but not after adjustment for age and gender. However, increased VO2Max significantly associated with reduced total LDL particle size after similar adjustments (P = 0.046). While stretch exercise associated with increased protective large high-density lipoprotein particle size, the overall effect was not sustained following adjustments for gender and age. However, changes in serum BDNF were associated with changes in triglyceride and cholesterol transport particle sizes (P < 0.051).Conclusion: Promotion of stretch and aerobic exercise to increase CRF in elderly AA volunteers with MCI may also promote beneficial changes in lipoprotein particle profile. Because high BDNF concentration may reduce CVD risk, training-related improvements in BDNF levels are likely advantageous. Large randomized studies are needed to confirm our observations and to further elucidate the role for exercise therapy in reducing CVD risk in elderly AAs with MCI.Keywords: lipoprotein, elderly, exercise, cardiovascular disease, Alzheimer’s disease, brain-derived neurotrophic factor, cardiovascular fitness

There is presently an ongoing debate on the relative merits of suggested criteria for spirometric airway obstruction. This study tests the null hypothesis that no superiority exists with the use of fixed ratio (FR) of forced expiratory volume in the first second (FEV1)/forced vital capacity (FVC) 0.7 versus less than lower limit predicted (LLN) criteria with or without FEV180% predicted in regards to future mortality.In 1988-1994 the Third National Health and Nutrition Examination Survey (NHANES III) measured FEV1 and FVC with mortality follow-up data through December 31, 2011. For this survival analysis 7472 persons aged 40 and over with complete data formed the analytic sample.There were a total of 3554 deaths. Weighted Cox proportional hazards regression revealed an increased hazard ratio in persons with both fixed ratio and lower limit of normal with a low FEV1 (1.79, p 0.0001), in those with fixed ratio only with a low FEV1 (1.77, p 0.0001), in those with abnormal fixed ratio only with a normal FEV1 (1.28, p 0.0001) compared with persons with no airflow obstruction (reference group). These remained significant after adjusting for demographic variables and other confounding variables.The addition of FEV1 80% of predicted increased the prognostic power of the fixed ratio0.7 and/or below the lower limit of predicted criteria for airway obstruction.

Objectives This study sought to evaluate the influence of race/ethnicity on the relationship between body mass index (BMI) and mortality in heart failure with preserved ejection fraction (HFpEF) and HF with reduced EF (HFrEF) patients. Background Prior studies demonstrated an “obesity paradox” among overweight and obese patients, where they have a better HF prognosis than normal weight patients. Less is known about the relationship between BMI and mortality among diverse patients with HF, particularly given disparities in obesity and HF prevalence. Methods The authors used Get With The Guidelines–Heart Failure data to assess the relationship between BMI and in-hospital mortality by using logistic regression modeling. The authors assessed 30-day and 1-year rates of all-cause mortality following discharge by using Cox regression modeling. Results A total of 39,647 patients with HF were included (32,434 [81.8%] white subjects; 3,809 [9.6%] black subjects; 1,928 [4.9%] Hispanic subjects; 544 [1.4%] Asian subjects; and 932 [2.3%] other subjects); 59.7% of subjects had HFpEF, and 30.7% were obese. More black and Hispanic patients had Class I or higher obesity (BMI ≥30 kg/m 2 ) than whites, Asians, or other racial/ethnic groups (p 2 with a small risk increase above 30 kg/m 2 (BMI: 30 vs. 18.5 kg/m 2 ), hazard ratio (HR) of 0.63 (95% confidence interval [CI]: 0.54 to 0.73). A modest relationship was observed in HFrEF subjects (BMI: 30 vs. 18.5 kg/m 2 ; HR: 0.73; 95% CI: 0.60 to 0.89), with no risk increase above 30 kg/m 2 . There were no significant interactions between BMI and race or ethnicity related to 30-day mortality (p > 0.05). Conclusions This work is one of the first suggesting the obesity paradox for 30-day mortality exists at all BMI levels in HFrEF but not in patients with HFpEF. Higher BMI was associated with lower 30-day mortality across racial/ethnic groups in a manner inconsistent with the J-shaped relationship noted for coronary artery disease. The differential slope of obesity and mortality among HFpEF and patients with HFrEF potentially suggests differing mechanistic factors, requiring further exploration.

Background: It is increasingly evident that high blood pressure can promote reduction in global and regional brain volumes. While these effects may preferentially affect the hippocampus, reports are inconsistent. Methods: Using data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI), we examined the relationships of hippocampal volume to pulse pressure (PPR) and systolic (SBP) and diastolic (DBP) blood pressure according to apolipoprotein (APOE) ɛ4 positivity and cognitive status. The ADNI data included 1,308 participants: Alzheimer disease (AD = 237), late mild cognitive impairment (LMCI = 454), early mild cognitive impairment (EMCI = 254), and cognitively normal (CN = 365), with up to 24 months of follow-up. Results: Higher quartiles of PPR were significantly associated with lower hippocampal volumes (Q1 vs. Q4, p = 0.034) in the CN and AD groups, but with increasing hippocampal volume (Q1, p = 0.008; Q2, p = 0.020; Q3, p = 0.017; Q4 = reference) in the MCI groups. In adjusted stratified analyses among non-APOE ɛ4 carriers, the effects in the CN (Q1 vs. Q4, p = 0.006) and EMCI groups (Q1, p = 0.002; Q2, p = 0.013; Q3, p = 0.002; Q4 = reference) remained statistically significant. Also, higher DBP was significantly associated with higher hippocampal volume (p = 0.002) while higher SBP was significantly associated with decreasing hippocampal volume in the EMCI group (p = 0.015). Conclusion: Changes in PPR, SBP, and DBP differentially influenced hippocampal volumes depending on the cognitive and APOE genotypic categories.

The effects of oral intake of capsaicin oleoresin (CO) on arterial blood pressure was examined in male spontaneously hypertensive (SHR) rats. Animals were randomized into control (C), capsaicin oleoresin (CO), capsaicin oleoresin-irbesartan (COI) and capsaicin oleoresin-amlodipine besylate (COAB) fed groups. The experimental groups received 50 mg of Capsaicin Oleoresin only, CO with 25 mg of Irbesartan, and CO with 2.5 mg of Amlodipine per kilogram of body weight every other day for 4 weeks. Blood pressure was measured weekly by tail-cuff for 4 weeks. Biological samples were obtained at baseline, day 18, and day 34 (terminal) for aldosterone, arginine vasopressin (AVP), renin, 6-Keto-PGF-1α, Prostaglandin E2, catecholamines, adrenocorticotropic hormone (ACTH) levels, and serum minerals. Statistical significance was set at p≤0.05. The results trended towards decreasing (p=0.190) systolic blood pressure (SBP) in the COAB and CO compared to the COI and control groups. However, significance among group differences were observed for urine aldosterone and AVP, and serum sodium, calcium, magnesium, potassium, and catecholamine (p≤0.05), but not for ACTH, renin, and 6-Keto-PGF-1α levels. Capsaicin treatment was non-significantly associated with decreased SBP in SHR. These findings suggested that the effects of Capsaicin on SPB may involve aldosterone and arteriolar vascular tone. Key words: Capsaicin oleoresin, amlodipine besylate, irbesartan, arginine vasopressin, spontaneously hypertensive rats.

Insulin resistance syndrome (IRS), high blood pressure, elevated blood glucose and triacylglycerol-rich lipoproteins (TG-RL), as well as low levels of high-density lipoprotein (HDL-C) are disorders that combine to define metabolic syndrome (MetS). Metabolic syndrome is on the rise in the United States and is believed to be a powerful predictor of risk for diabetes and coronary events. Modulation of the activity of lipoprotein lipase (LPL) in MetS affects lipolysis of TG-RL, which has a direct correlation with the levels of plasma HDL-C. This study examined if increasing LPL activity by dietary means in a model for MetS leads to reduced IRS and increase in plasma HDL-C concentration. Ninety day-old Spontaneously Hypertensive Stroke-Prone male rats were originally fed lab chow diet for seven days. This was followed by feeding a fatty acid diet for 7 days containing one of the following: triolein (TO), trans fatty acids-rich (TFA, margarine) and 0 fatty acids (Control) with /without an LPL-rising drug (NO-1866) by gavages (5 mg or 25 mg/kg b. wt.). The results show that blood glucose and triacylglycerol levels were decreased with NO-1886. HDL-C levels increased with NO-1866 in the control and triolein group but not in the TFA group. Animals in the triolein group had higher levels of phospholipids and lower levels of insulin. Inclusion of NO-1866 lowered HOMA-IR by almost 40% in the control and the TFA group, but no further reduction was observed in the TO group. The control TFA groups had up to 45% higher HOMA-IR than the TO group. Overall the data suggest that raising the activity of lipoprotein lipase by dietary means, including the feeding of monounsaturated fat may increase HDL-C, reduce plasma triacylglycerol and other indices of MetS risk, and thus may decrease the incidence of vascular complications through the normalization of lipid metabolism in subjects with MetS.

Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423) or other ancestry (n = 20,029). We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by ~30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive to PA. In additional genome-wide meta-analyses adjusting for PA and interaction with PA, we identify 11 novel adiposity loci, suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discovery.

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., A full list of acknowledgments appears in the Supplementary Note 4. Co-author A.J.M.d.C. recently passed away while this work was in process. This work was performed under the auspices of the Genetic Investigation of ANthropometric Traits (GIANT) consortium. We acknowledge the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium for encouraging CHARGE studies to participate in this effort and for the contributions of CHARGE members to the analyses conducted for this research. Funding for this study was provided by the Aase and Ejner Danielsens Foundation; Academy of Finland (41071, 77299, 102318, 110413, 117787, 121584, 123885, 124243, 124282, 126925, 129378, 134309, 286284); Accare Center for Child and Adolescent Psychiatry; Action on Hearing Loss (G51); Agence Nationale de la 359 Recherche; Agency for Health Care Policy Research (HS06516); ALF/LUA research grant in Gothenburg; ALFEDIAM; ALK-Abelló A/S; Althingi; American Heart Association (13POST16500011); Amgen; Andrea and Charles Bronfman Philanthropies; Ardix Medical; Arthritis Research UK; Association Diabète Risque Vasculaire; Australian National Health and Medical Research Council (241944, 339462, 389875, 389891, 389892, 389927, 389938, 442915, 442981, 496739, 552485, 552498); Avera Institute; Bayer Diagnostics; Becton Dickinson; BHF (RG/14/5/30893); Boston Obesity Nutrition Research Center (DK46200), Bristol-Myers Squibb; British Heart Foundation (RG/10/12/28456, RG2008/08, RG2008/014, SP/04/002); Medical Research Council of Canada; Canadian Institutes for Health Research (FRCN-CCT-83028); Cancer Research UK; Cardionics; Cavadis B.V., Center for Medical Systems Biology; Center of Excellence in Genomics; CFI; CIHR; City of Kuopio; CNAMTS; Cohortes Santé TGIR; Contrat de Projets État-Région; Croatian Science Foundation (8875); Danish Agency for Science, Technology and Innovation; Danish Council for Independent Research (DFF-1333-00124, DFF-1331-00730B); County Council of Dalarna; Dalarna University; Danish Council for Strategic Research; Danish Diabetes Academy; Danish Medical Research Council; Department of Health, UK; Development Fund from the University of Tartu (SP1GVARENG); Diabetes Hilfs- und Forschungsfonds Deutschland; Diabetes UK; Diabetes Research and Wellness Foundation Fellowship; Donald W. Reynolds Foundation; Dr Robert Pfleger-Stiftung; Dutch Brain Foundation; Dutch Diabetes Research Foundation; Dutch Inter University Cardiology Institute; Dutch Kidney Foundation (E033); Dutch Ministry of Justice; the DynaHEALTH action No. 633595, Economic Structure Enhancing Fund of the Dutch Government; Else Kröner-Fresenius-Stiftung (2012_A147, P48/08//A11/08); Emil Aaltonen Foundation; Erasmus University Medical Center Rotterdam; Erasmus MC and Erasmus University Rotterdam; the Municipality of Rotterdam; Estonian Government (IUT20-60, IUT24-6); Estonian Research Roadmap through the Estonian Ministry of Education and Research (3.2.0304.11-0312); European Research Council (ERC Starting Grant and 323195:SZ-245 50371-GLUCOSEGENES-FP7-IDEAS-ERC); European Regional Development Fund; European Science Foundation (EU/QLRT-2001-01254); European Commission (018947, 018996, 201668, 223004, 230374, 279143, 284167, 305739, BBMRI-LPC-313010, HEALTH-2011.2.4.2-2-EU-MASCARA, HEALTH-2011-278913, HEALTH-2011-294713-EPLORE, HEALTH-F2-2008-201865-GEFOS, HEALTH-F2-2013-601456, HEALTH-F4-2007-201413, HEALTH-F4-2007-201550-HYPERGENES, HEALTH-F7-305507 HOMAGE, IMI/115006, LSHG-CT-2006-018947, LSHG-CT-2006-01947, LSHM-CT-2004-005272, LSHM-CT-2006-037697, LSHM-CT-2007-037273, QLG1-CT-2002-00896, QLG2-CT-2002-01254); Faculty of Biology and Medicine of Lausanne; Federal Ministry of Education and Research (01ZZ0103, 01ZZ0403, 01ZZ9603, 03IS2061A, 03ZIK012); Federal State of Mecklenburg-West Pomerania; Fédération Française de Cardiologie; Finnish Cultural Foundation; Finnish Diabetes Association; Finnish Foundation of Cardiovascular Research; Finnish Heart Association; Fondation Leducq; Food Standards Agency; Foundation for Strategic Research; French Ministry of Research; FRSQ; Genetic Association Information Network (GAIN) of the Foundation for the NIH; German Federal Ministry of Education and Research (BMBF, 01ER1206, 01ER1507); GlaxoSmithKline; Greek General Secretary of Research and Technology; Göteborg Medical Society; Health and Safety Executive; Healthcare NHS Trust; Healthway; Western Australia; Heart Foundation of Northern Sweden; Helmholtz Zentrum München—German Research Center for Environmental Health; Hjartavernd; Ingrid Thurings Foundation; INSERM; InterOmics (PB05 MIUR-CNR); INTERREG IV Oberrhein Program (A28); Interuniversity Cardiology Institute of the Netherlands (ICIN, 09.001); Italian Ministry of Health (ICS110.1/RF97.71); Italian Ministry of Economy and Finance (FaReBio di Qualità); Marianne and Marcus Wallenberg Foundation; the Ministry of Health, Welfare and Sports, the Netherlands; J.D.E. and Catherine T, MacArthur Foundation Research Networks on Successful Midlife Development and Socioeconomic Status and Health; Juho Vainio Foundation; Juvenile Diabetes Research Foundation International; KfH Stiftung Präventivmedizin e.V.; King's College London; Knut and Alice Wallenberg Foundation; Kuopio University Hospital; Kuopio, Tampere and Turku University Hospital Medical Funds (X51001); La Fondation de France; Leenaards Foundation; Lilly; LMUinnovativ; Lundberg Foundation; Magnus Bergvall Foundation; MDEIE; Medical Research Council UK (G0000934, G0601966, G0700931, MC_U106179471, MC_UU_12019/1); MEKOS Laboratories; Merck Santé; Ministry for Health, Welfare and Sports, The Netherlands; Ministry of Cultural Affairs of Mecklenburg-West Pomerania; Ministry of Economic Affairs, The Netherlands; Ministry of Education and Culture of Finland (627;2004-2011); Ministry of Education, Culture and Science, The Netherlands; Ministry of Science, Education and Sport in the Republic of Croatia (108-1080315-0302); MRC centre for Causal Analyses in Translational Epidemiology; MRC Human Genetics Unit; MRC-GlaxoSmithKline pilot programme (G0701863); MSD Stipend Diabetes; National Institute for Health Research; Netherlands Brain Foundation (F2013(1)-28); Netherlands CardioVascular Research Initiative (CVON2011-19); Netherlands Genomics Initiative (050-060-810); Netherlands Heart Foundation (2001 D 032, NHS2010B280); Netherlands Organization for Scientific Research (NWO) and Netherlands Organisation for Health Research and Development (ZonMW) (56-464-14192, 60-60600-97-118, 100-001-004, 261-98-710, 400-05-717, 480-04-004, 480-05-003, 481-08-013, 904-61-090, 904-61-193, 911-11-025, 985-10-002, Addiction-31160008, BBMRI–NL 184.021.007, GB-MaGW 452-04-314, GB-MaGW 452-06-004, GB-MaGW 480-01-006, GB-MaGW 480-07-001, GB-MW 940-38-011, Middelgroot-911-09-032, NBIC/BioAssist/RK 2008.024, Spinozapremie 175.010.2003.005, 175.010.2007.006); Neuroscience Campus Amsterdam; NHS Foundation Trust; National Institutes of Health (1RC2MH089951, 1Z01HG000024, 24152, 263MD9164, 263MD821336, 2R01LM010098, 32100-2, 32122, 32108, 5K99HL130580-02, AA07535, AA10248, AA11998, AA13320, AA13321, AA13326, AA14041, AA17688, AG13196, CA047988, DA12854, DK56350, DK063491, DK078150, DK091718, DK100383, DK078616, ES10126, HG004790, HHSN268200625226C, HHSN268200800007C, HHSN268201200036C, HHSN268201500001I, HHSN268201100046C, HHSN268201100001C, HHSN268201100002C, HHSN268201100003C, HHSN268201100004C, HHSN271201100004C, HL043851, HL45670, HL080467, HL085144, HL087660, HL054457, HL119443, HL118305, HL071981, HL034594, HL126024, HL130114, KL2TR001109, MH66206, MH081802, N01AG12100, N01HC55015, N01HC55016, N01C55018, N01HC55019, N01HC55020, N01HC55021, N01HC55022, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086, N01HC95159, N01HC95160, N01HC95161, N01HC95162, N01HC95163, N01HC95164, N01HC95165, N01HC95166, N01HC95167, N01HC95168, N01HC95169, N01HG65403, N01WH22110, N02HL6‐4278, N01-HC-25195, P01CA33619, R01HD057194, R01HD057194, R01AG023629, R01CA63, R01D004215701A, R01DK075787, R01DK062370, R01DK072193, R01DK075787, R01DK089256, R01HL53353, R01HL59367, R01HL086694, R01HL087641, R01HL087652, R01HL103612, R01HL105756, R01HL117078, R01HL120393, R03 AG046389, R37CA54281, RC2AG036495, RC4AG039029, RPPG040710371, RR20649, TW008288, TW05596, U01AG009740, U01CA98758, U01CA136792, U01DK062418, U01HG004402, U01HG004802, U01HG007376, U01HL080295, UL1RR025005, UL1TR000040, UL1TR000124, UL1TR001079, 2T32HL007055-36, T32GM074905, HG002651, HL084729, N01-HC-25195, UM1CA182913); NIH, National Institute on Aging (Intramural funding, NO1-AG-1-2109); Northern Netherlands Collaboration of Provinces; Novartis Pharma; Novo Nordisk; Novo Nordisk Foundation; Nutricia Research Foundation (2016-T1); ONIVINS; Parnassia Bavo group; Pierre Fabre; Province of Groningen; Päivikki and Sakari Sohlberg Foundation; Påhlssons Foundation; Paavo Nurmi Foundation; Radboud Medical Center Nijmegen; Research Centre for Prevention and Health, the Capital Region of Denmark; the Research Institute for Diseases in the Elderly; Research into Ageing; Robert Dawson Evans Endowment of the Department of Medicine at Boston University School of Medicine and Boston Medical Center; Roche; Royal Society; Russian Foundation for Basic Research (NWO-RFBR 047.017.043); Rutgers University Cell and DNA Repository (NIMH U24 MH068457-06); Sanofi-Aventis; Scottish Government Health Directorates, Chief Scientist Office (CZD/16/6); Siemens Healthcare; Social Insurance Institution of Finland (4/26/2010); Social Ministry of the Federal State of Mecklenburg-West Pomerania; Société Francophone du 358 Diabète; State of Bavaria; Stiftelsen för Gamla Tjänarinnor; Stockholm County Council (560183, 592229); Strategic Cardiovascular and Diabetes Programmes of Karolinska Institutet and Stockholm County Council; Stroke Association; Swedish Diabetes Association; Swedish Diabetes Foundation (2013-024); Swedish Foundation for Strategic Research; Swedish Heart-Lung Foundation (20120197, 20150711); Swedish Research Council (0593, 8691, 2012-1397, 2012-1727, and 2012-2215); Swedish Society for Medical Research; Swiss Institute of Bioinformatics; Swiss National Science Foundation (3100AO-116323/1, 31003A-143914, 33CSCO-122661, 33CS30-139468, 33CS30-148401, 51RTP0_151019); Tampere Tuberculosis Foundation; Technology Foundation STW (11679); The Fonds voor Wetenschappelijk Onderzoek Vlaanderen, Ministry of the Flemish Community (G.0880.13, G.0881.13); The Great Wine Estates of the Margaret River Region of Western Australia; Timber Merchant Vilhelm Bangs Foundation; Topcon; Tore Nilsson Foundation; Torsten and Ragnar Söderberg's Foundation; United States – Israel Binational Science Foundation (Grant 2011036), Umeå University; University Hospital of Regensburg; University of Groningen; University Medical Center Groningen; University of Michigan; University of Utrecht; Uppsala Multidisciplinary Center for Advanced Computational Science (UPPMAX) (b2011036); Velux Foundation; VU University’s Institute for Health and Care Research; Västra Götaland Foundation; Wellcome Trust (068545, 076113, 079895, 084723, 088869, WT064890, WT086596, WT098017, WT090532, WT098051, 098381); Wissenschaftsoffensive TMO; Yrjö Jahnsson Foundation; and Åke Wiberg Foundation. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute (NHLBI); the National Institutes of Health (NIH); or the U.S. Department of Health and Human Services.

OBJECTIVES: The aims of this study were to develop and implement a “Food as Medicine” intervention using quantitative methods supported by health literacy and food choice and behavioral models to target chronic diseases under free-living conditions in adults diagnosed with chronic diseases. The hypothesis of this study is that “Food as Medicine” nutrition and lifestyle intervention sessions will result in significant improvements in food choices, as well as shopping and cooking behaviors. METHODS: The Food as Medicine (FAM) study is a community-based pilot study that measured the effectiveness of a nutrition intervention to improve chronic disease risk factors and outcomes among African Americans with either pre-diabetes, type 2 diabetes mellitus, hypertension, elevated total blood cholesterol levels, obesity or a combination of these disorders. The study enrolled patients who were attending both Howard University Family Medicine and Internal Medicine Practices, and were residents of wards seven or eight in the District of Columbia. Fifty-four participants were enrolled and assigned to five cohorts, which consisted of five group sessions over three months, and focused on improving diet and health literacy through nutritionist-led, culturally-tailored, nutrition education classes that included health literacy, mindfulness exercises, and cooking demonstrations. RESULTS: After program completion, FAM participants demonstrated significant improvements in all outcome measures of interest: healthy dietary patterns (P

Pump thrombosis remains the catastrophic complication of Left ventricular assist device (LVAD) therapy. There is limited data available on the trend of in-hospital outcomes associated with pump thrombosis in LVAD patients. Patients with LVAD placement in the Healthcare Cost and Utilization Project

The HEART score was designed to aid in disposition of patients presenting to the emergency department (ED) with chest pain (CP). Using prospectively collected data from the local and regional electronic health record systems, CP presentations to the ED of an academic institution were investigated.

Possession of the Apolipoprotein E (APOE) gene ε4 allele is the most prevalent genetic risk factor for late onset Alzheimer’s disease (AD). Recent evidence suggests that APOE genotype differentially affects the expression of brain-derived neurotrophic factor (BDNF). Notably, aerobic exercise-induced upregulation of BDNF is well documented; and exercise has been shown to improve cognitive function. As BDNF is known for its role in neuroplasticity and survival, its upregulation is a proposed mechanism for the neuroprotective effects of physical exercise. In this pilot study designed to analyze exercise-induced BDNF upregulation in an understudied population, we examined the effects of ApoEε4 (ε4) carrier status on changes in BDNF expression after a standardized exercise program. African Americans, age 55 years and older, diagnosed with mild cognitive impairment participated in a six-month, supervised program of either stretch (control treatment) or aerobic (experimental treatment) exercise. An exercise-induced increase in VO2Max was detected only in male participants. BDNF levels in serum were measured using ELISA. Age, screening MMSE scores and baseline measures of BMI, VO2Max, and BDNF did not differ between ε4 carriers and non-ε4 carriers. A significant association between ε4 status and serum BDNF levels was detected. Non-ε4 carriers showed a significant increase in BDNF levels at the 6 month time point while ε4 carriers did not. We believe we have identified a relationship between the ε4 allele and BDNF response to physiologic adaptation which likely impacts the extent of neuroprotective benefit gained from engagement in physical exercise. Replication of our results with inclusion of diverse racial cohorts, and a no-exercise control group will be necessary to determine the scope of this association in the general population.

Background: Current guidelines do not support the routine use of computed tomography (CT) scan of the head in the diagnostic workup of syncope. There is a lack of research to support whether these guidelines apply to the Black population. Aims: This study aims to evaluate the yield of neuroimaging in the evaluation of Syncope in a predominantly Black patient population and to test whether current guidelines based on studies conducted in other populations hold true in this group. Material and Methods: A retrospective review of records of 151 patients admitted to a University Hospital with Syncope from 2011 to 2014 was performed. Data collected include CT head, magnetic resonance imaging of the brain, magnetic resonance angiogram, electroencephalogram, and orthostatic vital signs. Demographic data, admitting service, and comorbid conditions were identified. Syncope was classified as cardiogenic, orthostatic, vasovagal, situational, or undetermined. Statistical analysis was performed to determine which diagnostic tools were useful in identifying the potential causes of syncope. Data analysis was conducted using the Statistical Analysis System software 9.3 (SAS Institute, Cary, NC) and Statistical Analysis and Graphics (NCSS 9.0.7, Kaysville, UT). Results: One hundred and twenty eight (84.8%) of the patients were Black. The average age was 56.62 ± 18.78 standard deviation and 68.2% (103) were female. One hundred and fourteen patients (75.5%) had a CT brain. Five out of 114 patients had an acute abnormality on CT (4.4%). Only 1 of these 5 patients had an abnormality that was related to syncope. CT brain (P = 0.978) was not found to be predictive of underlying etiology of syncope despite high frequency of use. Conclusions: CT head was not useful in determining the etiology of syncope in a predominantly Black population. Current guidelines and studies conducted in other populations have detected similar findings.

Background: Obesity predisposes patients to pulmonary complication: however, the association in critically ill Black populations is poorly understood. Objectives: To determine the association of body mass index (BMI) on pulmonary complications in Black patients in the ICU. Methods: A retrospective chart review of adult patients (n=605) aged 18 years and older with a medical ICU stay of greater than 24 hours during 2012 was performed. Patients were categorized based on BMI as under weight (BMI≤18.4kg/m2), normal weight (18.5-24.9kg/m2), overweight (25-29.9kg/m2), class I (30-34.99kg/m2), class II (35-39.99kg/m2) or, class III obesity (≥40kg/m2). Primary outcomes were need for and duration of mechanical ventilation and rate of ARDS. Secondary outcomes included ICU and hospital length of stay (LOS) and ICU mortality. Results: The overall rate of obesity was 35%. Patients with obesity (BMI≥30kg/m2) were more likely to be female (p Conclusion: Obesity was neither associated with increased pulmonary complications or mortality in critically ill Black patients. However patients with class II and III obesity require longer ICU and hospital stay.

Purpose: New onset supraventricular arrhythmias (SVA) are commonly reported in mixed intensive care settings. We sought to determine the incidence, risk factors and outcomes of new onset SVA in African American (AA) patients with severe sepsis admitted to medical intensive care unit (MICU).Methods: Patients admitted to MICU between January 2012 through December 2012 were studied. Patients with a previous history of arrhythmia or with new onset of ventricular arrhythmia were excluded. Data on risk factors, critical care interventions and outcomes were obtained.Results: One hundred and thirty-one patients were identified. New onset SVA occurred in 34 (26%) patients. Of those 34, 20 (59%) had atrial fibrillation (AF), 6 (18%) had atrial flutter and 8 (24%) had other forms of SVA. Compared with patients without SVA, patients with new onset SVA were older (69 ± 12 yrs vs 59 ± 13 yrs, P=.003), had congestive heart failure (47% vs 24%, P=.015) and dyslipidemia (41% vs 15%, P=.002). Additionally, they had a higher mean mortality prediction model (MPM II) score (65 ± 25 vs 49 ± 26, P=.001) and an increased incidence of respiratory failure (85% vs 55%, P=.001). Hospital mortality in patients with new onset SVA was 18 (53%) vs 30 (31%); P=.024; however, in a multivariate analysis, new onset SVA was associated with nonsignificantly increased odds (OR 2.58, 95% CI 0.86-8.05) for in-hospital mortality.Conclusion: New onset SVA was prevalent in AA patients with severe sepsis and occurred more frequently with advanced age, increased severity of illness, congestive heart failure, and acute respiratory failure; it was associated with higher unadjusted in hospital mortality. However, after multiple adjustments, new onset SVA did not remain an independent predictor of mortality. Ethn Dis.2016;26(2):205-212; doi:10.18865/ ed.26.2.205

Objective Multiple studies have identified single-nucleotide polymorphisms (SNPs) that are associated with coronary heart disease (CHD). We examined whether SNPs selected based on predefined criteria will improve CHD risk prediction when added to traditional risk factors (TRFs). Methods SNPs were selected from the literature based on association with CHD, lack of association with a known CHD risk factor, and successful replication. A genetic risk score (GRS) was constructed based on these SNPs. Cox proportional hazards model was used to calculate CHD risk based on the Atherosclerosis Risk in Communities (ARIC) and Framingham CHD risk scores with and without the GRS. Results The GRS was associated with risk for CHD (hazard ratio [HR] = 1.10; 95% confidence interval [CI]: 1.07–1.13). Addition of the GRS to the ARIC risk score significantly improved discrimination, reclassification, and calibration beyond that afforded by TRFs alone in non-Hispanic whites in the ARIC study. The area under the receiver operating characteristic curve (AUC) increased from 0.742 to 0.749 ( Δ = 0.007; 95% CI, 0.004–0.013), and the net reclassification index (NRI) was 6.3%. Although the risk estimates for CHD in the Framingham Offspring (HR = 1.12; 95% CI: 1.10–1.14) and Rotterdam (HR = 1.08; 95% CI: 1.02–1.14) Studies were significantly improved by adding the GRS to TRFs, improvements in AUC and NRI were modest. Conclusion Addition of a GRS based on direct associations with CHD to TRFs significantly improved discrimination and reclassification in white participants of the ARIC Study, with no significant improvement in the Rotterdam and Framingham Offspring Studies.

Introduction: Cancer affects people of all races in the U.S.; however, the burden is greater for minority populations. This is influenced by factors such as demographics, behavioral factors, and access to medical services. The disparity is well documented in some solid tumors. However, little information exists on a racial disparity in survival among minority populations diagnosed with chronic myeloid leukemia (CML) especially in the era of targeted therapies. A better understanding of the population impact of CML will drive further research into approaches to improve overall outcomes. Methods: All cases of CML diagnosed between 1973 and 2017 and with available follow-up data reported in the Surveillance, Epidemiology, and End Results database were reviewed. We performed a population-based study of CML to evaluate survival by race and calendar year of diagnosis: 1975-1989 (the era of cytotoxic therapy; busulfan and hydroxyurea), 1990-2000 (the era of Allogeneic hematopoietic stem cell transplantation or interferon-alfa ± cytarabine), and 2001-2015 (the era of targeted therapy; Tyrosine Kinase Inhibitors). Results: A total of 14572 (56.4% were females) patients diagnosed with CML were included in our analysis. The racial distribution was 83.4% white, 10% black, 0.8% American Indian/Alaska Native and 5.9% Asian or Pacific Islander. 5314 (36.5%), 3725 (25.5%) and 5544 (38%) cases of CML were diagnosed during the 1975-1989, 1990-2000 and 2001-2015 eras respectively. The median 5-year survival improved by race with each era, with the greatest improvement observed among patients diagnosed during the 2001-2015 era. Although a trend of improvement in the median 5-year survival is seen across all age categories, patients 65 years and older continue to experience only a modest survival benefit in the era of targeted therapies (Table 1). No significant differences in survival by race was observed in the era of targeted therapies (Figure 1). Conclusions: This survival analysis includes a longer follow-up duration (Diagnosis Years: 1973-2015) for patients with CML compared to prior studies. Although an overall improvement in median survival is seen across all age groups and by each era, survival benefits are lagging in certain populations (black and American Indian/ Alaska Native) older than 65. SEER database captures information from metropolitan counties in the United States and this may not truly reflect the health of the entire US population. Disclosures No relevant conflicts of interest to declare.

OBJECTIVE Whole-grain foods are touted for multiple health benefits, including enhancing insulin sensitivity and reducing type 2 diabetes risk. Recent genome-wide association studies (GWAS) have identified several single nucleotide polymorphisms (SNPs) associated with fasting glucose and insulin concentrations in individuals free of diabetes. We tested the hypothesis that whole-grain food intake and genetic variation interact to influence concentrations of fasting glucose and insulin. RESEARCH DESIGN AND METHODS Via meta-analysis of data from 14 cohorts comprising ∼48,000 participants of European descent, we studied interactions of whole-grain intake with loci previously associated in GWAS with fasting glucose (16 loci) and/or insulin (2 loci) concentrations. For tests of interaction, we considered a P value RESULTS Greater whole-grain food intake was associated with lower fasting glucose and insulin concentrations independent of demographics, other dietary and lifestyle factors, and BMI (β [95% CI] per 1-serving-greater whole-grain intake: −0.009 mmol/l glucose [−0.013 to −0.005], P < 0.0001 and −0.011 pmol/l [ln] insulin [−0.015 to −0.007], P = 0.0003). No interactions met our multiple testing–adjusted statistical significance threshold. The strongest SNP interaction with whole-grain intake was rs780094 (GCKR) for fasting insulin (P = 0.006), where greater whole-grain intake was associated with a smaller reduction in fasting insulin concentrations in those with the insulin-raising allele. CONCLUSIONS Our results support the favorable association of whole-grain intake with fasting glucose and insulin and suggest a potential interaction between variation in GCKR and whole-grain intake in influencing fasting insulin concentrations.

BackgroundRecent studies suggest that meat intake is associated with diabetes-related phenotypes. However, whether the associations of meat intake and glucose and insulin homeostasis are modified by genes related to glucose and insulin is unknown.ObjectiveWe investigated the associations of meat intake and the interaction of meat with genotype on fasting glucose and insulin concentrations in Caucasians free of diabetes mellitus.DesignFourteen studies that are part of the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium participated in the analysis. Data were provided for up to 50,345 participants. Using linear regression within studies and a fixed-effects meta-analysis across studies, we examined 1) the associations of processed meat and unprocessed red meat intake with fasting glucose and insulin concentrations; and 2) the interactions of processed meat and unprocessed red meat with genetic risk score related to fasting glucose or insulin resistance on fasting glucose and insulin concentrations.ResultsProcessed meat was associated with higher fasting glucose, and unprocessed red meat was associated with both higher fasting glucose and fasting insulin concentrations after adjustment for potential confounders [not including body mass index (BMI)]. For every additional 50-g serving of processed meat per day, fasting glucose was 0.021 mmol/L (95% CI: 0.011, 0.030 mmol/L) higher. Every additional 100-g serving of unprocessed red meat per day was associated with a 0.037-mmol/L (95% CI: 0.023, 0.051-mmol/L) higher fasting glucose concentration and a 0.049-ln-pmol/L (95% CI: 0.035, 0.063-ln-pmol/L) higher fasting insulin concentration. After additional adjustment for BMI, observed associations were attenuated and no longer statistically significant. The association of processed meat and fasting insulin did not reach statistical significance after correction for multiple comparisons. Observed associations were not modified by genetic loci known to influence fasting glucose or insulin resistance.ConclusionThe association of higher fasting glucose and insulin concentrations with meat consumption was not modified by an index of glucose- and insulin-related single-nucleotide polymorphisms. Six of the participating studies are registered at clinicaltrials.gov as NCT0000513 (Atherosclerosis Risk in Communities), NCT00149435 (Cardiovascular Health Study), NCT00005136 (Family Heart Study), NCT00005121 (Framingham Heart Study), NCT00083369 (Genetics of Lipid Lowering Drugs and Diet Network), and NCT00005487 (Multi-Ethnic Study of Atherosclerosis).

Background: Discrimination, a form of chronic psychological stress, is related to certain chronic health conditions such as poor physical health and hypertension. However, little is known about the associations of everyday discrimination with risk of myocardial infarction. Methods and Results: We assessed the association between everyday discrimination (discrimination) and myocardial infarction (MI) using a prospective, nested case control study of 548 women (267 cases, 281 controls), selected from 26,763 women without a history of cardiovascular disease at baseline who participated in the Women’s Heath Study (WHS). Among 267 MI cases, there was a mean follow-up of 8.8 + 4.1 years from date of WHS randomization to date of MI event. At baseline, the mean age of participants was 53.6 + 6.1 years. Cases and controls were matched for age and smoking history. Discrimination was assessed by 5 questions where women reported whether they were: 1) treated with less courtesy/respect than others; 2) treated as not being smart; 3) treated as if others were afraid of them; 4) received poorer service at restaurants/stores; or 5) felt threatened/harassed. Responses were based on a Likert scale of 1=never to 5=at least once/weekly with higher scores indicating more experiences with discrimination. In unadjusted logistic regression models of increasing tertiles of discrimination, we found no significant association between discrimination and odds of MI [Odds Ratios (OR) and 95% confidence intervals (95%CI): 1.00, 1.28 (0.85-1.94), 1.06 (0.69-1.64); p trend =0.5]. Adjustment for cardiovascular disease risk factors (lipid parameters, hsCRP, family history of MI, hypertension, body mass index, diabetes, and alcohol consumption) revealed an inverse-U-shaped relationship [OR, 95%CI: 1.00, 2.14 (1.21-3.77), 1.55 (0.87-2.78); p trend = 0.03], suggesting that these factors obscured the association in unadjusted models. Notably, addition of education and income to the crude model alone [1.00, 1.38 (0.89, 2.15), 0.97 (0.61, 1.54) p trend = 0.2] or to the model with the cardiovascular risk factors [1.00, 2.27 (1.25-4.10), 1.36 (0.73, 2.53); p trend = 0.02] had minimal impact on odds of MI in these women. Conclusion: Among women participating in the WHS follow-up cohort, higher levels of everyday discrimination were related to increased odds of myocardial infarction in an inverse-U-shaped manner, a finding that is obscured by traditional cardiovascular disease risk factors. Access to measures associated with a healthy heart might be important to myocardial infarction risk attenuation among women reporting everyday discrimination. Further research is warranted to elucidate the relationship between everyday discrimination and increased risk of MI.

Background Obesity prevalence in United States (US) adults exceeds 30% with highest prevalence being among blacks. Obesity is known to have significant effects on respiratory function and obese patients commonly report respiratory complaints requiring pulmonary function tests (PFTs). However, there is no large study showing the relationship between body mass index (BMI) and PFTs in healthy African Americans (AA). Objective To determine the effect of BMI on PFTs in AA patients who did not have evidence of underlying diseases of the respiratory system. Methods We reviewed PFTs of 339 individuals sent for lung function testing who had normal spirometry and lung diffusion capacity for carbon monoxide (DLCO) with wide range of BMI. Results Functional residual capacity (FRC) and expiratory reserve volume (ERV) decreased exponentially with increasing BMI, such that morbid obesity resulted in patients breathing near their residual volume (RV). However, the effects on the extremes of lung volumes, at total lung capacity (TLC) and residual volume (RV) were modest. There was a significant linear inverse relationship between BMI and DLCO, but the group means values remained within the normal ranges even for morbidly obese patients. Conclusions We showed that BMI has significant effects on lung function in AA adults and the greatest effects were on FRC and ERV, which occurred at BMI values < 30 kg/m2. These physiological effects of weight gain should be considered when interpreting PFTs and their effects on respiratory symptoms even in the absence of disease and may also exaggerate existing lung diseases.

Purpose: We sought to determine whether body mass index (BMI) is associated with worse intensive care unit (ICU) outcomes among Black patients.Methods: Patients admitted to the medical ICU during 2012 were categorized into six BMI groups based on the World Health Organization criteria. ICU mortality, ICU and hospital length of stay (LOS), need for and duration of mechanical ventilation and organ failure rate were assessed.Results: A total of 605 patients with mean age 58.9 ± 16.0 years were studied. Compared with those with normal BMI, obese patients had significant higher rates of hypertension, diabetes mellitus and obstructive sleep apnea diagnoses (PConclusion: Obesity was not associated with increased ICU mortality; however, obesity was associated with increased comorbid illness and with significant longer ICU and hospital length of stay. Ethn Dis.2017;27(2):161-168; doi:10.18865/ed.27.2.161

In recent years, longitudinal family-based studies have had success in identifying genetic variants that influence complex traits in genome-wide association studies. In this paper, we suggest that longitudinal analyses may contain valuable information that can enable identification of additional associations compared to baseline analyses. Using Genetic Analysis Workshop 18 data, consisting of whole genome sequence data in a pedigree-based sample, we compared 3 methods for the genetic analysis of longitudinal data to an analysis that used baseline data only. These longitudinal methods were (a) longitudinal mixed-effects model; (b) analysis of the mean trait over time; and (c) a 2-stage analysis, with estimation of a random intercept in the first stage and regression of the random intercept on a single-nucleotide polymorphism at the second stage. All methods accounted for the familial correlation among subjects within a pedigree. The analyses considered common variants with minor allele frequency above 5% on chromosome 3. Analyses were performed without knowledge of the simulation model. The 3 longitudinal methods showed consistent results, which were generally different from those found by using only the baseline observation. The gene CACNA2D3, identified by both longitudinal and baseline approaches, had a stronger signal in the longitudinal analysis (p = 2.65 × 10(-7)) compared to that in the baseline analysis (p = 2.48 × 10(-5)). The effect size of the longitudinal mixed-effects model and mean trait were higher compared to the 2-stage approach. The longitudinal results provided stable results different from that using 1 observation at baseline and generally had lower p values.

Background: Genome-wide association studies (GWAS) have identified several genetic loci that influence fasting glucose (FG) and insulin (FI). Whether the favorable relation between eating a healthy diet and FG or FI is the same regardless of genetic risk is unknown. Objective: We studied 15 well-characterized U.S., Northern European and Mediterranean cohorts that had dietary and genetic data (maximum N = 51,289) to test whether genotype and healthy diet interact to influence FG or FI concentrations. Design: Within each cohort, we constructed a healthy diet score comprising foods with previous evidence of associations with metabolic risk: whole grains, fish, fruits, vegetables, nuts/seeds (favorable food groups) and red meat, sweets, sugared beverages, fried potatoes (unfavorable food groups). Intakes of each food group were categorized in quartiles and assigned ascending values (0, 1, 2, 3) for favorable foods and descending values (3, 2, 1, 0) for unfavorable foods. These values were summed to generate an overall diet score (range: 0 to 27 points), with higher scores representing healthier diets. We used multivariable linear regression including an additive genetic model within cohorts followed by inverse weighted meta-analysis of all cohorts to quantify 1) associations between healthy diet and FG and FI and 2) interactions of healthy diet with 16 established FG- or two FI-associated loci on FG and FI concentrations. Results: Healthier diets (per additional diet score unit) were associated with lower FG (β: -0.004; 95% CI: -0.005, -0.003 mmol/L, p: Conclusions: A healthy diet score allowing summarization of dietary intake as an environmental exposure across diverse cohorts is favorably associated with FG and FI concentrations regardless of genotype at FG or FI-associated loci. Modest dietary differences are far larger than an individual’s apparent genetic risk at these loci.

Genome-wide association studies often emphasize single-nucleotide polymorphisms with the smallest p-values with less attention given to single-nucleotide polymorphisms not ranked near the top. We suggest that gene pathways contain valuable information that can enable identification of additional associations. We used gene set information to identify disease-related pathways using three methods: gene set enrichment analysis (GSEA), empirical enrichment p-values, and Ingenuity pathway analysis (IPA). Association tests were performed for common single-nucleotide polymorphisms and aggregated rare variants with traits Q1 and Q4. These pathway methods were evaluated by type I error, power, and the ranking of the VEGF pathway, the gene set used in the simulation model. GSEA and IPA had high power for detecting the VEGF pathway for trait Q1 (91.2% and 93%, respectively). These two methods were conservative with deflated type I errors (0.0083 and 0.0072, respectively). The VEGF pathway ranked 1 or 2 in 123 of 200 replicates using IPA and ranked among the top 5 in 114 of 200 replicates for GSEA. The empirical enrichment method had lower power and higher type I error. Thus pathway analysis approaches may be useful in identifying biological pathways that influence disease outcomes.

BACKGROUNDAIM: n-3 PUFA has been shown to decrease the risk of several components of the metabolic syndrome; however, the role of n-3 PUFA on glucose metabolism is not clear. Our aim was to systematically review the effect of n-3 PUFA on IS by conducting a meta-analysis of available RCTs.We followed the guidelines of Cochrane's review of systematic interventions. We searched MEDLINE, EMBASE, CENTRAL and clinicaltrials.gov from the beginning of each database until October 2010. Meta-analysis was performed using a random effects model to estimate a pooled SMD and the corresponding 95% CI.From 303 screened citations, 11 RCTs (n = 618) were eligible for inclusion in the analysis. In a pooled estimate, n-3 PUFA intervention had no effects on IS compared to placebo (SMD 0.08, 95% CI -0.11-0.28). Similarly, n-3 PUFA had no effects on IS in sub-group analyses (Type 2 diabetes vs. other population; QUICKI and other test subgroups). In the HOMA subgroup, n-3 PUFA was associated with a statistically significant increase in IS (SMD 0.30, CI 0.03-0.58) when compared to placebo.This meta-analysis is consistent with a lack of n-3 PUFA effects on IS.

Background— Several bone marrow–derived cell populations may have angiogenic activity, including cells termed endothelial progenitor cells. Decreased numbers of circulating angiogenic cell populations have been associated with increased cardiovascular risk. However, few data exist from large, unselected samples, and the genetic determinants of these traits are unclear. Methods and Results— We examined the clinical and genetic correlates of early-outgrowth colony-forming units (CFUs) in 1799 participants of the Framingham Heart Study (mean age, 66 years; 54% women). Among individuals without cardiovascular disease (n=1612), CFU number was inversely related to advanced age ( P =0.004), female sex ( P =0.04), and triglycerides ( P =0.008) and positively related to hormone replacement ( P =0.008) and statin therapy ( P =0.027) in stepwise multivariable analyses. Overall, CFU number was inversely related to the Framingham risk score ( P =0.01) but not with prevalent cardiovascular disease. In genome-wide association analyses in the entire sample, polymorphisms were associated with CFUs at the MOSC1 locus ( P =3.3×10 −7 ) and at the SLC22A3-LPAL2-LPA locus ( P =4.9×10 −7 ), a previously replicated susceptibility locus for myocardial infarction. Furthermore, alleles at the SLC22A3-LPAL2-LPA locus that were associated with decreased CFUs were also related to increased risk of myocardial infarction ( P =1.1×10 −4 ). Conclusions— In a community-based sample, early-outgrowth CFUs are inversely associated with select cardiovascular risk factors. Furthermore, genetic variants at the SLC22A3-LPAL2-LPA locus are associated with both decreased CFUs and an increased risk of myocardial infarction. These findings are consistent with the hypothesis that decreased circulating angiogenic cell populations promote susceptibility to myocardial infarction.

We sought to find significant gene × gene interaction in a genome-wide association analysis of rheumatoid arthritis (RA) by performing pair-wise tests of interaction among collections of single-nucleotide polymorphisms (SNPs) obtained by one of two methods. The first method involved screening the results of the genome-wide association analysis for main effects p-values < 1 × 10-4. The second method used biological databases such as the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes to define gene collections that each contained one of four genes with known associations with RA: PTPN22, STAT4, TRAF1, and C5. We used a permutation approach to determine whether any of these SNP sets had empirical enrichment of significant interaction effects. We found that the SNP set obtained by the first method was significantly enriched with significant interaction effects (empirical p = 0.003). Additionally, we found that the "protein complex assembly" collection of genes from the Gene Ontology collection containing the TRAF1 gene was significantly enriched with interaction effects with p-values < 1 × 10-8 (empirical p = 0.012).