Suchergebnisse

Reduction in excess calories and improvement in dietary composition may prevent many primary and secondary cardiovascular events. Current guidelines recommend diets high in fruits, vegetables, whole grains, nuts, and legumes; moderate in low-fat dairy and seafood; and low in processed meats, sugar-sweetened beverages, refined grains, and sodium. Supplementation can be useful for some people but cannot replace a good diet. Factors that influence individuals to consume a low-quality diet are myriad and include lack of knowledge, lack of availability, high cost, time scarcity, social and cultural norms, marketing of poor quality foods, and palatability. Governments should focus on cardiovascular disease as a global threat and enact policies that will reach all levels of society and create a food environment wherein healthy foods are accessible, affordable, and desirable. Health professionals should be proficient in basic nutritional knowledge to promote a sustainable pattern of healthful eating for cardiovascular disease prevention for both healthy individuals and those at higher risk

BACKGROUND: Perturbed lipid metabolic pathways may play important roles in the development of cardiovascular disease (CVD). However, existing epidemiological studies have focused more on discovering individual lipid metabolites for CVD risk prediction rather than assessing metabolic pathways. METHODS: This study included a subcohort of 787 participants and all 230 incident CVD cases from the PREDIMED trial. Applying a network-based analytical method, we identified lipid subnetworks and clusters from a global network of 200 lipid metabolites and linked these subnetworks/clusters to CVD risk. RESULTS: Lipid metabolites with more double bonds clustered within one subnetwork, whereas lipid metabolites with fewer double bonds clustered within other subnetworks. We identified 10 lipid clusters that were divergently associated with CVD risk. The hazard ratios [HRs, 95% confidence interval (CI)] of CVD per a 1-standard deviation (SD) increment in cluster score were 1.39 (1.17-1.66) for the hydroxylated phosphatidylcholine (HPC) cluster and 1.24 (1.11-1.37) for a cluster that included diglycerides and a monoglyceride with stearic acyl chain. Every 1-SD increase in the score of cluster that included highly unsaturated phospholipids and cholesterol esters was associated with an HR for CVD of 0.81 (95% CI, 0.67-0.98). Despite a suggestion that MedDiet modified the association between a subnetwork that included most lipids with a high degree of unsaturation and CVD, changes in lipid subnetworks/clusters during the first-year follow-up were not significantly different between intervention groups. CONCLUSIONS: The degree of unsaturation was a major determinant of the architecture of lipid metabolic network. Lipid clusters that strongly predicted CVD risk, such as the HPC cluster, warrant further functional investigations. ; This work was supported by a research grant from the National Institutes of Health [R01 HL118264]. The Prevención con Dieta Mediterránea (PREDIMED) trial was supported by the official funding agency for biomedical research of the Spanish government, the Instituto de Salud Carlos III, through grants provided to research networks specifically developed for the trial (RTIC G03/140 to R.E. and RTIC RD 06/0045 to Dr. Miguel A. Martínez-González) and through the Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición and by grants from: the Centro Nacional de Investigaciones Cardiovasculares (CNIC 06/2007); the Fondo de Investigación Sanitaria–Fondo Europeo de Desarrollo Regional (PI04–2239, PI 05/2584, CP06/00100, PI07/0240, PI07/1138, PI07/0954, PI 07/0473, PI10/01407, PI10/02658, PI11/01647, P11/02505 and PI13/00462); the Ministerio de Ciencia e Innovación (AGL-2009–13906-C02 and AGL2010–22319-C03); the Fundación Mapfre 2010, Consejería de Salud de la Junta de Andalucía (PI0105/2007); the Public Health Division of the Department of Health of the Autonomous Government of Catalonia, Generalitat Valenciana (ACOMP06109, GVACOMP2010–181, GVACOMP2011–151, CS2010-AP-111, and CS2011-AP-042); and the Regional Government of Navarra (P27/2011). Dr. Dong D Wang was supported by a postdoctoral fellowship granted by the American Heart Association (16POST31100031)

To support food security for current and future generations, there is a need to understand the relation between sustainable diets and the health of a population. In recent years, a number of studies have investigated and compared different dietary patterns to better understand which foods and eating patterns have less of an environmental impact while meeting nutritional needs and promoting health. This systematic review (SR) of population-level dietary patterns and food sustainability extends and updates the SR that was conducted by the 2015 US Dietary Guidelines Advisory Committee, an expert committee commissioned by the federal government to inform dietary guidance as it relates to the committee's original conclusions. In the original SR, 15 studies met the criteria for inclusion; since then, an additional 8 studies have been identified and included. The relations between dietary intake patterns and both health and environmental outcomes were compared across studies, with methodologies that included modeling, life cycle assessment, and land use analysis. Across studies, consistent evidence indicated that a dietary pattern higher in plant-based foods (e.g., vegetables, fruits, legumes, seeds, nuts, whole grains) and lower in animal-based foods (especially red meat), as well as lower in total energy, is both healthier and associated with a lesser impact on the environment. This dietary pattern differs from current average consumption patterns in the United States. Our updated SR confirms and strengthens the conclusions of the original US Dietary Guidelines Advisory Committee SR, which found that adherence to several well-characterized dietary patterns, including vegetarian (with variations) diets, dietary guidelines–related diets, Mediterranean-style diets, the Dietary Approaches to Stop Hypertension (DASH) diet, and other sustainable diet scenarios, promotes greater health and has a less negative impact on the environment than current average dietary intakes.

Background Consumption of sugar-sweetened beverages (SSBs) has been consistently associated with a higher risk of obesity, type 2 diabetes, cardiovascular disease, and premature mortality, whereas evidence for artificially sweetened beverages (ASBs) and fruit juices on health is less solid. The aim of this study was to evaluate the consumption of SSBs, ASBs, and fruit juices in association with frailty risk among older women. Methods and findings We analyzed data from 71,935 women aged ≥60 (average baseline age was 63) participating in the Nurses' Health Study (NHS), an ongoing cohort study initiated in 1976 among female registered nurses in the United States. Consumption of beverages was derived from 6 repeated food frequency questionnaires (FFQs) administered between 1990 and 2010. Frailty was defined as having at least 3 of the following 5 criteria from the FRAIL scale: fatigue, poor strength, reduced aerobic capacity, having ≥5 chronic illnesses, and weight loss ?5%. The occurrence of frailty was assessed every 4 years from 1992 to 2014. During 22 years of follow-up, we identified 11,559 incident cases of frailty. Consumption of SSBs was associated with higher risk of frailty after adjustment for diet quality, body mass index (BMI), smoking status, and medication use, specifically, the relative risks (RRs) and 95% confidence interval (95% CI) for ≥2 serving/day versus no SSB consumption was 1.32 (1.10, 1.57); p-value <0.001. ASBs were also associated with frailty [RR ≥2 serving/day versus no consumption: 1.28 (1.17, 1.39); p-value <0.001]. Orange juice was associated with lower risk of frailty [RR ≥1 serving/day versus no consumption: 0.82 (0.76, 0.87); p-value <0.001], whereas other juices were associated with a slightly higher risk [RR ≥1 serving/day versus no consumption: 1.15 (1.03, 1.28); p-value <0.001]. A limitation of this study is that, due to self-reporting of diet and frailty, certain misclassification bias cannot be ruled out; also, some residual confounding may persist. Conclusions In this study, we observed that consumption of SSBs and ASBs was associated with a higher risk of frailty. However, orange juice intake showed an inverse association with frailty. These results need to be confirmed in further studies using other frailty definitions. Copyright: ; This work was supported by grants from the Instituto de Salud Carlos III, State Secretary of R+D+I of Spain and FEDER/FSE (FIS 16/609, 16/1512, 19/319) (FRA and ELG); the European Union (JPI A Healthy Diet for a Healthy Life, SALAMANDER project) (FRA); and the Nurses´ health study is supported by grant UM1 CA186107 from National Institutes of Health (http://www.nih.gov/).

IntroductionThe Department of Veterans Affairs (VA) Million Veteran Program (MVP) nutrition data is derived from dietary food/beverage intake information collected through a semiquantitative food frequency questionnaire (SFFQ).
MethodsEstimates of dietary energy, nutrient, and non-nutritive food components intakes data were derived from an extensively validated SFFQ, which assessed the habitual frequency of consumption of 61 food items, added sugar, fried food frequency, and 21 nutritional supplements over the 12 months preceding questionnaire administration.
ResultsComplete nutrition data was available for 353,418 MVP participants as of 30th September 2021. Overall, 91.5% of MVP participants with nutrition data were male with an average age of 65.7 years at enrollment. Participants who completed the SFFQ were primarily White (82.5%), and Blacks accounted for 13.2% of the responders. Mean ± SD energy intake for 353, 418 MVP participants was 1428 ±616 kcal/day, which was 1434 ±617 kcal/day for males and 1364 ±601 kcal/day for females. Energy intake and information on 322 nutrients and non-nutritive food components is available through contact with MVP for research collaborations at www.research.va.gov/mvp.
ConclusionsThe energy and nutrient data derived from MVP SFFQ are an invaluable resource for Veteran health and research. In conjunction with the MVP Lifestyle Survey, electronic health records, and genomic data, MVP nutrition data may be used to assess nutritional status and related risk factors, disease prevalence, and determinants of health that can provide scientific support for the development of evidence-based public health policy and health promotion programs and services for Veterans and general population.

As obesity rates increase, so too do the risks of type 2 diabetes, cardiovascular disease, and numerous other detrimental conditions. The prevalence of obesity in U.S. adults more than doubled between 1980 and 2010, from 15.0 to 36.1%. Although this trend may be leveling off, obesity and its individual, societal, and economic costs remain of grave concern. In June 2014, a Diabetes Care Editors' Expert Forum convened to review the state of obesity research and discuss the latest prevention initiatives and behavioral, medical, and surgical therapies. This article, an outgrowth of the forum, offers an expansive view of the obesity epidemic, beginning with a discussion of its root causes. Recent insights into the genetic and physiological factors that influence body weight are reviewed, as are the pathophysiology of obesity-related metabolic dysfunction and the concept of metabolically healthy obesity. The authors address the crucial question of how much weight loss is necessary to yield meaningful benefits. They describe the challenges of behavioral modification and predictors of its success. The effects of diabetes pharmacotherapies on body weight are reviewed, including potential weight-neutral combination therapies. The authors also summarize the evidence for safety and efficacy of pharmacotherapeutic and surgical obesity treatments. The article concludes with an impassioned call for researchers, clinicians, governmental agencies, health policymakers, and health-related industries to collectively embrace the urgent mandate to improve prevention and treatment and for society at large to acknowledge and manage obesity as a serious disease.

India has the second largest number of people with diabetes in the world following China. Evidence indicates that consumption of whole grains can reduce risk of type 2 diabetes. This manuscript describes the study design and methods of a trial in progress evaluating the effects of substituting whole grain brown rice for polished (refined) white rice on biomarkers of diabetes risk (glucose metabolism, dyslipidemia, inflammation). This is a randomized controlled clinical trial with a crossover design conducted in Chennai, India among overweight but otherwise healthy volunteers aged 25–65y with a body mass index ≥23kg/m2 and habitual rice consumption ≥200grams/day. The feasibility and cultural appropriateness of this type of intervention in the local environment will also be examined. If the intervention is efficacious, the findings can be incorporated into national-level policies which could include the provision of brown rice as an option or replacement for white rice in government institutions and food programs. This relatively simple dietary intervention has the potential to substantially diminish the burden of diabetes in Asia and elsewhere.

BACKGROUND: Glutamate metabolism may play a role in the pathophysiology of cardiometabolic disorders. However, there is limited evidence of an association between glutamate-related metabolites and, moreover, changes in these metabolites, and risk of cardiovascular disease (CVD). METHODS AND RESULTS: Plasma levels of glutamate and glutamine were measured at baseline and 1-year follow-up in a case-cohort study including 980 participants (mean age 68 years; 46% male) from the PREvención con DIeta MEDiterránea (PREDIMED) randomized trial, which assessed a Mediterranean diet intervention in the primary prevention of CVD. During median 4.8 years of follow-up, there were 229 incident CVD events (nonfatal stroke, nonfatal myocardial infarction, or CVD death). In fully adjusted models, per 1-SD, baseline glutamate was associated with 43% (95% CI: 16% to 76%) and 81% (39% to 137%) increased risk of composite CVD and stroke alone, respectively, and baseline glutamine-to-glutamate ratio with 25% (6% to 40%) and 44% (25% to 58%) decreased risk of composite CVD and stroke alone, respectively. Associations appeared linear for stroke (both Plinear trend≤0.005). Among participants with high baseline glutamate, the interventions lowered CVD risk by 37% compared to the control diet; the intervention effects were not significant when baseline glutamate was low (Pinteraction=0.02). No significant effect of the intervention on year-1 changes in metabolites was observed, and no effect of changes themselves on CVD risk was apparent. CONCLUSIONS: Baseline glutamate was associated with increased CVD risk, particularly stroke, and glutamine-to-glutamate ratio was associated with decreased risk. Participants with high glutamate levels may obtain greater benefits from the Mediterranean diet than those with low levels. ; This work was supported by the National Institutes of Health, 1R01HL118264. The PREDIMED trial was supported by the official funding agency for Biomedical Research of the Spanish Government, Instituto de Salud Carlos III, through grants provided to research networks specifically developed for the trial: RTIC G03/140 (Period 2003–2006, Coordinator: R. Estruch, MD, PhD), and RTIC RD 06/0045 (Period 2007–2013, Coordinator: M. A. Martinez-Gonzalez, MD, PhD). We also acknowledge the grants from Centro Nacional de Investigaciones Cardiovasculares CNIC06/2007,Fondo de Investigaci on Sanitaria—Fondo Europeo de Desarrollo Regional (PI04-2239, PI05/2584, CP06/00100, PI07/0240, PI07/1138, PI07/0954, PI 07/0473, PI08/1259, PI10/01407, PI11/01647, PI11/01791), and Consejer ıa de Salud de la Junta de Andaluc ıa (PI0105/2007). Ministerio de Ciencia e Innovaci on (AGL-2009- 13906-C02, AGL2010-22319-C03), Fundaci on Mapfre 2010, Consejeria de Salud de la Junta de Andalucia (PI0105/2007), Agencia Canaria de Investigaci on, Innovaci on y Sociedad de la Informaci on-EU FEDER (PI 2007/050), Public Health Division of the Department of Health of the Autonomous Government of Catalonia and Generalitat Valenciana (ACOMP06109, GVACOMP2010-181, GVACOMP2011-151, CS2010-AP-111, CS2011-AP-042, AP-042/11 and BEST11-263) and Ministerio de Econom ıa (PI07-0954, CNIC-06, AGL2010-22319-C03-03, PI11/02505). CIBEROBN is an initiative of ISCIII, Spain.

BACKGROUND: Previous studies have suggested that metabolite profiles of elevated acylcarnitines were associated with increased risk of cardiovascular disease (CVD) in populations with established coronary disease. However, to our knowledge, this association has not been evaluated in the context of primary cardiovascular prevention. OBJECTIVES: We evaluated the association between 28 plasma acylcarnitine species and risk of incident CVD and the potential modifying effect of Mediterranean diet (MedDiet) interventions. DESIGN: We measured plasma acylcarnitines with the use of high-throughput liquid chromatography-tandem mass spectrometry at baseline and after 1 y of follow-up, both individually and classified into short-, medium-, or long-chain scores, in a case-cohort study within the Prevención con Dieta Mediterránea (PREDIMED) study, which is a randomized Mediterranean dietary intervention for primary cardiovascular prevention. A randomly selected subcohort (n = 751) and all available incident CVD cases (n = 229) after 4.8 y of follow-up were included in the current study. RESULTS: After adjustment for age, sex, body mass index, and other CVD risk factors, participants in the highest quartile of baseline short- and medium-chain acylcarnitines had a higher risk of CVD than did participants in the lowest quartile [HRs: 1.80 (95% CI: 1.11, 2.91; P-trend 0.01) and 1.55 (95% CI: 1.01, 2.48; P-trend = 0.04), respectively]. Increased short-chain acylcarnitines after 1 y were associated with higher risks of total CVD and stroke. Participants with higher baseline concentrations of short-, medium-, and long-chain acylcarnitines who were randomly assigned to the control group had a higher risk of CVD than did subjects with lower concentrations of acylcarnitines who were assigned to the MedDiet group. CONCLUSIONS: Our data support the conclusion that metabolite profiles characterized by elevated concentrations of acylcarnitines are independently associated with risks of total CVD and stroke alone in participants at high risk of CVD. MedDiet interventions may mitigate the adverse associations shown between higher concentrations of acylcarnitines and CVD. ; The Prevención con Dieta Mediterránea (PREDIMED) trial was supported by the official funding agency for biomedical research of the Spanish government, the Instituto de Salud Carlos III, through grants provided to research networks specifically developed for the trial [grant RTIC G03/140 (to RE); grant RTIC RD 06/0045 (to MAM-G)] and through the Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición and by grants from Centro Nacional de Investigaciones Cardiovasculares (grant CNIC 06/2007), the Fondo de Investigación Sanitaria–Fondo Europeo de Desarrollo Regional (grants PI04–2239, PI 05/2584, CP06/00100, PI07/0240, PI07/1138, I07/0954, PI 07/0473, PI10/01407, PI10/02658, PI11/01647, P11/02505, and PI13/00462), the Ministerio de Ciencia e Innovación (grants AGL-2009–13906-C02 and AGL2010–22319-C03), the Fundación Mapfre 2010, Consejería de Salud de la Junta de Andalucía (grant PI0105/2007), the Public Health Division of the Department of Health of the Autonomous Government of Catalonia, Generalitat Valenciana (grants ACOMP06109, GVA-COMP2010–181, GVACOMP2011–151, CS2010-AP-111, and CS2011-AP-042), and the Regional Government of Navarra (grant P27/2011).

BACKGROUND: The relationship between plasma concentrations of betaine and choline metabolism and major cardiovascular disease (CVD) end points remains unclear. We have evaluated the association between metabolites from the choline pathway and risk of incident CVD and the potential modifying effect of Mediterranean diet interventions. METHODS AND RESULTS: We designed a case-cohort study nested within the PREDIMED (Prevention With Mediterranean Diet) trial, including 229 incident CVD cases and 751 randomly selected participants at baseline, followed up for 4.8 years. We used liquid chromatography-tandem mass spectrometry to measure, at baseline and at 1 year of follow-up, plasma concentrations of 5 metabolites in the choline pathway: trimethylamine N-oxide, betaine, choline, phosphocholine, and α-glycerophosphocholine. We have calculated a choline metabolite score using a weighted sum of these 5 metabolites. We used weighted Cox regression models to estimate CVD risk. The multivariable hazard ratios (95% confidence intervals) per 1-SD increase in choline and α-glycerophosphocholine metabolites were 1.24 (1.05-1.46) and 1.24 (1.03-1.50), respectively. The baseline betaine/choline ratio was inversely associated with CVD. The baseline choline metabolite score was associated with a 2.21-fold higher risk of CVD across extreme quartiles (95% confidence interval, 1.36-3.59; P<0.001 for trend) and a 2.27-fold higher risk of stroke (95% confidence interval, 1.24-4.16; P<0.001 for trend). Participants in the higher quartiles of the score who were randomly assigned to the control group had a higher risk of CVD compared with participants in the lower quartile and assigned to the Mediterranean diet groups (P=0.05 for interaction). No significant associations were observed for 1-year changes in individual plasma metabolites and CVD. CONCLUSIONS: A metabolite score combining plasma metabolites from the choline pathway was associated with an increased risk of CVD in a Mediterranean population at high cardiovascular risk. ; This work was supported by NIH research grant HL118264. The PREDIMED trial was supported by the official funding agency for biomedical research of the Spanish Government, Instituto de Salud Carlos III, through grants provided to research networks specifically developed for the trial (RTIC G03/140 to Estruch; RTIC RD 06/0045 to Martínez‐González) and through Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición; and by grants from Centro Nacional de Investigaciones Cardiovasculares (06/2007), Fondo de Investigación Sanitaria–Fondo Europeo de Desarrollo Regional (PI04–2239, PI05/2584, CP06/00100, PI07/0240, PI07/1138, PI07/0954, PI 07/0473, PI10/01407, PI10/02658, PI11/01647, P11/02505, and PI13/00462), Ministerio de Ciencia e Innovación (AGL‐2009–13906‐C02 and AGL2010–22319‐C03), Fundación Mapfre 2010, Consejería de Salud de la Junta de Andalucía (PI0105/2007), Public Health Division of the Department of Health of the Autonomous Government of Catalonia, Generalitat Valenciana (ACOMP06109, GVA‐COMP2010–181, GVACOMP2011–151, CS2010‐AP‐111, and CS2011‐AP‐042), and Regional Government of Navarra (P27/2011). Guasch‐Ferré was supported by a postdoctoral fellowship granted by the Agency for Administration of University and Research Grants of the Autonomous Government of Catalonia (2014‐BP‐A 00017).

Studies examining associations between purine metabolites and type 2 diabetes (T2D) are limited. We prospectively examined associations between plasma levels of purine metabolites with T2D risk and the modifying effects of transcription factor-7-like-2 (TCF7L2) rs7903146 polymorphism on these associations. This is a case-cohort design study within the PREDIMED study, with 251 incident T2D cases and a random sample of 694 participants (641 non-cases and 53 overlapping cases) without T2D at baseline (median follow-up: 3.8 years). Metabolites were semi-quantitatively profiled with LC-MS/MS. Cox regression analysis revealed that high plasma allantoin levels, including allantoin-to-uric acid ratio and high xanthine-to-hypoxanthine ratio were inversely and positively associated with T2D risk, respectively, independently of classical risk factors. Elevated plasma xanthine and inosine levels were associated with a higher T2D risk in homozygous carriers of the TCF7L2-rs7903146 T-allele. The potential mechanisms linking the aforementioned purine metabolites and T2D risk must be also further investigated. ; This study was supported by research grant R01-DK-102896 from the National Institutes of Health. The Prevención con DietaMediterránea (PREDIMED) trial was supported by the official funding agency for biomedical research of the Spanish government, the Instituto de Salud Carlos III, through grants provided to research networks specifically developed for the trial [grant RTIC G03/140 (to Ramón Estruch); grant RTIC RD 06/0045 (to Miguel A. Martínez-González)] and through the Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición and by grants from Centro Nacional de Investigaciones Cardiovasculares (grant CNIC 06/2007), the Fondo de Investigación Sanitaria Fondo Europeo de Desarrollo Regional (grants PI04–2239, PI 05/2584, CP06/00100, PI07/0240, PI07/1138, PI07/0954, PI 07/0473, PI10/01407, PI10/02658, PI11/01647, P11/02505, and PI13/00462), the Ministerio de Ciencia e Innovación (grants AGL-2009–13906-C02 and AGL2010–22319-C03), the Fundación Mapfre 2010, Consejería de Salud de la Junta de Andalucía (grant PI0105/2007), the Public Health Division of the Department of Health of the Autonomous Government of Catalonia, Generalitat Valenciana (grants ACOMP06109, GVA-COMP2010–181, GVACOMP2011–151, CS2010-AP-111, and CS2011-AP-042), and the Regional Government of Navarra (grant P27/2011). Genotyping of the TCF7L2-rs7903146 polymorphism was supported by PROMETEO17/2017 from the Generalitat Valenciana, and 538/U/2016 from Fundacio la Marato-TV3. Dr. Christopher Papandreou was supported by a postdoctoral fellowship granted by the Autonomous Government of Catalonia (PERIS 2016-2020 INCORPORACIÓ DE CIENTÍFICAS I TECNÒLEGS, SLT002/0016/00428). Dr Marta Guasch-Ferré was supported by a postdoctoral fellowship granted by the Lilly Foundation European Association of Diabetes (EASD) through the Institut d'Investigacions Sanitàries Pere i Virgili (IISPV), Tarragona, Spain. The authors are indebted to George A. Fragkiadakis (Department of Nutrition & Dietetics, Technological Education Institute of Crete, Greece) for his intellectual contributions to this manuscript.

Few studies have examined the association of a wide range of metabolites with total and subtypes of coffee consumption. The aim of this study was to investigate associations of plasma metabolites with total, caffeinated, and decaffeinated coffee consumption. We also assessed the ability of metabolites to discriminate between coffee consumption categories. This is a cross-sectional analysis of 1664 participants from the PREDIMED study. Metabolites were semiquantitatively profiled using a multiplatform approach. Consumption of total coffee, caffeinated coffee and decaffeinated coffee was assessed by using a validated food frequency questionnaire. We assessed associations between 387 metabolite levels with total, caffeinated, or decaffeinated coffee consumption (≥50 mL coffee/day) using elastic net regression analysis. Ten-fold cross-validation analyses were used to estimate the discriminative accuracy of metabolites for total and subtypes of coffee. We identified different sets of metabolites associated with total coffee, caffeinated and decaffeinated coffee consumption. These metabolites consisted of lipid species (e.g., sphingomyelin, phosphatidylethanolamine, and phosphatidylcholine) or were derived from glycolysis (alpha-glycerophosphate) and polyphenol metabolism (hippurate). Other metabolites included caffeine, 5-acetylamino-6-amino-3-methyluracil, cotinine, kynurenic acid, glycocholate, lactate, and allantoin. The area under the curve (AUC) was 0.60 (95% CI 0.56–0.64), 0.78 (95% CI 0.75–0.81) and 0.52 (95% CI 0.49–0.55), in the multimetabolite model, for total, caffeinated, and decaffeinated coffee consumption, respectively. Our comprehensive metabolic analysis did not result in a new, reliable potential set of metabolites for coffee consumption. ; This study was funded by the National Institutes of Health (R01DK102896, F31DK114938, NIH/NHLBI 1R01HL118264, NIH/NHLBI 2R01HL118264), the Spanish Ministry of Health (Instituto de Salud Carlos III, RD 06/0045- Coordinator: MAM-G), the Ministerio de Economía y Competitividad-Fondo Europeo de Desarrollo Regional (Projects CNIC-06/2007, RTIC G03/140, CIBER 06/03, PI06-1326, PI07-0954, PI11/02505, SAF2009-12304 and AGL2010-22319-C03-03), and by the Generalitat Valenciana (ACOMP2010-181, AP111/10, AP-042/11, ACOM2011/145, ACOMP/2012/190, ACOMP/2013/159 and ACOMP/213/165). Dr. Christopher Papandreou was supported by a postdoctoral fellowship granted by the Autonomous Government of Catalonia (PERIS2016-2020 Incorporació de Científics I Tecnòlegs, SLT002/0016/00428). Dr. Marta Guasch-Ferré was supported by EFSD (European Foundation for the Study of Diabetes)/Lilly through the Institut d'Investigacions Sanitàries Pere I Virgili (IISPV).

OBJECTIVE: To investigate whether the genetic burden of type 2 diabetes modifies the association between the quality of dietary fat and the incidence of type 2 diabetes. DESIGN: Individual participant data meta-analysis. DATA SOURCES: Eligible prospective cohort studies were systematically sourced from studies published between January 1970 and February 2017 through electronic searches in major medical databases (Medline, Embase, and Scopus) and discussion with investigators. REVIEW METHODS: Data from cohort studies or multicohort consortia with available genome-wide genetic data and information about the quality of dietary fat and the incidence of type 2 diabetes in participants of European descent was sought. Prospective cohorts that had accrued five or more years of follow-up were included. The type 2 diabetes genetic risk profile was characterized by a 68-variant polygenic risk score weighted by published effect sizes. Diet was recorded by using validated cohort-specific dietary assessment tools. Outcome measures were summary adjusted hazard ratios of incident type 2 diabetes for polygenic risk score, isocaloric replacement of carbohydrate (refined starch and sugars) with types of fat, and the interaction of types of fat with polygenic risk score. RESULTS: Of 102 305 participants from 15 prospective cohort studies, 20 015 type 2 diabetes cases were documented after a median follow-up of 12 years (interquartile range 9.4-14.2). The hazard ratio of type 2 diabetes per increment of 10 risk alleles in the polygenic risk score was 1.64 (95% confidence interval 1.54 to 1.75, I2=7.1%, τ2=0.003). The increase of polyunsaturated fat and total omega 6 polyunsaturated fat intake in place of carbohydrate was associated with a lower risk of type 2 diabetes, with hazard ratios of 0.90 (0.82 to 0.98, I2=18.0%, τ2=0.006; per 5% of energy) and 0.99 (0.97 to 1.00, I2=58.8%, τ2=0.001; per increment of 1 g/d), respectively. Increasing monounsaturated fat in place of carbohydrate was associated with a higher risk of type 2 diabetes (hazard ratio 1.10, 95% confidence interval 1.01 to 1.19, I2=25.9%, τ2=0.006; per 5% of energy). Evidence of small study effects was detected for the overall association of polyunsaturated fat with the risk of type 2 diabetes, but not for the omega 6 polyunsaturated fat and monounsaturated fat associations. Significant interactions between dietary fat and polygenic risk score on the risk of type 2 diabetes (P>0.05 for interaction) were not observed. CONCLUSIONS: These data indicate that genetic burden and the quality of dietary fat are each associated with the incidence of type 2 diabetes. The findings do not support tailoring recommendations on the quality of dietary fat to individual type 2 diabetes genetic risk profiles for the primary prevention of type 2 diabetes, and suggest that dietary fat is associated with the risk of type 2 diabetes across the spectrum of type 2 diabetes genetic risk. ; The EPIC-InterAct study received funding from the European Union (Integrated Project LSHM-CT-2006-037197 in the Framework Programme 6 of the European Community). We thank all EPIC participants and staff for their contribution to the study. We thank Nicola Kerrison (MRC Epidemiology Unit, University of Cambridge, Cambridge, UK) for managing the data for the InterAct Project. In addition, InterAct investigators acknowledge funding from the following agencies: MT: Health Research Fund (FIS) of the Spanish Ministry of Health; the CIBER en Epidemiología y Salud Pública (CIBERESP), Spain; Murcia Regional Government (N° 6236); JS: JS was supported by a Heisenberg-Professorship (SP716/2-1), a Clinical Research Group (KFO218/1) and a research group (Molecular Nutrition to JS) of the Bundesministerium für Bildung und Forschung (BMBF); YTvdS, JWJB, PHP, IS: Verification of diabetes cases was additionally funded by NL Agency grant IGE05012 and an Incentive Grant from the Board of the UMC Utrecht; HBBdM: Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF), Statistics Netherlands (The Netherlands); MDCL: Health Research Fund (FIS) of the Spanish Ministry of Health; Murcia Regional Government (N° 6236); FLC: Cancer Research UK; PD: Wellcome Trust; LG: Swedish Research Council; GH: The county of Västerbotten; RK: Deutsche Krebshilfe; TJK: Cancer Research UK; KK: Medical Research Council UK, Cancer Research UK; AK: Medical Research Council (Cambridge Lipidomics Biomarker Research Initiative); CN: Health Research Fund (FIS) of the Spanish Ministry of Health; Murcia Regional Government (N° 6236); KO: Danish Cancer Society; OP: Faculty of Health Science, 47 University of Aarhus, Denmark; JRQ: Asturias Regional Government; LRS: Asturias Regional Government; AT: Danish Cancer Society; RT: AIRE-ONLUS Ragusa, AVIS-Ragusa, Sicilian Regional Government; DLvdA, WMMV: Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF), Statistics Netherlands (The Netherlands); MMC: Wellcome Trust (083270/Z/07/Z), MRC (G0601261).

HapMap imputed genome-wide association studies (GWAS) have revealed >50 loci at which common variants with minor allele frequency >5% are associated with kidney function. GWAS using more complete reference sets for imputation, such as those from The 1000 Genomes project, promise to identify novel loci that have been missed by previous efforts. To investigate the value of such a more complete variant catalog, we conducted a GWAS meta-analysis of kidney function based on the estimated glomerular filtration rate (eGFR) in 110,517 European ancestry participants using 1000 Genomes imputed data. We identified 10 novel loci with p-value < 5 × 10−8 previously missed by HapMap-based GWAS. Six of these loci (HOXD8, ARL15, PIK3R1, EYA4, ASTN2, and EPB41L3) are tagged by common SNPs unique to the 1000 Genomes reference panel. Using pathway analysis, we identified 39 significant (FDR < 0.05) genes and 127 significantly (FDR < 0.05) enriched gene sets, which were missed by our previous analyses. Among those, the 10 identified novel genes are part of pathways of kidney development, carbohydrate metabolism, cardiac septum development and glucose metabolism. These results highlight the utility of re-imputing from denser reference panels, until whole-genome sequencing becomes feasible in large samples. ; 3C. Three-City Study. The work was made possible by the participation of the control subjects, the patients, and their families. We thank Dr. Anne Boland (CNG) for her technical help in preparing the DNA samples for analyses. This work was supported by the National Foundation for Alzheimer's disease and related disorders, the Institut Pasteur de Lille and the Centre National de Génotypage. The 3C Study was performed as part of a collaboration between the Institut National de la Santé et de la Recherche Médicale (Inserm), the Victor Segalen Bordeaux II University and Sanofi-Synthélabo. The Fondation pour la Recherche Médicale funded the preparation and initiation of the study. The 3C Study was also funded by the Caisse Nationale Maladie des Travailleurs Salariés, Direction Générale de la Santé, MGEN, Institut de la Longévité, Agence Française de Sécurité Sanitaire des Produits de Santé, the Aquitaine and Bourgogne Regional Councils, Fondation de France and the joint French Ministry of Research/INSERM "Cohortes et collections de données biologiques" programme. Lille Génopôle received an unconditional grant from Eisai. AGES. Age, Gene/Environment Susceptibility-Reykjavik Study. This study has been funded by NIH contract N01-AG-1-2100, the NIA Intramural Research Program, Hjartavernd (the Icelandic Heart Association), and the Althingi (the Icelandic Parliament). The study is approved by the Icelandic National Bioethics Committee, VSN: 00-063. The researchers are indebted to the participants for their willingness to participate in the study. ARIC. Atherosclerosis Risk in Communities study. The ARIC study is carried out as a collaborative study supported by National Heart, Lung, and Blood Institute contracts (HHSN268201100005C, HHSN268201100006C, HHSN268201100007C, HHSN268201100008C, HHSN268201100009C, HHSN268201100010C, HHSN268201100011C, and HHSN268201100012C), R01HL087641, R01HL59367 and R01HL086694; National Human Genome Research Institute contract U01HG004402; and National Institutes of Health contract HHSN268200625226C. The authors thank the staff and participants of the ARIC study for their important contributions. Infrastructure was partly supported by Grant Number UL1RR025005, a component of the National Institutes of Health and NIH Roadmap for Medical Research. This work as well as YL and AK were supported by the German Research Foundation (KO 3598/2-1, KO 3598/3-1 and CRC1140 A05 to AK). ASPS. Austrian Stroke Prevention Study. The research reported in this article was funded by the Austrian Science Fond (FWF) grant number P20545-P05 and P13180. The Medical University of Graz supports the databank of the ASPS. The authors thank the staff and the participants of the ASPS for their valuable contributions. We thank Birgit Reinhart for her long-term administrative commitment and Ing Johann Semmler for the technical assistance at creating the DNA-bank. BMES. Blue Mountains Eye Study. The BMES has been supported by the Australian RADGAC grant (1992- 94) and Australian National Health & Medical Research Council, Canberra Australia (Grant Nos: 974159, 211069, 991407, 457349). The GWAS studies of Blue Mountains Eye Study population are supported by the Australian National Health & Medical Research Council (Grant Nos: 512423, 475604, 529912) and the Wellcome Trust, UK (2008). EGH and JJW are funded by the Australian National Health & Medical Research Council Fellowship Schemes. CILENTO. Italian Network on Genetic Isolates – Cilento. We thank the populations of Cilento for their participation in the study. The study was supported by the Italian Ministry of Universities and CNR 36 (PON03PE_00060_7, Interomics Flagship Project), the Assessorato Ricerca Regione Campania, the Fondazione con il SUD (2011-PDR-13), and the Istituto Banco di Napoli - Fondazione to MC. COLAUS. The CoLaus authors thank Yolande Barreau, Mathieu Firmann, Vladimir Mayor, Anne-Lise Bastian, Binasa Ramic, Martine Moranville, Martine Baumer, Marcy Sagette, Jeanne Ecoffey and Sylvie Mermoud for data collection. The CoLaus study received financial contributions from GlaxoSmithKline, the Faculty of Biology and Medicine of Lausanne, the Swiss National Science Foundation (33CSCO- 122661, 3200BO-111361/2, 3100AO-116323/1, 310000-112552). The computations for CoLaus imputation were performed in part at the Vital-IT center for high performance computing of the Swiss Institute of Bioinformatics. We thank Vincent Mooser for his contribution to the CoLaus study. EGCUT. Estonian Genome Center University of Tartu. EGCUT received financing from FP7 grants (278913, 306031, 313010) and targeted financing from Estonian Government (SF0180142s08). EGCUT studies were covered from Infra-structure grant no. 3.2.0304.11-0312 funded mostly by the European Regional Development Fund, Center of Excellence in Genomics (EXCEGEN) and University of Tartu (SP1GVARENG). We acknowledge EGCUT technical personnel, especially Mr V. Soo and S. Smit. Data analyses were carried out in part in the High Performance Computing Center of the University of Tartu. FamHS. Family Heart Study. The FHS work was supported in part by NIH grants 5R01HL08770003, 5R01HL08821502 (Michael A. Province) from the NHLBI and 5R01DK07568102, 5R01DK06833603 from the NIDDK (I.B.B.). The authors thank the staff and participants of the FamHS for their important contributions. FHS. Framingham Heart Study. This research was conducted in part using data and resources from the Framingham Heart Study of the National Heart Lung and Blood Institute of the National Institutes of Health and Boston University School of Medicine. The analyses reflect intellectual input and resource development from the Framingham Heart Study investigators participating in the SNP Health Association Resource (SHARe) project. This work was partially supported by the National Heart, Lung and Blood Institute's Framingham Heart Study (Contract No. N01-HC-25195) and its contract with Affymetrix, Inc. for genotyping services (Contract No. N02-HL-6-4278). A portion of this research utilized the Linux Cluster for Genetic Analysis (LinGA-II) funded by the Robert Dawson Evans Endowment of the Department of Medicine at Boston University School of Medicine and Boston Medical Center. GENDIAN. GENetics of DIAbetic Nephropathy study. The support of the physicians, the patients, and the staff of the Diabetes Zentrum Mergentheim (Head: Prof. Dr. Thomas Haak), the diabetes outpatient clinic Dr Nusser - Dr Kreisel, the dialysis centers KfH Amberg, KfH Bayreuth, KfH Deggendorf, KfH Donauwörth, KfH Freising, KfH Freyung, KfH Fürth, KfH Hof, KfH Ingolstadt, KfH Kelheim, KfH München Elsenheimerstraße, KfH München-Schwabing, KfH Neumarkt, KfH Neusäß, KfH Oberschleißheim, KfH Passau, KfH Plauen, KfH Regensburg Günzstraße, KfH Regensburg Caritas-Krankenhaus, KfH Straubing, KfH Sulzbach-Rosenberg, KfH Weiden, Dialysezentrum Augsburg Dr. Kirschner, Dialysezentrum Bad Alexandersbad, KfH Bamberg, Dialysezentrum Emmering, Dialysezentrum Klinikum Landshut, Dialysezentrum Landshut, Dialysezentrum Pfarrkirchen, Dialysezentrum Schwandorf, Dr. Angela Götz, the medical doctoral student Johanna Christ and the Study Nurse Ingrid Lugauer. The expert technical assistance of Claudia Strohmeier is acknowledged. Phenotyping was funded by the Dr. Robert PflegerStiftung (Dr Carsten A. Böger), the MSD Stipend Diabetes (Dr Carsten A. Böger) and the University Hospital of Regensburg (intramural grant ReForM A to Dr. A. Götz, ReForM C to Dr. Carsten Böger). Genome-wide genotyping was funded by the KfH Stiftung Präventivmedizin e.V. (Dr. Carsten A. Böger, Dr. Jens Brüning), the Else Kröner-Fresenius-Stiftung (2012_A147 to Dr Carsten A. Böger and Dr Iris M. Heid) and the University Hospital Regensburg (Dr Carsten A. Böger). Data analysis was funded by the Else 37 Kröner-Fresenius Stiftung (Dr. Iris M. Heid and Dr. Carsten A. Böger: 2012_A147; Dr. Carsten A. Böger and Dr. Bernhard K. Krämer: P48/08//A11/08). GENDIAN Study Group: Mathias Gorski, Iris M. Heid, Bernhard K. Krämer, Myriam Rheinberger, Michael Broll, Alexander Lammert, Jens Brüning, Matthias Olden, Klaus Stark, Claudia Strohmeier, Simone Neumeier, Sarah Hufnagel, Petra Jackermeier, Emilia Ruff, Johanna Christ, Peter Nürnberg, Thomas Haak, Carsten A. Böger. HABC. Health Aging and Body Composition Study. The HABC study was funded by the National Institutes of Aging. This research was supported by NIA contracts N01AG62101, N01AG62103, and N01AG62106. The genome-wide association study was funded by NIA grant 1R01AG032098-01A1 to Wake Forest University Health Sciences and genotyping services were provided by the Center for Inherited Disease Research (CIDR). CIDR is fully funded through a federal contract from the National Institutes of Health to The Johns Hopkins University, contract number HHSN268200782096C. This research was supported in part by the Intramural Research Program of the NIH, National Institute on Aging. HCS. Hunter Community Study. The University of Newcastle provided $300,000 from its Strategic Initiatives Fund, and $600,000 from the Gladys M Brawn Senior Research Fellowship scheme; Vincent Fairfax Family Foundation, a private philanthropic trust, provided $195,000; The Hunter Medical Research Institute provided media support during the initial recruitment of participants; and Dr Anne Crotty, Prof. Rodney Scott and Associate Prof. Levi provided financial support towards freezing costs for the long-term storage of participant blood samples. The authors would like to thank the men and women participating in the HCS as well as all the staff, investigators and collaborators who have supported or been involved in the project to date. A special thank you should go to Alison Koschel and Debbie Quain who were instrumental in setting up the pilot study and initial phase of the project. HPFS. Health Professionals Follow-Up Study. The NHS/HPFS type 2 diabetes GWAS (U01HG004399) is a component of a collaborative project that includes 13 other GWAS (U01HG004738, U01HG004422, U01HG004402, U01HG004729, U01HG004726, U01HG004735, U01HG004415, U01HG004436, U01HG004423, U01HG004728, RFAHG006033; National Institute of Dental & Craniofacial Research: U01DE018993, U01DE018903) funded as part of the Gene Environment-Association Studies (GENEVA) under the NIH Genes, Environment and Health Initiative (GEI). Assistance with phenotype harmonization and genotype cleaning, as well as with general study coordination, was provided by the GENEVA Coordinating Center (U01HG004446). Assistance with data cleaning was provided by the National Center for Biotechnology Information. Genotyping was performed at the Broad Institute of MIT and Harvard, with funding support from the NIH GEI (U01HG04424), and Johns Hopkins University Center for Inherited Disease Research, with support from the NIH GEI (U01HG004438) and the NIH contract "High throughput genotyping for studying the genetic contributions to human disease"(HHSN268200782096C). Additional funding for the current research was provided by the National Cancer Institute (P01CA087969, P01CA055075), and the National Institute of Diabetes and Digestive and Kidney Diseases (R01DK058845). We thank the staff and participants of the NHS and HPFS for their dedication and commitment. INGI-CARLANTINO. Italian Network on Genetic Isolates – Carlantino. We thank Anna Morgan and Angela D'Eustacchio for technical support. We are grateful to the municipal administrators for their collaboration on the project and for logistic support. We thank all participants to this study. INGI-FVG. Italian Network on Genetic Isolates – Friuli Venezia-Giulia. We thank Anna Morgan and Angela D'Eustacchio for technical support. We are grateful to the municipal administrators for their collaboration on the project and for logistic support. We thank all participants to this study. 38 INGI-VAL BORBERA. Italian Network on Genetic Isolates – Val Borbera. We thank the inhabitants of the Val Borbera who made this study possible, the local administrations and the ASL-Novi Ligure (Al) for support. We also thank Clara Camaschella for data collection supervision and organization of the clinical data collection, Fiammetta Vigano` for technical help and Corrado Masciullo for building the analysis platform. The research was supported by funds from Compagnia di San Paolo, Torino, Italy; Fondazione Cariplo, Italy and Ministry of Health, Ricerca Finalizzata 2008 and 2011/2012, CCM 2010, PRIN 2009 and Telethon, Italy to DT. IPM. Mount Sinai BioMe Biobank Program. The Mount Sinai BioMe Biobank Program is supported by The Andrea and Charles Bronfman Philanthropies. KORA-F3 and F4. The genetic epidemiological work was funded by the NIH subcontract from the Children's Hospital, Boston, US, (H.E.W., I.M.H, prime grant 1 R01 DK075787-01A1), the German National Genome Research Net NGFN2 and NGFNplus (H.E.W. 01GS0823; WK project A3, number 01GS0834), the Munich Center of Health Sciences (MC Health) as part of LMUinnovativ, and by the Else KrönerFresenius-Stiftung (P48/08//A11/08; C.A.B., B.K.K; 2012_A147 to CAB and IMH.). The Genetic Epidemiology at the University of Regensburg received financial contributions from the BMBF (01ER1206 and 01ER1507). The kidney parameter measurements in F3 were funded by the Else Kröner-FreseniusStiftung (C.A.B., B.K.K.) and the Regensburg University Medical Center, Germany; in F4 by the University of Ulm, Germany (W.K.). Genome wide genotyping costs in F3 and F4 were in part funded by the Else Kröner-Fresenius-Stiftung (C.A.B., B.K.K.). De novo genotyping in F3 and F4 were funded by the Else Kröner-Fresenius-Stiftung (C.A.B., B.K.K.). The KORA research platform and the MONICA Augsburg studies were initiated and financed by the Helmholtz Zentrum München, German Research Center for Environmental Health, by the German Federal Ministry of Education and Research and by the State of Bavaria. Genotyping was performed in the Genome Analysis Center (GAC) of the Helmholtz Zentrum München. The LINUX platform for computation were funded by the University of Regensburg for the Department of Epidemiology and Preventive Medicine at the Regensburg University Medical Center. LIFELINES. The authors wish to acknowledge the services of the Lifelines Cohort Study, the contributing research centers delivering data to Lifelines, and all the study participants. Lifelines group authors: Behrooz Z Alizadeh1 , H Marike Boezen1 , Lude Franke2 , Pim van der Harst3 , Gerjan Navis4 , Marianne Rots5 , Harold Snieder1 , Morris Swertz2 , Bruce HR Wolffenbuttel6 and Cisca Wijmenga2 1. Department of Epidemiology, University of Groningen, University Medical Center Groningen, The Netherlands 2. Department of Genetics, University of Groningen, University Medical Center Groningen, The Netherlands 3. Department of Cardiology, University of Groningen, University Medical Center Groningen, The Netherlands 4. Department of Internal Medicine, Division of Nephrology, University of Groningen, University Medical Center Groningen, The Netherlands 5. Department of Medical Biology, University of Groningen, University Medical Center Groningen, The Netherlands 6. Department of Endocrinology, University of Groningen, University Medical Center Groningen, The Netherlands MESA. Multi-Ethnic Study of Atherosclerosis. University of Washington (N01-HC-95159),Regents of the University of California (N01-HC-95160), Columbia University (N01-HC-95161), Johns Hopkins University 39 (N01-HC-95162, N01-HC-95168), University of Minnesota (N01-HC-95163), Northwestern University (N01-HC-95164), Wake Forest University (N01-HC-95165), University of Vermont (N01-HC-95166), New England Medical Center (N01-HC-95167), Harbor-UCLA Research and Education Institute (N01-HC- 95169), Cedars-Sinai Medical Center (R01-HL-071205), University of Virginia (subcontract to R01-HL- 071205) MICROS. Microisolates in South Tyrol study. We owe a debt of gratitude to all participants. We thank the primary care practitioners R. Stocker, S. Waldner, T. Pizzecco, J. Plangger, U. Marcadent and the personnel of the Hospital of Silandro (Department of Laboratory Medicine) for their participation and collaboration in the research project. In South Tyrol, the study was supported by the Ministry of Health and Department of Educational Assistance, University and Research of the Autonomous Province of Bolzano, the South Tyrolean Sparkasse Foundation, and the European Union framework program 6 EUROSPAN project (contract no. LSHG-CT-2006-018947). NESDA. The Netherlands Study of Depression and Anxiety. The infrastructure for the NESDA study is funded through the Geestkracht programme of the Dutch Scientific Organization (ZON-MW, grant number 10-000-1002) and matching funds from participating universities and mental health care organizations. Genotyping in NESDA was funded by the Genetic Association Information Network (GAIN) of the Foundation for the US National Institutes of Health. NHS. Nurses' Health Study. The NHS/HPFS type 2 diabetes GWAS (U01HG004399) is a component of a collaborative project that includes 13 other GWAS (U01HG004738, U01HG004422, U01HG004402, U01HG004729, U01HG004726, U01HG004735, U01HG004415, U01HG004436, U01HG004423, U01HG004728, RFAHG006033; National Institute of Dental & Craniofacial Research: U01DE018993, U01DE018903) funded as part of the Gene Environment-Association Studies (GENEVA) under the NIH Genes, Environment and Health Initiative (GEI). Assistance with phenotype harmonization and genotype cleaning, as well as with general study coordination, was provided by the GENEVA Coordinating Center (U01HG004446). Assistance with data cleaning was provided by the National Center for Biotechnology Information. Genotyping was performed at the Broad Institute of MIT and Harvard, with funding support from the NIH GEI (U01HG04424), and Johns Hopkins University Center for Inherited Disease Research, with support from the NIH GEI (U01HG004438) and the NIH contract "High throughput genotyping for studying the genetic contributions to human disease"(HHSN268200782096C). The NHS renal function and albuminuria work was supported by DK66574. Additional funding for the current research was provided by the National Cancer Institute (P01CA087969, P01CA055075), and the National Institute of Diabetes and Digestive and Kidney Diseases (R01DK058845). We thank the staff and participants of the NHS and HPFS for their dedication and commitment. NSPHS. The Northern Swedish Population Health Study. The NSPHS was supported by grants from the Swedish Natural Sciences Research Council, the European Union through the EUROSPAN project (contract no. LSHG-CT-2006-018947), the Foundation for Strategic Research (SSF) and the Linneaus Centre for Bioinformatics (LCB). We are also grateful for the contribution of samples from the Medical Biobank in Umeå and for the contribution of the district nurse Svea Hennix in the Karesuando study. RS-I. The Rotterdam Study. The GWA study was funded by the Netherlands Organisation of Scientific Research NWO Investments (nr. 175.010.2005.011, 911-03-012), the Research Institute for Diseases in the Elderly (014-93-015; RIDE2), the Netherlands Genomics Initiative (NGI)/Netherlands Consortium for Healthy Aging (NCHA) project nr. 050-060-810. We thank Pascal Arp, Mila Jhamai, Dr Michael 40 Moorhouse, Marijn Verkerk, and Sander Bervoets for their help in creating the GWAS database. The Rotterdam Study is funded by Erasmus Medical Center and Erasmus University, Rotterdam, Netherlands Organization for the Health Research and Development (ZonMw), the Research Institute for Diseases in the Elderly (RIDE), the Ministry of Education, Culture and Science, the Ministry for Health, Welfare and Sports, the European Commission (DG XII), and the Municipality of Rotterdam. The authors are very grateful to the participants and staff from the Rotterdam Study, the participating general practitioners and the pharmacists. We would like to thank Dr. Tobias A. Knoch, Luc V. de Zeeuw, Anis Abuseiris, and Rob de Graaf as well as their institutions the Erasmus Computing Grid, Rotterdam, The Netherlands, and especially the national German MediGRID and Services@MediGRID part of the German D-Grid, both funded by the German Bundesministerium fuer Forschung und Technology under grants #01 AK 803 A-H and # 01 IG 07015 G, for access to their grid resources. Abbas Dehghan is supported by NWO grant (vici, 918-76-619). SAPALDIA. Swiss Study on Air Pollution and Lung Diseases in Adults. The SAPALDIA Team: Study directorate: T Rochat (p), NM Probst Hensch (e/g), N Künzli (e/exp), C Schindler (s), JM Gaspoz (c) Scientific team: JC Barthélémy (c), W Berger (g), R Bettschart (p), A Bircher (a), O Brändli (p), C Brombach (n), M Brutsche (p), L Burdet (p), M Frey (p), U Frey (pd), MW Gerbase (p), D Gold (e/c/p), E de Groot (c), W Karrer (p), R Keller (p), B Martin (pa), D Miedinger (o), U Neu (exp), L Nicod (p), M Pons (p), F Roche (c), T Rothe (p), E Russi (p), P Schmid-Grendelmeyer (a), A Schmidt-Trucksäss (pa), A Turk (p), J Schwartz (e), D. Stolz (p), P Straehl (exp), JM Tschopp (p), A von Eckardstein (cc), E Zemp Stutz (e). Scientific team at coordinating centers: M Adam (e/g), C Autenrieth (pa), PO Bridevaux (p), D Carballo (c), E Corradi (exp), I Curjuric (e), J Dratva (e), A Di Pasquale (s), E Dupuis Lozeron (s), E Fischer (e), M Germond (s), L Grize (s), D Keidel (s), S Kriemler (pa), A Kumar (g), M Imboden (g), N Maire (s), A Mehta (e), H Phuleria (exp), E Schaffner (s), GA Thun (g) A Ineichen (exp), M Ragettli (e), M Ritter (exp), T Schikowski (e), M Tarantino (s), M Tsai (exp) (a) allergology, (c) cardiology, (cc) clinical chemistry, (e) epidemiology, (exp) exposure, (g) genetic and molecular biology, (m) meteorology, (n) nutrition, (o) occupational health, (p) pneumology, (pa) physical activity, (pd) pediatrics, (s) statistics. Funding: The Swiss National Science Foundation (grants no 33CSCO-134276/1, 33CSCO-108796, 3247BO-104283, 3247BO-104288, 3247BO- 104284, 3247-065896, 3100-059302, 3200-052720, 3200-042532, 4026-028099), the Federal Office for Forest, Environment and Landscape, the Federal Office of Public Health, the Federal Office of Roads and Transport, the canton's government of Aargau, Basel-Stadt, Basel-Land, Geneva, Luzern, Ticino, Valais, and Zürich, the Swiss Lung League, the canton's Lung League of Basel Stadt/ Basel Landschaft, Geneva, Ticino, Valais and Zurich, SUVA, Freiwillige Akademische Gesellschaft, UBS Wealth Foundation, Talecris Biotherapeutics GmbH, Abbott Diagnostics, European Commission 018996 (GABRIEL), Wellcome Trust WT 084703MA. The study could not have been done without the help of the study participants, technical and administrative support and the medical teams and field workers at the local study sites. Local fieldworkers : Aarau: S Brun, G Giger, M Sperisen, M Stahel, Basel: C Bürli, C Dahler, N Oertli, I Harreh, F Karrer, G Novicic, N Wyttenbacher, Davos: A Saner, P Senn, R Winzeler, Geneva: F Bonfils, B Blicharz, C Landolt, J Rochat, Lugano: S Boccia, E Gehrig, MT Mandia, G Solari, B Viscardi, Montana: AP Bieri, C Darioly, M Maire, Payerne: F Ding, P Danieli A Vonnez, Wald: D Bodmer, E Hochstrasser, R Kunz, C Meier, J Rakic, U Schafroth, A Walder. Administrative staff: C Gabriel, R Gutknecht. SHIP and SHIP-TREND. The Study of Health in Pomerania. SHIP is part of the Community Medicine Research net of the University of Greifswald, Germany, which is funded by the Federal Ministry of Education and Research (grants no. 01ZZ9603, 01ZZ0103, and 01ZZ0403), the Ministry of Cultural Affairs as well as the Social Ministry of the Federal State of Mecklenburg-West Pomerania, and the network 41 'Greifswald Approach to Individualized Medicine (GANI_MED)' funded by the Federal Ministry of Education and Research (grant 03IS2061A). Genome-wide data have been supported by the Federal Ministry of Education and Research (grant no. 03ZIK012) and a joint grant from Siemens Healthcare, Erlangen, Germany and the Federal State of Mecklenburg- West Pomerania. The University of Greifswald is a member of the 'Center of Knowledge Interchange' program of the Siemens AG and the Caché Campus program of the InterSystems GmbH. The SHIP authors are grateful to Mario Stanke for the opportunity to use his Server Cluster for the SNP imputation as well as to Holger Prokisch and Thomas Meitinger (Helmholtz Zentrum München) for the genotyping of the SHIP-TREND cohort. TRAILS. TRacking Adolescents' Individual Lives. Trails is a collaborative project involving various departments of the University Medical Center and University of Groningen, the Erasmus University Medical Center Rotterdam, the University of Utrecht, the Radboud Medical Center Nijmegen, and the Parnassia Bavo group, all in the Netherlands. TRAILS has been financially supported by grants from the Netherlands Organization for Scientific Research NWO (Medical Research Council program grant GB-MW 940-38-011; ZonMW Brainpower grant 100-001-004; ZonMw Risk Behavior and Dependence grants 60- 60600-98-018 and 60-60600-97-118; ZonMw Culture and Health grant 261-98-710; Social Sciences Council medium-sized investment grants GB-MaGW 480-01-006 and GB-MaGW 480-07-001; Social Sciences Council project grants GB-MaGW 457-03-018, GB-MaGW 452-04-314, and GB-MaGW 452-06- 004; NWO large-sized investment grant 175.010.2003.005; NWO Longitudinal Survey and Panel Funding 481-08-013); the Sophia Foundation for Medical Research (projects 301 and 393), the Dutch Ministry of Justice (WODC), the European Science Foundation (EuroSTRESS project FP-006), and the participating universities. We are grateful to all adolescents, their parents and teachers who participated in this research and to everyone who worked on this project and made it possible. Statistical analyses were carried out on the Genetic Cluster Computer (http://www.geneticcluster.org), which is financially supported by the Netherlands Scientific Organization (NWO 480-05-003) along with a supplement from the Dutch Brain Foundation. WGHS. Women's Genome Health Study. The WGHS is supported by the National Heart, Lung, and Blood Institute (HL043851 and HL080467) and the National Cancer Institute (CA047988 and UM1CA182913), with collaborative scientific support and funding for genotyping provided by Amgen. YFS. Young Finns Study. The YFS has been financially supported by the Academy of Finland: grants 134309 (Eye), 126925, 121584, 124282, 129378 (Salve), 117787 (Gendi), and 41071 (Skidi), the Social Insurance Institution of Finland, Kuopio, Tampere and Turku University Hospital Medical Funds (grant 9M048 and 9N035 for TeLeht), Juho Vainio Foundation, Paavo Nurmi Foundation, Finnish Foundation of Cardiovascular Research and Finnish Cultural Foundation, Tampere Tuberculosis Foundation and Emil Aaltonen Foundation (T.L). The technical assistance in the statistical analyses by Ville Aalto and Irina Lisinen is acknowledged. ; Peer Reviewed