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2. Assessment of differentially methylated loci in individuals with end-stage kidney disease attributed to diabetic kidney disease: an exploratory study

Author

Smyth, LJ, Kilner, J, Nair, V, Liu, H, Brennan, E, Kerr, K, Sandholm, N, Cole, J, Dahlström, E, Syreeni, A, Salem, RM, Nelson, RG, Looker, HC, Wooster, C, Anderson, K, McKay, GJ, Kee, F, Young, I, Andrews, D, Forsblom, C, Hirschhorn, JN, Godson, C, Groop, PH, Maxwell, AP, Susztak, K, Kretzler, M, Florez, JC, and McKnight, AJ

Subjects
Biological Sciences, Genetics, Autoimmune Disease, Diabetes, Biotechnology, Kidney Disease, Human Genome, Clinical Research, 2.1 Biological and endogenous factors, Aetiology, Metabolic and endocrine, Renal and urogenital, Good Health and Well Being, Adult, DNA Methylation, Diabetes Mellitus, Type 1, Diabetic Nephropathies, Epigenesis, Genetic, Epigenomics, Female, Humans, Kidney Failure, Chronic, Male, Association, EPIC, End-stage, Kidney, Methylation, Nephropathy, Clinical Sciences, Paediatrics and Reproductive Medicine
Abstract

BackgroundA subset of individuals with type 1 diabetes mellitus (T1DM) are predisposed to developing diabetic kidney disease (DKD), the most common cause globally of end-stage kidney disease (ESKD). Emerging evidence suggests epigenetic changes in DNA methylation may have a causal role in both T1DM and DKD. The aim of this exploratory investigation was to assess differences in blood-derived DNA methylation patterns between individuals with T1DM-ESKD and individuals with long-duration T1DM but no evidence of kidney disease upon repeated testing to identify potential blood-based biomarkers. Blood-derived DNA from individuals (107 cases, 253 controls and 14 experimental controls) were bisulphite treated before DNA methylation patterns from both groups were generated and analysed using Illumina's Infinium MethylationEPIC BeadChip arrays (n = 862,927 sites). Differentially methylated CpG sites (dmCpGs) were identified (false discovery rate adjusted p ≤ × 10-8 and fold change ± 2) by comparing methylation levels between ESKD cases and T1DM controls at single site resolution. Gene annotation and functionality was investigated to enrich and rank methylated regions associated with ESKD in T1DM.ResultsTop-ranked genes within which several dmCpGs were located and supported by functional data with methylation look-ups in other cohorts include: AFF3, ARID5B, CUX1, ELMO1, FKBP5, HDAC4, ITGAL, LY9, PIM1, RUNX3, SEPTIN9 and UPF3A. Top-ranked enrichment pathways included pathways in cancer, TGF-β signalling and Th17 cell differentiation.ConclusionsEpigenetic alterations provide a dynamic link between an individual's genetic background and their environmental exposures. This robust evaluation of DNA methylation in carefully phenotyped individuals has identified biomarkers associated with ESKD, revealing several genes and implicated key pathways associated with ESKD in individuals with T1DM.

Published
2021

3. Endoscopic retrograde cholangiopancreatography is not necessary in all patients with an abnormal intraoperative cholangiogram

Author

Andrawus Beany, Anandpreet S Ghataura, Shaanan T E Yong, Kee F Loo, Rajvinder Singh, Biju George, and Mohamed A Chinnaratha

Subjects
endoscopic retrograde cholangiopancreatography, filling defect, gallstone disease, intraoperative cholangiogram, magnetic resonance cholangiopancreatography, Diseases of the digestive system. Gastroenterology, RC799-869
Published
2023
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4. Impact of Lipoprotein(a) Level on Low-Density Lipoprotein Cholesterol– or Apolipoprotein B–Related Risk of Coronary Heart Disease

Author

Arnold, N, Blaum, C, Goßling, A, Brunner, F, Bay, B, Zeller, T, Ferrario, M, Brambilla, P, Cesana, G, Leoni, V, Palmieri, L, Donfrancesco, C, Ojeda, F, Linneberg, A, Söderberg, S, Iacoviello, L, Gianfagna, F, Costanzo, S, Sans, S, Veronesi, G, Thorand, B, Peters, A, Tunstall-Pedoe, H, Kee, F, Salomaa, V, Schnabel, R, Kuulasmaa, K, Blankenberg, S, Waldeyer, C, Koenig, W, Arnold N., Blaum C., Goßling A., Brunner F. J., Bay B., Zeller T., Ferrario M. M., Brambilla P., Cesana G., Leoni V., Palmieri L., Donfrancesco C., Ojeda F., Linneberg A., Söderberg S., Iacoviello L., Gianfagna F., Costanzo S., Sans S., Veronesi G., Thorand B., Peters A., Tunstall-Pedoe H., Kee F., Salomaa V., Schnabel R. B., Kuulasmaa K., Blankenberg S., Waldeyer C., Koenig W., Arnold, N, Blaum, C, Goßling, A, Brunner, F, Bay, B, Zeller, T, Ferrario, M, Brambilla, P, Cesana, G, Leoni, V, Palmieri, L, Donfrancesco, C, Ojeda, F, Linneberg, A, Söderberg, S, Iacoviello, L, Gianfagna, F, Costanzo, S, Sans, S, Veronesi, G, Thorand, B, Peters, A, Tunstall-Pedoe, H, Kee, F, Salomaa, V, Schnabel, R, Kuulasmaa, K, Blankenberg, S, Waldeyer, C, Koenig, W, Arnold N., Blaum C., Goßling A., Brunner F. J., Bay B., Zeller T., Ferrario M. M., Brambilla P., Cesana G., Leoni V., Palmieri L., Donfrancesco C., Ojeda F., Linneberg A., Söderberg S., Iacoviello L., Gianfagna F., Costanzo S., Sans S., Veronesi G., Thorand B., Peters A., Tunstall-Pedoe H., Kee F., Salomaa V., Schnabel R. B., Kuulasmaa K., Blankenberg S., Waldeyer C., and Koenig W.

Abstract

Background: Conventional low-density lipoprotein cholesterol (LDL-C) quantification includes cholesterol attributable to lipoprotein(a) (Lp(a)-C) due to their overlapping densities. Objectives: The purposes of this study were to compare the association between LDL-C and LDL-C corrected for Lp(a)-C (LDLLp(a)corr) with incident coronary heart disease (CHD) in the general population and to investigate whether concomitant Lp(a) values influence the association of LDL-C or apolipoprotein B (apoB) with coronary events. Methods: Among 68,748 CHD-free subjects at baseline LDLLp(a)corr was calculated as “LDL-C—Lp(a)-C,” where Lp(a)-C was 30% or 17.3% of total Lp(a) mass. Fine and Gray competing risk-adjusted models were applied for the association between the outcome incident CHD and: 1) LDL-C and LDLLp(a)corr in the total sample; and 2) LDL-C and apoB after stratification by Lp(a) mass (≥/<90th percentile). Results: Similar risk estimates for incident CHD were found for LDL-C and LDL-CLp(a)corr30 or LDL-CLp(a)corr17.3 (subdistribution HR with 95% CI) were 2.73 (95% CI: 2.34-3.20) vs 2.51 (95% CI: 2.15-2.93) vs 2.64 (95% CI: 2.26-3.10), respectively (top vs bottom fifth; fully adjusted models). Categorization by Lp(a) mass resulted in higher subdistribution HRs for uncorrected LDL-C and incident CHD at Lp(a) ≥90th percentile (4.38 [95% CI: 2.08-9.22]) vs 2.60 [95% CI: 2.21-3.07]) at Lp(a) <90th percentile (top vs bottom fifth; Pinteraction0.39). In contrast, apoB risk estimates were lower in subjects with higher Lp(a) mass (2.43 [95% CI: 1.34-4.40]) than in Lp(a) <90th percentile (3.34 [95% CI: 2.78-4.01]) (Pinteraction0.49). Conclusions: Correction of LDL-C for its Lp(a)-C content provided no meaningful information on CHD-risk estimation at the population level. Simple categorization of Lp(a) mass (≥/<90th percentile) influenced the association between LDL-C or apoB with future CHD mostly at higher Lp(a) levels.

Published
2024

9. Regional and temporal differences in the associations between cardiovascular disease and its classic risk factors: an analysis of 49 cohorts from 11 European countries

Author

Reinikainen, J, Kuulasmaa, K, Oskarsson, V, Amouyel, P, Biasch, K, Brenner, H, De Ponti, R, Donfrancesco, C, Drygas, W, Ferrieres, J, Grassi, G, Grimsgaard, S, Iacoviello, L, Jousilahti, P, Kårhus, L, Kee, F, Linneberg, A, Luksiene, D, Mariño, J, Moitry, M, Palmieri, L, Peters, A, Piwonska, A, Quarti-Trevano, F, Salomaa, V, Sans, S, Schmidt, C, Schöttker, B, Söderberg, S, Tamosiunas, A, Thorand, B, Tunstall-Pedoe, H, Vanuzzo, D, Veronesi, G, Woodward, M, Lekadir, K, Niiranen, T, Kårhus, LL, Schmidt, CO, Reinikainen, J, Kuulasmaa, K, Oskarsson, V, Amouyel, P, Biasch, K, Brenner, H, De Ponti, R, Donfrancesco, C, Drygas, W, Ferrieres, J, Grassi, G, Grimsgaard, S, Iacoviello, L, Jousilahti, P, Kårhus, L, Kee, F, Linneberg, A, Luksiene, D, Mariño, J, Moitry, M, Palmieri, L, Peters, A, Piwonska, A, Quarti-Trevano, F, Salomaa, V, Sans, S, Schmidt, C, Schöttker, B, Söderberg, S, Tamosiunas, A, Thorand, B, Tunstall-Pedoe, H, Vanuzzo, D, Veronesi, G, Woodward, M, Lekadir, K, Niiranen, T, Kårhus, LL, and Schmidt, CO

Abstract

Aims: The regional and temporal differences in the associations between cardiovascular disease (CVD) and its classic risk factors are unknown. The current study examined these associations in different European regions over a 30-year period. Methods and results: The study sample comprised 553 818 individuals from 49 cohorts in 11 European countries (baseline: 1982-2012) who were followed up for a maximum of 10 years. Risk factors [sex, smoking, diabetes, non-HDL cholesterol, systolic blood pressure (BP), and body mass index (BMI)] and CVD events (coronary heart disease or stroke) were harmonized across cohorts. Risk factor-outcome associations were analysed using multivariable-adjusted Cox regression models, and differences in associations were assessed using meta-regression. The differences in the risk factor-CVD associations between central Europe, northern Europe, southern Europe, and the UK were generally small. Men had a slightly higher hazard ratio (HR) in southern Europe (P = 0.043 for overall difference), and those with diabetes had a slightly lower HR in central Europe (P = 0.022 for overall difference) compared with the other regions. Of the six CVD risk factors, minor HR decreases per decade were observed for non-HDL cholesterol [7% per mmol/L; 95% confidence interval (CI), 3-10%] and systolic BP (4% per 20 mmHg; 95% CI, 1-8%), while a minor HR increase per decade was observed for BMI (7% per 10 kg/m2; 95% CI, 1-13%). Conclusion: The results demonstrate that all classic CVD risk factors are still relevant in Europe, irrespective of regional area. Preventive strategies should focus on risk factors with the greatest population attributable risk.

Published
2024

13. Impact of prediagnostic smoking and smoking cessation on colorectal cancer prognosis: a meta-analysis of individual patient data from cohorts within the CHANCES consortium

Author

Ordóñez-Mena, J.M., Walter, V., Schöttker, B., Jenab, M., O’Doherty, M.G., Kee, F., Bueno-de-Mesquita, B., Peeters, P.H.M., Stricker, B.H., Ruiter, R., Hofman, A., Söderberg, S., Jousilahti, P., Kuulasmaa, K., Freedman, N.D., Wilsgaard, T., Wolk, A., Nilsson, L.M., Tjønneland, A., Quirós, J.R., van Duijnhoven, F J B, Siersema, P.D., Boffetta, P., Trichopoulou, A., and Brenner, H.

Published
2018
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14. Can the association between LDL-Cholesterol and incident coronary heart disease (CHD) be modulated by concomitant Lp(a) levels in the general population?

Author

Arnold, N, primary, Blaum, C, additional, Gossling, A, additional, Zeller, T, additional, Soderberg, S, additional, Iacoviello, L, additional, Sans, S, additional, Veronesi, G, additional, Thorand, B, additional, Kee, F, additional, Salomaa, V, additional, Kuulasmaa, K, additional, Blankenberg, S, additional, Waldeyer, C, additional, and Koenig, W, additional

Published
2023
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20. Simple cardiovascular risk stratification by replacing total serum cholesterol with anthropometric measures: The MORGAM prospective cohort project

Author

Rosberg, V, Vishram-Nielsen, J, Kristensen, A, Pareek, M, Sehested, T, Nilsson, P, Linneberg, A, Palmieri, L, Giampaoli, S, Donfrancesco, C, Kee, F, Mancia, G, Cesana, G, Veronesi, G, Grassi, G, Kuulasmaa, K, Salomaa, V, Palosaari, T, Sans, S, Ferrieres, J, Dallongeville, J, Soderberg, S, Moitry, M, Drygas, W, Tamosiunas, A, Peters, A, Brenner, H, Schottker, B, Grimsgaard, S, Biering-Sorensen, T, Olsen, M, Rosberg V., Vishram-Nielsen J. K., Kristensen A. M. D., Pareek M., Sehested T. S. G., Nilsson P. M., Linneberg A., Palmieri L., Giampaoli S., Donfrancesco C., Kee F., Mancia G., Cesana G., Veronesi G., Grassi G., Kuulasmaa K., Salomaa V., Palosaari T., Sans S., Ferrieres J., Dallongeville J., Soderberg S., Moitry M., Drygas W., Tamosiunas A., Peters A., Brenner H., Schottker B., Grimsgaard S., Biering-Sorensen T., Olsen M. H., Rosberg, V, Vishram-Nielsen, J, Kristensen, A, Pareek, M, Sehested, T, Nilsson, P, Linneberg, A, Palmieri, L, Giampaoli, S, Donfrancesco, C, Kee, F, Mancia, G, Cesana, G, Veronesi, G, Grassi, G, Kuulasmaa, K, Salomaa, V, Palosaari, T, Sans, S, Ferrieres, J, Dallongeville, J, Soderberg, S, Moitry, M, Drygas, W, Tamosiunas, A, Peters, A, Brenner, H, Schottker, B, Grimsgaard, S, Biering-Sorensen, T, Olsen, M, Rosberg V., Vishram-Nielsen J. K., Kristensen A. M. D., Pareek M., Sehested T. S. G., Nilsson P. M., Linneberg A., Palmieri L., Giampaoli S., Donfrancesco C., Kee F., Mancia G., Cesana G., Veronesi G., Grassi G., Kuulasmaa K., Salomaa V., Palosaari T., Sans S., Ferrieres J., Dallongeville J., Soderberg S., Moitry M., Drygas W., Tamosiunas A., Peters A., Brenner H., Schottker B., Grimsgaard S., Biering-Sorensen T., and Olsen M. H.

Abstract

To assess whether anthropometric measures (body mass index [BMI], waist-hip ratio [WHR], and estimated fat mass [EFM]) are independently associated with major adverse cardiovascular events (MACE), and to assess their added prognostic value compared with serum total-cholesterol. The study population comprised 109,509 individuals (53% men) from the MORGAM-Project, aged 19–97 years, without established cardiovascular disease, and not on antihypertensive treatment. While BMI was reported in all, WHR and EFM were reported in ∼52,000 participants. Prognostic importance of anthropometric measurements and total-cholesterol was evaluated using adjusted Cox proportional-hazards regression, logistic regression, area under the receiver-operating-characteristic curve (AUCROC), and net reclassification improvement (NRI). The primary endpoint was MACE, a composite of stroke, myocardial infarction, or death from coronary heart disease. Age interacted significantly with anthropometric measures and total-cholesterol on MACE (P ≤ 0.003), and therefore age-stratified analyses (<50 versus ≥ 50 years) were performed. BMI, WHR, EFM, and total-cholesterol were independently associated with MACE (P ≤ 0.003) and resulted in significantly positive NRI when added to age, sex, smoking status, and systolic blood pressure. Only total-cholesterol increased discrimination ability (AUCROC difference; P < 0.001). In subjects < 50 years, the prediction model with total-cholesterol was superior to the model including BMI, but not superior to models containing WHR or EFM, while in those ≥ 50 years, the model with total-cholesterol was superior to all models containing anthropometric variables, whether assessed individually or combined. We found a potential role for replacing total-cholesterol with anthropometric measures for MACE-prediction among individuals < 50 years when laboratory measurements are unavailable, but not among those ≥ 50 years.

Published
2022

21. Alcohol intake and total mortality in 142 960 individuals from the MORGAM Project: a population-based study

Author

Di Castelnuovo, A, Costanzo, S, Bonaccio, M, Mcelduff, P, Linneberg, A, Salomaa, V, Mannisto, S, Moitry, M, Ferrieres, J, Dallongeville, J, Thorand, B, Brenner, H, Ferrario, M, Veronesi, G, Pettenuzzo, E, Tamosiunas, A, Njolstad, I, Drygas, W, Nikitin, Y, Soderberg, S, Kee, F, Grassi, G, Westermann, D, Schrage, B, Dabboura, S, Zeller, T, Kuulasmaa, K, Blankenberg, S, Donati, M, de Gaetano, G, Iacoviello, L, Di Castelnuovo A., Costanzo S., Bonaccio M., McElduff P., Linneberg A., Salomaa V., Mannisto S., Moitry M., Ferrieres J., Dallongeville J., Thorand B., Brenner H., Ferrario M., Veronesi G., Pettenuzzo E., Tamosiunas A., Njolstad I., Drygas W., Nikitin Y., Soderberg S., Kee F., Grassi G., Westermann D., Schrage B., Dabboura S., Zeller T., Kuulasmaa K., Blankenberg S., Donati M. B., de Gaetano G., Iacoviello L., Di Castelnuovo, A, Costanzo, S, Bonaccio, M, Mcelduff, P, Linneberg, A, Salomaa, V, Mannisto, S, Moitry, M, Ferrieres, J, Dallongeville, J, Thorand, B, Brenner, H, Ferrario, M, Veronesi, G, Pettenuzzo, E, Tamosiunas, A, Njolstad, I, Drygas, W, Nikitin, Y, Soderberg, S, Kee, F, Grassi, G, Westermann, D, Schrage, B, Dabboura, S, Zeller, T, Kuulasmaa, K, Blankenberg, S, Donati, M, de Gaetano, G, Iacoviello, L, Di Castelnuovo A., Costanzo S., Bonaccio M., McElduff P., Linneberg A., Salomaa V., Mannisto S., Moitry M., Ferrieres J., Dallongeville J., Thorand B., Brenner H., Ferrario M., Veronesi G., Pettenuzzo E., Tamosiunas A., Njolstad I., Drygas W., Nikitin Y., Soderberg S., Kee F., Grassi G., Westermann D., Schrage B., Dabboura S., Zeller T., Kuulasmaa K., Blankenberg S., Donati M. B., de Gaetano G., and Iacoviello L.

Abstract

Aim: To test the association of alcohol consumption with total and cause-specific mortality risk. Design: Prospective observational multi-centre population-based study. Setting: Sixteen cohorts (15 from Europe) in the MOnica Risk, Genetics, Archiving and Monograph (MORGAM) Project. Participants: A total of 142 960 individuals (mean age 50 ± 13 years, 53.9% men). Measurements: Average alcohol intake by food frequency questionnaire, total and cause-specific mortality. Findings: In comparison with life-time abstainers, consumption of alcohol less than 10 g/day was associated with an average 11% [95% confidence interval (CI) = 7–14%] reduction in the risk of total mortality, while intake > 20 g/day was associated with a 13% (95% CI = 7–20%) increase in the risk of total mortality. Comparable findings were observed for cardiovascular (CV) deaths. With regard to cancer, drinking up to 10 g/day was not associated with either mortality risk reduction or increase, while alcohol intake > 20 g/day was associated with a 22% (95% CI = 10–35%) increased risk of mortality. The association of alcohol with fatal outcomes was similar in men and women, differed somewhat between countries and was more apparent in individuals preferring wine, suggesting that benefits may not be due to ethanol but other ingredients. Mediation analysis showed that high-density lipoprotein cholesterol explained 2.9 and 18.7% of the association between low alcohol intake and total as well as CV mortality, respectively. Conclusions: In comparison with life-time abstainers, consuming less than one drink per day (nadir at 5 g/day) was associated with a reduced risk of total, cardiovascular and other causes mortality, except cancer. Intake of more than two drinks per day was associated with an increased risk of total, cardiovascular and especially cancer mortality.

Published
2022

23. Computer vision, causal inference and public health modelling approaches to generate evidence on the impacts of urban planning in non-communicable disease and health inequalities in UK and Australian cities: A proposed collaborative approach

Author

Hunter, RF, Garcia, L, Stevenson, M, Nice, K, Wijnands, JS, Kee, F, Ellis, G, Anderson, N, Seneviratne, S, Moeinaddini, M, Godic, B, Akaraci, S, Thompson, J, Hunter, RF, Garcia, L, Stevenson, M, Nice, K, Wijnands, JS, Kee, F, Ellis, G, Anderson, N, Seneviratne, S, Moeinaddini, M, Godic, B, Akaraci, S, and Thompson, J

Abstract

Background Given that the majority of the world’s population live in cities, it is essential to global health efforts that we design them in ways that both reduce non-communicable diseases (NCDs) risk and that facilitate adoption and maintenance of healthy lifestyles. Current approaches tend to focus on the relationship between urban design-related factors that affect health at the local or neighbourhood level but few studies have explored this relationship both within and across entire cities, nor explored the causal pathways between urban-designed related factors and NCDs. The aim of this research program is to use computer vision, causal inference, and public health modelling methods for understanding the causal relationship between urban design and health at the neighbourhood level, and to explore intervention approaches at the city scale. Methods Phase 1 will use machine learning and computer vision techniques to analyse gridded, local-level aerial images (with an optical resolution of <20cm), of all UK and Australian cities with populations over 100,000. It will identify a variety of urban features within these images and derive associations between them and NCD incidence and risk factors identified through location-based health surveys. Phase 2, using data from prospective health cohorts and linked objective built environment data, will apply Bayesian networks to investigate the possible causal pathways between built environment, lifestyle factors, and NCD incidence. Phase 3 will estimate the health impacts of actionable changes in urban design. Using health impact assessment modelling, we will calculate the NCD burden that could be prevented if cities were to adopt urban features of healthier counterparts. A similar approach will be applied on finer-grained scale within all case study cities, enabling assessment of health impacts of changes in individual locations. Phase 4 will develop an interactive web-based toolkit to enable urban designers, p

Published
2023

24. Drinking alcohol in moderation is associated with lower rate of all-cause mortality in individuals with higher rather than lower educational level: findings from the MORGAM project

Author

Di Castelnuovo, A, Bonaccio, M, Costanzo, S, Mcelduff, P, Linneberg, A, Salomaa, V, Männistö, S, Ferrières, J, Dallongeville, J, Thorand, B, Brenner, H, Ferrario, M, Veronesi, G, Tamosiunas, A, Grimsgaard, S, Drygas, W, Malyutina, S, Söderberg, S, Nordendahl, M, Kee, F, Grassi, G, Dabboura, S, Borchini, R, Westermann, D, Schrage, B, Zeller, T, Kuulasmaa, K, Blankenberg, S, Donati, M, Iacoviello, L, de Gaetano, G, Di Castelnuovo, Augusto, Bonaccio, Marialaura, Costanzo, Simona, McElduff, Patrick, Linneberg, Allen, Salomaa, Veikko, Männistö, Satu, Ferrières, Jean, Dallongeville, Jean, Thorand, Barbara, Brenner, Hermann, Ferrario, Marco, Veronesi, Giovanni, Tamosiunas, Abdonas, Grimsgaard, Sameline, Drygas, Wojciech, Malyutina, Sofia, Söderberg, Stefan, Nordendahl, Maria, Kee, Frank, Grassi, Guido, Dabboura, Salim, Borchini, Rossana, Westermann, Dirk, Schrage, Benedikt, Zeller, Tanja, Kuulasmaa, Kari, Blankenberg, Stefan, Donati, Maria Benedetta, Iacoviello, Licia, de Gaetano, Giovanni, Di Castelnuovo, A, Bonaccio, M, Costanzo, S, Mcelduff, P, Linneberg, A, Salomaa, V, Männistö, S, Ferrières, J, Dallongeville, J, Thorand, B, Brenner, H, Ferrario, M, Veronesi, G, Tamosiunas, A, Grimsgaard, S, Drygas, W, Malyutina, S, Söderberg, S, Nordendahl, M, Kee, F, Grassi, G, Dabboura, S, Borchini, R, Westermann, D, Schrage, B, Zeller, T, Kuulasmaa, K, Blankenberg, S, Donati, M, Iacoviello, L, de Gaetano, G, Di Castelnuovo, Augusto, Bonaccio, Marialaura, Costanzo, Simona, McElduff, Patrick, Linneberg, Allen, Salomaa, Veikko, Männistö, Satu, Ferrières, Jean, Dallongeville, Jean, Thorand, Barbara, Brenner, Hermann, Ferrario, Marco, Veronesi, Giovanni, Tamosiunas, Abdonas, Grimsgaard, Sameline, Drygas, Wojciech, Malyutina, Sofia, Söderberg, Stefan, Nordendahl, Maria, Kee, Frank, Grassi, Guido, Dabboura, Salim, Borchini, Rossana, Westermann, Dirk, Schrage, Benedikt, Zeller, Tanja, Kuulasmaa, Kari, Blankenberg, Stefan, Donati, Maria Benedetta, Iacoviello, Licia, and de Gaetano, Giovanni

Abstract

The association between socioeconomic status (SES) and alcohol-related diseases has been widely explored. Less is known, however, on whether the association of moderate drinking with all-cause mortality is modified by educational level (EL). Using harmonized data from 16 cohorts in the MORGAM Project (N = 142,066) the association of pattern of alcohol intake with hazard of all-cause mortality across EL (lower = primary-school; middle = secondary-school; higher = university/college degree) was assessed using multivariable Cox-regression and spline curves. A total of 16,695 deaths occurred in 11.8 years (median). In comparison with life-long abstainers, participants drinking 0.1–10 g/d of ethanol had 13% (HR = 0.87; 95%CI: 0.74–1.02), 11% (HR = 0.89; 0.84–0.95) and 5% (HR = 0.95; 0.89–1.02) lower rate of death in higher, middle and lower EL, respectively. Conversely, drinkers > 20 g/d had 1% (HR = 1.01; 0.82–1.25), 10% (HR = 1.10; 1.02–1.19) and 17% (HR = 1.17; 1.09–1.26) higher rate of death. The association of alcohol consumption with all-cause mortality was nonlinear, with a different J-shape by EL levels. It was consistent across both sexes and in various approaches of measuring alcohol consumption, including combining quantity and frequency and it was more evident when the beverage of preference was wine. We observed that drinking in moderation (≤ 10 g/d) is associated with lower mortality rate more evidently in individuals with higher EL than in people with lower EL, while heavy drinking is associated with higher mortality rate more evidently in individuals with lower EL than in people with higher EL, suggesting that advice on reducing alcohol intake should especially target individuals of low EL.

Published
2023

25. Global Effect of Modifiable Risk Factors on Cardiovascular Disease and Mortality

Author

Magnussen, C, Ojeda, F, Leong, D, Alegre-Diaz, J, Amouyel, P, Aviles-Santa, L, De Bacquer, D, Ballantyne, C, Bernabé-Ortiz, A, Bobak, M, Brenner, H, Carrillo-Larco, R, de Lemos, J, Dobson, A, Dörr, M, Donfrancesco, C, Drygas, W, Dullaart, R, Engström, G, Ferrario, M, Ferrières, J, de Gaetano, G, Goldbourt, U, Gonzalez, C, Grassi, G, Hodge, A, Hveem, K, Iacoviello, L, Ikram, M, Irazola, V, Jobe, M, Jousilahti, P, Kaleebu, P, Kavousi, M, Kee, F, Khalili, D, Koenig, W, Kontsevaya, A, Kuulasmaa, K, Lackner, K, Leistner, D, Lind, L, Linneberg, A, Lorenz, T, Lyngbakken, M, Malekzadeh, R, Malyutina, S, Mathiesen, E, Melander, O, Metspalu, A, Miranda, J, Moitry, M, Mugisha, J, Nalini, M, Nambi, V, Ninomiya, T, Oppermann, K, D'Orsi, E, Pająk, A, Palmieri, L, Panagiotakos, D, Perianayagam, A, Peters, A, Poustchi, H, Prentice, A, Prescott, E, Risérus, U, Salomaa, V, Sans, S, Sakata, S, Schöttker, B, Schutte, A, Sepanlou, S, Sharma, S, Shaw, J, Simons, L, Söderberg, S, Tamosiunas, A, Thorand, B, Tunstall-Pedoe, H, Twerenbold, R, Vanuzzo, D, Veronesi, G, Waibel, J, Wannamethee, S, Watanabe, M, Wild, P, Yao, Y, Zeng, Y, Ziegler, A, Blankenberg, S, Magnussen, Christina, Ojeda, Francisco M, Leong, Darryl P, Alegre-Diaz, Jesus, Amouyel, Philippe, Aviles-Santa, Larissa, De Bacquer, Dirk, Ballantyne, Christie M, Bernabé-Ortiz, Antonio, Bobak, Martin, Brenner, Hermann, Carrillo-Larco, Rodrigo M, de Lemos, James, Dobson, Annette, Dörr, Marcus, Donfrancesco, Chiara, Drygas, Wojciech, Dullaart, Robin P, Engström, Gunnar, Ferrario, Marco M, Ferrières, Jean, de Gaetano, Giovanni, Goldbourt, Uri, Gonzalez, Clicerio, Grassi, Guido, Hodge, Allison M, Hveem, Kristian, Iacoviello, Licia, Ikram, M Kamran, Irazola, Vilma, Jobe, Modou, Jousilahti, Pekka, Kaleebu, Pontiano, Kavousi, Maryam, Kee, Frank, Khalili, Davood, Koenig, Wolfgang, Kontsevaya, Anna, Kuulasmaa, Kari, Lackner, Karl J, Leistner, David M, Lind, Lars, Linneberg, Allan, Lorenz, Thiess, Lyngbakken, Magnus Nakrem, Malekzadeh, Reza, Malyutina, Sofia, Mathiesen, Ellisiv B, Melander, Olle, Metspalu, Andres, Miranda, J Jaime, Moitry, Marie, Mugisha, Joseph, Nalini, Mahdi, Nambi, Vijay, Ninomiya, Toshiharu, Oppermann, Karen, d'Orsi, Eleonora, Pająk, Andrzej, Palmieri, Luigi, Panagiotakos, Demosthenes, Perianayagam, Arokiasamy, Peters, Annette, Poustchi, Hossein, Prentice, Andrew M, Prescott, Eva, Risérus, Ulf, Salomaa, Veikko, Sans, Susana, Sakata, Satoko, Schöttker, Ben, Schutte, Aletta E, Sepanlou, Sadaf G, Sharma, Sanjib Kumar, Shaw, Jonathan E, Simons, Leon A, Söderberg, Stefan, Tamosiunas, Abdonas, Thorand, Barbara, Tunstall-Pedoe, Hugh, Twerenbold, Raphael, Vanuzzo, Diego, Veronesi, Giovanni, Waibel, Julia, Wannamethee, S Goya, Watanabe, Masafumi, Wild, Philipp S, Yao, Yao, Zeng, Yi, Ziegler, Andreas, Blankenberg, Stefan, Magnussen, C, Ojeda, F, Leong, D, Alegre-Diaz, J, Amouyel, P, Aviles-Santa, L, De Bacquer, D, Ballantyne, C, Bernabé-Ortiz, A, Bobak, M, Brenner, H, Carrillo-Larco, R, de Lemos, J, Dobson, A, Dörr, M, Donfrancesco, C, Drygas, W, Dullaart, R, Engström, G, Ferrario, M, Ferrières, J, de Gaetano, G, Goldbourt, U, Gonzalez, C, Grassi, G, Hodge, A, Hveem, K, Iacoviello, L, Ikram, M, Irazola, V, Jobe, M, Jousilahti, P, Kaleebu, P, Kavousi, M, Kee, F, Khalili, D, Koenig, W, Kontsevaya, A, Kuulasmaa, K, Lackner, K, Leistner, D, Lind, L, Linneberg, A, Lorenz, T, Lyngbakken, M, Malekzadeh, R, Malyutina, S, Mathiesen, E, Melander, O, Metspalu, A, Miranda, J, Moitry, M, Mugisha, J, Nalini, M, Nambi, V, Ninomiya, T, Oppermann, K, D'Orsi, E, Pająk, A, Palmieri, L, Panagiotakos, D, Perianayagam, A, Peters, A, Poustchi, H, Prentice, A, Prescott, E, Risérus, U, Salomaa, V, Sans, S, Sakata, S, Schöttker, B, Schutte, A, Sepanlou, S, Sharma, S, Shaw, J, Simons, L, Söderberg, S, Tamosiunas, A, Thorand, B, Tunstall-Pedoe, H, Twerenbold, R, Vanuzzo, D, Veronesi, G, Waibel, J, Wannamethee, S, Watanabe, M, Wild, P, Yao, Y, Zeng, Y, Ziegler, A, Blankenberg, S, Magnussen, Christina, Ojeda, Francisco M, Leong, Darryl P, Alegre-Diaz, Jesus, Amouyel, Philippe, Aviles-Santa, Larissa, De Bacquer, Dirk, Ballantyne, Christie M, Bernabé-Ortiz, Antonio, Bobak, Martin, Brenner, Hermann, Carrillo-Larco, Rodrigo M, de Lemos, James, Dobson, Annette, Dörr, Marcus, Donfrancesco, Chiara, Drygas, Wojciech, Dullaart, Robin P, Engström, Gunnar, Ferrario, Marco M, Ferrières, Jean, de Gaetano, Giovanni, Goldbourt, Uri, Gonzalez, Clicerio, Grassi, Guido, Hodge, Allison M, Hveem, Kristian, Iacoviello, Licia, Ikram, M Kamran, Irazola, Vilma, Jobe, Modou, Jousilahti, Pekka, Kaleebu, Pontiano, Kavousi, Maryam, Kee, Frank, Khalili, Davood, Koenig, Wolfgang, Kontsevaya, Anna, Kuulasmaa, Kari, Lackner, Karl J, Leistner, David M, Lind, Lars, Linneberg, Allan, Lorenz, Thiess, Lyngbakken, Magnus Nakrem, Malekzadeh, Reza, Malyutina, Sofia, Mathiesen, Ellisiv B, Melander, Olle, Metspalu, Andres, Miranda, J Jaime, Moitry, Marie, Mugisha, Joseph, Nalini, Mahdi, Nambi, Vijay, Ninomiya, Toshiharu, Oppermann, Karen, d'Orsi, Eleonora, Pająk, Andrzej, Palmieri, Luigi, Panagiotakos, Demosthenes, Perianayagam, Arokiasamy, Peters, Annette, Poustchi, Hossein, Prentice, Andrew M, Prescott, Eva, Risérus, Ulf, Salomaa, Veikko, Sans, Susana, Sakata, Satoko, Schöttker, Ben, Schutte, Aletta E, Sepanlou, Sadaf G, Sharma, Sanjib Kumar, Shaw, Jonathan E, Simons, Leon A, Söderberg, Stefan, Tamosiunas, Abdonas, Thorand, Barbara, Tunstall-Pedoe, Hugh, Twerenbold, Raphael, Vanuzzo, Diego, Veronesi, Giovanni, Waibel, Julia, Wannamethee, S Goya, Watanabe, Masafumi, Wild, Philipp S, Yao, Yao, Zeng, Yi, Ziegler, Andreas, and Blankenberg, Stefan

Abstract

BACKGROUND: Five modifiable risk factors are associated with cardiovascular disease and death from any cause. Studies using individual-level data to evaluate the regional and sex-specific prevalence of the risk factors and their effect on these outcomes are lacking. METHODS: We pooled and harmonized individual-level data from 112 cohort studies conducted in 34 countries and 8 geographic regions participating in the Global Cardiovascular Risk Consortium. We examined associations between the risk factors (body-mass index, systolic blood pressure, non-high-density lipoprotein cholesterol, current smoking, and diabetes) and incident cardiovascular disease and death from any cause using Cox regression analyses, stratified according to geographic region, age, and sex. Population-attributable fractions were estimated for the 10-year incidence of cardiovascular disease and 10-year all-cause mortality. RESULTS: Among 1,518,028 participants (54.1% of whom were women) with a median age of 54.4 years, regional variations in the prevalence of the five modifiable risk factors were noted. Incident cardiovascular disease occurred in 80,596 participants during a median follow-up of 7.3 years (maximum, 47.3), and 177,369 participants died during a median follow-up of 8.7 years (maximum, 47.6). For all five risk factors combined, the aggregate global population-attributable fraction of the 10-year incidence of cardiovascular disease was 57.2% (95% confidence interval [CI], 52.4 to 62.1) among women and 52.6% (95% CI, 49.0 to 56.1) among men, and the corresponding values for 10-year all-cause mortality were 22.2% (95% CI, 16.8 to 27.5) and 19.1% (95% CI, 14.6 to 23.6). CONCLUSIONS: Harmonized individual-level data from a global cohort showed that 57.2% and 52.6% of cases of incident cardiovascular disease among women and men, respectively, and 22.2% and 19.1% of deaths from any cause among women and men, respectively, may be attributable to five modifiable risk factors. (Funded by the

Published
2023

27. Alcoholic beverage preference and diabetes incidence across Europe: the Consortium on Health and Ageing Network of Cohorts in Europe and the United States (CHANCES) project

Author

Sluik, D, Jankovic, N, Hughes, M, O'Doherty, M G, Schöttker, B, Drygas, W, Rolandsson, O, Männistö, S, Ordóñez-Mena, J M, Ferrieres, J, Bamia, C, de Gaetano, G, Kiefte-De Jong, J C, Franco, O H, Sluijs, I, Spijkerman, A M W, Sans, S, Eriksson, S, Kromhout, D, Trichopoulou, A, Wilsgaard, T, Brenner, H, Kuulasmaa, K, Laatikainen, T, Söderberg, S, Iacoviello, L, Boffetta, P, Kee, F, and Feskens, E J M

Published
2017
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28. Adolescents' Views about a Proposed Rewards Intervention to Promote Healthy Food Choice in Secondary School Canteens

Author

McEvoy, C. T., Lawton, J., Kee, F., Young, I. S., Woodside, J. V., McBratney, J., and McKinley, M. C.

Abstract

Using rewards may be an effective method to positively influence adolescent eating behaviour, but evidence regarding this approach is limited. The aim of this study was to explore young adolescent views about a proposed reward intervention associated with food choice in school canteens. Focus groups were held in 10 schools located in lower socioeconomic areas within Northern Ireland and involved 90 pupils aged 11-12 years (54 girls, 36 boys). Our findings indicated a high degree of acceptability for a reward scheme but there was major diversity in the type of rewards valued by pupils, largely defined by geographical area and socio-cultural differences. Pupils from rural areas tended to emphasize group-based and longer-term rewards, whereas pupils from urban-city schools tended to suggest individualistic and immediate rewards. The major factors influencing food choice were food price, value for money, taste and visual appearance. Pupils felt that factors outside of their control, such as being assigned to the second lunch sitting placed considerable constraints on their food choice. This research not only indicated a high degree of acceptability for a rewards-based intervention but also highlighted a number of socio-cultural and environmental factors that should be considered by researchers when developing such an intervention.

Published
2014
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30. Fruit and vegetable intake and risk of incident of type 2 diabetes: results from the consortium on health and ageing network of cohorts in Europe and the United States (CHANCES)

Author

Mamluk, L, O'Doherty, M G, Orfanos, P, Saitakis, G, Woodside, J V, Liao, L M, Sinha, R, Boffetta, P., Trichopoulou, A., and Kee, F.

Subjects
Usage, Risk factors, Health aspects, Type 2 diabetes -- Risk factors, Fruits (Food) -- Usage -- Health aspects, Vegetables -- Usage -- Health aspects, Fruit -- Usage -- Health aspects
Abstract

Author(s): L Mamluk [sup.1] , M G O'Doherty [sup.1] , P Orfanos [sup.2] , G Saitakis [sup.2] , J V Woodside [sup.1] , L M Liao [sup.3] , R Sinha [...], Background/objectives: There is limited information to support definitive recommendations concerning the role of diet in the development of type 2 Diabetes mellitus (T2DM). The results of the latest meta-analyses suggest that an increased consumption of green leafy vegetables may reduce the incidence of diabetes, with either no association or weak associations demonstrated for total fruit and vegetable intake. Few studies have, however, focused on older subjects. Subjects/methods: The relationship between T2DM and fruit and vegetable intake was investigated using data from the NIH-AARP study and the EPIC Elderly study. All participants below the age of 50 and/or with a history of cancer, diabetes or coronary heart disease were excluded from the analysis. Multivariate logistic regression analysis was used to calculate the odds ratio of T2DM comparing the highest with the lowest estimated portions of fruit, vegetable, green leafy vegetables and cabbage intake. Results: Comparing people with the highest and lowest estimated portions of fruit, vegetable or green leafy vegetable intake indicated no association with the risk of T2DM. However, although the pooled OR across all studies showed no effect overall, there was significant heterogeneity across cohorts and independent results from the NIH-AARP study showed that fruit and green leafy vegetable intake was associated with a reduced risk of T2DM OR 0.95 (95% CI 0.91,0.99) and OR 0.87 (95% CI 0.87,0.90) respectively. Conclusions: Fruit and vegetable intake was not shown to be related to incident T2DM in older subjects. Summary analysis also found no associations between green leafy vegetable and cabbage intake and the onset of T2DM. Future dietary pattern studies may shed light on the origin of the heterogeneity across populations.

Published
2017
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35. C-reactive protein as a possible modifier of Lipoprotein(a)-related risk for coronary heart disease in Europe: results from the BiomarCARE project

Author

Arnold, N, primary, Blaum, C, additional, Gossling, A, additional, Zeller, T, additional, Linneberg, A, additional, Soderberg, S, additional, Iacoviello, L, additional, Sans, S, additional, Leoni, V, additional, Kee, F, additional, Salomaa, V, additional, Kuulasmaa, K, additional, Blankenberg, S, additional, Koenig, W, additional, and Waldeyer, C, additional

Published
2022
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36. Biomarker-based prediction of fatal and non-fatal cardiovascular outcomes in individuals of the general population with and without diabetes mellitus

Author

Haller, P M, primary, Gossling, A, additional, Brenner, H, additional, Iacoviello, L, additional, Kee, F, additional, Linneberg, A, additional, Thorand, B, additional, Salomaa, V, additional, Soederberg, S, additional, Voelzke, H, additional, Sans, S, additional, Palmieri, L, additional, Veronesi, G, additional, Blankenberg, S, additional, and Westermann, D, additional

Published
2022
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38. Coronavirus disease 2019 is associated with catheter-related thrombosis in critically ill patients: A multicenter case-control study

Author

Alexander P.J. Vlaar, Pieter R. Tuinman, Jasper M. Smit, David J. van Westerloo, Frederikus A. Klok, Kee F. Choi, Jorge E. Lopez Matta, Roel Vink, Menno V. Huisman, Carlos V. Elzo Kraemer, Armand R. J. Girbes, Marcella C.A. Müller, Frank E.H.P. van Baarle, Intensive care medicine, ACS - Diabetes & metabolism, AII - Infectious diseases, ACS - Pulmonary hypertension & thrombosis, Intensive Care Medicine, Graduate School, AII - Inflammatory diseases, APH - Quality of Care, and ACS - Microcirculation

Subjects
Male, Catheterization, Central Venous, medicine.medical_specialty, 2019-20 coronavirus outbreak, Coronavirus disease 2019 (COVID-19), Critical Illness, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Catheter-related thrombosis, Letter to the Editors-in-Chief, Venous thrombosis, medicine, Humans, Intensive care medicine, Aged, Critically ill, business.industry, Case-control study, COVID-19, Thrombosis, Hematology, Catheter related thrombosis, Middle Aged, medicine.disease, Central venous catheters, Critical care, Case-Control Studies, Female, business
Published
2021
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39. Prevalent diabetes and risk of total, colorectal, prostate and breast cancers in an ageing population: meta-analysis of individual participant data from cohorts of the CHANCES consortium

Author

Amadou, A., Freisling, H., Jenab, M., Tsilidis, K.K., Trichopoulou, A., Boffetta, P., Van Guelpen, B., Mokoroa, O., Wilsgaard, T., Kee, F., Schöttker, B., Ordóñez-Mena, J.M., Männistö, S., Söderberg, S., Vermeulen, R.C.H., Quirós, J.R., Liao, L.M., Sinha, R., Kuulasmaa, K., Brenner, H., Romieu, I., IRAS OH Epidemiology Chemical Agents, dIRAS RA-2, Sub Algemeen Theoretical Physics, IRAS OH Epidemiology Chemical Agents, dIRAS RA-2, Sub Algemeen Theoretical Physics, Amadou A., Freisling H., Jenab M., Tsilidis K.K., Trichopoulou A., Boffetta P., Van Guelpen B., Mokoroa O., Wilsgaard T., Kee F., Schottker B., Ordonez-Mena J.M., Mannisto S., Soderberg S., Vermeulen R.C.H., Quiros J.R., Liao L.M., Sinha R., Kuulasmaa K., Brenner H., and Romieu I.

Subjects
Male, Aging, Cancer Research, medicine.medical_specialty, Colorectal cancer, Breast Neoplasms, Colorectal Neoplasm, Overweight, Article, Cohort Studies, 03 medical and health sciences, 0302 clinical medicine, Breast cancer, Risk Factors, Neoplasms, Internal medicine, Diabetes Mellitus, Prevalence, medicine, Humans, Prospective cohort study, Aged, Aged, 80 and over, business.industry, Risk Factor, Hazard ratio, Prostatic Neoplasms, Cancer, Diabetes Mellitu, Middle Aged, medicine.disease, Obesity, United States, Confidence interval, Europe, Oncology, 030220 oncology & carcinogenesis, Prostatic Neoplasm, Neoplasm, Female, Cohort Studie, medicine.symptom, Colorectal Neoplasms, business, Breast Neoplasm, Human
Abstract

BACKGROUND: We investigated whether associations between prevalent diabetes and cancer risk are pertinent to older adults and whether associations differ across subgroups of age, body weight status or levels of physical activity. METHODS: We harmonised data from seven prospective cohort studies of older individuals in Europe and the United States participating in the CHANCES consortium. Cox proportional hazard regression was used to estimate the associations of prevalent diabetes with cancer risk (all cancers combined, and for colorectum, prostate and breast). We calculated summary risk estimates across cohorts using pooled analysis and random-effects meta-analysis. RESULTS: A total of 667,916 individuals were included with an overall median (P25–P75) age at recruitment of 62.3 (57–67) years. During a median follow-up time of 10.5 years, 114,404 total cancer cases were ascertained. Diabetes was not associated with the risk of all cancers combined (hazard ratio (HR) = 0.94; 95% confidence interval (CI): 0.86–1.04; I(2) = 63.3%). Diabetes was positively associated with colorectal cancer risk in men (HR = 1.17; 95% CI: 1.08–1.26; I(2) = 0%) and a similar HR in women (1.13; 95% CI: 0.82–1.56; I(2) = 46%), but with a confidence interval including the null. Diabetes was inversely associated with prostate cancer risk (HR = 0.81; 95% CI: 0.77–0.85; I(2) = 0%), but not with postmenopausal breast cancer (HR = 0.96; 95% CI: 0.89–1.03; I(2) = 0%). In exploratory subgroup analyses, diabetes was inversely associated with prostate cancer risk only in men with overweight or obesity. CONCLUSIONS: Prevalent diabetes was positively associated with colorectal cancer risk and inversely associated with prostate cancer risk in older Europeans and Americans.

Published
2021

44. Refining a primary care shared decision-making aid for lifestyle change: a mixed-methods study.

Author

Heron, N, O'Connor, SR, Kee, F, Thompson, DR, Cupples, M, Donnelly, M, Heron, N, O'Connor, SR, Kee, F, Thompson, DR, Cupples, M, and Donnelly, M

Abstract

BACKGROUND: The important role of primary care in promoting healthy lifestyle behaviours needs informed support. AIM: To elicit views on a 39-item shared decision-making (SDM) aid (SHARE-D) for lifestyle change and refine it to improve implementation. DESIGN & SETTING: Mixed-methods study. METHOD: Health professionals, patients, and support workers, with experience of managing or a history of cardio- or cerebrovascular disease, were purposively recruited based on age, sex, and urban/rural location (n = 34). Participants completed a survey, rating the importance of including each item in a decision-aid, designed for use by patients with health professionals, and suggesting modifications. Semi-structured interviews (n = 30/34) were conducted and analysed thematically. RESULTS: Substantial agreement was observed on rating item inclusion. Based on survey and interview data, 9/39 items were removed; 13 were amended. Qualitative themes were: 1) core content of the decision-aid; 2) barriers to use; 3) motivation for lifestyle change; and 4) primary care implementation. 'Self-reflective' questions and goal setting were viewed as essential components. The paper-based format, length, clarity, and time required were barriers to its use. Optional support considered within the aid was seen as important to motivate change. A digital version, integrated into patient record systems was regarded as critical to implementation. A revised 30-item aid was considered suitable for facilitating brief conversations and promoting patient autonomy. CONCLUSION: The SHARE-D decision aid for healthy lifestyle change appears to have good content validity and acceptability. Survey and interview data provided in-depth information to support implementation of a refined version. Further studies should examine its effectiveness.

Published
2022

45. A saturated map of common genetic variants associated with human height

Author

Yengo, L, Vedantam, S, Marouli, E, Sidorenko, J, Bartell, E, Sakaue, S, Graff, M, Eliasen, AU, Jiang, Y, Raghavan, S, Miao, J, Arias, JD, Graham, SE, Mukamel, RE, Spracklen, CN, Yin, X, Chen, S-H, Ferreira, T, Highland, HH, Ji, Y, Karaderi, T, Lin, K, Lull, K, Malden, DE, Medina-Gomez, C, Machado, M, Moore, A, Rueger, S, Sim, X, Vrieze, S, Ahluwalia, TS, Akiyama, M, Allison, MA, Alvarez, M, Andersen, MK, Ani, A, Appadurai, V, Arbeeva, L, Bhaskar, S, Bielak, LF, Bollepalli, S, Bonnycastle, LL, Bork-Jensen, J, Bradfield, JP, Bradford, Y, Braund, PS, Brody, JA, Burgdorf, KS, Cade, BE, Cai, H, Cai, Q, Campbell, A, Canadas-Garre, M, Catamo, E, Chai, J-F, Chai, X, Chang, L-C, Chang, Y-C, Chen, C-H, Chesi, A, Choi, SH, Chung, R-H, Cocca, M, Concas, MP, Couture, C, Cuellar-Partida, G, Danning, R, Daw, EW, Degenhard, F, Delgado, GE, Delitala, A, Demirkan, A, Deng, X, Devineni, P, Dietl, A, Dimitriou, M, Dimitrov, L, Dorajoo, R, Ekici, AB, Engmann, JE, Fairhurst-Hunter, Z, Farmaki, A-E, Faul, JD, Fernandez-Lopez, J-C, Forer, L, Francescatto, M, Freitag-Wolf, S, Fuchsberger, C, Galesloot, TE, Gao, Y, Gao, Z, Geller, F, Giannakopoulou, O, Giulianini, F, Gjesing, AP, Goel, A, Gordon, SD, Gorski, M, Grove, J, Guo, X, Gustafsson, S, Haessler, J, Hansen, TF, Havulinna, AS, Haworth, SJ, He, J, Heard-Costa, N, Hebbar, P, Hindy, G, Ho, Y-LA, Hofer, E, Holliday, E, Horn, K, Hornsby, WE, Hottenga, J-J, Huang, H, Huang, J, Huerta-Chagoya, A, Huffman, JE, Hung, Y-J, Huo, S, Hwang, MY, Iha, H, Ikeda, DD, Isono, M, Jackson, AU, Jager, S, Jansen, IE, Johansson, I, Jonas, JB, Jonsson, A, Jorgensen, T, Kalafati, I-P, Kanai, M, Kanoni, S, Karhus, LL, Kasturiratne, A, Katsuya, T, Kawaguchi, T, Kember, RL, Kentistou, KA, Kim, H-N, Kim, YJ, Kleber, ME, Knol, MJ, Kurbasic, A, Lauzon, M, Le, P, Lea, R, Lee, J-Y, Leonard, HL, Li, SA, Li, X, Liang, J, Lin, H, Lin, S-Y, Liu, J, Liu, X, Lo, KS, Long, J, Lores-Motta, L, Luan, J, Lyssenko, V, Lyytikainen, L-P, Mahajan, A, Mamakou, V, Mangino, M, Manichaikul, A, Marten, J, Mattheisen, M, Mavarani, L, McDaid, AF, Meidtner, K, Melendez, TL, Mercader, JM, Milaneschi, Y, Miller, JE, Millwood, IY, Mishra, PP, Mitchell, RE, Mollehave, LT, Morgan, A, Mucha, S, Munz, M, Nakatochi, M, Nelson, CP, Nethander, M, Nho, CW, Nielsen, AA, Nolte, IM, Nongmaithem, SS, Noordam, R, Ntalla, I, Nutile, T, Pandit, A, Christofidou, P, Parna, K, Pauper, M, Petersen, ERB, Petersen, L, Pitkanen, N, Polasek, O, Poveda, A, Preuss, MH, Pyarajan, S, Raffield, LM, Rakugi, H, Ramirez, J, Rasheed, A, Raven, D, Rayner, NW, Riveros, C, Rohde, R, Ruggiero, D, Ruotsalainen, SE, Ryan, KA, Sabater-Lleal, M, Saxena, R, Scholz, M, Sendamarai, A, Shen, B, Shi, J, Shin, JH, Sidore, C, Sitlani, CM, Slieker, RKC, Smit, RAJ, Smith, A, Smith, JA, Smyth, LJ, Southam, LE, Steinthorsdottir, V, Sun, L, Takeuchi, F, Tallapragada, D, Taylor, KD, Tayo, BO, Tcheandjieu, C, Terzikhan, N, Tesolin, P, Teumer, A, Theusch, E, Thompson, DJ, Thorleifsson, G, Timmers, PRHJ, Trompet, S, Turman, C, Vaccargiu, S, van der Laan, SW, van der Most, PJ, van Klinken, JB, van Setten, J, Verma, SS, Verweij, N, Veturi, Y, Wang, CA, Wang, C, Wang, L, Wang, Z, Warren, HR, Wei, WB, Wickremasinghe, AR, Wielscher, M, Wiggins, KL, Winsvold, BS, Wong, A, Wu, Y, Wuttke, M, Xia, R, Xie, T, Yamamoto, K, Yang, J, Yao, J, Young, H, Yousri, NA, Yu, L, Zeng, L, Zhang, W, Zhang, X, Zhao, J-H, Zhao, W, Zhou, W, Zimmermann, ME, Zoledziewska, M, Adair, LS, Adams, HHH, Aguilar-Salinas, CA, Al-Mulla, F, Arnett, DK, Asselbergs, FW, Asvold, BO, Attia, J, Banas, B, Bandinelli, S, Bennett, DA, Bergler, T, Bharadwaj, D, Biino, G, Bisgaard, H, Boerwinkle, E, Boger, CA, Bonnelykke, K, Boomsma, D, Borglum, AD, Borja, JB, Bouchard, C, Bowden, DW, Brandslund, I, Brumpton, B, Buring, JE, Caulfield, MJ, Chambers, JC, Chandak, GR, Chanock, SJ, Chaturvedi, N, Chen, Y-DI, Chen, Z, Cheng, C-Y, Christophersen, IE, Ciullo, M, Cole, JW, Collins, FS, Cooper, RS, Cruz, M, Cucca, F, Cupples, LA, Cutler, MJ, Damrauer, SM, Dantoft, TM, de Borst, GJ, de Groot, LCPGM, De Jager, PL, de Kleijn, DP, de Silva, HJ, Dedoussis, G, den Hollander, A, Du, S, Easton, DF, Elders, PJM, Eliassen, AH, Ellinor, PT, Elmstahl, S, Erdmann, J, Evans, MK, Fatkin, D, Feenstra, B, Feitosa, MF, Ferrucci, L, Ford, I, Fornage, M, Franke, A, Franks, PW, Freedman, B, Gasparini, P, Gieger, C, Girotto, G, Goddard, ME, Golightly, YM, Gonzalez-Villalpando, C, Gordon-Larsen, P, Grallert, H, Grant, SFA, Grarup, N, Griffiths, L, Gudnason, V, Haiman, C, Hakonarson, H, Hansen, T, Hartman, CA, Hattersley, AT, Hayward, C, Heckbert, SR, Heng, C-K, Hengstenberg, C, Hewitt, AW, Hishigaki, H, Hoyng, CB, Huang, PL, Huang, W, Hunt, SC, Hveem, K, Hypponen, E, Iacono, WG, Ichihara, S, Ikram, MA, Isasi, CR, Jackson, RD, Jarvelin, M-R, Jin, Z-B, Jockel, K-H, Joshi, PK, Jousilahti, P, Jukema, JW, Kahonen, M, Kamatani, Y, Kang, KD, Kaprio, J, Kardia, SLR, Karpe, F, Kato, N, Kee, F, Kessler, T, Khera, A, Khor, CC, Kiemeney, LALM, Kim, B-J, Kim, EK, Kim, H-L, Kirchhof, P, Kivimaki, M, Koh, W-P, Koistinen, HA, Kolovou, GD, Kooner, JS, Kooperberg, C, Kottgen, A, Kovacs, P, Kraaijeveld, A, Kraft, P, Krauss, RM, Kumari, M, Kutalik, Z, Laakso, M, Lange, LA, Langenberg, C, Launer, LJ, Le Marchand, L, Lee, H, Lee, NR, Lehtimaki, T, Li, H, Li, L, Lieb, W, Lin, X, Lind, L, Linneberg, A, Liu, C-T, Loeffler, M, London, B, Lubitz, SA, Lye, SJ, Mackey, DA, Magi, R, Magnusson, PKE, Marcus, GM, Vidal, PM, Martin, NG, Marz, W, Matsuda, F, McGarrah, RW, McGue, M, McKnight, AJ, Medland, SE, Mellstrom, D, Metspalu, A, Mitchell, BD, Mitchell, P, Mook-Kanamori, DO, Morris, AD, Mucci, LA, Munroe, PB, Nalls, MA, Nazarian, S, Nelson, AE, Neville, MJ, Newton-Cheh, C, Nielsen, CS, Nothen, MM, Ohlsson, C, Oldehinkel, AJ, Orozco, L, Pahkala, K, Pajukanta, P, Palmer, CNA, Parra, EJ, Pattaro, C, Pedersen, O, Pennell, CE, Penninx, BWJH, Perusse, L, Peters, A, Peyser, PA, Porteous, DJ, Posthuma, D, Power, C, Pramstaller, PP, Province, MA, Qi, Q, Qu, J, Rader, DJ, Raitakari, OT, Ralhan, S, Rallidis, LS, Rao, DC, Redline, S, Reilly, DF, Reiner, AP, Rhee, SY, Ridker, PM, Rienstra, M, Ripatti, S, Ritchie, MD, Roden, DM, Rosendaal, FR, Rotter, J, Rudan, I, Rutters, F, Sabanayagam, C, Saleheen, D, Salomaa, V, Samani, NJ, Sanghera, DK, Sattar, N, Schmidt, B, Schmidt, H, Schmidt, R, Schulze, MB, Schunkert, H, Scott, LJ, Scott, RJ, Sever, P, Shiroma, EJ, Shoemaker, MB, Shu, X-O, Simonsick, EM, Sims, M, Singh, JR, Singleton, AB, Sinner, MF, Smith, JG, Snieder, H, Spector, TD, Stampfer, MJ, Stark, KJ, Strachan, DP, t' Hart, LM, Tabara, Y, Tang, H, Tardif, J-C, Thanaraj, TA, Timpson, NJ, Tonjes, A, Tremblay, A, Tuomi, T, Tuomilehto, J, Tusie-Luna, M-T, Uitterlinden, AG, van Dam, RM, van der Harst, P, Van der Velde, N, van Duijn, CM, van Schoor, NM, Vitart, V, Volker, U, Vollenweider, P, Volzke, H, Wacher-Rodarte, NH, Walker, M, Wang, YX, Wareham, NJ, Watanabe, RM, Watkins, H, Weir, DR, Werge, TM, Widen, E, Wilkens, LR, Willemsen, G, Willett, WC, Wilson, JF, Wong, T-Y, Woo, J-T, Wright, AF, Wu, J-Y, Xu, H, Yajnik, CS, Yokota, M, Yuan, J-M, Zeggini, E, Zemel, BS, Zheng, W, Zhu, X, Zmuda, JM, Zonderman, AB, Zwart, J-A, Chasman, D, Cho, YS, Heid, IM, McCarthy, M, Ng, MCY, O'Donnell, CJ, Rivadeneira, F, Thorsteinsdottir, U, Sun, Y, Tai, ES, Boehnke, M, Deloukas, P, Justice, AE, Lindgren, CM, Loos, RJF, Mohlke, KL, North, KE, Stefansson, K, Walters, RG, Winkler, TW, Young, KL, Loh, P-R, Esko, T, Assimes, TL, Auton, A, Abecasis, GR, Willer, CJ, Locke, AE, Berndt, S, Lettre, G, Frayling, TM, Okada, Y, Wood, AR, Visscher, PM, Hirschhorn, JN, Yengo, L, Vedantam, S, Marouli, E, Sidorenko, J, Bartell, E, Sakaue, S, Graff, M, Eliasen, AU, Jiang, Y, Raghavan, S, Miao, J, Arias, JD, Graham, SE, Mukamel, RE, Spracklen, CN, Yin, X, Chen, S-H, Ferreira, T, Highland, HH, Ji, Y, Karaderi, T, Lin, K, Lull, K, Malden, DE, Medina-Gomez, C, Machado, M, Moore, A, Rueger, S, Sim, X, Vrieze, S, Ahluwalia, TS, Akiyama, M, Allison, MA, Alvarez, M, Andersen, MK, Ani, A, Appadurai, V, Arbeeva, L, Bhaskar, S, Bielak, LF, Bollepalli, S, Bonnycastle, LL, Bork-Jensen, J, Bradfield, JP, Bradford, Y, Braund, PS, Brody, JA, Burgdorf, KS, Cade, BE, Cai, H, Cai, Q, Campbell, A, Canadas-Garre, M, Catamo, E, Chai, J-F, Chai, X, Chang, L-C, Chang, Y-C, Chen, C-H, Chesi, A, Choi, SH, Chung, R-H, Cocca, M, Concas, MP, Couture, C, Cuellar-Partida, G, Danning, R, Daw, EW, Degenhard, F, Delgado, GE, Delitala, A, Demirkan, A, Deng, X, Devineni, P, Dietl, A, Dimitriou, M, Dimitrov, L, Dorajoo, R, Ekici, AB, Engmann, JE, Fairhurst-Hunter, Z, Farmaki, A-E, Faul, JD, Fernandez-Lopez, J-C, Forer, L, Francescatto, M, Freitag-Wolf, S, Fuchsberger, C, Galesloot, TE, Gao, Y, Gao, Z, Geller, F, Giannakopoulou, O, Giulianini, F, Gjesing, AP, Goel, A, Gordon, SD, Gorski, M, Grove, J, Guo, X, Gustafsson, S, Haessler, J, Hansen, TF, Havulinna, AS, Haworth, SJ, He, J, Heard-Costa, N, Hebbar, P, Hindy, G, Ho, Y-LA, Hofer, E, Holliday, E, Horn, K, Hornsby, WE, Hottenga, J-J, Huang, H, Huang, J, Huerta-Chagoya, A, Huffman, JE, Hung, Y-J, Huo, S, Hwang, MY, Iha, H, Ikeda, DD, Isono, M, Jackson, AU, Jager, S, Jansen, IE, Johansson, I, Jonas, JB, Jonsson, A, Jorgensen, T, Kalafati, I-P, Kanai, M, Kanoni, S, Karhus, LL, Kasturiratne, A, Katsuya, T, Kawaguchi, T, Kember, RL, Kentistou, KA, Kim, H-N, Kim, YJ, Kleber, ME, Knol, MJ, Kurbasic, A, Lauzon, M, Le, P, Lea, R, Lee, J-Y, Leonard, HL, Li, SA, Li, X, Liang, J, Lin, H, Lin, S-Y, Liu, J, Liu, X, Lo, KS, Long, J, Lores-Motta, L, Luan, J, Lyssenko, V, Lyytikainen, L-P, Mahajan, A, Mamakou, V, Mangino, M, Manichaikul, A, Marten, J, Mattheisen, M, Mavarani, L, McDaid, AF, Meidtner, K, Melendez, TL, Mercader, JM, Milaneschi, Y, Miller, JE, Millwood, IY, Mishra, PP, Mitchell, RE, Mollehave, LT, Morgan, A, Mucha, S, Munz, M, Nakatochi, M, Nelson, CP, Nethander, M, Nho, CW, Nielsen, AA, Nolte, IM, Nongmaithem, SS, Noordam, R, Ntalla, I, Nutile, T, Pandit, A, Christofidou, P, Parna, K, Pauper, M, Petersen, ERB, Petersen, L, Pitkanen, N, Polasek, O, Poveda, A, Preuss, MH, Pyarajan, S, Raffield, LM, Rakugi, H, Ramirez, J, Rasheed, A, Raven, D, Rayner, NW, Riveros, C, Rohde, R, Ruggiero, D, Ruotsalainen, SE, Ryan, KA, Sabater-Lleal, M, Saxena, R, Scholz, M, Sendamarai, A, Shen, B, Shi, J, Shin, JH, Sidore, C, Sitlani, CM, Slieker, RKC, Smit, RAJ, Smith, A, Smith, JA, Smyth, LJ, Southam, LE, Steinthorsdottir, V, Sun, L, Takeuchi, F, Tallapragada, D, Taylor, KD, Tayo, BO, Tcheandjieu, C, Terzikhan, N, Tesolin, P, Teumer, A, Theusch, E, Thompson, DJ, Thorleifsson, G, Timmers, PRHJ, Trompet, S, Turman, C, Vaccargiu, S, van der Laan, SW, van der Most, PJ, van Klinken, JB, van Setten, J, Verma, SS, Verweij, N, Veturi, Y, Wang, CA, Wang, C, Wang, L, Wang, Z, Warren, HR, Wei, WB, Wickremasinghe, AR, Wielscher, M, Wiggins, KL, Winsvold, BS, Wong, A, Wu, Y, Wuttke, M, Xia, R, Xie, T, Yamamoto, K, Yang, J, Yao, J, Young, H, Yousri, NA, Yu, L, Zeng, L, Zhang, W, Zhang, X, Zhao, J-H, Zhao, W, Zhou, W, Zimmermann, ME, Zoledziewska, M, Adair, LS, Adams, HHH, Aguilar-Salinas, CA, Al-Mulla, F, Arnett, DK, Asselbergs, FW, Asvold, BO, Attia, J, Banas, B, Bandinelli, S, Bennett, DA, Bergler, T, Bharadwaj, D, Biino, G, Bisgaard, H, Boerwinkle, E, Boger, CA, Bonnelykke, K, Boomsma, D, Borglum, AD, Borja, JB, Bouchard, C, Bowden, DW, Brandslund, I, Brumpton, B, Buring, JE, Caulfield, MJ, Chambers, JC, Chandak, GR, Chanock, SJ, Chaturvedi, N, Chen, Y-DI, Chen, Z, Cheng, C-Y, Christophersen, IE, Ciullo, M, Cole, JW, Collins, FS, Cooper, RS, Cruz, M, Cucca, F, Cupples, LA, Cutler, MJ, Damrauer, SM, Dantoft, TM, de Borst, GJ, de Groot, LCPGM, De Jager, PL, de Kleijn, DP, de Silva, HJ, Dedoussis, G, den Hollander, A, Du, S, Easton, DF, Elders, PJM, Eliassen, AH, Ellinor, PT, Elmstahl, S, Erdmann, J, Evans, MK, Fatkin, D, Feenstra, B, Feitosa, MF, Ferrucci, L, Ford, I, Fornage, M, Franke, A, Franks, PW, Freedman, B, Gasparini, P, Gieger, C, Girotto, G, Goddard, ME, Golightly, YM, Gonzalez-Villalpando, C, Gordon-Larsen, P, Grallert, H, Grant, SFA, Grarup, N, Griffiths, L, Gudnason, V, Haiman, C, Hakonarson, H, Hansen, T, Hartman, CA, Hattersley, AT, Hayward, C, Heckbert, SR, Heng, C-K, Hengstenberg, C, Hewitt, AW, Hishigaki, H, Hoyng, CB, Huang, PL, Huang, W, Hunt, SC, Hveem, K, Hypponen, E, Iacono, WG, Ichihara, S, Ikram, MA, Isasi, CR, Jackson, RD, Jarvelin, M-R, Jin, Z-B, Jockel, K-H, Joshi, PK, Jousilahti, P, Jukema, JW, Kahonen, M, Kamatani, Y, Kang, KD, Kaprio, J, Kardia, SLR, Karpe, F, Kato, N, Kee, F, Kessler, T, Khera, A, Khor, CC, Kiemeney, LALM, Kim, B-J, Kim, EK, Kim, H-L, Kirchhof, P, Kivimaki, M, Koh, W-P, Koistinen, HA, Kolovou, GD, Kooner, JS, Kooperberg, C, Kottgen, A, Kovacs, P, Kraaijeveld, A, Kraft, P, Krauss, RM, Kumari, M, Kutalik, Z, Laakso, M, Lange, LA, Langenberg, C, Launer, LJ, Le Marchand, L, Lee, H, Lee, NR, Lehtimaki, T, Li, H, Li, L, Lieb, W, Lin, X, Lind, L, Linneberg, A, Liu, C-T, Loeffler, M, London, B, Lubitz, SA, Lye, SJ, Mackey, DA, Magi, R, Magnusson, PKE, Marcus, GM, Vidal, PM, Martin, NG, Marz, W, Matsuda, F, McGarrah, RW, McGue, M, McKnight, AJ, Medland, SE, Mellstrom, D, Metspalu, A, Mitchell, BD, Mitchell, P, Mook-Kanamori, DO, Morris, AD, Mucci, LA, Munroe, PB, Nalls, MA, Nazarian, S, Nelson, AE, Neville, MJ, Newton-Cheh, C, Nielsen, CS, Nothen, MM, Ohlsson, C, Oldehinkel, AJ, Orozco, L, Pahkala, K, Pajukanta, P, Palmer, CNA, Parra, EJ, Pattaro, C, Pedersen, O, Pennell, CE, Penninx, BWJH, Perusse, L, Peters, A, Peyser, PA, Porteous, DJ, Posthuma, D, Power, C, Pramstaller, PP, Province, MA, Qi, Q, Qu, J, Rader, DJ, Raitakari, OT, Ralhan, S, Rallidis, LS, Rao, DC, Redline, S, Reilly, DF, Reiner, AP, Rhee, SY, Ridker, PM, Rienstra, M, Ripatti, S, Ritchie, MD, Roden, DM, Rosendaal, FR, Rotter, J, Rudan, I, Rutters, F, Sabanayagam, C, Saleheen, D, Salomaa, V, Samani, NJ, Sanghera, DK, Sattar, N, Schmidt, B, Schmidt, H, Schmidt, R, Schulze, MB, Schunkert, H, Scott, LJ, Scott, RJ, Sever, P, Shiroma, EJ, Shoemaker, MB, Shu, X-O, Simonsick, EM, Sims, M, Singh, JR, Singleton, AB, Sinner, MF, Smith, JG, Snieder, H, Spector, TD, Stampfer, MJ, Stark, KJ, Strachan, DP, t' Hart, LM, Tabara, Y, Tang, H, Tardif, J-C, Thanaraj, TA, Timpson, NJ, Tonjes, A, Tremblay, A, Tuomi, T, Tuomilehto, J, Tusie-Luna, M-T, Uitterlinden, AG, van Dam, RM, van der Harst, P, Van der Velde, N, van Duijn, CM, van Schoor, NM, Vitart, V, Volker, U, Vollenweider, P, Volzke, H, Wacher-Rodarte, NH, Walker, M, Wang, YX, Wareham, NJ, Watanabe, RM, Watkins, H, Weir, DR, Werge, TM, Widen, E, Wilkens, LR, Willemsen, G, Willett, WC, Wilson, JF, Wong, T-Y, Woo, J-T, Wright, AF, Wu, J-Y, Xu, H, Yajnik, CS, Yokota, M, Yuan, J-M, Zeggini, E, Zemel, BS, Zheng, W, Zhu, X, Zmuda, JM, Zonderman, AB, Zwart, J-A, Chasman, D, Cho, YS, Heid, IM, McCarthy, M, Ng, MCY, O'Donnell, CJ, Rivadeneira, F, Thorsteinsdottir, U, Sun, Y, Tai, ES, Boehnke, M, Deloukas, P, Justice, AE, Lindgren, CM, Loos, RJF, Mohlke, KL, North, KE, Stefansson, K, Walters, RG, Winkler, TW, Young, KL, Loh, P-R, Esko, T, Assimes, TL, Auton, A, Abecasis, GR, Willer, CJ, Locke, AE, Berndt, S, Lettre, G, Frayling, TM, Okada, Y, Wood, AR, Visscher, PM, and Hirschhorn, JN

Abstract

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.

Published
2022

46. Colorectal Cancer Screening within Colonoscopy Capacity Constraints:Can FIT-Based Programs Save More Lives by Trading off More Sensitive Test Cutoffs against Longer Screening Intervals?

Author

McFerran, E., O’Mahony, J. F., Naber, S., Sharp, L., Zauber, A. G., Lansdorp-Vogelaar, I., Kee, F., McFerran, E., O’Mahony, J. F., Naber, S., Sharp, L., Zauber, A. G., Lansdorp-Vogelaar, I., and Kee, F.

Abstract

Introduction. Colorectal cancer (CRC) prevention programs using fecal immunochemical testing (FIT) in screening rely on colonoscopy for secondary and surveillance testing. Colonoscopy capacity is an important constraint. Some European programs lack sufficient capacity to provide optimal screening intensity regarding age ranges, intervals, and FIT cutoffs. It is currently unclear how to optimize programs within colonoscopy capacity constraints. Design. Microsimulation modeling, using the MISCAN-Colon model, was used to determine if more effective CRC screening programs can be identified within constrained colonoscopy capacity. A total of 525 strategies were modeled and compared, varying 3 key screening parameters: screening intervals, age ranges, and FIT cutoffs, including previously unevaluated 4- and 5-year screening intervals (using a lifetime horizon and 100% adherence). Results were compared with the policy decisions taken in Ireland to provide CRC screening within available colonoscopy capacity. Outcomes estimated net costs, quality-adjusted life-years (QALYs), and required colonoscopies. The optimal strategies within finite colonoscopy capacity constraints were identified. Results. Combining a reduced FIT cutoff of 10 µg Hb/g, an extended screening interval of 4 y and an age range of 60–72 y requires 6% fewer colonoscopies, reduces net costs by 23% while preventing 15% more CRC deaths and saving 16% more QALYs relative to a strategy (FIT 40 µg Hb/g, 2-yearly, 60–70 year) approximating current policy. Conclusion. Previously overlooked longer screening intervals may optimize cancer prevention with finite colonoscopy capacity constraints. Changes could save lives, reduce costs, and relieve colonoscopy capacity pressures. These findings are relevant to CRC screening programs across Europe that employ FIT-based testing, which face colonoscopy capacity constraints.

Published
2022

50. The contribution of educational class in improving accuracy of cardiovascular risk prediction across European regions: The MORGAM Project Cohort Component

Author

Ferrario, Marco M, Veronesi, Giovanni, Chambless, Lloyd E, Tunstall-Pedoe, Hugh, Kuulasmaa, Kari, Salomaa, Veikko, Borglykke, Anders, Hart, Nigel, Söderberg, Stefan, Cesana, Giancarlo, Jørgensen, T., Agger, C., Borglykke, A., Salomaa, V., Juolevi, A., Vartiainen, E., Jousilahti, P., Kuulasmaa, K., Cepaitis, Z., Haukijärvi, A., Joseph, B.J, Kulathinal, S., Niemelä, M., Saarela, O., Ducimetière, P., Bingham, A., Arveiler, D., Haas, B., Wagner, A., Ferrières, J., Ruidavets, J-B., Bongard, V., Amouyel, P., Montaye, M., Dallongeville, J., Döring, A., Wichmann, E., Ferrario, M., Ferrario, M., Veronesi, G., Cesana, G., Fornari, C., Sega, R., Mancia, G., Facchetti, R., Vanuzzo, D., Pilotto, L., Picco, F., Mattiussi, F., Gigante, S., Tamosiunas, A., Domarkiene, S., Rastenyte, D., Bernotiene, G., Radisauskas, R., Baceviciene, M., Luksiene, D., Malinauskiene, V., Bernotaite, L., Pająk, A., Kawalec, E., Broda, G., Kurjata, P., Rywik, S.L., Polakowska, M., Pytlak, A., Nikitin, Yu., Malyutina, S., Gafarov, V., Feigin, V., Siminova, G., Voevoda, M., Vinogradova, T., Nasonova, N., Veriovkin, E., Eliasson, M., Söderberg, S., Stegmayr, B., Eriksson, M., Asplund, K., Kee, F, Evans, A., Yarnell, J., Gardner, E., Tunstall-Pedoe, H., Woodward, M, Evans, A., Cashman, S., Evans, A., Blankenberg, S., Ferrario, M., Kee, F., Kuulasmaa, K., Palotie, A., Perola, M., Peters, A., Salomaa, V., Tregouet, D., Tunstall-Pedoe, H., Asplund, K., Cambien, F., Tiret, L, Peltonen, L., Shields, D., Stegmayr, B., and Wiklund, P.-G.

Published
2014
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