Age- and sex-specific causal effects of adiposity on cardiovascular risk factors

88siObservational studies have reported different effects of adiposity on cardiovascular risk factors across age and sex. Since cardiovascular risk factors are enriched in obese individuals, it has not been easy to dissect the effects of adiposity from those of other risk factors. We used a Mendelian randomization approach, applying a set of 32 genetic markers to estimate the causal effect of adiposity on blood pressure, glycemic indices, circulating lipid levels, and markers of inflammation and liver disease in up to 67,553 individuals. All analyses were stratified by age (cutoff 55 years of age) and sex. The genetic score was associated with BMI in both nonstratified analysis (P = 2.8 × 10(-107)) and stratified analyses (all P < 3.3 × 10(-30)). We found evidence of a causal effect of adiposity on blood pressure, fasting levels of insulin, C-reactive protein, interleukin-6, HDL cholesterol, and triglycerides in a nonstratified analysis and in the <55-year stratum. Further, we found evidence of a smaller causal effect on total cholesterol (P for difference = 0.015) in the ≥55-year stratum than in the <55-year stratum, a finding that could be explained by biology, survival bias, or differential medication. In conclusion, this study extends previous knowledge of the effects of adiposity by providing sex- and age-specific causal estimates on cardiovascular risk factors.noneFall, T.; Hägg, S.; Ploner, A.; Mägi, R.; Fischer, K.; Draisma, H.H.; Sarin, A.-P.; Benyamin, B.; Ladenvall, C.; Åkerlund, M.; Kals, M.; Esko, T.; Nelson, C.P.; Kaakinen, M.; Huikari, V.; Mangino, M.; Meirhaeghe, A.; Kristiansson, K.; Nuotio, M.-L.; Kobl, M.; Grallert, H.; Dehghan, A.; Kuningas, M.; de Vries, P.S.; de Bruijn, R.F.; Willems, S.M.; Heikkilä, K.; Silventoinen, K.; Pietiläinen, K.H.; Legry, V.; Giedraitis, V.; Goumidi, L.; Syvänen, A.-C.; Strauch, K.; Koenig, W.; Lichtner, P.; Herder, C.; Palotie, A.; Menni, C.; Uitterlinden, A.G.; Kuulasmaa, K.; Havulinna, A.S.; Moreno, L.A.; Gonzalez-Gross, M.; Evans, A.; Tregouet, D.-A.; Yarnell, J.W.; Virtamo, J.; Ferrières, J.; Veronesi, G.; Perola, M.; Arveiler, D.; Brambilla, P.; Lind, L.; Kaprio, J.; Hofman, A.; Stricker, B.H.; van Duijn, C.M.; Ikram, M.A.; Franco, O.H.; Cottel, D.; Dallongeville, J.; Hall, A.S.; Jula, A.; Tobin, M.D.; Penninx, B.W.; Peters, A.; Gieger, C.; Samani, N.J.; Montgomery, G.W.; Whitfield, J.B.; Martin, N.G.; Groop, L.; Spector, T.D.; Magnusson, P.K.; Amouyel, P.; Boomsma, D.I.; Nilsson, P.M.; Järvelin, M.-R.; Lyssenko, V.; Metspalu, A.; Strachan, D.P.; Salomaa, V.; Ripatti, S.; Pedersen, N.L.; Prokopenko, I.; Mccarthy, M.I.; Ingelsson, E.Fall, T.; Hägg, S.; Ploner, A.; Mägi, R.; Fischer, K.; Draisma, H. H.; Sarin, A. P.; Benyamin, B.; Ladenvall, C.; Åkerlund, M.; Kals, M.; Esko, T.; Nelson, C. P.; Kaakinen, M.; Huikari, V.; Mangino, M.; Meirhaeghe, A.; Kristiansson, K.; Nuotio, M. L.; Kobl, M.; Grallert, H.; Dehghan, A.; Kuningas, M.; de Vries, P. S.; de Bruijn, R. F.; Willems, S. M.; Heikkilä, K.; Silventoinen, K.; Pietiläinen, K. H.; Legry, V.; Giedraitis, V.; Goumidi, L.; Syvänen, A. C.; Strauch, K.; Koenig, W.; Lichtner, P.; Herder, C.; Palotie, A.; Menni, C.; Uitterlinden, A. G.; Kuulasmaa, K.; Havulinna, A. S.; Moreno, L. A.; Gonzalez Gross, M.; Evans, A.; Tregouet, D. A.; Yarnell, J. W.; Virtamo, J.; Ferrières, J.; Veronesi, Giovanni; Perola, M.; Arveiler, D.; Brambilla, P.; Lind, L.; Kaprio, J.; Hofman, A.; Stricker, B. H.; van Duijn, C. M.; Ikram, M. A.; Franco, O. H.; Cottel, D.; Dallongeville, J.; Hall, A. S.; Jula, A.; Tobin, M. D.; Penninx, B. W.; Peters, A.; Gieger, C.; Samani, N. J.; Montgomery, G. W.; Whitfield, J. B.; Martin, N. G.; Groop, L.; Spector, T. D.; Magnusson, P. K.; Amouyel, P.; Boomsma, D. I.; Nilsson, P. M.; Järvelin, M. R.; Lyssenko, V.; Metspalu, A.; Strachan, D. P.; Salomaa, V.; Ripatti, S.; Pedersen, N. L.; Prokopenko, I.; Mccarthy, M. I.; Ingelsson, E

A survey of parametric fingerprint-positioning methods

The term fingerprint-based (FP) positioning includes a wide variety of methods for determining a receiver’s position using a database of radio signal strength measurements that were collected earlier at known locations. Nonparametric methods such as the weighted k-nearest neighbor (WKNN) method are infeasible for large-scale mobile device services because of the large data storage and transmission requirements. In this work we present an overview of parametric FP methods that use model-based representations of the survey data. We look at three different groups of parametric methods: methods that use coverage areas, methods that use path loss models, and methods that use Gaussian mixtures. Within each group we study different approaches and discuss their pros and cons. Furthermore, we test the positioning performance of several of the analyzed approaches in different scenarios using real-world WLAN indoor data and compare the results to those of the WKNN method.publishedVersionPeer reviewe

Age- and sex-specific causal effects of adiposity on cardiovascular risk factors

Observational studies have reported different effects of adiposity on cardiovascular risk factors across age and sex. Since cardiovascular risk factors are enriched in obese individuals, it has not been easy to dissect the effects of adiposity from those of other risk factors. We used a Mendelian randomization approach, applying a set of 32 genetic markers to estimate the causal effect of adiposity on blood pressure, glycemic indices, circulating lipid levels, and markers of inflammation and liver disease in up to 67,553 individuals. All analyses were stratified by age (cutoff 55 years of age) and sex. The genetic score was associated with BMI in both nonstratified analysis (P = 2.8 × 10(-107)) and stratified analyses (all P < 3.3 × 10(-30)). We found evidence of a causal effect of adiposity on blood pressure, fasting levels of insulin, C-reactive protein, interleukin-6, HDL cholesterol, and triglycerides in a nonstratified analysis and in the <55-year stratum. Further, we found evidence of a smaller causal effect on total cholesterol (P for difference = 0.015) in the ≥55-year stratum than in the <55-year stratum, a finding that could be explained by biology, survival bias, or differential medication. In conclusion, this study extends previous knowledge of the effects of adiposity by providing sex- and age-specific causal estimates on cardiovascular risk factors