Genes vs Physical activity/lifestyle to prolong life – by Werner Bartens in SZ See also “Physical activity genes for physical fitness and risk of coronary heart disease.” at;Med Sci Sports Exerc.;2013 Apr;45(4):691-7. doi: 10.1249/MSS.0b013e3182784e9f. Pubmed;“CONCLUSIONS:;In this large prospective cohort of women genes associated with physical fitness did not modify the inverse association between physical activity and CHD risk.” and ICAMPAM Poster “ACCELEROMICS MEETS GENOMICS – Physical activity and genes for personalized medicine – results from an international expert panel meeting” by;Daumer M12 Kaufman K3 Schwaab B4 Duerr D5 Butterworth A6 Deloukas P7 Moore C6 Hellsten Y8 PilegaardH9 Soaz Gonzalez C1 Schimpl M12 Neuhaus A1 Tusker F10 Xin W11 Klose H-P11 Slawski M12 Kulikowski K13 onbehalf of the participants of the acceleromics meets genomics expert panel (full list in appendix/on website)1SLCMSR e.V. – The Human Motion Institute Munich Germany2Trium Analysis Online GmbH Munich Germany3Mayo Clinic Motion Analysis Lab Rochester Minnesota USA4Klinikum Hoehenried gGmbH Bernried Germany5Ludwig Maximilians Universitaet Muenchen Institute for Mathematics Munich Germany6University of Cambridge Cardiovascular Epidemiology Unit Cambridge UK7The Wellcome Trust Sanger Institute Hinxton UK8University of Copenhagen Department of Exercise and Sport Sciences Copenhagen DK9University of Copenhagen Department of Biology Copenhagen DK10Technical University of Munich Department of Sport Science Munich Germany11Robert Bosch Healthcare GmbH Suttgart Germany12Saarland University Department of Computer Science Saarbruecken Germany13Rutgers University Department of Computer Science Piscataway USA Discussion and conclusion: “Mobile accelerometry has great potential for improving human health by contributing to the diagnosis of gait and balance disorders in daily life and clinical practice improving outcome measuresin chronic disabling diseases as well as a tool for prescribing and monitoring exercise therapy. It alsoprovides the potential for greater insight into associations between physical activity and disease riskseg cardiovascular disease either independently or through interaction with genetic variants.Standardization of sampling methods data formats and validation rules for assessingperformance are needed and sharing and publishing raw data would be advantageous but entailsdifficult IP issues. At a later stage decision-support tools may couple information about lifestyleincluding physical activity profiles and risk genes. This will most likely start with prediction ofresponders/non-responders to treatment and rare diseases with a strong genetic backgroundcomponent. Independent assessment of the impact of the technologies and tools in clinical practiceis desirable.”