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1. Self-rated health in individuals with and without disease is associated with multiple biomarkers representing multiple biological domains

Author

Kananen, L., Enroth, L., Raitanen, J., Jylhava, J., Burkle, A., Moreno-Villanueva, M., Bernhardt, J., Toussaint, O., Grubeck-Loebenstein, B., Malavolta, M., Basso, A., Piacenza, F., Collino, S., Gonos, E.S., Sikora, E., Gradinaru, D., Jansen, E.H.J.M., Dolle, M.E.T., Salmon, M., Stuetz, W., Weber, D., Grune, T., Breusing, N., Simm, A., Capri, M., Franceschi, C., Slagboom, P.E., Talbot, D.C.S., Libert, C., Koskinen, S., Bruunsgaard, H., Hansen, A.M., Lund, R., Hurme, M., Jylha, M., Kananen L., Enroth L., Raitanen J., Jylhava J., Burkle A., Moreno-Villanueva M., Bernhardt J., Toussaint O., Grubeck-Loebenstein B., Malavolta M., Basso A., Piacenza F., Collino S., Gonos E.S., Sikora E., Gradinaru D., Jansen E.H.J.M., Dolle M.E.T., Salmon M., Stuetz W., Weber D., Grune T., Breusing N., Simm A., Capri M., Franceschi C., Slagboom P.E., Talbot D.C.S., Libert C., Koskinen S., Bruunsgaard H., Hansen A., Lund R., Hurme M., Jylha M., Tampere University, Health Sciences, and BioMediTech

Subjects
Quality of life, Adult, Male, Aging, Adolescent, Health Status, Science, education, Predictive markers, Article, Diagnostic Self Evaluation, Young Adult, ddc:570, Medicine and Health Sciences, Humans, Aged, Aged, 80 and over, Health care, Biology and Life Sciences, biomarkers, Middle Aged, 3141 Health care science, body regions, Somatosensory system, Medicine, Female, 3111 Biomedicine, Self Report
Abstract

Self-rated health (SRH) is one of the most frequently used indicators in health and social research. Its robust association with mortality in very different populations implies that it is a comprehensive measure of health status and may even reflect the condition of the human organism beyond clinical diagnoses. Yet the biological basis of SRH is poorly understood. We used data from three independent European population samples (N approx. 15,000) to investigate the associations of SRH with 150 biomolecules in blood or urine (biomarkers). Altogether 57 biomarkers representing different organ systems were associated with SRH. In almost half of the cases the association was independent of disease and physical functioning. Biomarkers weakened but did not remove the association between SRH and mortality. We propose three potential pathways through which biomarkers may be incorporated into an individual’s subjective health assessment, including (1) their role in clinical diseases; (2) their association with health-related lifestyles; and (3) their potential to stimulate physical sensations through interoceptive mechanisms. Our findings indicate that SRH has a solid biological basis and it is a valid but non-specific indicator of the biological condition of the human organism. publishedVersion

Published
2021

2. Are body mass index, waist circumference and waist-to-hip ratio associated with leptin in 90-year-old people?

Author

Lisko, I., Tiainen, K., Stenholm, S., Luukkaala, T., Hurme, M., Lehtimaki, T., Hervonen, A., and Jylha, M.

Subjects
Aged -- Physiological aspects, Adipose tissues -- Physiological aspects, Leptin -- Physiological aspects, Body mass index, Food/cooking/nutrition, Health
Abstract

Data on how body mass index (BMI), waist circumference (WC) and waist-to-hip ratio (WHR) are associated with body fat in the oldest-old people are scarce. The purpose of this study was to examine if BMI, WC or WHR are associated with leptin, a biological surrogate measure of body fat in 90-year-old people. The data comes from the Vitality 90 + Study, a prospective population-based study of people living in Tampere, Finland. BMI, WC, WHR and plasma concentration of leptin were available for 160 women and 54 men aged 90 years. BMI and WC had a strong significant positive association with leptin both in women and in men, but WHR was associated with leptin only in men. In conclusion, based on the circulating level of leptin, BMI and WC, and WHR in men, reflect body fat in 90- year-old people, but WHR seems to be a poor indicator of body fat in 90-year-old women. European Journal of Clinical Nutrition (2013) 67, 420-422; doi: 10.1038/ejcn.2013.39; published online 27 February 2013 Keywords: body fat; anthropometrics; leptin; nutritional status; oldest-old, INTRODUCTION In younger and middle-aged adults, high body fat is a major public health concern but in the oldest-old low body fat, which reflects malnutrition, is a greater concern. However, [...]

Published
2013
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4. Genome-wide meta-analysis associates HLA-DQA1/DRB1 and LPA and lifestyle factors with human longevity

Author

Joshi, P.K., Pirastu, N., Kentistou, K.A., Fischer, K., Hofer, E., Schraut, K.E., Clark, D.W., Nutile, T., Barnes, C.L.K., Timmers, P., Shen, X., Gandin, I., McDaid, A.F., Hansen, T.F., Gordon, S.D.S., Giulianini, F., Boutin, T.S., Abdellaoui, A., Zhao, W., Medina-Gomez, C., Bartz, T.M., Trompet, S., Lange, L.A., Raffield, L., Spek, A van der, Galesloot, T.E., Proitsi, P., Yanek, L.R., Bielak, L.F., Payton, A., Murgia, F., Concas, M.P., Biino, G., Tajuddin, S.M., Seppala, I., Amin, N., Boerwinkle, E., Borglum, A.D., Campbell, A., Demerath, E.W., Demuth, I., Faul, J.D., Ford, I., Gialluisi, A., Gogele, M., Graff, M, Hingorani, A., Hottenga, J.J., Hougaard, D.M., Hurme, M.A., Ikram, M.A., Jylha, M., Kuh, D., Ligthart, L., Lill, C.M., Lindenberger, U., Lumley, T., Magi, R., Marques-Vidal, P., Medland, S.E., Milani, L., Nagy, R., Ollier, W.E., Peyser, P.A., Pramstaller, P.P., Ridker, P.M., Rivadeneira, F., Ruggiero, D., Saba, Y., Schmidt, R., Schmidt, H., Slagboom, P.E., Smith, B.H., Smith, J.A., Sotoodehnia, N., Steinhagen-Thiessen, E., Rooij, F.J. van, Verbeek, A.L., Vermeulen, S.H., Vollenweider, P., Wang, Y, Werge, T., Whitfield, J.B., Zonderman, A.B., Lehtimaki, T., Evans, M.K., Pirastu, M., Fuchsberger, C., Bertram, L., Pendleton, N., Kardia, S.L., Ciullo, M., Becker, D.M., Wong, A., Psaty, B.M., Duijn, C.M. van, Wilson, J.G., Jukema, J.W., Kiemeney, L.A., and Uitterlinden, A.G.

Subjects
Urological cancers Radboud Institute for Health Sciences [Radboudumc 15], Women's cancers Radboud Institute for Health Sciences [Radboudumc 17]
Abstract

Contains fulltext : 177742.pdf (Publisher’s version ) (Open Access) Genomic analysis of longevity offers the potential to illuminate the biology of human aging. Here, using genome-wide association meta-analysis of 606,059 parents' survival, we discover two regions associated with longevity (HLA-DQA1/DRB1 and LPA). We also validate previous suggestions that APOE, CHRNA3/5, CDKN2A/B, SH2B3 and FOXO3A influence longevity. Next we show that giving up smoking, educational attainment, openness to new experience and high-density lipoprotein (HDL) cholesterol levels are most positively genetically correlated with lifespan while susceptibility to coronary artery disease (CAD), cigarettes smoked per day, lung cancer, insulin resistance and body fat are most negatively correlated. We suggest that the effect of education on lifespan is principally mediated through smoking while the effect of obesity appears to act via CAD. Using instrumental variables, we suggest that an increase of one body mass index unit reduces lifespan by 7 months while 1 year of education adds 11 months to expected lifespan.Variability in human longevity is genetically influenced. Using genetic data of parental lifespan, the authors identify associations at HLA-DQA/DRB1 and LPA and find that genetic variants that increase educational attainment have a positive effect on lifespan whereas increasing BMI negatively affects lifespan. 13 p.

Published
2017

5. Genome-wide meta-analysis associates HLA-DQA1/DRB1 and LPA and lifestyle factors with human longevity

Author

Joshi, PK, Pirastu, N, Kentistou, KA, Fischer, K, Hofer, E, Schraut, KE, Clark, DW, Nutile, T, Barnes, CLK, Timmers, P, Shen, X, Gandin, I, McDaid, AF, Hansen, TF, Gordon, SD, Giulianini, F, Boutin, TS, Abdellaoui, A, Zhao, W, Medina-Gomez, C, Bartz, TM, Trompet, S, Lange, LA, Raffield, L, van der Spek, Ashley, Galesloot, TE, Proitsi, P, Yanek, LR, Bielak, LF, Payton, A, Murgia, F, Concas, MP, Biino, G, Tajuddin, S M, Seppala, I, Amin, Najaf, Boerwinkle, E, Borglum, AD, Campbell, A (Archie), Demerath, EW, Demuth, I, Faul, JD, Ford, I, Gialluisi, A, Gogele, M, Graff, M, Hingorani, A, Hottenga, JJ, Hougaard, DM, Hurme, MA, Ikram, Arfan, Jylha, M, Kuh, D, Ligthart, L, Lill, CM, Lindenberger, U, Lumley, T, Magi, R, Marques-Vidal, P, Medland, SE, Milani, L, Nagy, R, Ollier, WER, Peyser, PA, Pramstaller, PP, Ridker, PM, Rivadeneira, F, Ruggiero, D, Saba, Y, Schmidt, R, Schmidt, H, Slagboom, PE (Eline), Smith, BH, Smith, JA, Sotoodehnia, N, Steinhagen-Thiessen, E, van Rooij, FJA, Verbeek, AL, Vermeulen, SH, Vollenweider, P, Wang, YP, Werge, T, Whitfield, JB, Zonderman, AB, Lehtimaki, T, Evans, MK, Pirastu, M, Fuchsberger, C, Bertram, L, Pendleton, N, Kardia, SLR, Ciullo, M, Becker, DM, Wong, A, Psaty, BM, Duijn, Cornelia, Wilson, JG, Jukema, JW, Kiemeney, L, Uitterlinden, André, Franceschini, N, North, KE, Weir, DR, Metspalu, A, Boomsma, DI, Hayward, C, Chasman, D, Martin, NG, Sattar, N, Campbell, H, Esko, T, Kutalik, Z, Wilson, JF, Joshi, PK, Pirastu, N, Kentistou, KA, Fischer, K, Hofer, E, Schraut, KE, Clark, DW, Nutile, T, Barnes, CLK, Timmers, P, Shen, X, Gandin, I, McDaid, AF, Hansen, TF, Gordon, SD, Giulianini, F, Boutin, TS, Abdellaoui, A, Zhao, W, Medina-Gomez, C, Bartz, TM, Trompet, S, Lange, LA, Raffield, L, van der Spek, Ashley, Galesloot, TE, Proitsi, P, Yanek, LR, Bielak, LF, Payton, A, Murgia, F, Concas, MP, Biino, G, Tajuddin, S M, Seppala, I, Amin, Najaf, Boerwinkle, E, Borglum, AD, Campbell, A (Archie), Demerath, EW, Demuth, I, Faul, JD, Ford, I, Gialluisi, A, Gogele, M, Graff, M, Hingorani, A, Hottenga, JJ, Hougaard, DM, Hurme, MA, Ikram, Arfan, Jylha, M, Kuh, D, Ligthart, L, Lill, CM, Lindenberger, U, Lumley, T, Magi, R, Marques-Vidal, P, Medland, SE, Milani, L, Nagy, R, Ollier, WER, Peyser, PA, Pramstaller, PP, Ridker, PM, Rivadeneira, F, Ruggiero, D, Saba, Y, Schmidt, R, Schmidt, H, Slagboom, PE (Eline), Smith, BH, Smith, JA, Sotoodehnia, N, Steinhagen-Thiessen, E, van Rooij, FJA, Verbeek, AL, Vermeulen, SH, Vollenweider, P, Wang, YP, Werge, T, Whitfield, JB, Zonderman, AB, Lehtimaki, T, Evans, MK, Pirastu, M, Fuchsberger, C, Bertram, L, Pendleton, N, Kardia, SLR, Ciullo, M, Becker, DM, Wong, A, Psaty, BM, Duijn, Cornelia, Wilson, JG, Jukema, JW, Kiemeney, L, Uitterlinden, André, Franceschini, N, North, KE, Weir, DR, Metspalu, A, Boomsma, DI, Hayward, C, Chasman, D, Martin, NG, Sattar, N, Campbell, H, Esko, T, Kutalik, Z, and Wilson, JF

Published
2017

16. USF1 GENE IS INVOLVED IN THE REGULATION OF HUMAN LONGEVITY

Author

Ozsait, B., primary, Komurcu-Bayrak, E., additional, Jylha, M., additional, Perola, M., additional, Kristiansson, K., additional, Mononen, N., additional, Hurme, M., additional, Laaksonen, R., additional, Hervonen, A., additional, Erginel-Unaltuna, N., additional, Karhunen, P., additional, and Lehtimaki, T., additional

Published
2008
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23. Self-rated health is associated with biomarkers, but predicts mortality independently of them

Author

Jylha, M., Volpato, S., and Guralnik, J.

Subjects
Health, Seniors
Abstract

We examined the associations of frequently used biomarkers with SRH, and the influence of these biomarkers on the association between SRH and mortality. The subjects were 3840 men and women aged 70 and older at baseline who participated in the sixth follow-up of the EPESE Study. Adjusted for age and sex, higher white cell count, higher hemoglobin, higher level of albumin, and lower creatinine were significantly associated with good self-rated health. The linear relationship between higher white cell count and higher hemoglobin, respectively, with good SRH was still significant after adjusting for other biomarkers, blood pressure, coronary heart disease, stroke, diabetes, cancer, ADL, smoking, and education. Self-rated health significantly predicted mortality, and this was true even after adjusting for biomarkers. We conclude that self-ratings of health have a biological basis, but the biological and clinical information that was available could not exhaustively explain the association of SRH with mortality.

Published
2002

27. Health problems associated with lower urinary tract symptoms in older women: a population-based study.

Author

Nuotio M, Jylha M, Luukkaala T, and Tammela TLJ

Abstract

OBJECTIVE: To identify health problems associated with lower urinary tract symptoms (LUTS) in an older female population. DESIGN: Population-based cross-sectional survey. SETTING: Third wave for the Tampere Longitudinal Study on Ageing (TamELSA) in 1999-2000. SUBJECTS: A total of 203 women aged 70 years and over. MAIN OUTCOME MEASURES: LUTS categorized as urge symptoms only, voiding symptoms only, and urge and voiding symptoms combined. The health indicators were polypharmacy (> 3 medications), use of sleeping medication, constipation, treated urinary tract infections (UTIs), and neurological, cardiovascular, and musculoskeletal diseases. RESULTS: Of the respondents 16% reported urge symptoms, 22% voiding symptoms, and 26% combined symptoms. In the multinomial logistic regression models, constipation and musculoskeletal diseases were significantly associated with voiding symptoms (OR 4.33; 95% CI 1.62-11.57 and OR 5.25; 95% CI 1.94-14.18, respectively) and with combined symptoms (OR 4.33; 95% CI 1.67-11.21 and OR 2.84; 95% CI 1.17-6.89, respectively). UTIs (OR 2.78; 95% CI 1.09-7.08) were associated with combined symptoms. CONCLUSIONS: Voiding symptoms comprise a significant part of lower urinary tract symptomalogy in older women. Although constipation, musculoskeletal diseases, and UTIs are the main health problems associated with LUTS, other concomitant diseases and medications also need to be assessed in older female patients with LUTS. [ABSTRACT FROM AUTHOR]

Published
2005
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31. Self-rated health and self-assessed change in health in elderly men and women -- a five-year longitudinal study.

Author

Leinonen R, Heikkinen E, and Jylha M

Abstract

The purpose of the present investigation was two fold: (1) to examine how men and women self-rate their health as they age from 75 to 80 yr and how they assess the change in their health over the five year period; and (2) to ascertain how self-assessed change in health over the follow-up period corresponded to the difference in self-ratings of health between the assessments performed at baseline and at follow-up. The study was part of the Evergreen-project with the study group comprising all inhabitants born in 1914 (N = 388) living in Jyvaskyla, central Finland. At baseline, 93.4%, and at follow-up, 93.3%, of those who were eligible participated in the interview. Self-rated health, when asked using the same questions, did not change at follow-up compared to baseline. However, nearly half of the follow-up group reported that their health had become worse over the five year period. Gender differences in self-rated health were not found, although women reported more often than men that their health had become worse and some of the men said their health had become better. It is concluded that self-rated health seems to be age-adjusted; elderly people who say their health has become worse as they age actually self-rate their health as the same or better than before. [ABSTRACT FROM AUTHOR]

Published
1998
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32. Circulating cell-free DNA in health and disease - the relationship to health behaviours, ageing phenotypes and metabolomics

Author

Laura Kananen, Mikko Hurme, Alexander Bürkle, Maria Moreno-Villanueva, Jürgen Bernhardt, Florence Debacq-Chainiaux, Beatrix Grubeck-Loebenstein, Marco Malavolta, Andrea Basso, Francesco Piacenza, Sebastiano Collino, Efstathios S. Gonos, Ewa Sikora, Daniela Gradinaru, Eugene H. J. M. Jansen, Martijn E. T. Dollé, Michel Salmon, Wolfgang Stuetz, Daniela Weber, Tilman Grune, Nicolle Breusing, Andreas Simm, Miriam Capri, Claudio Franceschi, Eline Slagboom, Duncan Talbot, Claude Libert, Jani Raitanen, Seppo Koskinen, Tommi Härkänen, Sari Stenholm, Mika Ala-Korpela, Terho Lehtimäki, Olli T. Raitakari, Olavi Ukkola, Mika Kähönen, Marja Jylhä, Juulia Jylhävä, Tampere University, Health Sciences, BioMediTech, Department of Clinical Chemistry, Clinical Medicine, Department of Clinical Physiology and Nuclear Medicine, Kananen L., Hurme M., Burkle A., Moreno-Villanueva M., Bernhardt J., Debacq-Chainiaux F., Grubeck-Loebenstein B., Malavolta M., Basso A., Piacenza F., Collino S., Gonos E.S., Sikora E., Gradinaru D., Jansen E.H.J.M., Dolle M.E.T., Salmon M., Stuetz W., Weber D., Grune T., Breusing N., Simm A., Capri M., Franceschi C., Slagboom E., Talbot D., Libert C., Raitanen J., Koskinen S., Harkanen T., Stenholm S., Ala-Korpela M., Lehtimaki T., Raitakari O.T., Ukkola O., Kahonen M., Jylha M., and Jylhava J.

Subjects
Aging, Frailty, Biology and Life Sciences, Metabolomic, 3121 Internal medicine, 3142 Public health care science, environmental and occupational health, 3141 Health care science, Cell-free DNA, Health behaviours, Medicine and Health Sciences, Health behaviour, Metabolomics, 3111 Biomedicine, Geriatrics and Gerontology, Morbidity, Biomarker of ageing
Abstract

Circulating cell-free DNA (cf-DNA) has emerged as a promising biomarker of ageing, tissue damage and cellular stress. However, less is known about health behaviours, ageing phenotypes and metabolic processes that lead to elevated cf-DNA levels. We sought to analyse the relationship of circulating cf-DNA level to age, sex, smoking, physical activity, vegetable consumption, ageing phenotypes (physical functioning, the number of diseases, frailty) and an extensive panel of biomarkers including blood and urine metabolites and inflammatory markers in three human cohorts (N = 5385; 17–82 years). The relationships were assessed using correlation statistics, and linear and penalised regressions (the Lasso), also stratified by sex.cf-DNA levels were significantly higher in men than in women, and especially in middle-aged men and women who smoke, and in older more frail individuals. Correlation statistics of biomarker data showed that cf-DNA level was higher with elevated inflammation (C-reactive protein, interleukin-6), and higher levels of homocysteine, and proportion of red blood cells and lower levels of ascorbic acid. Inflammation (C-reactive protein, glycoprotein acetylation), amino acids (isoleucine, leucine, tyrosine), and ketogenesis (3-hydroxybutyrate) were included in the cf-DNA level-related biomarker profiles in at least two of the cohorts.In conclusion, circulating cf-DNA level is different by sex, and related to health behaviour, health decline and metabolic processes common in health and disease. These results can inform future studies where epidemiological and biological pathways of cf-DNA are to be analysed in details, and for studies evaluating cf-DNA as a potential clinical marker.

Published
2023

33. Design, recruitment, logistics, and data management of the GEHA (Genetics of Healthy Ageing) project

Author

C. Gilbault, G. Pelicci, Marian Beekman, Axel Skytthe, Serena Dato, A. Skouteri, Konstantinos Voutetakis, Luca Deiana, Ciriaco Carru, Ewa Sikora, Claudio Franceschi, Friederike Flachsbart, Leena Peltonen, James W. Vaupel, P. Laiho, Joanna Collerton, V. Bezrukov, Stefan Schreiber, Michel Poulain, Karen Davies, Irene Maeve Rea, Mikko Hurme, Giuseppe Passarino, Federica Sevini, Katarzyna Broczek, Outi Törnwall, Antti Hervonen, Elisa Cevenini, Hélène Blanché, Bernard Jeune, Maria Scurti, Rodolfo Cotichini, Jean-Marie Robine, Erica Haimes, A.J.M. de Craen, Thomas B. L. Kirkwood, R. Masciulli, José Remacle, Lene Christiansen, Dorota Janiszewska, F. Balard, Almut Nebel, A. Leon, P.E. Slagboom, Lars Bolund, A. Marchisio, Liana Spazzafumo, Marja Jylhä, Virgilia Toccaceli, G. De Benedictis, Markus Perola, Olivier Toussaint, Jutta Gampe, M A Stazi, Silvana Valensin, Peter Kristensen, Kaare Christensen, Efstathios S. Gonos, University of Southern Denmark (SDU), University of Bologna/Università di Bologna, Laboratoire Lorrain de Sciences Sociales (2L2S), Université de Lorraine (UL), Institut National de la Santé et de la Recherche Médicale (INSERM), Netherlands Consortium for Healthy Ageing, Leiden University Medical Center (LUMC), Universiteit Leiden-Universiteit Leiden, Institute of Gerontology [Kiev], Fondation Jean Dausset - Centre d’Etudes du Polymorphisme Humain [Paris] (CEPH), Beijing Genomics Institute [Shenzhen] (BGI), Institute of Human Genetics [Aarhus], Nencki Institute of Experimental Biology, Polska Akademia Nauk = Polish Academy of Sciences (PAN), Medical University of Warsaw - Poland, Università degli Studi di Sassari = University of Sassari [Sassari] (UNISS), Odense University Hospital (OUH), Newcastle University [Newcastle], Istituto Superiore di Sanità (ISS), Universiteit Leiden, Università della Calabria [Arcavacata di Rende] (Unical), Institute of Clinical Molecular Biology, Kiel University, Max Planck Institute for Demographic Research (MPIDR), Max-Planck-Gesellschaft, Université Catholique de Louvain = Catholic University of Louvain (UCL), National Hellenic Research Foundation [Athens], Tampere School of Public Health, University of Tampere [Finland], University of Aarhus, The National Institute for Health and Welfare, National Institute for Health and Welfare [Helsinki], Research Innovation [Italy], IFOM Institute of Milan, Queen's University [Belfast] (QUB), Eppendorf Array Technologies, CERMES3 - Centre de recherche Médecine, sciences, santé, santé mentale, société (CERMES3 - UMR 8211 / U988 / UM 7), École des hautes études en sciences sociales (EHESS)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Istituto Nazionale Ricovero e Cura Anziani, Université de Namur [Namur] (UNamur), European Project: 26813,GEHA, University of Bologna, Istituto Superiore di Sanita [Rome], University of Calabria, The Queen’s University of Belfast, Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Descartes - Paris 5 (UPD5)-École des hautes études en sciences sociales (EHESS), Skytthe A., Valensin S., Jeune B., Cevenini E., Balard F., Beekman M., Bezrukov V., Blanche H., Bolund L., Broczek K., Carru C., Christensen K., Christiansen L., Collerton J.C., Cotichini R., de Craen A.J., Dato S., Davies K., De Benedictis G., Deiana L., Flachsbart F., Gampe J., Gilbault C., Gonos E.S., Haimes E., Hervonen A., Hurme M.A., Janiszewska D., Jylha M., Kirkwood T.B., Kristensen P., Laiho P., Leon A., Marchisio A., Masciulli R., Nebel A., Passarino G., Pelicci G., Peltonen L., Perola M., Poulain M., Rea I.M., Remacle J., Robine J.M., Schreiber S., Scurti M., Sevini F., Sikora E., Skouteri A., Slagboom P.E., Spazzafumo L., Stazi M.A., Toccaceli V., Toussaint O., Tornwall O., Vaupel J.W., Voutetakis K., Franceschi C., GEHA consortium [Pini Elisa, Palmas Maria Giustina, Panourgia Maria Panagiota], balard, frédéric, and GEnetics for Healthy Aging - GEHA - 26813 - OLD

Subjects
Research design, Gerontology, Male, Questionnaires, Aging, Genetic Linkage, [SDV]Life Sciences [q-bio], Genome-wide association study, Biochemistry, Nonagenarian sib pairs, [SHS]Humanities and Social Sciences, 0302 clinical medicine, Endocrinology, Cognition, Surveys and Questionnaires, 80 and over, Medicine, ComputingMilieux_MISCELLANEOUS, media_common, Genetics, Aged, 80 and over, 0303 health sciences, Life style, Longevity, Middle Aged, HEALTHY AGING, [SDV] Life Sciences [q-bio], Europe, Research Design, Extreme longevity tracking, Female, [SHS] Humanities and Social Sciences, media_common.quotation_subject, Article, 03 medical and health sciences, Healthy ageing, Humans, Family, Molecular Biology, Life Style, 030304 developmental biology, Genetic association, Aged, nonagenarian sib pair, business.industry, Patient Selection, Cell Biology, Multicenter study, business, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

In 2004, the integrated European project GEHA (Genetics of Healthy Ageing) was initiated with the aim of identifying genes involved in healthy ageing and longevity. The first step in the project was the recruitment of more than 2500 pairs of siblings aged 90years or more together with one younger control person from 15 areas in 11 European countries through a coordinated and standardised effort. A biological sample, preferably a blood sample, was collected from each participant, and basic physical and cognitive measures were obtained together with information about health, life style, and family composition. From 2004 to 2008 a total of 2535 families comprising 5319 nonagenarian siblings were identified and included in the project. In addition, 2548 younger control persons aged 50-75years were recruited. A total of 2249 complete trios with blood samples from at least two old siblings and the younger control were formed and are available for genetic analyses (e.g. linkage studies and genome-wide association studies). Mortality follow-up improves the possibility of identifying families with the most extreme longevity phenotypes. With a mean follow-up time of 3.7years the number of families with all participating siblings aged 95years or more has increased by a factor of 5 to 750 families compared to when interviews were conducted. Thus, the GEHA project represents a unique source in the search for genes related to healthy ageing and longevity. In 2004, the integrated European project GEHA (Genetics of Healthy Ageing) was initiated with the aim of identifying genes involved in healthy ageing and longevity. The first step in the project was the recruitment of more than 2500 pairs of siblings aged 90years or more together with one younger control person from 15 areas in 11 European countries through a coordinated and standardised effort. A biological sample, preferably a blood sample, was collected from each participant, and basic physical and cognitive measures were obtained together with information about health, life style, and family composition. From 2004 to 2008 a total of 2535 families comprising 5319 nonagenarian siblings were identified and included in the project. In addition, 2548 younger control persons aged 50-75years were recruited. A total of 2249 complete trios with blood samples from at least two old siblings and the younger control were formed and are available for genetic analyses (e.g. linkage studies and genome-wide association studies). Mortality follow-up improves the possibility of identifying families with the most extreme longevity phenotypes. With a mean follow-up time of 3.7years the number of families with all participating siblings aged 95years or more has increased by a factor of 5 to 750 families compared to when interviews were conducted. Thus, the GEHA project represents a unique source in the search for genes related to healthy ageing and longevity.

Published
2011

34. Changes in older people's care profiles during the last 2 years of life, 1996-1998 and 2011-2013: a retrospective nationwide study in Finland.

Author

Aaltonen M, Forma L, Pulkki J, Raitanen J, Rissanen P, and Jylha M

Subjects
Aged, Aged, 80 and over, Cross-Sectional Studies, Dementia epidemiology, Female, Finland epidemiology, Homes for the Aged, Humans, Male, Patient Transfer statistics & numerical data, Registries, Retrospective Studies, Time Factors, Home Care Services statistics & numerical data, Hospitalization statistics & numerical data, Long-Term Care statistics & numerical data, Nursing Homes statistics & numerical data, Terminal Care statistics & numerical data
Abstract

Objectives: The time of death is increasingly postponed to a very high age. How this change affects the use of care services at the population level is unknown. This study analyses the care profiles of older people during their last 2 years of life, and investigates how these profiles differ for the study years 1996-1998 and 2011-2013., Design: Retrospective cross-sectional nationwide data drawn from the Care Register for Health Care, the Care Register for Social Care and the Causes of Death Register. The data included the use of hospital and long-term care services during the last 2 years of life for all those who died in 1998 and in 2013 at the age of ≥70 years in Finland., Methods: We constructed four care profiles using two criteria: (1) number of days in round-the-clock care (vs at home) in the last 2 years of life and (2) care transitions during the last 6 months of life (ie, end-of-life care transitions)., Results: Between the study periods, the average age at death and the number of diagnoses increased. Most older people (1998: 64.3%, 2013: 59.3%) lived at home until their last months of life (profile 2) after which they moved into hospital or long-term care facilities. This profile became less common and the profiles with a high use of care services became more common (profiles 3 and 4 together in 1998: 25.0%, in 2013: 30.9%). People with dementia, women and the oldest old were over-represented in the latter profiles. In both study periods, fewer than one in ten stayed at home for the whole last 6 months (profile 1)., Conclusions: Postponement of death to a very old age may translate into more severe disability in the last months or years of life. Care systems must be prepared for longer periods of long-term care services needed at the end of life., Competing Interests: Competing interests: None declared., (© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.)

Published
2017
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