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Genetic variation in healthy oldest-old.

ABSTRACT: Individuals who live to 85 and beyond without developing major age-related diseases may achieve this, in part, by lacking disease susceptibility factors, or by possessing resistance factors that enhance their ability to avoid disease and prolong lifespan. Healthy aging is a complex phenotype likely to be affected by both genetic and environmental factors. We sequenced 24 candidate healthy aging genes in DNA samples from 47 healthy individuals aged eighty-five years or older (the 'oldest-old'), to characterize genetic variation that is present in this exceptional group. These healthy seniors were never diagnosed with cancer, cardiovascular disease, pulmonary disease, diabetes, or Alzheimer disease. We re-sequenced all exons, intron-exon boundaries and selected conserved non-coding sequences of candidate genes involved in aging-related processes, including dietary restriction (PPARG, PPARGC1A, SIRT1, SIRT3, UCP2, UCP3), metabolism (IGF1R, APOB, SCD), autophagy (BECN1, FRAP1), stem cell activation (NOTCH1, DLL1), tumor suppression (TP53, CDKN2A, ING1), DNA methylation (TRDMT1, DNMT3A, DNMT3B) Progeria syndromes (LMNA, ZMPSTE24, KL) and stress response (CRYAB, HSPB2). We detected 935 variants, including 848 single nucleotide polymorphisms (SNPs) and 87 insertion or deletions; 41% (385) were not recorded in dbSNP. This study is the first to present a comprehensive analysis of genetic variation in aging-related candidate genes in healthy oldest-old. These variants and especially our novel polymorphisms are valuable resources to test for genetic association in models of disease susceptibility or resistance. In addition, we propose an innovative tagSNP selection strategy that combines variants identified through gene re-sequencing- and HapMap-derived SNPs.

SUBMITTER: Halaschek-Wiener J

PROVIDER: S-EPMC2722017 | biostudies-literature | 2009 Aug

REPOSITORIES: biostudies-literature

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Genetic variation in healthy oldest-old.

Halaschek-Wiener Julius J Amirabbasi-Beik Mahsa M Monfared Nasim N Pieczyk Markus M Sailer Christian C Kollar Anita A Thomas Ruth R Agalaridis Georgios G Yamada So S Oliveira Lisa L Collins Jennifer A JA Meneilly Graydon G Marra Marco A MA Madden Kenneth M KM Le Nhu D ND Connors Joseph M JM Brooks-Wilson Angela R AR

PloS one 20090814 8

Individuals who live to 85 and beyond without developing major age-related diseases may achieve this, in part, by lacking disease susceptibility factors, or by possessing resistance factors that enhance their ability to avoid disease and prolong lifespan. Healthy aging is a complex phenotype likely to be affected by both genetic and environmental factors. We sequenced 24 candidate healthy aging genes in DNA samples from 47 healthy individuals aged eighty-five years or older (the 'oldest-old'), t ...[more]

PMID: 19680556

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Project description:BackgroundIn oldest-old patients (>80), few trials showed efficacy of treating hypertension and they included mostly the healthiest elderly. The resulting lack of knowledge has led to inconsistent guidelines, mainly based on systolic blood pressure (SBP), cardiovascular disease (CVD) but not on frailty despite the high prevalence in oldest-old. This may lead to variation how General Practitioners (GPs) treat hypertension. Our aim was to investigate treatment variation of GPs in oldest-olds across countries and to identify the role of frailty in that decision.MethodsUsing a survey, we compared treatment decisions in cases of oldest-old varying in SBP, CVD, and frailty. GPs were asked if they would start antihypertensive treatment in each case. In 2016, we invited GPs in Europe, Brazil, Israel, and New Zealand. We compared the percentage of cases that would be treated per countries. A logistic mixed-effects model was used to derive odds ratio (OR) for frailty with 95% confidence intervals (CI), adjusted for SBP, CVD, and GP characteristics (sex, location and prevalence of oldest-old per GP office, and years of experience). The mixed-effects model was used to account for the multiple assessments per GP.ResultsThe 29 countries yielded 2543 participating GPs: 52% were female, 51% located in a city, 71% reported a high prevalence of oldest-old in their offices, 38% and had >20 years of experience. Across countries, considerable variation was found in the decision to start antihypertensive treatment in the oldest-old ranging from 34 to 88%. In 24/29 (83%) countries, frailty was associated with GPs' decision not to start treatment even after adjustment for SBP, CVD, and GP characteristics (OR 0.53, 95%CI 0.48-0.59; ORs per country 0.11-1.78).ConclusionsAcross countries, we found considerable variation in starting antihypertensive medication in oldest-old. The frail oldest-old had an odds ratio of 0.53 of receiving antihypertensive treatment. Future hypertension trials should also include frail patients to acquire evidence on the efficacy of antihypertensive treatment in oldest-old patients with frailty, with the aim to get evidence-based data for clinical decision-making.

Project description:Introduction:Frailty has been studied among the old population due to its association with negative outcomes. Presently there is no gold standard for measuring frailty, but several studies have used the frailty phenotype of Fried consisting of five components (weakness, slowness, unintentional weight loss, exhaustion, and low physical activity) that classify individuals as robust, pre-frail, or frail, depending on the number of components affected, respectively, zero, one or two, and three or more. This study aims to explore the specific contribution of each of these components to the frailty phenotype in a sample of oldest old community-dwelling individuals. Materials and Methods:Individuals aged 80+ years old living in the community (N = 142) participated in this study. Sociodemographic data (age, sex, educational level, and marital status) and Fried's frailty phenotype were collected. Descriptive analysis summarized sociodemographic information and the frailty components. Multiple correspondence analysis (MCA) was performed to detect and explore relationships between frailty's five components. Results:Participants had a mean age of 88.07 years (SD = 5.30 years) and were mainly women (73.9%). The majority of the sample were considered frail (71.8%) and pre-frail (24.7%), and the most recurrent component for both groups was slowness. From the MCA analysis, a two-dimension solution was considered the most adequate, with 53.47% of variance explained. Dimension 1 (32.21% of variance explained) showed weakness as the most discriminant component; dimension 2 (21.26% of variance explained) showed unintentional weight loss as the most discriminant component. Discussion:Results revealed a high number of pre-frail and frail participants. MCA proved to add an important understanding in examining the frailty phenotype; it revealed weakness as the most discriminant component for dimension 1, suggesting a high association with the frailty phenotype. MCA also identified two main features of frailty: one related with physical features (motor behavioral and grip strength) including weakness, low physical activity, and slowness; and the second related with intrinsic conditions (unintentional weight loss and exhaustion). Conclusion:This study corroborates the need of a differentiated approach to the frailty phenotype among very old individuals, bringing for consideration the specific influence of its components.

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Genetic variation in healthy oldest-old.

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Genetic variation in healthy oldest-old.

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