Age, gender, and cancer but not neurodegenerative and cardiovascular diseases strongly modulate systemic effect of the Apolipoprotein E4 allele on lifespan

Enduring interest in the Apolipoprotein E (ApoE) polymorphism is ensured by its evolutionary-driven uniqueness in humans and its prominent role in geriatrics and gerontology. We use large samples of longitudinally followed populations from the Framingham Heart Study (FHS) original and offspring cohorts and the Long Life Family Study (LLFS) to investigate gender-specific effects of the ApoE4 allele on human survival in a wide range of ages from midlife to extreme old ages, and the sensitivity of these effects to cardiovascular disease (CVD), cancer, and neurodegenerative disorders (ND). The analyses show that women's lifespan is more sensitive to the e4 allele than men's in all these populations. A highly significant adverse effect of the e4 allele is limited to women with moderate lifespan of about 70 to 95 years in two FHS cohorts and the LLFS with relative risk of death RR = 1.48 (p = 3.6×10(−6)) in the FHS cohorts. Major human diseases including CVD, ND, and cancer, whose risks can be sensitive to the e4 allele, do not mediate the association of this allele with lifespan in large FHS samples. Non-skin cancer non-additively increases mortality of the FHS women with moderate lifespans increasing the risks of death of the e4 carriers with cancer two-fold compared to the non-e4 carriers, i.e., RR = 2.07 (p = 5.0×10(−7)). The results suggest a pivotal role of non-sex-specific cancer as a nonlinear modulator of survival in this sample that increases the risk of death of the ApoE4 carriers by 150% (p = 5.3×10(−8)) compared to the non-carriers. This risk explains the 4.2 year shorter life expectancy of the e4 carriers compared to the non-carriers in this sample. The analyses suggest the existence of age- and gender-sensitive systemic mechanisms linking the e4 allele to lifespan which can non-additively interfere with cancer-related mechanisms

A standard procedure for creating a frailty index

<p>Abstract</p> <p>Background</p> <p>Frailty can be measured in relation to the accumulation of deficits using a frailty index. A frailty index can be developed from most ageing databases. Our objective is to systematically describe a standard procedure for constructing a frailty index.</p> <p>Methods</p> <p>This is a secondary analysis of the Yale Precipitating Events Project cohort study, based in New Haven CT. Non-disabled people aged 70 years or older (n = 754) were enrolled and re-contacted every 18 months. The database includes variables on function, cognition, co-morbidity, health attitudes and practices and physical performance measures. Data came from the baseline cohort and those available at the first 18-month follow-up assessment.</p> <p>Results</p> <p>Procedures for selecting health variables as candidate deficits were applied to yield 40 deficits. Recoding procedures were applied for categorical, ordinal and interval variables such that they could be mapped to the interval 0–1, where 0 = absence of a deficit, and 1= full expression of the deficit. These individual deficit scores were combined in an index, where 0= no deficit present, and 1= all 40 deficits present. The values of the index were well fit by a gamma distribution. Between the baseline and follow-up cohorts, the age-related slope of deficit accumulation increased from 0.020 (95% confidence interval, 0.014–0.026) to 0.026 (0.020–0.032). The 99% limit to deficit accumulation was 0.6 in the baseline cohort and 0.7 in the follow-up cohort. Multivariate Cox analysis showed the frailty index, age and sex to be significant predictors of mortality.</p> <p>Conclusion</p> <p>A systematic process for creating a frailty index, which relates deficit accumulation to the individual risk of death, showed reproducible properties in the Yale Precipitating Events Project cohort study. This method of quantifying frailty can aid our understanding of frailty-related health characteristics in older adults.</p

The frailty index outperforms DNA methylation age and its derivatives as an indicator of biological age

The measurement of biological age as opposed to chronological age is important to allow the study of factors that are responsible for the heterogeneity in the decline in health and function ability among individuals during aging. Various measures of biological aging have been proposed. Frailty indices based on health deficits in diverse body systems have been well studied, and we have documented the use of a frailty index (FI(34)) composed of 34 health items, for measuring biological age. A different approach is based on leukocyte DNA methylation. It has been termed DNA methylation age, and derivatives of this metric called age acceleration difference and age acceleration residual have also been employed. Any useful measure of biological age must predict survival better than chronological age does. Meta-analyses indicate that age acceleration difference and age acceleration residual are significant predictors of mortality, qualifying them as indicators of biological age. In this article, we compared the measures based on DNA methylation with FI(34). Using a well-studied cohort, we assessed the efficiency of these measures side by side in predicting mortality. In the presence of chronological age as a covariate, FI(34) was a significant predictor of mortality, whereas none of the DNA methylation age-based metrics were. The outperformance of FI(34) over DNA methylation age measures was apparent when FI(34) and each of the DNA methylation age measures were used together as explanatory variables, along with chronological age: FI(34) remained significant but the DNA methylation measures did not. These results indicate that FI(34) is a robust predictor of biological age, while these DNA methylation measures are largely a statistical reflection of the passage of chronological time

Indicators of "Healthy Aging" in older women (65-69 years of age). A data-mining approach based on prediction of long-term survival

<p>Abstract</p> <p>Background</p> <p>Prediction of long-term survival in healthy adults requires recognition of features that serve as early indicators of successful aging. The aims of this study were to identify predictors of long-term survival in older women and to develop a multivariable model based upon longitudinal data from the Study of Osteoporotic Fractures (SOF).</p> <p>Methods</p> <p>We considered only the youngest subjects (<it>n </it>= 4,097) enrolled in the SOF cohort (65 to 69 years of age) and excluded older SOF subjects more likely to exhibit a "frail" phenotype. A total of 377 phenotypic measures were screened to determine which were of most value for prediction of long-term (19-year) survival. Prognostic capacity of individual predictors, and combinations of predictors, was evaluated using a cross-validation criterion with prediction accuracy assessed according to time-specific AUC statistics.</p> <p>Results</p> <p>Visual contrast sensitivity score was among the top 5 individual predictors relative to all 377 variables evaluated (mean AUC = 0.570). A 13-variable model with strong predictive performance was generated using a forward search strategy (mean AUC = 0.673). Variables within this model included a measure of physical function, smoking and diabetes status, self-reported health, contrast sensitivity, and functional status indices reflecting cumulative number of daily living impairments (HR ≥ 0.879 or RH ≤ 1.131; P < 0.001). We evaluated this model and show that it predicts long-term survival among subjects assigned differing causes of death (e.g., cancer, cardiovascular disease; P < 0.01). For an average follow-up time of 20 years, output from the model was associated with multiple outcomes among survivors, such as tests of cognitive function, geriatric depression, number of daily living impairments and grip strength (P < 0.03).</p> <p>Conclusions</p> <p>The multivariate model we developed characterizes a "healthy aging" phenotype based upon an integration of measures that together reflect multiple dimensions of an aging adult (65-69 years of age). Age-sensitive components of this model may be of value as biomarkers in human studies that evaluate anti-aging interventions. Our methodology could be applied to data from other longitudinal cohorts to generalize these findings, identify additional predictors of long-term survival, and to further develop the "healthy aging" concept.</p

Frailty in primary care: a review of its conceptualization and implications for practice

Frail, older patients pose a challenge to the primary care physician who may often feel overwhelmed by their complex presentation and tenuous health status. At the same time, family physicians are ideally suited to incorporate the concept of frailty into their practice. They have the propensity and skill set that lends itself to patient-centred care, taking into account the individual subtleties of the patient's health within their social context. Tools to identify frailty in the primary care setting are still in the preliminary stages of development. Even so, some practical measures can be taken to recognize frailty in clinical practice and begin to address how its recognition may impact clinical care. This review seeks to address how frailty is recognised and managed, especially in the realm of primary care

A common polymorphism of the human cardiac sodium channel alpha subunit (SCN5A) gene is associated with sudden cardiac death in chronic ischemic heart disease

Cardiac death remains one of the leading causes of mortality worldwide. Recent research has shed light on pathophysiological mechanisms underlying cardiac death, and several genetic variants in novel candidate genes have been identified as risk factors. However, the vast majority of studies performed so far investigated genetic associations with specific forms of cardiac death only (sudden, arrhythmogenic, ischemic etc.). The aim of the present investigation was to find a genetic marker that can be used as a general, powerful predictor of cardiac death risk. To this end, a case-control association study was performed on a heterogeneous cohort of cardiac death victims (n=360) and age-matched controls (n=300). Five single nucleotide polymorphisms (SNPs) from five candidate genes (beta2 adrenergic receptor, nitric oxide synthase 1 adaptor protein, ryanodine receptor 2, sodium channel type V alpha subunit and transforming growth factor-beta receptor 2) that had previously been shown to associate with certain forms of cardiac death were genotyped using sequence-specific real-time PCR probes. Logistic regression analysis revealed that the CC genotype of the rs11720524 polymorphism in the SCN5A gene encoding a subunit of the cardiac voltage-gated sodium channel occurred more frequently in the highly heterogeneous cardiac death cohort compared to the control population (p=0.019, odds ratio: 1.351). A detailed subgroup analysis uncovered that this effect was due to an association of this variant with cardiac death in chronic ischemic heart disease (p=0.012, odds ratio =1.455). None of the other investigated polymorphisms showed association with cardiac death in this context. In conclusion, our results shed light on the role of this non-coding polymorphism in cardiac death in ischemic cardiomyopathy. Functional studies are needed to explore the pathophysiological background of this association. © 2015 Marcsa et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited