Walter, S.

Determinants of Healthy Aeging: Studies of Disability and Survival among the Elderly (Doctoral Thesis)

2012-01-18T00:00:00Z

The increase in life expectancy over the last century is one of society’s major achievements. In particular in developed countries, though increasingly in developing countries, a higher life expectancy and a reduction in birth rates result in an ageing of the population, i.e. the shift of the median age in the population towards older ages. Thus, while human population growth approximates 1.2% annually, this population growth is not constant across all ages. Annually, the population older than 60 increases by 2 – 3%, while the population older than 80 increases by 4%. By 2050, more than one third of all Europeans are expected to be older than 60 years.[1] These demographic trends are supported by evidence showing that the recent increases in life expectancy in Western countries can mainly be attributed to better survival among the elderly. Ageing of the population poses a challenge for both developed and developing countries. The goal of this thesis is to identify risk factors for disability, disease-free survival, mortality and longevity. Specifically we asked the following research questions: 1. What genetic loci are associated with longevity and time to death and disease? (Chapter 2) 2. Do body mass index, physical activity, and happiness influence time to death and time spent with disability? (Chapter 3) 3. Which set of risk factors best predicts death and how do different groups of risk factors compare in their predictive power? (Chapter 4)

A genome-wide association study of aging (Article)

2011-11-01T00:00:00Z

Human longevity and healthy aging show moderate heritability (20%-50%). We conducted a meta-analysis of genome-wide association studies from 9 studies from the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium for 2 outcomes: (1) all-cause mortality, and (2) survival free of major disease or death. No single nucleotide polymorphism (SNP) was a genome-wide significant predictor of either outcome (p < 5 × 10-8). We found 14 independent SNPs that predicted risk of death, and 8 SNPs that predicted event-free survival (p < 10-5). These SNPs are in or near genes that are highly expressed in the brain (HECW2, HIP1, BIN2, GRIA1), genes involved in neural development and function (KCNQ4, LMO4, GRIA1, NETO1) and autophagy (ATG4C), and genes that are associated with risk of various diseases including cancer and Alzheimer's disease. In addition to considerable overlap between the traits, pathway and network analysis corroborated these findings. These findings indicate that variation in genes involved in neurological processes may be an important factor in regulating aging free of major disease and achieving longevity.

Genome-wide association analysis of coffee drinking suggests association with CYP1A1/CYP1A2 and NRCAM (Article)

2011-08-30T00:00:00Z

Coffee consumption is a model for addictive behavior. We performed a meta-analysis of genome-wide association studies (GWASs) on coffee intake from 8 Caucasian cohorts (N=18 176) and sought replication of our top findings in a further 7929 individuals. We also performed a gene expression analysis treating different cell lines with caffeine. Genome-wide significant association was observed for two single-nucleotide polymorphisms (SNPs) in the 15q24 region. The two SNPs rs2470893 and rs2472297 (P-values=1.6 × 10-11and 2.7 × 10-11), which were also in strong linkage disequilibrium (r2=0.7) with each other, lie in the 23-kb long commonly shared 5′ flanking region between CYP1A1 and CYP1A2 genes. CYP1A1 was found to be downregulated in lymphoblastoid cell lines treated with caffeine. CYP1A1 is known to metabolize polycyclic aromatic hydrocarbons, which are important constituents of coffee, whereas CYP1A2 is involved in the primary metabolism of caffeine. Significant evidence of association was also detected at rs382140 (P-value=3.9 × 10-09) near NRCAM-a gene implicated in vulnerability to addiction, and at another independent hit rs6495122 (P-value=7.1 × 10-09)-an SNP associated with blood pressure-in the 15q24 region near the gene ULK3, in the meta-analysis of discovery and replication cohorts. Our results from GWASs and expression analysis also strongly implicate CAB39L in coffee drinking. Pathway analysis of differentially expressed genes revealed significantly enriched ubiquitin proteasome (P-value=2.2 × 10-05) and Parkinson's disease pathways (P-value=3.6 × 10-05).Molecular Psychiatry advance online publication, 30 August 2011; doi:10.1038/mp.2011.101.

Is positive affect associated with survival? a population-based study of elderly persons (Article)

2011-06-06T00:00:00Z

Study results on the association of positive affect with survival are conflicting. This disagreement potentially arises from poor control for health or negative affect and for the various age groups studied. The authors examined if positive affect predicts survival; whether this association is preserved after controlling for negative affect, socioeconomic status, lifestyle, and health; and whether this association varies with age. The study is set within the population-based Rotterdam Study (1997-2007) and included 4,411 participants aged 61 years or older, followed for on average 7.19 (standard deviation = 2.20) years. Positive affect was not consistently associated with survival across all ages. A significant interaction of positive affect with age on survival (P = 0.02) was found. Subsequent age stratification revealed that positive affect independently predicted survival in elderly persons aged <80 years (per affect score, hazard ratio = 0.96, 95% confidence interval: 0.93, 0.99) but not in those aged ≥80 years in fully adjusted models (hazard ratio = 1.00, 95% confidence interval: 0.96, 1.04). In the oldest old, the association was partly explained by differences in baseline health. In conclusion, the results suggest that there may be an association of positive affect with survival in the younger and middle old but not in the oldest old in whom perception of positive affect is more likely to be determined by health.

Sequence variants at CHRNB3-CHRNA6 and CYP2A6 affect smoking behavior (Article)

2010-05-01T00:00:00Z

Smoking is a common risk factor for many diseases1. We conducted genome-wide association meta-analyses for the number of cigarettes smoked per day (CPD) in smokers (n = 31,266) and smoking initiation (n = 46,481) using samples from the ENGAGE Consortium. In a second stage, we tested selected SNPs with in silico replication in the Tobacco and Genetics (TAG) and Glaxo Smith Kline (Ox-GSK) consortia cohorts (n = 45,691 smokers) and assessed some of those in a third sample of European ancestry (n = 9,040). Variants in three genomic regions associated with CPD (P 5 × 108), including previously identified SNPs at 15q25 represented by rs1051730[A] (effect size = 0.80 CPD, P = 2.4 × 1069), and SNPs at 19q13 and 8p11, represented by rs4105144[C] (effect size = 0.39 CPD, P = 2.2 × 1012) and rs6474412-T (effect size = 0.29 CPD, P = 1.4 × 108), respectively. Among the genes at the two newly associated loci are genes encoding nicotine-metabolizing enzymes (CYP2A6 and CYP2B6) and nicotinic acetylcholine receptor subunits (CHRNB3 and CHRNA6), all of which have been highlighted in previous studies of smoking and nicotine dependence. Nominal associations with lung cancer were observed at both 8p11 (rs6474412[T], odds ratio (OR) = 1.09, P = 0.04) and 19q13 (rs4105144[C], OR = 1.12, P = 0.0006).

A Meta-analysis of four genome-wide association studies of survival to age 90 years or older: The cohorts for heart and aging research in genomic epidemiology consortium (Article)

2010-05-01T00:00:00Z

Background.Genome-wide association studies (GWAS) may yield insights into longevity.Methods.We performed a meta-analysis of GWAS in Caucasians from four prospective cohort studies: the Age, Gene/Environment Susceptibility-Reykjavik Study, the Cardiovascular Health Study, the Framingham Heart Study, and the Rotterdam Study participating in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. Longevity was defined as survival to age 90 years or older (n = 1,836); the comparison group comprised cohort members who died between the ages of 55 and 80 years (n = 1,955). In a second discovery stage, additional genotyping was conducted in the Leiden Longevity Study cohort and the Danish 1905 cohort.Results.There were 273 single-nucleotide polymorphism (SNP) associations with p <. 0001, but none reached the prespecified significance level of 5 × 10-8. Of the most significant SNPs, 24 were independent signals, and 16 of these SNPs were successfully genotyped in the second discovery stage, with one association for rs9664222, reaching 6.77 × 10-7for the combined meta-analysis of CHARGE and the stage 2 cohorts. The SNP lies in a region near MINPP1 (chromosome 10), a well-conserved gene involved in regulation of cellular proliferation. The minor allele was associated with lower odds of survival past age 90 (odds ratio = 0.82). Associations of interest in a homologue of the longevity assurance gene (LASS3) and PAPPA2 were not strengthened in the second stage.Conclusion.Survival studies of larger size or more extreme or specific phenotypes may support or refine these initial findings.

Genome-wide meta-analyses identify multiple loci associated with smoking behavior (Article)

2010-05-01T00:00:00Z

Consistent but indirect evidence has implicated genetic factors in smoking behavior. We report meta-analyses of several smoking phenotypes within cohorts of the Tobacco and Genetics Consortium (n = 74,053). We also partnered with the European Network of Genetic and Genomic Epidemiology (ENGAGE) and Oxford-GlaxoSmithKline (Ox-GSK) consortia to follow up the 15 most significant regions (n 140,000). We identified three loci associated with number of cigarettes smoked per day. The strongest association was a synonymous 15q25 SNP in the nicotinic receptor gene CHRNA3 (rs1051730[A], Β = 1.03, standard error (s.e.) = 0.053, P = 2.8 × 10 73). Two 10q25 SNPs (rs1329650[G], Β = 0.367, s.e. = 0.059, P = 5.7 × 10 10; and rs1028936[A], Β = 0.446, s.e. = 0.074, P = 1.3 × 10 9) and one 9q13 SNP in EGLN2 (rs3733829[G], Β = 0.333, s.e. = 0.058, P = 1.0 × 10 8) also exceeded genome-wide significance for cigarettes per day. For smoking initiation, eight SNPs exceeded genome-wide significance, with the strongest association at a nonsynonymous SNP in BDNF on chromosome 11 (rs6265[C], odds ratio (OR) = 1.06, 95% confidence interval (Cl) 1.04-1.08, P = 1.8 × 10 8). One SNP located near DBH on chromosome 9 (rs3025343[G], OR = 1.12, 95% Cl 1.08-1.18, P = 3.6 × 10 8) was significantly associated with smoking cessation.

Variable selection: Current practice in epidemiological studies (Article)

2009-12-01T00:00:00Z

Selection of covariates is among the most controversial and difficult tasks in epidemiologic analysis. Correct variable selection addresses the problem of confounding in etiologic research and allows unbiased estimation of probabilities in prognostic studies. The aim of this commentary is to assess how often different variable selection techniques were applied in contemporary epidemiologic analysis. It was of particular interest to see whether modern methods such as shrinkage or penalized regression were used in recent publications. Stepwise selection methods remained the predominant method for variable selection in publications in epidemiological journals in 2008. Shrinkage methods were not used in any of the reviewed articles. Editors, reviewers and authors have insufficiently promoted the new, less controversial approaches of variable selection in the biomedical literature, whereas statisticians may not have adequately addressed the method's feasibility.