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Cognitive decline is a feared aspect of growing old. It is a major contributor to lower quality of life and loss of independence in old age. We investigated the genetic contribution to individual differences in nonpathological cognitive ageing in five cohorts of older adults. We undertook a genome-wide association analysis using 549 692 single-nucleotide polymorphisms (SNPs) in 3511 unrelated adults in the Cognitive Ageing Genetics in England and Scotland (CAGES) project. These individuals have detailed longitudinal cognitive data from which phenotypes measuring each individual's cognitive changes were constructed. One SNP--rs2075650, located in TOMM40 (translocase of the outer mitochondrial membrane 40 homolog)--had a genome-wide significant association with cognitive ageing (P=2.5 × 10(-8)). This result was replicated in a meta-analysis of three independent Swedish cohorts (P=2.41 × 10(-6)). An Apolipoprotein E (APOE) haplotype (adjacent to TOMM40), previously associated with cognitive ageing, had a significant effect on cognitive ageing in the CAGES sample (P=2.18 × 10(-8); females, P=1.66 × 10(-11); males, P=0.01). Fine SNP mapping of the TOMM40/APOE region identified both APOE (rs429358; P=3.66 × 10(-11)) and TOMM40 (rs11556505; P=2.45 × 10(-8)) as loci that were associated with cognitive ageing. Imputation and conditional analyses in the discovery and replication cohorts strongly suggest that this effect is due to APOE (rs429358). Functional genomic analysis indicated that SNPs in the TOMM40/APOE region have a functional, regulatory non-protein-coding effect. The APOE region is significantly associated with nonpathological cognitive ageing. The identity and mechanism of one or multiple causal variants remain unclear.

Background: Falls risk in older people is multifactorial and complex. There is uncertainty about the importance of specific risk factors. Genetic algorithm neural networks (GANNs) can examine all available data and select the best nonlinear combination of variables for predicting falls. The aim of this work was to develop a risk profile for operationally defined new falls in a random sample of older people by use of a GANN approach., Methods: A random sample of 1042 community-dwelling people aged 65 and older, living in Nottingham, England, were interviewed at baseline (1985) and survivors reinterviewed at a 4-year follow-up (n = 690). The at-risk group (n = 435) was defined as those survivors who had not fallen in the year before the baseline interview. A GANN was used to examine all available attributes and, from these, to select the best nonlinear combination of variables that predicted those people who fell 4 years later., Results: The GANN selected a combination of 16 from a potential 253 variables and correctly predicted 35/114 new fallers (sensitivity = 31%; positive predictive value = 57%) and 295/321 nonfallers (specificity = 92%; negative predictive value = 79%); total correct = 76%. The variables selected by the GANN related to personal health, opportunity, and personal circumstances., Conclusions: This study demonstrates the capacity of GANNs to examine all available data and then to identify the best 16 variables for predicting falls. The risk profile complements risk factors in the current literature identified by use of standard and conventional statistical methods. Additional data about environmental factors might enhance the sensitivity of the GANN approach and help identify those older people who are at risk of falling.

It is commonly believed that patients admitted to hospital from nursing homes/residential homes (NHRH) with infections are less likely to respond to treatment and have a higher fatality rate than counterparts admitted from their own homes ('the Community'). It is also believed that NHRH's harbour a reservoir of unusual and resistant organisms. These preconceptions may influence how these patients are managed. A database of 10593 sequential admissions to a Geriatric Medical unit over a three-year period was used to identify NHRH and community populations with a principal diagnosis of infection. They were investigated using the Department of Microbiology's database. The admission rate in the NHRH group was twice that of the community group. There were no significant differences in length of stay (LOS) [16 +/- 2 vs 17 +/- 2 days (s.e.m.)], or mean survival time (ST)(61 days (37-84) vs 48 days (25-72): 95% confidence intervals) between the two groups. Subgroups of the NHRH group did have significantly different survival times. Fatality rate was not significantly different between the NHRH (40%) or Community (35%) groups. Both the NHRH and community group underwent very similar levels of investigation (189 vs 200 investigations performed). The types and frequencies of pathogen seen in the two groups were very similar.