Predictors of placebo group decline in the Alzheimer's disease Assessment Scale-cognitive subscale (ADAS-Cog) in 24 week clinical trials of Alzheimer's disease.

One limitation of several recent 24 week Alzheimer's disease (AD) clinical trials was the lack of cognitive decline detected by the AD Assessment Scale-cognitive subscale (ADAS-cog) in the placebo groups, possibly obscuring true medication effects. Data from 733 individuals in the placebo arms of six AD clinical trials performed 1996-1997 were pooled to examine the relationship of clinical, demographic, and genetic characteristics with the 24 week change in ADAS-cog. Baseline cognitive and functional status and the screening-to-baseline change in ADAS-cog were the strongest independent predictors of the 24 week change in ADAS-cog. The ADAS-cog did not detect progression in patients with mild dementia (screening Mini-Mental State Exam, MMSE, >or=20). The change in ADAS-cog from screening to baseline was inversely correlated with the 24 week change score; it was more difficult to detect cognitive decline at 24 weeks if individuals markedly worsened from screening to baseline. The effects of baseline MMSE and screening-to-baseline change in ADAS-cog generalized to the placebo group (N=106) of another AD study performed in 2004-2005. Overcoming lack of placebo decline in AD clinical trials will require scales more sensitive to cognitive decline in mild AD and strategies to reduce within-person variability in outcome measures.

Partnership between academia and industry for drug discovery in Alzheimer's disease.

Drug discovery has traditionally been almost exclusively the purview of pharmaceutical and biotechnology companies, whereas universities have focused on basic research. However, given the challenges involved in discovering and developing truly effective, symptomatic treatments and disease-modifying drugs for Alzheimer's disease, there is a need to reassess this simple division of labor. Whereas each sector is likely to retain a core interest and expertise at either end of the drug discovery spectrum, there is room for closer cooperation at the intersection of the for-profit and not-for-profit sectors. The Alzheimer's Association Research Roundtable convened a meeting of senior industry researchers and academic investigators to discuss this intersection and to assess the opportunity for closer partnership on Alzheimer's disease drug discovery and development.

An assessment of the Irish population for large-scale genetic mapping studies involving epilepsy and other complex diseases.

The recent completion of the International HapMap Project has rapidly advanced our understanding of linkage disequilibrium (LD) in the human genome. Today, tagging SNPs (tSNPs) can be quickly and easily selected and consequently HapMap data are regularly applied to both small- and large-scale genetic mapping studies. However, to correctly interpret the application of HapMap-derived tSNPs in a genetic mapping study, an understanding of how well HapMap data represents LD in the study population is critical. The Irish population had not previously been characterised in this way. Here, we do so using a set of 4424 SNPs selected from 279 candidate genes for epilepsy genotyped across 1118 healthy individuals from the Irish, British, Finnish and Australian populations. By considering the Irish population alongside surrounding European populations, our results confirm that the HapMap European-derived population accurately estimates patterning of LD in European descent populations. The Irish population appears notably well matched to the European HapMap population, and is markedly similar to the neighbouring British population. Although we were unable to detect significant substructure within the Irish population (a favourable result for genetic mapping), methods for controlling stratification should always be incorporated. This analysis therefore confirms that the genetic architecture of the Irish population is well suited to the study of complex traits and that tSNPs selected using the HapMap data can be confidently applied to the Irish population.