Distinguishing anticipation from causality: anticipatory bias in the estimation of information flow.

We report that transfer entropy estimates obtained from low-resolution and/or small data sets show net information flow away from a purely anticipatory element whereas transfer entropy calculated using exact distributions show the flow towards it. This means that for real-world data sets anticipatory elements can appear to be strongly driving the network dynamics even when there is no possibility of such an influence. Furthermore, we show that in the low-resolution limit there is no statistic that can distinguish anticipatory elements from causal ones.

Combinatorial Mismatch Scan (CMS) for loci associated with dementia in the Amish.

BACKGROUND: Population heterogeneity may be a significant confounding factor hampering detection and verification of late onset Alzheimer's disease (LOAD) susceptibility genes. The Amish communities located in Indiana and Ohio are relatively isolated populations that may have increased power to detect disease susceptibility genes. METHODS: We recently performed a genome scan of dementia in this population that detected several potential loci. However, analyses of these data are complicated by the highly consanguineous nature of these Amish pedigrees. Therefore we applied the Combinatorial Mismatch Scanning (CMS) method that compares identity by state (IBS) (under the presumption of identity by descent (IBD)) sharing in distantly related individuals from such populations where standard linkage and association analyses are difficult to implement. CMS compares allele sharing between individuals in affected and unaffected groups from founder populations. Comparisons between cases and controls were done using two Fisher's exact tests, one testing for excess in IBS allele frequency and the other testing for excess in IBS genotype frequency for 407 microsatellite markers. RESULTS: In all, 13 dementia cases and 14 normal controls were identified who were not related at least through the grandparental generation. The examination of allele frequencies identified 24 markers (6%) nominally (p < or = 0.05) associated with dementia; the most interesting (empiric p < or = 0.005) markers were D3S1262, D5S211, and D19S1165. The examination of genotype frequencies identified 21 markers (5%) nominally (p < or = 0.05) associated with dementia; the most significant markers were both located on chromosome 5 (D5S1480 and D5S211). Notably, one of these markers (D5S211) demonstrated differences (empiric p < or = 0.005) under both tests. CONCLUSION: Our results provide the initial groundwork for identifying genes involved in late-onset Alzheimer's disease within the Amish community. Genes identified within this isolated population will likely play a role in a subset of late-onset AD cases across more general populations. Regions highlighted by markers demonstrating suggestive allelic and/or genotypic differences will be the focus of more detailed examination to characterize their involvement in dementia.

A genome-wide linkage analysis of dementia in the Amish.

Susceptibility genes for Alzheimer's disease are proving to be highly challenging to detect and verify. Population heterogeneity may be a significant confounding factor contributing to this difficulty. To increase the power for disease susceptibility gene detection, we conducted a genome-wide genetic linkage screen using individuals from the relatively isolated, genetically homogeneous, Amish population. Our genome linkage analysis used a 407-microsatellite-marker map (average density 7 cM) to search for autosomal genes linked to dementia in five Amish families from four Midwestern U.S. counties. Our highest two-point lod score (3.01) was observed at marker D4S1548 on chromosome 4q31. Five other regions (10q22, 3q28, 11p13, 4q28, 19p13) also demonstrated suggestive linkage with markers having two-point lod scores >2.0. While two of these regions are novel (4q31 and 11p13), the other regions lie close to regions identified in previous genome scans in other populations. Our results identify regions of the genome that may harbor genes involved in a subset of dementia patients, in particular the North American Amish community.