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PubMed2005

Large recursive partitioning analysis of complex disease pharmacogenetic studies. II. Statistical considerations.

Identifying genetic variations predictive of important phenotypes, such as disease susceptibility, drug efficacy, and adverse events, remains a challenging task. There are individual polymorphisms that can be tested one at a time, but there is the more difficult problem of the identification of combinations of polymorphisms or even more complex interactions of genes with environmental factors. Diseases, drug responses or side effects can result from different mechanisms. Identification of subgroups of people where there is a common mechanism is a problem for diagnosis and prescribing of treatment. Recursive partitioning (RP) is a simple statistical tool for segmenting a population into non-overlapping groups where the response of interest, disease susceptibility, drug efficacy and adverse events are more homogeneous within the segments. We suggest that the use of RP is not only more technically feasible than other search methods but it is less susceptible to multiple-testing problems. The numbers of combinations of gene-gene and gene-environment interactions is potentially astronomical and RP greatly reduces the effective search and inference space. Moreover, the certain reliance of RP on the presence of marginal effects is justifiable as was found by using analytical and numerical arguments. In the context of haplotype analysis, results suggest that the analysis of individual SNPs is likely to be successful even when susceptibilities are determined by haplotypes. Retrospective clinical studies where cases and controls are collected will be a common design. This report provides methods that can be used to adjust the RP analysis to reflect the population incidence of the response of interest. Confidence limits on the incidence of the response in the segmented subgroups are also discussed. RP is a straightforward way to create realistic subgroups, and prediction intervals for the within-subgroup disease incidence are easily obtained.

Biomedical Research↗
PubMedDate not supplied

High genetic diversity in Sarracenia leucophylla(Sarraceniaceae), a carnivorous wetland herb.

Eighteen allozyme loci were used to examine genetic diversity in 10 natural populations of Sarracenia leucophylla Raf., a pitcher plant restricted to the southeastern United States. One ex situ population propagated for restoration in Georgia was also analyzed. S. leucophylla is an insect-pollinated, outcrossing perennial wetland herb that is threatened over much of its geographic range. Fifteen loci (83.3%) were polymorphic, with a mean number of alleles of 3.33. Compared to species having similar life-history traits and to previously analyzed Sarracenia species, S. leucophylla displayed unexpectedly high genetic diversity. For example, genetic diversity within the species (Hes) was 0.224 and mean population genetic diversity (Hep) was 0.183. Although small S. leucophylla populations maintained less genetic diversity than larger ones, these differences were not statistically significant. Nonetheless, this suggests that small populations may have lost rare alleles. Statistically significant genetic differentiation among populations was found (theta = 0.192, P < .01), although it was not atypical considering the species' life-history characteristics. A significant correlation (P < .01) between genetic and geographic distance was found, indicating an isolation-by-distance effect. However, the correlation coefficient for this relationship was low (r = 0.46), suggesting that factors other than gene flow play a prominent role in the geographic distribution of genetic diversity within the species. The ex situ population captured most of the allozyme variation found in its source population.

Cluster Analysis↗
PubMed2003

Positional identification of microdeletions with genetic markers.

The positional identification of genetic factors for both simple and complex diseases is difficult. There is increasing evidence that small deletions are a fairly common cause for many genetic diseases and some complex diseases. To date, no statistical basis has been available for the identification of microdeletions in family studies. Here, we present an approach to the identification of novel microdeletions for parent-affected offspring trios. We present several different approaches that can be applied to identify microdeletions and also evaluate the statistical behavior of one of these methods in simulated data. The results show that for the study of single nucleotide polymorphisms, the error rate has an approximately linear effect in decreasing the ability to identify microdeletions. On the other hand, heterogeneity of causation, with only some families showing a microdeletion had a more severe influence upon the ability to identify de novo microdeletions.

Chromosome Mapping↗
PubMed1999

Statistical approaches for evaluation of genetic risk factor of peripheral arterial occlusive disease.

In the paper we show results of medical study from statistical point of view. The medical study was aimed to study genetic risk factors of peripheral arterial occlusive diseases in Czech population. Two genes, CBS and MTHFR were examined, as various genotypes of these genes are thought to have impact on amino thiols, who participate in variety of reactions in vasculature. Statistical part of the study was responsible for analysis and interpretation of collected data.

Adult↗
PubMed2001

The use of common genetic polymorphisms to enhance the epidemiologic study of environmental carcinogens.

Overwhelming evidence indicates that environmental exposures, broadly defined, are responsible for most cancer. There is reason to believe, however, that relatively common polymorphisms in a wide spectrum of genes may modify the effect of these exposures. We discuss the rationale for using common polymorphisms to enhance our understanding of how environmental exposures cause cancer and comment on epidemiologic strategies to assess these effects, including study design, genetic and statistical analysis, and sample size requirements. Special attention is given to sources of potential bias in population studies of gene--environment interactions, including exposure and genotype misclassification and population stratification (i.e., confounding by ethnicity). Nevertheless, by merging epidemiologic and molecular approaches in the twenty-first century, there will be enormous opportunities for unraveling the environmental determinants of cancer. In particular, studies of genetically susceptible subgroups may enable the detection of low levels of risk due to certain common exposures that have eluded traditional epidemiologic methods. Further, by identifying susceptibility genes and their pathways of action, it may be possible to identify previously unsuspected carcinogens. Finally, by gaining a more comprehensive understanding of environmental and genetic risk factors, there should emerge new clinical and public health strategies aimed at preventing and controlling cancer.

Animals↗
PubMed2005

Marine landscapes and population genetic structure of herring (Clupea harengus L.) in the Baltic Sea.

Numerically small but statistically significant genetic differentiation has been found in many marine fish species despite very large census population sizes and absence of obvious barriers to migrating individuals. Analyses of morphological traits have previously identified local spawning groups of herring (Clupea harengus L.) in the environmentally heterogeneous Baltic Sea, whereas allozyme markers have not revealed differentiation. We analysed variation at nine microsatellite loci in 24 samples of spring-spawning herring collected at 11 spawning locations throughout the Baltic Sea. Significant temporal differentiation was observed at two locations, which we ascribe to sympatrically spawning but genetically divergent 'spawning waves'. Significant differentiation was also present on a geographical scale, though pairwise F(ST) values were generally low, not exceeding 0.027. Partial Mantel tests showed no isolation by geographical distance, but significant associations were observed between genetic differentiation and environmental parameters (salinity and surface temperature) (0.001 < P < or = 0.099), though these outcomes were driven mainly by populations in the southwestern Baltic Sea, which also exhibits the steepest environmental gradients. Application of a novel method for detecting barriers to gene flow by combining geographical coordinates and genetic differentiation allowed us to identify two zones of lowered gene flow. These zones were concordant with the separation of the Baltic Sea into major basins, with environmental gradients and with differences in migration behaviour. We suggest that similar use of landscape genetics approaches may increase the understanding of the biological significance of genetic differentiation in other marine fishes.

Animals↗
PubMed2005

A non-iterative confidence interval estimating procedure for the intraclass kappa statistic with multinomial outcomes.

We obtain the asymptotic sample variance of the intraclass kappa statistic for multinomial outcome data. A modified Wald type procedure based on this theory is then used for confidence interval construction. The results of a simulation study show that the proposed non-iterative approach performs very well in terms of confidence interval coverage and width for samples as small as 50. The procedure is illustrated with two examples from previously published medical studies.

Carotid Stenosis↗
PubMed2006

Chromosome aberrations in solid tumors have a stochastic nature.

An important question nowadays is whether chromosome aberrations are random events or arise from an internal deterministic mechanism, which leads to the delicate task of quantifying the degree of randomness. For this purpose, we have defined several Shannon information functions to evaluate disorder inside a tumor and between tumors of the same kind. We have considered 79 different kinds of solid tumors with 30 or more karyotypes retrieved from the Mitelman Database of Chromosome Aberrations in Cancer. The Kaplan-Meier cumulative survival was also obtained for each solid tumor type in order to correlate data with tumor malignance. The results here show that aberration spread is specific for each tumor type, with high degree of diversity for those tumor types with worst survival indices. Those tumor types with preferential variants (e.g. high proportion of a given karyotype) have shown better survival statistics, indicating that aberration recurrence is a good prognosis. Indeed, global spread of both numerical and structural abnormalities demonstrates the stochastic nature of chromosome aberrations by setting a signature of randomness associated to the production of disorder. These results also indicate that tumor malignancy correlates not only with karyotypic diversity taken from different tumor types but also taken from single tumors. Therefore, by quantifying aberration spread, we could confront diverse models and verify which of them points to the most likely outcome. Our results suggest that the generating process of chromosome aberrations is neither deterministic nor totally random, but produces variations that are distributed between these two boundaries.

Chromosome Aberrations↗
PubMed2003

An exploratory factor analysis of the Tail Suspension Test in 12 inbred strains of mice and an F2 intercross.

To explore the genetic dimensions of the stress response in rodents, we tested 12 inbred strains of mice and an F2 intercross (n=745) on the Tail Suspension Test (TST) and the Tail Suspension-Induced Hyperthermia (TSIH) paradigm. These selected 12 strains provide a representative sampling of the genetic heterogeneity of mousedom. An F2 intercross was derived from NMRI and 129S6 strains, which differ in their responses on the TST. Both inbred strains and F2 mice underwent a standardized protocol of automated TST with two sessions: (1) baseline and (2) imipramine TST. The duration of immobility and the body temperature after TST were recorded. The inbred strains were also tested in the Light-Dark Transition (LDT) test and in the Open Field Test (OFT), measuring the distance traveled, vertical movements, and center time as independent variables. The F2 mice were measured for core temperature after TST (TSIH). High intercorrelations among strain means were found for the LDT and OFT measures. Principal components analysis extracted four factors: "exploratory fear," body weight, imipramine response on immobility, and "stress reactivity." These dimensions were largely confirmed in the F2 population with one additional factor: imipramine response on TSIH. The results support a distinction between "stress reactivity" as measured by the TST and "exploratory fear" behavior as measured by the LDT and OFT.

Adrenergic Uptake Inhibitors↗
PubMed2006

Detection of divergent genes in microbial aCGH experiments.

BACKGROUND: Array-based comparative genome hybridization (aCGH) is a tool for rapid comparison of genomes from different bacterial strains. The purpose of such analysis is to detect highly divergent or absent genes in a sample strain compared to an index strain. Development of methods for analyzing aCGH data has primarily focused on copy number abberations in cancer research. In microbial aCGH analyses, genes are typically ranked by log-ratios, and classification into divergent or present is done by choosing a cutoff log-ratio, either manually or by statistics calculated from the log-ratio distribution. As experimental settings vary considerably, it is not possible to develop a classical discriminant or statistical learning approach. METHODS: We introduce a more efficient method for analyzing microbial aCGH data using a finite mixture model and a data rotation scheme. Using the average posterior probabilities from the model fitted to log-ratios before and after rotation, we get a score for each gene, and demonstrate its advantages for ranking and detecting divergent genes with enlarged specificity and sensitivity. RESULTS: The procedure is tested and compared to other approaches on simulated data sets, as well as on four experimental validation data sets for aCGH analysis on fully sequenced strains of Staphylococcus aureus and Streptococcus pneumoniae. CONCLUSION: When tested on simulated data as well as on four different experimental validation data sets from experiments with only fully sequenced strains, our procedure out-competes the standard procedures of using a simple log-ratio cutoff for classification into present and divergent genes.

Computational Biology↗
PubMed1989

[Alpha-amylase polymorphism. 1. A comparative study of alpha-amylase Hp and Gm].

Individual phenotypes, phenotypical and genetic frequencies of the alpha-amylase enzyme have been established by means of populational genetic researches. The most common phenotype is AmylA Amyl2A (85.15%) followed by AmylA Amyl2A 2B (6.27%), AmylAIB Amyl2A (5.37%), Amyl IA Amyl2A 2B (2.15%), AmylA Amyl2B (0.53%), AmylC Amyl2B (0.35%), AmylC Amyl2A 2B (0.18%). The difference between the observed and theoretically expected phenotypes of Amy, Hp and M Gm(1) is insignificant. The examined contingent from the Bulgarian population is found to be in genetic balance. Statistical analysis of the reuö results does not prove a genetic link between Amy, Hp and Gm (1).

Humans↗
PubMed2005

Haplotype sharing analysis using mantel statistics.

OBJECTIVE: The potential value of haplotypes has attracted widespread interest in the mapping of complex traits. Haplotype sharing methods take the linkage disequilibrium information between multiple markers into account, and may have good power to detect predisposing genes. We present a new approach based on Mantel statistics for spacetime clustering, which is developed in order to improve the power of haplotype sharing analysis for gene mapping in complex disease. METHODS: The new statistic correlates genetic similarity and phenotypic similarity across pairs of haplotypes for case-only and case-control studies. The genetic similarity is measured as the shared length between haplotypes around a putative disease locus. The phenotypic similarity is measured as the mean-corrected cross-product based on the respective phenotypes. We analyzed two tests for statistical significance with respect to type I error: (1) assuming asymptotic normality, and (2) using a Monte Carlo permutation procedure. The results were compared to the chi(2) test for association based on 3-marker haplotypes. RESULTS: The results of the type I error rates for the Mantel statistics using the permutational procedure yielded pointwise valid tests. The approach based on the assumption of asymptotic normality was seriously liberal. CONCLUSION: Power comparisons showed that the Mantel statistics were better than or equal to the chi(2) test for all simulated disease models.

Case-Control Studies↗