Biomedical subjects

Ole Christian Lingjaerde

Publications and source records attributed to Ole Christian Lingjaerde.

4 recordsLinked to original sources

PubMed2006

Multilocus analysis of SNP and metabolic data within a given pathway.

BACKGROUND: Complex traits, which are under the influence of multiple and possibly interacting genes, have become a subject of new statistical methodological research. One of the greatest challenges facing human geneticists is the identification and characterization of susceptibility genes for common multifactorial diseases and their association to different quantitative phenotypic traits. RESULTS: Two types of data from the same metabolic pathway were used in the analysis: categorical measurements of 18 SNPs; and quantitative measurements of plasma levels of several steroids and their precursors. Using the combinatorial partitioning method we tested various thresholds for each metabolic trait and each individual SNP locus. One SNP in CYP19, 3UTR, two SNPs in CYP1B1 (R48G and A119S) and one in CYP1A1 (T461N) were significantly differently distributed between the high and low level metabolic groups. The leave one out cross validation method showed that 6 SNPs in concert make 65% correct prediction of phenotype. Further we used pattern recognition, computing the p-value by Monte Carlo simulation to identify sets of SNPs and physiological characteristics such as age and weight that contribute to a given metabolic level. Since the SNPs detected by both methods reside either in the same gene (CYP1B1) or in 3 different genes in immediate vicinity on chromosome 15 (CYP19, CYP11 and CYP1A1) we investigated the possibility that they form intragenic and intergenic haplotypes, which may jointly account for a higher activity in the pathway. We identified such haplotypes associated with metabolic levels. CONCLUSION: The methods reported here may enable to study multiple low-penetrance genetic factors that together determine various quantitative phenotypic traits. Our preliminary data suggest that several genes coding for proteins involved in a common pathway, that happen to be located on common chromosomal areas and may form intragenic haplotypes, together account for a higher activity of the whole pathway.

Aged↗

PubMed2006

Statistical dissection of genetic pathways involved in prostate carcinogenesis.

Molecular markers that could stratify prostate cancer patients according to risk of disease progression would allow a significant improvement in the management of this clinically heterogeneous disease. In the present study, we analyzed the genetic profile of a consecutive series of 51 clinically confined prostate carcinomas and 27 benign prostatic hyperplasias using comparative genomic hybridization (CGH). We then added our findings to the existing literature data in order to perform a meta-analysis on a total of 294 prostate cancers with detailed CGH and clinicopathological information, using multivariate statistical methods that included principal component, hierarchical clustering, time of occurrence, and regression analyses. Whereas several genomic imbalances were shared by organ-confined, locally invasive, and metastatic prostate cancers, 6q and 10q losses and 7q and 8q gains were significantly more frequent in patients with extra-prostatic disease. Regression analysis indicated that 8q gain and 13q loss were the best predictors of locally invasive disease, whereas 8q gain and 6q and 10q losses were associated with metastatic disease. We propose a genetic pathway of prostate carcinogenesis with two distinct initiating events, namely, 8p and 13q losses. These primary imbalances are then preferentially followed by 8q gain and 6q, 16q, and 18q losses, which in turn are followed by a set of late events that make recurrent and metastatic prostate cancers genetically more complex. We conclude that significant differences exist in the genetic profile of organ-confined, locally invasive, and advanced prostate cancer and that genetic features may carry prognostic information independently of Gleason grade.

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PubMed2004

CGH-Explorer: a program for analysis of array-CGH data.

SUMMARY: CGH-Explorer is a program for visualization and statistical analysis of microarray-based comparative genomic hybridization (array-CGH) data. The program has preprocessing facilities, tools for graphical exploration of individual arrays or groups of arrays, and tools for statistical identification of regions of amplification and deletion.

Computer Graphics↗

PubMed2002

Adaptive weighted least squares method for the estimation of DNA fragment lengths from agarose gels.

The size of DNA fragments is most frequently estimated from their electrophoretic mobilities. Agarose gels are used to estimate the size of DNA fragments ranging from a few hundred nucleotides to more than 20 kbp. The common practice when estimating the unknown fragment sizes is to plot the log of the size of molecular weight standards against their mobility and read the values of unknowns from this graph. However, due to perturbations in the gel, such plots often show pronounced curvature which may introduce significant subjectivity into the interpolation process. We present a new method "adaptive weighted least squares (AWLS)" based on the significance test to choose the order of polynomial. We compare this with the method introduced by Schaffer based on the modification of the Southern method. The results obtained by AWLS are significantly better than the method introduced by Schaffer. Different lanes are tested for consistency.

DNA↗