Biomedical subjects

Rolf Sundberg

Publications and source records attributed to Rolf Sundberg.

3 recordsLinked to original sources

PubMed2006

Control of confounding through secondary samples.

The control of confounding is essential in many statistical problems, especially in those that attempt to estimate exposure effects. In some cases, in addition to the 'primary' sample, there is another 'secondary' sample which, though having no direct information about the exposure effect, contains information about the confounding factors. The purpose of this article is to study the influence of the secondary sample on likelihood inference for the exposure effect. In particular, we investigate the interplay between the efficiency improvement and the possible bias introduced by the secondary sample as a function of the degree of confounding in the primary sample and the sizes of the primary and secondary samples. In the case of weak confounding, the secondary sample can only little improve estimation of the exposure effect, whereas with strong confounding the secondary sample can be much more useful. On the other hand, it will be more important to consider possible biasing effects in the latter case. For illustration, we use a formal example of a generalized linear model and a real example with sparse data from a case-control study of the association between gastric cancer and HM-CAP/Band 120.

Case-Control Studies↗

PubMed2005

Statistical modeling in case-control real-time RT-PCR assays, for identification of differentially expressed genes in schizophrenia.

Aspects of experimental design, statistical modeling, and statistical inference in case-control real-time reverse transcription-polymerase chain reaction (RT-PCR) assays are discussed. The background is mRNA expression data from an investigation of genes previously suggested to be schizophrenia related. Real-time RT-PCR allows large samples of individuals. However, with more individuals than positions per plate, incomplete designs are required. A basic multivariate (for several genes jointly) random-effects analysis of covariance model, incorporating heterogeneity both between and within individuals, is formulated. The use of reference genes to form additional regressors is found to be highly efficient. Because regressions between and within individuals are usually different, it is important first to average over the intraindividual replicates. This has consequences for the influence of plate effects. Topics also discussed are testing for a significant mean disease effect, differential coregulation, and the difficulty of identifying genes affected in only a subgroup of cases.

Analysis of Variance↗

PubMed2003

Decrease of serotonin receptor 2C in schizophrenia brains identified by high-resolution mRNA expression analysis.

BACKGROUND: RNA expression profiling can provide hints for the selection of candidate susceptibility genes, for formulation of hypotheses about the development of a disease, and/or for selection of candidate gene targets for novel drug development. We measured messenger RNA expression levels of 16 candidate genes in brain samples from 55 schizophrenia patients and 55 controls. This is the largest sample so far used to identify genes differentially expressed in schizophrenia brains. METHODS: We used a sensitive real-time polymerase chain reaction methodology and a novel statistical approach, including the development of a linear model of analysis of covariance type. RESULTS: We found two genes differentially expressed: monoamine oxidase B was significantly increased in schizophrenia brain (p =.001), whereas one of the serotonin receptor genes, serotonin receptor 2C, was significantly decreased (p =.001). Other genes, previously proposed to be differentially expressed in schizophrenia brain, were invariant in our analysis. CONCLUSIONS: The differential expression of serotonin receptor 2C is particularly relevant for the development of new atypical antipsychotic drugs. The strategy presented here is useful to evaluate hypothesizes for the development of the disease proposed by other investigators.

Cerebral Cortex↗