Applications of multifactor dimensionality reduction to genome-wide data using the R package 'MDR'

A review of multivariate analyses in imaging genetics

Recent advances in neuroimaging technology and molecular genetics provide the unique opportunity to investigate genetic influence on the variation of brain attributes. Since the year 2000, when the initial publication on brain imaging and genetics was released, imaging genetics has been a rapidly growing research approach with increasing publications every year. Several reviews have been offered to the research community focusing on various study designs. In addition to study design, analytic tools and their proper implementation are also critical to the success of a study. In this review, we survey recent publications using data from neuroimaging and genetics, focusing on methods capturing multivariate effects accommodating the large number of variables from both imaging data and genetic data. We group the analyses of genetic or genomic data into either a priori driven or data driven approach, including gene-set enrichment analysis, multifactor dimensionality reduction, principal component analysis, independent component analysis (ICA), and clustering. For the analyses of imaging data, ICA and extensions of ICA are the most widely used multivariate methods. Given detailed reviews of multivariate analyses of imaging data available elsewhere, we provide a brief summary here that includes a recently proposed method known as independent vector analysis. Finally, we review methods focused on bridging the imaging and genetic data by establishing multivariate and multiple genotype-phenotype-associations, including sparse partial least squares, sparse canonical correlation analysis, sparse reduced rank regression and parallel ICA. These methods are designed to extract latent variables from both genetic and imaging data, which become new genotypes and phenotypes, and the links between the new genotype-phenotype pairs are maximized using different cost functions. The relationship between these methods along with their assumptions, advantages, and limitations are discussed.

Multifactor dimensionality reduction analysis of the correlation of Chinese medicine syndrome evolvement and cardiovascular events in patients with stable coronary heart disease

OBJECTIVE

To analyze the correlation of Chinese medicine syndrome evolvement and cardiovascular: events in patients with stable coronary heart disease (CHD).

METHODS

This prospective cohort study investigated and: collected the clinical information of patients with stable CHD and observed the syndrome type at the baseline and 6-month at follow-up, as well as the cardiovascular events during the 6-month and 12-month follow-up. The patients were divided into the event group and the non-event group. The interaction and the impact of syndrome evolvement on cardiovascular events were examined through multifactor dimensionality reduction (MDR) analysis and the results were verified by Chi-square test.

RESULTS

Totally 1,333 of 1,503 stable CHD patients enrolled met the inclusion criteria: of MDR analysis. Among them, 959 (71.9%) cases were males and 374 (28.1%) cases were females. Thirty seven cases had cardiovascular events during 6 to 12 months after the study began. The results of the MDR analysis and verification using Chi-square test showed that the development of cardiovascular events was positively correlated with interaction between blood stasis and toxic syndrome at the baseline, blood stasis at the baseline and qi deficiency at the 6-month follow-up, toxic syndrome at the baseline and qi deficiency at the 6-month follow-up, toxic syndrome at the base line and blood stasis at the 6-month follow-up, qi deficiency and blood stasis at the 6-month follow-up (P<0.05 for all).

CONCLUSIONS

Blood stasis, toxic syndrome and qi deficiency are important factors of stable CHD. There: are positive correlation between cardiovascular events and syndrome evolution from blood stasis to qi deficiency, from toxic syndrome to qi deficiency and from toxic syndrome to blood stasis, indicating the pathogenesis of toxin consuming qi, toxin leading to blood-stasis in stable CHD patients prone to recurrent cardiovascular events.