Analysis of binary traits: testing association in the presence of linkage

A randomized controlled trial to determine the effect of spinal stabilization exercise intervention based on pain level and standing balance differences in patients with low back pain

Background

A number of studies have evaluated exercise interventions compared with other treatment strategies for subjects with recurrent low back pain (LBP); however, subject pain level and balance were not carefully considered. The purpose of this study was to investigate the effectiveness of spinal stabilization exercises (SSE) for managing pain and increasing balance strategy changes following unexpected perturbations in patients diagnosed with recurrent LBP.

Material/Methods

Twenty-one age- and gender-matched patients participated in a supervised SSE or control exercise program 5 times a week over a 4-week period. The Million Visual Analogue Scale (MVAS) and Oswestry Disability Index (ODI) were used to measure each patient’s level of pain and disability. Balance measurements were derived from recordings of the anterior-posterior (A/P) and medio-lateral (M/L) center of pressure (COP) displacements during 3 consecutive, unexpected random perturbations.

Results

The level of reported pain and disability significantly decreased following treatment for both groups. Although the M/L sway was not significantly different in either group (p=0.86), there was a significant difference between group and measurement time during A/P sway (p=0.04). The A/P displacement of the SSE group significantly decreased compared with the control group. The decreased A/P displacement can be linked to the SSE intervention, which helps prevent further injury by limiting an individual’s response rate to external perturbations.

Conclusions

Clinicians might consider SSE for LBP patients as a possible rehabilitation strategy to reduce A/P displacement.

Family based studies and genetic epidemiology: theory and practice

Family based studies have underpinned many successes in uncovering the causes of monogenic and oligogenic diseases. Now research is focussing on the identification and characterisation of genes underlying common diseases and it is widely accepted that these studies will require large population based samples. Population based family study designs have the potential to facilitate the analysis of the effects of both genes and environment. These types of studies integrate the population based approaches of classic epidemiology and the methods enabling the analysis of correlations between relatives sharing both genes and environment. The extent to which such studies are feasible will depend upon population- and disease-specific factors. To review this topic, a symposium was held to present and discuss the costs, requirements and advantages of population based family study designs. This article summarises the features of the meeting held at The University of Sheffield, August 2006.

Association mapping: methodologies, strategies, and issues

Recent advances in molecular genetic technology allow for detailed characterization of genetic variation and easy cost-efficient accumulation of such data, even for large human samples. One such advance that presents incredible opportunities for identifying associations between genetic polymorphisms and disease-related phenotypes is the ability to quickly type a large number of single-nucleotide polymorphisms (SNPs). Contributors to Group 10 of Genetic Analysis Workshop 14 explored the potential of SNP genotypes for the association mapping of disease-related genes in family-based studies. Using both real data involving alcoholism susceptibility, made available by the Collaborative Study on the Genetics of Alcoholism (COGA), and simulated data involving personality-disorder susceptibility, group members investigated specific methodological issues involved in association mapping, such as multiple testing, single SNPs vs. combinations and haplotypes, and the effect of linkage disequilibrium on SNP-based linkage; evaluated existing methodologies for association mapping using SNPs, short-tandem repeats (STRs), or a combination of the two; and introduced new or modified association-mapping methods, including a gamma random effects (GRE) model and the quantitative trait linkage disequilibrium (QTLD) test. These papers are unified by the application of association-based methods to analyze SNPs, microsatellite markers, or both, to identify chromosomal regions harboring genes that contribute to quantitative endophenotype variation, and thus to disease risk. Their diversity attests to the breadth and flexibility of association-mapping approaches to the genetics of complex disease.