Collaborative meta-analysis finds no evidence of a strong interaction between stress and 5-HTTLPR genotype contributing to the development of depression.

The hypothesis that the S allele of the 5-HTTLPR serotonin transporter promoter region is associated with increased risk of depression, but only in individuals exposed to stressful situations, has generated much interest, research and controversy since first proposed in 2003. Multiple meta-analyses combining results from heterogeneous analyses have not settled the issue. To determine the magnitude of the interaction and the conditions under which it might be observed, we performed new analyses on 31 data sets containing 38 802 European ancestry subjects genotyped for 5-HTTLPR and assessed for depression and childhood maltreatment or other stressful life events, and meta-analysed the results. Analyses targeted two stressors (narrow, broad) and two depression outcomes (current, lifetime). All groups that published on this topic prior to the initiation of our study and met the assessment and sample size criteria were invited to participate. Additional groups, identified by consortium members or self-identified in response to our protocol (published prior to the start of analysis) with qualifying unpublished data, were also invited to participate. A uniform data analysis script implementing the protocol was executed by each of the consortium members. Our findings do not support the interaction hypothesis. We found no subgroups or variable definitions for which an interaction between stress and 5-HTTLPR genotype was statistically significant. In contrast, our findings for the main effects of life stressors (strong risk factor) and 5-HTTLPR genotype (no impact on risk) are strikingly consistent across our contributing studies, the original study reporting the interaction and subsequent meta-analyses. Our conclusion is that if an interaction exists in which the S allele of 5-HTTLPR increases risk of depression only in stressed individuals, then it is not broadly generalisable, but must be of modest effect size and only observable in limited situations.

A novel approach for discovering human behavior patterns using unsupervised methods.

BACKGROUND: As is well known, elderly people gradually lose the ability of self-care. The decline can be reflected in changes in their daily life behavior. A solution to assess their health status is to design sensor-enhanced living environments to observe their behavior, in which unobtrusive sensors are usually used. With respect to information extraction from the dataset collected by means of these kinds of sensors, unsupervised methods have to be relied on for practical application. Under the assumption that human lifestyle is associated with health status, this study intends to propose a novel approach to discover behavior patterns using unsupervised methods. METHODS: To evaluate the feasibility of this approach it was applied to datasets collected in the GAL-NATARS study. The study is part of the Lower Saxony research network Design of Environments for Aging (GAL) and conducted in subjects' home environments. The subjects recruited in GAL-NATARS study are older people (age ≥ 70 years), who are discharged from hospital to live alone again at their homes after treatment of a femoral fracture. RESULTS: The change of lifestyle regularity is measured. By analyzing the correlation between the extracted information and medical assessment results of four subjects, two of them exhibited impressive association and the other two showed less association. CONCLUSIONS: The approach may provide complementary information for health assessment; however, the dominant relationship between the change of behavior patterns and the health status has to be shown and datasets from more subjects must be collected in future studies. LIMITATIONS: Merely environmental data were used and no wearable sensor for activity detection or vital parameter measurement is taken into account. Therefore, this cannot comprehensively reflect reality.

Development and pilot study of a bed-exit alarm based on a body-worn accelerometer.

BACKGROUND: Falls are a major problem in hospitals and nursing homes. The consequences of falls can be severe, both for the individual and for the caring institution. OBJECTIVE: The aim of the work presented here is to reduce the number of falls on a geriatric ward by monitoring patients more closely. To achieve this goal, a bed-exit alarm that reliably detects an attempt to get up has been constructed. MATERIALS AND METHODS: A requirements analysis revealed the nurses' and physicians' needs and preferences. Based on the gathered information, an incremental design process generated different prototypes. These were tested for the reliability of their ability to detect attempts to get up in both laboratory settings and with geriatric patients. Based on the result of these tests, a scalable technical solution has been developed and proven its reliability in a 1-year, randomized controlled pilot clinical trial on a geriatric ward. RESULTS: The developed system is unobtrusive and easy to deploy. It has been tested in laboratory settings, usability tests and a 1-year randomized clinical trial with 98 patients. This paper focuses on the technical development of the system. We present different prototypes, the experiments and the pilot study used to evaluate their performance. Last but not least, we discuss the lessons learned so far. CONCLUSION: The developed bed-exit alarm is able to reliably detect patients' attempts to get up. The results of the clinical trial show that the system is able to reduce the number of falls on a geriatric ward. Next steps are the design of a specialized sensor node that is easier to use and can be applied on an even larger scale due to its reduced cost. A multicenter trial with a larger number of patients is required to confirm the results of this pilot study.