Uncovering Local Trends in Genetic Effects of Multiple Phenotypes via Functional Linear Models

Recent technological advances equipped researchers with capabilities that go beyond traditional genotyping of loci known to be polymorphic in a general population. Genetic sequences of study participants can now be assessed directly. This capability removed technology-driven bias toward scoring predominantly common polymorphisms and let researchers reveal a wealth of rare and sample-specific variants. Although the relative contributions of rare and common polymorphisms to trait variation are being debated, researchers are faced with the need for new statistical tools for simultaneous evaluation of all variants within a region. Several research groups demonstrated flexibility and good statistical power of the functional linear model approach. In this work we extend previous developments to allow inclusion of multiple traits and adjustment for additional covariates. Our functional approach is unique in that it provides a nuanced depiction of effects and interactions for the variables in the model by representing them as curves varying over a genetic region. We demonstrate flexibility and competitive power of our approach by contrasting its performance with commonly used statistical tools and illustrate its potential for discovery and characterization of genetic architecture of complex traits using sequencing data from the Dallas Heart Study

Rationale, design and methods for a community-based study of clustering and cumulative effects on chronic disease process and their effects on ageing: the Busselton healthy ageing study

Background: The global trend of increased life expectancy and increased prevalence of chronic and degenerative diseases will impact on health systems. To identify effective intervention and prevention strategies, greater understanding of the risk factors for and cumulative effects of chronic disease processes and their effects on function and quality of life is needed. The Busselton Healthy Ageing Study aims to enhance understanding of ageing by relating the clustering and interactions of common chronic conditions in adults to function. Longitudinal (3–5 yearly) follow-up is planned. Methods/design: Phase I (recruitment) is a cross-sectional community-based prospective cohort study involving up to 4,000 ‘Baby Boomers’ (born from 1946 to 1964) living in the Busselton Shire, Western Australia. The study protocol involves a detailed, self-administered health and risk factor questionnaire and a range of physical assessments including body composition and bone density measurements, cardiovascular profiling (blood pressure, ECG and brachial pulse wave velocity), retinal photography, tonometry, auto-refraction, spirometry and bronchodilator responsiveness, skin allergy prick tests, sleep apnoea screening, tympanometry and audiometry, grip strength, mobility, balance and leg extensor strength. Cognitive function and reserve, semantic memory, and pre-morbid intelligence are assessed. Participants provide a fasting blood sample for assessment of lipids, blood glucose, C-reactive protein and renal and liver function, and RNA, DNA and serum are stored. Clinically relevant results are provided to all participants. The prevalence of risk factors, symptoms and diagnosed illness will be calculated and the burden of illness will be estimated based on the observed relationships and clustering of symptoms and illness within individuals. Risk factors for combinations of illness will be compared with those for single illnesses and the relation of combinations of illness and symptoms to cognitive and physical function will be estimated. Discussion: This study will enable a thorough characterization of multiple disease processes and their risk factors within a community-based sample of individuals to determine their singular, interactive and cumulative effects on ageing. The project will provide novel cross-sectional data and establish a cohort that will be used for longitudinal analyses of the genetic, lifestyle and environmental factors that determine whether an individual ages well or with impairment

An updated global picture of cigarette smoking persistence among adults

Background: Cross-national variance in smoking prevalence is relatively well documented. The aim of this study is to estimate levels of smoking persistence across 21 countries with a hypothesized inverse relationship between country income level and smoking persistence. Methods: Data from the World Health Organization World Mental Health Survey Initiative were used to estimate cross-national differences in smoking persistence—the proportion of adults who started to smoke and persisted in smoking by the date of the survey. Results: There is large variation in smoking persistence from 25% (Nigeria) to 85% (China), with a random-effects meta-analytic summary estimate of 55% with considerable cross-national variation. (Cochran’s heterogeneity Q statistic = 6845; p < 0.001). Meta-regressions indicated that observed differences are not attributable to differences in country’s income level, age distribution of smokers, or how recent the onset of smoking began within each country. Conclusion: While smoking should remain an important public health issue in any country where smokers are present, this report identifies several countries with higher levels of smoking persistence (namely, China and India)