Quantifying the heritability of task-related brain activation and performance during the N-back working memory task: A twin fMRI study

Working memory-related brain activation has been widely studied, and impaired activation patterns have been reported for several psychiatric disorders. We investigated whether variation in N-back working memory brain activation is genetically influenced in 60 pairs of twins, (29 monozygotic (MZ), 31 dizygotic (DZ); mean age 24.4 ± 1.7S.D.). Task-related brain response (BOLD percent signal difference of 2 minus 0-back) was measured in three regions of interest. Although statistical power was low due to the small sample size, for middle frontal gyrus, angular gyrus, and supramarginal gyrus, the MZ correlations were, in general, approximately twice those of the DZ pairs, with non-significant heritability estimates (14-30%) in the low-moderate range. Task performance was strongly influenced by genes (57-73%) and highly correlated with cognitive ability (0.44-0.55). This study, which will be expanded over the next 3 years, provides the first support that individual variation in working memory-related brain activation is to some extent influenced by genes.

Meeting the challenges of neuroimaging genetics

As research encompassing neuroimaging and genetics gains momentum, extraordinary information will be uncovered on the genetic architecture of the human brain. However, there are significant challenges to be addressed first. Not the least of these challenges is to accomplish the sample size necessary to detect subtle genetic influences on the morphometry and function of the healthy brain. Aside from sample size, image acquisition and analysis methods need to be refined in order to ensure optimum sensitivity to genetic and complementary environmental influences. Then there is the vexing issue of interpreting the resulting data. We describe how researchers from the east coast of Australia and the west coast of America have embarked upon a collaboration to meet these challenges using data currently being collected from a large-scale twin study, and offer some opinions about future directions in the field.

Combining meta- and mega-analytic approaches for multi-site diffusion imaging based genetic studies: From the enigma-DTI working group

Meta-analyses estimate a statistical effect size for a test or an analysis by combining results from multiple studies without necessarily having access to each individual study's raw data. Multi-site meta-analysis is crucial for imaging genetics, as single sites rarely have a sample size large enough to pick up effects of single genetic variants associated with brain measures. However, if raw data can be shared, combining data in a "mega-analysis" is thought to improve power and precision in estimating global effects. As part of an ENIGMA-DTI investigation, we use fractional anisotropy (FA) maps from 5 studies (total N=2, 203 subjects, aged 9-85) to estimate heritability. We combine the studies through meta-and mega-analyses as well as a mixture of the two - combining some cohorts with mega-analysis and meta-analyzing the results with those of the remaining sites. A combination of mega-and meta-approaches may boost power compared to meta-analysis alone.

Multi-site study of additive genetic effects on fractional anisotropy of cerebral white matter: Comparing meta and megaanalytical approaches for data pooling

Combining datasets across independent studies can boost statistical power by increasing the numbers of observations and can achieve more accurate estimates of effect sizes. This is especially important for genetic studies where a large number of observations are required to obtain sufficient power to detect and replicate genetic effects. There is a need to develop and evaluate methods for joint-analytical analyses of rich datasets collected in imaging genetics studies. The ENIGMA-DTI consortium is developing and evaluating approaches for obtaining pooled estimates of heritability through meta-and mega-genetic analytical approaches, to estimate the general additive genetic contributions to the intersubject variance in fractional anisotropy (FA) measured from diffusion tensor imaging (DTI). We used the ENIGMA-DTI data harmonization protocol for uniform processing of DTI data from multiple sites. We evaluated this protocol in five family-based cohorts providing data from a total of 2248 children and adults (ages: 9-85) collected with various imaging protocols. We used the imaging genetics analysis tool, SOLAR-Eclipse, to combine twin and family data from Dutch, Australian and Mexican-American cohorts into one large "mega-family". We showed that heritability estimates may vary from one cohort to another. We used two meta-analytical (the sample-size and standard-error weighted) approaches and a mega-genetic analysis to calculate heritability estimates across-population. We performed leave-one-out analysis of the joint estimates of heritability, removing a different cohort each time to understand the estimate variability. Overall, meta- and mega-genetic analyses of heritability produced robust estimates of heritability.

A comprehensive neuropsychiatric study of elderly twins: The Older Australian Twins Study

The Older Australian Twins Study (OATS) was recently initiated to investigate genetic and environmental factors and their associations and interactions in healthy brain ageing and ageing-related neurocognitive disorders. The study extends the classic MZ-DZ design to include one or two equivalently aged siblings for each twin pair and utilizes the rich resources of the Australian Twin Registry. The study has a number of distinguishing features including comprehensive psychiatric, neuropsychological, cardiovascular, metabolic, and neuroimaging assessments, a longitudinal design and links with a brain donor program. The study measures many behavioral and environmental factors, but in particular lifetime physical and mental activity, physical and psychological trauma, loss of parent early in life, later losses and life events, early-life socioeconomic environment, alcohol and drug use, occupational exposure, and nutrition. It also includes comprehensive cardiovascular assessment, blood biochemistry, genetics and proteomics. The socio-demographic and health data on the first 172 pairs of twins participating in this study are presented. Prevalence of mild cognitive impairment is 12.8% and of dementia 1.5% in the sample. The target sample size is 1000, with at least 400 pairs of twins aged 65-90 years. The cohort will be assessed every two years, with in-depth assessments being repeated. OATS offers an excellent opportunity for collaboration with other similar studies as well as researchers who share the same interests.

Corrigendum to "Mapping hippocampal and ventricular change in Alzheimer disease" [NeuroImage 22 (2004) 1754-1766] (DOI:10.1016/j.neuroimage.2004.03.040)

We recently noticed an error in the demographic data in this article. The validity of the findings and the conclusions of the paper is not affected. However, there is an error in the reported sample size and in the means and standard deviations of the subjects’ ages and MMSE scores. We would like to correct this error, which came to light when we were re-analyzing the data for a meta-analysis. The error occurred because an older version of a spreadsheet was incorrectly used when reporting the sample composition. Instead of examining 12 Alzheimer's disease patients and 14 healthy elderly controls, we in fact examined 17 Alzheimer’s disease patients and 14 healthy elderly controls. All maps and morphometric data reported in the paper are correct, except that the sample size was in fact slightly higher than that originally reported, and the maps computed in the paper were based on the larger sample (which included five more subjects in the Alzheimer’s disease group). All of the maps and figures in the paper are correct, and the conclusions of the paper are unchanged. We apologize for this error, which falls under the sole responsibility of the first author. The corrected demographic information appears below.

Does the technique employed for skin temperature assessment alter outcomes? A systematic review

Skin temperature is an important physiological measure that can reflect the presence of illness and injury as well as provide insight into the localised interactions between the body and the environment. The aim of this systematic review was to analyse the agreement between conductive and infrared means of assessing skin temperature which are commonly employed in in clinical, occupational, sports medicine, public health and research settings. Full-text eligibility was determined independently by two reviewers. Studies meeting the following criteria were included in the review: 1) the literature was written in English, 2) participants were human (in vivo), 3) skin surface temperature was assessed at the same site, 4) with at least two commercially available devices employed—one conductive and one infrared—and 5) had skin temperature data reported in the study. A computerised search of four electronic databases, using a combination of 21 keywords, and citation tracking was performed in January 2015. A total of 8,602 were returned. Methodology quality was assessed by 2 authors independently, using the Cochrane risk of bias tool. A total of 16 articles (n = 245) met the inclusion criteria. Devices are classified to be in agreement if they met the clinically meaningful recommendations of mean differences within ±0.5 °C and limits of agreement of ±1.0 °C. Twelve of the included studies found mean differences greater than ±0.5 °C between conductive and infrared devices. In the presence of external stimulus (e.g. exercise and/or heat) five studies foundexacerbated measurement differences between conductive and infrared devices. This is the first review that has attempted to investigate presence of any systemic bias between infrared and conductive measures by collectively evaluating the current evidence base. There was also a consistently high risk of bias across the studies, in terms of sample size, random sequence generation, allocation concealment, blinding and incomplete outcome data. This systematic review questions the suitability of using infrared cameras in stable, resting, laboratory conditions. Furthermore, both infrared cameras and thermometers in the presence of sweat and environmental heat demonstrate poor agreement when compared to conductive devices. These findings have implications for clinical, occupational, public health, sports science and research fields.

Resampling-based approaches to study variation in morphological modularity

Modularity has been suggested to be connected to evolvability because a higher degree of independence among parts allows them to evolve as separate units. Recently, the Escoufier RV coefficient has been proposed as a measure of the degree of integration between modules in multivariate morphometric datasets. However, it has been shown, using randomly simulated datasets, that the value of the RV coefficient depends on sample size. Also, so far there is no statistical test for the difference in the RV coefficient between a priori defined groups of observations. Here, we (1), using a rarefaction analysis, show that the value of the RV coefficient depends on sample size also in real geometric morphometric datasets; (2) propose a permutation procedure to test for the difference in the RV coefficient between a priori defined groups of observations; (3) show, through simulations, that such a permutation procedure has an appropriate Type I error; (4) suggest that a rarefaction procedure could be used to obtain sample-size-corrected values of the RV coefficient; and (5) propose a nearest-neighbor procedure that could be used when studying the variation of modularity in geographic space. The approaches outlined here, readily extendable to non-morphometric datasets, allow study of the variation in the degree of integration between a priori defined modules. A Java application – that will allow performance of the proposed test using a software with graphical user interface – has also been developed and is available at the Morphometrics at Stony Brook Web page (http://life.bio.sunysb.edu/morph/).

Time and cost performance of design–build projects

The design-build (DB) delivery method has been widely used in the United States due to its reputed superior cost and time performance. However, rigorous studies have produced inconclusive support and only in terms of overall results, with few attempts being made to relate project characteristics with performance levels. This paper provides a larger and more finely grained analysis of a set of 418 DB projects from the online project database of the Design-Build Institute of America (DBIA), in terms of the time-overrun rate (TOR), early start rate (ESR), early completion rate (ECR) and cost overrun rate (COR) associated with project type (e.g., commercial/institutional buildings and civil infrastructure projects), owners (e.g., Department of Defense and private corporations), procurement methods (e.g., ‘best value with discussion’ and qualifications-based selection), contract methods (e.g., lump sum and GMP) and LEED levels (e.g., gold and silver). The results show ‘best value with discussion’ to be the dominant procurement method and lump sum the most frequently used contract method. The DB method provides relatively good time performance, with more than 75% of DB projects completed on time or before schedule. However, with more than 50% of DB projects cost overrunning, the DB advantage of cost saving remains uncertain. ANOVA tests indicate that DB projects within different procurement methods have significantly different time performance and that different owner types and contract methods significantly affect cost performance. In addition to contributing to empirical knowledge concerning the cost and time performance of DB projects with new solid evidence from a large sample size, the findings and practical implications of this study are beneficial to owners in understanding the likely schedule and budget implications involved for their particular project characteristics.

Promise and pitfalls of the Immunochip

Genomewide association studies (GWAS) have proven a powerful hypothesis-free method to identify common disease-associated variants. Even quite large GWAS, however, have only at best identified moderate proportions of the genetic variants contributing to disease heritability. To provide cost-effective genotyping of common and rare variants to map the remaining heritability and to fine-map established loci, the Immunochip Consortium has developed a 200,000 SNP chip that has been produced in very large numbers for a fraction of the cost of GWAS chips. This chip provides a powerful tool for immunogenetics gene mapping.

Mapping genes for osteoporosis-Old dogs and new tricks

In stark contrast to its horticultural origins, modern genetics is an extremely technology-driven field. Almost all the major advances in the field over the past 20 years have followed technological developments that have permitted change in study designs. The development of PCR in the 1980s led to RFLP mapping of monogenic diseases. The development of fluorescent-tagged genotyping methods led to linkage mapping approaches for common diseases that dominated the 1990s. The development of microarray SNP genotyping has led to the genome-wide association study era of the new millennium. And now the development of next-generation sequencing technologies is about to open up a new era of gene-mapping, enabling many potential new study designs. This review aims to present the strengths and weaknesses of the current approaches, and present some new ideas about gene-mapping approaches that are likely to advance our knowledge of the genes involved in heritable bone traits such as bone mineral density (BMD) and fracture.

Methods for constructing uncertainty intervals for queries of Bayesian nets

In this paper the issue of finding uncertainty intervals for queries in a Bayesian Network is reconsidered. The investigation focuses on Bayesian Nets with discrete nodes and finite populations. An earlier asymptotic approach is compared with a simulation-based approach, together with further alternatives, one based on a single sample of the Bayesian Net of a particular finite population size, and another which uses expected population sizes together with exact probabilities. We conclude that a query of a Bayesian Net should be expressed as a probability embedded in an uncertainty interval. Based on an investigation of two Bayesian Net structures, the preferred method is the simulation method. However, both the single sample method and the expected sample size methods may be useful and are simpler to compute. Any method at all is more useful than none, when assessing a Bayesian Net under development, or when drawing conclusions from an ‘expert’ system.

The prevalence, predictors and associations of hypertension in Sri Lanka: A cross-sectional population based national survey

We studied the community prevalence, patterns and predictors of hypertension in a large sub-population of South Asian adults with a view of identifying differential risk factors. Data were collected between years 2005-2006 and 5000 adults were invited for the study. The sample size was 4485, and about 39.5% were males. Mean systolic and diastolic blood pressures were 127.1 ± 19.8 mmHg and 75.4 ± 11.3 mmHg, respectively. Age-adjusted prevalence in all adults, males and females was 23.7%, 23.4% and 23.8%, respectively. Urban adults had a significantly higher prevalence of hypertension than rural adults. In the binary logistic-regression analysis, male gender (OR: 1.2), increasing age, Sri Lankan Moor ethnicity (OR: 1.6), physical inactivity (OR: 1.7), presence of diabetes (OR: 2.2) and central obesity (OR: 2.3) all were significantly associated with hypertension. In conclusion, nearly one-third of the Sri Lankan adult population is hypertensive. Hence, public health initiatives should encourage healthier lifestyles with emphasis on preventing obesity and increasing physical activity.

Exploring the nexus between tourism and output in Cook Islands: An ARDL bounds approach

Tourism plays an important role in the development of Cook Islands. In this paper we examine the nexus between tourism and growth using quarterly data over the period 2009Q1–2014Q2 using the recently upgraded ARDL bounds test to cointegration tool, Microfit 5.01, which provides sample adjusted bounds and hence is more reliable for small sample size studies. We perform the cointegration using the ARDL bounds test and examine the direction of causality. Using visitor arrival and output in per capita terms as respective proxy for tourism development and growth, we examine the long-run association and report the elasticity coefficient of tourism and causality nexus, accordingly. Using unit root break tests, we note that 2011Q1 and 2011Q2 are two structural break periods in the output series. However, we note that this period is not statistically significant in the ARDL model and hence excluded from the estimation. Subsequently, the regression results show the two series are cointegrated. The long-run elasticity coefficient of tourism is estimated to be 0.83 and the short-run is 0.73. A bidirectional causality between tourism and income is noted for Cook Islands which indicates that tourism development and income mutually reinforce each other. In light of this, socio-economic policies need to focus on broad-based, inclusive and income-generating tourism development projects which are expected to have feedback effect.

Dietary and exercise interventions to improve quality of life, metabolic risk factors and androgen deficiency symptoms in men with prostate cancer undergoing androgen deprivation therapy

Introduction Lifestyle interventions might be useful in the management of adverse effects of androgen deprivation therapy (ADT) in men with prostate cancer. Objectives To examine the effects of dietary and exercise interventions on quality of life (QoL), metabolic risk factors and androgen deficiency symptoms in men with prostate cancer undergoing ADT. Methods CINAHL, Cochrane library, Medline and PsychINFO were searched to identify randomised controlled trials published from January, 2004 to October, 2014. Data extraction and methodological quality assessment was independently conducted by two reviewers. Meta-analysis was conducted using RevMan® 5.3.5. Results Of 2183 articles retrieved, 11 studies met the inclusion criteria and had low risk of bias.Nine studies evaluated exercise (resistance and/or aerobic and/or counselling) and three evaluated dietary supplementation. Median sample size =79 (33–121) and median intervention duration was 12 weeks (12–24). Exercise improved QoL measures (SMD 0.26, 95%CI −0.01 to 0.53) but not body composition, metabolic risk or vasomotor symptoms. Qualitative analysis indicated soy (or isoflavone) supplementation did not improve vasomotor symptoms; however, may improve QoL. Conclusions Few studies have evaluated the efficacy of lifestyle interventions in the management of adverse effects of ADT. We found inconclusive results for exercise in improving QoL and negative results for other outcomes. For soy-based products, we found negative results for modifying vasomotor symptoms and inconclusive results for improving QoL. Future work should investigate the best mode of exercise for improving QoL and other interventions such as dietary counselling should be investigated for their potential to modify these outcomes.