Genetic risk score analysis indicates migraine with and without comorbid depression are genetically different disorders

Migraine and major depressive disorder (MDD) are comorbid, moderately heritable and to some extent influenced by the same genes. In a previous paper, we suggested the possibility of causality (one trait causing the other) underlying this comorbidity. We present a new application of polygenic (genetic risk) score analysis to investigate the mechanisms underlying the genetic overlap of migraine and MDD. Genetic risk scores were constructed based on data from two discovery samples in which genome-wide association analyses (GWA) were performed for migraine and MDD, respectively. The Australian Twin Migraine GWA study (N = 6,350) included 2,825 migraine cases and 3,525 controls, 805 of whom met the diagnostic criteria for MDD. The RADIANT GWA study (N = 3,230) included 1,636 MDD cases and 1,594 controls. Genetic risk scores for migraine and for MDD were used to predict pure and comorbid forms of migraine and MDD in an independent Dutch target sample (NTR-NESDA, N = 2,966), which included 1,476 MDD cases and 1,058 migraine cases (723 of these individuals had both disorders concurrently). The observed patterns of prediction suggest that the 'pure' forms of migraine and MDD are genetically distinct disorders. The subgroup of individuals with comorbid MDD and migraine were genetically most similar to MDD patients. These results indicate that in at least a subset of migraine patients with MDD, migraine may be a symptom or consequence of MDD. © 2013 Springer-Verlag Berlin Heidelberg.

Lewis's medical-surgical nursing: Assessment and management of clinical problems [ANZ Edition, 4th Ed.]

"Using the nursing process as a framework for practice, the fourth edition has been extensively revised to reflect the rapid changing nature of nursing practice and the increasing focus on key nursing care priorities. Building on the strengths of the third Australian and New Zealand edition and incorporating relevant global nursing research and practice from the prominent US title Medical-Surgical Nursing, 9Th Edition, Lewis’s Medical-Surgical Nursing, 4th Edition is an essential resource for students seeking to understand the role of the professional nurse in the contemporary health environment."--Publisher website

Young drivers’ responses to anti-speeding advertisements: Comparison of self-report and objective measures of persuasive processing and outcomes

Objective Self-report measures are typically used to assess the effectiveness of road safety advertisements. However, psychophysiological measures of persuasive processing (i.e., skin conductance response [SCR]) and objective driving measures of persuasive outcomes (i.e., in-vehicle GPS devices) may provide further insights into the effectiveness of these advertisements. This study aimed to explore the persuasive processing and outcomes of two anti-speeding advertisements by incorporating both self-report and objective measures of speeding behaviour. In addition, this study aimed to compare the findings derived from these different measurement approaches. Methods Young drivers (N = 20, Mage = 21.01 years) viewed either a positive or negative emotion-based anti-speeding television advertisement. Whilst viewing the advertisement, SCR activity was measured to assess ad-evoked arousal responses. The RoadScout® GPS device was then installed into participants’ vehicles for one week to measure on-road speed-related driving behaviour. Self-report measures assessed persuasive processing (emotional and arousal responses) and actual driving behaviour. Results There was general correspondence between the self-report measures of arousal and the SCR and between the self-report measure of actual driving behaviour and the objective driving data (as assessed via the GPS devices). Conclusions This study provides insights into how psychophysiological and GPS devices could be used as objective measures in conjunction with self-report measures to further understand the persuasive processes and outcomes of emotion-based anti-speeding advertisements.

Localization of type 1 diabetes susceptibility to the MHC class I genes HLA-B and HLA-A

The major histocompatibility complex (MHC) on chromosome 6 is associated with susceptibility to more common diseases than any other region of the human genome, including almost all disorders classified as autoimmune. In type 1 diabetes the major genetic susceptibility determinants have been mapped to the MHC class II genes HLA-DQB1 and HLA-DRB1 (refs 1–3), but these genes cannot completely explain the association between type 1 diabetes and the MHC region4, 5, 6, 7, 8, 9, 10, 11. Owing to the region's extreme gene density, the multiplicity of disease-associated alleles, strong associations between alleles, limited genotyping capability, and inadequate statistical approaches and sample sizes, which, and how many, loci within the MHC determine susceptibility remains unclear. Here, in several large type 1 diabetes data sets, we analyse a combined total of 1,729 polymorphisms, and apply statistical methods—recursive partitioning and regression...

New genetic loci link adipose and insulin biology to body fat distribution

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10−8). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms.

Genetic studies of body mass index yield new insights for obesity biology

Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P < 5 × 10−8), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for ~2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.

A mega-analysis of genome-wide association studies for major depressive disorder

Prior genome-wide association studies (GWAS) of major depressive disorder (MDD) have met with limited success. We sought to increase statistical power to detect disease loci by conducting a GWAS mega-analysis for MDD. In the MDD discovery phase, we analyzed more than 1.2 million autosomal and X chromosome single-nucleotide polymorphisms (SNPs) in 18 759 independent and unrelated subjects of recent European ancestry (9240 MDD cases and 9519 controls). In the MDD replication phase, we evaluated 554 SNPs in independent samples (6783 MDD cases and 50 695 controls). We also conducted a cross-disorder meta-analysis using 819 autosomal SNPs with P<0.0001 for either MDD or the Psychiatric GWAS Consortium bipolar disorder (BIP) mega-analysis (9238 MDD cases/8039 controls and 6998 BIP cases/7775 controls). No SNPs achieved genome-wide significance in the MDD discovery phase, the MDD replication phase or in pre-planned secondary analyses (by sex, recurrent MDD, recurrent early-onset MDD, age of onset, pre-pubertal onset MDD or typical-like MDD from a latent class analyses of the MDD criteria). In the MDD-bipolar cross-disorder analysis, 15 SNPs exceeded genome-wide significance (P<5 x 10(-8)), and all were in a 248 kb interval of high LD on 3p21.1 (chr3:52 425 083-53 822 102, minimum P=5.9 x 10(-9) at rs2535629). Although this is the largest genome-wide analysis of MDD yet conducted, its high prevalence means that the sample is still underpowered to detect genetic effects typical for complex traits. Therefore, we were unable to identify robust and replicable findings. We discuss what this means for genetic research for MDD. The 3p21.1 MDD-BIP finding should be interpreted with caution as the most significant SNP did not replicate in MDD samples, and genotyping in independent samples will be needed to resolve its status.

Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs

Most psychiatric disorders are moderately to highly heritable. The degree to which genetic variation is unique to individual disorders or shared across disorders is unclear. To examine shared genetic etiology, we use genome-wide genotype data from the Psychiatric Genomics Consortium (PGC) for cases and controls in schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorders (ASD) and attention-deficit/hyperactivity disorder (ADHD). We apply univariate and bivariate methods for the estimation of genetic variation within and covariation between disorders. SNPs explained 17-29% of the variance in liability. The genetic correlation calculated using common SNPs was high between schizophrenia and bipolar disorder (0.68 +/- 0.04 s.e.), moderate between schizophrenia and major depressive disorder (0.43 +/- 0.06 s.e.), bipolar disorder and major depressive disorder (0.47 +/- 0.06 s.e.), and ADHD and major depressive disorder (0.32 +/- 0.07 s.e.), low between schizophrenia and ASD (0.16 +/- 0.06 s.e.) and non-significant for other pairs of disorders as well as between psychiatric disorders and the negative control of Crohn's disease. This empirical evidence of shared genetic etiology for psychiatric disorders can inform nosology and encourages the investigation of common pathophysiologies for related disorders.

Genome-wide association study of major depressive disorder: New results, meta-analysis, and lessons learned

Major depressive disorder (MDD) is a common complex disorder with a partly genetic etiology. We conducted a genome-wide association study of the MDD2000+ sample (2431 cases, 3673 screened controls and >1 M imputed single-nucleotide polymorphisms (SNPs)). No SNPs achieved genome-wide significance either in the MDD2000+ study, or in meta-analysis with two other studies totaling 5763 cases and 6901 controls. These results imply that common variants of intermediate or large effect do not have main effects in the genetic architecture of MDD. Suggestive but notable results were: (a) gene-based tests suggesting roles for adenylate cyclase 3 (ADCY3, 2p23.3) and galanin (GAL, 11q13.3); published functional evidence relates both of these to MDD and serotonergic signaling; (b) support for the bipolar disorder risk variant SNP rs1006737 in CACNA1C (P=0.020, odds ratio=1.10), and; (c) lack of support for rs2251219, a SNP identified in a meta-analysis of affective disorder studies (P=0.51). We estimate that sample sizes 1.8- to 2.4-fold greater are needed for association studies of MDD compared with those for schizophrenia to detect variants that explain the same proportion of total variance in liability. Larger study cohorts characterized for genetic and environmental risk factors accumulated prospectively are likely to be needed to dissect more fully the etiology of MDD.

FTO genotype is associated with phenotypic variability of body mass index

There is evidence across several species for genetic control of phenotypic variation of complex traits1, 2, 3, 4, such that the variance among phenotypes is genotype dependent. Understanding genetic control of variability is important in evolutionary biology, agricultural selection programmes and human medicine, yet for complex traits, no individual genetic variants associated with variance, as opposed to the mean, have been identified. Here we perform a meta-analysis of genome-wide association studies of phenotypic variation using ~170,000 samples on height and body mass index (BMI) in human populations. We report evidence that the single nucleotide polymorphism (SNP) rs7202116 at the FTO gene locus, which is known to be associated with obesity (as measured by mean BMI for each rs7202116 genotype)5, 6, 7, is also associated with phenotypic variability. We show that the results are not due to scale effects or other artefacts, and find no other experiment-wise significant evidence for effects on variability, either at loci other than FTO for BMI or at any locus for height. The difference in variance for BMI among individuals with opposite homozygous genotypes at the FTO locus is approximately 7%, corresponding to a difference of ~0.5 kilograms in the standard deviation of weight. Our results indicate that genetic variants can be discovered that are associated with variability, and that between-person variability in obesity can partly be explained by the genotype at the FTO locus. The results are consistent with reported FTO by environment interactions for BMI8, possibly mediated by DNA methylation9, 10. Our BMI results for other SNPs and our height results for all SNPs suggest that most genetic variants, including those that influence mean height or mean BMI, are not associated with phenotypic variance, or that their effects on variability are too small to detect even with samples sizes greater than 100,000.

GWAS of butyrylcholinesterase activity identifies four novel loci, independent effects within BCHE and secondary associations with metabolic risk factors

Serum butyrylcholinesterase (BCHE) activity is associated with obesity, blood pressure and biomarkers of cardiovascular and diabetes risk. We have conducted a genome-wide association scan to discover genetic variants affecting BCHE activity, and to clarify whether the associations between BCHE activity and cardiometabolic risk factors are caused by variation in BCHE or whether BCHE variation is secondary to the metabolic abnormalities. We measured serum BCHE in adolescents and adults from three cohorts of Australian twin and family studies. The genotypes from approximately 2.4 million single-nucleotide polymorphisms (SNPs) were available in 8791 participants with BCHE measurements. We detected significant associations with BCHE activity at three independent groups of SNPs at the BCHE locus (P = 5.8 x 10(-262), 7.8 x 10(-47), 2.9 x 10(-12)) and at four other loci: RNPEP (P = 9.4 x 10(-16)), RAPH1-ABI2 (P = 4.1 x 10(-18)), UGT1A1 (P = 4.0 x 10(-8)) and an intergenic region on chromosome 8 (P = 1.4 x 10(-8)). These loci affecting BCHE activity were not associated with metabolic risk factors. On the other hand, SNPs in genes previously associated with metabolic risk had effects on BCHE activity more often than can be explained by chance. In particular, SNPs within FTO and GCKR were associated with BCHE activity, but their effects were partly mediated by body mass index and triglycerides, respectively. We conclude that variation in BCHE activity is due to multiple variants across the spectrum from uncommon/large effect to common/small effect, and partly results from (rather than causes) metabolic abnormalities.

The use of neurocognitive methods in assessing health communication messages: A systematic review

We review 20 studies that examined persuasive processing and outcomes of health messages using neurocognitive measures. The results suggest that cognitive processes and neural activity in regions thought to reflect self-related processing may be more prominent in the persuasive process of self-relevant messages. Furthermore, activity in the medial prefrontal cortex (MPFC), the superior temporal gyrus, and the middle frontal gyrus were identified as predictors of message effectiveness, with the MPFC accounting for additional variance in behaviour change beyond that accounted for by self-report measures. Incorporating neurocognitive measures may provide a more comprehensive understanding of the processing and outcomes of health messages.

Public Demand for Safer Speeds: Identification of Interventions for Trial

Speeding is a major contributor to road injuries and fatalities and remains prevalent. Changing community perceptions about speeding is an important priority. Austroads commissioned research to identify a range of potential interventions for future trial and evaluation aimed at creating, increasing, and/or sustaining public demand for safer speeds. This project had three phases: a literature review; consultations with key stakeholders regarding intervention options (including feasibility, and likely benefits and costs of identified interventions); and providing research results, including recommendations for future phases of the program of work. The literature review led to the development of a draft Campaign Strategy targeting nine aims across three themes underpinning this research: 1) creating, 2) increasing, and 3) sustaining public demand for safer speeds on the road. Twenty-one stakeholders commented on the suitability and feasibility of, and likely barriers to, countermeasures within the draft Campaign Strategy and its applicability to the Australian and New Zealand context. There was overwhelming positive support for the proposed Campaign Strategy by the majority of respondents; many, noting that it addressed key misperceptions and complemented many existing approaches. A small number of respondents expressed some concerns with various aspects. Stakeholder feedback was incorporated into the final proposed Campaign Strategy to enhance its potential effectiveness. Wide diversity across jurisdictions makes the recommendation of individual interventions for specific areas problematic. Individual jurisdictions should consider a range of costs and benefits of the proposed Campaign Strategy to determine the likely feasibility from their unique perspective. Issues to be addressed when considering implementation of the proposed Campaign Strategy include speed limit setting policies, resourcing, messaging and advertising strategies, and political will associated with promoting safer speeds.

Directional dominance on stature and cognition in diverse human populations

Homozygosity has long been associated with rare, often devastating, Mendelian disorders1, and Darwin was one of the first to recognize that inbreeding reduces evolutionary fitness2. However, the effect of the more distant parental relatedness that is common in modern human populations is less well understood. Genomic data now allow us to investigate the effects of homozygosity on traits of public health importance by observing contiguous homozygous segments (runs of homozygosity), which are inferred to be homozygous along their complete length. Given the low levels of genome-wide homozygosity prevalent in most human populations, information is required on very large numbers of people to provide sufficient power3, 4. Here we use runs of homozygosity to study 16 health-related quantitative traits in 354,224 individuals from 102 cohorts, and find statistically significant associations between summed runs of homozygosity and four complex traits: height, forced expiratory lung volume in one second, general cognitive ability and educational attainment (P < 1 × 10−300, 2.1 × 10−6, 2.5 × 10−10 and 1.8 × 10−10, respectively). In each case, increased homozygosity was associated with decreased trait value, equivalent to the offspring of first cousins being 1.2 cm shorter and having 10 months’ less education. Similar effect sizes were found across four continental groups and populations with different degrees of genome-wide homozygosity, providing evidence that homozygosity, rather than confounding, directly contributes to phenotypic variance. Contrary to earlier reports in substantially smaller samples5, 6, no evidence was seen of an influence of genome-wide homozygosity on blood pressure and low density lipoprotein cholesterol, or ten other cardio-metabolic traits. Since directional dominance is predicted for traits under directional evolutionary selection7, this study provides evidence that increased stature and cognitive function have been positively selected in human evolution, whereas many important risk factors for late-onset complex diseases may not have been.