Genome-wide meta-analysis identifies 56 bone mineral density loci and reveals 14 loci associated with risk of fracture

Bone mineral density (BMD) is the most widely used predictor of fracture risk. We performed the largest meta-analysis to date on lumbar spine and femoral neck BMD, including 17 genome-wide association studies and 32,961 individuals of European and east Asian ancestry. We tested the top BMD-associated markers for replication in 50,933 independent subjects and for association with risk of low-trauma fracture in 31,016 individuals with a history of fracture (cases) and 102,444 controls. We identified 56 loci (32 new) associated with BMD at genome-wide significance (P < 5 × 10−8). Several of these factors cluster within the RANK-RANKL-OPG, mesenchymal stem cell differentiation, endochondral ossification and Wnt signaling pathways. However, we also discovered loci that were localized to genes not known to have a role in bone biology. Fourteen BMD-associated loci were also associated with fracture risk (P < 5 × 10−4, Bonferroni corrected), of which six reached P < 5 × 10−8, including at 18p11.21 (FAM210A), 7q21.3 (SLC25A13), 11q13.2 (LRP5), 4q22.1 (MEPE), 2p16.2 (SPTBN1) and 10q21.1 (DKK1). These findings shed light on the genetic architecture and pathophysiological mechanisms underlying BMD variation and fracture susceptibility.

Genome-wide association study of CNVs in 16,000 cases of eight common diseases and 3,000 shared controls

Copy number variants (CNVs) account for a major proportion of human genetic polymorphism and have been predicted to have an important role in genetic susceptibility to common disease. To address this we undertook a large, direct genome-wide study of association between CNVs and eight common human diseases. Using a purpose-designed array we typed 19,000 individuals into distinct copy-number classes at 3,432 polymorphic CNVs, including an estimated 50% of all common CNVs larger than 500 base pairs. We identified several biological artefacts that lead to false-positive associations, including systematic CNV differences between DNAs derived from blood and cell lines. Association testing and follow-up replication analyses confirmed three loci where CNVs were associated with diseaseIRGM for Crohns disease, HLA for Crohns disease, rheumatoid arthritis and type 1 diabetes, and TSPAN8 for type 2 diabetesalthough in each case the locus had previously been identified in single nucleotide polymorphism (SNP)-based studies, reflecting our observation that most common CNVs that are well-typed on our array are well tagged by SNPs and so have been indirectly explored through SNP studies. We conclude that common CNVs that can be typed on existing platforms are unlikely to contribute greatly to the genetic basis of common human diseases. © 2010 Macmillan Publishers Limited. All rights reserved.

Common variants in the region around Osterix are associated with bone mineral density and growth in childhood

Peak bone mass achieved in adolescence is a determinant of bone mass in later life. In order to identify genetic variants affecting bone mineral density (BMD), we performed a genome-wide association study of BMD and related traits in 1518 children from the Avon Longitudinal Study of Parents and Children (ALSPAC). We compared results with a scan of 134 adults with high or low hip BMD. We identified associations with BMD in an area of chromosome 12 containing the Osterix (SP7) locus, a transcription factor responsible for regulating osteoblast differentiation (ALSPAC: P = 5.8 × 10-4; Australia: P = 3.7 × 10-4). This region has previously shown evidence of association with adult hip and lumbar spine BMD in an Icelandic population, as well as nominal association in a UK population. A meta-analysis of these existing studies revealed strong association between SNPs in the Osterix region and adult lumbar spine BMD (P = 9.9 × 10-11). In light of these findings, we genotyped a further 3692 individuals from ALSPAC who had whole body BMD and confirmed the association in children as well (P = 5.4 × 10-5). Moreover, all SNPs were related to height in ALSPAC children, but not weight or body mass index, and when height was included as a covariate in the regression equation, the association with total body BMD was attenuated. We conclude that genetic variants in the region of Osterix are associated with BMD in children and adults probably through primary effects on growth.

Genome-wide association study identifies eight loci associated with blood pressure

Elevated blood pressure is a common, heritable cause of cardiovascular disease worldwide. To date, identification of common genetic variants influencing blood pressure has proven challenging. We tested 2.5 million genotyped and imputed SNPs for association with systolic and diastolic blood pressure in 34,433 subjects of European ancestry from the Global BPgen consortium and followed up findings with direct genotyping (N 71,225 European ancestry, N 12,889 Indian Asian ancestry) and in silico comparison (CHARGE consortium, N = 29,136). We identified association between systolic or diastolic blood pressure and common variants in eight regions near the CYP17A1 (P = 7 × 10 24), CYP1A2 (P = 1 × 10 23), FGF5 (P = 1 × 10 21), SH2B3 (P = 3 × 10 18), MTHFR (P = 2 × 10 13), c10orf107 (P = 1 × 10 9), ZNF652 (P = 5 × 10 9) and PLCD3 (P = 1 × 10 8) genes. All variants associated with continuous blood pressure were associated with dichotomous hypertension. These associations between common variants and blood pressure and hypertension offer mechanistic insights into the regulation of blood pressure and may point to novel targets for interventions to prevent cardiovascular disease.

Genetic analyses in a sample of individuals with high or low BMD shows association with multiple Wnt pathway genes

INTRODUCTION Although the high heritability of BMD variation has long been established, few genes have been conclusively shown to affect the variation of BMD in the general population. Extreme truncate selection has been proposed as a more powerful alternative to unselected cohort designs in quantitative trait association studies. We sought to test these theoretical predictions in studies of the bone densitometry measures BMD, BMC, and femoral neck area, by investigating their association with members of the Wnt pathway, some of which have previously been shown to be associated with BMD in much larger cohorts, in a moderate-sized extreme truncate selected cohort (absolute value BMD Z-scores = 1.5-4.0; n = 344). MATERIALS AND METHODS Ninety-six tag-single nucleotide polymorphism (SNPs) lying in 13 Wnt signaling pathway genes were selected to tag common genetic variation (minor allele frequency [MAF] > 5% with an r(2) > 0.8) within 5 kb of all exons of 13 Wnt signaling pathway genes. The genes studied included LRP1, LRP5, LRP6, Wnt3a, Wnt7b, Wnt10b, SFRP1, SFRP2, DKK1, DKK2, FZD7, WISP3, and SOST. Three hundred forty-four cases with either high or low BMD were genotyped by Illumina Goldengate microarray SNP genotyping methods. Association was tested either by Cochrane-Armitage test for dichotomous variables or by linear regression for quantitative traits. RESULTS Strong association was shown with LRP5, polymorphisms of which have previously been shown to influence total hip BMD (minimum p = 0.0006). In addition, polymorphisms of the Wnt antagonist, SFRP1, were significantly associated with BMD and BMC (minimum p = 0.00042). Previously reported associations of LRP1, LRP6, and SOST with BMD were confirmed. Two other Wnt pathway genes, Wnt3a and DKK2, also showed nominal association with BMD. CONCLUSIONS This study shows that polymorphisms of multiple members of the Wnt pathway are associated with BMD variation. Furthermore, this study shows in a practical trial that study designs involving extreme truncate selection and moderate sample sizes can robustly identify genes of relevant effect sizes involved in BMD variation in the general population. This has implications for the design of future genome-wide studies of quantitative bone phenotypes relevant to osteoporosis.

Global, regional, and national incidence, prevalence, and years lived with disability for 301 acute and chronic diseases and injuries in 188 countries, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013

Background Up-to-date evidence about levels and trends in disease and injury incidence, prevalence, and years lived with disability (YLDs) is an essential input into global, regional, and national health policies. In the Global Burden of Disease Study 2013 (GBD 2013), we estimated these quantities for acute and chronic diseases and injuries for 188 countries between 1990 and 2013. Methods Estimates were calculated for disease and injury incidence, prevalence, and YLDs using GBD 2010 methods with some important refi nements. Results for incidence of acute disorders and prevalence of chronic disorders are new additions to the analysis. Key improvements include expansion to the cause and sequelae list, updated systematic reviews, use of detailed injury codes, improvements to the Bayesian meta-regression method (DisMod-MR), and use of severity splits for various causes. An index of data representativeness, showing data availability, was calculated for each cause and impairment during three periods globally and at the country level for 2013. In total, 35 620 distinct sources of data were used and documented to calculated estimates for 301 diseases and injuries and 2337 sequelae. The comorbidity simulation provides estimates for the number of sequelae, concurrently, by individuals by country, year, age, and sex. Disability weights were updated with the addition of new population-based survey data from four countries. Findings Disease and injury were highly prevalent; only a small fraction of individuals had no sequelae. Comorbidity rose substantially with age and in absolute terms from 1990 to 2013. Incidence of acute sequelae were predominantly infectious diseases and short-term injuries, with over 2 billion cases of upper respiratory infections and diarrhoeal disease episodes in 2013, with the notable exception of tooth pain due to permanent caries with more than 200 million incident cases in 2013. Conversely, leading chronic sequelae were largely attributable to non-communicable diseases, with prevalence estimates for asymptomatic permanent caries and tension-type headache of 2∙4 billion and 1∙6 billion, respectively. The distribution of the number of sequelae in populations varied widely across regions, with an expected relation between age and disease prevalence. YLDs for both sexes increased from 537∙6 million in 1990 to 764∙8 million in 2013 due to population growth and ageing, whereas the age-standardised rate decreased little from 114∙87 per 1000 people to 110∙31 per 1000 people between 1990 and 2013. Leading causes of YLDs included low back pain and major depressive disorder among the top ten causes of YLDs in every country. YLD rates per person, by major cause groups, indicated the main drivers of increases were due to musculoskeletal, mental, and substance use disorders, neurological disorders, and chronic respiratory diseases; however HIV/AIDS was a notable driver of increasing YLDs in sub-Saharan Africa. Also, the proportion of disability-adjusted life years due to YLDs increased globally from 21·1% in 1990 to 31·2% in 2013. Interpretation Ageing of the world’s population is leading to a substantial increase in the numbers of individuals with sequelae of diseases and injuries. Rates of YLDs are declining much more slowly than mortality rates. The non-fatal dimensions of disease and injury will require more and more attention from health systems. The transition to nonfatal outcomes as the dominant source of burden of disease is occurring rapidly outside of sub-Saharan Africa. Our results can guide future health initiatives through examination of epidemiological trends and a better understanding of variation across countries.

Association scan of 14,500 nonsynonymous SNPs in four diseases identifies autoimmunity variants

We have genotyped 14,436 nonsynonymous SNPs (nsSNPs) and 897 major histocompatibility complex (MHC) tag SNPs from 1,000 independent cases of ankylosing spondylitis (AS), autoimmune thyroid disease (AITD), multiple sclerosis (MS) and breast cancer (BC). Comparing these data against a common control dataset derived from 1,500 randomly selected healthy British individuals, we report initial association and independent replication in a North American sample of two new loci related to ankylosing spondylitis, ARTS1 and IL23R, and confirmation of the previously reported association of AITD with TSHR and FCRL3. These findings, enabled in part by increased statistical power resulting from the expansion of the control reference group to include individuals from the other disease groups, highlight notable new possibilities for autoimmune regulation and suggest that IL23R may be a common susceptibility factor for the major 'seronegative' diseases.

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...

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks in 188 countries, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013

Background The Global Burden of Disease, Injuries, and Risk Factor study 2013 (GBD 2013) is the first of a series of annual updates of the GBD. Risk factor quantification, particularly of modifiable risk factors, can help to identify emerging threats to population health and opportunities for prevention. The GBD 2013 provides a timely opportunity to update the comparative risk assessment with new data for exposure, relative risks, and evidence on the appropriate counterfactual risk distribution. Methods Attributable deaths, years of life lost, years lived with disability, and disability-adjusted life-years (DALYs) have been estimated for 79 risks or clusters of risks using the GBD 2010 methods. Risk–outcome pairs meeting explicit evidence criteria were assessed for 188 countries for the period 1990–2013 by age and sex using three inputs: risk exposure, relative risks, and the theoretical minimum risk exposure level (TMREL). Risks are organised into a hierarchy with blocks of behavioural, environmental and occupational, and metabolic risks at the first level of the hierarchy. The next level in the hierarchy includes nine clusters of related risks and two individual risks, with more detail provided at levels 3 and 4 of the hierarchy. Compared with GBD 2010, six new risk factors have been added: handwashing practices, occupational exposure to trichloroethylene, childhood wasting, childhood stunting, unsafe sex, and low glomerular filtration rate. For most risks, data for exposure were synthesised with a Bayesian meta-regression method, DisMod-MR 2.0, or spatial-temporal Gaussian process regression. Relative risks were based on meta-regressions of published cohort and intervention studies. Attributable burden for clusters of risks and all risks combined took into account evidence on the mediation of some risks such as high body-mass index (BMI) through other risks such as high systolic blood pressure and high cholesterol. Findings All risks combined account for 57·2% (95% uncertainty interval [UI] 55·8–58·5) of deaths and 41·6% (40·1–43·0) of DALYs. Risks quantified account for 87·9% (86·5–89·3) of cardiovascular disease DALYs, ranging to a low of 0% for neonatal disorders and neglected tropical diseases and malaria. In terms of global DALYs in 2013, six risks or clusters of risks each caused more than 5% of DALYs: dietary risks accounting for 11·3 million deaths and 241·4 million DALYs, high systolic blood pressure for 10·4 million deaths and 208·1 million DALYs, child and maternal malnutrition for 1·7 million deaths and 176·9 million DALYs, tobacco smoke for 6·1 million deaths and 143·5 million DALYs, air pollution for 5·5 million deaths and 141·5 million DALYs, and high BMI for 4·4 million deaths and 134·0 million DALYs. Risk factor patterns vary across regions and countries and with time. In sub-Saharan Africa, the leading risk factors are child and maternal malnutrition, unsafe sex, and unsafe water, sanitation, and handwashing. In women, in nearly all countries in the Americas, north Africa, and the Middle East, and in many other high-income countries, high BMI is the leading risk factor, with high systolic blood pressure as the leading risk in most of Central and Eastern Europe and south and east Asia. For men, high systolic blood pressure or tobacco use are the leading risks in nearly all high-income countries, in north Africa and the Middle East, Europe, and Asia. For men and women, unsafe sex is the leading risk in a corridor from Kenya to South Africa. Interpretation Behavioural, environmental and occupational, and metabolic risks can explain half of global mortality and more than one-third of global DALYs providing many opportunities for prevention. Of the larger risks, the attributable burden of high BMI has increased in the past 23 years. In view of the prominence of behavioural risk factors, behavioural and social science research on interventions for these risks should be strengthened. Many prevention and primary care policy options are available now to act on key risks.

Managing the impacts of sugarcane farming on the Great Barrier Reef: An evaluation of the implementation of the Polluter Pays Principle

This report provides an evaluation of the implementation of the Polluter Pays Principle (PPP) – a principle of international environmental law – in the context of pollution from sugarcane farming affecting Australia’s Great Barrier Reef (GBR). The research was part of an experiment to test methods for evaluating the effectiveness of environmental laws. Overall, we found that whilst the PPP is reflected to a limited extent in Australian law (more so in Queensland law, than at the national level), the behaviour one might expect in terms of implementing the principle was largely inadequate. Evidence of a longer term, explicit commitment to the PPP was particularly weak.

The first episode of psychosis: The experience of relatives

Objective The aim was to determine the extent of and the correlates of the distress and impact of care families of patients with first episode psychosis were experiencing when they first came for treatment. Method Subjects were 238 individuals who had presented with a first episode of psychosis and their family members. Family members were assessed with the Psychological General Well-Being Scale, and the Experience of Caregiving Inventory. Patient data included assessment of positive and negative symptoms, depression, quality of life, and substance use. Results Family members of these first-episode patients were experiencing distress and difficulties. It was the family's appraisal of the impact of the illness that was associated with their psychological well-being. Conclusion As the majority of these first episode families are keen to be involved early and have engaged in an intervention programme, the next step should be an evaluation of their involvement to determine if it is effective.

Generalised growth models for aquatic species with an application to blacklip abalone (Haliotis rubra)

This paper presents a maximum likelihood method for estimating growth parameters for an aquatic species that incorporates growth covariates, and takes into consideration multiple tag-recapture data. Individual variability in asymptotic length, age-at-tagging, and measurement error are also considered in the model structure. Using distribution theory, the log-likelihood function is derived under a generalised framework for the von Bertalanffy and Gompertz growth models. Due to the generality of the derivation, covariate effects can be included for both models with seasonality and tagging effects investigated. Method robustness is established via comparison with the Fabens, improved Fabens, James and a non-linear mixed-effects growth models, with the maximum likelihood method performing the best. The method is illustrated further with an application to blacklip abalone (Haliotis rubra) for which a strong growth-retarding tagging effect that persisted for several months was detected

Improved estimation of size-transition matrices using tag-recapture data

We derive a new method for determining size-transition matrices (STMs) that eliminates probabilities of negative growth and accounts for individual variability. STMs are an important part of size-structured models, which are used in the stock assessment of aquatic species. The elements of STMs represent the probability of growth from one size class to another, given a time step. The growth increment over this time step can be modelled with a variety of methods, but when a population construct is assumed for the underlying growth model, the resulting STM may contain entries that predict negative growth. To solve this problem, we use a maximum likelihood method that incorporates individual variability in the asymptotic length, relative age at tagging, and measurement error to obtain von Bertalanffy growth model parameter estimates. The statistical moments for the future length given an individual's previous length measurement and time at liberty are then derived. We moment match the true conditional distributions with skewed-normal distributions and use these to accurately estimate the elements of the STMs. The method is investigated with simulated tag-recapture data and tag-recapture data gathered from the Australian eastern king prawn (Melicertus plebejus).

Latitudinal and seasonal effects on growth of the Australian eastern king prawn (Melicertus plebejus)

The growth of the Australian eastern king prawn (Melicertus plebejus) is understood in greater detail by quantifying the latitudinal effect. The latitudinal effect is the change in the species' growth rate during migration. Mark-recapture data (N = 1635, latitude 22.21 degrees S-34.00 degrees S) presents northerly movement of the eastern king prawn, with New South Wales prawns showing substantial average movement of 140 km (standard deviation: 176 km) north. A generalized von Bertalanffy growth model framework is used to incorporate the latitudinal effect together with the canonical seasonal effect. Applying this method to eastern king prawn mark-recapture data guarantees consistent estimates for the latitudinal and seasonal effects. For M. plebejus, it was found that growth rate peaks on 25 and 29 January for males and females, respectively; is at a minimum on 27 and 31 July, respectively; and that the shape parameter, k (per year), changes by -0.0236 and -0.0556 every 1 degree of latitude south increase for males and females, respectively.

Does the size of subsamples taken from multispecies trawl catches affect estimates of catch composition and abundance?

Although subsampling is a common method for describing the composition of large and diverse trawl catches, the accuracy of these techniques is often unknown. We determined the sampling errors generated from estimating the percentage of the total number of species recorded in catches, as well as the abundance of each species, at each increase in the proportion of the sorted catch. We completely partitioned twenty prawn trawl catches from tropical northern Australia into subsamples of about 10 kg each. All subsamples were then sorted, and species numbers recorded. Catch weights ranged from 71 to 445 kg, and the number of fish species in trawls ranged from 60 to 138, and invertebrate species from 18 to 63. Almost 70% of the species recorded in catches were "rare" in subsamples (less than one individual per 10 kg subsample or less than one in every 389 individuals). A matrix was used to show the increase in the total number of species that were recorded in each catch as the percentage of the sorted catch increased. Simulation modelling showed that sorting small subsamples (about 10% of catch weights) identified about 50% of the total number of species caught in a trawl. Larger subsamples (50% of catch weight on average) identified about 80% of the total species caught in a trawl. The accuracy of estimating the abundance of each species also increased with increasing subsample size. For the "rare" species, sampling error was around 80% after sorting 10% of catch weight and was just less than 50% after 40% of catch weight had been sorted. For the "abundant" species (five or more individuals per 10 kg subsample or five or more in every 389 individuals), sampling error was around 25% after sorting 10% of catch weight, but was reduced to around 10% after 40% of catch weight had been sorted.