A network analysis to identify mediators of germline-driven differences in breast cancer prognosis.

Identifying the underlying genetic drivers of the heritability of breast cancer prognosis remains elusive. We adapt a network-based approach to handle underpowered complex datasets to provide new insights into the potential function of germline variants in breast cancer prognosis. This network-based analysis studies ~7.3 million variants in 84,457 breast cancer patients in relation to breast cancer survival and confirms the results on 12,381 independent patients. Aggregating the prognostic effects of genetic variants across multiple genes, we identify four gene modules associated with survival in estrogen receptor (ER)-negative and one in ER-positive disease. The modules show biological enrichment for cancer-related processes such as G-alpha signaling, circadian clock, angiogenesis, and Rho-GTPases in apoptosis

The relevance of WHO injury surveillance guidelines for evaluation: learning from the aboriginal community-centered injury surveillance system (ACCISS) and two institution-based systems

<p>Abstract</p> <p>Background</p> <p>Over the past three decades, the capacity to develop and implement injury surveillance systems (ISS) has grown worldwide and is reflected by the diversity of data gathering environments in which ISS operate. The capacity to evaluate ISS, however, is less advanced and existing evaluation guidelines are ambiguous. Furthermore, the applied relevance of these guidelines to evaluate ISS operating in various settings is unclear. The aim of this paper was to examine how the World Health Organization (WHO) injury surveillance guidelines have been applied to evaluate systems operating in three different contexts.</p> <p>Methods</p> <p>The attributes of a good surveillance system as well as instructions for conducting evaluations, outlined in the WHO injury surveillance guidelines, were used to develop an analytical framework. Using this framework, a comparative analysis of the application of the guidelines was conducted using; the Aboriginal Community-Centered Injury Surveillance System (ACCISS) from Canada, the Shantou-Emergency Department Injury Surveillance Project (S-EDISP) from China, and the Yorkhill-Canadian Hospitals Injury Reporting and Prevention Program (Y-CHIRPP) imported from Canada and implemented in Scotland.</p> <p>Results</p> <p>The WHO guidelines provide only a basic platform for evaluation. The guidelines over emphasize epidemiologic attributes and methods and under emphasize public health and injury prevention perspectives requiring adaptation for context-based relevance. Evaluation elements related to the dissemination and use of knowledge, acceptability, and the sustainability of ISS are notably inadequate. From a public health perspective, alternative reference points are required for re-conceptualizing evaluation paradigms. This paper offers an ISS evaluation template that considers how the WHO guidelines could be adapted and applied.</p> <p>Conclusions</p> <p>Findings suggest that attributes of a good surveillance system, when used as evaluation metrics, cannot be weighted equally across ISS. In addition, the attribute of acceptability likely holds more relevance than previously recognized and should be viewed as a critical underpinning attribute of ISS. Context-oriented evaluations sensitive to distinct operational environments are more likely to address knowledge gaps related to; understanding links between the production of injury data and its use, and the effectiveness, impact, and sustainability of ISS. Current frameworks are predisposed to disassociating epidemiologic approaches from subjective factors and social processes.</p

Treatment- and population-specific genetic risk factors for anti-drug antibodies against interferon-beta: a GWAS

BackgroundUpon treatment with biopharmaceuticals, the immune system may produce anti-drug antibodies (ADA) that inhibit the therapy. Up to 40% of multiple sclerosis patients treated with interferon beta (IFN beta) develop ADA, for which a genetic predisposition exists. Here, we present a genome-wide association study on ADA and predict the occurrence of antibodies in multiple sclerosis patients treated with different interferon beta preparations.MethodsWe analyzed a large sample of 2757 genotyped and imputed patients from two cohorts (Sweden and Germany), split between a discovery and a replication dataset. Binding ADA (bADA) levels were measured by capture-ELISA, neutralizing ADA (nADA) titers using a bioassay. Genome-wide association analyses were conducted stratified by cohort and treatment preparation, followed by fixed-effects meta-analysis.ResultsBinding ADA levels and nADA titers were correlated and showed a significant heritability (47% and 50%, respectively). The risk factors differed strongly by treatment preparation: The top-associated and replicated variants for nADA presence were the HLA-associated variants rs77278603 in IFN beta -1a s.c.- (odds ratio (OR)=3.55 (95% confidence interval=2.81-4.48), p=2.1x10(-26)) and rs28366299 in IFN beta -1b s.c.-treated patients (OR=3.56 (2.69-4.72), p=6.6x10(-19)). The rs77278603-correlated HLA haplotype DR15-DQ6 conferred risk specifically for IFN beta -1a s.c. (OR=2.88 (2.29-3.61), p=7.4x10(-20)) while DR3-DQ2 was protective (OR=0.37 (0.27-0.52), p=3.7x10(-09)). The haplotype DR4-DQ3 was the major risk haplotype for IFN beta -1b s.c. (OR=7.35 (4.33-12.47), p=1.5x10(-13)). These haplotypes exhibit large population-specific frequency differences. The best prediction models were achieved for ADA in IFN beta -1a s.c.-treated patients. Here, the prediction in the Swedish cohort showed AUC=0.91 (0.85-0.95), sensitivity=0.78, and specificity=0.90;patients with the top 30% of genetic risk had, compared to patients in the bottom 30%, an OR =73.9 (11.8-463.6, p=4.4x10(-6)) of developing nADA. In the German cohort, the AUC of the same model was 0.83 (0.71-0.92), sensitivity=0.80, specificity=0.76, with an OR=13.8 (3.0-63.3, p=7.5x10(-4)).ConclusionsWe identified several HLA-associated genetic risk factors for ADA against interferon beta, which were specific for treatment preparations and population backgrounds. Genetic prediction models could robustly identify patients at risk for developing ADA and might be used for personalized therapy recommendations and stratified ADA screening in clinical practice. These analyses serve as a roadmap for genetic characterizations of ADA against other biopharmaceutical compounds

Genome-wide Association Study of Platelet Count Identifies Ancestry-Specific Loci in Hispanic/Latino Americans

Platelets play an essential role in hemostasis and thrombosis. We performed a genome-wide association study of platelet count in 12,491 participants of the Hispanic Community Health Study/Study of Latinos by using a mixed-model method that accounts for admixture and family relationships. We discovered and replicated associations with five genes (ACTN1, ETV7, GABBR1-MOG, MEF2C, and ZBTB9-BAK1). Our strongest association was with Amerindian-specific variant rs117672662 (p value = 1.16 × 10−28) in ACTN1, a gene implicated in congenital macrothrombocytopenia. rs117672662 exhibited allelic differences in transcriptional activity and protein binding in hematopoietic cells. Our results underscore the value of diverse populations to extend insights into the allelic architecture of complex traits

A network analysis to identify mediators of germline-driven differences in breast cancer prognosis

cited By 0Identifying the underlying genetic drivers of the heritability of breast cancer prognosis remains elusive. We adapt a network-based approach to handle underpowered complex datasets to provide new insights into the potential function of germline variants in breast cancer prognosis. This network-based analysis studies similar to 7.3 million variants in 84,457 breast cancer patients in relation to breast cancer survival and confirms the results on 12,381 independent patients. Aggregating the prognostic effects of genetic variants across multiple genes, we identify four gene modules associated with survival in estrogen receptor (ER)-negative and one in ER-positive disease. The modules show biological enrichment for cancer-related processes such as G-alpha signaling, circadian clock, angiogenesis, and Rho-GTPases in apoptosis.Peer reviewe

Ageing increases reliance on sensorimotor prediction through structural and functional differences in frontostriatal circuits

This is the author accepted manuscript. It is currently under an indefinite embargo pending publication by Nature Publishing Group.The control of voluntary movement changes markedly with age. A critical component of motor control is the integration of sensory information with predictions of the consequences of action, arising from internal models of movement. This leads to sensorimotor attenuation – a reduction in the perceived intensity of sensations from self-generated compared to external actions. Here we show that sensorimotor attenuation occurs in 98% of adults in a population-based cohort (n=325; 18-88 years; the Cambridge Centre for Ageing and Neuroscience). Importantly, attenuation increases with age, in proportion to reduced sensory sensitivity. This effect is associated with differences in the structure and functional connectivity of the pre-supplementary motor area (pre-SMA), assessed with magnetic resonance imaging. The results suggest that ageing alters the balance between the sensorium and predictive models, mediated by the pre-SMA and its connectivity in frontostriatal circuits. This shift may contribute to the motor and cognitive changes observed with age.Cam-CAN research was supported by the Biotechnology and Biological Sciences Research Council (BB/H008217/1). JBR and NW were supported by the James S. McDonnell Foundation 21st Century Science Initiative, Scholar Award in Understanding Human Cognition. JBR was also supported by Wellcome Trust [103838] and the Medical Research Council [MC-A060-5PQ30]. DMW was supported by the Wellcome Trust [097803], Human Frontier Science Program and the Royal Society Noreen Murray Professorship in Neurobiology. RNH was supported by the Medical Research Council [MC-A060-5PR10]. RAK was supported by a Sir Henry Wellcome Trust Postdoctoral Fellowship [107392]. LG was funded by a Rubicon grant from the Netherlands Organisation for Scientific Research (NWO)

Poorer White Matter Microstructure Predicts Slower and More Variable Reaction Time Performance: Evidence for a Neural Noise Hypothesis in a Large Lifespan Cohort

Most prior research has focused on characterizing averages in cognition, brain characteristics, or behavior, and attempting to predict differences in these averages among individuals. However, this overwhelming focus on mean levels may leave us with an incomplete picture of what drives individual differences in behavioral phenotypes by ignoring the variability of behavior around an individual's mean. In particular, enhanced white matter (WM) structural microstructure has been hypothesized to support consistent behavioral performance by decreasing Gaussian noise in signal transfer. Conversely, lower indices of WM microstructure are associated with greater within-subject variance in the ability to deploy performance-related resources, especially in clinical populations. We tested a mechanistic account of the “neural noise” hypothesis in a large adult lifespan cohort (Cambridge Centre for Ageing and Neuroscience) with over 2500 adults (ages 18-102; 1508 female; 1173 male; 2681 behavioral sessions; 708 MRI scans) using WM fractional anisotropy to predict mean levels and variability in reaction time performance on a simple behavioral task using a dynamic structural equation model. By modeling robust and reliable individual differences in within-person variability, we found support for a neural noise hypothesis (Kail, 1997), with lower fractional anisotropy predicted individual differences in separable components of behavioral performance estimated using dynamic structural equation model, including slower mean responses and increased variability. These effects remained when including age, suggesting consistent effects of WM microstructure across the adult lifespan unique from concurrent effects of aging. Crucially, we show that variability can be reliably separated from mean performance using advanced modeling tools, enabling tests of distinct hypotheses for each component of performance

Genome-wide association study of germline variants and breast cancer-specific mortality.

BackgroundWe examined the associations between germline variants and breast cancer mortality using a large meta-analysis of women of European ancestry.MethodsMeta-analyses included summary estimates based on Cox models of twelve datasets using ~10.4 million variants for 96,661 women with breast cancer and 7697 events (breast cancer-specific deaths). Oestrogen receptor (ER)-specific analyses were based on 64,171 ER-positive (4116) and 16,172 ER-negative (2125) patients. We evaluated the probability of a signal to be a true positive using the Bayesian false discovery probability (BFDP).ResultsWe did not find any variant associated with breast cancer-specific mortality at P &lt; 5 × 10-8. For ER-positive disease, the most significantly associated variant was chr7:rs4717568 (BFDP = 7%, P = 1.28 × 10-7, hazard ratio [HR] = 0.88, 95% confidence interval [CI] = 0.84-0.92); the closest gene is AUTS2. For ER-negative disease, the most significant variant was chr7:rs67918676 (BFDP = 11%, P = 1.38 × 10-7, HR = 1.27, 95% CI = 1.16-1.39); located within a long intergenic non-coding RNA gene (AC004009.3), close to the HOXA gene cluster.ConclusionsWe uncovered germline variants on chromosome 7 at BFDP &lt; 15% close to genes for which there is biological evidence related to breast cancer outcome. However, the paucity of variants associated with mortality at genome-wide significance underpins the challenge in providing genetic-based individualised prognostic information for breast cancer patients

Combined Associations of a Polygenic Risk Score and Classical Risk Factors With Breast Cancer Risk.

We evaluated the joint associations between a new 313-variant PRS (PRS313) and questionnaire-based breast cancer risk factors for women of European ancestry, using 72 284 cases and 80 354 controls from the Breast Cancer Association Consortium. Interactions were evaluated using standard logistic regression and a newly developed case-only method for breast cancer risk overall and by estrogen receptor status. After accounting for multiple testing, we did not find evidence that per-standard deviation PRS313 odds ratio differed across strata defined by individual risk factors. Goodness-of-fit tests did not reject the assumption of a multiplicative model between PRS313 and each risk factor. Variation in projected absolute lifetime risk of breast cancer associated with classical risk factors was greater for women with higher genetic risk (PRS313 and family history) and, on average, 17.5% higher in the highest vs lowest deciles of genetic risk. These findings have implications for risk prevention for women at increased risk of breast cancer