Epigenetic Age Acceleration Assessed with Human White-Matter Images

The accurate estimation of age using methylation data has proved a useful and heritable biomarker, with acceleration in epigenetic age predicting a number of age-related phenotypes. Measures of white matter integrity in the brain are also heritable and highly sensitive to both normal and pathological aging processes across adulthood. We consider the phenotypic and genetic interrelationships between epigenetic age acceleration and white matter integrity in humans. Our goal was to investigate processes that underlie interindividual variability in age-related changes in the brain. Using blood taken from a Mexican-American extended pedigree sample (n = 628; age = 23.28-93.11 years), epigenetic age was estimated using the method developed by Horvath (2013). For n = 376 individuals, diffusion tensor imaging scans were also available. The interrelationship between epigenetic age acceleration and global white matter integrity was investigated with variance decomposition methods. To test for neuroanatomical specificity, 16 specific tracts were additionally considered. We observed negative phenotypic correlations between epigenetic age acceleration and global white matter tract integrity (ρpheno = -0.119, p = 0.028), with evidence of shared genetic (ρgene = -0.463, p = 0.013) but not environmental influences. Negative phenotypic and genetic correlations with age acceleration were also seen for a number of specific white matter tracts, along with additional negative phenotypic correlations between granulocyte abundance and white matter integrity. These findings (i.e., increased acceleration in epigenetic age in peripheral blood correlates with reduced white matter integrity in the brain and shares common genetic influences) provide a window into the neurobiology of aging processes within the brain and a potential biomarker of normal and pathological brain aging

The genetic basis of the comorbidity between cannabis use and major depression

Background and aims—While the prevalence of major depression is elevated amongst cannabis users, the role of genetics in this pattern of comorbidity is not clear. This study aimed to estimate the heritability of cannabis use and major depression, quantify the genetic overlap between these two traits, and localize regions of the genome that segregate in families with cannabis use and major depression. Design—Family-based univariate and bivariate genetic analysis. Setting—San Antonio, Texas, USA Participants—Genetics of Brain Structure and Function study (GOBS) participants: 1,284 Mexican-Americans from 75 large multi-generation families and an additional 57 genetically unrelated spouses. Measurements—Phenotypes of lifetime history of cannabis use and major depression, measured using the semi-structured MINI-Plus interview. Genotypes measured using ~1M single nucleotide polymorphisms (SNPs) on Illumina BeadChips. A sub-selection of these SNPs were used to build multipoint identity-by-descent matrices for linkage analysis. Findings—Both cannabis use (h2=0.614, p=1.00×10−6, SE=0.151) and major depression (h2=0.349, p=1.06×10−5, SE=0.100) are heritable traits, and there is significant genetic correlation between the two (ρg=0.424, p=0.0364, SE=0.195). Genome-wide linkage scans identify a significant univariate linkage peak for major depression on chromosome 22 (LOD=3.144 at 2cM), with a suggestive peak for cannabis use on chromosome 21 (LOD=2.123 at 37cM). A significant pleiotropic linkage peak influencing both cannabis use and major depression was identified on chromosome 11, using a bivariate model (LOD=3.229 at 112cM). Follow-up of this pleiotropic signal identified a SNP 20kb upstream of NCAM1 (rs7932341) that shows significant bivariate association (p=3.10×10−5). However this SNP is rare (7 minor allele carriers) and does not drive the linkage signal observed. Conclusions—There appears to be significant genetic overlap between cannabis use and major depression among Mexican-Americans, a pleiotropy that appears to be localized to a region on chromosome 11q23 that has been previously linked to these phenotypes

Genome-wide significant loci for addiction and anxiety

Background Psychiatric comorbidity is common among individuals with addictive disorders, with patients frequently suffering from anxiety disorders. While the genetic architecture of comorbid addictive and anxiety disorders remains unclear, elucidating the genes involved could provide important insights into the underlying etiology. Methods Here we examine a sample of 1284 Mexican-Americans from randomly selected extended pedigrees. Variance decomposition methods were used to examine the role of genetics in addiction phenotypes (lifetime history of alcohol dependence, drug dependence or chronic smoking) and various forms of clinically relevant anxiety. Genome-wide univariate and bivariate linkage scans were conducted to localize the chromosomal regions influencing these traits. Results Addiction phenotypes and anxiety were shown to be heritable and univariate genome-wide linkage scans revealed significant quantitative trait loci for drug dependence (14q13.2-q21.2, LOD = 3.322) and a broad anxiety phenotype (12q24.32-q24.33, LOD = 2.918). Significant positive genetic correlations were observed between anxiety and each of the addiction subtypes (ρg = 0.550–0.655) and further investigation with bivariate linkage analyses identified significant pleiotropic signals for alcohol dependence-anxiety (9q33.1-q33.2, LOD = 3.054) and drug dependence-anxiety (18p11.23-p11.22, LOD = 3.425). Conclusions This study confirms the shared genetic underpinnings of addiction and anxiety and identifies genomic loci involved in the etiology of these comorbid disorders. The linkage signal for anxiety on 12q24 spans the location of TMEM132D, an emerging gene of interest from previous GWAS of anxiety traits, whilst the bivariate linkage signal identified for anxiety-alcohol on 9q33 peak coincides with a region where rare CNVs have been associated with psychiatric disorders. Other signals identified implicate novel regions of the genome in addiction genetics

Integrated Risk Assessment for the Blue Economy

With the anticipated boom in the ‘blue economy’ and associated increases in industrialization across the world’s oceans, new and complex risks are being introduced to ocean ecosystems. As a result, conservation and resource management increasingly look to factor in potential interactions among the social, ecological and economic components of these systems. Investigation of these interactions requires interdisciplinary frameworks that incorporate methods and insights from across the social and biophysical sciences. Risk assessment methods, which have been developed across numerous disciplines and applied to various real-world settings and problems, provide a unique connection point for cross-disciplinary engagement. However, research on risk is often conducted in distinct spheres by experts whose focus is on narrow sources or outcomes of risk. Movement toward a more integrated treatment of risk to ensure a balanced approach to developing and managing ocean resources requires cross-disciplinary engagement and understanding. Here, we provide a primer on risk assessment intended to encourage the development and implementation of integrated risk assessment processes in the emerging blue economy. First, we summarize the dominant framework for risk in the ecological/biophysical sciences. Then, we discuss six key insights from the long history of risk research in the social sciences that can inform integrated assessments of risk: (1) consider the subjective nature of risk, (2) understand individual social and cultural influences on risk perceptions, (3) include diverse expertise, (4) consider the social scales of analysis, (5) incorporate quantitative and qualitative approaches, and (6) understand interactions and feedbacks within systems. Finally, we show how these insights can be incorporated into risk assessment and management, and apply them to a case study of whale entanglements in fishing gear off the United States west coast

Development of core entrustable professional activities linked to a competency-based veterinary education framework

Purpose: Despite the adoption of competency-based education in some veterinary schools over the past 15 years, only recently has a concerted effort been directed toward this in veterinary education internationally. Methods: In 2015, educational leaders from the Association of American Veterinary Medical Colleges (AAVMC) member schools came together with a strong call to action to create shared tools for clinical competency assessment. Results: This resulted in the formation of the AAVMC Competency-Based Veterinary Education (CBVE) Working Group, which then embarked on the creation of a shared competency framework and the development of eight core entrustable professional activities (EPAs) linked to this framework. Conclusions: This paper will report on the development of these EPAs and their integration with the concurrently-developed CBVE Framework

Fine-mapping of the HNF1B multicancer locus identifies candidate variants that mediate endometrial cancer risk.

Common variants in the hepatocyte nuclear factor 1 homeobox B (HNF1B) gene are associated with the risk of Type II diabetes and multiple cancers. Evidence to date indicates that cancer risk may be mediated via genetic or epigenetic effects on HNF1B gene expression. We previously found single-nucleotide polymorphisms (SNPs) at the HNF1B locus to be associated with endometrial cancer, and now report extensive fine-mapping and in silico and laboratory analyses of this locus. Analysis of 1184 genotyped and imputed SNPs in 6608 Caucasian cases and 37 925 controls, and 895 Asian cases and 1968 controls, revealed the best signal of association for SNP rs11263763 (P = 8.4 × 10(-14), odds ratio = 0.86, 95% confidence interval = 0.82-0.89), located within HNF1B intron 1. Haplotype analysis and conditional analyses provide no evidence of further independent endometrial cancer risk variants at this locus. SNP rs11263763 genotype was associated with HNF1B mRNA expression but not with HNF1B methylation in endometrial tumor samples from The Cancer Genome Atlas. Genetic analyses prioritized rs11263763 and four other SNPs in high-to-moderate linkage disequilibrium as the most likely causal SNPs. Three of these SNPs map to the extended HNF1B promoter based on chromatin marks extending from the minimal promoter region. Reporter assays demonstrated that this extended region reduces activity in combination with the minimal HNF1B promoter, and that the minor alleles of rs11263763 or rs8064454 are associated with decreased HNF1B promoter activity. Our findings provide evidence for a single signal associated with endometrial cancer risk at the HNF1B locus, and that risk is likely mediated via altered HNF1B gene expression

Tumour risks and genotype-phenotype correlations associated with germline variants in succinate dehydrogenase subunit genes SDHB, SDHC and SDHD.

BACKGROUND: Germline pathogenic variants in SDHB/SDHC/SDHD are the most frequent causes of inherited phaeochromocytomas/paragangliomas. Insufficient information regarding penetrance and phenotypic variability hinders optimum management of mutation carriers. We estimate penetrance for symptomatic tumours and elucidate genotype-phenotype correlations in a large cohort of SDHB/SDHC/SDHD mutation carriers. METHODS: A retrospective survey of 1832 individuals referred for genetic testing due to a personal or family history of phaeochromocytoma/paraganglioma. 876 patients (401 previously reported) had a germline mutation in SDHB/SDHC/SDHD (n=673/43/160). Tumour risks were correlated with in silico structural prediction analyses. RESULTS: Tumour risks analysis provided novel penetrance estimates and genotype-phenotype correlations. In addition to tumour type susceptibility differences for individual genes, we confirmed that the SDHD:p.Pro81Leu mutation has a distinct phenotype and identified increased age-related tumour risks with highly destabilising SDHB missense mutations. By Kaplan-Meier analysis, the penetrance (cumulative risk of clinically apparent tumours) in SDHB and (paternally inherited) SDHD mutation-positive non-probands (n=371/67 with detailed clinical information) by age 60 years was 21.8% (95% CI 15.2% to 27.9%) and 43.2% (95% CI 25.4% to 56.7%), respectively. Risk of malignant disease at age 60 years in non-proband SDHB mutation carriers was 4.2%(95% CI 1.1% to 7.2%). With retrospective cohort analysis to adjust for ascertainment, cumulative tumour risks for SDHB mutation carriers at ages 60 years and 80 years were 23.9% (95% CI 20.9% to 27.4%) and 30.6% (95% CI 26.8% to 34.7%). CONCLUSIONS: Overall risks of clinically apparent tumours for SDHB mutation carriers are substantially lower than initially estimated and will improve counselling of affected families. Specific genotype-tumour risk associations provides a basis for novel investigative strategies into succinate dehydrogenase-related mechanisms of tumourigenesis and the development of personalised management for SDHB/SDHC/SDHD mutation carriers