Loss of SORCS2 is Associated with Neuronal DNA Double-Strand Breaks

SORCS2 is one of five proteins that constitute the Vps10p-domain receptor family. Members of this family play important roles in cellular processes linked to neuronal survival, differentiation and function. Genetic and functional studies implicate SORCS2 in cognitive function, as well as in neurodegenerative and psychiatric disorders. DNA damage and DNA repair deficits are linked to ageing and neurodegeneration, and transient neuronal DNA double-strand breaks (DSBs) also occur as a result of neuronal activity. Here, we report a novel role for SORCS2 in DSB formation. We show that SorCS2 loss is associated with elevated DSB levels in the mouse dentate gyrus and that knocking out SORCS2 in a human neuronal cell line increased Topoisomerase IIβ-dependent DSB formation and reduced neuronal viability. Neuronal stimulation had no impact on levels of DNA breaks in vitro, suggesting that the observed differences may not be the result of aberrant neuronal activity in these cells. Our findings are consistent with studies linking the VPS10 receptors and DNA damage to neurodegenerative conditions.

Pulmonary Function and Blood DNA Methylation: A Multiancestry Epigenome-Wide Association Meta-analysis

Rationale: Methylation integrates factors present at birth and modifiable across the lifespan that can influence pulmonary function. Studies are limited in scope and replication. Objectives: To conduct large-scale epigenome-wide meta-analyses of blood DNA methylation and pulmonary function. Methods: Twelve cohorts analyzed associations of methylation at cytosine-phosphate-guanine probes (CpGs), using Illumina 450K or EPIC/850K arrays, with FEV₁, FVC, and FEV₁/FVC. We performed multiancestry epigenome-wide meta-analyses (total of 17,503 individuals; 14,761 European, 2,549 African, and 193 Hispanic/Latino ancestries) and interpreted results using integrative epigenomics. Measurements and Main Results: We identified 1,267 CpGs (1,042 genes) differentially methylated (false discovery rate, <0.025) in relation to FEV₁, FVC, or FEV₁/FVC, including 1,240 novel and 73 also related to chronic obstructive pulmonary disease (1,787 cases). We found 294 CpGs unique to European or African ancestry and 395 CpGs unique to never or ever smokers. The majority of significant CpGs correlated with nearby gene expression in blood. Findings were enriched in key regulatory elements for gene function, including accessible chromatin elements, in both blood and lung. Sixty-nine implicated genes are targets of investigational or approved drugs. One example novel gene highlighted by integrative epigenomic and druggable target analysis is TNFRSF4. Mendelian randomization and colocalization analyses suggest that epigenome-wide association study signals capture causal regulatory genomic loci. Conclusions: We identified numerous novel loci differentially methylated in relation to pulmonary function; few were detected in large genome-wide association studies. Integrative analyses highlight functional relevance and potential therapeutic targets. This comprehensive discovery of potentially modifiable, novel lung function loci expands knowledge gained from genetic studies, providing insights into lung pathogenesis.

Epigenome-wide association study of alcohol consumption in N = 8161 individuals and relevance to alcohol use disorder pathophysiology: identification of the cystine/glutamate transporter SLC7A11 as a top target

Alcohol misuse is common in many societies worldwide and is associated with extensive morbidity and mortality, often leading to alcohol use disorders (AUD) and alcohol-related end-organ damage. The underlying mechanisms contributing to the development of AUD are largely unknown; however, growing evidence suggests that alcohol consumption is strongly associated with alterations in DNA methylation. Identification of alcohol-associated methylomic variation might provide novel insights into pathophysiology and novel treatment targets for AUD. Here we performed the largest single-cohort epigenome-wide association study (EWAS) of alcohol consumption to date (N = 8161) and cross-validated findings in AUD populations with relevant endophenotypes, as well as alcohol-related animal models. Results showed 2504 CpGs significantly associated with alcohol consumption (Bonferroni p value < 6.8 × 10-8) with the five leading probes located in SLC7A11 (p = 7.75 × 10-108), JDP2 (p = 1.44 × 10-56), GAS5 (p = 2.71 × 10-47), TRA2B (p = 3.54 × 10-42), and SLC43A1 (p = 1.18 × 10-40). Genes annotated to associated CpG sites are implicated in liver and brain function, the cellular response to alcohol and alcohol-associated diseases, including hypertension and Alzheimer's disease. Two-sample Mendelian randomization confirmed the causal relationship of consumption on AUD risk (inverse variance weighted (IVW) p = 5.37 × 10-09). A methylation-based predictor of alcohol consumption was able to discriminate AUD cases in two independent cohorts (p = 6.32 × 10-38 and p = 5.41 × 10-14). The top EWAS probe cg06690548, located in the cystine/glutamate transporter SLC7A11, was replicated in an independent cohort of AUD and control participants (N = 615) and showed strong hypomethylation in AUD (p < 10-17). Decreased CpG methylation at this probe was consistently associated with clinical measures including increased heavy drinking days (p < 10-4), increased liver function enzymes (GGT (p = 1.03 × 10-21), ALT (p = 1.29 × 10-6), and AST (p = 1.97 × 10-8)) in individuals with AUD. Postmortem brain analyses documented increased SLC7A11 expression in the frontal cortex of individuals with AUD and animal models showed marked increased expression in liver, suggesting a mechanism by which alcohol leads to hypomethylation-induced overexpression of SLC7A11. Taken together, our EWAS discovery sample and subsequent validation of the top probe in AUD suggest a strong role of abnormal glutamate signaling mediated by methylomic variation in SLC7A11. Our data are intriguing given the prominent role of glutamate signaling in brain and liver and might provide an important target for therapeutic intervention.

Birth weight associations with DNA methylation differences in an adult population

The Developmental Origins of Health and Disease (DOHaD) theory predicts that prenatal and early life events shape adult health outcomes. Birth weight is a useful indicator of the foetal experience and has been associated with multiple adult health outcomes. DNA methylation (DNAm) is one plausible mechanism behind the relationship of birth weight to adult health. Through data linkage between Generation Scotland and historic Scottish birth cohorts, and birth records held through the NHS Information and Statistics Division, a sample of 1,757 individuals with available birth weight and DNAm data was derived. Epigenome-wide association studies (EWAS) were performed in two independently generated DNAm subgroups (nSet1 = 1,395, nSet2 = 362), relating adult DNAm from whole blood to birth weight. Meta-analysis yielded one genome-wide significant CpG site (p = 5.97x10-9), cg00966482. There was minimal evidence for attenuation of the effect sizes for the lead loci upon adjustment for numerous potential confounder variables (body mass index, educational attainment, and socioeconomic status). Associations between birth weight and epigenetic measures of biological age were also assessed. Associations between lower birth weight and higher Grim Age acceleration (p(FDR) = 3.6x10-3) and shorter DNAm-derived telomere length (p(FDR) = 1.7x10-3) are described, although results for three other epigenetic clocks were null. Our results provide support for an association between birth weight and DNAm both locally at one CpG site, and globally via biological ageing estimates.

Identification of epigenome-wide DNA methylation differences between carriers of APOE ε4 and APOE ε2 alleles

BACKGROUND

The apolipoprotein E (APOE) ε4 allele is the strongest genetic risk factor for late onset Alzheimer's disease, whilst the ε2 allele confers protection. Previous studies report differential DNA methylation of APOE between ε4 and ε2 carriers, but associations with epigenome-wide methylation have not previously been characterised.

METHODS

Using the EPIC array, we investigated epigenome-wide differences in whole blood DNA methylation patterns between Alzheimer's disease-free APOE ε4 (n = 2469) and ε2 (n = 1118) carriers from the two largest single-cohort DNA methylation samples profiled to date. Using a discovery, replication and meta-analysis study design, methylation differences were identified using epigenome-wide association analysis and differentially methylated region (DMR) approaches. Results were explored using pathway and methylation quantitative trait loci (meQTL) analyses.

RESULTS

We obtained replicated evidence for DNA methylation differences in a ~ 169 kb region, which encompasses part of APOE and several upstream genes. Meta-analytic approaches identified DNA methylation differences outside of APOE: differentially methylated positions were identified in DHCR24, LDLR and ABCG1 (2.59 × 10-100 ≤ P ≤ 2.44 × 10-8) and DMRs were identified in SREBF2 and LDLR (1.63 × 10-4 ≤ P ≤ 3.01 × 10-2). Pathway and meQTL analyses implicated lipid-related processes and high-density lipoprotein cholesterol was identified as a partial mediator of the methylation differences in ABCG1 and DHCR24.

CONCLUSIONS

APOE ε4 vs. ε2 carrier status is associated with epigenome-wide methylation differences in the blood. The loci identified are located in trans as well as cis to APOE and implicate genes involved in lipid homeostasis.

Epigenome-wide analyses identify DNA methylation signatures of dementia risk

INTRODUCTION

Dementia pathogenesis begins years before clinical symptom onset, necessitating the understanding of premorbid risk mechanisms. Here we investigated potential pathogenic mechanisms by assessing DNA methylation associations with dementia risk factors in Alzheimer's disease (AD)-free participants.

METHODS

Associations between dementia risk measures (family history, AD genetic risk score [GRS], and dementia risk scores [combining lifestyle, demographic, and genetic factors]) and whole-blood DNA methylation were assessed in discovery and replication samples (n = ~400 to ~5000) from Generation Scotland.

RESULTS

AD genetic risk and two dementia risk scores were associated with differential methylation. The GRS associated predominantly with methylation differences in cis but also identified a genomic region implicated in Parkinson disease. Loci associated with dementia risk scores were enriched for those previously associated with body mass index and alcohol consumption.

DISCUSSION

Dementia risk measures show widespread association with blood-based methylation, generating several hypotheses for assessment by future studies.

Characterisation of an inflammation-related epigenetic score and its association with cognitive ability

BACKGROUND

Chronic systemic inflammation has been associated with incident dementia, but its association with age-related cognitive decline is less clear. The acute responses of many inflammatory biomarkers mean they may provide an unreliable picture of the chronicity of inflammation. Recently, a large-scale epigenome-wide association study identified DNA methylation correlates of C-reactive protein (CRP)-a widely used acute-phase inflammatory biomarker. DNA methylation is thought to be relatively stable in the short term, marking it as a potentially useful signature of exposure.

METHODS

We utilise a DNA methylation-based score for CRP and investigate its trajectories with age, and associations with cognitive ability in comparison with serum CRP and a genetic CRP score in a longitudinal study of older adults (n = 889) and a large, cross-sectional cohort (n = 7028).

RESULTS

We identified no homogeneous trajectories of serum CRP with age across the cohorts, whereas the epigenetic CRP score was consistently found to increase with age (standardised β = 0.07 and 0.01) and to do so more rapidly in males compared to females. Additionally, the epigenetic CRP score had higher test-retest reliability compared to serum CRP, indicating its enhanced temporal stability. Higher serum CRP was not found to be associated with poorer cognitive ability (standardised β = - 0.08 and - 0.05); however, a consistent negative association was identified between cognitive ability and the epigenetic CRP score in both cohorts (standardised β = - 0.15 and - 0.08).

CONCLUSIONS

An epigenetic proxy of CRP may provide a more reliable signature of chronic inflammation, allowing for more accurate stratification of individuals, and thus clearer inference of associations with incident health outcomes.

DNA methylation in APOE: The relationship with Alzheimer's and with cardiovascular health

INTRODUCTION

Genetic variation in the apolipoprotein E (APOE) gene is associated with Alzheimer's disease (AD) and risk factors for cardiovascular disease (CVD). DNA methylationat APOE has been associated with altered cognition and AD. It is unclear if epigenetic marks could be used for predicting future disease.

METHODS

We assessed blood-based DNA methylation at 13 CpGs in the APOE gene in 5828 participants from the Generation Scotland (GS) cohort. Using linear mixed models regression, we examined the relationships among APOE methylation, cognition, cholesterol, the family history of AD and the risk for CVD.

RESULTS

DNA methylation at two CpGs was associated with the ratio of total cholesterol and HDL cholesterol, but not with cognition, family history of AD, or the risk of CVD.

DISCUSSION

APOE methylation is associated with the levels of blood cholesterol, but there is no evidence for the utility of APOE methylation as a biomarker for predicting AD or CVD.

Glycosylation of immunoglobulin G is regulated by a large network of genes pleiotropic with inflammatory diseases

Effector functions of immunoglobulin G (IgG) are regulated by the composition of a glycan moiety, thus affecting activity of the immune system. Aberrant glycosylation of IgG has been observed in many diseases, but little is understood about the underlying mechanisms. We performed a genome-wide association study of IgG N-glycosylation (N = 8090) and, using a data-driven network approach, suggested how associated loci form a functional network. We confirmed in vitro that knockdown of IKZF1 decreases the expression of fucosyltransferase FUT8, resulting in increased levels of fucosylated glycans, and suggest that RUNX1 and RUNX3, together with SMARCB1, regulate expression of glycosyltransferase MGAT3. We also show that variants affecting the expression of genes involved in the regulation of glycoenzymes colocalize with variants affecting risk for inflammatory diseases. This study provides new evidence that variation in key transcription factors coupled with regulatory variation in glycogenes modifies IgG glycosylation and has influence on inflammatory diseases.

An epigenome-wide association study of sex-specific chronological ageing

BACKGROUND

Advanced age is associated with cognitive and physical decline and is a major risk factor for a multitude of disorders. There is also a gap in life expectancy between males and females. DNA methylation differences have been shown to be associated with both age and sex. Here, we investigate age-by-sex differences in blood-based DNA methylation in an unrelated cohort of 2586 individuals between the ages of 18 and 87 years, with replication in a further 4450 individuals between the ages of 18 and 93 years.

METHODS

Linear regression models were applied, with stringent genome-wide significance thresholds (p < 3.6 × 10-8) used in both the discovery and replication data. A second, highly conservative mixed linear model method that better controls the false-positive rate was also applied, using the same genome-wide significance thresholds.

RESULTS

Using the linear regression method, 52 autosomal and 597 X-linked CpG sites, mapping to 251 unique genes, replicated with concordant effect size directions in the age-by-sex interaction analysis. The site with the greatest difference mapped to GAGE10, an X-linked gene. Here, DNA methylation levels remained stable across the male adult age range (DNA methylation by age r = 0.02) but decreased across female adult age range (DNA methylation by age r = - 0.61). One site (cg23722529) with a significant age-by-sex interaction also had a quantitative trait locus (rs17321482) that is a genome-wide significant variant for prostate cancer. The mixed linear model method identified 11 CpG sites associated with the age-by-sex interaction.

CONCLUSION

The majority of differences in age-associated DNA methylation trajectories between sexes are present on the X chromosome. Several of these differences occur within genes that have been implicated in sexually dimorphic traits.

A meta-analysis of genome-wide association studies of epigenetic age acceleration

'Epigenetic age acceleration' is a valuable biomarker of ageing, predictive of morbidity and mortality, but for which the underlying biological mechanisms are not well established. Two commonly used measures, derived from DNA methylation, are Horvath-based (Horvath-EAA) and Hannum-based (Hannum-EAA) epigenetic age acceleration. We conducted genome-wide association studies of Horvath-EAA and Hannum-EAA in 13,493 unrelated individuals of European ancestry, to elucidate genetic determinants of differential epigenetic ageing. We identified ten independent SNPs associated with Horvath-EAA, five of which are novel. We also report 21 Horvath-EAA-associated genes including several involved in metabolism (NHLRC, TPMT) and immune system pathways (TRIM59, EDARADD). GWAS of Hannum-EAA identified one associated variant (rs1005277), and implicated 12 genes including several involved in innate immune system pathways (UBE2D3, MANBA, TRIM46), with metabolic functions (UBE2D3, MANBA), or linked to lifespan regulation (CISD2). Both measures had nominal inverse genetic correlations with father's age at death, a rough proxy for lifespan. Nominally significant genetic correlations between Hannum-EAA and lifestyle factors including smoking behaviours and education support the hypothesis that Hannum-based epigenetic ageing is sensitive to variations in environment, whereas Horvath-EAA is a more stable cellular ageing process. We identified novel SNPs and genes associated with epigenetic age acceleration, and highlighted differences in the genetic architecture of Horvath-based and Hannum-based epigenetic ageing measures. Understanding the biological mechanisms underlying individual differences in the rate of epigenetic ageing could help explain different trajectories of age-related decline.

A meta-analysis of genome-wide association studies of epigenetic age acceleration

'Epigenetic age acceleration' is a valuable biomarker of ageing, predictive of morbidity and mortality, but for which the underlying biological mechanisms are not well established. Two commonly used measures, derived from DNA methylation, are Horvath-based (Horvath-EAA) and Hannum-based (Hannum-EAA) epigenetic age acceleration. We conducted genome-wide association studies of Horvath-EAA and Hannum-EAA in 13,493 unrelated individuals of European ancestry, to elucidate genetic determinants of differential epigenetic ageing. We identified ten independent SNPs associated with Horvath-EAA, five of which are novel. We also report 21 Horvath-EAA-associated genes including several involved in metabolism (NHLRC, TPMT) and immune system pathways (TRIM59, EDARADD). GWAS of Hannum-EAA identified one associated variant (rs1005277), and implicated 12 genes including several involved in innate immune system pathways (UBE2D3, MANBA, TRIM46), with metabolic functions (UBE2D3, MANBA), or linked to lifespan regulation (CISD2). Both measures had nominal inverse genetic correlations with father's age at death, a rough proxy for lifespan. Nominally significant genetic correlations between Hannum-EAA and lifestyle factors including smoking behaviours and education support the hypothesis that Hannum-based epigenetic ageing is sensitive to variations in environment, whereas Horvath-EAA is a more stable cellular ageing process. We identified novel SNPs and genes associated with epigenetic age acceleration, and highlighted differences in the genetic architecture of Horvath-based and Hannum-based epigenetic ageing measures. Understanding the biological mechanisms underlying individual differences in the rate of epigenetic ageing could help explain different trajectories of age-related decline.

Identification of novel differentially methylated sites with potential as clinical predictors of impaired respiratory function and COPD

Background

The causes of poor respiratory function and COPD are incompletely understood, but it is clear that genes and the environment play a role. As DNA methylation is under both genetic and environmental control, we hypothesised that investigation of differential methylation associated with these phenotypes would permit mechanistic insights, and improve prediction of COPD. We investigated genome-wide differential DNA methylation patterns using the recently released 850 K Illumina EPIC array. This is the largest single population, whole-genome epigenetic study to date.

Methods

Epigenome-wide association studies (EWASs) of respiratory function and COPD were performed in peripheral blood samples from the Generation Scotland: Scottish Family Health Study (GS:SFHS) cohort (n = 3781; 274 COPD cases and 2919 controls). In independent COPD incidence data (n = 149), significantly differentially methylated sites (DMSs; p < 3.6 × 10⁻⁸) were evaluated for their added predictive power when added to a model including clinical variables, age, sex, height and smoking history using receiver operating characteristic analysis. The Lothian Birth Cohort 1936 (LBC1936) was used to replicate association (n = 895) and prediction (n = 178) results.

Findings

We identified 28 respiratory function and/or COPD associated DMSs, which mapped to genes involved in alternative splicing, JAK-STAT signalling, and axon guidance. In prediction analyses, we observed significant improvement in discrimination between COPD cases and controls (p < .05) in independent GS:SFHS (p = .016) and LBC1936 (p = .010) datasets by adding DMSs to a clinical model.

Interpretation

Identification of novel DMSs has provided insight into the molecular mechanisms regulating respiratory function and aided prediction of COPD risk. Further studies are needed to assess the causality and clinical utility of identified associations.

Fund

Wellcome Trust Strategic Award 10436/Z/14/Z.

Epigenetic prediction of complex traits and death

BACKGROUND

Genome-wide DNA methylation (DNAm) profiling has allowed for the development of molecular predictors for a multitude of traits and diseases. Such predictors may be more accurate than the self-reported phenotypes and could have clinical applications.

RESULTS

Here, penalized regression models are used to develop DNAm predictors for ten modifiable health and lifestyle factors in a cohort of 5087 individuals. Using an independent test cohort comprising 895 individuals, the proportion of phenotypic variance explained in each trait is examined for DNAm-based and genetic predictors. Receiver operator characteristic curves are generated to investigate the predictive performance of DNAm-based predictors, using dichotomized phenotypes. The relationship between DNAm scores and all-cause mortality (n = 212 events) is assessed via Cox proportional hazards models. DNAm predictors for smoking, alcohol, education, and waist-to-hip ratio are shown to predict mortality in multivariate models. The predictors show moderate discrimination of obesity, alcohol consumption, and HDL cholesterol. There is excellent discrimination of current smoking status, poorer discrimination of college-educated individuals and those with high total cholesterol, LDL with remnant cholesterol, and total:HDL cholesterol ratios.

CONCLUSIONS

DNAm predictors correlate with lifestyle factors that are associated with health and mortality. They may supplement DNAm-based predictors of age to identify the lifestyle profiles of individuals and predict disease risk.

Clinically driven analysis reveals gene-socioeconomic status interaction influencing periodontal disease in the electronic health record-linked Generation Scotland: Scottish Family Health Study (GS: SFHS) cohort

IntroductionHeritability (proportion of trait variation attributable to genetic factors) is not a fixed property. It can vary across different social settings and environments. Exploration of gene-environment interaction has been limited by lack of large sample sizes. Biobanks linked to electronic health records pose a solution to this sample size problem. Objectives and ApproachSocial inequalities in periodontal health have been well documented in the dental scientific literature. However, gene-socioeconomic status interaction has yet to be examined. We identified 2,192 cases and 11,525 controls from linked electronic periodontal treatment records within the Generation Scotland: Scottish Family Health Study (GS: SFHS) (www.generationscotland.org). The measure of socioeconomic status used was the Scottish Index of Multiple Deprivation. The objective of this study was to investigate the gene-socioeconomic status interaction within this data. A reaction norm model was used to evaluate the presence of a gene-socioeconomic status interaction in the statistical software ASReml. ResultsWe estimated the heritability of periodontal disease at 10.42% (95% confidence interval 5.97-14.88%). Socioeconomic status modified the heritability of periodontal disease. The heritability of was 13.37%, 0.14% and 11.70% in areas of high, moderate and low deprivation respectively; indicating the occurrence of a gene-socioeconomic status interaction with periodontal disease. These results indicate that socioeconomic status explains a large portion of genetic variation in periodontal disease risk. This information suggests that effective intervention and prevention programs for periodontal disease should involve socioeconomic aspects in their planning, implementations and evaluation. For instance, interventions targeted to reduce smoking in more deprived subjects with a genetic predisposition to periodontal disease could enhance the effect of health promotion strategies in reducing risk. Conclusion/ImplicationsThis study presents contemporary evidence in a large population based cohort that gene-socioeconomic interaction leads to the progression of periodontal disease. This information may lead to the development of better preventative strategies for clinical dentistry.

N-Glycan Profile and Kidney Disease in Type 1 Diabetes

OBJECTIVE

Poorer glycemic control in type 1 diabetes may alter N-glycosylation patterns on circulating glycoproteins, and these alterations may be linked with diabetic kidney disease (DKD). We investigated associations between N-glycans and glycemic control and renal function in type 1 diabetes.

RESEARCH DESIGN AND METHODS

Using serum samples from 818 adults who were considered to have extreme annual loss in estimated glomerular filtration rate (eGFR; i.e., slope) based on retrospective clinical records, from among 6,127 adults in the Scottish Diabetes Research Network Type 1 Bioresource Study, we measured total and IgG-specific N-glycan profiles. This yielded a relative abundance of 39 total (GP) and 24 IgG (IGP) N-glycans. Linear regression models were used to investigate associations between N-glycan structures and HbA_1c, albumin-to-creatinine ratio (ACR), and eGFR slope. Models were adjusted for age, sex, duration of type 1 diabetes, and total serum IgG.

RESULTS

Higher HbA_1c was associated with a lower relative abundance of simple biantennary N-glycans and a higher relative abundance of more complex structures with more branching, galactosylation, and sialylation (GP12, 26, 31, 32, and 34, and IGP19 and 23; all P < 3.79 × 10^-4). Similar patterns were seen for ACR and greater mean annual loss of eGFR, which were also associated with fewer of the simpler N-glycans (all P < 3.79 × 10^-4).

CONCLUSIONS

Higher HbA_1c in type 1 diabetes is associated with changes in the serum N-glycome that have elsewhere been shown to regulate the epidermal growth factor receptor and transforming growth factor-β pathways that are implicated in DKD. Furthermore, N-glycans are associated with ACR and eGFR slope. These data suggest that the role of altered N-glycans in DKD warrants further investigation.

Canine Brachycephaly Is Associated with a Retrotransposon-Mediated Missplicing of SMOC2

In morphological terms, “form” is used to describe an object’s shape and size. In dogs, facial form is stunningly diverse. Facial retrusion, the proximodistal shortening of the snout and widening of the hard palate is common to brachycephalic dogs and is a welfare concern, as the incidence of respiratory distress and ocular trauma observed in this class of dogs is highly correlated with their skull form. Progress to identify the molecular underpinnings of facial retrusion is limited to association of a missense mutation in BMP3 among small brachycephalic dogs. Here, we used morphometrics of skull isosurfaces derived from 374 pedigree and mixed-breed dogs to dissect the genetics of skull form. Through deconvolution of facial forms, we identified quantitative trait loci that are responsible for canine facial shapes and sizes. Our novel insights include recognition that the FGF4 retrogene insertion, previously associated with appendicular chondrodysplasia, also reduces neurocranium size. Focusing on facial shape, we resolved a quantitative trait locus on canine chromosome 1 to a 188-kb critical interval that encompasses SMOC2. An intronic, transposable element within SMOC2 promotes the utilization of cryptic splice sites, causing its incorporation into transcripts, and drastically reduces SMOC2 gene expression in brachycephalic dogs. SMOC2 disruption affects the facial skeleton in a dose-dependent manner. The size effects of the associated SMOC2 haplotype are profound, accounting for 36% of facial length variation in the dogs we tested. Our data bring new focus to SMOC2 by highlighting its clinical implications in both human and veterinary medicine.

•

A population-based genetics study of dogs that required diagnostic imaging

•

Resolution of a QTL associated with face length reduction (brachycephaly)

•

Association of brachycephaly with a retrotransposon that disrupts SMOC2 splicing

•

The SMOC2 locus explains up to 36% of face length variation in dogs

Hui and Walter's latent-class model extended to estimate diagnostic test properties from surveillance data: a latent model for latent data

Diagnostic test sensitivity and specificity are probabilistic estimates with far reaching implications for disease control, management and genetic studies. In the absence of ‘gold standard’ tests, traditional Bayesian latent class models may be used to assess diagnostic test accuracies through the comparison of two or more tests performed on the same groups of individuals. The aim of this study was to extend such models to estimate diagnostic test parameters and true cohort-specific prevalence, using disease surveillance data. The traditional Hui-Walter latent class methodology was extended to allow for features seen in such data, including (i) unrecorded data (i.e. data for a second test available only on a subset of the sampled population) and (ii) cohort-specific sensitivities and specificities. The model was applied with and without the modelling of conditional dependence between tests. The utility of the extended model was demonstrated through application to bovine tuberculosis surveillance data from Northern and the Republic of Ireland. Simulation coupled with re-sampling techniques, demonstrated that the extended model has good predictive power to estimate the diagnostic parameters and true herd-level prevalence from surveillance data. Our methodology can aid in the interpretation of disease surveillance data, and the results can potentially refine disease control strategies.

Genomic prediction of complex human traits: relatedness, trait architecture and predictive meta-models

We explore the prediction of individuals' phenotypes for complex traits using genomic data. We compare several widely used prediction models, including Ridge Regression, LASSO and Elastic Nets estimated from cohort data, and polygenic risk scores constructed using published summary statistics from genome-wide association meta-analyses (GWAMA). We evaluate the interplay between relatedness, trait architecture and optimal marker density, by predicting height, body mass index (BMI) and high-density lipoprotein level (HDL) in two data cohorts, originating from Croatia and Scotland. We empirically demonstrate that dense models are better when all genetic effects are small (height and BMI) and target individuals are related to the training samples, while sparse models predict better in unrelated individuals and when some effects have moderate size (HDL). For HDL sparse models achieved good across-cohort prediction, performing similarly to the GWAMA risk score and to models trained within the same cohort, which indicates that, for predicting traits with moderately sized effects, large sample sizes and familial structure become less important, though still potentially useful. Finally, we propose a novel ensemble of whole-genome predictors with GWAMA risk scores and demonstrate that the resulting meta-model achieves higher prediction accuracy than either model on its own. We conclude that although current genomic predictors are not accurate enough for diagnostic purposes, performance can be improved without requiring access to large-scale individual-level data. Our methodologically simple meta-model is a means of performing predictive meta-analysis for optimizing genomic predictions and can be easily extended to incorporate multiple population-level summary statistics or other domain knowledge.

Genomic prediction for tuberculosis resistance in dairy cattle

Background

The increasing prevalence of bovine tuberculosis (bTB) in the UK and the limitations of the currently available diagnostic and control methods require the development of complementary approaches to assist in the sustainable control of the disease. One potential approach is the identification of animals that are genetically more resistant to bTB, to enable breeding of animals with enhanced resistance. This paper focuses on prediction of resistance to bTB. We explore estimation of direct genomic estimated breeding values (DGVs) for bTB resistance in UK dairy cattle, using dense SNP chip data, and test these genomic predictions for situations when disease phenotypes are not available on selection candidates.

Methodology/Principal Findings

We estimated DGVs using genomic best linear unbiased prediction methodology, and assessed their predictive accuracies with a cross validation procedure and receiver operator characteristic (ROC) curves. Furthermore, these results were compared with theoretical expectations for prediction accuracy and area-under-the-ROC-curve (AUC). The dataset comprised 1151 Holstein-Friesian cows (bTB cases or controls). All individuals (592 cases and 559 controls) were genotyped for 727,252 loci (Illumina Bead Chip). The estimated observed heritability of bTB resistance was 0.23±0.06 (0.34 on the liability scale) and five-fold cross validation, replicated six times, provided a prediction accuracy of 0.33 (95% C.I.: 0.26, 0.40). ROC curves, and the resulting AUC, gave a probability of 0.58, averaged across six replicates, of correctly classifying cows as diseased or as healthy based on SNP chip genotype alone using these data.

Conclusions/Significance

These results provide a first step in the investigation of the potential feasibility of genomic selection for bTB resistance using SNP data. Specifically, they demonstrate that genomic selection is possible, even in populations with no pedigree data and on animals lacking bTB phenotypes. However, a larger training population will be required to improve prediction accuracies.

Field-isolated genotypes of Mycobacterium bovis vary in virulence and influence case pathology but do not affect outbreak size

Strains of many infectious agents differ in fundamental epidemiological parameters including transmissibility, virulence and pathology. We investigated whether genotypes of Mycobacterium bovis (the causative agent of bovine tuberculosis, bTB) differ significantly in transmissibility and virulence, combining data from a nine-year survey of the genetic structure of the M. bovis population in Northern Ireland with detailed records of the cattle population during the same period. We used the size of herd breakdowns as a proxy measure of transmissibility and the proportion of skin test positive animals (reactors) that were visibly lesioned as a measure of virulence. Average breakdown size increased with herd size and varied depending on the manner of detection (routine herd testing or tracing of infectious contacts) but we found no significant variation among M. bovis genotypes in breakdown size once these factors had been accounted for. However breakdowns due to some genotypes had a greater proportion of lesioned reactors than others, indicating that there may be variation in virulence among genotypes. These findings indicate that the current bTB control programme may be detecting infected herds sufficiently quickly so that differences in virulence are not manifested in terms of outbreak sizes. We also investigated whether pathology of infected cattle varied according to M. bovis genotype, analysing the distribution of lesions recorded at post mortem inspection. We concentrated on the proportion of cases lesioned in the lower respiratory tract, which can indicate the relative importance of the respiratory and alimentary routes of infection. The distribution of lesions varied among genotypes and with cattle age and there were also subtle differences among breeds. Age and breed differences may be related to differences in susceptibility and husbandry, but reasons for variation in lesion distribution among genotypes require further investigation.

Bias, accuracy, and impact of indirect genetic effects in infectious diseases

Selection for improved host response to infectious disease offers a desirable alternative to chemical treatment but has proven difficult in practice, due to low heritability estimates of disease traits. Disease data from field studies is often binary, indicating whether an individual has become infected or not following exposure to an infectious disease. Numerous studies have shown that from this data one can infer genetic variation in individuals’ underlying susceptibility. In a previous study, we showed that with an indirect genetic effect (IGE) model it is possible to capture some genetic variation in infectivity, if present, as well as in susceptibility. Infectivity is the propensity of transmitting infection upon contact with a susceptible individual. It is an important factor determining the severity of an epidemic. However, there are severe shortcomings with the Standard IGE models as they do not accommodate the dynamic nature of disease data. Here we adjust the Standard IGE model to (1) make expression of infectivity dependent on the individuals’ disease status (Case Model) and (2) to include timing of infection (Case-ordered Model). The models are evaluated by comparing impact of selection, bias, and accuracy of each model using simulated binary disease data. These were generated for populations with known variation in susceptibility and infectivity thus allowing comparisons between estimated and true breeding values. Overall the Case Model provided better estimates for host genetic susceptibility and infectivity compared to the Standard Model in terms of bias, impact, and accuracy. Furthermore, these estimates were strongly influenced by epidemiological characteristics. However, surprisingly, the Case-Ordered model performed considerably worse than the Standard and the Case Models, pointing toward limitations in incorporating disease dynamics into conventional variance component estimation methodology and software used in animal breeding.

Evidence for genetic variance in resistance to tuberculosis in Great Britain and Irish Holstein-Friesian populations

Background

Here, we jointly summarise scientific evidence for genetic variation in resistance to infection with Mycobacterium bovis, the primary agent of bovine tuberculosis (TB), provided by two recent and separate studies of Holstein-Friesian dairy cow populations in Great Britain (GB) and Ireland.

Methods

The studies quantified genetic variation within archived data from field and abattoir surveillance control programmes within each country. These data included results from the single intradermal comparative tuberculin test (SICTT), abattoir inspection for TB lesions and laboratory confirmation of disease status. Threshold animal models were used to estimate variance components for responsiveness to the SICTT and abattoir confirmed M. bovis infection. The link functions between the observed 0/1 scale and the liability scale were the complementary log-log in the GB, and logit link function in the Irish population.

Results and discussion

The estimated heritability of susceptibility to TB, as judged by responsiveness to the SICTT, was 0.16 (0.012) and 0.14 (0.025) in the GB and Irish populations, respectively. For abattoir or laboratory confirmation of infection, estimates were 0.18 (0.044) and 0.18 (0.041) from the GB and the Irish populations, respectively.

Conclusions

Estimates were all significantly different from zero and indicate that exploitable variation exists among GB and Irish Holstein Friesian dairy cows for resistance to TB. Epidemiological analysis suggests that factors such as variation in exposure or imperfect sensitivity and specificity would have resulted in underestimation of the true values.

Genetics of animal health and disease in cattle

There have been considerable recent advancements in animal breeding and genetics relevant to disease control in cattle, which can now be utilised as part of an overall programme for improved cattle health. This review summarises the contribution of genetic makeup to differences in resistance to many diseases affecting cattle. Significant genetic variation in susceptibility to disease does exist among cattle suggesting that genetic selection for improved resistance to disease will be fruitful. Deficiencies in accurately recorded data on individual animal susceptibility to disease are, however, currently hindering the inclusion of health and disease resistance traits in national breeding goals. Developments in 'omics' technologies, such as genomic selection, may help overcome some of the limitations of traditional breeding programmes and will be especially beneficial in breeding for lowly heritable disease traits that only manifest themselves following exposure to pathogens or environmental stressors in adulthood. However, access to large databases of phenotypes on health and disease will still be necessary. This review clearly shows that genetics make a significant contribution to the overall health and resistance to disease in cattle. Therefore, breeding programmes for improved animal health and disease resistance should be seen as an integral part of any overall national disease control strategy.

Genetic correlations between measures of Mycobacterium bovis infection and economically important traits in Irish Holstein-Friesian dairy cows

Mycobacterium bovis is the primary agent of tuberculosis (TB) in cattle. The failure of Ireland and some other countries to reach TB-free status indicates a need to investigate complementary control strategies. One such approach would be genetic selection for increased resistance to TB. Previous research has shown that considerable genetic variation exists for susceptibility to the measures of M. bovis infection, confirmed M. bovis infection, and M. bovis-purified protein derivative (PPD) responsiveness. The objective of this study was to estimate the genetic and phenotypic correlations between economically important traits and these measures of M. bovis infection. A total of 20,148 and 17,178 cows with confirmed M. bovis infection and M. bovis-PPD responsiveness records, respectively, were available for inclusion in the analysis. First- to third-parity milk, fat, and protein yields, somatic cell count, calving interval, and survival, as well as first-parity body condition score records, were available on cows that calved between 1985 and 2007. Bivariate linear-linear and threshold-linear sire mixed models were used to estimate (co)variance components. The genetic correlations between economically important traits and the measures of M. bovis infection estimated from the linear-linear and threshold-linear sire models were similar. The genetic correlations between susceptibility to confirmed M. bovis infection and economically important traits investigated in this study were all close to zero. Mycobacterium bovis-PPD responsiveness was positively genetically correlated with fat production (0.39) and body condition score (0.36), and negatively correlated with somatic cell score (-0.34) and survival (-0.62). Hence, selection for increased survival may indirectly reduce susceptibility to M. bovis infection, whereas selection for reduced somatic cell count and increased fat production and body condition score may increase susceptibility to M. bovis infection.

Genetics of tuberculosis in Irish Holstein-Friesian dairy herds

Information is lacking on genetic parameters for tuberculosis (TB) susceptibility in dairy cattle. Mycobacterium bovis is the principal agent of tuberculosis in cattle. The objective of this study was to quantify the genetic variation present among Irish Holstein-Friesian dairy herds in their susceptibility to M. bovis infection. A total of 15,182 cow and 8,104 heifer single intradermal comparative tuberculin test (SICTT, a test for M. bovis exposure and presumed infection) records from November 1, 2002, to October 31, 2005, were available for inclusion in the analysis. Data on observed carcass TB lesions from abattoirs were also available for inclusion in the analysis. The only animals retained were those present in a herd during episodes in which at least 2 animals showed evidence of infection; this ensured a high likelihood of exposure to M. bovis. Linear animal models, and sire and animal threshold models were used to estimate the variance components for susceptibility to M. bovis-purified protein derivative (PPD) responsiveness and confirmed M. bovis infection. The heritability estimates from the threshold sire models were biased upward because the relatedness between dam-daughter pairs was ignored. The threshold animal model produced heritability estimates of 0.14 in cows and 0.12 in heifers for susceptibility to M. bovis-PPD responsiveness, and 0.18 in cows for confirmed M. bovis infection susceptibility. Therefore, exploitable genetic variation exists among Irish dairy cows for susceptibility to M. bovis infection. Sire rankings from the linear and threshold animal models were similar, indicating that either model could be used for the analysis of susceptibility to M. bovis-PPD responsiveness. A favorable genetic correlation close to unity was observed between susceptibility to confirmed M. bovis infection and M. bovis-PPD responsiveness, indicating that direct selection for resistance to M. bovis-PPD responsiveness will indirectly reduce susceptibility to confirmed M. bovis infection. Data from the national TB eradication program could be used routinely to estimate breeding values for susceptibility to M. bovis infection.

Microfauna associated with amoebic gill disease in sea-farmed Atlantic salmon, Salmo salar L., smolts

A study of microfauna, associated with pathological changes in the gills of Atlantic salmon, Salmo salar L., was conducted over 2001-2002. Monthly samples of 1(+) salmon smolts were taken, protozoan populations were quantified and gill health was assessed histologically. Protozoan densities were correlated with pathological changes, in order to determine their possible role in lesions in the gills. The most severe gill tissue changes were observed in summer/autumn and the least in spring. A diverse polyphyletic protozoan community was observed colonizing the gills, including Neoparamoeba sp., other amoebae, scuticociliates, Ichthyobodo-like flagellates, trichodinid ciliates and prostomatean ciliates. The earlier gill tissue changes in the gill were not always associated with the presence of these microorganisms, whereas amoebae (other than Neoparamoeba sp.), Ichthyobodo-like flagellates and trichodinid ciliates correlated with augmenting gill lesions. Neoparamoeba sp. was present, but its abundance did not correlate with the disease. This study suggests that a diversity of protozoans including Ichthyobodo-like flagellates, trichodinid ciliates and amoebae other than Neoparamoeba sp. are involved in the aetiology of amoebic gill disease in the Irish situation.

Environmental risk factors associated with amoebic gill disease in cultured salmon, Salmo salar L., smolts in Ireland

A 2-year study was carried out on amoebic gill disease (AGD) involving monthly samples of 1+ Atlantic salmon, Salmo salar L., smolts, histological assessment of the gills and analysis of environmental data. Gill pathology was seen before amoebae could be detected microscopically. These changes in gill integrity were associated with marine environmental conditions, particularly elevated ammonium, nitrite and chlorophyll levels. The results suggest that the environmental changes predispose salmon to colonization by amoebae and ciliates. High densities of histophagous scuticociliates were observed in the gills during periods of advanced gill pathology. A number of different amoebae were observed in close association with gill pathology. Neoparamoeba was not seen in high densities, nor was it associated with gill pathology, indicating that Neoparamoeba may not be the primary agent of the AGD in Irish salmonid culture.