Inferring Geographic Coordinates of Origin for Europeans Using Small Panels of Ancestry Informative Markers

Recent large-scale studies of European populations have demonstrated the existence of population genetic structure within Europe and the potential to accurately infer individual ancestry when information from hundreds of thousands of genetic markers is used. In fact, when genomewide genetic variation of European populations is projected down to a two-dimensional Principal Components Analysis plot, a surprising correlation with actual geographic coordinates of self-reported ancestry has been reported. This substructure can hamper the search of susceptibility genes for common complex disorders leading to spurious correlations. The identification of genetic markers that can correct for population stratification becomes therefore of paramount importance. Analyzing 1,200 individuals from 11 populations genotyped for more than 500,000 SNPs (Population Reference Sample), we present a systematic exploration of the extent to which geographic coordinates of origin within Europe can be predicted, with small panels of SNPs. Markers are selected to correlate with the top principal components of the dataset, as we have previously demonstrated. Performing thorough cross-validation experiments we show that it is indeed possible to predict individual ancestry within Europe down to a few hundred kilometers from actual individual origin, using information from carefully selected panels of 500 or 1,000 SNPs. Furthermore, we show that these panels can be used to correctly assign the HapMap Phase 3 European populations to their geographic origin. The SNPs that we propose can prove extremely useful in a variety of different settings, such as stratification correction or genetic ancestry testing, and the study of the history of European populations

A Novel Test for Gene-Ancestry Interactions in Genome-Wide Association Data

Genome-wide association study (GWAS) data on a disease are increasingly available from multiple related populations. In this scenario, meta-analyses can improve power to detect homogeneous genetic associations, but if there exist ancestry-specific effects, via interactions on genetic background or with a causal effect that co-varies with genetic background, then these will typically be obscured. To address this issue, we have developed a robust statistical method for detecting susceptibility gene-ancestry interactions in multi-cohort GWAS based on closely-related populations. We use the leading principal components of the empirical genotype matrix to cluster individuals into “ancestry groups” and then look for evidence of heterogeneous genetic associations with disease or other trait across these clusters. Robustness is improved when there are multiple cohorts, as the signal from true gene-ancestry interactions can then be distinguished from gene-collection artefacts by comparing the observed interaction effect sizes in collection groups relative to ancestry groups. When applied to colorectal cancer, we identified a missense polymorphism in iron-absorption gene CYBRD1 that associated with disease in individuals of English, but not Scottish, ancestry. The association replicated in two additional, independently-collected data sets. Our method can be used to detect associations between genetic variants and disease that have been obscured by population genetic heterogeneity. It can be readily extended to the identification of genetic interactions on other covariates such as measured environmental exposures. We envisage our methodology being of particular interest to researchers with existing GWAS data, as ancestry groups can be easily defined and thus tested for interactions

Multicohort study of change in job strain, poor mental health and incident cardiometabolic disease

Objectives: Several recent large-scale studies have indicated a prospective association between job strain and coronary heart disease, stroke and diabetes. Job strain is also associated with poorer mental health, a risk factor for cardiometabolic disease. This study investigates the prospective relationships between change in job strain, poor mental health and cardiometabolic disease, and whether poor mental health is a potential mediator of the relationship between job strain and cardiometabolic disease.Methods: We used data from five cohort studies from Australia, Finland, Sweden and UK, including 47 757 men and women. Data on job strain across two measurements 1-5 years apart (time 1 (T1)-time 2 (T2)) were used to define increase or decrease in job strain. Poor mental health (symptoms in the top 25% of the distribution of the scales) at T2 was considered a potential mediator in relation to incident cardiometabolic disease, including cardiovascular disease and diabetes, following T2 for a mean of 5-18 years.Results: An increase in job strain was associated with poor mental health (HR 1.56, 95% CI 1.38 to 1.76), and a decrease in job strain was associated with lower risk in women (HR 0.70, 95% CI 0.60-0.84). However, no clear association was observed between poor mental health and incident cardiometabolic disease (HR 1.08, 95% CI 0.96-1.23), nor between increase (HR 1.01, 95% CI 0.90-1.14) and decrease (HR 1.08, 95% CI 0.96-1.22) in job strain and cardiometabolic disease.Conclusions: The results did not support that change in job strain is a risk factor for cardiometabolic disease and yielded no support for poor mental health as a mediator.</p

Tracing Cattle Breeds with Principal Components Analysis Ancestry Informative SNPs

The recent release of the Bovine HapMap dataset represents the most detailed survey of bovine genetic diversity to date, providing an important resource for the design and development of livestock production. We studied this dataset, comprising more than 30,000 Single Nucleotide Polymorphisms (SNPs) for 19 breeds (13 taurine, three zebu, and three hybrid breeds), seeking to identify small panels of genetic markers that can be used to trace the breed of unknown cattle samples. Taking advantage of the power of Principal Components Analysis and algorithms that we have recently described for the selection of Ancestry Informative Markers from genomewide datasets, we present a decision-tree which can be used to accurately infer the origin of individual cattle. In doing so, we present a thorough examination of population genetic structure in modern bovine breeds. Performing extensive cross-validation experiments, we demonstrate that 250-500 carefully selected SNPs suffice in order to achieve close to 100% prediction accuracy of individual ancestry, when this particular set of 19 breeds is considered. Our methods, coupled with the dense genotypic data that is becoming increasingly available, have the potential to become a valuable tool and have considerable impact in worldwide livestock production. They can be used to inform the design of studies of the genetic basis of economically important traits in cattle, as well as breeding programs and efforts to conserve biodiversity. Furthermore, the SNPs that we have identified can provide a reliable solution for the traceability of breed-specific branded products

A global view of the OCA2-HERC2 region and pigmentation

Mutations in the gene OCA2 are responsible for oculocutaneous albinism type 2, but polymorphisms in and around OCA2 have also been associated with normal pigment variation. In Europeans, three haplotypes in the region have been shown to be associated with eye pigmentation and a missense SNP (rs1800407) has been associated with green/hazel eyes (Branicki et al. in Ann Hum Genet 73:160–170, 2009). In addition, a missense mutation (rs1800414) is a candidate for light skin pigmentation in East Asia (Yuasa et al. in Biochem Genet 45:535–542, 2007; Anno et al. in Int J Biol Sci 4, 2008). We have genotyped 3,432 individuals from 72 populations for 21 SNPs in the OCA2-HERC2 region including those previously associated with eye or skin pigmentation. We report that the blue-eye associated alleles at all three haplotypes were found at high frequencies in Europe; however, one is restricted to Europe and surrounding regions, while the other two are found at moderate to high frequencies throughout the world. We also observed that the derived allele of rs1800414 is essentially limited to East Asia where it is found at high frequencies. Long-range haplotype tests provide evidence of selection for the blue-eye allele at the three haplotyped systems but not for the green/hazel eye SNP allele. We also saw evidence of selection at the derived allele of rs1800414 in East Asia. Our data suggest that the haplotype restricted to Europe is the strongest marker for blue eyes globally and add further inferential evidence that the derived allele of rs1800414 is an East Asian skin pigmentation allele

Interactional justice at work is related to sickness absence: a study using repeated measures in the Swedish working population

Background: Research has shown that perceived unfairness contributes to higher rates of sickness absence. While shorter, but more frequent periods of sickness absence might be a possibility for the individual to get relief from high strain, long-term sickness absence might be a sign of more serious health problems. The Uncertainty Management Model suggests that justice is particularly important in times of uncertainty, e.g. perceived job insecurity. The present study investigated the association between interpersonal and informational justice at work with long and frequent sickness absence respectively, under conditions of job insecurity. Methods: Data were derived from the 2010, 2012, and 2014 biennial waves of the Swedish Longitudinal Occupational Survey of Health (SLOSH). The final analytic sample consisted of 19,493 individuals. We applied repeated measures regression analyses through generalized estimating equations (GEE), a method for longitudinal data that simultaneously analyses variables at different time points. We calculated risk of long and frequent sickness absence, respectively in relation to interpersonal and informational justice taking perceptions of job insecurity into account. Results: We found informational and interpersonal justice to be associated with risk of long and frequent sickness absence independently of job insecurity and demographic variables. Results from autoregressive GEE provided some support for a causal relationship between justice perceptions and sickness absence. Contrary to expectations, we found no interaction between justice and job insecurity. Conclusions: Our results underline the need for fair and just treatment of employees irrespective of perceived job insecurity in order to keep the workforce healthy and to minimize lost work days due to sickness absence

Multivariate Analysis of Dopaminergic Gene Variants as Risk Factors of Heroin Dependence

BACKGROUND: Heroin dependence is a debilitating psychiatric disorder with complex inheritance. Since the dopaminergic system has a key role in rewarding mechanism of the brain, which is directly or indirectly targeted by most drugs of abuse, we focus on the effects and interactions among dopaminergic gene variants. OBJECTIVE: To study the potential association between allelic variants of dopamine D2 receptor (DRD2), ANKK1 (ankyrin repeat and kinase domain containing 1), dopamine D4 receptor (DRD4), catechol-O-methyl transferase (COMT) and dopamine transporter (SLC6A3) genes and heroin dependence in Hungarian patients. METHODS: 303 heroin dependent subjects and 555 healthy controls were genotyped for 7 single nucleotide polymorphisms (SNPs) rs4680 of the COMT gene; rs1079597 and rs1800498 of the DRD2 gene; rs1800497 of the ANKK1 gene; rs1800955, rs936462 and rs747302 of the DRD4 gene. Four variable number of tandem repeats (VNTRs) were also genotyped: 120 bp duplication and 48 bp VNTR in exon 3 of DRD4 and 40 bp VNTR and intron 8 VNTR of SLC6A3. We also perform a multivariate analysis of associations using Bayesian networks in Bayesian multilevel analysis (BN-BMLA). FINDINGS AND CONCLUSIONS: In single marker analysis the TaqIA (rs1800497) and TaqIB (rs1079597) variants were associated with heroin dependence. Moreover, -521 C/T SNP (rs1800955) of the DRD4 gene showed nominal association with a possible protective effect of the C allele. After applying the Bonferroni correction TaqIB was still significant suggesting that the minor (A) allele of the TaqIB SNP is a risk component in the genetic background of heroin dependence. The findings of the additional multiple marker analysis are consistent with the results of the single marker analysis, but this method was able to reveal an indirect effect of a promoter polymorphism (rs936462) of the DRD4 gene and this effect is mediated through the -521 C/T (rs1800955) polymorphism in the promoter

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors

Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders

Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed analyses of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyper-activity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders, identifying three groups of inter-related disorders. Meta-analysis across these eight disorders detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning prenatally in the second trimester, and play prominent roles in neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.Peer reviewe