Genetics of height and risk of atrial fibrillation: A Mendelian randomization study.

BACKGROUND: Observational studies have identified height as a strong risk factor for atrial fibrillation, but this finding may be limited by residual confounding. We aimed to examine genetic variation in height within the Mendelian randomization (MR) framework to determine whether height has a causal effect on risk of atrial fibrillation. METHODS AND FINDINGS: In summary-level analyses, MR was performed using summary statistics from genome-wide association studies of height (GIANT/UK Biobank; 693,529 individuals) and atrial fibrillation (AFGen; 65,446 cases and 522,744 controls), finding that each 1-SD increase in genetically predicted height increased the odds of atrial fibrillation (odds ratio [OR] 1.34; 95% CI 1.29 to 1.40; p = 5 × 10-42). This result remained consistent in sensitivity analyses with MR methods that make different assumptions about the presence of pleiotropy, and when accounting for the effects of traditional cardiovascular risk factors on atrial fibrillation. Individual-level phenome-wide association studies of height and a height genetic risk score were performed among 6,567 European-ancestry participants of the Penn Medicine Biobank (median age at enrollment 63 years, interquartile range 55-72; 38% female; recruitment 2008-2015), confirming prior observational associations between height and atrial fibrillation. Individual-level MR confirmed that each 1-SD increase in height increased the odds of atrial fibrillation, including adjustment for clinical and echocardiographic confounders (OR 1.89; 95% CI 1.50 to 2.40; p = 0.007). The main limitations of this study include potential bias from pleiotropic effects of genetic variants, and lack of generalizability of individual-level findings to non-European populations. CONCLUSIONS: In this study, we observed evidence that height is likely a positive causal risk factor for atrial fibrillation. Further study is needed to determine whether risk prediction tools including height or anthropometric risk factors can be used to improve screening and primary prevention of atrial fibrillation, and whether biological pathways involved in height may offer new targets for treatment of atrial fibrillation

The promoter polymorphism -232C/G of the PCK1 gene is associated with type 2 diabetes in a UK-resident South Asian population

Background: The PCK1 gene, encoding cytosolic phosphoenolpyruvate carboxykinase (PEPCK-C), has previously been implicated as a candidate gene for type 2 diabetes (T2D) susceptibility. Rodent models demonstrate that over-expression of Pck1 can result in T2D development and a single nucleotide polymorphism (SNP) in the promoter region of human PCK1 (-232C/G) has exhibited significant association with the disease in several cohorts. Within the UK-resident South Asian population, T2D is 4 to 6 times more common than in indigenous white Caucasians. Despite this, few studies have reported on the genetic susceptibility to T2D in this ethnic group and none of these has investigated the possible effect of PCK1 variants. We therefore aimed to investigate the association between common variants of the PCK1 gene and T2D in a UK-resident South Asian population of Punjabi ancestry, originating predominantly from the Mirpur area of Azad Kashmir, Pakistan. \ud \ud Methods: We used TaqMan assays to genotype five tagSNPs covering the PCK1 gene, including the -232C/G variant, in 903 subjects with T2D and 471 normoglycaemic controls. \ud \ud Results: Of the variants studied, only the minor allele (G) of the -232C/G SNP demonstrated a significant association with T2D, displaying an OR of 1.21 (95% CI: 1.03 - 1.42, p = 0.019). \ud \ud Conclusion: This study is the first to investigate the association between variants of the PCK1 gene and T2D in South Asians. Our results suggest that the -232C/G promoter polymorphism confers susceptibility to T2D in this ethnic group. \ud \ud Trial registration: UKADS Trial Registration: ISRCTN38297969

Is the thrifty genotype hypothesis supported by evidence based on confirmed type 2 diabetes- and obesity-susceptibility variants?

AIMS/HYPOTHESIS: According to the thrifty genotype hypothesis, the high prevalence of type 2 diabetes and obesity is a consequence of genetic variants that have undergone positive selection during historical periods of erratic food supply. The recent expansion in the number of validated type 2 diabetes- and obesity-susceptibility loci, coupled with access to empirical data, enables us to look for evidence in support (or otherwise) of the thrifty genotype hypothesis using proven loci. METHODS: We employed a range of tests to obtain complementary views of the evidence for selection: we determined whether the risk allele at associated 'index' single-nucleotide polymorphisms is derived or ancestral, calculated the integrated haplotype score (iHS) and assessed the population differentiation statistic fixation index (F (ST)) for 17 type 2 diabetes and 13 obesity loci. RESULTS: We found no evidence for significant differences for the derived/ancestral allele test. None of the studied loci showed strong evidence for selection based on the iHS score. We find a high F (ST) for rs7901695 at TCF7L2, the largest type 2 diabetes effect size found to date. CONCLUSIONS/INTERPRETATION: Our results provide some evidence for selection at specific loci, but there are no consistent patterns of selection that provide conclusive confirmation of the thrifty genotype hypothesis. Discovery of more signals and more causal variants for type 2 diabetes and obesity is likely to allow more detailed examination of these issues

ZPS: visualization of recent adaptive evolution of proteins

<p>Abstract</p> <p>Background</p> <p>Detection of adaptive amino acid changes in proteins under recent short-term selection is of great interest for researchers studying microevolutionary processes in microbial pathogens or any other biological species. However, independent occurrence of such point mutations within genetically diverse haplotypes makes it difficult to detect the selection footprint by using traditional molecular evolutionary analyses. The recently developed Zonal Phylogeny (ZP) has been shown to be a useful analytic tool for identifying the footprints of short-term positive selection. ZP separates protein-encoding genes into evolutionarily long-term (with silent diversity) and short-term (without silent diversity) categories, or zones, followed by statistical analysis to detect signs of positive selection in the short-term zone. However, successful broad application of ZP for analysis of large haplotype datasets requires automation of the relatively labor-intensive computational process.</p> <p>Results</p> <p>Here we present Zonal Phylogeny Software (ZPS), an application that describes the distribution of single nucleotide polymorphisms (SNPs) of synonymous (silent) and non-synonymous (replacement) nature along branches of the DNA tree for any given protein-coding gene locus. Based on this information, ZPS separates the protein variant haplotypes with silent variability (Primary zone) from those that have recently evolved from the Primary zone variants by amino acid changes (External zone). Further comparative analysis of mutational hot-spot frequencies and haplotype diversity between the two zones allows determination of whether the External zone haplotypes emerged under positive selection.</p> <p>Conclusions</p> <p>As a visualization tool, ZPS depicts the protein tree in a DNA tree, indicating the most parsimonious numbers of synonymous and non-synonymous changes along the branches of a maximum-likelihood based DNA tree, along with information on homoplasy, reversion and structural mutation hot-spots. Through zonal differentiation, ZPS allows detection of recent adaptive evolution via selection of advantageous structural mutations, even when the advantage conferred by such mutations is relatively short-term (as in the case of "source-sink" evolutionary dynamics, which may represent a major mode of virulence evolution in microbes).</p

Mendelian randomization study of B-type natriuretic peptide and type 2 diabetes: evidence of causal association from population studies

&lt;p&gt;Background: Genetic and epidemiological evidence suggests an inverse association between B-type natriuretic peptide (BNP) levels in blood and risk of type 2 diabetes (T2D), but the prospective association of BNP with T2D is uncertain, and it is unclear whether the association is confounded.&lt;/p&gt; &lt;p&gt;Methods and Findings: We analysed the association between levels of the N-terminal fragment of pro-BNP (NT-pro-BNP) in blood and risk of incident T2D in a prospective case-cohort study and genotyped the variant rs198389 within the BNP locus in three T2D case-control studies. We combined our results with existing data in a meta-analysis of 11 case-control studies. Using a Mendelian randomization approach, we compared the observed association between rs198389 and T2D to that expected from the NT-pro-BNP level to T2D association and the NT-pro-BNP difference per C allele of rs198389. In participants of our case-cohort study who were free of T2D and cardiovascular disease at baseline, we observed a 21% (95% CI 3%-36%) decreased risk of incident T2D per one standard deviation (SD) higher log-transformed NT-pro-BNP levels in analysis adjusted for age, sex, body mass index, systolic blood pressure, smoking, family history of T2D, history of hypertension, and levels of triglycerides, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol. The association between rs198389 and T2D observed in case-control studies (odds ratio = 0.94 per C allele, 95% CI 0.91-0.97) was similar to that expected (0.96, 0.93-0.98) based on the pooled estimate for the log-NT-pro-BNP level to T2D association derived from a meta-analysis of our study and published data (hazard ratio = 0.82 per SD, 0.74-0.90) and the difference in NT-pro-BNP levels (0.22 SD, 0.15-0.29) per C allele of rs198389. No significant associations were observed between the rs198389 genotype and potential confounders.&lt;/p&gt; &lt;p&gt;Conclusions: Our results provide evidence for a potential causal role of the BNP system in the aetiology of T2D. Further studies are needed to investigate the mechanisms underlying this association and possibilities for preventive interventions.&lt;/p&gt

The scale of population structure in Arabidopsis thaliana

The population structure of an organism reflects its evolutionary history and influences its evolutionary trajectory. It constrains the combination of genetic diversity and reveals patterns of past gene flow. Understanding it is a prerequisite for detecting genomic regions under selection, predicting the effect of population disturbances, or modeling gene flow. This paper examines the detailed global population structure of Arabidopsis thaliana. Using a set of 5,707 plants collected from around the globe and genotyped at 149 SNPs, we show that while A. thaliana as a species self-fertilizes 97% of the time, there is considerable variation among local groups. This level of outcrossing greatly limits observed heterozygosity but is sufficient to generate considerable local haplotypic diversity. We also find that in its native Eurasian range A. thaliana exhibits continuous isolation by distance at every geographic scale without natural breaks corresponding to classical notions of populations. By contrast, in North America, where it exists as an exotic species, A. thaliana exhibits little or no population structure at a continental scale but local isolation by distance that extends hundreds of km. This suggests a pattern for the development of isolation by distance that can establish itself shortly after an organism fills a new habitat range. It also raises questions about the general applicability of many standard population genetics models. Any model based on discrete clusters of interchangeable individuals will be an uneasy fit to organisms like A. thaliana which exhibit continuous isolation by distance on many scales

Psychometric precision in phenotype definition is a useful step in molecular genetic investigation of psychiatric disorders

Affective disorders are highly heritable, but few genetic risk variants have been consistently replicated in molecular genetic association studies. The common method of defining psychiatric phenotypes in molecular genetic research is either a summation of symptom scores or binary threshold score representing the risk of diagnosis. Psychometric latent variable methods can improve the precision of psychiatric phenotypes, especially when the data structure is not straightforward. Using data from the British 1946 birth cohort, we compared summary scores with psychometric modeling based on the General Health Questionnaire (GHQ-28) scale for affective symptoms in an association analysis of 27 candidate genes (249 single-nucleotide polymorphisms (SNPs)). The psychometric method utilized a bi-factor model that partitioned the phenotype variances into five orthogonal latent variable factors, in accordance with the multidimensional data structure of the GHQ-28 involving somatic, social, anxiety and depression domains. Results showed that, compared with the summation approach, the affective symptoms defined by the bi-factor psychometric model had a higher number of associated SNPs of larger effect sizes. These results suggest that psychometrically defined mental health phenotypes can reflect the dimensions of complex phenotypes better than summation scores, and therefore offer a useful approach in genetic association investigations

An evaluation of different meta-analysis approaches in the presence of allelic heterogeneity

Meta-analysis has proven a useful tool in genetic association studies. Allelic heterogeneity can arise from ethnic background differences across populations being meta-analyzed (for example, in search of common frequency variants through genome-wide association studies), and through the presence of multiple low frequency and rare associated variants in the same functional unit of interest (for example, within a gene or a regulatory region). The latter challenge will be increasingly relevant in whole-genome and whole-exome sequencing studies investigating association with complex traits. Here, we evaluate the performance of different approaches to meta-analysis in the presence of allelic heterogeneity. We simulate allelic heterogeneity scenarios in three populations and examine the performance of current approaches to the analysis of these data. We show that current approaches can detect only a small fraction of common frequency causal variants. We also find that for low-frequency variants with large effects (odds ratios 2–3), single-point tests have high power, but also high false-positive rates. P-value based meta-analysis of summary results from allele-matching locus-wide tests outperforms collapsing approaches. We conclude that current strategies for the combination of genetic association data in the presence of allelic heterogeneity are insufficiently powered

Positive Selection in East Asians for an EDAR Allele that Enhances NF-κB Activation

Genome-wide scans for positive selection in humans provide a promising approach to establish links between genetic variants and adaptive phenotypes. From this approach, lists of hundreds of candidate genomic regions for positive selection have been assembled. These candidate regions are expected to contain variants that contribute to adaptive phenotypes, but few of these regions have been associated with phenotypic effects. Here we present evidence that a derived nonsynonymous substitution (370A) in EDAR, a gene involved in ectodermal development, was driven to high frequency in East Asia by positive selection prior to 10,000 years ago. With an in vitro transfection assay, we demonstrate that 370A enhances NF-κB activity. Our results suggest that 370A is a positively selected functional genetic variant that underlies an adaptive human phenotype