Hepcidin-regulating Iron-metabolism Genes and Pancreatic Ductal Adenocarcinoma: A Pathway Analysis of Genome-wide Association Studies

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer, and epidemiological studies have suggested positive associations with iron and red meat intake. Rare mutations in genes involved in the hepcidin-regulating pathway are known to cause iron overload and hemochromatosis. We hypothesize that the hepcidin-regulating pathway as characterized by common variants from genome-wide association studies will be associated with PDAC. Methods: We conducted a large pathway-based meta-analysis of the hepcidin-regulating genes using the summary based adaptive rank truncated product (sARTP) method in 9,253 PDAC cases and 12,525 controls of European descent from the Pancreatic Cancer Cohort (PanScan) and the Pancreatic Cancer Case-Control (PANC4) consortia. Our analysis included 11 hepcidin-regulating genes (BMP2, BMP6, FTH1, FTL, HAMP, HFE, HJV, NRF2, SLC40A1, TFR1, TFR2) and adjacent genomic regions (20 kb upstream and downstream) with a total of 412 single-nucleotide polymorphisms (SNPs). We also conducted the sARTP with four iron status biomarkers (serum iron, transferrin, transferrin saturation, and ferritin, n = 23,986) using summary statistics from previous GWAS studies (Benyamin, et al. 2014) to examine if the hepcidin-regulating genes were also associated with these iron traits. The sARTP method combines SNP-level associations across variants in a gene or a pathway. Signals from up to five of the most associated SNPs for each gene studied were accumulated. Results: The hepcidin-regulating pathway was significantly associated with PDAC (P-value = 0.002) with the HJV, TFR2, and TFR1 genes contributing the most to the association (gene level P-values = 0.001, 0.014, and 0.019, respectively). The pathway associations were more significant in women than men. This pathway was also significantly associated with the four biomarkers of iron metabolism (P-values <1.5 × 10–7). Conclusions: Our results support that genetic susceptibility related to the hepcidin-regulating pathway is associated with PDAC and a potential role of iron metabolism in pancreatic carcinogenesis. Further studies are needed to evaluate the modifying effect of iron-rich foods and genetic susceptibility of this pathway and PDAC risk.

EigenGWAS: finding loci under selection through genome-wide association studies of eigenvectors in structured populations

We develop a novel approach to identify regions of the genome underlying population genetic differentiation in any genetic data where the underlying population structure is unknown, or where the interest is assessing divergence along a gradient. By combining the statistical framework for genome-wide association studies (GWASs) with eigenvector decomposition (EigenGWAS), which is commonly used in population genetics to characterize the structure of genetic data, loci under selection can be identified without a requirement for discrete populations. We show through theory and simulation that our approach can identify regions under selection along gradients of ancestry, and in real data we confirm this by demonstrating LCT to be under selection between HapMap CEU-TSI cohorts, and we then validate this selection signal across European countries in the POPRES samples. HERC2 was also found to be differentiated between both the CEU-TSI cohort and within the POPRES sample, reflecting the likely anthropological differences in skin and hair colour between northern and southern European populations. Controlling for population stratification is of great importance in any quantitative genetic study and our approach also provides a simple, fast and accurate way of predicting principal components in independent samples. With ever increasing sample sizes across many fields, this approach is likely to be greatly utilized to gain individual-level eigenvectors avoiding the computational challenges associated with conducting singular value decomposition in large data sets. We have developed freely available software, Genetic Analysis Repository (GEAR), to facilitate the application of the methods.

Childhood intelligence is heritable, highly polygenic and associated with FNBP1L

Intelligence in childhood, as measured by psychometric cognitive tests, is a strong predictor of many important life outcomes, including educational attainment, income, health and lifespan. Results from twin, family and adoption studies are consistent with general intelligence being highly heritable and genetically stable throughout the life course. No robustly associated genetic loci or variants for childhood intelligence have been reported. Here, we report the first genome-wide association study (GWAS) on childhood intelligence (age range 6-18 years) from 17,989 individuals in six discovery and three replication samples. Although no individual single-nucleotide polymorphisms (SNPs) were detected with genome-wide significance, we show that the aggregate effects of common SNPs explain 22-46% of phenotypic variation in childhood intelligence in the three largest cohorts (P=3.9 × 10(-15), 0.014 and 0.028). FNBP1L, previously reported to be the most significantly associated gene for adult intelligence, was also significantly associated with childhood intelligence (P=0.003). Polygenic prediction analyses resulted in a significant correlation between predictor and outcome in all replication cohorts. The proportion of childhood intelligence explained by the predictor reached 1.2% (P=6 × 10(-5)), 3.5% (P=10(-3)) and 0.5% (P=6 × 10(-5)) in three independent validation cohorts. Given the sample sizes, these genetic prediction results are consistent with expectations if the genetic architecture of childhood intelligence is like that of body mass index or height. Our study provides molecular support for the heritability and polygenic nature of childhood intelligence. Larger sample sizes will be required to detect individual variants with genome-wide significance.

Multicenter dizygotic twin cohort study confirms two linkage susceptibility loci for body mass index at 3q29 and 7q36 and identifies three further potential novel loci

OBJECTIVE

To identify common loci and potential genetic variants affecting body mass index (BMI, kg m(-2)) in study populations originating from Europe.

DESIGN

We combined genome-wide linkage scans of six cohorts from Australia, Denmark, Finland, the Netherlands, Sweden and the United Kingdom with an approximately 10-cM microsatellite marker map. Variance components linkage analysis was carried out with age, sex and country of origin as covariates.

SUBJECTS

The GenomEUtwin consortium consists of twin cohorts from eight countries (Australia, Denmark, the Netherlands, Finland, Italy, Norway, Sweden and the United Kingdom) with a total data collection of more than 500,000 monozygotic and dizygotic (DZ) twin pairs. Variance due to early-life events and the environment is reduced within twin pairs, which makes DZ pairs highly valuable for linkage studies of complex traits. This study totaled 4401 European-originated twin families (10,535 individuals) from six countries (Australia, Denmark, the Netherlands, Finland, Sweden and the United Kingdom).

RESULTS

We found suggestive evidence for a quantitative trait locus on 3q29 and 7q36 in the combined sample of DZ twins (multipoint logarithm of odds score (MLOD) 2.6 and 2.4, respectively). Two individual cohorts showed strong evidence independently for three additional loci: 16q23 (MLOD=3.7) and 2p24 (MLOD=3.4) in the Dutch cohort and 20q13 (MLOD=3.2) in the Finnish cohort.

CONCLUSION

Linkage analysis of the combined data in this large twin cohort study provided evidence for suggestive linkage to BMI. In addition, two cohorts independently provided significant evidence of linkage to three new loci. The results of our study suggest a smaller environmental variance between DZ twins than full siblings, with a corresponding increase in heritability for BMI as well as an increase in linkage signal in well-replicated regions. The results are consistent with the possibility of locus heterogeneity for some genomic regions, and indicate a lack of major common quantitative trait locus variants affecting BMI in European populations.

Are there common genetic and environmental factors behind the endophenotypes associated with the metabolic syndrome?

AIMS/HYPOTHESIS

The cluster of obesity, insulin resistance, dyslipidaemia and hypertension, called the metabolic syndrome, has been suggested as a risk factor for cardiovascular disease and type 2 diabetes. The aim of the present study was to evaluate whether there are common genetic and environmental factors influencing this cluster in a general population of twin pairs.

MATERIALS AND METHODS

A multivariate genetic analysis was performed on nine endophenotypes associated with the metabolic syndrome from 625 adult twin pairs of the GEMINAKAR study of the Danish Twin Registry.

RESULTS

All endophenotypes showed moderate to high heritability (0.31-0.69) and small common environmental variance (0.05-0.21). In general, genetic and phenotypic correlations between the endophenotypes were strong only within sets of physiologically similar endophenotypes, but weak to moderate for other pairs of endophenotypes. However, moderate correlations between insulin resistance indices and either obesity-related endophenotypes or triacylglycerol levels indicated that some common genetic backgrounds are shared between those components.

CONCLUSIONS/INTERPRETATION

We demonstrated that, in a general population, the endophenotypes associated with the metabolic syndrome apparently do not share a substantial common genetic or familial environmental background.