The potential for enhancing the power of genetic association studies in African Americans through the reuse of existing genotype data

Exploring regional aspects of 3D facial variation within European individuals

Facial ancestry can be described as variation that exists in facial features that are shared amongst members of a population due to environmental and genetic effects. Even within Europe, faces vary among subregions and may lead to confounding in genetic association studies if unaccounted for. Genetic studies use genetic principal components (PCs) to describe facial ancestry to circumvent this issue. Yet the phenotypic effect of these genetic PCs on the face has yet to be described, and phenotype-based alternatives compared. In anthropological studies, consensus faces are utilized as they depict a phenotypic, not genetic, ancestry effect. In this study, we explored the effects of regional differences on facial ancestry in 744 Europeans using genetic and anthropological approaches. Both showed similar ancestry effects between subgroups, localized mainly to the forehead, nose, and chin. Consensus faces explained the variation seen in only the first three genetic PCs, differing more in magnitude than shape change. Here we show only minor differences between the two methods and discuss a combined approach as a possible alternative for facial scan correction that is less cohort dependent, more replicable, non-linear, and can be made open access for use across research groups, enhancing future studies in this field.

Genome-Wide Association Studies of Cancer in Diverse Populations

Genome-wide association studies (GWAS) of cancer have identified more than 700 risk loci, of which approximately 80% were first discovered in European ancestry populations, approximately 15% in East Asians, 3% in multiethnic scans, and less than 1% in African and Latin American populations. These percentages closely mirror the distribution of samples included in the discovery phase of cancer GWAS to date (84% European, 11% East Asian, 4% African, and 1% Latin American ancestry). GWAS in non-European ancestry populations have provided insight into ancestry-specific variation in cancer and have pointed to regions of susceptibility that are of particular importance in certain populations. Uncovering and characterizing cancer risk loci in diverse populations is critical for understanding underlying biological mechanisms and developing future genetic risk prediction models in non-European ancestry populations. New GWAS and continued collaborations will be required to eliminate population inequalities in the number of studies, sample sizes, and variant content on GWAS arrays, and to better align genetic research in cancer to the global distribution of race/ethnicity Cancer Epidemiol Biomarkers Prev; 27(4); 405-17. ©2018 AACRSee all articles in this CEBP Focus section, "Genome-Wide Association Studies in Cancer."

Characterization of genetic loci that affect susceptibility to inflammatory bowel diseases in African Americans

BACKGROUND & AIMS

Inflammatory bowel disease (IBD) has familial aggregation in African Americans (AAs), but little is known about the molecular genetic susceptibility. Mapping studies using the Immunochip genotyping array expand the number of susceptibility loci for IBD in Caucasians to 163, but the contribution of the 163 loci and European admixture to IBD risk in AAs is unclear. We performed a genetic mapping study using the Immunochip to determine whether IBD susceptibility loci in Caucasians also affect risk in AAs and identify new associated loci.

METHODS

We recruited AAs with IBD and without IBD (controls) from 34 IBD centers in the United States; additional controls were collected from 4 other Immunochip studies. Association and admixture loci were mapped for 1088 patients with Crohn's disease, 361 with ulcerative colitis, 62 with IBD type unknown, and 1797 controls; 130,241 autosomal single-nucleotide polymorphisms (SNPs) were analyzed.

RESULTS

The strongest associations were observed between ulcerative colitis and HLA rs9271366 (P = 7.5 × 10(-6)), Crohn's disease and 5p13.1 rs4286721 (P = 3.5 × 10(-6)), and IBD and KAT2A rs730086 (P = 2.3 × 10(-6)). Additional suggestive associations (P < 4.2 × 10(-5)) were observed between Crohn's disease and IBD and African-specific SNPs in STAT5A and STAT3; between IBD and SNPs in IL23R, IL12B, and C2orf43; and between ulcerative colitis and SNPs near HDAC11 and near LINC00994. The latter 3 loci have not been previously associated with IBD, but require replication. Established Caucasian associations were replicated in AAs (P < 3.1 × 10(-4)) at NOD2, IL23R, 5p15.3, and IKZF3. Significant admixture (P < 3.9 × 10(-4)) was observed for 17q12-17q21.31 (IZKF3 through STAT3), 10q11.23-10q21.2, 15q22.2-15q23, and 16p12.2-16p12.1. Network analyses showed significant enrichment (false discovery rate <1 × 10(-5)) in genes that encode members of the JAK-STAT, cytokine, and chemokine signaling pathways, as well those involved in pathogenesis of measles.

CONCLUSIONS

In a genetic analysis of 3308 AA IBD cases and controls, we found that many variants associated with IBD in Caucasians also showed association evidence with these diseases in AAs; we also found evidence for variants and loci not previously associated with IBD. The complex genetic factors that determine risk for or protection against IBD in different populations require further study.

Red blood cell alloimmunization in sickle cell disease: listen to your ancestors

Red blood cell (RBC) alloimmunization occurs in approximately 30% of transfused sickle cell disease patients compared to 2-5% of all transfusion recipients. Because RBC transfusion is an important part of therapy in sickle cell disease, the need for additional antigen matching once alloimmunization occurs is problematic and leads to therapeutic limitations. Thus, identification of risk factors would benefit this patient population. Genome-wide analyses, in particular, methods which take into account genetic ancestry such as admixture mapping, could identify molecular markers which could be used to identify immune responders to transfusion.

The role of local ancestry adjustment in association studies using admixed populations

Association analysis using admixed populations imposes challenges and opportunities for disease mapping. By developing some explicit results for the variance of an allele of interest conditional on either local or global ancestry and by simulation of recently admixed genomes we evaluate power and false-positive rates under a variety of scenarios concerning linkage disequilibrium (LD) and the presence of unmeasured variants. Pairwise LD patterns were compared between admixed and nonadmixed populations using the HapMap phase 3 data. Based on the above, we showed that as follows:

For causal variants with similar effect size in all populations, power is generally higher in a study using admixed population than using nonadmixed population, especially for highly differentiated SNPs. This gain of power is achieved with adjustment of global ancestry, which completely removes any cross-chromosome inflation of type I error rates, and addresses much of the intrachromosome inflation.

If reliably estimated, adjusting for local ancestry precisely recovers the localization that could have been achieved in a stratified analysis of source populations. Improved localization is most evident for highly differentiated SNPs; however, the advantage of higher power is lost on exactly the same differentiated SNPs.

In the real admixed populations such as African Americans and Latinos, the expansion of LD is not as dramatic as in our simulation.

While adjustment for global ancestry is required prior to announcing a novel association seen in an admixed population, local ancestry adjustment may best be regarded as a localization tool not strictly required for discovery purposes.

Genetic epidemiology with a capital E: where will we be in another 10 years?

In a commentary on the evolution of the field of genetic epidemiology over the past 10 years, Khoury et al. (2011) highlight several important developments, including the emergence of evaluation of genetic discoveries for their translational utility and of standards for reporting genetic findings. In this companion to their article, I reflect on some of these trends and speculate about the direction of the field in the future. In particular, I emphasize the opportunities posed by novel technologies like next-generation sequencing and the biological insights emerging from integrative genomics, but I also question the utility of large consortia. The basic principles of population-based research and the importance of taking account of the environment remain important to the field.

Using biological knowledge to discover higher order interactions in genetic association studies

The recent successes of genome-wide association studies (GWAS) have revealed that many of the replicated findings have explained only a small fraction of the heritability of common diseases. One hypothesis that investigators have suggested is that higher order interactions between SNPs or SNPs and environmental risk factors may account for some of this missing heritability. Searching for these interactions poses great statistical and computational challenges. In this article, we propose a novel method that addresses these challenges by incorporating external biological knowledge into a fully Bayesian analysis. The method is designed to be scalable for high-dimensional search spaces (where it supports interactions of any order) because priors that use such knowledge focus the search in regions that are more biologically plausible and avoid having to enumerate all possible interactions. We provide several examples based on simulated data demonstrating how external information can enhance power, specificity, and effect estimates in comparison to conventional approaches based on maximum likelihood estimates. We also apply the method to data from a GWAS for breast cancer, revealing a set of interactions enriched for the Gene Ontology terms growth, metabolic process, and biological regulation.