Combining identity by descent and association in genetic case-control studies

Further evidence for the association of GAL, GALR1 and NPY1R variants with opioid dependence

Aim: Heroin addiction is a chronic, relapsing disease that has genetic and environmental, including drug-induced, contributions. Stress influences the development of addictions. This study was conducted to determine if variants in stress-related genes are associated with opioid dependence (OD). Patients & methods: One hundred and twenty variants in 26 genes were analyzed in 597 Dutch subjects. Patients included 281 OD in methadone maintenance with or without heroin-assisted treatment and 316 controls. Results: Twelve SNPs in seven genes showed a nominally significant association with OD. Experiment-wise significant associations (p < 0.05) were found for three SNP pairs, through an interaction effect: NPY1R/GAL rs4691910/rs1893679, NPY1R/GAL rs4691910/rs3136541 and GALR1/GAL rs9807208/rs3136541. Conclusion: This study lends more evidence to previous reports of association of stress-related variants with heroin dependence.

A 3' UTR SNP rs885863, a cis-eQTL for the circadian gene VIPR2 and lincRNA 689, is associated with opioid addiction

There is a reciprocal relationship between the circadian and the reward systems. Polymorphisms in several circadian rhythm-related (clock) genes were associated with drug addiction. This study aims to search for associations between 895 variants in 39 circadian rhythm-related genes and opioid addiction (OUD). Genotyping was performed with the Smokescreen^® array. Ancestry was verified by principal/MDS component analysis and the sample was limited to European Americans (EA) (OUD; n = 435, controls; n = 138). Nominally significant associations (p < 0.01) were detected for several variants in genes encoding vasoactive intestinal peptide receptor 2 (VIPR2), period circadian regulator 2 (PER2), casein kinase 1 epsilon (CSNK1E), and activator of transcription and developmental regulator (AUTS2), but no signal survived correction for multiple testing. There was intriguing association signal for the untranslated region (3’ UTR) variant rs885863 in VIPR2, (p = .0065; OR = 0.51; 95% CI 0.31–0.51). The result was corroborated in an independent EA OUD sample (n = 398, p = 0.0036; for the combined samples). Notably, this SNP is an expression quantitative trait locus (cis-eQTL) for VIPR2 and a long intergenic non-coding RNA, lincRNA 689, in a tissue-specific manner, based on the Genotype-Tissue Expression (GTEx) project. Vasoactive intestinal peptide (VIP) is an important peptide of light-activated suprachiasmatic nucleus cells. It regulates diverse physiological processes including circadian rhythms, learning and memory, and stress response. This is the first report of an association of a VIPR2 variant and OUD. Additionally, analysis of combinations of single nucleotide polymorphisms (SNPs) genotypes revealed an association of PER2 SNP rs80136044, and SNP rs4128839, located 41.6 kb downstream of neuropeptide Y receptor type 1 gene, NPY1R (p = 3.4 × 10⁻⁶, OR = 11.4, 95% CI 2.7–48.2). The study provides preliminary insight into the relationship between genetic variants in circadian rhythm genes and long non-coding RNA (lncRNAs) in their vicinity, and opioid addiction.

Detection of identity by descent using next-generation whole genome sequencing data

BACKGROUND

Identity by descent (IBD) has played a fundamental role in the discovery of genetic loci underlying human diseases. Both pedigree-based and population-based linkage analyses rely on estimating recent IBD, and evidence of ancient IBD can be used to detect population structure in genetic association studies. Various methods for detecting IBD, including those implemented in the soft- ware programs fastIBD and GERMLINE, have been developed in the past several years using population genotype data from microarray platforms. Now, next-generation DNA sequencing data is becoming increasingly available, enabling the comprehensive analysis of genomes, in- cluding identifying rare variants. These sequencing data may provide an opportunity to detect IBD with higher resolution than previously possible, potentially enabling the detection of disease causing loci that were previously undetectable with sparser genetic data.

RESULTS

Here, we investigate how different levels of variant coverage in sequencing and microarray genotype data influences the resolution at which IBD can be detected. This includes microarray genotype data from the WTCCC study, denser genotype data from the HapMap Project, low coverage sequencing data from the 1000 Genomes Project, and deep coverage complete genome data from our own projects. With high power (78%), we can detect segments of length 0.4 cM or larger using fastIBD and GERMLINE in sequencing data. This compares to similar power to detect segments of length 1.0 cM or higher with microarray genotype data. We find that GERMLINE has slightly higher power than fastIBD for detecting IBD segments using sequencing data, but also has a much higher false positive rate.

CONCLUSION

We further quantify the effect of variant density, conditional on genetic map length, on the power to resolve IBD segments. These investigations into IBD resolution may help guide the design of future next generation sequencing studies that utilize IBD, including family-based association studies, association studies in admixed populations, and homozygosity mapping studies.

Genome-wide association studies for discrete traits

Genome-wide association studies of discrete traits generally use simple methods of analysis based on chi(2) tests for contingency tables or logistic regression, at least for an initial scan of the entire genome. Nevertheless, more power might be obtained by using various methods that analyze multiple markers in combination. Methods based on sliding windows, wavelets, Bayesian shrinkage, or penalized likelihood methods, among others, were explored by various participants of Genetic Analysis Workshop 16 Group 1 to combine information across multiple markers within a region, while others used Bayesian variable selection methods for genome-wide multivariate analyses of all markers simultaneously. Imputation can be used to fill in missing markers on individual subjects within a study or in a meta-analysis of studies using different panels. Although multiple imputation theoretically should give more robust tests of association, one participant contribution found little difference between results of single and multiple imputation. Careful control of population stratification is essential, and two contributions found that previously reported associations with two genes disappeared after more precise control. Other issues considered by this group included subgroup analysis, gene-gene interactions, and the use of biomarkers.

VALID: visualization of association study results and linkage disequilibrium

Promising findings from genetic association studies are commonly presented with two distinct figures: one gives the association study results and the other indicates linkage disequilibrium (LD) between genetic markers in the region(s) of interest. Fully interpreting the results of such studies requires synthesizing the information in these figures, which is generally done in a subjective and unsystematic manner. Here we present a method to formally combine association results and LD and display them in the same figure; we have developed a freely available web-based application that can be used to generate figures to display the combined data. To demonstrate this approach we apply it to fine mapping data from the prostate cancer 8q24 loci. Combining these two sources of information in a single figure allows one to more clearly assess patterns of association, facilitating the interpretation of genome-wide and fine mapping data and improving our ability to localize causal variants.

Adjusting for HLA-DRbeta1 in a genome-wide association analysis of rheumatoid arthritis and related biomarkers

Background

There is a long-established association between rheumatoid arthritis and HLA-DRβ1. The shared epitope (SE) allele is an indicator of the presence of any of the HLA-DRβ1 alleles associated with RA. Other autoantibodies are also associated with RA, specifically rheumatoid factor IgM (RFUW) and anti-cyclic citrullinated peptide (anti-CCP).

Methods

Using the Genetic Analysis Workshop 16 North American Rheumatoid Arthritis Consortium genome-wide association data, we sought to find non-HLA-DRβ1 genetic associations by stratifying across SE status, and using the continuous biomarker phenotypes of RFUW and anti-CCP. To evaluate the binary RA phenotype, we applied the recently developed FP test and compared it to logistic regression or a genotype count-based test. We adjusted for multiple testing using the Bonferroni correction, the Q value approach, or permutation-based p-values. A case-only analysis of the biomarkers RFUW and anti-CCP used linear regression and ANOVAs.

Results

The initial genome-wide association analysis using all cases and controls provides substantial evidence of an association on chromosomes 9 and 2 within the immune system-related gene UBXD2. In SE-positive subjects, many single-nucleotide polymorphisms were significant, including some on chromosome 6. Due to very few SE negative cases, we had limited power to detect associations in SE negative subjects. We were also unable to find genetic associations with either RFUW or anti-CCP.

Conclusion

Our analyses have confirmed previous findings for genes PTPN22 and C5. We also identified a novel candidate gene on chromosome 2, UBXD2. Results suggest FP test may be more powerful than the genotype count-based test.