How Can Genetic Studies Help Us to Understand Links Between Birth Weight and Type 2 Diabetes?

PURPOSE OF REVIEW

In observational epidemiology, both low and high birth weights are associated with later type 2 diabetes. The mechanisms underlying the associations are poorly understood. We review evidence for the roles of genetic and non-genetic factors linking both sides of the birth weight distribution to risk of type 2 diabetes, focusing on contributions made by the most recent genome-wide association studies (GWAS) of birth weight.

RECENT FINDINGS

There are now nine genetic loci robustly implicated in both fetal growth and type 2 diabetes. At many of these, the same alleles are associated both with a higher risk of type 2 diabetes and a lower birth weight. This supports the Fetal Insulin Hypothesis and reflects a general pattern for type 2 diabetes susceptibility alleles: genome-wide, there is an inverse genetic correlation with birth weight, and initial estimates suggest genetic factors explain a large part of the covariance between the two traits. However, the associations at individual loci show heterogeneity; some fetal risk alleles are associated with higher birth weight. For most of these, the association reflects their correlation with the maternal risk allele which raises maternal glucose, thus increasing fetal insulin-mediated growth. GWAS have improved our understanding of the mechanisms underlying associations between type 2 diabetes and birth weight but questions remain about the relative importance of genetic versus non-genetic factors and of maternal versus fetal genotypes. To answer these questions, future work will require well-powered analyses of parents and offspring.

KNN-MDR: a learning approach for improving interactions mapping performances in genome wide association studies

Background

Finding epistatic interactions in large association studies like genome-wide association studies (GWAS) with the nowadays-available large volume of genomic data is a challenging and largely unsolved issue. Few previous studies could handle genome-wide data due to the intractable difficulties met in searching a combinatorial explosive search space and statistically evaluating epistatic interactions given a limited number of samples. Our work is a contribution to this field. We propose a novel approach combining K-Nearest Neighbors (KNN) and Multi Dimensional Reduction (MDR) methods for detecting gene-gene interactions as a possible alternative to existing algorithms, e especially in situations where the number of involved determinants is high. After describing the approach, a comparison of our method (KNN-MDR) to a set of the other most performing methods (i.e., MDR, BOOST, BHIT, MegaSNPHunter and AntEpiSeeker) is carried on to detect interactions using simulated data as well as real genome-wide data.

Results

Experimental results on both simulated data and real genome-wide data show that KNN-MDR has interesting properties in terms of accuracy and power, and that, in many cases, it significantly outperforms its recent competitors.

Conclusions

The presented methodology (KNN-MDR) is valuable in the context of loci and interactions mapping and can be seen as an interesting addition to the arsenal used in complex traits analyses.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-017-1599-7) contains supplementary material, which is available to authorized users.

An Analytic Solution to the Computation of Power and Sample Size for Genetic Association Studies under a Pleiotropic Mode of Inheritance

Our motivation here is to calculate the power of 3 statistical tests used when there are genetic traits that operate under a pleiotropic mode of inheritance and when qualitative phenotypes are defined by use of thresholds for the multiple quantitative phenotypes. Specifically, we formulate a multivariate function that provides the probability that an individual has a vector of specific quantitative trait values conditional on having a risk locus genotype, and we apply thresholds to define qualitative phenotypes (affected, unaffected) and compute penetrances and conditional genotype frequencies based on the multivariate function. We extend the analytic power and minimum-sample-size-necessary (MSSN) formulas for 2 categorical data-based tests (genotype, linear trend test [LTT]) of genetic association to the pleiotropic model. We further compare the MSSN of the genotype test and the LTT with that of a multivariate ANOVA (Pillai). We approximate the MSSN for statistics by linear models using a factorial design and ANOVA. With ANOVA decomposition, we determine which factors most significantly change the power/MSSN for all statistics. Finally, we determine which test statistics have the smallest MSSN. In this work, MSSN calculations are for 2 traits (bivariate distributions) only (for illustrative purposes). We note that the calculations may be extended to address any number of traits. Our key findings are that the genotype test usually has lower MSSN requirements than the LTT. More inclusive thresholds (top/bottom 25% vs. top/bottom 10%) have higher sample size requirements. The Pillai test has a much larger MSSN than both the genotype test and the LTT, as a result of sample selection. With these formulas, researchers can specify how many subjects they must collect to localize genes for pleiotropic phenotypes.

Role of autophagy in the pathogenesis of inflammatory bowel disease

Inflammatory bowel disease (IBD) results from a complex series of interactions between susceptibility genes, the environment, and the immune system. Recently, some studies provided strong evidence that the process of autophagy affects several aspects of mucosal immune responses. Autophagy is a cellular stress response that plays key roles in physiological processes, such as innate and adaptive immunity, adaptation to starvation, degradation of aberrant proteins or organelles, antimicrobial defense, and protein secretion. Dysfunctional autophagy is recognized as a contributing factor in many chronic inflammatory diseases, including IBD. Autophagy plays multiple roles in IBD pathogenesis by altering processes that include intracellular bacterial killing, antimicrobial peptide secretion by Paneth cells, goblet cell function, proinflammatory cytokine production by macrophages, antigen presentation by dendritic cells, and the endoplasmic reticulum stress response in enterocytes. Recent studies have identified susceptibility genes involved in autophagy, such as NOD2, ATG16L1, and IRGM, and active research is ongoing all over the world. The aim of this review is a systematic appraisal of the current literature to provide a better understanding of the role of autophagy in the pathogenesis of IBD. Understanding these mechanisms will bring about new strategies for the treatment and prevention of IBD.

An adaptive two-sample test for high-dimensional means

Several two-sample tests for high-dimensional data have been proposed recently, but they are powerful only against certain alternative hypotheses. In practice, since the true alternative hypothesis is unknown, it is unclear how to choose a powerful test. We propose an adaptive test that maintains high power across a wide range of situations and study its asymptotic properties. Its finite-sample performance is compared with that of existing tests. We apply it and other tests to detect possible associations between bipolar disease and a large number of single nucleotide polymorphisms on each chromosome based on data from a genome-wide association study. Numerical studies demonstrate the superior performance and high power of the proposed test across a wide spectrum of applications.

Epigenetic and genetic alterations and their influence on gene regulation in chronic lymphocytic leukemia

BACKGROUND

To understand the changes of gene regulation in carcinogenesis, we explored signals of DNA methylation - a stable epigenetic mark of gene regulatory elements - and designed a computational model to profile loss and gain of regulatory elements (REs) during carcinogenesis. We also utilized sequencing data to analyze the allele frequency of single nucleotide polymorphisms (SNPs) and detected the cancer-associated SNPs, i.e., the SNPs displaying the significant allele frequency difference between cancer and normal samples.

RESULTS

After applying this model to chronic lymphocytic leukemia (CLL) data, we identified REs differentially activated (dREs) between normal and CLL cells, consisting of 6,802 dREs gained and 4,606 dREs lost in CLL. The identified regulatory perturbations coincide with changes in the expression of target genes. In particular, the genes encoding DNA methyltransferases harbor multiple lost-in-cancer dREs and zero gained-in-cancer dREs, indicating that the damaged regulation of these genes might be one of the key causes of tumor formation. dREs display a significantly elevated density of the genome-wide association study (GWAS) SNPs associated with CLL and CLL-related traits. We observed that most of dRE GWAS SNPs associated with CLL and CLL-related traits (83%) display a significant haplotype association among the identified cancer-associated alleles and the risk alleles that have been reported in GWAS. Also dREs are enriched for the binding sites of the well-established B-cell and CLL transcription factors (TFs) NF-kB, AP2, P53, E2F1, PAX5, and SP1. We also identified CLL-associated SNPs and demonstrated that the mutations at these SNPs change the binding sites of key TFs much more frequently than expected.

CONCLUSIONS

Through exploring sequencing data measuring DNA methylation, we identified the epigenetic alterations (more specifically, DNA methylation) and genetic mutations along non-coding genomic regions CLL, and demonstrated that these changes play a critical role in carcinogenesis through damaging the regulation of key genes and alternating the binding of key TFs in B and CLL cells.

GW-SEM: A Statistical Package to Conduct Genome-Wide Structural Equation Modeling

Improving the accuracy of phenotyping through the use of advanced psychometric tools will increase the power to find significant associations with genetic variants and expand the range of possible hypotheses that can be tested on a genome-wide scale. Multivariate methods, such as structural equation modeling (SEM), are valuable in the phenotypic analysis of psychiatric and substance use phenotypes, but these methods have not been integrated into standard genome-wide association analyses because fitting a SEM at each single nucleotide polymorphism (SNP) along the genome was hitherto considered to be too computationally demanding. By developing a method that can efficiently fit SEMs, it is possible to expand the set of models that can be tested. This is particularly necessary in psychiatric and behavioral genetics, where the statistical methods are often handicapped by phenotypes with large components of stochastic variance. Due to the enormous amount of data that genome-wide scans produce, the statistical methods used to analyze the data are relatively elementary and do not directly correspond with the rich theoretical development, and lack the potential to test more complex hypotheses about the measurement of, and interaction between, comorbid traits. In this paper, we present a method to test the association of a SNP with multiple phenotypes or a latent construct on a genome-wide basis using a diagonally weighted least squares (DWLS) estimator for four common SEMs: a one-factor model, a one-factor residuals model, a two-factor model, and a latent growth model. We demonstrate that the DWLS parameters and p-values strongly correspond with the more traditional full information maximum likelihood parameters and p-values. We also present the timing of simulations and power analyses and a comparison with and existing multivariate GWAS software package.

Heritability of vaccine-induced measles neutralizing antibody titers

Understanding how genetics influences inter-individual variation of antibody titers in response to measles vaccination is vital to understanding possible sources of vaccine failure as well as improved vaccine development. Although it is recognized that both the human leukocyte antigen (HLA) genes and the immunoglobulin allotype genes play significant roles in immune response, there is significant variation in antibody titers that is not explained by these genes. To obtain a more complete estimate of the role of the entire genome, we used a large panel of single nucleotide polymorphisms to estimate the heritability of antibody response to measles vaccine. Based on 935 subjects with European ancestry, we estimated the heritability to be 49% (standard error 0.17). We also estimated the heritability attributable to each chromosome, and found a large range in chromosome-specific heritabilities. Notably, chromosome 1 had the largest estimate (28%), while chromosome 6, which harbors HLA, had an estimated heritability of 13%. Compared with a prior study of twins in the same community, which resulted in a heritability estimate of 88.5%, our study suggests there are either many rare genetic variants, or many common genetic variants of small effect sizes that contribute to variations of antibody titers in response to measles vaccine.

Novel linkage disequilibrium clustering algorithm identifies new lupus genes on meta-analysis of GWAS datasets

Systemic lupus erythematosus (SLE) is a complex disorder. Genetic association studies of complex disorders suffer from the following three major issues: phenotypic heterogeneity, false positive (type I error), and false negative (type II error) results. Hence, genes with low to moderate effects are missed in standard analyses, especially after statistical corrections. OASIS is a novel linkage disequilibrium clustering algorithm that can potentially address false positives and negatives in genome-wide association studies (GWAS) of complex disorders such as SLE. OASIS was applied to two SLE dbGAP GWAS datasets (6077 subjects; ∼0.75 million single-nucleotide polymorphisms). OASIS identified three known SLE genes viz. IFIH1, TNIP1, and CD44, not previously reported using these GWAS datasets. In addition, 22 novel loci for SLE were identified and the 5 SLE genes previously reported using these datasets were verified. OASIS methodology was validated using single-variant replication and gene-based analysis with GATES. This led to the verification of 60% of OASIS loci. New SLE genes that OASIS identified and were further verified include TNFAIP6, DNAJB3, TTF1, GRIN2B, MON2, LATS2, SNX6, RBFOX1, NCOA3, and CHAF1B. This study presents the OASIS algorithm, software, and the meta-analyses of two publicly available SLE GWAS datasets along with the novel SLE genes. Hence, OASIS is a novel linkage disequilibrium clustering method that can be universally applied to existing GWAS datasets for the identification of new genes.

Genome-wide association study of rust traits in orchardgrass using SLAF-seq technology

BACKGROUND

While orchardgrass (Dactylis glomerata L.) is a well-known perennial forage species, rust diseases cause serious reductions in the yield and quality of orchardgrass; however, genetic mechanisms of rust resistance are not well understood in orchardgrass.

RESULTS

In this study, a genome-wide association study (GWAS) was performed using specific-locus amplified fragment sequencing (SLAF-seq) technology in orchardgrass. A total of 2,334,889 SLAF tags were generated to produce 2,309,777 SNPs. ADMIXTURE analysis revealed unstructured subpopulations for 33 accessions, indicating that this orchardgrass population could be used for association analysis. Linkage disequilibrium (LD) analysis revealed an average r2 of 0.4 across all SNP pairs, indicating a high extent of LD in these samples. Through GWAS, a total of 4,604 SNPs were found to be significantly (P < 0.01) associated with the rust trait. The bulk analysis discovered a number of 5,211 SNPs related to rust trait. Two candidate genes, including cytochrome P450, and prolamin were implicated in disease resistance through prediction of functional genes surrounding each high-quality SNP (P < 0.01) associated with rust traits based on GWAS analysis and bulk analysis.

CONCLUSIONS

The large number of SNPs associated with rust traits and these two candidate genes may provide the basis for further research on rust resistance mechanisms and marker-assisted selection (MAS) for rust-resistant lineages.

A Review of the Genetics of Intracranial Berry Aneurysms and Implications for Genetic Counseling

Here we review the current understanding of the genetic architecture of intracranial berry aneurysms (IBA) to aid in the genetic counseling of patients at risk for this condition. The familial subtype of IBA, familial intracranial aneurysms (FIA), is associated with increased frequency of IBA, increased risk of rupture, and increased morbidity and mortality after rupture. Family history is the strongest predictor for the development of IBA. However, a genetic test is not yet available to assess risk within a family. Studies using linkage analysis, genome-wide association, and next-generation sequencing have found several candidate loci and genes associated with disease onset, but have not conclusively implicated a single gene. In addition to family history, a separate or concurrent diagnosis of autosomal dominant polycystic kidney disease is a strong genetic risk factor for IBA formation. We also discuss the relative risk for developing IBA in several Mendelian syndromes including vascular Ehlers-Danlos syndrome, Marfan syndrome, Neurofibromatosis Type I, and Loeys-Dietz syndrome.

Genomic characterization of a core set of the USDA-NPGS Ethiopian sorghum germplasm collection: implications for germplasm conservation, evaluation, and utilization in crop improvement

BACKGROUND

The USDA Agriculture Research Service National Plant Germplasm System (NPGS) preserves the largest sorghum germplasm collection in the world, which includes 7,217 accessions from the center of diversity in Ethiopia. The characterization of this exotic germplasm at a genome-wide scale will improve conservation efforts and its utilization in research and breeding programs. Therefore, we phenotyped a representative core set of 374 Ethiopian accessions at two locations for agronomic traits and characterized the genomes.

RESULTS

Using genotyping-by-sequencing, we identified 148,476 single-nucleotide polymorphism (SNP) markers distributed across the entire genome. Over half of the alleles were rare (frequency < 0.05). The genetic profile of each accession was unique (i.e., no duplicates), and the average genetic distance among accessions was 0.70. Based on population structure and cluster analyses, we separated the collection into 11 populations with pairwise F _ST values ranging from 0.11 to 0.47. In total, 198 accessions (53%) were assigned to one of these populations with an ancestry membership coefficient of larger than 0.60; these covered 90% of the total genomic variation. We characterized these populations based on agronomic and seed compositional traits. We performed a cluster analysis with the sorghum association panel based on 26,026 SNPs and determined that nine of the Ethiopian populations expanded the genetic diversity in the panel. Genome-wide association analysis demonstrated that these low-coverage data and the observed population structure could be employed for the genomic dissection of important phenotypes in this core set of Ethiopian sorghum germplasm.

CONCLUSIONS

The NPGS Ethiopian sorghum germplasm is a genetically and phenotypically diverse collection comprising 11 populations with high levels of admixture. Genetic associations with agronomic traits can be used to improve the screening of exotic germplasm for selection of specific populations. We detected many rare alleles, suggesting that this germplasm contains potentially useful undiscovered alleles, but their discovery and characterization will require extensive effort. The genotypic data available for these accessions provide a valuable resource for sorghum breeders and geneticists to effectively improve crops.

Eigen-Epistasis for detecting gene-gene interactions

BACKGROUND

A large amount of research has been devoted to the detection and investigation of epistatic interactions in genome-wide association studies (GWASs). Most of the literature focuses on low-order interactions between single-nucleotide polymorphisms (SNPs) with significant main effects.

RESULTS

In this paper we propose an original approach for detecting epistasis at the gene level, without systematically filtering on significant genes. We first compute interaction variables for each gene pair by finding its Eigen-Epistasis component, defined as the linear combination of Gene SNPs having the highest correlation with the phenotype. The selection of significant effects is done using a penalized regression method based on Group Lasso controlling the False Discovery Rate.

CONCLUSION

The method is tested against two recent alternative proposals from the literature using synthetic data, and shows good performances in different settings. We demonstrate the power of our approach by detecting new gene-gene interactions on three genome-wide association studies.

[Function and mechanism of zinc finger protein ZNF50 in inhibiting the growth of esophageal squamous cell carcinoma cells]

Objective: To investigate the function and mechanism of zinc finger protein 750 (ZNF750) in esophageal squamous cell carcinoma (ESCC). Methods: Xenograft in nude mice was applied to detect the tumorigenesis of ZNF750-depleted ESCC cells. Western blot was performed to observe the expression of downstream target protein of ZNF750 in ESCC cell lines and xenograft tumor tissues in which ZNF750 was knocked down. 3-(4, 5-dimethyl-2-thiazolyl)-2, 5-diphenyl-2H tetrazolium bromide (MTT) assay was used to determine the proliferation of ZNF750 stably depleted cells after restoration of its target protein. Results: The tumor weight of blank control, negative control and ZNF750 knockdown groups was 137±26 mg, 161±31 mg and 463±89 mg, respectively, with a statistically significant difference (P<0.01). The expressions of Kruppel-like factor 4 (KLF4) in ZNF750-depleted ESCC cells and its derived tumor tissue xenograft in nude mice were significantly down-regulated. Restoration of KLF4 in ZNF750 stably depleted cells significantly inhibited the cell proliferation (P<0.01). Conclusions: ZNF750 may be a new tumor suppressor in the tumorigenesis of ESCC, and the inhibition of cell proliferation induced by ZNF750 may be partially through the regulation of KLF4 expression.

Genetic studies of alcohol dependence in the context of the addiction cycle

Family, twin and adoption studies demonstrate clearly that alcohol dependence and alcohol use disorders are phenotypically complex and heritable. The heritability of alcohol use disorders is estimated at approximately 50-60% of the total phenotypic variability. Vulnerability to alcohol use disorders can be due to multiple genetic or environmental factors or their interaction which gives rise to extensive and daunting heterogeneity. This heterogeneity makes it a significant challenge in mapping and identifying the specific genes that influence alcohol use disorders. Genetic linkage and (candidate gene) association studies have been used now for decades to map and characterize genomic loci and genes that underlie the genetic vulnerability to alcohol use disorders. These approaches have been moderately successful in identifying several genes that contribute to the complexity of alcohol use disorders. Recently, genome-wide association studies have become one of the major tools for identifying genes for alcohol use disorders by examining correlations between millions of common single-nucleotide polymorphisms with diagnosis status. Genome-wide association studies are just beginning to uncover novel biology; however, the functional significance of results remains a matter of extensive debate and uncertainty. In this review, we present a select group of genome-wide association studies of alcohol dependence, as one example of a way to generate functional hypotheses, within the addiction cycle framework. This analysis may provide novel directions for validating the functional significance of alcohol dependence candidate genes. This article is part of the Special Issue entitled "Alcoholism".

Phenotype-Specific Association of Single-Nucleotide Polymorphisms with Heart Failure and Preserved Ejection Fraction: a Genome-Wide Association Analysis of the Cardiovascular Health Study

Little is known about genetics of heart failure with preserved ejection fraction (HFpEF) in part because of the many comorbidities in this population. To identify single-nucleotide polymorphisms (SNPs) associated with HFpEF, we analyzed phenotypic and genotypic data from the Cardiovascular Health Study, which profiled patients using a 50,000 SNP array. Results were explored using novel SNP- and gene-centric tools. We performed analyses to determine whether some SNPs were relevant only in certain phenotypes. Among 3804 patients, 7 clinical factors and 9 SNPs were significantly associated with HFpEF; the most notable of which was rs6996224, a SNP associated with transforming growth factor-beta receptor 3. Most SNPs were associated with HFpEF only in the absence of a clinical predictor. Significant SNPs represented genes involved in myocyte proliferation, transforming growth factor-beta/erbB signaling, and extracellular matrix formation. These findings suggest that genetic factors may be more important in some phenotypes than others.

Clinical utility and functional analysis of variants in atrial fibrillation-associated locus 4q25

BACKGROUND

Chromosome 4q25 has been repeatedly identified as atrial fibrillation (AF)-sensitive locus in multiple genome-wide association studies (GWAS) and is considered to hold some clues to AF pathogenesis. We aimed to investigate the clinical utilities in Japanese and to unveil the function of the 4q25 locus in affecting transcription of adjacent genes.

METHODS

We conducted AF GWAS in Japanese population (1382 AF cases and 1478 controls) and the replication panel (1666 AF cases and 1229 controls) with detailed clinical information which showed the acceleration of AF onset. Stepwise investigations with linkage disequilibrium analysis, histone code patterns, and reporter assay in the 4q25 locus were performed.

RESULTS

The AF GWAS confirmed a significant association of rs4611994 and rs1906617 in chromosome 4q25 with AF. In the clinical analysis, AF onset of the individuals with risk allele accelerated 2.5 years compared with those with protective allele (p=0.00012). Next, in the functional analysis, three single nucleotide polymorphisms (SNPs) in the variant group selected by linkage disequilibrium analysis were identified as candidates for the cis-regulatory element toward adjacent genes in chromatin immunoprecipitation assay. Among them, rs4611994 and rs72900144 regions showed higher effects on the transcriptional activity of luciferase gene in the risk alleles than those in the protective alleles (p<0.0001, p<0.005, respectively).

CONCLUSIONS

AF GWAS in Japanese confirmed the association with 4q25 locus and indicated that its SNP affected the acceleration of AF onset. The candidate regions of the causative SNPs, rs4611994 and rs72900144, could alter the adjacent gene expression level.

SCOPA and META-SCOPA: software for the analysis and aggregation of genome-wide association studies of multiple correlated phenotypes

Background

Genome-wide association studies (GWAS) of single nucleotide polymorphisms (SNPs) have been successful in identifying loci contributing genetic effects to a wide range of complex human diseases and quantitative traits. The traditional approach to GWAS analysis is to consider each phenotype separately, despite the fact that many diseases and quantitative traits are correlated with each other, and often measured in the same sample of individuals. Multivariate analyses of correlated phenotypes have been demonstrated, by simulation, to increase power to detect association with SNPs, and thus may enable improved detection of novel loci contributing to diseases and quantitative traits.

Results

We have developed the SCOPA software to enable GWAS analysis of multiple correlated phenotypes. The software implements “reverse regression” methodology, which treats the genotype of an individual at a SNP as the outcome and the phenotypes as predictors in a general linear model. SCOPA can be applied to quantitative traits and categorical phenotypes, and can accommodate imputed genotypes under a dosage model. The accompanying META-SCOPA software enables meta-analysis of association summary statistics from SCOPA across GWAS. Application of SCOPA to two GWAS of high-and low-density lipoprotein cholesterol, triglycerides and body mass index, and subsequent meta-analysis with META-SCOPA, highlighted stronger association signals than univariate phenotype analysis at established lipid and obesity loci. The META-SCOPA meta-analysis also revealed a novel signal of association at genome-wide significance for triglycerides mapping to GPC5 (lead SNP rs71427535, p = 1.1x10⁻⁸), which has not been reported in previous large-scale GWAS of lipid traits.

Conclusions

The SCOPA and META-SCOPA software enable discovery and dissection of multiple phenotype association signals through implementation of a powerful reverse regression approach.

A novel approach to genome-wide association analysis identifies genetic associations with primary biliary cholangitis and primary sclerosing cholangitis in Polish patients

Background

Primary biliary cholangitis (PBC) and primary sclerosing cholangitis (PSC) are forms of hepatic autoimmunity, and risk for both diseases has a strong genetic component. This study aimed to define the genetic architecture of PBC and PSC within the Polish population.

Methods

Subjects were 443 women with PBC, 120 patients with PSC, and 934 healthy controls recruited from Gastroenterology Departments in various Polish hospitals. Allelotyping employed a pooled-DNA sample-based genome-wide association study (GWAS) approach, using Illumina Human Omni2.5-Exome BeadChips and the following novel selection criteria for risk loci: blocks of at least 10 single nucleotide polymorphisms (SNPs) in strong linkage disequilibrium, where the distance between each adjacent SNP pair in the block was less than 30 kb, and each SNP was associated with disease at a significance level of P < 0.005. A selected index SNP from each block was validated using TaqMan SNP genotyping assays.

Results

Nineteen and twenty-one SNPs were verified as associated with PBC and PSC, respectively, by individual genotyping; 19 (10/9, PBC/PSC) SNPs reached a stringent (corrected) significance threshold and a further 21 (9/12, PBC/PSC) reached a nominal level of significance (P < 0.05 with odds ratio (OR) > 1.2 or < 0.83), providing suggestive evidence of association. The SNPs mapped to seven (1p31.3, 3q13, 6p21, 7q32.1, 11q23.3, 17q12, 19q13.33) and one (6p21) chromosome region previously associated with PBC and PSC, respectively. The SNP, rs35730843, mapping to the POLR2G gene promoter (P = 1.2 × 10^-5, OR = 0.39) demonstrated the highest effect size, and was protective for PBC, whereas for PSC respective SNPs were: rs13191240 in the intron of ADGRB3 gene (P = 0.0095, OR = 0.2) and rs3822659 (P = 0.0051, OR = 0.236) along with rs9686714 (P = 0.00077, OR = 0.2), both located in the WWC1 gene.

Conclusions

Our cost-effective GWAS approach followed by individual genotyping confirmed several previously identified associations and discovered new susceptibility loci associated with PBC and/or PSC in Polish patients. However, further functional studies are warranted to understand the roles of these newly identified variants in the development of the two disorders.

Electronic supplementary material

The online version of this article (doi:10.1186/s12920-016-0239-9) contains supplementary material, which is available to authorized users.

Identification of novel candidate genes for the inverted teat defect in sows using a genome-wide marker panel

The number of functional teats is an important selection criterion in pig breeding. Inherited defects of the udder, such as the inverted teat, do have a considerable negative impact on the nursing ability of the sow. To investigate the genetic background of this defect and the number of functional teats in Swedish maternal lines, samples from 230 Yorkshire pigs were selected for genotyping using the PorcineSNP60K BeadChip (Illumina Inc.), each pig with at least one inverted teat was matched with one non-affected pig (fullsib or pairs with matching herd and gender). A genome-wide association study on these 230 pigs was performed using the two-step approach implemented in GenABEL using 46,652 single nucleotide polymorphisms across all autosomes and the X chromosome. A number of significant regions were identified for the inverted teat defect on chromosomes 2, 10, and 18. Many of the regions associated with the number of functional teats were located in the same or close regions, except two associated markers on the X chromosome and one on chromosome 3. We identified some of the regions on chromosomes previously reported in one linkage and one gene expression study. We conclude, despite being able to suggest new candidate genes, that further studies are needed to better understand the biologic background of the teat development. Despite the in-depth comparison of identified regions for the inverted teat defect done here, more studies are required to allow a clear identification of genetic regions relevant for this defect across many pig populations.

Previous GWAS hits in relation to young-onset breast cancer

PURPOSE

Genome-wide association studies (GWAS) have identified dozens of single-nucleotide polymorphisms (SNPs) associated with breast cancer. Few studies focused on young-onset breast cancer, which exhibits etiologic and tumor-type differences from older-onset disease. Possible confounding by prenatal effects of the maternal genome has also not been considered.

METHODS

Using a family-based design for breast cancer before age 50, we assessed the relationship between breast cancer and 77 GWAS-identified breast cancer risk SNPs. We estimated relative risks (RR) for inherited and maternally mediated genetic effects. We also used published RR estimates to calculate genetic risk scores and model joint effects.

RESULTS

Seventeen of the candidate SNPs were nominally associated with young-onset breast cancer in our 1296 non-Hispanic white affected families (uncorrected p value <0.05). Top-ranked SNPs included rs3803662-A (TOX3, RR = 1.39; p = 7.0 × 10-6), rs12662670-G (ESR1, RR = 1.56; p = 5.7 × 10-4), rs2981579-A (FGFR2, RR = 1.24; p = 0.002), and rs999737-G (RAD51B, RR = 1.37; p = 0.003). No maternally mediated effects were found. A risk score based on all 77 SNPs indicated that their overall relationship to young-onset breast cancer risk was more than additive (additive-fit p = 2.2 × 10-7) and consistent with a multiplicative joint effect (multiplicative-fit p = 0.27). With the multiplicative formulation, the case sister's genetic risk score exceeded that of her unaffected sister in 59% of families.

CONCLUSIONS

The results of this family-based study indicate that no effects of previously identified risk SNPs were explained by prenatal effects of maternal variants. Many of the known breast cancer risk variants were associated with young-onset breast cancer, with evidence that TOX3, ESR1, FGFR2, and RAD51B are important for young-onset disease.

The genetics of alcohol dependence and alcohol-related liver disease

The susceptibility to developing alcohol dependence and significant alcohol-related liver injury is determined by a number of constitutional, environmental and genetic factors, although the nature and level of interplay between them remains unclear. The familiality and heritability of alcohol dependence is well-documented but, to date, no strong candidate genes conferring increased risk have emerged, although variants in alcohol dehydrogenase and acetaldehyde dehydrogenase have been shown to confer protection, predominantly in individuals of East Asian ancestry. Population contamination with confounders such as drug co-dependence and psychiatric and physical co-morbidity may explain the essentially negative genome-wide association studies in this disorder. The familiality and hereditability of alcohol-related cirrhosis is not as well-documented but three strong candidate genes PNPLA3, TM6SF2 and MBOAT7, have been identified. The mechanisms by which variants in these genes confer risk and the nature of the functional interplay between them remains to be determined but, when elucidated, will undoubtedly increase our understanding of the pathophysiology of this disease. The way in which this genetic information could potentially inform patient management has yet to be determined and tested.

Mendelian Randomization

Confounding and reverse causality have prevented us from drawing meaningful clinical interpretation even in well-powered observational studies. Confounding may be attributed to our inability to randomize the exposure variable in observational studies. Mendelian randomization (MR) is one approach to overcome confounding. It utilizes one or more genetic polymorphisms as a proxy for the exposure variable of interest. Polymorphisms are randomly distributed in a population, they are static throughout an individual's lifetime, and may thus help in inferring directionality in exposure-outcome associations. Genome-wide association studies (GWAS) or meta-analyses of GWAS are characterized by large sample sizes and the availability of many single nucleotide polymorphisms (SNPs), making GWAS-based MR an attractive approach. GWAS-based MR comes with specific challenges, including multiple causality. Despite shortcomings, it still remains one of the most powerful techniques for inferring causality.With MR still an evolving concept with complex statistical challenges, the literature is relatively scarce in terms of providing working examples incorporating real datasets. In this chapter, we provide a step-by-step guide for causal inference based on the principles of MR with a real dataset using both individual and summary data from unrelated individuals. We suggest best possible practices and give recommendations based on the current literature.

Data analysis in the post-genome-wide association study era

Since the first report of a genome-wide association study (GWAS) on human age-related macular degeneration, GWAS has successfully been used to discover genetic variants for a variety of complex human diseases and/or traits, and thousands of associated loci have been identified. However, the underlying mechanisms for these loci remain largely unknown. To make these GWAS findings more useful, it is necessary to perform in-depth data mining. The data analysis in the post-GWAS era will include the following aspects: fine-mapping of susceptibility regions to identify susceptibility genes for elucidating the biological mechanism of action; joint analysis of susceptibility genes in different diseases; integration of GWAS, transcriptome, and epigenetic data to analyze expression and methylation quantitative trait loci at the whole-genome level, and find single-nucleotide polymorphisms that influence gene expression and DNA methylation; genome-wide association analysis of disease-related DNA copy number variations. Applying these strategies and methods will serve to strengthen GWAS data to enhance the utility and significance of GWAS in improving understanding of the genetics of complex diseases or traits and translate these findings for clinical applications.

Eosinophilic Esophagitis: A Comprehensive Review

Eosinophilic esophagitis (EoE) is an emerging chronic atopic clinical-pathologic disease with an estimated prevalence of 1/1000 similar to the one of Crohn's diseases. Usually, EoE is firstly suspected due to symptoms that are caused by esophageal dysfunction and/or fibrosis. EoE diagnosis is confirmed if the esophageal biopsy shows at least 15 eosinophils per high power field (eos/hpf) as a peak value in one or more of at least four specimens obtained randomly from the esophagus. Most of the patients affected by EoE have other atopic diseases such as allergic rhinitis, asthma, IgE-mediated food allergies, and/or atopic dermatitis. The local inflammation is a T helper type 2 (Th2) flogosis, which most likely is driven by a mixed IgE and non-IgE-mediated reaction to food and/or environmental allergens. Recently published genetic studies showed also that EoE is associated with single nucleotide polymorphism (SNP) on genes which are important in atopic inflammation such as thymic stromal lymphopoietin (TSLP) located close to the Th2 cytokine cluster (IL-4, IL-5, IL-13) on chromosome 5q22. When the EoE diagnosis is made, it is imperative to control the local eosinophilic inflammation not only to give symptomatic relief to the patient but also to prevent complications such as esophageal stricture and food impaction. EoE is treated like many other atopic diseases with a combination of topical steroids and/or food antigen avoidance.

Meta-analysis for genome-wide association studies using case-control design: application and practice

This review aimed to arrange the process of a systematic review of genome-wide association studies in order to practice and apply a genome-wide meta-analysis (GWMA). The process has a series of five steps: searching and selection, extraction of related information, evaluation of validity, meta-analysis by type of genetic model, and evaluation of heterogeneity. In contrast to intervention meta-analyses, GWMA has to evaluate the Hardy-Weinberg equilibrium (HWE) in the third step and conduct meta-analyses by five potential genetic models, including dominant, recessive, homozygote contrast, heterozygote contrast, and allelic contrast in the fourth step. The 'genhwcci' and 'metan' commands of STATA software evaluate the HWE and calculate a summary effect size, respectively. A meta-regression using the 'metareg' command of STATA should be conducted to evaluate related factors of heterogeneities.

Gene-environment interaction in type 2 diabetes

Type 2 diabetes is a typical multifactorial disease, but the causes can largely be divided into genetic and environmental factors. In recent years, focus has shifted to the interaction between these factors (i.e., gene-environment interactions). It has become widely known that changes in the intrauterine environment such as intrauterine growth restriction result in gene expression changes in various tissues, which ultimately lead to the onset of diabetes. Epigenetic modification is considered to be a particularly important mechanism in these effects, as it is easily affected by environmental changes that occur during the fetal and neonatal periods. Moreover, recent reports have revealed that epigenetic modifications are passed down through generations. Although genome-wide association studies have identified many type 2 diabetes susceptibility genes, these genes do not pose a significantly high risk when isolated as single factors. In particular, it has been suggested that the interaction of the FTO or KCNQ1 genes with environmental factors increases the incidence of diabetes. These findings suggest that detailed analyses of individual gene-environment interactions hold promise for gaining new insight into the mechanisms and risk factors contributing to type 2 diabetes, with application to personalized diagnoses and treatments. We look forward to future developments in this regard.

Genome-wide association study identifies variants in HORMAD2 associated with tonsillectomy

BACKGROUND

Inflammation of the tonsils is a normal response to infection, but some individuals experience recurrent, severe tonsillitis and massive hypertrophy of the tonsils in which case surgical removal of the tonsils may be considered.

OBJECTIVE

To identify common genetic variants associated with tonsillectomy.

METHODS

We used tonsillectomy information from Danish health registers and carried out a genome-wide association study comprising 1464 patients and 12 019 controls of Northwestern European ancestry, with replication in an independent sample set of 1575 patients and 1367 controls.

RESULTS

The variant rs2412971, intronic in HORMAD2 at chromosome 22q12.2, was robustly associated with tonsillectomy (OR=1.22; p=1.48×10^-9) and is highly correlated with SNPs previously found to be associated with IgA nephropathy, Crohn's disease (CD) and early onset inflammatory bowel disease (IBD). The risk allele for tonsillectomy corresponded to increased risk of IgA nephropathy and decreased risk of CD and IBD. We further performed lookup analyses of the top SNP for outcomes related to tonsillectomy in the combined discovery and replication sample and found that rs2412971 was associated with acute tonsillitis (OR=1.19; p=7.82×10^-4), chronic disease of the tonsils (OR=1.19; p=2.32×10^-6) and appendectomy (OR=1.18; p=1.13×10^-3).

CONCLUSIONS

We identified and replicated a genetic association at 22q12.2 with tonsillectomy. Further functional investigation is required to illuminate whether the molecular mechanisms underlying the genetic association involve general lymphoid hyper-reaction throughout the mucosa-associated lymphoid tissue system.

A genome-wide association study of emotion dysregulation: Evidence for interleukin 2 receptor alpha

Emotion dysregulation has been implicated as a risk factor for many psychiatric conditions. Therefore, examining genetic risk associated with emotion dysregulation could help inform cross-disorder risk more generally. A genome-wide association study (GWAS) of emotion dysregulation using single nucleotide polymorphism (SNP) array technology was conducted in a highly traumatized, minority, urban sample (N = 2600, males = 774). Post-hoc analyses examined associations between SNPs identified in the GWAS and current depression, posttraumatic stress disorder (PTSD), and history of suicide attempt. Methylation quantitative trait loci were identified and gene set enrichment analyses were used to broadly determine biological processes involved with these SNPs. Among males, SNP rs6602398, located within the interleukin receptor 2A gene, IL2RA, was significantly associated with emotion dysregulation (p = 1.1 × 10^-8). Logistic regression analyses revealed this SNP was significantly associated with depression (Exp(B) = 2.67, p < 0.001) and PTSD (Exp(B) = 2.07, p < 0.01). This SNP was associated with differential DNA methylation (p < 0.05) suggesting it may be functionally active. Finally, through gene set enrichment analyses, ten psychiatric disease pathways (adjusted p < 0.01) and the calcium signaling pathway (adjusted p = 0.008) were significantly associated with emotion dysregulation. We found initial evidence for an association between emotion dysregulation and genetic risk loci that have already been implicated in medical disorders that have high comorbidity with psychiatric disorders. Our results provide further evidence that emotion dysregulation can be understood as a potential psychiatric cross-disorder risk factor, and that sex differences across these phenotypes may be critical. Continued research into genetic and biological risk associated with emotion dysregulation is needed.

Meta-analysis of genome-wide association studies of HDL cholesterol response to statins

BACKGROUND

In addition to lowering low density lipoprotein cholesterol (LDL-C), statin therapy also raises high density lipoprotein cholesterol (HDL-C) levels. Inter-individual variation in HDL-C response to statins may be partially explained by genetic variation.

METHODS AND RESULTS

We performed a meta-analysis of genome-wide association studies (GWAS) to identify variants with an effect on statin-induced high density lipoprotein cholesterol (HDL-C) changes. The 123 most promising signals with p<1×10-4 from the 16 769 statin-treated participants in the first analysis stage were followed up in an independent group of 10 951 statin-treated individuals, providing a total sample size of 27 720 individuals. The only associations of genome-wide significance (p<5×10-8) were between minor alleles at the CETP locus and greater HDL-C response to statin treatment.

CONCLUSIONS

Based on results from this study that included a relatively large sample size, we suggest that CETP may be the only detectable locus with common genetic variants that influence HDL-C response to statins substantially in individuals of European descent. Although CETP is known to be associated with HDL-C, we provide evidence that this pharmacogenetic effect is independent of its association with baseline HDL-C levels.

Optimizing R with SparkR on a commodity cluster for biomedical research

BACKGROUND AND OBJECTIVES

Medical researchers are challenged today by the enormous amount of data collected in healthcare. Analysis methods such as genome-wide association studies (GWAS) are often computationally intensive and thus require enormous resources to be performed in a reasonable amount of time. While dedicated clusters and public clouds may deliver the desired performance, their use requires upfront financial efforts or anonymous data, which is often not possible for preliminary or occasional tasks. We explored the possibilities to build a private, flexible cluster for processing scripts in R based on commodity, non-dedicated hardware of our department.

METHODS

For this, a GWAS-calculation in R on a single desktop computer, a Message Passing Interface (MPI)-cluster, and a SparkR-cluster were compared with regards to the performance, scalability, quality, and simplicity.

RESULTS

The original script had a projected runtime of three years on a single desktop computer. Optimizing the script in R already yielded a significant reduction in computing time (2 weeks). By using R-MPI and SparkR, we were able to parallelize the computation and reduce the time to less than three hours (2.6 h) on already available, standard office computers. While MPI is a proven approach in high-performance clusters, it requires rather static, dedicated nodes. SparkR and its Hadoop siblings allow for a dynamic, elastic environment with automated failure handling. SparkR also scales better with the number of nodes in the cluster than MPI due to optimized data communication.

CONCLUSION

R is a popular environment for clinical data analysis. The new SparkR solution offers elastic resources and allows supporting big data analysis using R even on non-dedicated resources with minimal change to the original code. To unleash the full potential, additional efforts should be invested to customize and improve the algorithms, especially with regards to data distribution.

Replication of Caucasian Loci Associated with Osteoporosis-related Traits in East Asians

Background

Most reported genome-wide association studies (GWAS) seeking to identify the loci of osteoporosis-related traits have involved Caucasian populations. We aimed to identify the single nucleotide polymorphisms (SNPs) of osteoporosis-related traits among East Asian populations from the bone mineral density (BMD)-related loci of an earlier GWAS meta-analysis.

Methods

A total of 95 SNPs, identified at the discovery stage of the largest GWAS meta-analysis of BMD, were tested to determine associations with osteoporosis-related traits (BMD, osteoporosis, or fracture) in Korean subjects (n=1,269). The identified SNPs of osteoporosis-related traits in Korean subjects were included in the replication analysis using Chinese (n=2,327) and Japanese (n=768) cohorts.

Results

A total of 17 SNPs were associated with low BMD in Korean subjects. Specifically, 9, 6, 9, and 5 SNPs were associated with the presence of osteoporosis, non-vertebral fractures, vertebral fractures, and any fracture, respectively. Collectively, 35 of the 95 SNPs (36.8%) were associated with one or more osteoporosis-related trait in Korean subjects. Of the 35 SNPs, 19 SNPs (54.3%) were also associated with one or more osteoporosis-related traits in East Asian populations. Twelve SNPs were associated with low BMD in the Chinese and Japanese cohorts. Specifically, 3, 4, and 2 SNPs were associated with the presence of hip fractures, vertebral fractures, and any fracture, respectively.

Conclusions

Our results identified the common SNPs of osteoporosis-related traits in both Caucasian and East Asian populations. These SNPs should be further investigated to assess whether they are true genetic markers of osteoporosis.

Genetic susceptibility to cutaneous radiation injury

The use of ionizing radiation is critical to cancer treatment and fluoroscopic procedures. However, despite efforts to minimize total radiation dose, many patients experience toxic cutaneous side-effects of ionizing radiation, ranging from mild erythema to subcutaneous fibrosis, telangiectasia formation, and ulceration. Extent of injury is highly variable among patients. Studying the genetic determinants of radiation injury can help develop protocols to reduce radiation toxicity, as well as drive research into effective modulators of the genes and gene products associated with radiation injury. Many studies in the past two decades have identified single-nucleotide polymorphisms that may be associated with susceptibility to cutaneous radiation injury, such as those in genes related to the following cellular responses to ionizing radiation: inflammation, DNA repair, oxidation and stress response, and cell-cycle and apoptosis. This review summarizes the current literature on potential major genes and polymorphisms, in the previously described damage response pathways, that are involved in susceptibility to cutaneous radiation injury. Potential pitfalls of current research and further avenues of discovery will be explored.

What can time-frequency and phase coherence measures tell us about the genetic basis of P3 amplitude?

In a recent comprehensive investigation, we largely failed to identify significant genetic markers associated with P3 amplitude or to corroborate previous associations between P3 and specific single nucleotide polymorphisms (SNPs) or genes. In the present study we extended this line of investigation to examine time-frequency (TF) activity and intertrial phase coherence (ITPC) in the P3 time window, both of which are associated with P3 amplitude. Previous genome-wide research has reported associations between P3-related theta and delta activity and individual genetic variants. A large, population-based sample of 4211 subjects, comprising male and female adolescent twins and their parents, was genotyped for 527,828 single nucleotide polymorphisms (SNPs), from which over six million SNPs were accurately imputed. Heritability estimates were greater for TF energy than ITPC, whether based on biometric models or the combined influence of all measured SNPs (derived from genome-wide complex trait analysis). The magnitude of overlap in the specific SNPs associated with delta energy and ITPC and P3 amplitude was significant. A genome-wide analysis of all SNPs, accompanied by an analysis of approximately 17,600 genes, indicated a region of chromosome 2 around TEKT4 that was significantly associated with theta ITPC. Analysis of candidate SNPs and genes previously reported to be associated with P3 or related phenotypes yielded one association surviving correction for multiple tests: between theta energy and CRHR1. However, we did not obtain significant associations for SNPs implicated in previous genome-wide studies of TF measures. Identifying specific genetic variants associated with P3 amplitude remains a challenge.

A genome-wide association study of essential hypertension in an Australian population using a DNA pooling approach

Despite the success of genome-wide association studies (GWAS) in detecting genetic loci involved in complex traits, few susceptibility genes have been detected for essential hypertension (EH). We aimed to use pooled DNA GWAS approach to identify and validate novel genomic loci underlying EH susceptibility in an Australian case-control population. Blood samples and questionnaires detailing medical history, blood pressure, and prescribed medications were collected for 409 hypertensives and 409 age-, sex- and ethnicity-matched normotensive controls. Case and control DNA were pooled in quadruplicate and hybridized to Illumina 1 M-Duo arrays. Allele frequencies agreed with those reported in reference data and known EH association signals were represented in the top-ranked SNPs more frequently than expected by chance. Validation showed that pooled DNA GWAS gave reliable estimates of case and control allele frequencies. Although no markers reached Bonferroni-corrected genome-wide significance levels (5.0 × 10^-8), the top marker rs34870220 near ASGR1 approached significance (p = 4.32 × 10^-7), as did several candidate loci (p < 1 × 10^-6) on chromosomes 2, 4, 6, 9, 12, and 17. Four markers (located in or near genes NHSL1, NKFB1, GLI2, and LRRC10) from the top ten ranked SNPs were individually genotyped in pool samples and were tested for association between cases and controls using the χ ² test. Of these, rs1599961 (NFKB1) and rs12711538 (GLI2) showed significant difference between cases and controls (p < 0.01). Additionally, four top-ranking markers within NFKB1 were found to be in LD, suggesting a single strong association signal for this gene.

Pooled genome wide association detects association upstream of FCRL3 with Graves' disease

Background

Graves’ disease is an autoimmune thyroid disease of complex inheritance. Multiple genetic susceptibility loci are thought to be involved in Graves’ disease and it is therefore likely that these can be identified by genome wide association studies. This study aimed to determine if a genome wide association study, using a pooling methodology, could detect genomic loci associated with Graves’ disease.

Results

Nineteen of the top ranking single nucleotide polymorphisms including HLA-DQA1 and C6orf10, were clustered within the Major Histo-compatibility Complex region on chromosome 6p21, with rs1613056 reaching genome wide significance (p = 5 × 10⁻⁸). Technical validation of top ranking non-Major Histo-compatablity complex single nucleotide polymorphisms with individual genotyping in the discovery cohort revealed four single nucleotide polymorphisms with p ≤ 10⁻⁴. Rs17676303 on chromosome 1q23.1, located upstream of FCRL3, showed evidence of association with Graves’ disease across the discovery, replication and combined cohorts. A second single nucleotide polymorphism rs9644119 downstream of DPYSL2 showed some evidence of association supported by finding in the replication cohort that warrants further study.

Conclusions

Pooled genome wide association study identified a genetic variant upstream of FCRL3 as a susceptibility locus for Graves’ disease in addition to those identified in the Major Histo-compatibility Complex. A second locus downstream of DPYSL2 is potentially a novel genetic variant in Graves’ disease that requires further confirmation.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3276-z) contains supplementary material, which is available to authorized users.

Genetics of Parkinson's disease

Almost two decades after the identification of SNCA as the first causative gene in Parkinson's disease (PD) and the subsequent understanding that genetic factors play a substantial role in PD development, our knowledge of the genetic architecture underlying this disease has vastly improved. Approximately 5-10% of patients suffer from a monogenic form of PD where autosomal dominant mutations in SNCA, LRRK2, and VPS35 and autosomal recessive mutations in PINK1, DJ-1, and Parkin cause the disease with high penetrance. Furthermore, recent whole-exome sequencing have described autosomal recessive DNAJC6 mutations in predominately atypical, but also cases with typical PD. In addition, several other genes have been linked to atypical Parkinsonian phenotypes. However, the vast majority of PD is genetically complex, i.e. it is caused by the combined action of common genetic variants in concert with environmental factors. By the application of genome-wide association studies, 26 PD risk loci have been established to date. Similar to other genetically complex diseases, these show only moderate effects on PD risk. Increasing this etiologic complexity, many of the involved genetic and environmental risk factors likely interact in an intricate fashion. This article aims to provide a comprehensive overview of the current knowledge in PD genetics.

Association of 3q13.32 variants with hip trochanter and intertrochanter bone mineral density identified by a genome-wide association study

We performed a GWAS of trochanter and intertrochanter bone mineral density (BMD) in the Framingham Heart Study and replicated in three independent studies. Our results identified one novel locus around the associated variations at chromosomal region 3q13.32 and replicated two loci at chromosomal regions 3p21 and 8q24. Our findings provide useful insights that enhance our understanding of bone development, osteoporosis, and fracture pathogenesis.

INTRODUCTION

Hip trochanter (TRO) and intertrochanter (INT) subregions have important clinical relevance to subtrochanteric and intertrochanteric fractures but have rarely been studied by genome-wide association studies (GWASs).

METHODS

Aiming to identify genomic loci associated with BMD variation at TRO and INT regions, we performed a GWAS utilizing the Framingham Heart Study (FHS, N = 6,912) as discovery sample and utilized the Women's Health Initiative (WHI) African-American subsample (N = 845), WHI Hispanic subsample (N = 446), and Omaha osteoporosis study (N = 971), for replication.

RESULTS

Combining the evidence from both the discovery and the replication samples, we identified one novel locus around the associated variations at chromosomal region 3q13.32 (rs1949542, discovery p = 6.16 × 10^-8, replication p = 2.86 × 10^-4 for INT-BMD; discovery p = 1.35 × 10^-7, replication p = 4.16 × 10^-4 for TRO-BMD, closest gene RP11-384F7.1). We also replicated two loci at chromosomal regions 3p21 (rs148725943, discovery p = 6.61 × 10^-7, replication p = 5.22 × 10^-4 for TRO-BMD, closest gene CTNNB1) and 8q24 (rs7839059, discovery p = 2.28 × 10^-7, replication p = 1.55 × 10^-3 for TRO-BMD, closest gene TNFRSF11B) that were reported previously. We demonstrated that the effects at both 3q13.32 and 3p21 were specific to the TRO, but not to the femoral neck and spine. In contrast, the effect at 8q24 was common to all the sites.

CONCLUSION

Our findings provide useful insights that enhance our understanding of bone development, osteoporosis, and fracture pathogenesis.

Genetic Variants and Multiple Sclerosis Risk Gene SLC9A9 Expression in Distinct Human Brain Regions

A recent genome-wide association study reported a significant association between rs9828519 (G) and nonresponsiveness to interferon-beta (IFN-β) treatment and dysregulation of SLC9A9 expression in multiple sclerosis (MS) cases. We hypothesize that disease-relevant tissues are necessary to detect the effects of rs9828519-tagged SNPs on SLC9A9 expression. Here, we investigated whether SLC9A9 expression is regulated by rs9828519-tagged SNPs in human brain tissue. We used HaploReg to identify the proxy SNPs of the rs9828519 variant based on linkage disequilibrium information from the 1000 Genomes Project. We evaluated the potential association between these SNPs and SLC9A9 expression using multiple expression quantitative trait loci datasets including 10 brain regions of 134 individuals from Braineac, 2 brain regions of 773 samples from brain expression GWAS datasets, and 12 brain regions from the GTEx. We discovered differential SLC9A9 expression in different brain regions and identified 15 rs9828519-tagged SNPs that significantly regulated SLC9A9 expression only in occipital cortex, intralobular white matter, and substantia nigra. Our results advance the understanding of the involvement of SLC9A9 and rs9828519 mechanisms in MS.

Pharmacogenomic Study of Clozapine-Induced Agranulocytosis/Granulocytopenia in a Japanese Population

BACKGROUND

Clozapine-induced agranulocytosis (CIA)/clozapine-induced granulocytopenia (CIG) (CIAG) is a life-threatening event for schizophrenic subjects treated with clozapine.

METHODS

To examine the genetic factor for CIAG, a genome-wide pharmacogenomic analysis was conducted using 50 subjects with CIAG and 2905 control subjects.

RESULTS

We identified a significant association in the human leukocyte antigen (HLA) region (rs1800625, p = 3.46 × 10(-9), odds ratio [OR] = 3.8); therefore, subsequent HLA typing was performed. We detected a significant association of HLA-B*59:01 with CIAG (p = 3.81 × 10(-8), OR = 10.7) and confirmed this association by comparing with an independent clozapine-tolerant control group (n = 380, p = 2.97 × 10(-5), OR = 6.3). As we observed that the OR of CIA (OR: 9.3~15.8) was approximately double that in CIG (OR: 4.4~7.4), we hypothesized that the CIG subjects were a mixed population of those who potentially would develop CIA and those who would not develop CIA (non-CIA). This hypothesis allowed the proportion of the CIG who were non-CIA to be calculated, enabling us to estimate the positive predictive value of the nonrisk allele on non-CIA in CIG subjects. Assuming this model, we estimated that 1) ~50% of CIG subjects would be non-CIA; and 2) ~60% of the CIG subjects without the risk allele would be non-CIA and therefore not expected to develop CIA.

CONCLUSIONS

Our results suggest that HLA-B*59:01 is a risk factor for CIAG in the Japanese population. Furthermore, if our model is true, the results suggest that rechallenging certain CIG subjects with clozapine may not be always contraindicated.

The genetics of breast cancer risk in the post-genome era: thoughts on study design to move past BRCA and towards clinical relevance

More than 12 % of women will be diagnosed with breast cancer in their lifetime. Although there have been tremendous advances in elucidating genetic risk factors underlying both familial and sporadic breast cancer, much of the genetic contribution to breast cancer etiology remains unknown. The discovery of BRCA1 and BRCA2 over 20 years ago remains the seminal event in the field and has paved the way for the discovery of other high-penetrance susceptibility genes by linkage analysis. The advent of genome-wide association studies made possible the next wave of discoveries, in which over 80 low-penetrance and moderate-penetrance variants were identified. Although these studies were highly successful at discovering variants associated with both familial and sporadic breast cancer, the variants identified to date explain only 50 % of the heritability of breast cancer. In this review, we look back at the investigative strategies that have led to our current understanding of breast cancer genetics, consider the challenges of performing association studies in heterogeneous complex diseases such as breast cancer, and look ahead toward the types of study designs that may lead to the identification of the genetic variation accounting for the remaining missing heritability.

Genomic Selection Using Extreme Phenotypes and Pre-Selection of SNPs in Large Yellow Croaker (Larimichthys crocea)

Genomic selection (GS) is an effective method to improve predictive accuracies of genetic values. However, high cost in genotyping will limit the application of this technology in some species. Therefore, it is necessary to find some methods to reduce the genotyping costs in genomic selection. Large yellow croaker is one of the most commercially important marine fish species in southeast China and Eastern Asia. In this study, genotyping-by-sequencing was used to construct the libraries for the NGS sequencing and find 29,748 SNPs in the genome. Two traits, eviscerated weight (EW) and the ratio between eviscerated weight and whole body weight (REW), were chosen to study. Two strategies to reduce the costs were proposed as follows: selecting extreme phenotypes (EP) for genotyping in reference population or pre-selecting SNPs to construct low-density marker panels in candidates. Three methods of pre-selection of SNPs, i.e., pre-selecting SNPs by absolute effects (SE), by single marker analysis (SMA), and by fixed intervals of sequence number (EL), were studied. The results showed that using EP was a feasible method to save the genotyping costs in reference population. Heritability did not seem to have obvious influences on the predictive abilities estimated by EP. Using SMA was the most feasible method to save the genotyping costs in candidates. In addition, the combination of EP and SMA in genomic selection also showed good results, especially for trait of REW. We also described how to apply the new methods in genomic selection and compared the genotyping costs before and after using the new methods. Our study may not only offer a reference for aquatic genomic breeding but also offer a reference for genomic prediction in other species including livestock and plants, etc.

Genome-wide association meta-analyses identified 1q43 and 2q32.2 for hip Ward's triangle areal bone mineral density

Aiming to identify genomic variants associated with osteoporosis, we performed a genome-wide association meta-analysis of bone mineral density (BMD) at Ward's triangle of the hip in 7175 subjects from 6 samples. We performed in silico replications with femoral neck, trochanter, and inter-trochanter BMDs in 6912 subjects from the Framingham heart study (FHS), and with forearm, femoral neck and lumbar spine BMDs in 32965 subjects from the GEFOS summary results. Combining the evidence from all samples, we identified 2 novel loci for areal BMD: 1q43 (rs1414660, discovery p=1.20×10(-8), FHS p=0.05 for trochanter BMD; rs9287237, discovery p=3.55×10(-7), FHS p=9.20×10(-3) for trochanter BMD, GEFOS p=0.02 for forearm BMD, nearest gene FMN2) and 2q32.2 (rs56346965, discovery p=7.48×10(-7), FHS p=0.10 for inter-trochanter BMD, GEFOS p=0.02 for spine BMD, nearest gene NAB1). The two lead SNPs rs1414660 and rs56346965 are eQTL sites for the genes GREM2 and NAB1 respectively. Functional annotation of GREM2 and NAB1 illustrated their involvement in BMP signaling pathway and in bone development. We also replicated three previously reported loci: 5q14.3 (rs10037512, discovery p=3.09×10(-6), FHS p=8.50×10(-3), GEFOS p=1.23×10(-24) for femoral neck BMD, nearest gene MEF2C), 6q25.1 (rs3020340, discovery p=1.64×10(-6), GEFOS p=1.69×10(-3) for SPN-BMD, nearest gene ESR1) and 7q21.3 (rs13310130, discovery p=8.79×10(-7), GEFOS p=2.61×10(-7) for spine BMD, nearest gene SHFM1). Our findings provide additional insights that further enhance our understanding of bone development, osteoporosis, and fracture pathogenesis.

CellMapper: rapid and accurate inference of gene expression in difficult-to-isolate cell types

We present a sensitive approach to predict genes expressed selectively in specific cell types, by searching publicly available expression data for genes with a similar expression profile to known cell-specific markers. Our method, CellMapper, strongly outperforms previous computational algorithms to predict cell type-specific expression, especially for rare and difficult-to-isolate cell types. Furthermore, CellMapper makes accurate predictions for human brain cell types that have never been isolated, and can be rapidly applied to diverse cell types from many tissues. We demonstrate a clinically relevant application to prioritize candidate genes in disease susceptibility loci identified by GWAS.

Genome-wide association study of working memory brain activation

In a population-based genome-wide association (GWA) study of n-back working memory task-related brain activation, we extracted the average percent BOLD signal change (2-back minus 0-back) from 46 regions-of-interest (ROIs) in functional MRI scans from 863 healthy twins and siblings. ROIs were obtained by creating spheres around group random effects analysis local maxima, and by thresholding a voxel-based heritability map of working memory brain activation at 50%. Quality control for test-retest reliability and heritability of ROI measures yielded 20 reliable (r>0.7) and heritable (h²>20%) ROIs. For GWA analysis, the cohort was divided into a discovery (n=679) and replication (n=97) sample. No variants survived the stringent multiple-testing-corrected genome-wide significance threshold (p<4.5×10^-9), or were replicated (p<0.0016), but several genes were identified that are worthy of further investigation. A search of 529,379 genomic markers resulted in discovery of 31 independent single nucleotide polymorphisms (SNPs) associated with BOLD signal change at a discovery level of p<1×10^-5. Two SNPs (rs7917410 and rs7672408) were associated at a significance level of p<1×10^-7. Only one, most strongly affecting BOLD signal change in the left supramarginal gyrus (R²=5.5%), had multiple SNPs associated at p<1×10^-5 in linkage disequilibrium with it, all located in and around the BANK1 gene. BANK1 encodes a B-cell-specific scaffold protein and has been shown to negatively regulate CD40-mediated AKT activation. AKT is part of the dopamine-signaling pathway, suggesting a mechanism for the involvement of BANK1 in the BOLD response to working memory. Variants identified here may be relevant to (the susceptibility to) common disorders affecting brain function.

Genetic Factors of the Disease Course after Sepsis: A Genome-Wide Study for 28Day Mortality

Sepsis is the dysregulated host response to an infection which leads to life-threatening organ dysfunction that varies by host genomic factors. We conducted a genome-wide association study (GWAS) in 740 adult septic patients and focused on 28 day mortality as outcome. Variants with suggestive evidence for an association (p ≤ 10^− 5) were validated in two additional GWA studies (n = 3470) and gene coding regions related to the variants were assessed in an independent exome sequencing study (n = 74).

In the discovery GWAS, we identified 243 autosomal variants which clustered in 14 loci (p ≤ 10^− 5). The best association signal (rs117983287; p = 8.16 × 10^− 8) was observed for a missense variant located at chromosome 9q21.2 in the VPS13A gene. VPS13A was further supported by additional GWAS (p = 0.03) and sequencing data (p = 0.04). Furthermore, CRISPLD2 (p = 5.99 × 10^− 6) and a region on chromosome 13q21.33 (p = 3.34 × 10^− 7) were supported by both our data and external biological evidence.

We found 14 loci with suggestive evidence for an association with 28 day mortality and found supportive, converging evidence for three of them in independent data sets. Elucidating the underlying biological mechanisms of VPS13A, CRISPLD2, and the chromosome 13 locus should be a focus of future research activities.

•

A low frequency missense variant in VPS13A on chromosome 9q21.2 was associated with 28 day mortality after sepsis

•

A frequent intronic variant in CRISPLD2 was also supported and was reported to be associated with procalcitonin levels

•

Similarly supported was an intergenic frequent variant on chromosome13q21.33 – a region related to chronic kidney disease

Sepsis is the dysregulated host response to an infection which leads to life-threatening organ dysfunction that is known to vary by host genomic factors. However, the detection of genetic variants related to sepsis outcomes has been challenging so far. We conducted a discovery genome-wide association study (GWAS) in 740 adult patients with sepsis looking for variants that vary with 28 day mortality. We followed-up our best findings by additional GWAS and exome sequencing data in 3544 adult patients and report three regions including the genes VPS13A and CRISPLD2 that were supported by our data and external biological evidence.

Genomics of Alzheimer's disease: Value of high-throughput genomic technologies to dissect its etiology

Late-onset Alzheimer's disease (AD), the most common neurodegenerative disorder in western countries, is clinically defined by progressive worsening in cognitive functions along with function and behavioral impairment. This ultimately results in complete incapacity and death. AD is a clinically and pathologically heterogeneous disease, and this is reflected by the numerous genetic findings that point to several diverse molecular mechanisms and pathways. Linkage, genome-wide association and next-generation sequencing studies have led to the identification of more than 20 novel susceptibility loci for AD. While these observations have significantly increased the knowledge of pathogenic mechanisms and potential therapeutic targets, a large part of the genetic component underlying AD is still unexplained. This review will summarize and discuss the major genetic findings and their potential impact on AD diagnosis and prediction of prognosis.

Analysis of multiple related phenotypes in genome-wide association studies

Most genome-wide association studies (GWAS) have been conducted by focusing on one phenotype of interest for identifying genetic variants associated with common complex phenotypes. However, despite many successful results from GWAS, only a small number of genetic variants tend to be identified and replicated given a very stringent genome-wide significance criterion, and explain only a small fraction of phenotype heritability. In order to improve power by using more information from data, we propose an alternative multivariate approach, which considers multiple related phenotypes simultaneously. We demonstrate through computer simulation that the multivariate approach can improve power for detecting disease-predisposing genetic variants and pleiotropic variants that have simultaneous effects on multiple related phenotypes. We apply the multivariate approach to a GWA dataset of 8,842 Korean individuals genotyped for 327,872 SNPs, and detect novel genetic variants associated with metabolic syndrome related phenotypes. Considering several related phenotype simultaneously, the multivariate approach provides not only more powerful results than the conventional univariate approach but also clue to identify pleiotropic genes that are important to the pathogenesis of many related complex phenotypes.

Genome-wide association study on the FEV1/FVC ratio in never-smokers identifies HHIP and FAM13A

BACKGROUND

Although a striking proportion (25% to 45%) of patients with chronic obstructive pulmonary disease are never-smokers, most genetic susceptibility studies have not focused on this group exclusively.

OBJECTIVE

The aim of this study was to identify common genetic variants associated with FEV₁ and its ratio to forced vital capacity (FVC) in never-smokers.

METHODS

Genome-wide association studies were performed in 5070 never-smokers of the identification cohort LifeLines, and results (P < 10^-5) were verified by using a meta-analysis of the Vlagtwedde-Vlaardingen study and the Rotterdam Study I-III (total n = 1966). Furthermore, we aimed to assess the effects of the replicated variants in more detail by performing genetic risk score, expression quantitative trait loci, and variant*ever-smoking interaction analyses.

RESULTS

We identified associations between the FEV₁/FVC ratio and 5 common genetic variants in the identification cohort, and 2 of these associations were replicated. The 2 variants annotated to the genes hedgehog interacting protein (HHIP) and family with sequence similarity 13 member A (FAM13A) were shown to have an additive effect on FEV₁/FVC levels in the genetic risk score analysis; were associated with gene expression of HHIP and FAM13A in lung tissue, respectively; and were genome-wide significant in a meta-analysis including both identification and 4 verification cohorts (P < 2.19 × 10^-7). Finally, we did not identify significant interactions between the variants and ever smoking. Results of the FEV₁ identification analysis were not replicated.

CONCLUSION

The genes HHIP and FAM13A confer a risk for airway obstruction in general that is not driven exclusively by cigarette smoking, which is the main risk factor for chronic obstructive pulmonary disease.