Joint eQTL assessment of whole blood and dura mater tissue from individuals with Chiari type I malformation

Background

Expression quantitative trait loci (eQTL) play an important role in the regulation of gene expression. Gene expression levels and eQTLs are expected to vary from tissue to tissue, and therefore multi-tissue analyses are necessary to fully understand complex genetic conditions in humans. Dura mater tissue likely interacts with cranial bone growth and thus may play a role in the etiology of Chiari Type I Malformation (CMI) and related conditions, but it is often inaccessible and its gene expression has not been well studied. A genetic basis to CMI has been established; however, the specific genetic risk factors are not well characterized.

Results

We present an assessment of eQTLs for whole blood and dura mater tissue from individuals with CMI. A joint-tissue analysis identified 239 eQTLs in either dura or blood, with 79% of these eQTLs shared by both tissues. Several identified eQTLs were novel and these implicate genes involved in bone development (IPO8, XYLT1, and PRKAR1A), and ribosomal pathways related to marrow and bone dysfunction, as potential candidates in the development of CMI.

Conclusions

Despite strong overall heterogeneity in expression levels between blood and dura, the majority of cis-eQTLs are shared by both tissues. The power to detect shared eQTLs was improved by using an integrative statistical approach. The identified tissue-specific and shared eQTLs provide new insight into the genetic basis for CMI and related conditions.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-014-1211-8) contains supplementary material, which is available to authorized users.     

Psychosocial Predictors of Metabolic Syndrome among Latino Groups in the Multi-Ethnic Study of Atherosclerosis (MESA)

Objective

We sought to determine the contribution of psychological variables to risk for metabolic syndrome (MetS) among Latinos enrolled in the Multi-Ethnic Study of Atherosclerosis (MESA), and to investigate whether social support moderates these associations, and whether inflammatory markers mediate the association between psychological variables and MetS.

Research design and methods

Cross-sectional analyses at study baseline were conducted with a national Latino cohort (n = 1,388) that included Mexican Americans, Dominican Americans, Puerto Rican Americans and Central/South Americans. Hierarchical logistic regression analyses were conducted to test the effects of psychosocial variables (chronic stress, depressive symptoms, and social support) on MetS. In addition, separate subgroup-specific models, controlling for nationality, age, gender, socioeconomic position, language spoken at home, exercise, smoking and drinking status, and testing for the effects of chronic stress, depressive symptoms and inflammation (IL-6, CRP, fibrinogen) in predicting risk for MetS were conducted.

Results

In the overall sample, high chronic stress independently predicted risk for MetS, however this association was found to be significant only in Mexican Americans and Puerto Rican Americans. Social support did not moderate the associations between chronic stress and MetS for any group. Chronic stress was not associated with inflammatory markers in either the overall sample or in each group.

Conclusions

Our results suggest a differential contribution of chronic stress to the prevalence of MetS by national groups.     

Synthesis of 53 tissue and cell line expression QTL datasets reveals master eQTLs

Background

Gene expression genetic studies in human tissues and cells identify cis- and trans-acting expression quantitative trait loci (eQTLs). These eQTLs provide insights into regulatory mechanisms underlying disease risk. However, few studies systematically characterized eQTL results across cell and tissues types. We synthesized eQTL results from >50 datasets, including new primary data from human brain, peripheral plaque and kidney samples, in order to discover features of human eQTLs.

Results

We find a substantial number of robust cis-eQTLs and far fewer trans-eQTLs consistent across tissues. Analysis of 45 full human GWAS scans indicates eQTLs are enriched overall, and above nSNPs, among positive statistical signals in genetic mapping studies, and account for a significant fraction of the strongest human trait effects. Expression QTLs are enriched for gene centricity, higher population allele frequencies, in housekeeping genes, and for coincidence with regulatory features, though there is little evidence of 5′ or 3′ positional bias. Several regulatory categories are not enriched including microRNAs and their predicted binding sites and long, intergenic non-coding RNAs. Among the most tissue-ubiquitous cis-eQTLs, there is enrichment for genes involved in xenobiotic metabolism and mitochondrial function, suggesting these eQTLs may have adaptive origins. Several strong eQTLs (CDK5RAP2, NBPFs) coincide with regions of reported human lineage selection. The intersection of new kidney and plaque eQTLs with related GWAS suggest possible gene prioritization. For example, butyrophilins are now linked to arterial pathogenesis via multiple genetic and expression studies. Expression QTL and GWAS results are made available as a community resource through the NHLBI GRASP database [http://apps.nhlbi.nih.gov/grasp/].

Conclusions

Expression QTLs inform the interpretation of human trait variability, and may account for a greater fraction of phenotypic variability than protein-coding variants. The synthesis of available tissue eQTL data highlights many strong cis-eQTLs that may have important biologic roles and could serve as positive controls in future studies. Our results indicate some strong tissue-ubiquitous eQTLs may have adaptive origins in humans. Efforts to expand the genetic, splicing and tissue coverage of known eQTLs will provide further insights into human gene regulation.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-532) contains supplementary material, which is available to authorized users.     

Allelic mapping bias in RNA-sequencing is not a major confounder in eQTL studies

Background

RNA sequencing (RNA-seq) is the current gold-standard method to quantify gene expression for expression quantitative trait locus (eQTL) studies. However, a potential caveat in these studies is that RNA-seq reads carrying the non-reference allele of variant loci can have lower probability to map correctly to the reference genome, which could bias gene quantifications and cause false positive eQTL associations. In this study, we analyze the effect of this allelic mapping bias in eQTL discovery.

Results

We simulate RNA-seq read mapping over 9.5 M common SNPs and indels, with 15.6% of variants showing biased mapping rate for reference versus non-reference reads. However, removing potentially biased RNA-seq reads from an eQTL dataset of 185 individuals has a very small effect on gene and exon quantifications and eQTL discovery. We detect only a handful of likely false positive eQTLs, and overall eQTL SNPs show no significant enrichment for high mapping bias.

Conclusion

Our results suggest that RNA-seq quantifications are generally robust against allelic mapping bias, and that this does not have a severe effect on eQTL discovery. Nevertheless, we provide our catalog of putatively biased loci to allow better controlling for mapping bias to obtain more accurate results in future RNA-seq studies.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-014-0467-2) contains supplementary material, which is available to authorized users.     

Meta-eQTL: a tool set for flexible eQTL meta-analysis

Background

Increasing number of eQTL (Expression Quantitative Trait Loci) datasets facilitate genetics and systems biology research. Meta-analysis tools are in need to jointly analyze datasets of same or similar issue types to improve statistical power especially in trans-eQTL mapping. Meta-analysis framework is also necessary for ChrX eQTL discovery.

Results

We developed a novel tool, meta-eqtl, for fast eQTL meta-analysis of arbitrary sample size and arbitrary number of datasets. Further, this tool accommodates versatile modeling, eg. non-parametric model and mixed effect models. In addition, meta-eqtl readily handles calculation of chrX eQTLs.

Conclusions

We demonstrated and validated meta-eqtl as fast and comprehensive tool to meta-analyze multiple datasets and ChrX eQTL discovery. Meta-eqtl is a set of command line utilities written in R, with some computationally intensive parts written in C. The software runs on Linux platforms and is designed to intelligently adapt to high performance computing (HPC) cluster. We applied the novel tool to liver and adipose tissue data, and revealed eSNPs underlying diabetes GWAS loci.     

Investigating the Molecular Basis of Retinal Degeneration in a Familial Cohort of Pakistani Decent by Exome Sequencing

Purpose

To define the molecular basis of retinal degeneration in consanguineous Pakistani pedigrees with early onset retinal degeneration.

Methods

A cohort of 277 individuals representing 26 pedigrees from the Punjab province of Pakistan was analyzed. Exomes were captured with commercial kits and sequenced on an Illumina HiSeq 2500. Candidate variants were identified using standard tools and analyzed using exomeSuite to detect all potentially pathogenic changes in genes implicated in retinal degeneration. Segregation analysis was performed by dideoxy sequencing and novel variants were additionally investigated for their presence in ethnicity-matched controls.

Results

We identified a total of nine causal mutations, including six novel variants in RPE65, LCA5, USH2A, CNGB1, FAM161A, CERKL and GUCY2D as the underlying cause of inherited retinal degenerations in 13 of 26 pedigrees. In addition to the causal variants, a total of 200 variants each observed in five or more unrelated pedigrees investigated in this study that were absent from the dbSNP, HapMap, 1000 Genomes, NHLBI ESP6500, and ExAC databases were identified, suggesting that they are common in, and unique to the Pakistani population.

Conclusions

We identified causal mutations associated with retinal degeneration in nearly half of the pedigrees investigated in this study through next generation whole exome sequencing. All novel variants detected in this study through exome sequencing have been cataloged providing a reference database of variants common in, and unique to the Pakistani population.     

Single Gene Prognostic Biomarkers in Ovarian Cancer: A Meta-Analysis

Purpose

To discover novel prognostic biomarkers in ovarian serous carcinomas.

Methods

A meta-analysis of all single genes probes in the TCGA and HAS ovarian cohorts was performed to identify possible biomarkers using Cox regression as a continuous variable for overall survival. Genes were ranked by p-value using Stouffer’s method and selected for statistical significance with a false discovery rate (FDR) <.05 using the Benjamini-Hochberg method.

Results

Twelve genes with high mRNA expression were prognostic of poor outcome with an FDR <.05 (AXL, APC, RAB11FIP5, C19orf2, CYBRD1, PINK1, LRRN3, AQP1, DES, XRCC4, BCHE, and ASAP3). Twenty genes with low mRNA expression were prognostic of poor outcome with an FDR <.05 (LRIG1, SLC33A1, NUCB2, POLD3, ESR2, GOLPH3, XBP1, PAXIP1, CYB561, POLA2, CDH1, GMNN, SLC37A4, FAM174B, AGR2, SDR39U1, MAGT1, GJB1, SDF2L1, and C9orf82).

Conclusion

A meta-analysis of all single genes identified thirty-two candidate biomarkers for their possible role in ovarian serous carcinoma. These genes can provide insight into the drivers or regulators of ovarian cancer and should be evaluated in future studies. Genes with high expression indicating poor outcome are possible therapeutic targets with known antagonists or inhibitors. Additionally, the genes could be combined into a prognostic multi-gene signature and tested in future ovarian cohorts.     

Identification of Genes Whose Expression Profile Is Associated with Non-Progression towards AIDS Using eQTLs

Background

Many genome-wide association studies have been performed on progression towards the acquired immune deficiency syndrome (AIDS) and they mainly identified associations within the HLA loci. In this study, we demonstrate that the integration of biological information, namely gene expression data, can enhance the sensitivity of genetic studies to unravel new genetic associations relevant to AIDS.

Methods

We collated the biological information compiled from three databases of expression quantitative trait loci (eQTLs) involved in cells of the immune system. We derived a list of single nucleotide polymorphisms (SNPs) that are functional in that they correlate with differential expression of genes in at least two of the databases. We tested the association of those SNPs with AIDS progression in two cohorts, GRIV and ACS. Tests on permuted phenotypes of the GRIV and ACS cohorts or on randomised sets of equivalent SNPs allowed us to assess the statistical robustness of this method and to estimate the true positive rate.

Results

Eight genes were identified with high confidence (p = 0.001, rate of true positives 75%). Some of those genes had previously been linked with HIV infection. Notably, ENTPD4 belongs to the same family as CD39, whose expression has already been associated with AIDS progression; while DNAJB12 is part of the HSP90 pathway, which is involved in the control of HIV latency. Our study also drew our attention to lesser-known functions such as mitochondrial ribosomal proteins and a zinc finger protein, ZFP57, which could be central to the effectiveness of HIV infection. Interestingly, for six out of those eight genes, down-regulation is associated with non-progression, which makes them appealing targets to develop drugs against HIV.     

Altered Expression of Fibrosis Genes in Capsules of Failed Ahmed Glaucoma Valve Implants

Purpose

Ahmed glaucoma valve (AGV) implant is an aqueous shunt device used to control intraocular pressure in glaucoma. Implant failure results from impervious encapsulation of the shunt plate causing increased hydraulic resistance and raised intraocular pressure. We hypothesized that deregulation of fibrosis pathway contributes to capsular resistance. We tested this by studying fibrosis related gene expression in failed AGV implants.

Methods

Differential gene expression was examined in failed AGV capsules and compared to normal control tenon. Following total RNA extraction, 84 key genes in fibrosis pathway were examined by real-time PCR using RT² Profiler PCR Array. Relative gene expression was calculated using ΔΔC_t method. Gene specific TaqMan assays were used to validate select genes with ≥2 fold differential expression in the array expression profile.

Results

We observed differential expression in several genes in the fibrosis pathway. Almost half (39/84) of examined genes showed ≥2 fold differential expression in majority of capsules examined on the array. TaqMan assays for select genes including CCN2 (CTGF), THBS1, SERPINE1, THBS2, COL3A1, MMP3, and IL1A in an increased validation sample set showed significant changes in expression (p value from <0.001 to 0.022) at a high frequency in concurrence with our array results.

Conclusions

Pathway-focused analyses identified candidate genes with altered expression providing molecular evidence for deregulation of the fibrosis pathway in AGV failure.     

Facility Death Review of Maternal and Neonatal Deaths in Bangladesh

Objectives

To explore the experiences, acceptance, and effects of conducting facility death review (FDR) of maternal and neonatal deaths and stillbirths at or below the district level in Bangladesh.

Methods

This was a qualitative study with healthcare providers involved in FDRs. Two districts were studied: Thakurgaon district (a pilot district) and Jamalpur district (randomly selected from three follow-on study districts). Data were collected between January and November 2011. Data were collected from focus group discussions, in-depth interviews, and document review. Hospital administrators, obstetrics and gynecology consultants, and pediatric consultants and nurses employed in the same departments of the respective facilities participated in the study. Content and thematic analyses were performed.

Results

FDR for maternal and neonatal deaths and stillbirths can be performed in upazila health complexes at sub-district and district hospital levels. Senior staff nurses took responsibility for notifying each death and conducting death reviews with the support of doctors. Doctors reviewed the FDRs to assign causes of death. Review meetings with doctors, nurses, and health managers at the upazila and district levels supported the preparation of remedial action plans based on FDR findings, and interventions were planned accordingly. There were excellent examples of improved quality of care at facilities as a result of FDR. FDR also identified gaps and challenges to overcome in the near future to improve maternal and newborn health.

Discussion

FDR of maternal and neonatal deaths is feasible in district and upazila health facilities. FDR not only identifies the medical causes of a maternal or neonatal death but also explores remediable gaps and challenges in the facility. FDR creates an enabled environment in the facility to explore medical causes of deaths, including the gaps and challenges that influence mortality. FDRs mobilize health managers at upazila and district levels to forward plan and improve healthcare delivery.     

Sex influences eQTL effects of SLE and Sjögren’s syndrome-associated genetic polymorphisms

Background

Systemic lupus erythematosus (SLE) and primary Sjögren’s syndrome (pSS) are autoimmune disorders characterized by autoantibodies, dysregulated B cells, and notably high female-to-male incidence ratios. Genome-wide association studies have identified several susceptibility SNPs for both diseases. Many SNPs in the genome are expression quantitative trait loci (eQTLs), with context-dependent effects. Assuming that sex is a biological context, we investigated whether SLE/pSS SNPs act as eQTLs in B cells and used a disease-targeted approach to understand if they display sex-specific effects.

Methods

We used genome-wide genotype and gene expression data from primary B cells from 125 males and 162 females. The MatrixEQTL R package was used to identify eQTLs within a genomic window of 2 Mb centered on each of 22 established SLE and/or pSS susceptibility SNPs. To find sex-specific eQTLs, we used a linear model with a SNP * sex interaction term.

Results

We found ten SNPs affecting the expression of 16 different genes (FDR <?0.05). rs7574865-INPP1, rs7574865-MYO1B, rs4938573-CD3D, rs11755393-SNRPC, and rs4963128-PHRF1 were novel observations for the immune compartment and B cells. By analyzing the SNP * sex interaction terms, we identified six genes with differentially regulated expression in females compared to males, depending on the genotype of SLE/pSS-associated SNPs: SLC39A8 (BANK1 locus), CD74 (TNIP1 locus), PXK, CTSB (BLK/FAM167A locus), ARCN1 (CXCR5 locus), and DHX9 (NCF2 locus).

Conclusions

We identified several unknown sex-specific eQTL effects of SLE/pSS-associated genetic polymorphisms and provide novel insight into how gene-sex interactions may contribute to the sex bias in systemic autoimmune diseases.