Allelic heterogeneity and more detailed analyses of known loci explain additional phenotypic variation and reveal complex patterns of association

The identification of multiple signals at individual loci could explain additional phenotypic variance ('missing heritability') of common traits, and help identify causal genes. We examined gene expression levels as a model trait because of the large number of strong genetic effects acting in cis. Using expression profiles from 613 individuals, we performed genome-wide single nucleotide polymorphism (SNP) analyses to identify cis-expression quantitative trait loci (eQTLs), and conditional analysis to identify second signals. We examined patterns of association when accounting for multiple SNPs at a locus and when including additional SNPs from the 1000 Genomes Project. We identified 1298 cis-eQTLs at an approximate false discovery rate 0.01, of which 118 (9%) showed evidence of a second independent signal. For this subset of 118 traits, accounting for two signals resulted in an average 31% increase in phenotypic variance explained (Wilcoxon P< 0.0001). The association of SNPs with cis gene expression could increase, stay similar or decrease in significance when accounting for linkage disequilibrium with second signals at the same locus. Pairs of SNPs increasing in significance tended to have gene expression increasing alleles on opposite haplotypes, whereas pairs of SNPs decreasing in significance tended to have gene expression increasing alleles on the same haplotypes. Adding data from the 1000 Genomes Project showed that apparently independent signals could be potentially explained by a single association signal. Our results show that accounting for multiple variants at a locus will increase the variance explained in a substantial fraction of loci, but that allelic heterogeneity will be difficult to define without resequencing loci and functional work.     

Discovery and Functional Assessment of Gene Variants in the Vascular Endothelial Growth Factor Pathway

Angiogenesis is a host‐mediated mechanism in disease pathophysiology. The vascular endothelial growth factor (VEGF) pathway is a major determinant of angiogenesis, and a comprehensive annotation of the functional variation in this pathway is essential to understand the genetic basis of angiogenesis‐related diseases. We assessed the allelic heterogeneity of gene expression, population specificity of cis expression quantitative trait loci (eQTLs), and eQTL function in luciferase assays in CEU and Yoruba people of Ibadan, Nigeria (YRI) HapMap lymphoblastoid cell lines in 23 resequenced genes. Among 356 cis‐eQTLs, 155 and 174 were unique to CEU and YRI, respectively, and 27 were shared between CEU and YRI. Two cis‐eQTLs provided mechanistic evidence for two genome‐wide association study findings. Five eQTLs were tested for function in luciferase assays and the effect of two KRAS variants was concordant with the eQTL effect. Two eQTLs found in each of PRKCE, PIK3C2A, and MAP2K6 could predict 44%, 37%, and 45% of the variance in gene expression, respectively. This is the first analysis focusing on the pattern of functional genetic variation of the VEGF pathway genes in CEU and YRI populations and providing mechanistic evidence for genetic association studies of diseases for which angiogenesis plays a pathophysiologic role.     

Targeted sequencing of the LRRTM gene family in suicide attempters with bipolar disorder

Glutamatergic signaling is the primary excitatory neurotransmission pathway in the brain, and its relationship to neuropsychiatric disorders is of considerable interest. Our previous attempted suicide genome‐wide association study, and numerous studies investigating gene expression, genetic variation, and DNA methylation have implicated aberrant glutamatergic signaling in suicide risk. The glutamatergic pathway gene LRRTM4 was an associated gene identified in our attempted suicide genome‐wide association study, with association support seen primarily in females. Recent evidence has also shown that glutamatergic signaling is partly regulated by sex‐related hormones. The LRRTM gene family encodes neuronal leucine‐rich transmembrane proteins that localize to and promote glutamatergic synapse development. In this study, we sequenced the coding and regulatory regions of all four LRRTM gene members plus a large intronic region of LRRTM4 in 476 bipolar disorder suicide attempters and 473 bipolar disorder nonattempters. We identified two male‐specific variants, one female‐ and five male‐specific haplotypes significantly associated with attempted suicide in LRRTM4. Furthermore, variants within significant haplotypes may be brain expression quantitative trait loci for LRRTM4 and some of these variants overlap with predicted hormone response elements. Overall, these results provide supporting evidence for a sex‐specific association of genetic variation in LRRTM4 with attempted suicide.     

Aberrant DNA methylation as a diagnostic biomarker of diabetic embryopathy

PurposeMaternal diabetes is a known teratogen that can cause a wide spectrum of birth defects, collectively referred to as diabetic embryopathy (DE). However, the pathogenic mechanisms underlying DE remain uncertain and there are no definitive tests to establish the diagnosis. Here, we explore the potential of DNA methylation as a diagnostic biomarker for DE and to inform disease pathogenesis.MethodsBisulfite sequencing was used to identify gene regions with differential methylation between DE neonates and healthy infants born with or without prenatal exposure to maternal diabetes, and to investigate the role of allele-specific methylation at implicated sites.ResultsWe identified a methylation signature consisting of 237 differentially methylated loci that distinguished infants with DE from control infants. These loci were found proximal to genes associated with Mendelian syndromes that overlap the DE phenotype (e.g., CACNA1C, TRIO, ANKRD11) or genes known to influence embryonic development (e.g., BRAX1, RASA3). Further, we identified allele-specific methylation (ASM) at 11 of these loci, within which 61.5% of ASM single-nucleotide variants are known expression quantitative trait loci (eQTLs).ConclusionsOur study suggests a role for aberrant DNA methylation and cis-sequence variation in the pathogenesis of DE and highlights the diagnostic potential of DNA methylation for teratogenic birth defects.     

Celiac disease: moving from genetic associations to causal variants

Genome-wide association studies are providing insight into the genetic basis of common complex diseases: more than 1150 genetic loci [2165 unique single nucleotide polymorphisms (SNPs)] have recently been associated to 159 complex diseases. The hunt for genes contributing to immune-related diseases has been particularly successful in celiac disease, for example, with 27 genome-wide significantly associated loci identified so far. One of the current challenges is how to move from a genetic association with a disease to finding disease-associated genes and causal variants, as a step towards understanding the underlying disease process. About 50% of disease-associated SNPs affect the expression of nearby genes (so-called expression quantitative traits loci or eQTLs) and these can provide clues for finding causal variants. Although eQTLs can be useful, fine mapping and sequencing are required to refine the association signal. Ultimately, sophisticated study designs will be needed to find the causal variants involved in complex diseases. In this review, we use celiac disease as an example to describe the different aspects that need to be considered on the path from genetic association to disease-causing variants.     

Analysis of neurogranin (NRGN) in schizophrenia

A recent study reported a genome‐wide significant association between schizophrenia and rs12807809—a SNP located approximately 3 kbp upstream of the neurogranin gene (NRGN). We sought to determine if (a) NRGN contains common exonic variants or variants affecting expression (eQTLs) that could account for the association with rs12807809 and (b) there exist rare non‐synonymous highly penetrant variants that could potentially confer high risk of schizophrenia. We sequenced all four exons of NRGN in a screening set of 14 individuals but found no novel common polymorphisms. We additionally sequenced the coding exons in up to 1,113 individuals (699 cases) but this revealed only a singleton‐coding variant in exon 2 (G246T leading to Gly‐55 → Val amino acid change) in which prediction of function analysis suggested is likely to be benign. Finally, analysis of a brain expression dataset of at least 130 individuals did not identify any eQTLs that were correlated with associated SNP rs12807809 following correction for multiple testing. © 2011 Wiley‐Liss, Inc.     

Identification of cis-regulatory variation influencing protein abundance levels in human plasma

Proteins are central to almost all cellular processes, and dysregulation of expression and function is associated with a range of disorders. A number of studies in human have recently shown that genetic factors significantly contribute gene expression variation. In contrast, very little is known about the genetic basis of variation in protein abundance in man. Here, we assayed the abundance levels of proteins in plasma from 96 elderly Europeans using a new aptamer-based proteomic technology and performed genome-wide local (cis-) regulatory association analysis to identify protein quantitative trait loci (pQTL). We detected robust cis-associations for 60 proteins at a false discovery rate of 5%. The most highly significant single nucleotide polymorphism detected was rs7021589 (false discovery rate, 2.5 × 10(-12)), mapped within the gene coding sequence of Tenascin C (TNC). Importantly, we identified evidence of cis-regulatory variation for 20 previously disease-associated genes encoding protein, including variants with strong evidence of disease association show significant association with protein abundance levels. These results demonstrate that common genetic variants contribute to the differences in protein abundance levels in human plasma. Identification of pQTLs will significantly enhance our ability to discover and comprehend the biological and functional consequences of loci identified from genome-wide association study of complex traits. This is the first large-scale genetic association study of proteins in plasma measured using a novel, highly multiplexed slow off-rate modified aptamer (SOMAmer) proteomic platform.     

Tachykinin receptor 1 variants associated with aggression in suicidal behavior.

Substance P is involved in the modulation of depression, anxiety, and suicidal-related behaviors. We studied gene variants of Tachykinin Receptor 1 (TACR1-rs3771810, rs3771825, rs726506, rs1477157) in 167 German suicide attempters (affective spectrum n = 107, schizophrenia spectrum n = 35, borderline personality disorder n = 25), 92 Caucasian individuals who committed suicide and 312 German healthy subjects. Single markers and haplotype analysis in relation to suicidal behaviors (suicide attempters/completers) did not reveal any significant association. The rarest rs3771825 T allele however showed a marginal association with higher Reactive Aggression scores on the Questionnaire for Measuring Factors of Aggression (FAF) (F = 9.86, df = 1; P = 0.0017). Haplotype analyses confirmed the finding. Violence or impulsivity of suicide attempt and State-Trait Anger Expression Inventory (STAXI) scores were not associated with gene variants. In conclusion, our study suggests that TACR1 gene variants have no major influence on suicidal behavior but may modulate aggression features.     

High-resolution genetic mapping of the ACE-linked QTL influencing circulating ACE activity

Fine-mapping of trait loci through combined linkage and association analysis is an important component of strategies designed to identify causative gene variants, particularly in situations where the trait may be influenced by one or more of many polymorphisms within the same gene. Angiotensin-1 converting enzyme (ACE) provides one of the best models for developing and testing such methodologies, as a major fraction of the heritable variation in the activity of the angiotensin-1 converting enzyme (ACE) is tightly linked to the ACE gene. Moreover, ACE contains many frequent polymorphisms that are in strong linkage disequilibrium with each other. Although none of these variants induces a significant amino-acid change, one or more, either singly or in combination, are likely to have a strong effect on the quantitative phenotype. Here, we show that measured-haplotype analysis of SNP data from a large European family cohort can be used to localise the major ACE-linked genetic factors influencing the trait to a 16 kb interval within the gene, thus limiting the number of ACE variants that need to be considered in future studies designed to elucidate their biological effects. The approaches developed will be applicable to the fine-mapping of other quantitative trait loci in humans.     

Gene expression variation and expression quantitative trait mapping of human chromosome 21 genes

Inter-individual differences in gene expression are likely to account for an important fraction of phenotypic differences, including susceptibility to common disorders. Recent studies have shown extensive variation in gene expression levels in humans and other organisms, and that a fraction of this variation is under genetic control. We investigated the patterns of gene expression variation in a 25 Mb region of human chromosome 21, which has been associated with many Down syndrome (DS) phenotypes. Taqman real-time PCR was used to measure expression variation of 41 genes in lymphoblastoid cells of 40 unrelated individuals. For 25 genes found to be differentially expressed, additional analysis was performed in 10 CEPH families to determine heritabilities and map loci harboring regulatory variation. Seventy-six percent of the differentially expressed genes had significant heritabilities, and genomewide linkage analysis led to the identification of significant eQTLs for nine genes. Most eQTLs were in trans, with the best result (P=7.46 x 10(-8)) obtained for TMEM1 on chromosome 12q24.33. A cis-eQTL identified for CCT8 was validated by performing an association study in 60 individuals from the HapMap project. SNP rs965951 located within CCT8 was found to be significantly associated with its expression levels (P=2.5 x 10(-5)) confirming cis-regulatory variation. The results of our study provide a representative view of expression variation of chromosome 21 genes, identify loci involved in their regulation and suggest that genes, for which expression differences are significantly larger than 1.5-fold in control samples, are unlikely to be involved in DS-phenotypes present in all affected individuals.     

Impact of common regulatory single-nucleotide variants on gene expression profiles in whole blood

Genome-wide association studies (GWASs) have uncovered susceptibility loci for a large number of complex traits. Functional interpretation of candidate genes identified by GWAS and confident assignment of the causal variant still remains a major challenge. Expression quantitative trait (eQTL) mapping has facilitated identification of risk loci for quantitative traits and might allow prioritization of GWAS candidate genes. One major challenge of eQTL studies is the need for larger sample numbers and replication. The aim of this study was to evaluate the robustness and reproducibility of whole-blood eQTLs in humans and test their value in the identification of putative functional variants involved in the etiology of complex traits. In the current study, we performed comphrehensive eQTL mapping from whole blood. The discovery sample included 322 Caucasians from a general population sample (KORA F3). We identified 363 cis and 8 trans eQTLs after stringent Bonferroni correction for multiple testing. Of these, 98.6% and 50% of cis and trans eQTLs, respectively, could be replicated in two independent populations (KORA F4 (n=740) and SHIP-TREND (n=653)). Furthermore, we identified evidence of regulatory variation for SNPs previously reported to be associated with disease loci (n=59) or quantitative trait loci (n=20), indicating a possible functional mechanism for these eSNPs. Our data demonstrate that eQTLs in whole blood are highly robust and reproducible across studies and highlight the relevance of whole-blood eQTL mapping in prioritization of GWAS candidate genes in humans.     

A novel method,the Variant Impact On Linkage Effect Test (VIOLET), leads to improved identification of causal variants in linkage regions

The Human Genome Project was expected to individualize medicine by rapidly advancing knowledge of common complex disease through discovery of disease-causing genetic variants. However, this has proved challenging. Although linkage analysis has identified replicated chromosomal regions, subsequent detection of causal variants for complex traits has been limited. One explanation for this difficulty is that utilization of association to follow up linkage is problematic given that linkage and association are not required to co-occur. Indeed, co-occurrence is likely to occur only in special circumstances, such as Mendelian inheritance, but cannot be universally expected. To overcome this problem, we propose a novel method, the Variant Impact On Linkage Effect Test (VIOLET), which differs from other quantitative methods in that it is designed to follow up linkage by identifying variants that influence the variance explained by a quantitative trait locus. VIOLET''s performance was compared with measured genotype and combined linkage association in two data sets with quantitative traits. Using simulated data, VIOLET had high power to detect the causal variant and reduced false positives compared with standard methods. Using real data, VIOLET identified a single variant, which explained 24% of linkage; this variant exhibited only nominal association (P=0.04) using measured genotype and was not identified by combined linkage association. These results demonstrate that VIOLET is highly specific while retaining low false-negative results. In summary, VIOLET overcomes a barrier to gene discovery and thus may be broadly applicable to identify underlying genetic etiology for traits exhibiting linkage.