Genetic analysis of blood molecular phenotypes reveals common properties in the regulatory networks affecting complex traits.

We evaluate the shared genetic regulation of mRNA molecules, proteins and metabolites derived from whole blood from 3029 human donors. We find abundant allelic heterogeneity, where multiple variants regulate a particular molecular phenotype, and pleiotropy, where a single variant associates with multiple molecular phenotypes over multiple genomic regions. The highest proportion of share genetic regulation is detected between gene expression and proteins (66.6%), with a further median shared genetic associations across 49 different tissues of 78.3% and 62.4% between plasma proteins and gene expression. We represent the genetic and molecular associations in networks including 2828 known GWAS variants, showing that GWAS variants are more often connected to gene expression in trans than other molecular phenotypes in the network. Our work provides a roadmap to understanding molecular networks and deriving the underlying mechanism of action of GWAS variants using different molecular phenotypes in an accessible tissue.

Multiallelic Copy Number Variation in ORM1 is Associated with Plasma Cell-Free DNA Levels as an Intermediate Phenotype for Venous Thromboembolism.

Venous thromboembolism (VTE) is a common disease with high heritability. However, only a small portion of the genetic variance of VTE can be explained by known genetic risk factors. Neutrophil extracellular traps (NETs) have been associated with prothrombotic activity. Therefore, the genetic basis of NETs could reveal novel risk factors for VTE. A recent genome-wide association study of plasma cell-free DNA (cfDNA) levels in the Genetic Analysis of Idiopathic Thrombophilia 2 (GAIT-2) Project showed a significant associated locus near ORM1. We aimed to further explore this candidate region by next-generation sequencing, copy number variation (CNV) quantification, and expression analysis using an extreme phenotype sampling design involving 80 individuals from the GAIT-2 Project. The RETROVE study with 400 VTE cases and 400 controls was used to replicate the results. A total of 105 genetic variants and a multiallelic CNV (mCNV) spanning ORM1 were identified in GAIT-2. Of these, 17 independent common variants, a region of 22 rare variants, and the mCNV were significantly associated with cfDNA levels. In addition, eight of these common variants and the mCNV influenced ORM1 expression. The association of the mCNV and cfDNA levels was replicated in RETROVE (p-value = 1.19 × 10-6). Additional associations between the mCNV and thrombin generation parameters were identified. Our results reveal that increased mCNV dosages in ORM1 decreased gene expression and upregulated cfDNA levels. Therefore, the mCNV in ORM1 appears to be a novel marker for cfDNA levels, which could contribute to VTE risk.

Integrated GWAS and Gene Expression Suggest ORM1 as a Potential Regulator of Plasma Levels of Cell-Free DNA and Thrombosis Risk.

Plasma cell-free DNA (cfDNA) is a surrogate marker of neutrophil extracellular traps (NETs) that contribute to immunothrombosis. There is growing interest about the mechanisms underlying NET formation and elevated cfDNA, but little is known about the factors involved. We aimed to identify genes involved in the regulation of cfDNA levels using data from the Genetic Analysis of Idiopathic Thrombophilia (GAIT-2) Project.Imputed genotypes, whole blood RNA-Seq data, and plasma cfDNA quantification were available for 935 of the GAIT-2 participants from 35 families with idiopathic thrombophilia. We performed heritability and GWAS analysis for cfDNA. The heritability of cfDNA was 0.26 (p = 3.7 × 10-6), while the GWAS identified a significant association (rs1687391, p = 3.55 × 10-10) near the ORM1 gene, on chromosome 9. An eQTL (expression quantitative trait loci) analysis revealed a significant association between the lead GWAS variant and the expression of ORM1 in whole blood (p = 6.14 × 10-9). Additionally, ORM1 expression correlated with levels of cfDNA (p = 4.38 × 10-4). Finally, genetic correlation analysis between cfDNA and thrombosis identified a suggestive association (ρ g = 0.43, p = 0.089).All in all, we show evidence of the role of ORM1 in regulating cfDNA levels in plasma, which might contribute to the susceptibility to thrombosis through mechanisms of immunothrombosis.

Genetic variant effects on gene expression in human pancreatic islets and their implications for T2D.

Most signals detected by genome-wide association studies map to non-coding sequence and their tissue-specific effects influence transcriptional regulation. However, key tissues and cell-types required for functional inference are absent from large-scale resources. Here we explore the relationship between genetic variants influencing predisposition to type 2 diabetes (T2D) and related glycemic traits, and human pancreatic islet transcription using data from 420 donors. We find: (a) 7741 cis-eQTLs in islets with a replication rate across 44 GTEx tissues between 40% and 73%; (b) marked overlap between islet cis-eQTL signals and active regulatory sequences in islets, with reduced eQTL effect size observed in the stretch enhancers most strongly implicated in GWAS signal location; (c) enrichment of islet cis-eQTL signals with T2D risk variants identified in genome-wide association studies; and (d) colocalization between 47 islet cis-eQTLs and variants influencing T2D or glycemic traits, including DGKB and TCF7L2. Our findings illustrate the advantages of performing functional and regulatory studies in disease relevant tissues.

Sequence-Defined Macrocycles for Understanding and Controlling the Build-up of Hierarchical Order in Self-Assembled 2D Arrays.

Anfinsen's dogma that sequence dictates structure is fundamental to understanding the activity and assembly of proteins. This idea has been applied to all manner of oligomers but not to the behavior of cyclic oligomers, aka macrocycles. We do this here by providing the first proofs that sequence controls the hierarchical assembly of nonbiological macrocycles, in this case, at graphite surfaces. To design macrocycles with one (AAA), two (AAB), or three (ABC) different carbazole units, we needed to subvert the synthetic preferences for one-pot macrocyclizations. We developed a new stepwise synthesis with sequence-defined targets made in 11, 17, and 22 steps with 25, 10, and 5% yields, respectively. The linear build up of primary sequence (1°) also enabled a thermal Huisgen cycloaddition to proceed regioselectively for the first time using geometric control. The resulting macrocycles are planar (2° structure) and form H-bonded dimers (3°) at surfaces. Primary sequences encoded into the suite of tricarb macrocycles were shown by scanning-tunneling microscopy (STM) to impact the next levels of supramolecular ordering (4°) and 2D crystalline polymorphs (5°) at solution-graphite interfaces. STM imaging of an AAB macrocycle revealed the formation of a new gap phase that was inaccessible using only C3-symmetric macrocycles. STM imaging of two additional sequence-controlled macrocycles (AAD, ABE) allowed us to identify the factors driving the formation of this new polymorph. This demonstration of how sequence controls the hierarchical patterning of macrocycles raises the importance of stepwise syntheses relative to one-pot macrocyclizations to offer new approaches for greater understanding and control of hierarchical assembly.

Cross-tissue eQTL enrichment of associations in schizophrenia.

The genome-wide association study of the Psychiatric Genomics Consortium identified over one hundred schizophrenia susceptibility loci. The number of non-coding variants discovered suggests that gene regulation could mediate the effect of these variants on disease. Expression quantitative trait loci (eQTLs) contribute to variation in levels of mRNA. Given the co-occurrence of schizophrenia and several traits not involving the central nervous system (CNS), we investigated the enrichment of schizophrenia associations among eQTLs for four non-CNS tissues: adipose tissue, epidermal tissue, lymphoblastoid cells and blood. Significant enrichment was seen in eQTLs of all tissues: adipose (ß = 0.18, p = 8.8 × 10-06), epidermal (ß = 0.12, p = 3.1 × 10-04), lymphoblastoid (ß = 0.19, p = 6.2 × 10-08) and blood (ß = 0.19, p = 6.4 × 10-06). For comparison, we looked for enrichment of association with traits of known relevance to one or more of these tissues (body mass index, height, rheumatoid arthritis, systolic blood pressure and type-II diabetes) and found that schizophrenia enrichment was of similar scale to that observed when studying diseases in the context of a more likely causal tissue. To further investigate tissue specificity, we looked for differential enrichment of eQTLs with relevant Roadmap affiliation (enhancers and promoters) and varying distance from the transcription start site. Neither factor significantly contributed to the enrichment, suggesting that this is equally distributed in tissue-specific and cross-tissue regulatory elements. Our analyses suggest that functional correlates of schizophrenia risk are prevalent in non-CNS tissues. This could be because of pleiotropy or the effectiveness of variants affecting expression in different contexts. This suggests the utility of large, single-tissue eQTL experiments to increase eQTL discovery power in the study of schizophrenia, in addition to smaller, multiple-tissue approaches. Our results conform to the notion that schizophrenia is a systemic disorder involving many tissues.

Age-dependent changes in mean and variance of gene expression across tissues in a twin cohort.

Changes in the mean and variance of gene expression with age have consequences for healthy aging and disease development. Age-dependent changes in phenotypic variance have been associated with a decline in regulatory functions leading to increase in disease risk. Here, we investigate age-related mean and variance changes in gene expression measured by RNA-seq of fat, skin, whole blood and derived lymphoblastoid cell lines (LCLs) expression from 855 adult female twins. We see evidence of up to 60% of age effects on transcription levels shared across tissues, and 47% of those on splicing. Using gene expression variance and discordance between genetically identical MZ twin pairs, we identify 137 genes with age-related changes in variance and 42 genes with age-related discordance between co-twins; implying the latter are driven by environmental effects. We identify four eQTLs whose effect on expression is age-dependent (FDR 5%). Combined, these results show a complicated mix of environmental and genetically driven changes in expression with age. Using the twin structure in our data, we show that additive genetic effects explain considerably more of the variance in gene expression than aging, but less that other environmental factors, potentially explaining why reliable expression-derived biomarkers for healthy-aging have proved elusive compared with those derived from methylation.

Estimating the causal tissues for complex traits and diseases.

How to interpret the biological causes underlying the predisposing markers identified through genome-wide association studies (GWAS) remains an open question. One direct and powerful way to assess the genetic causality behind GWAS is through analysis of expression quantitative trait loci (eQTLs). Here we describe a new approach to estimate the tissues behind the genetic causality of a variety of GWAS traits, using the cis-eQTLs in 44 tissues from the Genotype-Tissue Expression (GTEx) Consortium. We have adapted the regulatory trait concordance (RTC) score to measure the probability of eQTLs being active in multiple tissues and to calculate the probability that a GWAS-associated variant and an eQTL tag the same functional effect. By normalizing the GWAS-eQTL probabilities by the tissue-sharing estimates for eQTLs, we generate relative tissue-causality profiles for GWAS traits. Our approach not only implicates the gene likely mediating individual GWAS signals, but also highlights tissues where the genetic causality for an individual trait is likely manifested.

Quantifying the regulatory effect size of cis-acting genetic variation using allelic fold change.

Mapping cis-acting expression quantitative trait loci (cis-eQTL) has become a popular approach for characterizing proximal genetic regulatory variants. In this paper, we describe and characterize log allelic fold change (aFC), the magnitude of expression change associated with a given genetic variant, as a biologically interpretable unit for quantifying the effect size of cis-eQTLs and a mathematically convenient approach for systematic modeling of cis-regulation. This measure is mathematically independent from expression level and allele frequency, additive, applicable to multiallelic variants, and generalizable to multiple independent variants. We provide efficient tools and guidelines for estimating aFC from both eQTL and allelic expression data sets and apply it to Genotype Tissue Expression (GTEx) data. We show that aFC estimates independently derived from eQTL and allelic expression data are highly consistent, and identify technical and biological correlates of eQTL effect size. We generalize aFC to analyze genes with two eQTLs in GTEx and show that in nearly all cases the two eQTLs act independently in regulating gene expression. In summary, aFC is a solid measure of cis-regulatory effect size that allows quantitative interpretation of cellular regulatory events from population data, and it is a valuable approach for investigating novel aspects of eQTL data sets.

A complete tool set for molecular QTL discovery and analysis.

Population scale studies combining genetic information with molecular phenotypes (for example, gene expression) have become a standard to dissect the effects of genetic variants onto organismal phenotypes. These kinds of data sets require powerful, fast and versatile methods able to discover molecular Quantitative Trait Loci (molQTL). Here we propose such a solution, QTLtools, a modular framework that contains multiple new and well-established methods to prepare the data, to discover proximal and distal molQTLs and, finally, to integrate them with GWAS variants and functional annotations of the genome. We demonstrate its utility by performing a complete expression QTL study in a few easy-to-perform steps. QTLtools is open source and available at https://qtltools.github.io/qtltools/.

Time-dependent genetic effects on gene expression implicate aging processes.

Gene expression is dependent on genetic and environmental factors. In the last decade, a large body of research has significantly improved our understanding of the genetic architecture of gene expression. However, it remains unclear whether genetic effects on gene expression remain stable over time. Here, we show, using longitudinal whole-blood gene expression data from a twin cohort, that the genetic architecture of a subset of genes is unstable over time. In addition, we identified 2213 genes differentially expressed across time points that we linked with aging within and across studies. Interestingly, we discovered that most differentially expressed genes were affected by a subset of 77 putative causal genes. Finally, we observed that putative causal genes and down-regulated genes were affected by a loss of genetic control between time points. Taken together, our data suggest that instability in the genetic architecture of a subset of genes could lead to widespread effects on the transcriptome with an aging signature.

A Low-Frequency Inactivating AKT2 Variant Enriched in the Finnish Population Is Associated With Fasting Insulin Levels and Type 2 Diabetes Risk.

To identify novel coding association signals and facilitate characterization of mechanisms influencing glycemic traits and type 2 diabetes risk, we analyzed 109,215 variants derived from exome array genotyping together with an additional 390,225 variants from exome sequence in up to 39,339 normoglycemic individuals from five ancestry groups. We identified a novel association between the coding variant (p.Pro50Thr) in AKT2 and fasting plasma insulin (FI), a gene in which rare fully penetrant mutations are causal for monogenic glycemic disorders. The low-frequency allele is associated with a 12% increase in FI levels. This variant is present at 1.1% frequency in Finns but virtually absent in individuals from other ancestries. Carriers of the FI-increasing allele had increased 2-h insulin values, decreased insulin sensitivity, and increased risk of type 2 diabetes (odds ratio 1.05). In cellular studies, the AKT2-Thr50 protein exhibited a partial loss of function. We extend the allelic spectrum for coding variants in AKT2 associated with disorders of glucose homeostasis and demonstrate bidirectional effects of variants within the pleckstrin homology domain of AKT2.

Genome-wide association analysis identifies TXNRD2, ATXN2 and FOXC1 as susceptibility loci for primary open-angle glaucoma.

Primary open-angle glaucoma (POAG) is a leading cause of blindness worldwide. To identify new susceptibility loci, we performed meta-analysis on genome-wide association study (GWAS) results from eight independent studies from the United States (3,853 cases and 33,480 controls) and investigated the most significantly associated SNPs in two Australian studies (1,252 cases and 2,592 controls), three European studies (875 cases and 4,107 controls) and a Singaporean Chinese study (1,037 cases and 2,543 controls). A meta-analysis of the top SNPs identified three new associated loci: rs35934224[T] in TXNRD2 (odds ratio (OR) = 0.78, P = 4.05 × 10(-11)) encoding a mitochondrial protein required for redox homeostasis; rs7137828[T] in ATXN2 (OR = 1.17, P = 8.73 × 10(-10)); and rs2745572[A] upstream of FOXC1 (OR = 1.17, P = 1.76 × 10(-10)). Using RT-PCR and immunohistochemistry, we show TXNRD2 and ATXN2 expression in retinal ganglion cells and the optic nerve head. These results identify new pathways underlying POAG susceptibility and suggest new targets for preventative therapies.

The First New Zealanders? An Alternative Interpretation of Stable Isotope Data from Wairau Bar, New Zealand.

PLOS ONE Volume 8 includes an article "The First New Zealanders: Patterns of Diet and Mobility Revealed through Isotope Analysis". The paper proposes that burial groups within the settlement phase site of Wairau Bar differ in terms of dietary stable isotopes and 87Sr/86Sr. The authors argue this difference is probably due to one group being a founding population while the other burials are later. Here we review the work of Kinaston et al. and present an alternative analysis and interpretation of the isotopic data. Treating the isotope data independently from cultural and biological factors we find that sex best explains dietary variation. Our reassessment of 87Sr/86Sr confirms the authors original finding of high mobility of early New Zealanders but suggests a larger range of individuals should be considered 'non-local' on current evidence.

Common genetic variants influence human subcortical brain structures.

The highly complex structure of the human brain is strongly shaped by genetic influences. Subcortical brain regions form circuits with cortical areas to coordinate movement, learning, memory and motivation, and altered circuits can lead to abnormal behaviour and disease. To investigate how common genetic variants affect the structure of these brain regions, here we conduct genome-wide association studies of the volumes of seven subcortical regions and the intracranial volume derived from magnetic resonance images of 30,717 individuals from 50 cohorts. We identify five novel genetic variants influencing the volumes of the putamen and caudate nucleus. We also find stronger evidence for three loci with previously established influences on hippocampal volume and intracranial volume. These variants show specific volumetric effects on brain structures rather than global effects across structures. The strongest effects were found for the putamen, where a novel intergenic locus with replicable influence on volume (rs945270; P = 1.08 × 10(-33); 0.52% variance explained) showed evidence of altering the expression of the KTN1 gene in both brain and blood tissue. Variants influencing putamen volume clustered near developmental genes that regulate apoptosis, axon guidance and vesicle transport. Identification of these genetic variants provides insight into the causes of variability in human brain development, and may help to determine mechanisms of neuropsychiatric dysfunction.

Gene expression changes with age in skin, adipose tissue, blood and brain.

BACKGROUND: Previous studies have demonstrated that gene expression levels change with age. These changes are hypothesized to influence the aging rate of an individual. We analyzed gene expression changes with age in abdominal skin, subcutaneous adipose tissue and lymphoblastoid cell lines in 856 female twins in the age range of 39-85 years. Additionally, we investigated genotypic variants involved in genotype-by-age interactions to understand how the genomic regulation of gene expression alters with age. RESULTS: Using a linear mixed model, differential expression with age was identified in 1,672 genes in skin and 188 genes in adipose tissue. Only two genes expressed in lymphoblastoid cell lines showed significant changes with age. Genes significantly regulated by age were compared with expression profiles in 10 brain regions from 100 postmortem brains aged 16 to 83 years. We identified only one age-related gene common to the three tissues. There were 12 genes that showed differential expression with age in both skin and brain tissue and three common to adipose and brain tissues. CONCLUSIONS: Skin showed the most age-related gene expression changes of all the tissues investigated, with many of the genes being previously implicated in fatty acid metabolism, mitochondrial activity, cancer and splicing. A significant proportion of age-related changes in gene expression appear to be tissue-specific with only a few genes sharing an age effect in expression across tissues. More research is needed to improve our understanding of the genetic influences on aging and the relationship with age-related diseases.

Evaluation of PAX3 genetic variants and nevus number.

The presence of a high nevus number is the strongest phenotypic predictor of melanoma risk. Here, we describe the results of a three-stage study directed at identifying risk variants for the high nevus phenotype. At the first stage, 263 melanoma cases from Barcelona were genotyped for 223 single-nucleotide polymorphisms (SNPs) in 39 candidate genes. Seven SNPs in the PAX3 gene were found to be significantly associated with nevus number under the additive model. Next, the associations for seven PAX3 variants were evaluated in 1217 melanoma cases and 475 controls from Leeds; and in 3054 healthy twins from TwinsUK. Associations with high nevus number were detected for rs6754024 (P values < 0.01) in the Barcelona and Leeds datasets and for rs2855268 (P values < 0.01) in the Barcelona and the TwinsUK sets. Associations (P values < 0.001) in the opposite direction were detected for rs7600206 and rs12995399 in the Barcelona and TwinsUK sets. This study suggests that SNPs in PAX3 are associated with nevus number, providing support for PAX3 as a candidate nevus gene. Further studies are needed to examine the role of PAX3 in melanoma susceptibility.

ZNF804A and cortical thickness in schizophrenia and bipolar disorder.

ZNF804A SNP rs1344706 confers genome-wide risk for schizophrenia and bipolar disorder. Both disorders affect cortical thickness. To determine if single nucleotide polymorphisms (SNPs) across ZNF804A are associated with cortical thinning, we investigated 63 SNPs (including rs1344706) in 365 psychosis patients and healthy controls. Results show no significant associations.

Identification of common variants associated with human hippocampal and intracranial volumes.

Identifying genetic variants influencing human brain structures may reveal new biological mechanisms underlying cognition and neuropsychiatric illness. The volume of the hippocampus is a biomarker of incipient Alzheimer's disease and is reduced in schizophrenia, major depression and mesial temporal lobe epilepsy. Whereas many brain imaging phenotypes are highly heritable, identifying and replicating genetic influences has been difficult, as small effects and the high costs of magnetic resonance imaging (MRI) have led to underpowered studies. Here we report genome-wide association meta-analyses and replication for mean bilateral hippocampal, total brain and intracranial volumes from a large multinational consortium. The intergenic variant rs7294919 was associated with hippocampal volume (12q24.22; N = 21,151; P = 6.70 × 10(-16)) and the expression levels of the positional candidate gene TESC in brain tissue. Additionally, rs10784502, located within HMGA2, was associated with intracranial volume (12q14.3; N = 15,782; P = 1.12 × 10(-12)). We also identified a suggestive association with total brain volume at rs10494373 within DDR2 (1q23.3; N = 6,500; P = 5.81 × 10(-7)).

Genome-wide association study identifies genetic loci associated with body mass index and high density lipoprotein-cholesterol levels during psychopharmacological treatment - a cross-sectional naturalistic study.

Metabolic and cardiovascular side effects are serious clinical problems related to psychopharmacological treatment, but the underlying mechanisms are mostly unknown. We performed a genome-wide association study of metabolic and cardiovascular risk factors during pharmacological therapy. Twelve indicators of metabolic side effects as well as cardiovascular risk factors were analyzed in a naturalistic sample of 594 patients of Norwegian ancestry. We analyzed interactions between gene variants and three categories of psychopharmacological agents based on their reported potential for side effects. For body mass index (BMI), two significantly associated loci were identified on 8q21.3. There were seven markers in one 30-kb region, and the strongest signal was rs7838490. In another locus 140kb away, six markers were significant, and rs6989402 obtained the strongest signal. Both of these loci are located upstream of the gene matrix metalloproteinase 16 (MMP16). For high density lipoprotein cholesterol (HDL-C), marker rs11615274 on 12q21 was significant. The results highlight three genomic regions potentially harboring susceptibility genes for drug-induced metabolic side effects, identifying MMP16 as a candidate gene. This deserves to be replicated in additional populations to provide more evidence for molecular genetic mechanisms of side effects during psychopharmacological treatment.