Metabolite Shifts Induced by Marathon Race Competition Differ between Athletes Based on Level of Fitness and Performance: A Substudy of the Enzy-MagIC Study.

This study compared metabolite shifts induced by training for, participation in, and recovery from a marathon race competition among athletes divided into three groups based on fitness (relative maximum oxygen uptake (VO2max)) and performance levels (net running time). Plasma samples from 76 male runners participating in the Munich Marathon were analyzed for metabolite shifts using a targeted metabolomics panel. For the entire cohort of runners, pronounced increases were measured immediately after the race for plasma concentrations of acylcarnitines (AC), the ratio (palmitoylcarnitine + stearoylcarnitine)/free carnitine that is used as a proxy for the activity of the mitochondrial enzyme carnitine palmitoyltransferase, and arginine-related metabolites, with decreases in most amino acids (AA) and phospholipids. Plasma levels of AA and phospholipids were strongly increased 24 and 72 h post-race. Post-race plasma concentrations of AC and arginine-related metabolites were higher in the low compared to top performers, indicating an accumulation of fatty acids and a reliance on protein catabolism to provide energy after the marathon event. This study showed that marathon race competition is associated with an extensive and prolonged perturbation in plasma metabolite concentrations with a strong AC signature that is greater in the slower, less aerobically fit runners. Furthermore, changes in the arginine-related metabolites were observed.

VarWatch-A stand-alone software tool for variant matching.

Massively parallel DNA sequencing of clinical samples holds great promise for the gene-based diagnosis of human inherited diseases because it allows rapid detection of putatively causative mutations at genome-wide level. Without additional evidence complementing their initial bioinformatics evaluation, however, the clinical relevance of such candidate genetic variants often remains unclear. In consequence, dedicated 'matching' services have been established in recent years that aim at the discovery of other, comparable case reports to facilitate individual diagnoses. However, legal concerns have been raised about the global sharing of genetic data, particularly in Europe where the recently enacted General Data Protection Regulation EU-2016/679 classifies genetic data as highly sensitive. Hence, unrestricted sharing of genetic data from clinical cases on platforms outside the national jurisdiction increasingly may be perceived as problematic. To allow collaborative data producers, particularly large consortia of diagnostic laboratories, to acknowledge these concerns while still practicing efficient case matching internally, novel tools are required. To this end, we developed VarWatch, an easy-to-deploy and highly scalable case matching software that provides users with comprehensive programmatic tools and a user-friendly interface to fulfil said purpose.

REduction of THRomboembolic EVents during Ablation using the laserballoon: The RETHREVA registry.

INTRODUCTION: Cerebral events (CEs), including silent (SCEs), are a known complication of left atrial catheter ablation (LACA) in patients with atrial fibrillation. The aim of this prospective registry was to gain more information about CEs during laserballoon LACA and to reduce the risk of their occurrence. METHODS AND RESULTS: We enrolled 74 patients (age 61 ± 11 years; 74% male; CHA2 DS2 -VASc 1.9 ± 1.4). Cerebral MRI (1.5 Tesla) was performed to detect CEs. ASPItest identified aspirin-resistant patients (ARPs). All bleeding complications were recorded. Due to an initial high CE rate, we evolved our clinical procedure step-by-step arriving at an optimized protocol: -Group 1: heparin after single transseptal puncture (TP), activated clotting time (ACT) > 300 seconds (CE: 64.3%). -Group 2: heparin after double TP, ACT > 300 seconds; 2a without (CE: 45.5%, RRR: -29.2%) and 2b with additional intravenous aspirin (CE: 36.4%, RRR: -43.4%; excluding ARP: 30%, RRR: -53.3%). -Group 3: heparin before double TP, ACT > 350 seconds; 3a without (CE: 54.5%, RRR: -15.2%) and 3b with aspirin (CE: 18.5%, RRR: -71.2%; excluding ARP: 8.7%, RRR: -86.5%). Larger LA diameter > 44 mm (OR: 1.149, P  =  0.005) and no aspirin use (OR: 4.308, P  =  0.008) were CE risk factors in multivariate logistic regression. In those patients receiving aspirin, aspirin resistance (OR: 22.4, P  =  0.011) was an exceptionally strong risk factor. CONCLUSION: These data support the use of intravenous aspirin including monitoring of aspirin resistance in addition to ACT-guided heparin. An optimized protocol of heparin before TP, double TP, and intravenous aspirin in non-ARP resulted in a significantly lowered CE incidence and severity.

NFAT5 and SLC4A10 Loci Associate with Plasma Osmolality.

Disorders of water balance, an excess or deficit of total body water relative to body electrolyte content, are common and ascertained by plasma hypo- or hypernatremia, respectively. We performed a two-stage genome-wide association study meta-analysis on plasma sodium concentration in 45,889 individuals of European descent (stage 1 discovery) and 17,637 additional individuals of European descent (stage 2 replication), and a transethnic meta-analysis of replicated single-nucleotide polymorphisms in 79,506 individuals (63,526 individuals of European descent, 8765 individuals of Asian Indian descent, and 7215 individuals of African descent). In stage 1, we identified eight loci associated with plasma sodium concentration at P<5.0 × 10-6 Of these, rs9980 at NFAT5 replicated in stage 2 meta-analysis (P=3.1 × 10-5), with combined stages 1 and 2 genome-wide significance of P=5.6 × 10-10 Transethnic meta-analysis further supported the association at rs9980 (P=5.9 × 10-12). Additionally, rs16846053 at SLC4A10 showed nominally, but not genome-wide, significant association in combined stages 1 and 2 meta-analysis (P=6.7 × 10-8). NFAT5 encodes a ubiquitously expressed transcription factor that coordinates the intracellular response to hypertonic stress but was not previously implicated in the regulation of systemic water balance. SLC4A10 encodes a sodium bicarbonate transporter with a brain-restricted expression pattern, and variant rs16846053 affects a putative intronic NFAT5 DNA binding motif. The lead variants for NFAT5 and SLC4A10 are cis expression quantitative trait loci in tissues of the central nervous system and relevant to transcriptional regulation. Thus, genetic variation in NFAT5 and SLC4A10 expression and function in the central nervous system may affect the regulation of systemic water balance.

Electrophysiological characterization of a large set of novel variants in the SCN5A-gene: identification of novel LQTS3 and BrS mutations.

SCN5A encodes for the α-subunit of the cardiac voltage-gated sodium channel Nav1.5. Gain-of-function mutations in SCN5A are related to congenital long QT syndrome (LQTS3) characterized by delayed cardiac repolarization, leading to a prolonged QT interval in the ECG. Loss-of-function mutations in SCN5A are related to Brugada syndrome (BrS), characterized by an ST-segment elevation in the right precordial leads (V1-V3). The aim of this study was the characterization of a large set of novel SCN5A variants found in patients with different cardiac phenotypes, mainly LQTS and BrS. SCN5A variants of 13 families were functionally characterized in Xenopus laevis oocytes using the two-electrode voltage-clamp technique. We found in most of the cases, but not all, that the electrophysiology of the variants correlated with the clinically diagnosed phenotype. A susceptibility to develop LQTS can be suggested in patients carrying the variants S216L, K480N, A572D, F816Y, and G983D. However, taking the phenotype into account, the presence of the variants in genomic data bases, the mutational segregation, combined with our in vitro and in silico experiments, the variants S216L, S262G, K480N, A572D, F816Y, G983D, and T1526P remain as variants of unknown significance. However, the SCN5A variants R568H and A993T can be classified as pathogenic LQTS3 causing mutations, while R222stop and R2012H are novel BrS causing mutations.

Candidate gene variants of the immune system and sudden infant death syndrome.

BACKGROUND: Sudden infant death syndrome (SIDS) causes early infant death with an incidence between 0.5 and 2.5 cases among 1000 live births. Besides central sleep apnea and thermal dysregulation, infections have been repeatedly suggested to be implicated in SIDS etiology. METHODS: To test the risk contribution of common genetic variants related to infection, we genotyped 40 single-nucleotide polymorphisms (SNPs) from 15 candidate genes for association with SIDS in a total of 579 cases and 1124 controls from Germany and the UK in a two-stage case control design. RESULTS: The discovery-stage series (267 SIDS cases and 303 controls) revealed nominally significant associations for variants in interleukin 6 (IL6) (rs1880243), interleukin 10 (IL10) (rs1800871, rs1800872), and mannose-binding lectin 2 (MBL2) (rs930506), and for several other variants in subgroups. Meta-analyses were then performed in adding genotype information from a genome-wide association study of another 312 European SIDS cases and 821 controls. Overall associations were observed for two independent variants in MBL2: rs930506 in a co-dominant model (odds ratio (OR) = 0.82, p = 0.04) and rs1838065 in a dominant model (OR = 1.27, p = 0.03). CONCLUSION: Our study did not replicate published associations of IL10 variants with SIDS. However, the evidence for two independent MBL2 variants in the combined analysis of two large series seems consistent with the hypothesis that infection may play a role in SIDS pathogenesis.

The cost-effectiveness of UGT1A1 genotyping before colorectal cancer treatment with irinotecan from the perspective of the German statutory health insurance.

BACKGROUND: The evidence concerning the cost-effectiveness of UGT1A1*28 genotyping is ambiguous and does not allow drawing valid conclusions for Germany. This study evaluates the cost-effectiveness of UGT1A1 genotyping in patients with metastatic colorectal cancer undergoing irinotecan-based chemotherapy compared to no testing from the perspective of the German statutory health insurance. MATERIAL AND METHODS: A decision-analytic Markov model with a life time horizon was developed. No testing was compared to two genotype-dependent therapy strategies: 1) dose reduction by 25%; and 2) administration of a prophylactic G-CSF growth factor analog for homozygous and heterozygous patients. Probability, quality of life and cost parameters used in this study were based on published literature. Deterministic and probabilistic sensitivity analyses were performed to account for parameter uncertainties. RESULTS: Strategy 1 dominated all remaining strategies. Compared to no testing, it resulted in only marginal QALY increases (0.0002) but a cost reduction of €580 per patient. Strategy 2 resulted in the same health gains but increased costs by €10 773. In the probabilistic analysis, genotyping and dose reduction was the optimal strategy in approximately 100% of simulations at a threshold of €50 000 per QALY. Deterministic sensitivity analysis shows that uncertainty for this strategy originated primarily from costs for irinotecan-based chemotherapy, from the prevalence of neutropenia among heterozygous patients, and from whether dose reduction is applied to both homozygotes and heterozygotes or only to the former. CONCLUSION: This model-based synthesis of the most recent evidence suggests that pharmacogenetic UGT1A1 testing prior to irinotecan-based chemotherapy dominates non-personalized colon cancer care in Germany. However, as structural uncertainty remains high, these results require validation in clinical practice, e.g. based on a managed-entry agreement.

Analysis for Genetic Modifiers of Disease Severity in Patients With Long-QT Syndrome Type 2.

BACKGROUND: Considerable interest exists in the identification of genetic modifiers of disease severity in the long-QT syndrome (LQTS) as their identification may contribute to refinement of risk stratification. METHODS AND RESULTS: We searched for single-nucleotide polymorphisms (SNPs) that modulate the corrected QT (QTc)-interval and the occurrence of cardiac events in 639 patients harboring different mutations in KCNH2. We analyzed 1201 SNPs in and around 18 candidate genes, and in another approach investigated 22 independent SNPs previously identified as modulators of QTc-interval in genome-wide association studies in the general population. In an analysis for quantitative effects on the QTc-interval, 3 independent SNPs at NOS1AP (rs10494366, P=9.5×10(-8); rs12143842, P=4.8×10(-7); and rs2880058, P=8.6×10(-7)) were strongly associated with the QTc-interval with marked effects (>12 ms/allele). Analysis of patients versus general population controls uncovered enrichment of QTc-prolonging alleles in patients for 2 SNPs, located respectively at NOS1AP (rs12029454; odds ratio, 1.85; 95% confidence interval, 1.32-2.59; P=3×10(-4)) and KCNQ1 (rs12576239; odds ratio, 1.84; 95% confidence interval, 1.31-2.60; P=5×10(-4)). An analysis of the cumulative effect of the 6 NOS1AP SNPs by means of a multilocus genetic risk score (GRS(NOS1AP)) uncovered a strong linear relationship between GRS(NOS1AP) and the QTc-interval (P=4.2×10(-7)). Furthermore, patients with a GRS(NOS1AP) in the lowest quartile had a lower relative risk of cardiac events compared with patients in the other quartiles combined (P=0.039). CONCLUSIONS: We uncovered unexpectedly large effects of NOS1AP SNPs on the QTc-interval and a trend for effects on risk of cardiac events. For the first time, we linked common genetic variation at KCNQ1 with risk of long-QT syndrome.

SNiPA: an interactive, genetic variant-centered annotation browser.

MOTIVATION: Linking genes and functional information to genetic variants identified by association studies remains difficult. Resources containing extensive genomic annotations are available but often not fully utilized due to heterogeneous data formats. To enhance their accessibility, we integrated many annotation datasets into a user-friendly webserver. AVAILABILITY AND IMPLEMENTATION: http://www.snipa.org/ CONTACT: g.kastenmueller@helmholtz-muenchen.de SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Points to consider for prioritizing clinical genetic testing services: a European consensus process oriented at accountability for reasonableness.

Given the cost constraints of the European health-care systems, criteria are needed to decide which genetic services to fund from the public budgets, if not all can be covered. To ensure that high-priority services are available equitably within and across the European countries, a shared set of prioritization criteria would be desirable. A decision process following the accountability for reasonableness framework was undertaken, including a multidisciplinary EuroGentest/PPPC-ESHG workshop to develop shared prioritization criteria. Resources are currently too limited to fund all the beneficial genetic testing services available in the next decade. Ethically and economically reflected prioritization criteria are needed. Prioritization should be based on considerations of medical benefit, health need and costs. Medical benefit includes evidence of benefit in terms of clinical benefit, benefit of information for important life decisions, benefit for other people apart from the person tested and the patient-specific likelihood of being affected by the condition tested for. It may be subject to a finite time window. Health need includes the severity of the condition tested for and its progression at the time of testing. Further discussion and better evidence is needed before clearly defined recommendations can be made or a prioritization algorithm proposed. To our knowledge, this is the first time a clinical society has initiated a decision process about health-care prioritization on a European level, following the principles of accountability for reasonableness. We provide points to consider to stimulate this debate across the EU and to serve as a reference for improving patient management.

Annotation of loci from genome-wide association studies using tissue-specific quantitative interaction proteomics.

Genome-wide association studies (GWAS) have identified thousands of loci associated with complex traits, but it is challenging to pinpoint causal genes in these loci and to exploit subtle association signals. We used tissue-specific quantitative interaction proteomics to map a network of five genes involved in the Mendelian disorder long QT syndrome (LQTS). We integrated the LQTS network with GWAS loci from the corresponding common complex trait, QT-interval variation, to identify candidate genes that were subsequently confirmed in Xenopus laevis oocytes and zebrafish. We used the LQTS protein network to filter weak GWAS signals by identifying single-nucleotide polymorphisms (SNPs) in proximity to genes in the network supported by strong proteomic evidence. Three SNPs passing this filter reached genome-wide significance after replication genotyping. Overall, we present a general strategy to propose candidates in GWAS loci for functional studies and to systematically filter subtle association signals using tissue-specific quantitative interaction proteomics.

An enhancer polymorphism at the cardiomyocyte intercalated disc protein NOS1AP locus is a major regulator of the QT interval.

QT interval variation is assumed to arise from variation in repolarization as evidenced from rare Na- and K-channel mutations in Mendelian QT prolongation syndromes. However, in the general population, common noncoding variants at a chromosome 1q locus are the most common genetic regulators of QT interval variation. In this study, we use multiple human genetic, molecular genetic, and cellular assays to identify a functional variant underlying trait association: a noncoding polymorphism (rs7539120) that maps within an enhancer of NOS1AP and affects cardiac function by increasing NOS1AP transcript expression. We further localized NOS1AP to cardiomyocyte intercalated discs (IDs) and demonstrate that overexpression of NOS1AP in cardiomyocytes leads to altered cellular electrophysiology. We advance the hypothesis that NOS1AP affects cardiac electrical conductance and coupling and thereby regulates the QT interval through propagation defects. As further evidence of an important role for propagation variation affecting QT interval in humans, we show that common polymorphisms mapping near a specific set of 170 genes encoding ID proteins are significantly enriched for association with the QT interval, as compared to genome-wide markers. These results suggest that focused studies of proteins within the cardiomyocyte ID are likely to provide insights into QT prolongation and its associated disorders.

A genome-wide association study identifies 6p21 as novel risk locus for dilated cardiomyopathy.

AIMS: Dilated cardiomyopathy (DCM) is one of the leading causes for cardiac transplantations and accounts for up to one-third of all heart failure cases. Since extrinsic and monogenic causes explain only a fraction of all cases, common genetic variants are suspected to contribute to the pathogenesis of DCM, its age of onset, and clinical progression. By a large-scale case-control genome-wide association study we aimed here to identify novel genetic risk loci for DCM. METHODS AND RESULTS: Applying a three-staged study design, we analysed more than 4100 DCM cases and 7600 controls. We identified and successfully replicated multiple single nucleotide polymorphism on chromosome 6p21. In the combined analysis, the most significant association signal was obtained for rs9262636 (P = 4.90 × 10(-9)) located in HCG22, which could again be replicated in an independent cohort. Taking advantage of expression quantitative trait loci (eQTL) as molecular phenotypes, we identified rs9262636 as an eQTL for several closely located genes encoding class I and class II major histocompatibility complex heavy chain receptors. CONCLUSION: The present study reveals a novel genetic susceptibility locus that clearly underlines the role of genetically driven, inflammatory processes in the pathogenesis of idiopathic DCM.

SNP prioritization using a Bayesian probability of association.

Prioritization is the process whereby a set of possible candidate genes or SNPs is ranked so that the most promising can be taken forward into further studies. In a genome-wide association study, prioritization is usually based on the P-values alone, but researchers sometimes take account of external annotation information about the SNPs such as whether the SNP lies close to a good candidate gene. Using external information in this way is inherently subjective and is often not formalized, making the analysis difficult to reproduce. Building on previous work that has identified 14 important types of external information, we present an approximate Bayesian analysis that produces an estimate of the probability of association. The calculation combines four sources of information: the genome-wide data, SNP information derived from bioinformatics databases, empirical SNP weights, and the researchers' subjective prior opinions. The calculation is fast enough that it can be applied to millions of SNPS and although it does rely on subjective judgments, those judgments are made explicit so that the final SNP selection can be reproduced. We show that the resulting probability of association is intuitively more appealing than the P-value because it is easier to interpret and it makes allowance for the power of the study. We illustrate the use of the probability of association for SNP prioritization by applying it to a meta-analysis of kidney function genome-wide association studies and demonstrate that SNP selection performs better using the probability of association compared with P-values alone.

Importance of different types of prior knowledge in selecting genome-wide findings for follow-up.

Biological plausibility and other prior information could help select genome-wide association (GWA) findings for further follow-up, but there is no consensus on which types of knowledge should be considered or how to weight them. We used experts' opinions and empirical evidence to estimate the relative importance of 15 types of information at the single-nucleotide polymorphism (SNP) and gene levels. Opinions were elicited from 10 experts using a two-round Delphi survey. Empirical evidence was obtained by comparing the frequency of each type of characteristic in SNPs established as being associated with seven disease traits through GWA meta-analysis and independent replication, with the corresponding frequency in a randomly selected set of SNPs. SNP and gene characteristics were retrieved using a specially developed bioinformatics tool. Both the expert and the empirical evidence rated previous association in a meta-analysis or more than one study as conferring the highest relative probability of true association, whereas previous association in a single study ranked much lower. High relative probabilities were also observed for location in a functional protein domain, although location in a region evolutionarily conserved in vertebrates was ranked high by the data but not by the experts. Our empirical evidence did not support the importance attributed by the experts to whether the gene encodes a protein in a pathway or shows interactions relevant to the trait. Our findings provide insight into the selection and weighting of different types of knowledge in SNP or gene prioritization, and point to areas requiring further research.

Network-based SNP meta-analysis identifies joint and disjoint genetic features across common human diseases.

BACKGROUND: Genome-wide association studies (GWAS) have provided a large set of genetic loci influencing the risk for many common diseases. Association studies typically analyze one specific trait in single populations in an isolated fashion without taking into account the potential phenotypic and genetic correlation between traits. However, GWA data can be efficiently used to identify overlapping loci with analogous or contrasting effects on different diseases. RESULTS: Here, we describe a new approach to systematically prioritize and interpret available GWA data. We focus on the analysis of joint and disjoint genetic determinants across diseases. Using network analysis, we show that variant-based approaches are superior to locus-based analyses. In addition, we provide a prioritization of disease loci based on network properties and discuss the roles of hub loci across several diseases. We demonstrate that, in general, agonistic associations appear to reflect current disease classifications, and present the potential use of effect sizes in refining and revising these agonistic signals. We further identify potential branching points in disease etiologies based on antagonistic variants and describe plausible small-scale models of the underlying molecular switches. CONCLUSIONS: The observation that a surprisingly high fraction (>15%) of the SNPs considered in our study are associated both agonistically and antagonistically with related as well as unrelated disorders indicates that the molecular mechanisms influencing causes and progress of human diseases are in part interrelated. Genetic overlaps between two diseases also suggest the importance of the affected entities in the specific pathogenic pathways and should be investigated further.

The metabochip, a custom genotyping array for genetic studies of metabolic, cardiovascular, and anthropometric traits.

Genome-wide association studies have identified hundreds of loci for type 2 diabetes, coronary artery disease and myocardial infarction, as well as for related traits such as body mass index, glucose and insulin levels, lipid levels, and blood pressure. These studies also have pointed to thousands of loci with promising but not yet compelling association evidence. To establish association at additional loci and to characterize the genome-wide significant loci by fine-mapping, we designed the "Metabochip," a custom genotyping array that assays nearly 200,000 SNP markers. Here, we describe the Metabochip and its component SNP sets, evaluate its performance in capturing variation across the allele-frequency spectrum, describe solutions to methodological challenges commonly encountered in its analysis, and evaluate its performance as a platform for genotype imputation. The metabochip achieves dramatic cost efficiencies compared to designing single-trait follow-up reagents, and provides the opportunity to compare results across a range of related traits. The metabochip and similar custom genotyping arrays offer a powerful and cost-effective approach to follow-up large-scale genotyping and sequencing studies and advance our understanding of the genetic basis of complex human diseases and traits.

Meta-analysis identifies six new susceptibility loci for atrial fibrillation.

Atrial fibrillation is a highly prevalent arrhythmia and a major risk factor for stroke, heart failure and death. We conducted a genome-wide association study (GWAS) in individuals of European ancestry, including 6,707 with and 52,426 without atrial fibrillation. Six new atrial fibrillation susceptibility loci were identified and replicated in an additional sample of individuals of European ancestry, including 5,381 subjects with and 10,030 subjects without atrial fibrillation (P < 5 × 10(-8)). Four of the loci identified in Europeans were further replicated in silico in a GWAS of Japanese individuals, including 843 individuals with and 3,350 individuals without atrial fibrillation. The identified loci implicate candidate genes that encode transcription factors related to cardiopulmonary development, cardiac-expressed ion channels and cell signaling molecules.

Cis-acting polymorphisms affect complex traits through modifications of microRNA regulation pathways.

Genome-wide association studies (GWAS) have become an effective tool to map genes and regions contributing to multifactorial human diseases and traits. A comparably small number of variants identified by GWAS are known to have a direct effect on protein structure whereas the majority of variants is thought to exert their moderate influences on the phenotype through regulatory changes in mRNA expression. MicroRNAs (miRNAs) have been identified as powerful posttranscriptional regulators of mRNAs. Binding to their target sites, which are mostly located within the 3'-untranslated region (3'-UTR) of mRNA transcripts, they modulate mRNA expression and stability. Until today almost all human mRNA transcripts are known to harbor at least one miRNA target site with an average of over 20 miRNA target sites per transcript. Among 5,101 GWAS-identified sentinel single nucleotide polymorphisms (SNPs) that correspond to 18,884 SNPs in linkage disequilibrium (LD) with the sentinels (r2 ≥ 0.8) we identified a significant overrepresentation of SNPs that affect the 3'-UTR of genes (OR = 2.33, 95% CI = 2.12-2.57, P < 10(-52)). This effect was even stronger considering all SNPs in one LD bin a single signal (OR = 4.27, 95% CI = 3.84-4.74, P < 10(-114)). Based on crosslinking immunoprecipitation data we identified four mechanisms affecting miRNA regulation by 3'-UTR mutations: (i) deletion or (ii) creation of miRNA recognition elements within validated RNA-induced silencing complex binding sites, (iii) alteration of 3'-UTR splicing leading to a loss of binding sites, and (iv) change of binding affinity due to modifications of 3'-UTR folding. We annotated 53 SNPs of a total of 288 trait-associated 3'-UTR SNPs as mediating at least one of these mechanisms. Using a qualitative systems biology approach, we demonstrate how our findings can be used to support biological interpretation of GWAS results as well as to provide new experimentally testable hypotheses.

Genome-wide association study identifies novel loci associated with circulating phospho- and sphingolipid concentrations.

Phospho- and sphingolipids are crucial cellular and intracellular compounds. These lipids are required for active transport, a number of enzymatic processes, membrane formation, and cell signalling. Disruption of their metabolism leads to several diseases, with diverse neurological, psychiatric, and metabolic consequences. A large number of phospholipid and sphingolipid species can be detected and measured in human plasma. We conducted a meta-analysis of five European family-based genome-wide association studies (N = 4034) on plasma levels of 24 sphingomyelins (SPM), 9 ceramides (CER), 57 phosphatidylcholines (PC), 20 lysophosphatidylcholines (LPC), 27 phosphatidylethanolamines (PE), and 16 PE-based plasmalogens (PLPE), as well as their proportions in each major class. This effort yielded 25 genome-wide significant loci for phospholipids (smallest P-value = 9.88×10(-204)) and 10 loci for sphingolipids (smallest P-value = 3.10×10(-57)). After a correction for multiple comparisons (P-value<2.2×10(-9)), we observed four novel loci significantly associated with phospholipids (PAQR9, AGPAT1, PKD2L1, PDXDC1) and two with sphingolipids (PLD2 and APOE) explaining up to 3.1% of the variance. Further analysis of the top findings with respect to within class molar proportions uncovered three additional loci for phospholipids (PNLIPRP2, PCDH20, and ABDH3) suggesting their involvement in either fatty acid elongation/saturation processes or fatty acid specific turnover mechanisms. Among those, 14 loci (KCNH7, AGPAT1, PNLIPRP2, SYT9, FADS1-2-3, DLG2, APOA1, ELOVL2, CDK17, LIPC, PDXDC1, PLD2, LASS4, and APOE) mapped into the glycerophospholipid and 12 loci (ILKAP, ITGA9, AGPAT1, FADS1-2-3, APOA1, PCDH20, LIPC, PDXDC1, SGPP1, APOE, LASS4, and PLD2) to the sphingolipid pathways. In large meta-analyses, associations between FADS1-2-3 and carotid intima media thickness, AGPAT1 and type 2 diabetes, and APOA1 and coronary artery disease were observed. In conclusion, our study identified nine novel phospho- and sphingolipid loci, substantially increasing our knowledge of the genetic basis for these traits.