Publications by authors named "Harm-Jan Westra"

77 Publications

Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression.

Nat Genet 2021 Sep 2;53(9):1300-1310. Epub 2021 Sep 2.

Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland.

Trait-associated genetic variants affect complex phenotypes primarily via regulatory mechanisms on the transcriptome. To investigate the genetics of gene expression, we performed cis- and trans-expression quantitative trait locus (eQTL) analyses using blood-derived expression from 31,684 individuals through the eQTLGen Consortium. We detected cis-eQTL for 88% of genes, and these were replicable in numerous tissues. Distal trans-eQTL (detected for 37% of 10,317 trait-associated variants tested) showed lower replication rates, partially due to low replication power and confounding by cell type composition. However, replication analyses in single-cell RNA-seq data prioritized intracellular trans-eQTL. Trans-eQTL exerted their effects via several mechanisms, primarily through regulation by transcription factors. Expression of 13% of the genes correlated with polygenic scores for 1,263 phenotypes, pinpointing potential drivers for those traits. In summary, this work represents a large eQTL resource, and its results serve as a starting point for in-depth interpretation of complex phenotypes.
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http://dx.doi.org/10.1038/s41588-021-00913-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8432599PMC
September 2021

Correction for both common and rare cell types in blood is important to identify genes that correlate with age.

BMC Genomics 2021 Mar 15;22(1):184. Epub 2021 Mar 15.

Department of Genetics, University Medical Centre Groningen, Groningen, The Netherlands.

Background: Aging is a multifactorial process that affects multiple tissues and is characterized by changes in homeostasis over time, leading to increased morbidity. Whole blood gene expression signatures have been associated with aging and have been used to gain information on its biological mechanisms, which are still not fully understood. However, blood is composed of many cell types whose proportions in blood vary with age. As a result, previously observed associations between gene expression levels and aging might be driven by cell type composition rather than intracellular aging mechanisms. To overcome this, previous aging studies already accounted for major cell types, but the possibility that the reported associations are false positives driven by less prevalent cell subtypes remains.

Results: Here, we compared the regression model from our previous work to an extended model that corrects for 33 additional white blood cell subtypes. Both models were applied to whole blood gene expression data from 3165 individuals belonging to the general population (age range of 18-81 years). We evaluated that the new model is a better fit for the data and it identified fewer genes associated with aging (625, compared to the 2808 of the initial model; P ≤ 2.5⨯10). Moreover, 511 genes (~ 18% of the 2808 genes identified by the initial model) were found using both models, indicating that the other previously reported genes could be proxies for less abundant cell types. In particular, functional enrichment of the genes identified by the new model highlighted pathways and GO terms specifically associated with platelet activity.

Conclusions: We conclude that gene expression analyses in blood strongly benefit from correction for both common and rare blood cell types, and recommend using blood-cell count estimates as standard covariates when studying whole blood gene expression.
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http://dx.doi.org/10.1186/s12864-020-07344-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7958454PMC
March 2021

Inflammation status modulates the effect of host genetic variation on intestinal gene expression in inflammatory bowel disease.

Nat Commun 2021 02 18;12(1):1122. Epub 2021 Feb 18.

Department of Gastroenterology and Hepatology, University of Groningen and University Medical Center Groningen, Groningen, The Netherlands.

More than 240 genetic risk loci have been associated with inflammatory bowel disease (IBD), but little is known about how they contribute to disease development in involved tissue. Here, we hypothesized that host genetic variation affects gene expression in an inflammation-dependent way, and investigated 299 snap-frozen intestinal biopsies from inflamed and non-inflamed mucosa from 171 IBD patients. RNA-sequencing was performed, and genotypes were determined using whole exome sequencing and genome wide genotyping. In total, 28,746 genes and 6,894,979 SNPs were included. Linear mixed models identified 8,881 independent intestinal cis-expression quantitative trait loci (cis-eQTLs) (FDR < 0.05) and interaction analysis revealed 190 inflammation-dependent intestinal cis-eQTLs (FDR < 0.05), including known IBD-risk genes and genes encoding immune-cell receptors and antibodies. The inflammation-dependent cis-eQTL SNPs (eSNPs) mainly interact with prevalence of immune cell types. Inflammation-dependent intestinal cis-eQTLs reveal genetic susceptibility under inflammatory conditions that can help identify the cell types involved in and the pathways underlying inflammation, knowledge that may guide future drug development and profile patients for precision medicine in IBD.
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http://dx.doi.org/10.1038/s41467-021-21458-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7892863PMC
February 2021

Large-scale association analyses identify host factors influencing human gut microbiome composition.

Nat Genet 2021 02 18;53(2):156-165. Epub 2021 Jan 18.

Department of Twin Research & Genetic Epidemiology, King's College London, London, UK.

To study the effect of host genetics on gut microbiome composition, the MiBioGen consortium curated and analyzed genome-wide genotypes and 16S fecal microbiome data from 18,340 individuals (24 cohorts). Microbial composition showed high variability across cohorts: only 9 of 410 genera were detected in more than 95% of samples. A genome-wide association study of host genetic variation regarding microbial taxa identified 31 loci affecting the microbiome at a genome-wide significant (P < 5 × 10) threshold. One locus, the lactase (LCT) gene locus, reached study-wide significance (genome-wide association study signal: P = 1.28 × 10), and it showed an age-dependent association with Bifidobacterium abundance. Other associations were suggestive (1.95 × 10 < P < 5 × 10) but enriched for taxa showing high heritability and for genes expressed in the intestine and brain. A phenome-wide association study and Mendelian randomization identified enrichment of microbiome trait loci in the metabolic, nutrition and environment domains and suggested the microbiome might have causal effects in ulcerative colitis and rheumatoid arthritis.
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http://dx.doi.org/10.1038/s41588-020-00763-1DOI Listing
February 2021

Genomic and drug target evaluation of 90 cardiovascular proteins in 30,931 individuals.

Nat Metab 2020 10 16;2(10):1135-1148. Epub 2020 Oct 16.

SCALLOP consortium.

Circulating proteins are vital in human health and disease and are frequently used as biomarkers for clinical decision-making or as targets for pharmacological intervention. Here, we map and replicate protein quantitative trait loci (pQTL) for 90 cardiovascular proteins in over 30,000 individuals, resulting in 451 pQTLs for 85 proteins. For each protein, we further perform pathway mapping to obtain trans-pQTL gene and regulatory designations. We substantiate these regulatory findings with orthogonal evidence for trans-pQTLs using mouse knockdown experiments (ABCA1 and TRIB1) and clinical trial results (chemokine receptors CCR2 and CCR5), with consistent regulation. Finally, we evaluate known drug targets, and suggest new target candidates or repositioning opportunities using Mendelian randomization. This identifies 11 proteins with causal evidence of involvement in human disease that have not previously been targeted, including EGF, IL-16, PAPPA, SPON1, F3, ADM, CASP-8, CHI3L1, CXCL16, GDF15 and MMP-12. Taken together, these findings demonstrate the utility of large-scale mapping of the genetics of the proteome and provide a resource for future precision studies of circulating proteins in human health.
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http://dx.doi.org/10.1038/s42255-020-00287-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7611474PMC
October 2020

Mendelian randomization while jointly modeling cis genetics identifies causal relationships between gene expression and lipids.

Nat Commun 2020 10 1;11(1):4930. Epub 2020 Oct 1.

University of Groningen, University Medical Centre Groningen, Department of Genetics, Antonius Deusinglaan 1, 9713, Groningen, AV, The Netherlands.

Inference of causality between gene expression and complex traits using Mendelian randomization (MR) is confounded by pleiotropy and linkage disequilibrium (LD) of gene-expression quantitative trait loci (eQTL). Here, we propose an MR method, MR-link, that accounts for unobserved pleiotropy and LD by leveraging information from individual-level data, even when only one eQTL variant is present. In simulations, MR-link shows false-positive rates close to expectation (median 0.05) and high power (up to 0.89), outperforming all other tested MR methods and coloc. Application of MR-link to low-density lipoprotein cholesterol (LDL-C) measurements in 12,449 individuals with expression and protein QTL summary statistics from blood and liver identifies 25 genes causally linked to LDL-C. These include the known SORT1 and ApoE genes as well as PVRL2, located in the APOE locus, for which a causal role in liver was not known. Our results showcase the strength of MR-link for transcriptome-wide causal inferences.
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http://dx.doi.org/10.1038/s41467-020-18716-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7530717PMC
October 2020

An epigenome-wide association study identifies multiple DNA methylation markers of exposure to endocrine disruptors.

Environ Int 2020 11 9;144:106016. Epub 2020 Sep 9.

Department of Epidemiology, University of Groningen, University Medical Center Groningen, 9713 GZ Groningen, the Netherlands; Department of Genetics, University of Groningen, University Medical Center Groningen, 9713 GZ Groningen, the Netherlands; Genomics Coordination Centre, Department of Genetics, University of Groningen, University Medical Center Groningen, 9713 GZ Groningen, the Netherlands. Electronic address:

Background: Exposure to environmental endocrine disrupting chemicals (EDCs) may play an important role in the epidemic of metabolic diseases. Epigenetic alterations may functionally link EDCs with gene expression and metabolic traits.

Objectives: We aimed to evaluate metabolic-related effects of the exposure to endocrine disruptors including five parabens, three bisphenols, and 13 metabolites of nine phthalates as measured in 24-hour urine on epigenome-wide DNA methylation.

Methods: A blood-based epigenome-wide association study was performed in 622 participants from the Lifelines DEEP cohort using Illumina Infinium HumanMethylation450 methylation data and EDC excretions in 24-hour urine. Out of the 21 EDCs, 13 compounds were detected in >75% of the samples and, together with bisphenol F, were included in these analyses. Furthermore, we explored the putative function of identified methylation markers and their correlations with metabolic traits.

Results: We found 20 differentially methylated cytosine-phosphate-guanines (CpGs) associated with 10 EDCs at suggestive p-value < 1 × 10, of which four, associated with MEHP and MEHHP, were genome-wide significant (Bonferroni-corrected p-value < 1.19 × 10). Nine out of 20 CpGs were significantly associated with at least one of the tested metabolic traits, such as fasting glucose, glycated hemoglobin, blood lipids, and/or blood pressure. 18 out of 20 EDC-associated CpGs were annotated to genes functionally related to metabolic syndrome, hypertension, obesity, type 2 diabetes, insulin resistance and glycemic traits.

Conclusions: The identified DNA methylation markers for exposure to the most common EDCs provide suggestive mechanism underlying the contributions of EDCs to metabolic health. Follow-up studies are needed to unravel the causality of EDC-induced methylation changes in metabolic alterations.
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http://dx.doi.org/10.1016/j.envint.2020.106016DOI Listing
November 2020

Integrating GWAS with bulk and single-cell RNA-sequencing reveals a role for LY86 in the anti-Candida host response.

PLoS Pathog 2020 04 6;16(4):e1008408. Epub 2020 Apr 6.

Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.

Candida bloodstream infection, i.e. candidemia, is the most frequently encountered life-threatening fungal infection worldwide, with mortality rates up to almost 50%. In the majority of candidemia cases, Candida albicans is responsible. Worryingly, a global increase in the number of patients who are susceptible to infection (e.g. immunocompromised patients), has led to a rise in the incidence of candidemia in the last few decades. Therefore, a better understanding of the anti-Candida host response is essential to overcome this poor prognosis and to lower disease incidence. Here, we integrated genome-wide association studies with bulk and single-cell transcriptomic analyses of immune cells stimulated with Candida albicans to further our understanding of the anti-Candida host response. We show that differential expression analysis upon Candida stimulation in single-cell expression data can reveal the important cell types involved in the host response against Candida. This confirmed the known major role of monocytes, but more interestingly, also uncovered an important role for NK cells. Moreover, combining the power of bulk RNA-seq with the high resolution of single-cell RNA-seq data led to the identification of 27 Candida-response QTLs and revealed the cell types potentially involved herein. Integration of these response QTLs with a GWAS on candidemia susceptibility uncovered a potential new role for LY86 in candidemia susceptibility. Finally, experimental follow-up confirmed that LY86 knockdown results in reduced monocyte migration towards the chemokine MCP-1, thereby implying that this reduced migration may underlie the increased susceptibility to candidemia. Altogether, our integrative systems genetics approach identifies previously unknown mechanisms underlying the immune response to Candida infection.
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http://dx.doi.org/10.1371/journal.ppat.1008408DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7173933PMC
April 2020

Genetic associations with radiological damage in rheumatoid arthritis: Meta-analysis of seven genome-wide association studies of 2,775 cases.

PLoS One 2019 9;14(10):e0223246. Epub 2019 Oct 9.

Primary Care Centre Versus Arthritis, Research Institute for Primary Care and Health Sciences, Primary Care Sciences, Keele University, Keele, United Kingdom.

Background: Previous studies of radiological damage in rheumatoid arthritis (RA) have used candidate-gene approaches, or evaluated single genome-wide association studies (GWAS). We undertook the first meta-analysis of GWAS of RA radiological damage to: (1) identify novel genetic loci for this trait; and (2) test previously validated variants.

Methods: Seven GWAS (2,775 RA cases, of a range of ancestries) were combined in a meta-analysis. Radiological damage was assessed using modified Larsen scores, Sharp van Der Heijde scores, and erosive status. Single nucleotide polymophsim (SNP) associations with radiological damage were tested at a single time-point using regression models. Primary analyses included age and disease duration as covariates. Secondary analyses also included rheumatoid factor (RF). Meta-analyses were undertaken in trans-ethnic and European-only cases.

Results: In the trans-ethnic primary meta-analysis, one SNP (rs112112734) in close proximity to HLA-DRB1, and strong linkage disequilibrium with the shared-epitope, attained genome-wide significance (P = 4.2x10-8). In the secondary analysis (adjusting for RF) the association was less significant (P = 1.7x10-6). In both trans-ethnic primary and secondary meta-analyses 14 regions contained SNPs with associations reaching P<5x10-6; in the European primary and secondary analyses 13 and 10 regions contained SNPs reaching P<5x10-6, respectively. Of the previously validated SNPs for radiological progression, only rs660895 (tagging HLA-DRB1*04:01) attained significance (P = 1.6x10-5) and had a consistent direction of effect across GWAS.

Conclusions: Our meta-analysis confirms the known association between the HLA-DRB1 shared epitope and RA radiological damage. The lack of replication of previously validated non-HLA markers highlights a requirement for further research to deliver clinically-useful prognostic genetic markers.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0223246PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6785117PMC
March 2020

IMPACT: Genomic Annotation of Cell-State-Specific Regulatory Elements Inferred from the Epigenome of Bound Transcription Factors.

Am J Hum Genet 2019 05 18;104(5):879-895. Epub 2019 Apr 18.

Center for Data Sciences, Harvard Medical School, Boston, MA 02115, USA; Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA; Graduate School of Arts and Sciences, Harvard University, Cambridge, MA 02138, USA; Arthritis Research UK Centre for Genetics and Genomics, Centre for Musculoskeletal Research, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK. Electronic address:

Despite significant progress in annotating the genome with experimental methods, much of the regulatory noncoding genome remains poorly defined. Here we assert that regulatory elements may be characterized by leveraging local epigenomic signatures where specific transcription factors (TFs) are bound. To link these two features, we introduce IMPACT, a genome annotation strategy that identifies regulatory elements defined by cell-state-specific TF binding profiles, learned from 515 chromatin and sequence annotations. We validate IMPACT using multiple compelling applications. First, IMPACT distinguishes between bound and unbound TF motif sites with high accuracy (average AUPRC 0.81, SE 0.07; across 8 tested TFs) and outperforms state-of-the-art TF binding prediction methods, MocapG, MocapS, and Virtual ChIP-seq. Second, in eight tested cell types, RNA polymerase II IMPACT annotations capture more cis-eQTL variation than sequence-based annotations, such as promoters and TSS windows (25% average increase in enrichment). Third, integration with rheumatoid arthritis (RA) summary statistics from European (N = 38,242) and East Asian (N = 22,515) populations revealed that the top 5% of CD4 Treg IMPACT regulatory elements capture 85.7% of RA h2, the most comprehensive explanation for RA h2 to date. In comparison, the average RA h2 captured by compared CD4 T histone marks is 42.3% and by CD4 T specifically expressed gene sets is 36.4%. Lastly, we find that IMPACT may be used in many different cell types to identify complex trait associated regulatory elements.
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http://dx.doi.org/10.1016/j.ajhg.2019.03.012DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6506796PMC
May 2019

An integrative approach for building personalized gene regulatory networks for precision medicine.

Genome Med 2018 12 19;10(1):96. Epub 2018 Dec 19.

Department of Genetics, 5th floor ERIBA building, Antonius Deusinglaan 1, 9713AV Groningen, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.

Only a small fraction of patients respond to the drug prescribed to treat their disease, which means that most are at risk of unnecessary exposure to side effects through ineffective drugs. This inter-individual variation in drug response is driven by differences in gene interactions caused by each patient's genetic background, environmental exposures, and the proportions of specific cell types involved in disease. These gene interactions can now be captured by building gene regulatory networks, by taking advantage of RNA velocity (the time derivative of the gene expression state), the ability to study hundreds of thousands of cells simultaneously, and the falling price of single-cell sequencing. Here, we propose an integrative approach that leverages these recent advances in single-cell data with the sensitivity of bulk data to enable the reconstruction of personalized, cell-type- and context-specific gene regulatory networks. We expect this approach will allow the prioritization of key driver genes for specific diseases and will provide knowledge that opens new avenues towards improved personalized healthcare.
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http://dx.doi.org/10.1186/s13073-018-0608-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6299585PMC
December 2018

Discovering in vivo cytokine-eQTL interactions from a lupus clinical trial.

Genome Biol 2018 10 19;19(1):168. Epub 2018 Oct 19.

Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, 02115, USA.

Background: Cytokines are critical to human disease and are attractive therapeutic targets given their widespread influence on gene regulation and transcription. Defining the downstream regulatory mechanisms influenced by cytokines is central to defining drug and disease mechanisms. One promising strategy is to use interactions between expression quantitative trait loci (eQTLs) and cytokine levels to define target genes and mechanisms.

Results: In a clinical trial for anti-IL-6 in patients with systemic lupus erythematosus, we measure interferon (IFN) status, anti-IL-6 drug exposure, and whole blood genome-wide gene expression at three time points. We show that repeat transcriptomic measurements increases the number of cis eQTLs identified compared to using a single time point. We observe a statistically significant enrichment of in vivo eQTL interactions with IFN status and anti-IL-6 drug exposure and find many novel interactions that have not been previously described. Finally, we find transcription factor binding motifs interrupted by eQTL interaction SNPs, which point to key regulatory mediators of these environmental stimuli and therefore potential therapeutic targets for autoimmune diseases. In particular, genes with IFN interactions are enriched for ISRE binding site motifs, while those with anti-IL-6 interactions are enriched for IRF4 motifs.

Conclusions: This study highlights the potential to exploit clinical trial data to discover in vivo eQTL interactions with therapeutically relevant environmental variables.
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http://dx.doi.org/10.1186/s13059-018-1560-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6195724PMC
October 2018

Fine-mapping and functional studies highlight potential causal variants for rheumatoid arthritis and type 1 diabetes.

Nat Genet 2018 10 17;50(10):1366-1374. Epub 2018 Sep 17.

Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.

To define potentially causal variants for autoimmune disease, we fine-mapped 76 rheumatoid arthritis (11,475 cases, 15,870 controls) and type 1 diabetes loci (9,334 cases, 11,111 controls). After sequencing 799 1-kilobase regulatory (H3K4me3) regions within these loci in 568 individuals, we observed accurate imputation for 89% of common variants. We defined credible sets of ≤5 causal variants at 5 rheumatoid arthritis and 10 type 1 diabetes loci. We identified potentially causal missense variants at DNASE1L3, PTPN22, SH2B3, and TYK2, and noncoding variants at MEG3, CD28-CTLA4, and IL2RA. We also identified potential candidate causal variants at SIRPG and TNFAIP3. Using functional assays, we confirmed allele-specific protein binding and differential enhancer activity for three variants: the CD28-CTLA4 rs117701653 SNP, MEG3 rs34552516 indel, and TNFAIP3 rs35926684 indel.
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http://dx.doi.org/10.1038/s41588-018-0216-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6364548PMC
October 2018

PR interval genome-wide association meta-analysis identifies 50 loci associated with atrial and atrioventricular electrical activity.

Nat Commun 2018 07 25;9(1):2904. Epub 2018 Jul 25.

Department of Biomedical Engineering, Johns Hopkins University, Baltimore, 21218, MD, USA.

Electrocardiographic PR interval measures atrio-ventricular depolarization and conduction, and abnormal PR interval is a risk factor for atrial fibrillation and heart block. Our genome-wide association study of over 92,000 European-descent individuals identifies 44 PR interval loci (34 novel). Examination of these loci reveals known and previously not-yet-reported biological processes involved in cardiac atrial electrical activity. Genes in these loci are over-represented in cardiac disease processes including heart block and atrial fibrillation. Variants in over half of the 44 loci were associated with atrial or blood transcript expression levels, or were in high linkage disequilibrium with missense variants. Six additional loci were identified either by meta-analysis of ~105,000 African and European-descent individuals and/or by pleiotropic analyses combining PR interval with heart rate, QRS interval, and atrial fibrillation. These findings implicate developmental pathways, and identify transcription factors, ion-channel genes, and cell-junction/cell-signaling proteins in atrio-ventricular conduction, identifying potential targets for drug development.
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http://dx.doi.org/10.1038/s41467-018-04766-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6060178PMC
July 2018

High-throughput identification of noncoding functional SNPs via type IIS enzyme restriction.

Nat Genet 2018 08 16;50(8):1180-1188. Epub 2018 Jul 16.

Division of Rheumatology, Immunology and Allergy, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.

Genome-wide association studies (GWAS) have identified many disease-associated noncoding variants, but cannot distinguish functional single-nucleotide polymorphisms (fSNPs) from others that reside incidentally within risk loci. To address this challenge, we developed an unbiased high-throughput screen that employs type IIS enzymatic restriction to identify fSNPs that allelically modulate the binding of regulatory proteins. We coupled this approach, termed SNP-seq, with flanking restriction enhanced pulldown (FREP) to identify regulation of CD40 by three disease-associated fSNPs via four regulatory proteins, RBPJ, RSRC2 and FUBP-1/TRAP150. Applying this approach across 27 loci associated with juvenile idiopathic arthritis, we identified 148 candidate fSNPs, including two that regulate STAT4 via the regulatory proteins SATB2 and H1.2. Together, these findings establish the utility of tandem SNP-seq/FREP to bridge the gap between GWAS and disease mechanism.
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http://dx.doi.org/10.1038/s41588-018-0159-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6072570PMC
August 2018

Pathogenic implications for autoimmune mechanisms derived by comparative eQTL analysis of CD4+ versus CD8+ T cells.

PLoS Genet 2017 Mar 1;13(3):e1006643. Epub 2017 Mar 1.

Estonian Genome Center, University of Tartu, Tartu, Estonia.

Inappropriate activation or inadequate regulation of CD4+ and CD8+ T cells may contribute to the initiation and progression of multiple autoimmune and inflammatory diseases. Studies on disease-associated genetic polymorphisms have highlighted the importance of biological context for many regulatory variants, which is particularly relevant in understanding the genetic regulation of the immune system and its cellular phenotypes. Here we show cell type-specific regulation of transcript levels of genes associated with several autoimmune diseases in CD4+ and CD8+ T cells including a trans-acting regulatory locus at chr12q13.2 containing the rs1131017 SNP in the RPS26 gene. Most remarkably, we identify a common missense variant in IL27, associated with type 1 diabetes that results in decreased functional activity of the protein and reduced expression levels of downstream IRF1 and STAT1 in CD4+ T cells only. Altogether, our results indicate that eQTL mapping in purified T cells provides novel functional insights into polymorphisms and pathways associated with autoimmune diseases.
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http://dx.doi.org/10.1371/journal.pgen.1006643DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5352142PMC
March 2017

reGenotyper: Detecting mislabeled samples in genetic data.

PLoS One 2017 13;12(2):e0171324. Epub 2017 Feb 13.

Groningen Bioinformatics Centre, University of Groningen, Groningen, The Netherlands.

In high-throughput molecular profiling studies, genotype labels can be wrongly assigned at various experimental steps; the resulting mislabeled samples seriously reduce the power to detect the genetic basis of phenotypic variation. We have developed an approach to detect potential mislabeling, recover the "ideal" genotype and identify "best-matched" labels for mislabeled samples. On average, we identified 4% of samples as mislabeled in eight published datasets, highlighting the necessity of applying a "data cleaning" step before standard data analysis.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0171324PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5305221PMC
August 2017

Identification of context-dependent expression quantitative trait loci in whole blood.

Nat Genet 2017 01 5;49(1):139-145. Epub 2016 Dec 5.

Molecular Epidemiology Section, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, the Netherlands.

Genetic risk factors often localize to noncoding regions of the genome with unknown effects on disease etiology. Expression quantitative trait loci (eQTLs) help to explain the regulatory mechanisms underlying these genetic associations. Knowledge of the context that determines the nature and strength of eQTLs may help identify cell types relevant to pathophysiology and the regulatory networks underlying disease. Here we generated peripheral blood RNA-seq data from 2,116 unrelated individuals and systematically identified context-dependent eQTLs using a hypothesis-free strategy that does not require previous knowledge of the identity of the modifiers. Of the 23,060 significant cis-regulated genes (false discovery rate (FDR) ≤ 0.05), 2,743 (12%) showed context-dependent eQTL effects. The majority of these effects were influenced by cell type composition. A set of 145 cis-eQTLs depended on type I interferon signaling. Others were modulated by specific transcription factors binding to the eQTL SNPs.
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http://dx.doi.org/10.1038/ng.3737DOI Listing
January 2017

52 Genetic Loci Influencing Myocardial Mass.

J Am Coll Cardiol 2016 09;68(13):1435-1448

Department of Medical Genetics, University Medical Center Utrecht, Utrecht, the Netherlands; Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht, the Netherlands.

Background: Myocardial mass is a key determinant of cardiac muscle function and hypertrophy. Myocardial depolarization leading to cardiac muscle contraction is reflected by the amplitude and duration of the QRS complex on the electrocardiogram (ECG). Abnormal QRS amplitude or duration reflect changes in myocardial mass and conduction, and are associated with increased risk of heart failure and death.

Objectives: This meta-analysis sought to gain insights into the genetic determinants of myocardial mass.

Methods: We carried out a genome-wide association meta-analysis of 4 QRS traits in up to 73,518 individuals of European ancestry, followed by extensive biological and functional assessment.

Results: We identified 52 genomic loci, of which 32 are novel, that are reliably associated with 1 or more QRS phenotypes at p < 1 × 10(-8). These loci are enriched in regions of open chromatin, histone modifications, and transcription factor binding, suggesting that they represent regions of the genome that are actively transcribed in the human heart. Pathway analyses provided evidence that these loci play a role in cardiac hypertrophy. We further highlighted 67 candidate genes at the identified loci that are preferentially expressed in cardiac tissue and associated with cardiac abnormalities in Drosophila melanogaster and Mus musculus. We validated the regulatory function of a novel variant in the SCN5A/SCN10A locus in vitro and in vivo.

Conclusions: Taken together, our findings provide new insights into genes and biological pathways controlling myocardial mass and may help identify novel therapeutic targets.
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http://dx.doi.org/10.1016/j.jacc.2016.07.729DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5478167PMC
September 2016

The genetics of blood pressure regulation and its target organs from association studies in 342,415 individuals.

Nat Genet 2016 10 12;48(10):1171-1184. Epub 2016 Sep 12.

Children's Hospital Oakland Research Institute, Oakland, CA 94609, USA.

To dissect the genetic architecture of blood pressure and assess effects on target organ damage, we analyzed 128,272 SNPs from targeted and genome-wide arrays in 201,529 individuals of European ancestry, and genotypes from an additional 140,886 individuals were used for validation. We identified 66 blood pressure-associated loci, of which 17 were new; 15 harbored multiple distinct association signals. The 66 index SNPs were enriched for cis-regulatory elements, particularly in vascular endothelial cells, consistent with a primary role in blood pressure control through modulation of vascular tone across multiple tissues. The 66 index SNPs combined in a risk score showed comparable effects in 64,421 individuals of non-European descent. The 66-SNP blood pressure risk score was significantly associated with target organ damage in multiple tissues but with minor effects in the kidney. Our findings expand current knowledge of blood pressure-related pathways and highlight tissues beyond the classical renal system in blood pressure regulation.
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http://dx.doi.org/10.1038/ng.3667DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5042863PMC
October 2016

Genome-wide association study identifies 74 loci associated with educational attainment.

Nature 2016 05 11;533(7604):539-42. Epub 2016 May 11.

Department of Neurology, General Hospital and Medical University Graz, Graz 8036, Austria.

Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals. Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends our earlier discovery sample of 101,069 individuals to 293,723 individuals, and a replication study in an independent sample of 111,349 individuals from the UK Biobank. We identify 74 genome-wide significant loci associated with the number of years of schooling completed. Single-nucleotide polymorphisms associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioural phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because educational attainment is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric diseases.
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http://dx.doi.org/10.1038/nature17671DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4883595PMC
May 2016

Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses.

Nat Genet 2016 06 18;48(6):624-33. Epub 2016 Apr 18.

Max Planck Institute for Human Development, Berlin, Germany.

Very few genetic variants have been associated with depression and neuroticism, likely because of limitations on sample size in previous studies. Subjective well-being, a phenotype that is genetically correlated with both of these traits, has not yet been studied with genome-wide data. We conducted genome-wide association studies of three phenotypes: subjective well-being (n = 298,420), depressive symptoms (n = 161,460), and neuroticism (n = 170,911). We identify 3 variants associated with subjective well-being, 2 variants associated with depressive symptoms, and 11 variants associated with neuroticism, including 2 inversion polymorphisms. The two loci associated with depressive symptoms replicate in an independent depression sample. Joint analyses that exploit the high genetic correlations between the phenotypes (|ρ^| ≈ 0.8) strengthen the overall credibility of the findings and allow us to identify additional variants. Across our phenotypes, loci regulating expression in central nervous system and adrenal or pancreas tissues are strongly enriched for association.
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http://dx.doi.org/10.1038/ng.3552DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4884152PMC
June 2016

Analysis of five chronic inflammatory diseases identifies 27 new associations and highlights disease-specific patterns at shared loci.

Nat Genet 2016 05 14;48(5):510-8. Epub 2016 Mar 14.

Institute of Human Genetics, University of Bonn, Bonn, Germany.

We simultaneously investigated the genetic landscape of ankylosing spondylitis, Crohn's disease, psoriasis, primary sclerosing cholangitis and ulcerative colitis to investigate pleiotropy and the relationship between these clinically related diseases. Using high-density genotype data from more than 86,000 individuals of European ancestry, we identified 244 independent multidisease signals, including 27 new genome-wide significant susceptibility loci and 3 unreported shared risk loci. Complex pleiotropy was supported when contrasting multidisease signals with expression data sets from human, rat and mouse together with epigenetic and expressed enhancer profiles. The comorbidities among the five immune diseases were best explained by biological pleiotropy rather than heterogeneity (a subgroup of cases genetically identical to those with another disease, possibly owing to diagnostic misclassification, molecular subtypes or excessive comorbidity). In particular, the strong comorbidity between primary sclerosing cholangitis and inflammatory bowel disease is likely the result of a unique disease, which is genetically distinct from classical inflammatory bowel disease phenotypes.
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http://dx.doi.org/10.1038/ng.3528DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4848113PMC
May 2016

New loci for body fat percentage reveal link between adiposity and cardiometabolic disease risk.

Nat Commun 2016 Feb 1;7:10495. Epub 2016 Feb 1.

Department of Twin Research and Genetic Epidemiology, King's College London, London SE1 7EH, UK.

To increase our understanding of the genetic basis of adiposity and its links to cardiometabolic disease risk, we conducted a genome-wide association meta-analysis of body fat percentage (BF%) in up to 100,716 individuals. Twelve loci reached genome-wide significance (P<5 × 10(-8)), of which eight were previously associated with increased overall adiposity (BMI, BF%) and four (in or near COBLL1/GRB14, IGF2BP1, PLA2G6, CRTC1) were novel associations with BF%. Seven loci showed a larger effect on BF% than on BMI, suggestive of a primary association with adiposity, while five loci showed larger effects on BMI than on BF%, suggesting association with both fat and lean mass. In particular, the loci more strongly associated with BF% showed distinct cross-phenotype association signatures with a range of cardiometabolic traits revealing new insights in the link between adiposity and disease risk.
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http://dx.doi.org/10.1038/ncomms10495DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4740398PMC
February 2016

The transcriptional landscape of age in human peripheral blood.

Nat Commun 2015 Oct 22;6:8570. Epub 2015 Oct 22.

Department of Internal Medicine, Erasmus Medical Centre Rotterdam, Rotterdam 3000CA, The Netherlands.

Disease incidences increase with age, but the molecular characteristics of ageing that lead to increased disease susceptibility remain inadequately understood. Here we perform a whole-blood gene expression meta-analysis in 14,983 individuals of European ancestry (including replication) and identify 1,497 genes that are differentially expressed with chronological age. The age-associated genes do not harbor more age-associated CpG-methylation sites than other genes, but are instead enriched for the presence of potentially functional CpG-methylation sites in enhancer and insulator regions that associate with both chronological age and gene expression levels. We further used the gene expression profiles to calculate the 'transcriptomic age' of an individual, and show that differences between transcriptomic age and chronological age are associated with biological features linked to ageing, such as blood pressure, cholesterol levels, fasting glucose, and body mass index. The transcriptomic prediction model adds biological relevance and complements existing epigenetic prediction models, and can be used by others to calculate transcriptomic age in external cohorts.
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http://dx.doi.org/10.1038/ncomms9570DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4639797PMC
October 2015
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