Publications by authors named "Nick Shrine"

37 Publications

Variants associated with expression have sex-differential effects on lung function.

Wellcome Open Res 2020 24;5:111. Epub 2021 May 24.

Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, EH4 2XU, UK.

Lung function is highly heritable and differs between the sexes throughout life. However, little is known about sex-differential genetic effects on lung function. We aimed to conduct the first genome-wide genotype-by-sex interaction study on lung function to identify genetic effects that differ between males and females. We tested for interactions between 7,745,864 variants and sex on spirometry-based measures of lung function in UK Biobank (N=303,612), and sought replication in 75,696 independent individuals from the SpiroMeta consortium. Five independent single-nucleotide polymorphisms (SNPs) showed genome-wide significant (P<5x10 ) interactions with sex on lung function, and 21 showed suggestive interactions (P<1x10 ). The strongest signal, from rs7697189 (chr4:145436894) on forced expiratory volume in 1 second (FEV ) (P=3.15x10 ), was replicated (P=0.016) in SpiroMeta. The C allele increased FEV more in males (untransformed FEV β=0.028 [SE 0.0022] litres) than females (β=0.009 [SE 0.0014] litres), and this effect was not accounted for by differential effects on height, smoking or pubertal age. rs7697189 resides upstream of the hedgehog-interacting protein ( ) gene and was previously associated with lung function and lung expression. We found expression was significantly different between the sexes (P=6.90x10 ), but we could not detect sex differential effects of rs7697189 on expression. We identified a novel genotype-by-sex interaction at a putative enhancer region upstream of the gene. Establishing the mechanism by which SNPs have different effects on lung function in males and females will be important for our understanding of lung health and diseases in both sexes.
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http://dx.doi.org/10.12688/wellcomeopenres.15846.2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7938335.2PMC
May 2021

Familial hypereosinophilia associated with eosinophilic gastrointestinal symptoms in individuals with a missense mutation in CKLF-like MARVEL transmembrane domain containing 3.

Clin Exp Allergy 2021 May 28. Epub 2021 May 28.

Institute for Lung Health, Department of Respiratory Sciences, Leicester Respiratory Biomedical Research Centre, University of Leicester and National Institute for Health Research, Glenfield Hospital, University Hospitals of Leicester NHS Trust, Leicester, UK.

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http://dx.doi.org/10.1111/cea.13957DOI Listing
May 2021

Pleiotropic associations of heterozygosity for the Z allele in the UK Biobank.

ERJ Open Res 2021 Apr 10;7(2). Epub 2021 May 10.

Division of Respiratory Medicine, University of Nottingham, and NIHR Nottingham BRC, NUH NHS Trust, Nottingham, UK.

Homozygosity for the Z allele causes α-antitrypsin deficiency, a rare condition that can cause lung and liver disease. However, the effects of Z allele heterozygosity on nonrespiratory phenotypes, and on lung function in the general population, remain unclear. We conducted a large, population-based study to determine Z allele effects on >2400 phenotypes in the UK Biobank (N=303 353). Z allele heterozygosity was strongly associated with increased height (β=1.02 cm, p=3.91×10), and with other nonrespiratory phenotypes including increased risk of gall bladder disease, reduced risk of heart disease and lower blood pressure, reduced risk of osteoarthritis and reduced bone mineral density, increased risk of headache and enlarged prostate, as well as with blood biomarkers of liver function. Heterozygosity was associated with higher height-adjusted forced expiratory volume in 1 s (FEV) (β=19.36 mL, p=9.21×10) and FEV/forced vital capacity (β=0.0031, p=1.22×10) in nonsmokers, whereas in smokers, this protective effect was abolished. Furthermore, we show for the first time that sex modifies the association of the Z allele on lung function. We conclude that Z allele heterozygosity and homozygosity exhibit opposing effects on lung function in the UK population, and that these associations are modified by smoking and sex. In exploratory analyses, heterozygosity for the Z allele also showed pleiotropic associations with nonrespiratory health-related traits and disease risk.
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http://dx.doi.org/10.1183/23120541.00049-2021DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8107350PMC
April 2021

Genetic and clinical characteristics of treatment-resistant depression using primary care records in two UK cohorts.

Mol Psychiatry 2021 Mar 22. Epub 2021 Mar 22.

Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.

Treatment-resistant depression (TRD) is a major contributor to the disability caused by major depressive disorder (MDD). Primary care electronic health records provide an easily accessible approach to investigate TRD clinical and genetic characteristics. MDD defined from primary care records in UK Biobank (UKB) and EXCEED studies was compared with other measures of depression and tested for association with MDD polygenic risk score (PRS). Using prescribing records, TRD was defined from at least two switches between antidepressant drugs, each prescribed for at least 6 weeks. Clinical-demographic characteristics, SNP-based heritability (h) and genetic overlap with psychiatric and non-psychiatric traits were compared in TRD and non-TRD MDD cases. In 230,096 and 8926 UKB and EXCEED participants with primary care data, respectively, the prevalence of MDD was 8.7% and 14.2%, of which 13.2% and 13.5% was TRD, respectively. In both cohorts, MDD defined from primary care records was strongly associated with MDD PRS, and in UKB it showed overlap of 71-88% with other MDD definitions. In UKB, TRD vs healthy controls and non-TRD vs healthy controls h was comparable (0.25 [SE = 0.04] and 0.19 [SE = 0.02], respectively). TRD vs non-TRD was positively associated with the PRS of attention deficit hyperactivity disorder, with lower socio-economic status, obesity, higher neuroticism and other unfavourable clinical characteristics. This study demonstrated that MDD and TRD can be reliably defined using primary care records and provides the first large scale population assessment of the genetic, clinical and demographic characteristics of TRD.
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http://dx.doi.org/10.1038/s41380-021-01062-9DOI Listing
March 2021

Genome-Wide Gene-by-Smoking Interaction Study of Chronic Obstructive Pulmonary Disease.

Am J Epidemiol 2021 05;190(5):875-885

Risk of chronic obstructive pulmonary disease (COPD) is determined by both cigarette smoking and genetic susceptibility, but little is known about gene-by-smoking interactions. We performed a genome-wide association analysis of 179,689 controls and 21,077 COPD cases from UK Biobank subjects of European ancestry recruited from 2006 to 2010, considering genetic main effects and gene-by-smoking interaction effects simultaneously (2-degrees-of-freedom (df) test) as well as interaction effects alone (1-df interaction test). We sought to replicate significant results in COPDGene (United States, 2008-2010) and SpiroMeta Consortium (multiple countries, 1947-2015) data. We considered 2 smoking variables: 1) ever/never and 2) current/noncurrent. In the 1-df test, we identified 1 genome-wide significant locus on 15q25.1 (cholinergic receptor nicotinic β4 subunit, or CHRNB4) for ever- and current smoking and identified PI*Z allele (rs28929474) of serpin family A member 1 (SERPINA1) for ever-smoking and 3q26.2 (MDS1 and EVI1 complex locus, or MECOM) for current smoking in an analysis of previously reported COPD loci. In the 2-df test, most of the significant signals were also significant for genetic marginal effects, aside from 16q22.1 (sphingomyelin phosphodiesterase 3, or SMPD3) and 19q13.2 (Egl-9 family hypoxia inducible factor 2, or EGLN2). The significant effects at 15q25.1 and 19q13.2 loci, both previously described in prior genome-wide association studies of COPD or smoking, were replicated in COPDGene and SpiroMeta. We identified interaction effects at previously reported COPD loci; however, we failed to identify novel susceptibility loci.
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http://dx.doi.org/10.1093/aje/kwaa227DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8096488PMC
May 2021

Whole genome sequence analysis of pulmonary function and COPD in 19,996 multi-ethnic participants.

Nat Commun 2020 10 14;11(1):5182. Epub 2020 Oct 14.

The Institute for Translational Genomics and Population Sciences, The Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA.

Chronic obstructive pulmonary disease (COPD), diagnosed by reduced lung function, is a leading cause of morbidity and mortality. We performed whole genome sequence (WGS) analysis of lung function and COPD in a multi-ethnic sample of 11,497 participants from population- and family-based studies, and 8499 individuals from COPD-enriched studies in the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program. We identify at genome-wide significance 10 known GWAS loci and 22 distinct, previously unreported loci, including two common variant signals from stratified analysis of African Americans. Four novel common variants within the regions of PIAS1, RGN (two variants) and FTO show evidence of replication in the UK Biobank (European ancestry n ~ 320,000), while colocalization analyses leveraging multi-omic data from GTEx and TOPMed identify potential molecular mechanisms underlying four of the 22 novel loci. Our study demonstrates the value of performing WGS analyses and multi-omic follow-up in cohorts of diverse ancestry.
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http://dx.doi.org/10.1038/s41467-020-18334-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7598941PMC
October 2020

Chronic obstructive pulmonary disease and related phenotypes: polygenic risk scores in population-based and case-control cohorts.

Lancet Respir Med 2020 07;8(7):696-708

Division of Pulmonary, Critical Care, and Sleep Medicine, National Jewish Health, Denver, CO, USA.

Background: Genetic factors influence chronic obstructive pulmonary disease (COPD) risk, but the individual variants that have been identified have small effects. We hypothesised that a polygenic risk score using additional variants would predict COPD and associated phenotypes.

Methods: We constructed a polygenic risk score using a genome-wide association study of lung function (FEV and FEV/forced vital capacity [FVC]) from the UK Biobank and SpiroMeta. We tested this polygenic risk score in nine cohorts of multiple ethnicities for an association with moderate-to-severe COPD (defined as FEV/FVC <0·7 and FEV <80% of predicted). Associations were tested using logistic regression models, adjusting for age, sex, height, smoking pack-years, and principal components of genetic ancestry. We assessed predictive performance of models by area under the curve. In a subset of studies, we also studied quantitative and qualitative CT imaging phenotypes that reflect parenchymal and airway pathology, and patterns of reduced lung growth.

Findings: The polygenic risk score was associated with COPD in European (odds ratio [OR] per SD 1·81 [95% CI 1·74-1·88] and non-European (1·42 [1·34-1·51]) populations. Compared with the first decile, the tenth decile of the polygenic risk score was associated with COPD, with an OR of 7·99 (6·56-9·72) in European ancestry and 4·83 (3·45-6·77) in non-European ancestry cohorts. The polygenic risk score was superior to previously described genetic risk scores and, when combined with clinical risk factors (ie, age, sex, and smoking pack-years), showed improved prediction for COPD compared with a model comprising clinical risk factors alone (AUC 0·80 [0·79-0·81] vs 0·76 [0·75-0·76]). The polygenic risk score was associated with CT imaging phenotypes, including wall area percent, quantitative and qualitative measures of emphysema, local histogram emphysema patterns, and destructive emphysema subtypes. The polygenic risk score was associated with a reduced lung growth pattern.

Interpretation: A risk score comprised of genetic variants can identify a small subset of individuals at markedly increased risk for moderate-to-severe COPD, emphysema subtypes associated with cigarette smoking, and patterns of reduced lung growth.

Funding: US National Institutes of Health, Wellcome Trust.
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http://dx.doi.org/10.1016/S2213-2600(20)30101-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7429152PMC
July 2020

Phenotypic and functional translation of IL33 genetics in asthma.

J Allergy Clin Immunol 2021 01 19;147(1):144-157. Epub 2020 May 19.

Department of Health Sciences, University of Leicester, Leicester, United Kingdom; National Institute for Health Research Leicester Respiratory Biomedical Research Centre, Leicester, United Kingdom.

Background: Asthma is a complex disease with multiple phenotypes that may differ in disease pathobiology and treatment response. IL33 single nucleotide polymorphisms (SNPs) have been reproducibly associated with asthma. IL33 levels are elevated in sputum and bronchial biopsies of patients with asthma. The functional consequences of IL33 asthma SNPs remain unknown.

Objective: This study sought to determine whether IL33 SNPs associate with asthma-related phenotypes and with IL33 expression in lung or bronchial epithelium. This study investigated the effect of increased IL33 expression on human bronchial epithelial cell (HBEC) function.

Methods: Association between IL33 SNPs (Chr9: 5,815,786-6,657,983) and asthma phenotypes (Lifelines/DAG [Dutch Asthma GWAS]/GASP [Genetics of Asthma Severity & Phenotypes] cohorts) and between SNPs and expression (lung tissue, bronchial brushes, HBECs) was done using regression modeling. Lentiviral overexpression was used to study IL33 effects on HBECs.

Results: We found that 161 SNPs spanning the IL33 region associated with 1 or more asthma phenotypes after correction for multiple testing. We report a main independent signal tagged by rs992969 associating with blood eosinophil levels, asthma, and eosinophilic asthma. A second, independent signal tagged by rs4008366 presented modest association with eosinophilic asthma. Neither signal associated with FEV, FEV/forced vital capacity, atopy, and age of asthma onset. The 2 IL33 signals are expression quantitative loci in bronchial brushes and cultured HBECs, but not in lung tissue. IL33 overexpression in vitro resulted in reduced viability and reactive oxygen species-capturing of HBECs, without influencing epithelial cell count, metabolic activity, or barrier function.

Conclusions: We identify IL33 as an epithelial susceptibility gene for eosinophilia and asthma, provide mechanistic insight, and implicate targeting of the IL33 pathway specifically in eosinophilic asthma.
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http://dx.doi.org/10.1016/j.jaci.2020.04.051DOI Listing
January 2021

Phenotypic and functional translation of IL1RL1 locus polymorphisms in lung tissue and asthmatic airway epithelium.

JCI Insight 2020 04 23;5(8). Epub 2020 Apr 23.

Department of Human Development and.

The IL1RL1 (ST2) gene locus is robustly associated with asthma; however, the contribution of single nucleotide polymorphisms (SNPs) in this locus to specific asthma subtypes and the functional mechanisms underlying these associations remain to be defined. We tested for association between IL1RL1 region SNPs and characteristics of asthma as defined by clinical and immunological measures and addressed functional effects of these genetic variants in lung tissue and airway epithelium. Utilizing 4 independent cohorts (Lifelines, Dutch Asthma GWAS [DAG], Genetics of Asthma Severity and Phenotypes [GASP], and Manchester Asthma and Allergy Study [MAAS]) and resequencing data, we identified 3 key signals associated with asthma features. Investigations in lung tissue and primary bronchial epithelial cells identified context-dependent relationships between the signals and IL1RL1 mRNA and soluble protein expression. This was also observed for asthma-associated IL1RL1 nonsynonymous coding TIR domain SNPs. Bronchial epithelial cell cultures from asthma patients, exposed to exacerbation-relevant stimulations, revealed modulatory effects for all 4 signals on IL1RL1 mRNA and/or protein expression, suggesting SNP-environment interactions. The IL1RL1 TIR signaling domain haplotype affected IL-33-driven NF-κB signaling, while not interfering with TLR signaling. In summary, we identify that IL1RL1 genetic signals potentially contribute to severe and eosinophilic phenotypes in asthma, as well as provide initial mechanistic insight, including genetic regulation of IL1RL1 isoform expression and receptor signaling.
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http://dx.doi.org/10.1172/jci.insight.132446DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7205441PMC
April 2020

Genetic landscape of chronic obstructive pulmonary disease identifies heterogeneous cell-type and phenotype associations.

Nat Genet 2019 03 25;51(3):494-505. Epub 2019 Feb 25.

Department of Internal Medicine and Environmental Health Center, School of Medicine, Kangwon National University, Chuncheon, South Korea.

Chronic obstructive pulmonary disease (COPD) is the leading cause of respiratory mortality worldwide. Genetic risk loci provide new insights into disease pathogenesis. We performed a genome-wide association study in 35,735 cases and 222,076 controls from the UK Biobank and additional studies from the International COPD Genetics Consortium. We identified 82 loci associated with P < 5 × 10; 47 of these were previously described in association with either COPD or population-based measures of lung function. Of the remaining 35 new loci, 13 were associated with lung function in 79,055 individuals from the SpiroMeta consortium. Using gene expression and regulation data, we identified functional enrichment of COPD risk loci in lung tissue, smooth muscle, and several lung cell types. We found 14 COPD loci shared with either asthma or pulmonary fibrosis. COPD genetic risk loci clustered into groups based on associations with quantitative imaging features and comorbidities. Our analyses provide further support for the genetic susceptibility and heterogeneity of COPD.
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http://dx.doi.org/10.1038/s41588-018-0342-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6546635PMC
March 2019

New genetic signals for lung function highlight pathways and chronic obstructive pulmonary disease associations across multiple ancestries.

Nat Genet 2019 03 25;51(3):481-493. Epub 2019 Feb 25.

Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK.

Reduced lung function predicts mortality and is key to the diagnosis of chronic obstructive pulmonary disease (COPD). In a genome-wide association study in 400,102 individuals of European ancestry, we define 279 lung function signals, 139 of which are new. In combination, these variants strongly predict COPD in independent populations. Furthermore, the combined effect of these variants showed generalizability across smokers and never smokers, and across ancestral groups. We highlight biological pathways, known and potential drug targets for COPD and, in phenome-wide association studies, autoimmune-related and other pleiotropic effects of lung function-associated variants. This new genetic evidence has potential to improve future preventive and therapeutic strategies for COPD.
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http://dx.doi.org/10.1038/s41588-018-0321-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6397078PMC
March 2019

Meta-analysis of up to 622,409 individuals identifies 40 novel smoking behaviour associated genetic loci.

Mol Psychiatry 2020 10 7;25(10):2392-2409. Epub 2019 Jan 7.

Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, Netherlands.

Smoking is a major heritable and modifiable risk factor for many diseases, including cancer, common respiratory disorders and cardiovascular diseases. Fourteen genetic loci have previously been associated with smoking behaviour-related traits. We tested up to 235,116 single nucleotide variants (SNVs) on the exome-array for association with smoking initiation, cigarettes per day, pack-years, and smoking cessation in a fixed effects meta-analysis of up to 61 studies (up to 346,813 participants). In a subset of 112,811 participants, a further one million SNVs were also genotyped and tested for association with the four smoking behaviour traits. SNV-trait associations with P < 5 × 10 in either analysis were taken forward for replication in up to 275,596 independent participants from UK Biobank. Lastly, a meta-analysis of the discovery and replication studies was performed. Sixteen SNVs were associated with at least one of the smoking behaviour traits (P < 5 × 10) in the discovery samples. Ten novel SNVs, including rs12616219 near TMEM182, were followed-up and five of them (rs462779 in REV3L, rs12780116 in CNNM2, rs1190736 in GPR101, rs11539157 in PJA1, and rs12616219 near TMEM182) replicated at a Bonferroni significance threshold (P < 4.5 × 10) with consistent direction of effect. A further 35 SNVs were associated with smoking behaviour traits in the discovery plus replication meta-analysis (up to 622,409 participants) including a rare SNV, rs150493199, in CCDC141 and two low-frequency SNVs in CEP350 and HDGFRP2. Functional follow-up implied that decreased expression of REV3L may lower the probability of smoking initiation. The novel loci will facilitate understanding the genetic aetiology of smoking behaviour and may lead to the identification of potential drug targets for smoking prevention and/or cessation.
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http://dx.doi.org/10.1038/s41380-018-0313-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7515840PMC
October 2020

Moderate-to-severe asthma in individuals of European ancestry: a genome-wide association study.

Lancet Respir Med 2019 Jan 11;7(1):20-34. Epub 2018 Dec 11.

Respiratory Medicine, Sir Charles Gairdner Hospital, Perth, WA, Australia.

Background: Few genetic studies that focus on moderate-to-severe asthma exist. We aimed to identity novel genetic variants associated with moderate-to-severe asthma, see whether previously identified genetic variants for all types of asthma contribute to moderate-to-severe asthma, and provide novel mechanistic insights using expression analyses in patients with asthma.

Methods: In this genome-wide association study, we used a two-stage case-control design. In stage 1, we genotyped patient-level data from two UK cohorts (the Genetics of Asthma Severity and Phenotypes [GASP] initiative and the Unbiased BIOmarkers in PREDiction of respiratory disease outcomes [U-BIOPRED] project) and used data from the UK Biobank to collect patient-level genomic data for cases and controls of European ancestry in a 1:5 ratio. Cases were defined as having moderate-to-severe asthma if they were taking appropriate medication or had been diagnosed by a doctor. Controls were defined as not having asthma, rhinitis, eczema, allergy, emphysema, or chronic bronchitis as diagnosed by a doctor. For stage 2, an independent cohort of cases and controls (1:5) was selected from the UK Biobank only, with no overlap with stage 1 samples. In stage 1 we undertook a genome-wide association study of moderate-to-severe asthma, and in stage 2 we followed up independent variants that reached the significance threshold of p less than 1 × 10 in stage 1. We set genome-wide significance at p less than 5 × 10. For novel signals, we investigated their effect on all types of asthma (mild, moderate, and severe). For all signals meeting genome-wide significance, we investigated their effect on gene expression in patients with asthma and controls.

Findings: We included 5135 cases and 25 675 controls for stage 1, and 5414 cases and 21 471 controls for stage 2. We identified 24 genome-wide significant signals of association with moderate-to-severe asthma, including several signals in innate or adaptive immune-response genes. Three novel signals were identified: rs10905284 in GATA3 (coded allele A, odds ratio [OR] 0·90, 95% CI 0·88-0·93; p=1·76 × 10), rs11603634 in the MUC5AC region (coded allele G, OR 1·09, 1·06-1·12; p=2·32 × 10), and rs560026225 near KIAA1109 (coded allele GATT, OR 1·12, 1·08-1·16; p=3·06 × 10). The MUC5AC signal was not associated with asthma when analyses included mild asthma. The rs11603634 G allele was associated with increased expression of MUC5AC mRNA in bronchial epithelial brush samples via proxy SNP rs11602802; (p=2·50 × 10) and MUC5AC mRNA was increased in bronchial epithelial samples from patients with severe asthma (in two independent analyses, p=0·039 and p=0·022).

Interpretation: We found substantial shared genetic architecture between mild and moderate-to-severe asthma. We also report for the first time genetic variants associated with the risk of developing moderate-to-severe asthma that regulate mucin production. Finally, we identify candidate causal genes in these loci and provide increased insight into this difficult to treat population.

Funding: Asthma UK, AirPROM, U-BIOPRED, UK Medical Research Council, and Rosetrees Trust.
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http://dx.doi.org/10.1016/S2213-2600(18)30389-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6314966PMC
January 2019

Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits.

Nat Genet 2018 10 17;50(10):1412-1425. Epub 2018 Sep 17.

Laboratory of Genetics and Genomics, NIA/NIH, Baltimore, MD, USA.

High blood pressure is a highly heritable and modifiable risk factor for cardiovascular disease. We report the largest genetic association study of blood pressure traits (systolic, diastolic and pulse pressure) to date in over 1 million people of European ancestry. We identify 535 novel blood pressure loci that not only offer new biological insights into blood pressure regulation but also highlight shared genetic architecture between blood pressure and lifestyle exposures. Our findings identify new biological pathways for blood pressure regulation with potential for improved cardiovascular disease prevention in the future.
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http://dx.doi.org/10.1038/s41588-018-0205-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6284793PMC
October 2018

Human copy number variation, gene expression, and the role of the CCL3L1-CCR5 axis in lung function.

Wellcome Open Res 2018 21;3:13. Epub 2018 Feb 21.

Department of Health Sciences, University of Leicester, Leicester, UK.

The CCL3L1-CCR5 signaling axis is important in a number of inflammatory responses, including macrophage function, and T-cell-dependent immune responses. Small molecule CCR5 antagonists exist, including the approved antiretroviral drug maraviroc, and therapeutic monoclonal antibodies are in development. Repositioning of drugs and targets into new disease areas can accelerate the availability of new therapies and substantially reduce costs. As it has been shown that drug targets with genetic evidence supporting their involvement in the disease are more likely to be successful in clinical development, using genetic association studies to identify new target repurposing opportunities could be fruitful. Here we investigate the potential of perturbation of the CCL3L1-CCR5 axis as treatment for respiratory disease. Europeans typically carry between 0 and 5 copies of and this multi-allelic variation is not detected by widely used genome-wide single nucleotide polymorphism studies.  We directly measured the complex structural variation of using the Paralogue Ratio Test and imputed (with validation) CCR5del32 genotypes in 5,000 individuals from UK Biobank, selected from the extremes of the lung function distribution, and analysed DNA and RNAseq data for from the 1000 Genomes Project. We confirmed the gene dosage effect of copy number on mRNA expression levels.  We found no evidence for association of copy number or CCR5del32 genotype with lung function. These results suggest that repositioning CCR5 antagonists is unlikely to be successful for the treatment of airflow obstruction.
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http://dx.doi.org/10.12688/wellcomeopenres.13902.2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5883389PMC
February 2018

Large-scale GWAS identifies multiple loci for hand grip strength providing biological insights into muscular fitness.

Nat Commun 2017 07 12;8:16015. Epub 2017 Jul 12.

MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge CB2 0QQ, UK.

Hand grip strength is a widely used proxy of muscular fitness, a marker of frailty, and predictor of a range of morbidities and all-cause mortality. To investigate the genetic determinants of variation in grip strength, we perform a large-scale genetic discovery analysis in a combined sample of 195,180 individuals and identify 16 loci associated with grip strength (P<5 × 10) in combined analyses. A number of these loci contain genes implicated in structure and function of skeletal muscle fibres (ACTG1), neuronal maintenance and signal transduction (PEX14, TGFA, SYT1), or monogenic syndromes with involvement of psychomotor impairment (PEX14, LRPPRC and KANSL1). Mendelian randomization analyses are consistent with a causal effect of higher genetically predicted grip strength on lower fracture risk. In conclusion, our findings provide new biological insight into the mechanistic underpinnings of grip strength and the causal role of muscular strength in age-related morbidities and mortality.
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http://dx.doi.org/10.1038/ncomms16015DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5510175PMC
July 2017

Genetic variants associated with susceptibility to idiopathic pulmonary fibrosis in people of European ancestry: a genome-wide association study.

Lancet Respir Med 2017 11 20;5(11):869-880. Epub 2017 Oct 20.

Fibrosis Discovery Performance Unit, GlaxoSmithKline, Stevenage, UK.

Background: Idiopathic pulmonary fibrosis (IPF) is a chronic progressive lung disease with high mortality, uncertain cause, and few treatment options. Studies have identified a significant genetic risk associated with the development of IPF; however, mechanisms by which genetic risk factors promote IPF remain unclear. We aimed to identify genetic variants associated with IPF susceptibility and provide mechanistic insight using gene and protein expression analyses.

Methods: We used a two-stage approach: a genome-wide association study in patients with IPF of European ancestry recruited from nine different centres in the UK and controls selected from UK Biobank (stage 1) matched for age, sex, and smoking status; and a follow-up of associated genetic variants in independent datasets of patients with IPF and controls from two independent US samples from the Chicago consortium and the Colorado consortium (stage 2). We investigated the effect of novel signals on gene expression in large transcriptomic and genomic data resources, and examined expression using lung tissue samples from patients with IPF and controls.

Findings: 602 patients with IPF and 3366 controls were selected for stage 1. For stage 2, 2158 patients with IPF and 5195 controls were selected. We identified a novel genome-wide significant signal of association with IPF susceptibility near A-kinase anchoring protein 13 (AKAP13; rs62025270, odds ratio [OR] 1·27 [95% CI 1·18-1·37], p=1·32 × 10) and confirmed previously reported signals, including in mucin 5B (MUC5B; rs35705950, OR 2·89 [2·56-3·26], p=1·12 × 10) and desmoplakin (DSP; rs2076295, OR 1·44 [1·35-1·54], p=7·81 × 10). For rs62025270, the allele A associated with increased susceptibility to IPF was also associated with increased expression of AKAP13 mRNA in lung tissue from patients who had lung resection procedures (n=1111). We showed that AKAP13 is expressed in the alveolar epithelium and lymphoid follicles from patients with IPF, and AKAP13 mRNA expression was 1·42-times higher in lung tissue from patients with IPF (n=46) than that in lung tissue from controls (n=51).

Interpretation: AKAP13 is a Rho guanine nucleotide exchange factor regulating activation of RhoA, which is known to be involved in profibrotic signalling pathways. The identification of AKAP13 as a susceptibility gene for IPF increases the prospect of successfully targeting RhoA pathway inhibitors in patients with IPF.

Funding: UK Medical Research Council, National Heart, Lung, and Blood Institute of the US National Institutes of Health, Agencia Canaria de Investigación, Innovación y Sociedad de la Información, Spain, UK National Institute for Health Research, and the British Lung Foundation.
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http://dx.doi.org/10.1016/S2213-2600(17)30387-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5666208PMC
November 2017

CNV-association meta-analysis in 191,161 European adults reveals new loci associated with anthropometric traits.

Nat Commun 2017 09 29;8(1):744. Epub 2017 Sep 29.

Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, 9713 GZ, The Netherlands.

There are few examples of robust associations between rare copy number variants (CNVs) and complex continuous human traits. Here we present a large-scale CNV association meta-analysis on anthropometric traits in up to 191,161 adult samples from 26 cohorts. The study reveals five CNV associations at 1q21.1, 3q29, 7q11.23, 11p14.2, and 18q21.32 and confirms two known loci at 16p11.2 and 22q11.21, implicating at least one anthropometric trait. The discovered CNVs are recurrent and rare (0.01-0.2%), with large effects on height (>2.4 cm), weight (>5 kg), and body mass index (BMI) (>3.5 kg/m). Burden analysis shows a 0.41 cm decrease in height, a 0.003 increase in waist-to-hip ratio and increase in BMI by 0.14 kg/m for each Mb of total deletion burden (P = 2.5 × 10, 6.0 × 10, and 2.9 × 10). Our study provides evidence that the same genes (e.g., MC4R, FIBIN, and FMO5) harbor both common and rare variants affecting body size and that anthropometric traits share genetic loci with developmental and psychiatric disorders.Individual SNPs have small effects on anthropometric traits, yet the impact of CNVs has remained largely unknown. Here, Kutalik and co-workers perform a large-scale genome-wide meta-analysis of structural variation and find rare CNVs associated with height, weight and BMI with large effect sizes.
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http://dx.doi.org/10.1038/s41467-017-00556-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5622064PMC
September 2017

Phenotypic and pharmacogenetic evaluation of patients with thiazide-induced hyponatremia.

J Clin Invest 2017 Sep 7;127(9):3367-3374. Epub 2017 Aug 7.

Division of Therapeutics and Molecular Medicine, University of Nottingham, Nottingham, United Kingdom.

Thiazide diuretics are among the most widely used treatments for hypertension, but thiazide-induced hyponatremia (TIH), a clinically significant adverse effect, is poorly understood. Here, we have studied the phenotypic and genetic characteristics of patients hospitalized with TIH. In a cohort of 109 TIH patients, those with severe TIH displayed an extended phenotype of intravascular volume expansion, increased free water reabsorption, urinary prostaglandin E2 excretion, and reduced excretion of serum chloride, magnesium, zinc, and antidiuretic hormone. GWAS in a separate cohort of 48 TIH patients and 2,922 controls from the 1958 British birth cohort identified an additional 14 regions associated with TIH. We identified a suggestive association with a variant in SLCO2A1, which encodes a prostaglandin transporter in the distal nephron. Resequencing of SLCO2A1 revealed a nonsynonymous variant, rs34550074 (p.A396T), and association with this SNP was replicated in a second cohort of TIH cases. TIH patients with the p.A396T variant demonstrated increased urinary excretion of prostaglandin E2 and metabolites. Moreover, the SLCO2A1 phospho-mimic p.A396E showed loss of transporter function in vitro. These findings indicate that the phenotype of TIH involves a more extensive metabolic derangement than previously recognized. We propose one mechanism underlying TIH development in a subgroup of patients in which SLCO2A1 regulation is altered.
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http://dx.doi.org/10.1172/JCI89812DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5669583PMC
September 2017

Novel Blood Pressure Locus and Gene Discovery Using Genome-Wide Association Study and Expression Data Sets From Blood and the Kidney.

Hypertension 2017 Jul 24. Epub 2017 Jul 24.

From the Department of Health Sciences (L.V.W., A.M.E., N. Shrine, C.B., T.B., M.D.T.), and Department of Cardiovascular Sciences and NIHR Leicester Biomedical Research Centre (C.P.N., P.S.B., N.J.S.), University of Leicester, United Kingdom; Department of Epidemiology (A.V., P.J.v.d.M., I.M.N., H. Snieder), Division of Nephrology, Department of Internal Medicine (M.H.d.B., M.A.S.), Interdisciplinary Center Psychopathology and Emotion Regulation (IPCE) (A.J.O., H.R., C.A.H.), Department of Genetics, (M.S.), and Department of Cardiology (P.v.d.H.), University of Groningen, University Medical Center Groningen, The Netherlands; Research Institute for Primordial Prevention of Non-Communicable Disease, Isfahan University of Medical Sciences, Iran (A.V.); Department of Psychiatry, VU University Medical Center, Neuroscience Campus Amsterdam, The Netherlands (R. Jansen); Hebrew SeniorLife, Harvard Medical School, Boston, MA (R. Joehanes); National Heart, Lung and Blood Institute's Framingham Heart Study, MA (R. Joehanes, A.D.J., M. Larson); Institute of Psychiatry, Psychology and Neuroscience (P.F.O.), and Department of Twin Research and Genetic Epidemiology (M.M., C. Menni, T.D.S.), King's College London, United Kingdom; Clinical Pharmacology, William Harvey Research Institute (C.P.C., H.R.W., M.R.B., M. Brown, B.M., M.R., P.B.M., M.J.C.) and NIHR Barts Cardiovascular Biomedical Research Unit (C.P.C., H.R.W., M.R.B., M. Brown, P.B.M., M.J.C.), Barts and The London School of Medicine and Dentistry, Queen Mary University of London, United Kingdom; Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA (L.M.R., F.G., P.M.R., D.I.C.); Department of Epidemiology (G.C.V., A. Hofman, A.G.U., O.H.F.), Genetic Epidemiology Unit, Department of Epidemiology (N.A., B.A.O., C.M.v.D.), and Department of Internal Medicine (A.G.U.), Erasmus MC, Rotterdam, The Netherlands; Department of Biological Psychology, Vrije Universiteit, Amsterdam, EMGO+ Institute, VU University Medical Center, The Netherlands (J.-J.H., E.J.d.G., G.W., D.I.B.); Cardiovascular Medicine Unit, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden (R.J.S., M. Frånberg, A. Hamsten); Centre for Molecular Medicine, Karolinska Universitetsjukhuset, Solna, Sweden (R.J.S., M. Frånberg, A. Hamsten); Estonian Genome Center (T.E., E.O., A. Metspalu), Institute of Biomedicine and Translational Medicine (S.S., M. Laan), and Estonian Genome Center (M.P.), University of Tartu, Estonia; Divisions of Endocrinology/Children's Hospital, Boston, MA (T.E.); Broad Institute of Harvard and MIT, Cambridge, MA (T.E., C.M.L., C.N.-C.); Center for Complex Disease Genomics, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (D.E.A., P.N., A. Chakravarti, G.B.E.); The Population Science Branch, Division of Intramural Research, National Heart Lung and Blood Institute (S.-J.H., D.L.), Laboratory of Neurogenetics, National Institute on Aging (M.A.N.), Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute (F.C.), and Center for Information Technology (Y.D., P.J.M., Q.T.N.), National Institutes of Health, Bethesda, MD; The Framingham Heart Study, Framingham, MA (S.-J.H., D.L.); The Institute for Translational Genomics and Population Sciences, Department of Pediatrics (X.G., J.Y.), and The Institute for Translational Genomics and Population Sciences, Departments of Pediatrics and Medicine (J.I.R.), LABioMed at Harbor-UCLA Medical Center, Torrance, CA; Institute of Social and Preventive Medicine, Lausanne University Hospital, Lausanne, Switzerland (Z.K., M. Bochud); Swiss Institute of Bioinformatics, Lausanne, Switzerland (Z.K.); Department of Cardiology (S. Trompet, J.W.J.) Department of Gerontology and Geriatrics (S. Trompet), Department of Clinical Epidemiology (R.L.-G., R.d.M., D.O.M.-K.), Department of Molecular Epidemiology (J.D.), and Department of Public Health and Primary Care (D.O.M.-K.), Leiden University Medical Center, The Netherlands; Institute for Community Medicine (A.T.), Department of Internal Medicine B (M.D.), and Interfaculty Institute for Genetics and Functional Genomics (U.V.), University Medicine Greifswald, Germany; DZHK (German Centre for Cardiovascular Research), partner site Greifswald, Germany (A.T., M.D., U.V.); Institute of Epidemiology II, Helmholtz Zentrum München, Neuherberg, Germany (J.S.R., A. Peters); Cardiovascular Health Research Unit, Department of Medicine (J.C.B., B.M.P.) and Departments of Biostatistics (K.R.), Epidemiology (B.M.P.), and Health Services (B.M.P.), University of Washington, Seattle; Icelandic Heart Association, Kopavogur, Iceland (A.V.S., V. Gudnason); Faculty of Medicine, University of Iceland, Reykjavik, Iceland (A.V.S., V. Gudnason); Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland (L.-P.L., T.L.); Department of Clinical Chemistry, Faculty of Medicine and Life Sciences, University of Tampere, Finland (L.-P.L., T.L.); Wellcome Trust Centre for Human Genetics (A. Mahajan, A.G., M. Farrall, T.F., C.M.L., H.W., A.P.M.), and Division of Cardiovascular Medicine, Radcliffe Department of Medicine (A.G., M. Farrall, H.W.), University of Oxford, United Kingdom; MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, United Kingdom (N.J.W., J.L., C.L., R.J.F.L., R.A.S., J.H.Z.); Clinical Division of Neurogeriatrics, Department of Neurology (E.H., R. Schmidt), Institute of Medical Informatics, Statistics and Documentation (E.H.), and Department of Neurology (H. Schmidt), Medical University Graz, Austria; Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics (P.K.J., H.C., I.R., S.W., J.F.W.), Centre for Cognitive Ageing and Cognitive Epidemiology (L.M.L., S.E.H., G.D., A.J.G., D.C.M.L., J.M.S., I.J.D.), Medical Genetics Section, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine (A. Campbell), Generation Scotland, Centre for Genomic and Experimental Medicine (A. Campbell, S.P., C.H.), Department of Psychology (G.D., D.C.M.L., A. Pattie, I.J.D.), Alzheimer Scotland Dementia Research Centre (J.M.S.), and Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine (C.H.), University of Edinburgh, Scotland, United Kingdom; Department of Health (K.K., A.S.H., T. Niiranen, P.J., A.J., S. Koskinen, P.K., V.S., M.P.), and Chronic Disease Prevention Unit (J.T.), National Institute for Health and Welfare (THL), Helsinki, Finland; Division of Genetics and Cell Biology, San Raffaele Scientific Institute, Milano, Italy (M.T., C.M.B., C.F.S., D.T.); Data Tecnica International, Glen Echo, MD (M.A.N.); Medical Genetics, IRCCS-Burlo Garofolo Children Hospital, Trieste, Italy (D.V., G.G., P.G.); Department of Medical, Surgical and Health Sciences, University of Trieste, Italy (D.V., I.G., M. Brumat, M. Cocca, A. Morgan, G.G., P.G.); Institute for Biomedicine, Eurac Research, Affiliated Institute of the University of Lübeck, Bolzano, Italy (F.D.G.M., P.P.P., A.S.P., A.A.H.); Department of Genetics and Genomic Sciences (K.L.A.), The Charles Bronfman Institute for Personalized Medicine (Y.L., E.P.B., R.J.F.L.), and Mindich Child health Development Institute (R.J.F.L.), Icahn School of Medicine at Mount Sinai, New York; Cardiovascular Epidemiology and Genetics, IMIM, and CIBERCV, Barcelona, Spain (J. Marrugat, R.E.); Institute of Genetics and Biophysics A. Buzzati-Traverso, CNR, Napoli, Italy (D.R., T. Nutile, R. Sorice, M. Ciullo); Department of Psychiatry, Royal College of Surgeons in Ireland, Education and Research Centre, Beaumont Hospital, Dublin (L.M.L.); UCD Conway Institute, Centre for Proteome Research (L.M.L.), and School of Medicine, Conway Institute (D.C.S.), University College Dublin, Belfield, Ireland; Department of Immunology, Genetics and Pathology, Uppsala Universitet, Science for Life Laboratory, Sweden (S.E., Å. Johansson, U.G.); Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor (A.U.J., M. Boehnke); NIHR Leicester Cardiovascular Biomedical Research Unit, Glenfield Hospital, Leicester United Kingdom (C.P.N., P.S.B., N.J.S.); MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine (J.E.H., V.V., J. Marten, A.F.W., J.F.W.), and Medical Genetics Section, Centre for Genomic and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine (S.E.H.), University of Edinburgh, Western General Hospital, Scotland, United Kingdom; Department of Epidemiology and Biostatistics, School of Public Health (W.Z., E.E., J.C.C., H.G., B.L., I.T., A.-C.V.), MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health (M.-R.J., P.E.), School of Public Health (N.P.), International Centre for Circulatory Health (S. Thom), and National Heart and Lung Institute (P.S.), Imperial College London, United Kingdom; Department of Cardiology, Ealing Hospital, London North West Healthcare NHS Trust, Southall, United Kingdom (W.Z., J.C.C., J.S.K.); Department of Medical Biology, Faculty of Medicine, University of Split, Croatia (T.Z.); Department of Hygiene and Epidemiology, University of Ioannina Medical School, Greece (E.E.); Medical Research Institute, University of Dundee, Ninewells Hospital and Medical School, Scotland, United Kingdom (N. Shah, A.S.F.D., C.N.A.P.); Department of Pharmacy, COMSATS Institute of Information Technology, Abbottabad, Pakistan (N. Shah); National Institute for Health Research Biomedical Research Centre, London, United Kingdom (M.M.); Department of Human Genetics, Wellcome Trust Sanger Institute, United Kingdom (B.P.P., E.Z.); INSERM U 1219, Bordeaux Population Health Center, France (G.C., C.T., S.D.); Bordeaux University, France (G.C., C.T., S.D.); Hunter Medical Research Institute, New Lambton, NSW, Australia (C.O., E.G.H., R. Scott, J.A.); Center for Statistical Genetics, Department of Biostatistics, Ann Arbor, MI (G.A.); Department of Genetics and Molecular Biology, Isfahan University of Medical Sciences, Iran (M.A.); Busselton Population Medical Research Institute, Western Australia (J.B., J.H.); PathWest Laboratory Medicine of Western Australia, Nedlands (J.B., J.H.); School of Pathology and Laboratory Medicine (J.B., J.H.), School of Population and Global Health (J.H.), and School of Medicine and Pharmacology (A. James), The University of Western Australia, Nedlands; Imperial College Healthcare NHS Trust, London, United Kingdom (J.C.C., J.S.K.); University of Dundee, Ninewells Hospital & Medical School, United Kingdom (J.C.); Institute of Genetic Medicine (H.J.C.), and Institute of Health and Society (C. Mamasoula), Newcastle University, Newcastle upon Tyne, United Kingdom; Department of Pathology, Amsterdam Medical Center, The Netherlands (J.J.D.); Department of Numerical Analysis and Computer Science, Stockholm University, Sweden (M. Frånberg); Department of Public Health and Caring Sciences, Geriatrics, Uppsala, Sweden (V. Giedraitis); Helmholtz Zentrum Muenchen, Deutsches Forschungszentrum fuer Gesundheit und Umwelt (GmbH), Neuherberg, Germany (C.G.); Department of Psychology, School of Social Sciences, Heriot-Watt University, Edinburgh, United Kingdom (A.J.G.); Intramural Research Program, Laboratory of Epidemiology, Demography, and Biometry, National Institute on Aging (T.B.H., L.J.L.); Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA (A. Hofman); Center For Life-Course Health Research (M.-R.J.), and Biocenter Oulu (M.-R.J.), University of Oulu, Finland; Unit of Primary Care, Oulu University Hospital, Finland (M.-R.J.); National Heart, Lung and Blood Institute, Cardiovascular Epidemiology and Human Genomics Branch, Bethesda, MD (A.D.J.); Department of Clinical Physiology, Tampere University Hospital, Finland (M.K.); Department of Clinical Physiology, Faculty of Medicine and Life Sciences, University of Tampere, Finland (M.K.); Cardiovascular Research Center (S. Kathiresan, C.N.-C.); Center for Human Genetics (S. Kathiresan), and Center for Human Genetic Research (C.N.-C.), Massachusetts General Hospital, Boston; Program in Medical and Population Genetics, Broad Institute, Cambridge, MA (S. Kathiresan, C.N.-C.); Department of Public Health and Primary Care, Institute of Public Health, University of Cambridge, United Kingdom (K.-T.K.); Department of Public Health, Faculty of Medicine, University of Split, Croatia (I.K., O.P.); Cardiology, Department of Specialties of Medicine, Geneva University Hospital, Switzerland (L. Lin, F.M., G.B.E.); Department of Medical Sciences, Cardiovascular Epidemiology (L. Lind, J.S.), and Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory (E.I.), Uppsala University, Sweden; Department of Psychiatry, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, The Netherlands (Y.M., B.W.J.H.P.); School of Molecular, Genetic and Population Health Sciences, University of Edinburgh, Medical School, Teviot Place, Scotland, United Kingdom (A.D.M.); Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston (A.C.M.); British Heart Foundation Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary and Life Sciences (S.P.), and Institute of Cardiovascular and Medical Sciences, Faculty of Medicine (D.J.S.), University of Glasgow, United Kingdom; Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Finland (A. Palotie, S.R., A.-P.S., M.P.); Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Canada (G.P., S. Thériault); Department of Neurology, General Central Hospital, Bolzano, Italy (P.P.P.); Department of Neurology, University of Lübeck, Germany (P.P.P.); Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Finland (O.T.R.); Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Finland (O.T.R.); Department of Cardiology, Fujian Provincial Hospital, Fujian Medical University, Fuzhou, China (M.R.); Harvard Medical School, Boston, MA (P.M.R., D.I.C.); Institute for Maternal and Child Health IRCCS Burlo Garofolo, Trieste, Italy (A.R.); Institute of Molecular Biology and Biochemistry, Centre for Molecular Medicine, Medical University of Graz, Austria (Y.S., H. Schmidt); INSERM U1078, Etablissement Français du Sang, Brest Cedex, France (A.S.P.); Faculty of Health, University of Newcastle, Callaghan, NSW, Australia (R. Scott, J.A.); John Hunter Hospital, New Lambton, NSW, Australia (R. Scott, J.A.); The New York Academy of Medicine, New York (D.S.); IRCCS Neuromed, Pozzilli, Isernia, Italy (R. Sorice, M. Ciullo); Molecular and Cellular Therapeutics, Royal College of Surgeons in Ireland, Dublin 2, Ireland (A.S.); Institute for Translational Genomics and Population Sciences, Los Angeles BioMedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA (K.D.T.); Division of Genetic Outcomes, Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA (K.D.T.); Department of Public Health (C.T.), and Department of Neurology (S.D.), Bordeaux University Hospital, France; Department of Internal Medicine, Lausanne University Hospital, CHUV, Switzerland (P.V.); Population Health Research Institute, McMaster University, Hamilton Ontario, Canada (D.C.); National Heart and Lung Institute, Imperial College London, Hammersmith Hospital Campus, United Kingdom (J.S.K.); Dasman Diabetes Institute, Kuwait (J.T.); Diabetes Research Group, King Abdulaziz University, Jeddah, Saudi Arabia (J.T.); Department of Neurosciences and Preventive Medicine, Danube-University Krems, Austria (J.T.); Division of Cardiovascular Sciences, The University of Manchester and Central Manchester University Hospitals NHS Foundation Trust, United Kingdom (B.D.K.); Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem (Y.M.L.); Kaiser Permanent Washington Health Research Institute, Seattle, WA (B.M.P.); Institute of Physiology, University Medicine Greifswald, Karlsburg, Germany (R.R); Department of Pulmonary Physiology and Sleep, Sir Charles Gairdner Hospital, Nedlands, Western Australia (A. James); Population Health Research Institute, St George's, University of London, United Kingdom (D.P.S.); Department of Medicine, Columbia University Medical Center, New York (W.P.); Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, CA (E.I.); Data Science Institute and Lancaster Medical School, Lancaster University, United Kingdom (J.K.); and Department of Biostatistics, University of Liverpool, United Kingdom (A.P.M.).

Elevated blood pressure is a major risk factor for cardiovascular disease and has a substantial genetic contribution. Genetic variation influencing blood pressure has the potential to identify new pharmacological targets for the treatment of hypertension. To discover additional novel blood pressure loci, we used 1000 Genomes Project-based imputation in 150 134 European ancestry individuals and sought significant evidence for independent replication in a further 228 245 individuals. We report 6 new signals of association in or near , , , , , and , and provide new replication evidence for a further 2 signals in and Combining large whole-blood gene expression resources totaling 12 607 individuals, we investigated all novel and previously reported signals and identified 48 genes with evidence for involvement in blood pressure regulation that are significant in multiple resources. Three novel kidney-specific signals were also detected. These robustly implicated genes may provide new leads for therapeutic innovation.
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http://dx.doi.org/10.1161/HYPERTENSIONAHA.117.09438DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5783787PMC
July 2017

Age at menarche and lung function: a Mendelian randomization study.

Eur J Epidemiol 2017 08 17;32(8):701-710. Epub 2017 Jun 17.

Population Health and Occupational Disease, NHLI, Imperial College London, Emmanuel Kaye Building, 1B Manresa Road, SW3 6LR, London, UK.

A trend towards earlier menarche in women has been associated with childhood factors (e.g. obesity) and hypothesised environmental exposures (e.g. endocrine disruptors present in household products). Observational evidence has shown detrimental effects of early menarche on various health outcomes including adult lung function, but these might represent spurious associations due to confounding. To address this we used Mendelian randomization where genetic variants are used as proxies for age at menarche, since genetic associations are not affected by classical confounding. We estimated the effects of age at menarche on forced vital capacity (FVC), a proxy for restrictive lung impairment, and ratio of forced expiratory volume in one second to FVC (FEV1/FVC), a measure of airway obstruction, in both adulthood and adolescence. We derived SNP-age at menarche association estimates for 122 variants from a published genome-wide meta-analysis (N = 182,416), with SNP-lung function estimates obtained by meta-analysing three studies of adult women (N = 46,944) and two of adolescent girls (N = 3025). We investigated the impact of departures from the assumption of no pleiotropy through sensitivity analyses. In adult women, in line with previous evidence, we found an effect on restrictive lung impairment with a 24.8 mL increase in FVC per year increase in age at menarche (95% CI 1.8-47.9; p = 0.035); evidence was stronger after excluding potential pleiotropic variants (43.6 mL; 17.2-69.9; p = 0.001). In adolescent girls we found an opposite effect (-56.5 mL; -108.3 to -4.7; p = 0.033), suggesting that the detrimental effect in adulthood may be preceded by a short-term post-pubertal benefit. Our secondary analyses showing results in the same direction in men and boys, in whom age at menarche SNPs have also shown association with sexual development, suggest a role for pubertal timing in general rather than menarche specifically. We found no effect on airway obstruction (FEV1/FVC).
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http://dx.doi.org/10.1007/s10654-017-0272-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5591357PMC
August 2017

Genetic variants affecting cross-sectional lung function in adults show little or no effect on longitudinal lung function decline.

Thorax 2017 05 7;72(5):400-408. Epub 2017 Feb 7.

Genetic Epidemiology Group, Department of Health Sciences, University of Leicester, Leicester, UK.

Background: Genome-wide association studies have identified numerous genetic regions that influence cross-sectional lung function. Longitudinal decline in lung function also includes a heritable component but the genetic determinants have yet to be defined.

Objectives: We aimed to determine whether regions associated with cross-sectional lung function were also associated with longitudinal decline and to seek novel variants which influence decline.

Methods: We analysed genome-wide data from 4167 individuals from the Busselton Health Study cohort, who had undergone spirometry (12 695 observations across eight time points). A mixed model was fitted and weighted risk scores were calculated for the joint effect of 26 known regions on baseline and longitudinal changes in FEV and FEV/FVC. Potential additional regions of interest were identified and followed up in two independent cohorts.

Results: The 26 regions previously associated with cross-sectional lung function jointly showed a strong effect on baseline lung function (p=4.44×10 for FEV/FVC) but no effect on longitudinal decline (p=0.160 for FEV/FVC). This was replicated in an independent cohort. 39 additional regions of interest (48 variants) were identified; these associations were not replicated in two further cohorts.

Conclusions: Previously identified genetic variants jointly have a strong effect on cross-sectional lung function in adults but little or no effect on the rate of decline of lung function. It is possible that they influence COPD risk through lung development. Although no genetic variants have yet been associated with lung function decline at stringent genome-wide significance, longitudinal change in lung function is heritable suggesting that there is scope for future discoveries.
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http://dx.doi.org/10.1136/thoraxjnl-2016-208448DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5520280PMC
May 2017

Genetic loci associated with chronic obstructive pulmonary disease overlap with loci for lung function and pulmonary fibrosis.

Nat Genet 2017 Mar 6;49(3):426-432. Epub 2017 Feb 6.

Pulmonary, Critical Care, Sleep and Allergy Division, Department of Internal Medicine, University of Nebraska Medical Center, Omaha, Nebraska, USA.

Chronic obstructive pulmonary disease (COPD) is a leading cause of mortality worldwide. We performed a genetic association study in 15,256 cases and 47,936 controls, with replication of select top results (P < 5 × 10) in 9,498 cases and 9,748 controls. In the combined meta-analysis, we identified 22 loci associated at genome-wide significance, including 13 new associations with COPD. Nine of these 13 loci have been associated with lung function in general population samples, while 4 (EEFSEC, DSP, MTCL1, and SFTPD) are new. We noted two loci shared with pulmonary fibrosis (FAM13A and DSP) but that had opposite risk alleles for COPD. None of our loci overlapped with genome-wide associations for asthma, although one locus has been implicated in joint susceptibility to asthma and obesity. We also identified genetic correlation between COPD and asthma. Our findings highlight new loci associated with COPD, demonstrate the importance of specific loci associated with lung function to COPD, and identify potential regions of genetic overlap between COPD and other respiratory diseases.
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http://dx.doi.org/10.1038/ng.3752DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5381275PMC
March 2017

Genome-wide association analyses for lung function and chronic obstructive pulmonary disease identify new loci and potential druggable targets.

Nat Genet 2017 Mar 6;49(3):416-425. Epub 2017 Feb 6.

Department of Internal Medicine B-Cardiology, Intensive Care, Pulmonary Medicine and Infectious Diseases, University Medicine Greifswald, Greifswald, Germany.

Chronic obstructive pulmonary disease (COPD) is characterized by reduced lung function and is the third leading cause of death globally. Through genome-wide association discovery in 48,943 individuals, selected from extremes of the lung function distribution in UK Biobank, and follow-up in 95,375 individuals, we increased the yield of independent signals for lung function from 54 to 97. A genetic risk score was associated with COPD susceptibility (odds ratio per 1 s.d. of the risk score (∼6 alleles) (95% confidence interval) = 1.24 (1.20-1.27), P = 5.05 × 10), and we observed a 3.7-fold difference in COPD risk between individuals in the highest and lowest genetic risk score deciles in UK Biobank. The 97 signals show enrichment in genes for development, elastic fibers and epigenetic regulation pathways. We highlight targets for drugs and compounds in development for COPD and asthma (genes in the inositol phosphate metabolism pathway and CHRM3) and describe targets for potential drug repositioning from other clinical indications.
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http://dx.doi.org/10.1038/ng.3787DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5326681PMC
March 2017

Targeted Sequencing of Lung Function Loci in Chronic Obstructive Pulmonary Disease Cases and Controls.

PLoS One 2017 23;12(1):e0170222. Epub 2017 Jan 23.

Genetic Epidemiology Group, Department of Health Sciences, University of Leicester, Leicester, United Kingdom.

Chronic obstructive pulmonary disease (COPD) is the third leading cause of death worldwide; smoking is the main risk factor for COPD, but genetic factors are also relevant contributors. Genome-wide association studies (GWAS) of the lung function measures used in the diagnosis of COPD have identified a number of loci, however association signals are often broad and collectively these loci only explain a small proportion of the heritability. In order to examine the association with COPD risk of genetic variants down to low allele frequencies, to aid fine-mapping of association signals and to explain more of the missing heritability, we undertook a targeted sequencing study in 300 COPD cases and 300 smoking controls for 26 loci previously reported to be associated with lung function. We used a pooled sequencing approach, with 12 pools of 25 individuals each, enabling high depth (30x) coverage per sample to be achieved. This pooled design maximised sample size and therefore power, but led to challenges during variant-calling since sequencing error rates and minor allele frequencies for rare variants can be very similar. For this reason we employed a rigorous quality control pipeline for variant detection which included the use of 3 independent calling algorithms. In order to avoid false positive associations we also developed tests to detect variants with potential batch effects and removed them before undertaking association testing. We tested for the effects of single variants and the combined effect of rare variants within a locus. We followed up the top signals with data available (only 67% of collapsing methods signals) in 4,249 COPD cases and 11,916 smoking controls from UK Biobank. We provide suggestive evidence for the combined effect of rare variants on COPD risk in TNXB and in sliding windows within MECOM and upstream of HHIP. These findings can lead to an improved understanding of the molecular pathways involved in the development of COPD.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0170222PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5256917PMC
August 2017

Genome-wide association study of copy number variation with lung function identifies a novel signal of association near BANP for forced vital capacity.

BMC Genet 2016 08 11;17(1):116. Epub 2016 Aug 11.

Department of Health Sciences, University of Leicester, University Road, Leicester, LE1 7RH, UK.

Background: Genome-wide association studies of Single Nucleotide Polymorphisms (SNPs) have identified 55 SNPs associated with lung function. However, little is known about the effect of copy number variants (CNVs) on lung function, although CNVs represent a significant proportion of human genetic polymorphism. To assess the effect of CNVs on lung function quantitative traits, we measured copy number at 2788 previously characterised, common copy number variable regions in 6 independent cohorts (n = 24,237) using intensity data from SNP genotyping experiments. We developed a pipeline for genome-wide association analysis and meta-analysis of CNV genotypes measured across multiple studies using SNP genotype array intensity data from different platform technologies. We then undertook cohort-level genome-wide association studies of CNV with lung function in a subset of 4 cohorts (n < =12,403) with lung function measurements and meta-analysed the results. Follow-up was undertaken for CNVs which were well tagged by SNPs, in up to 146,871 individuals.

Results: We generated robust copy number calls for 1962 out of 2788 (70 %) known CNV regions genome-wide, with 1103 measured with compatible class frequencies in at least 2 cohorts. We report a novel CNV association (discovery P = 0.0007) with Forced Vital Capacity (FVC) downstream of BANP on chromosome 16 that shows evidence of replication by a tag SNP in two independent studies (replication P = 0.004). In addition, we provide suggestive evidence (discovery P = 0.0002) for a role of complex copy number variation at a previously reported lung function locus, containing the rootletin gene CROCC, that is not tagged by SNPs.

Conclusions: We demonstrate how common CNV regions can be reliably and consistently called across cohorts, using an existing calling algorithm and rigorous quality control steps, using SNP genotyping array intensity data. Although many common biallelic CNV regions were well-tagged by common SNPs, we also identified associations with untagged mulitallelic CNV regions thereby illustrating the potential of our approach to identify some of the missing heritability of complex traits.
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http://dx.doi.org/10.1186/s12863-016-0423-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4981989PMC
August 2016
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