Publications by authors named "Fotios Drenos"

81 Publications

No evidence that vitamin D is able to prevent or affect the severity of COVID-19 in individuals with European ancestry: a Mendelian randomisation study of open data.

BMJ Nutr Prev Health 2021 7;4(1):42-48. Epub 2021 Jan 7.

Department of Life Sciences, Brunel University London, Uxbridge, UK.

Background: Upper respiratory tract infections are reportedly more frequent and more severe in individuals with lower vitamin D levels. Based on these findings, it has been suggested that vitamin D can prevent or reduce the severity of COVID-19.

Methods: We used two-sample Mendelian randomisation (MR) to assess the causal effect of vitamin D levels on SARS-CoV-2 infection risk and COVID-19 severity using publicly available data. We also carried out a genome-wide association analysis (GWA) of vitamin D deficiency in the UK Biobank (UKB) and used these results and two-sample MR to assess the causal effect of vitamin D deficiency on SARS-CoV-2 infection risk and COVID-19 severity.

Results: We found no evidence that vitamin D levels causally affect the risk of SARS-CoV-2 infection (ln(OR)=0.17 (95% CI -0.22 to 0.57, p=0.39)) nor did we find evidence that vitamin D levels causally affect COVID-19 severity (ln(OR)=0.36 (95% CI -0.89 to 1.61, p=0.57)). Based on our GWA analysis, we found that 17 independent variants are associated with vitamin D deficiency in the UKB. Using these variants as instruments for our two-sample MR analyses, we found no evidence that vitamin D deficiency causally affects the risk of SARS-CoV-2 infection (ln(OR)=-0.04 (95% CI -0.1 to 0.03, p=0.25)) nor did we find evidence that vitamin D deficiency causally affects COVID-19 severity (ln(OR)=-0.24 (95% CI -0.55 to 0.08, p=0.14)).

Conclusions: In conclusion, we found no evidence that vitamin D is protective against SARS-CoV-2 infection or COVID-19 severity. Our data support the recent statement by the National Institute for Health and Care Excellence that the use of vitamin D supplementation to mitigate COVID-19 is not supported by the available data.
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http://dx.doi.org/10.1136/bmjnph-2020-000151DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7798425PMC
January 2021

Discovery of rare variants associated with blood pressure regulation through meta-analysis of 1.3 million individuals.

Nat Genet 2020 12 23;52(12):1314-1332. Epub 2020 Nov 23.

Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark.

Genetic studies of blood pressure (BP) to date have mainly analyzed common variants (minor allele frequency > 0.05). In a meta-analysis of up to ~1.3 million participants, we discovered 106 new BP-associated genomic regions and 87 rare (minor allele frequency ≤ 0.01) variant BP associations (P < 5 × 10), of which 32 were in new BP-associated loci and 55 were independent BP-associated single-nucleotide variants within known BP-associated regions. Average effects of rare variants (44% coding) were ~8 times larger than common variant effects and indicate potential candidate causal genes at new and known loci (for example, GATA5 and PLCB3). BP-associated variants (including rare and common) were enriched in regions of active chromatin in fetal tissues, potentially linking fetal development with BP regulation in later life. Multivariable Mendelian randomization suggested possible inverse effects of elevated systolic and diastolic BP on large artery stroke. Our study demonstrates the utility of rare-variant analyses for identifying candidate genes and the results highlight potential therapeutic targets.
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http://dx.doi.org/10.1038/s41588-020-00713-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7610439PMC
December 2020

H2A Histone Family Member X (H2AX) Is Upregulated in Ovarian Cancer and Demonstrates Utility as a Prognostic Biomarker in Terms of Overall Survival.

J Clin Med 2020 Sep 2;9(9). Epub 2020 Sep 2.

Department of Life Sciences, Brunel University London, Uxbridge UB83PH, UK.

: H2AX can be of prognostic value in breast cancer, since in advanced stage patients with high levels, there was an association with worse overall survival (OS). However, the clinical relevance of H2AX in ovarian cancer (OC) remains to be elucidated. : OC expression studied using the TCGA/GTEX datasets. Subsequently, patients were classified as either high or low in terms of expression to compare OS and perform gene set enrichment. qRT-PCR validated findings followed by immunohistochemistry on a tissue microarray. The association between single nucleotide polymorphisms in the area of H2AX; prevalence and five-year OC survival was tested in samples from the UK Biobank. : was significantly overexpressed in OCs compared to normal tissues, with higher expression associated with better OS ( = 0.010). Gene Set Enrichment Analysis demonstrated gene sets involved in G2/M checkpoint, DNA repair mTORC1 signalling were enriched in the H2AX highly expressing OCs. Polymorphisms in the area around the gene were associated with both OC prevalence (rs72997349-C, = 0.005) and worse OS (rs10790282-G, = 0.011). Finally, we demonstrated that H2AX gene expression correlated with γ-H2AX staining in vitro. : Our findings suggest that H2AX can be a novel prognostic biomarker for OC.
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http://dx.doi.org/10.3390/jcm9092844DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7565050PMC
September 2020

Polycystic ovary syndrome (PCOS) and COVID-19: an overlooked female patient population at potentially higher risk during the COVID-19 pandemic.

BMC Med 2020 07 15;18(1):220. Epub 2020 Jul 15.

Warwickshire Institute for the Study of Diabetes, Endocrinology and Metabolism (WISDEM), University Hospitals Coventry and Warwickshire NHS Trust, Coventry, CV2 2DX, UK.

Background: In women of reproductive age, polycystic ovary syndrome (PCOS) constitutes the most frequent endocrine disorder. Women with PCOS are considered to typically belong to an age and sex group which is at lower risk for severe COVID-19.

Main Body: Emerging data link the risk of severe COVID-19 with certain factors such as hyper-inflammation, ethnicity predisposition, low vitamin D levels, and hyperandrogenism, all of which have known direct associations with PCOS. Moreover, in this common female patient population, there is markedly high prevalence of multiple cardio-metabolic conditions, such as type 2 diabetes, obesity, and hypertension, which may significantly increase the risk for adverse COVID-19-related outcomes. This strong overlap of risk factors for both worse PCOS cardio-metabolic manifestations and severe COVID-19 should be highlighted for the clinical practice, particularly since women with PCOS often receive fragmented care from multiple healthcare services. Comprehensively informing women with PCOS regarding the potential risks from COVID-19 and how this may affect their management is also essential.

Conclusion: Despite the immense challenges posed by the COVID-19 outbreak to the healthcare systems in affected countries, attention should be directed to maintain a high standard of care for complex patients such as many women with PCOS and provide relevant practical recommendations for optimal management in the setting of this fast moving pandemic.
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http://dx.doi.org/10.1186/s12916-020-01697-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7360476PMC
July 2020

A metabolic profile of all-cause mortality risk identified in an observational study of 44,168 individuals.

Nat Commun 2019 08 20;10(1):3346. Epub 2019 Aug 20.

Division of Human Nutrition, Wageningen University, PO Box 17, 6700 AA, Wageningen, The Netherlands.

Predicting longer-term mortality risk requires collection of clinical data, which is often cumbersome. Therefore, we use a well-standardized metabolomics platform to identify metabolic predictors of long-term mortality in the circulation of 44,168 individuals (age at baseline 18-109), of whom 5512 died during follow-up. We apply a stepwise (forward-backward) procedure based on meta-analysis results and identify 14 circulating biomarkers independently associating with all-cause mortality. Overall, these associations are similar in men and women and across different age strata. We subsequently show that the prediction accuracy of 5- and 10-year mortality based on a model containing the identified biomarkers and sex (C-statistic = 0.837 and 0.830, respectively) is better than that of a model containing conventional risk factors for mortality (C-statistic = 0.772 and 0.790, respectively). The use of the identified metabolic profile as a predictor of mortality or surrogate endpoint in clinical studies needs further investigation.
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http://dx.doi.org/10.1038/s41467-019-11311-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6702196PMC
August 2019

Protein-coding variants implicate novel genes related to lipid homeostasis contributing to body-fat distribution.

Nat Genet 2019 03 18;51(3):452-469. Epub 2019 Feb 18.

Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA.

Body-fat distribution is a risk factor for adverse cardiovascular health consequences. We analyzed the association of body-fat distribution, assessed by waist-to-hip ratio adjusted for body mass index, with 228,985 predicted coding and splice site variants available on exome arrays in up to 344,369 individuals from five major ancestries (discovery) and 132,177 European-ancestry individuals (validation). We identified 15 common (minor allele frequency, MAF ≥5%) and nine low-frequency or rare (MAF <5%) coding novel variants. Pathway/gene set enrichment analyses identified lipid particle, adiponectin, abnormal white adipose tissue physiology and bone development and morphology as important contributors to fat distribution, while cross-trait associations highlight cardiometabolic traits. In functional follow-up analyses, specifically in Drosophila RNAi-knockdowns, we observed a significant increase in the total body triglyceride levels for two genes (DNAH10 and PLXND1). We implicate novel genes in fat distribution, stressing the importance of interrogating low-frequency and protein-coding variants.
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http://dx.doi.org/10.1038/s41588-018-0334-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6560635PMC
March 2019

Publisher Correction: Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity.

Nat Genet 2018 05;50(5):766-767

Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany.

In the version of this article originally published, one of the two authors with the name Wei Zhao was omitted from the author list and the affiliations for both authors were assigned to the single Wei Zhao in the author list. In addition, the ORCID for Wei Zhao (Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA) was incorrectly assigned to author Wei Zhou. The errors have been corrected in the HTML and PDF versions of the article.
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http://dx.doi.org/10.1038/s41588-018-0082-3DOI Listing
May 2018

Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity.

Nat Genet 2018 01 22;50(1):26-41. Epub 2017 Dec 22.

Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany.

Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, noncoding variants from which pinpointing causal genes remains challenging. Here we combined data from 718,734 individuals to discover rare and low-frequency (minor allele frequency (MAF) < 5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which 8 variants were in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2 and ZNF169) newly implicated in human obesity, 2 variants were in genes (MC4R and KSR2) previously observed to be mutated in extreme obesity and 2 variants were in GIPR. The effect sizes of rare variants are ~10 times larger than those of common variants, with the largest effect observed in carriers of an MC4R mutation introducing a stop codon (p.Tyr35Ter, MAF = 0.01%), who weighed ~7 kg more than non-carriers. Pathway analyses based on the variants associated with BMI confirm enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically supported therapeutic targets in obesity.
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http://dx.doi.org/10.1038/s41588-017-0011-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5945951PMC
January 2018

New Blood Pressure-Associated Loci Identified in Meta-Analyses of 475 000 Individuals.

Circ Cardiovasc Genet 2017 Oct;10(5)

Background: Genome-wide association studies have recently identified >400 loci that harbor DNA sequence variants that influence blood pressure (BP). Our earlier studies identified and validated 56 single nucleotide variants (SNVs) associated with BP from meta-analyses of exome chip genotype data. An additional 100 variants yielded suggestive evidence of association.

Methods And Results: Here, we augment the sample with 140 886 European individuals from the UK Biobank, in whom 77 of the 100 suggestive SNVs were available for association analysis with systolic BP or diastolic BP or pulse pressure. We performed 2 meta-analyses, one in individuals of European, South Asian, African, and Hispanic descent (pan-ancestry, ≈475 000), and the other in the subset of individuals of European descent (≈423 000). Twenty-one SNVs were genome-wide significant (<5×10) for BP, of which 4 are new BP loci: rs9678851 (missense, ), rs7437940 (), rs13303 (missense, ), and rs1055144 (). In addition, we identified a potentially independent novel BP-associated SNV, rs3416322 (missense, ) at a known locus, uncorrelated with the previously reported SNVs. Two SNVs are associated with expression levels of nearby genes, and SNVs at 3 loci are associated with other traits. One SNV with a minor allele frequency <0.01, (rs3025380 at ) was genome-wide significant.

Conclusions: We report 4 novel loci associated with BP regulation, and 1 independent variant at an established BP locus. This analysis highlights several candidate genes with variation that alter protein function or gene expression for potential follow-up.
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http://dx.doi.org/10.1161/CIRCGENETICS.117.001778DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5776077PMC
October 2017

How close are we to implementing a genetic risk score for coronary heart disease?

Expert Rev Mol Diagn 2017 10 4;17(10):905-915. Epub 2017 Sep 4.

a Centre for Cardiovascular Genetics, BHF Laboratories, Institute of Cardiovascular Science , University College London , London , UK.

Introduction: Genome-wide association meta-analysis have now identified more than 150 loci where common variants (SNPs) are significantly associated with coronary heart disease (CHD) and CHD end points. Areas covered: The authors review publications from their own laboratory and published recently where identified CHD risk SNPs are used in combination, and 'scaled' by their effect size, to create a 'weighted' Genetic risk Score (GRS), which, in combination with an individual's classical CHD risk factors, can be used to identify those at overall low, intermediate and high future risk. Those at highest risk can be offered life-style and therapeutic options to reduce their risk and those at intermediate levels can be monitored. Expert commentary: The authors discuss the selection of the best variants to be included in the GRS, and the potential utility of such scores in different clinical settings. The limitations of the current data sets and the way forward in the next 5 years is discussed.
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http://dx.doi.org/10.1080/14737159.2017.1368388DOI Listing
October 2017

Discovery and replication of SNP-SNP interactions for quantitative lipid traits in over 60,000 individuals.

BioData Min 2017 24;10:25. Epub 2017 Jul 24.

Department of Population Health Sciences, Department of Ophthalmology and Visual Sciences, University of Wisconsin-Madison, Madison, WI USA.

Background: The genetic etiology of human lipid quantitative traits is not fully elucidated, and interactions between variants may play a role. We performed a gene-centric interaction study for four different lipid traits: low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), total cholesterol (TC), and triglycerides (TG).

Results: Our analysis consisted of a discovery phase using a merged dataset of five different cohorts ( = 12,853 to  = 16,849 depending on lipid phenotype) and a replication phase with ten independent cohorts totaling up to 36,938 additional samples. Filters are often applied before interaction testing to correct for the burden of testing all pairwise interactions. We used two different filters: 1. A filter that tested only single nucleotide polymorphisms (SNPs) with a main effect of  < 0.001 in a previous association study. 2. A filter that only tested interactions identified by Biofilter 2.0. Pairwise models that reached an interaction significance level of  < 0.001 in the discovery dataset were tested for replication. We identified thirteen SNP-SNP models that were significant in more than one replication cohort after accounting for multiple testing.

Conclusions: These results may reveal novel insights into the genetic etiology of lipid levels. Furthermore, we developed a pipeline to perform a computationally efficient interaction analysis with multi-cohort replication.
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http://dx.doi.org/10.1186/s13040-017-0145-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5525436PMC
July 2017

Assessment of the clinical utility of adding common single nucleotide polymorphism genetic scores to classical risk factor algorithms in coronary heart disease risk prediction in UK men.

Clin Chem Lab Med 2017 Aug;55(10):1605-1613

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Background: Risk prediction algorithms for coronary heart disease (CHD) are recommended for clinical use. However, their predictive ability remains modest and the inclusion of genetic risk may improve their performance.

Methods: QRISK2 was used to assess CHD risk using conventional risk factors (CRFs). The performance of a 19 single nucleotide polymorphism (SNP) gene score (GS) for CHD including variants identified by genome-wide association study and candidate gene studies (weighted using the results from the CARDIoGRAMplusC4D meta-analysis) was assessed using the second Northwick Park Heart Study (NPHSII) of 2775 healthy UK men (284 cases). To improve the GS, five SNPs with weak evidence of an association with CHD were removed and replaced with seven robustly associated SNPs - giving a 21-SNP GS.

Results: The weighted 19 SNP GS was associated with lipid traits (p<0.05) and CHD after adjustment for CRFs, (OR=1.31 per standard deviation, p=0.03). Addition of the 19 SNP GS to QRISK2 showed improved discrimination (area under the receiver operator characteristic curve 0.68 vs. 0.70 p=0.02), a positive net reclassification index (0.07, p=0.04) compared to QRISK2 alone and maintained good calibration (p=0.17). The 21-SNP GS was also associated with CHD after adjustment for CRFs (OR=1.39 per standard deviation, 1.42×10-3), but the combined QRISK2 plus GS score was poorly calibrated (p=0.03) and showed no improvement in discrimination (p=0.55) or reclassification (p=0.10) compared to QRISK2 alone.

Conclusions: The 19-SNP GS is robustly associated with CHD and showed potential clinical utility in the UK population.
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http://dx.doi.org/10.1515/cclm-2016-0984DOI Listing
August 2017

Rare and low-frequency coding variants alter human adult height.

Nature 2017 02 1;542(7640):186-190. Epub 2017 Feb 1.

Netherlands Comprehensive Cancer Organisation, Utrecht, 3501 DB, The Netherlands.

Height is a highly heritable, classic polygenic trait with approximately 700 common associated variants identified through genome-wide association studies so far. Here, we report 83 height-associated coding variants with lower minor-allele frequencies (in the range of 0.1-4.8%) and effects of up to 2 centimetres per allele (such as those in IHH, STC2, AR and CRISPLD2), greater than ten times the average effect of common variants. In functional follow-up studies, rare height-increasing alleles of STC2 (giving an increase of 1-2 centimetres per allele) compromised proteolytic inhibition of PAPP-A and increased cleavage of IGFBP-4 in vitro, resulting in higher bioavailability of insulin-like growth factors. These 83 height-associated variants overlap genes that are mutated in monogenic growth disorders and highlight new biological candidates (such as ADAMTS3, IL11RA and NOX4) and pathways (such as proteoglycan and glycosaminoglycan synthesis) involved in growth. Our results demonstrate that sufficiently large sample sizes can uncover rare and low-frequency variants of moderate-to-large effect associated with polygenic human phenotypes, and that these variants implicate relevant genes and pathways.
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http://dx.doi.org/10.1038/nature21039DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5302847PMC
February 2017

Genome-wide association analysis identifies novel blood pressure loci and offers biological insights into cardiovascular risk.

Nat Genet 2017 Mar 30;49(3):403-415. Epub 2017 Jan 30.

Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK.

Elevated blood pressure is the leading heritable risk factor for cardiovascular disease worldwide. We report genetic association of blood pressure (systolic, diastolic, pulse pressure) among UK Biobank participants of European ancestry with independent replication in other cohorts, and robust validation of 107 independent loci. We also identify new independent variants at 11 previously reported blood pressure loci. In combination with results from a range of in silico functional analyses and wet bench experiments, our findings highlight new biological pathways for blood pressure regulation enriched for genes expressed in vascular tissues and identify potential therapeutic targets for hypertension. Results from genetic risk score models raise the possibility of a precision medicine approach through early lifestyle intervention to offset the impact of blood pressure-raising genetic variants on future cardiovascular disease risk.
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http://dx.doi.org/10.1038/ng.3768DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5972004PMC
March 2017

Mechanistic insights from combining genomics with metabolomics.

Authors:
Fotios Drenos

Curr Opin Lipidol 2017 Apr;28(2):99-103

MRC Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Oakfield House, Bristol, UK.

Purpose Of Review: Metabolomics directly measure substrates and products of biological processes and pathways. Based on instrumentation and throughput advances, the use of metabolomics has only recently become feasible at the population level. This has led to an intense interest in using the new information in combination with genomics, and other omics technologies, to give biological context to the rapidly accumulating associations between genes and diseases or their risk factors.

Recent Findings: The use of metabolomics-genomic associations for the metabolic characterization of genes of interest has confirmed known pathways and permitted the identification of new ones. These include the unknown metabolite X12063 linking statins to myopathies, the role of glycerophospholipids in cholesterol metabolism, the structure of lipoprotein (a), the lipoprotein lipase-independent effect of Apolipoprotein C-III coding and the role of branched chain amino acids in the antagonistic coregulation of levels of HDLs and triglyceride.

Summary: The findings reviewed illustrate the importance of integrating metabolomics and genomics for the greater understanding of biological mechanisms. The limitations of the current approaches are also discussed together with approaches that will be required to make the most of the current multiomics data available.
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http://dx.doi.org/10.1097/MOL.0000000000000393DOI Listing
April 2017

Metabolic signatures of birthweight in 18 288 adolescents and adults.

Int J Epidemiol 2016 10;45(5):1539-1550

Department of Genomics and Biomarkers, National Institute for Health and Welfare, Helsinki, Finland.

Background: Lower birthweight is associated with increased susceptibility to cardiometabolic diseases in adulthood, but the underlying molecular pathways are incompletely understood. We examined associations of birthweight with a comprehensive metabolic profile measured in adolescents and adults.

Methods: High-throughput nuclear magnetic resonance metabolomics and biochemical assays were used to quantify 87 circulating metabolic measures in seven cohorts from Finland and the UK, comprising altogether 18 288 individuals (mean age 26 years, range 15-75). Metabolic associations with birthweight were assessed by linear regression models adjusted for sex, gestational age and age at blood sampling. The metabolic associations with birthweight were compared with the corresponding associations with adult body mass index (BMI).

Results: Lower birthweight adjusted for gestational age was adversely associated with cardiometabolic biomarkers, including lipoprotein subclasses, fatty acids, amino acids and markers of inflammation and impaired liver function (P < 0.0015 for 46 measures). Associations were consistent across cohorts with different ages at metabolic profiling, but the magnitudes were weak. The pattern of metabolic deviations associated with lower birthweight resembled the metabolic signature of higher adult BMI (R = 0.77) assessed at the same time as the metabolic profiling. The resemblance indicated that 1 kg lower birthweight is associated with similar metabolic aberrations as caused by 0.92 units higher BMI in adulthood.

Conclusions: Lower birthweight adjusted for gestational age is associated with adverse biomarker aberrations across multiple metabolic pathways. Coherent metabolic signatures between lower birthweight and higher adult adiposity suggest that shared molecular pathways may potentially underpin the metabolic deviations. However, the magnitudes of metabolic associations with birthweight are modest in comparison to the effects of adiposity, implying that birthweight is only a weak indicator of the metabolic risk profile in adulthood.
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http://dx.doi.org/10.1093/ije/dyw255DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5100627PMC
October 2016

Identifying gene-gene interactions that are highly associated with four quantitative lipid traits across multiple cohorts.

Hum Genet 2017 02 15;136(2):165-178. Epub 2016 Nov 15.

Institute for Quantitative Biomedical Sciences at Dartmouth, Hanover, NH, USA.

Genetic loci explain only 25-30 % of the heritability observed in plasma lipid traits. Epistasis, or gene-gene interactions may contribute to a portion of this missing heritability. Using the genetic data from five NHLBI cohorts of 24,837 individuals, we combined the use of the quantitative multifactor dimensionality reduction (QMDR) algorithm with two SNP-filtering methods to exhaustively search for SNP-SNP interactions that are associated with HDL cholesterol (HDL-C), LDL cholesterol (LDL-C), total cholesterol (TC) and triglycerides (TG). SNPs were filtered either on the strength of their independent effects (main effect filter) or the prior knowledge supporting a given interaction (Biofilter). After the main effect filter, QMDR identified 20 SNP-SNP models associated with HDL-C, 6 associated with LDL-C, 3 associated with TC, and 10 associated with TG (permutation P value <0.05). With the use of Biofilter, we identified 2 SNP-SNP models associated with HDL-C, 3 associated with LDL-C, 1 associated with TC and 8 associated with TG (permutation P value <0.05). In an independent dataset of 7502 individuals from the eMERGE network, we replicated 14 of the interactions identified after main effect filtering: 11 for HDL-C, 1 for LDL-C and 2 for TG. We also replicated 23 of the interactions found to be associated with TG after applying Biofilter. Prior knowledge supports the possible role of these interactions in the genetic etiology of lipid traits. This study also presents a computationally efficient pipeline for analyzing data from large genotyping arrays and detecting SNP-SNP interactions that are not primarily driven by strong main effects.
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http://dx.doi.org/10.1007/s00439-016-1738-7DOI Listing
February 2017

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

Meta-analysis identifies common and rare variants influencing blood pressure and overlapping with metabolic trait loci.

Nat Genet 2016 10 12;48(10):1162-70. Epub 2016 Sep 12.

Bill and Melinda Gates Foundation, Seattle, Washington, USA.

Meta-analyses of association results for blood pressure using exome-centric single-variant and gene-based tests identified 31 new loci in a discovery stage among 146,562 individuals, with follow-up and meta-analysis in 180,726 additional individuals (total n = 327,288). These blood pressure-associated loci are enriched for known variants for cardiometabolic traits. Associations were also observed for the aggregation of rare and low-frequency missense variants in three genes, NPR1, DBH, and PTPMT1. In addition, blood pressure associations at 39 previously reported loci were confirmed. The identified variants implicate biological pathways related to cardiometabolic traits, vascular function, and development. Several new variants are inferred to have roles in transcription or as hubs in protein-protein interaction networks. Genetic risk scores constructed from the identified variants were strongly associated with coronary disease and myocardial infarction. This large collection of blood pressure-associated loci suggests new therapeutic strategies for hypertension, emphasizing a link with cardiometabolic risk.
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http://dx.doi.org/10.1038/ng.3660DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5320952PMC
October 2016

Trans-ancestry meta-analyses identify rare and common variants associated with blood pressure and hypertension.

Nat Genet 2016 10 12;48(10):1151-1161. Epub 2016 Sep 12.

Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, NIH, Bethesda, Maryland, USA.

High blood pressure is a major risk factor for cardiovascular disease and premature death. However, there is limited knowledge on specific causal genes and pathways. To better understand the genetics of blood pressure, we genotyped 242,296 rare, low-frequency and common genetic variants in up to 192,763 individuals and used ∼155,063 samples for independent replication. We identified 30 new blood pressure- or hypertension-associated genetic regions in the general population, including 3 rare missense variants in RBM47, COL21A1 and RRAS with larger effects (>1.5 mm Hg/allele) than common variants. Multiple rare nonsense and missense variant associations were found in A2ML1, and a low-frequency nonsense variant in ENPEP was identified. Our data extend the spectrum of allelic variation underlying blood pressure traits and hypertension, provide new insights into the pathophysiology of hypertension and indicate new targets for clinical intervention.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5056636PMC
http://dx.doi.org/10.1038/ng.3654DOI Listing
October 2016

Cystatin C and Cardiovascular Disease: A Mendelian Randomization Study.

J Am Coll Cardiol 2016 08;68(9):934-45

Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig-Maximilians-University Munich, Munich, Germany; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany.

Background: Epidemiological studies show that high circulating cystatin C is associated with risk of cardiovascular disease (CVD), independent of creatinine-based renal function measurements. It is unclear whether this relationship is causal, arises from residual confounding, and/or is a consequence of reverse causation.

Objectives: The aim of this study was to use Mendelian randomization to investigate whether cystatin C is causally related to CVD in the general population.

Methods: We incorporated participant data from 16 prospective cohorts (n = 76,481) with 37,126 measures of cystatin C and added genetic data from 43 studies (n = 252,216) with 63,292 CVD events. We used the common variant rs911119 in CST3 as an instrumental variable to investigate the causal role of cystatin C in CVD, including coronary heart disease, ischemic stroke, and heart failure.

Results: Cystatin C concentrations were associated with CVD risk after adjusting for age, sex, and traditional risk factors (relative risk: 1.82 per doubling of cystatin C; 95% confidence interval [CI]: 1.56 to 2.13; p = 2.12 × 10(-14)). The minor allele of rs911119 was associated with decreased serum cystatin C (6.13% per allele; 95% CI: 5.75 to 6.50; p = 5.95 × 10(-211)), explaining 2.8% of the observed variation in cystatin C. Mendelian randomization analysis did not provide evidence for a causal role of cystatin C, with a causal relative risk for CVD of 1.00 per doubling cystatin C (95% CI: 0.82 to 1.22; p = 0.994), which was statistically different from the observational estimate (p = 1.6 × 10(-5)). A causal effect of cystatin C was not detected for any individual component of CVD.

Conclusions: Mendelian randomization analyses did not support a causal role of cystatin C in the etiology of CVD. As such, therapeutics targeted at lowering circulating cystatin C are unlikely to be effective in preventing CVD.
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http://dx.doi.org/10.1016/j.jacc.2016.05.092DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5451109PMC
August 2016

Variant rs10911021 that associates with coronary heart disease in type 2 diabetes, is associated with lower concentrations of circulating HDL cholesterol and large HDL particles but not with amino acids.

Cardiovasc Diabetol 2016 08 22;15(1):115. Epub 2016 Aug 22.

Centre for Cardiovascular Genetics, British Heart Foundation Laboratories, Institute of Cardiovascular Science, University College London, University Street, London, UK.

Aims: An intergenic locus on chromosome 1 (lead SNP rs10911021) was previously associated with coronary heart disease (CHD) in type 2 diabetes (T2D). Using data from the UCLEB consortium we investigated the relationship between rs10911021 and CHD in T2D, whether rs10911021 was associated with levels of amino acids involved in the γ-glutamyl cycle or any conventional risk factors (CRFs) for CHD in the T2D participants.

Methods: Four UCLEB studies (n = 6531) had rs10911021 imputation, CHD in T2D, CRF and metabolomics data determined using a nuclear magnetic resonance based platform.

Results: The expected direction of effect between rs10911021 and CHD in T2D was observed (1377 no CHD/160 CHD; minor allele OR 0.80, 95 % CI 0.60-1.06) although this was not statistically significant (p = 0.13). No association between rs10911021 and CHD was seen in non-T2D participants (11218 no CHD/1274 CHD; minor allele OR 1.00 95 % CIs 0.92-1.10). In T2D participants, while no associations were observed between rs10911021 and the nine amino acids measured, rs10911021 was associated with HDL-cholesterol (p = 0.0005) but the minor "protective" allele was associated with lower levels (-0.034 mmol/l per allele). Focusing more closely on the HDL-cholesterol subclasses measured, we observed that rs10911021 was associated with six large HDL particle measures in T2D (all p < 0.001). No significant associations were seen in non-T2D subjects.

Conclusions: Our findings are consistent with a true association between rs10911021 and CHD in T2D. The protective minor allele was associated with lower HDL-cholesterol and reductions in HDL particle traits. Our results indicate a complex relationship between rs10911021 and CHD in T2D.
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http://dx.doi.org/10.1186/s12933-016-0435-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4994200PMC
August 2016

Marginal role for 53 common genetic variants in cardiovascular disease prediction.

Heart 2016 10 30;102(20):1640-7. Epub 2016 Jun 30.

Centre for Cardiovascular Genetics, Institute of Cardiovascular Science, University College London, London, UK.

Objective: We investigated discrimination and calibration of cardiovascular disease (CVD) risk scores when genotypic was added to phenotypic information. The potential of genetic information for those at intermediate risk by a phenotype-based risk score was assessed.

Methods: Data were from seven prospective studies including 11 851 individuals initially free of CVD or diabetes, with 1444 incident CVD events over 10 years' follow-up. We calculated a score from 53 CVD-related single nucleotide polymorphisms and an established CVD risk equation 'QRISK-2' comprising phenotypic measures. The area under the receiver operating characteristic curve (AUROC), detection rate for given false-positive rate (FPR) and net reclassification improvement (NRI) index were estimated for gene scores alone and in addition to the QRISK-2 CVD risk score. We also evaluated use of genetic information only for those at intermediate risk according to QRISK-2.

Results: The AUROC was 0.635 for QRISK-2 alone and 0.623 with addition of the gene score. The detection rate for 5% FPR improved from 11.9% to 12.0% when the gene score was added. For a 10-year CVD risk cut-off point of 10%, the NRI was 0.25% when the gene score was added to QRISK-2. Applying the genetic risk score only to those with QRISK-2 risk of 10%-<20% and prescribing statins where risk exceeded 20% suggested that genetic information could prevent one additional event for every 462 people screened.

Conclusion: The gene score produced minimal incremental population-wide utility over phenotypic risk prediction of CVD. Tailored prediction using genetic information for those at intermediate risk may have clinical utility.
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http://dx.doi.org/10.1136/heartjnl-2016-309298DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5099215PMC
October 2016

Replication and Characterization of Association between ABO SNPs and Red Blood Cell Traits by Meta-Analysis in Europeans.

PLoS One 2016 9;11(6):e0156914. Epub 2016 Jun 9.

Centre for Cardiovascular Genetics, Institute of Cardiovascular Science, University College London, London, United Kingdom.

Red blood cell (RBC) traits are routinely measured in clinical practice as important markers of health. Deviations from the physiological ranges are usually a sign of disease, although variation between healthy individuals also occurs, at least partly due to genetic factors. Recent large scale genetic studies identified loci associated with one or more of these traits; further characterization of known loci and identification of new loci is necessary to better understand their role in health and disease and to identify potential molecular mechanisms. We performed meta-analysis of Metabochip association results for six RBC traits-hemoglobin concentration (Hb), hematocrit (Hct), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), mean corpuscular volume (MCV) and red blood cell count (RCC)-in 11 093 Europeans from seven studies of the UCL-LSHTM-Edinburgh-Bristol (UCLEB) Consortium. We identified 394 non-overlapping SNPs in five loci at genome-wide significance: 6p22.1-6p21.33 (with HFE among others), 6q23.2 (with HBS1L among others), 6q23.3 (contains no genes), 9q34.3 (only ABO gene) and 22q13.1 (with TMPRSS6 among others), replicating previous findings of association with RBC traits at these loci and extending them by imputation to 1000 Genomes. We further characterized associations between ABO SNPs and three traits: hemoglobin, hematocrit and red blood cell count, replicating them in an independent cohort. Conditional analyses indicated the independent association of each of these traits with ABO SNPs and a role for blood group O in mediating the association. The 15 most significant RBC-associated ABO SNPs were also associated with five cardiometabolic traits, with discordance in the direction of effect between groups of traits, suggesting that ABO may act through more than one mechanism to influence cardiometabolic risk.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0156914PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4900668PMC
July 2017

Metabolic Characterization of a Rare Genetic Variation Within APOC3 and Its Lipoprotein Lipase-Independent Effects.

Circ Cardiovasc Genet 2016 Jun 25;9(3):231-9. Epub 2016 Apr 25.

From the MRC Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol (F.D., G.D.S., M.A.-K., D.A.L., T.R.G., N.J.T.); Institute of Cardiovascular Science, University College London, London, United Kingdom (F.D., C.D., J.-P.C.); Computational Medicine, Faculty of Medicine, University of Oulu & Biocenter Oulu, Oulu (M.A.-K., J.K., P.W., P.S., A.J.K.); NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio (M.A.-K., J.K., P.S.); Public Health Genomics Unit, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland (J.K.); and Department of Non-communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom (C.D., J.-P.C.).

Background: Plasma triglyceride levels have been implicated in atherosclerosis and coronary heart disease. Apolipoprotein C-III (APOC3) plays a key role in the hydrolysis of triglyceride-rich lipoproteins to remnant particles by lipoprotein lipase (LPL) and their uptake by the liver. A rare variant in APOC3(rs138326449) has been associated with triglyceride, very low-density lipoprotein, and high-density lipoprotein levels, as well as risk of coronary heart disease. We aimed to characterize the impact of this locus across a broad set of mainly lipids-focused metabolic measures.

Methods And Results: A high-throughput serum nuclear magnetic resonance metabolomics platform was used to quantify 225 metabolic measures in 13 285 participants from 2 European population cohorts. We analyzed the effect of the APOC3 variant on the metabolic measures and used the common LPL(rs12678919) polymorphism to test for LPL-independent effects. Eighty-one metabolic measures showed evidence of association with APOC3(rs138326449). In addition to previously reported triglyceride and high-density lipoprotein associations, the variant was also associated with very low-density lipoprotein and high-density lipoprotein composition measures, other cholesterol measures, and fatty acids. Comparison of the APOC3 and LPL associations revealed that APOC3 association results for medium and very large very low-density lipoprotein composition are unlikely to be solely predictable by the action of APOC3 through LPL.

Conclusions: We characterized the effects of the rare APOC3(rs138326449) loss of function mutation in lipoprotein metabolism, as well as the effects of LPL(rs12678919). Our results improve our understanding of the role of APOC3 in triglyceride metabolism, its LPL independent action, and the complex and correlated nature of human metabolites.
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http://dx.doi.org/10.1161/CIRCGENETICS.115.001302DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4920206PMC
June 2016

A genetic risk score is associated with statin-induced low-density lipoprotein cholesterol lowering.

Pharmacogenomics 2016 04 5;17(6):583-91. Epub 2016 Apr 5.

Julius Center for Health Sciences & Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands.

Aim: To find new genetic loci associated with statin response, and to investigate the association of a genetic risk score (GRS) with this outcome.

Patients & Methods: In a discovery meta-analysis (five studies, 1991 individuals), we investigated the effects of approximately 50000 single nucleotide polymorphisms on statin response, following up associations with p < 1 × 10(-4) (three independent studies, 5314 individuals). We further assessed the effect of a GRS based on SNPs in ABCG2, LPA and APOE.

Results: No new SNPs were found associated with statin response. The GRS was associated with reduced statin response: 0.0394 mmol/l per allele (95% CI: 0.0171-0.0617, p = 5.37 × 10(-4)).

Conclusion: The GRS was associated with statin response, but the small effect size (˜2% of the average low-density lipoprotein cholesterol reduction) limits applicability.
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http://dx.doi.org/10.2217/pgs.16.8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5558527PMC
April 2016
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