Publications by authors named "Benjamin B Sun"

14 Publications

  • Page 1 of 1

A fast and efficient colocalization algorithm for identifying shared genetic risk factors across multiple traits.

Nat Commun 2021 02 3;12(1):764. Epub 2021 Feb 3.

Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK.

Genome-wide association studies (GWAS) have identified thousands of genomic regions affecting complex diseases. The next challenge is to elucidate the causal genes and mechanisms involved. One approach is to use statistical colocalization to assess shared genetic aetiology across multiple related traits (e.g. molecular traits, metabolic pathways and complex diseases) to identify causal pathways, prioritize causal variants and evaluate pleiotropy. We propose HyPrColoc (Hypothesis Prioritisation for multi-trait Colocalization), an efficient deterministic Bayesian algorithm using GWAS summary statistics that can detect colocalization across vast numbers of traits simultaneously (e.g. 100 traits can be jointly analysed in around 1 s). We perform a genome-wide multi-trait colocalization analysis of coronary heart disease (CHD) and fourteen related traits, identifying 43 regions in which CHD colocalized with ≥1 trait, including 5 previously unknown CHD loci. Across the 43 loci, we further integrate gene and protein expression quantitative trait loci to identify candidate causal genes.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41467-020-20885-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7858636PMC
February 2021

Phenome-wide Mendelian randomization mapping the influence of the plasma proteome on complex diseases.

Nat Genet 2020 10 7;52(10):1122-1131. Epub 2020 Sep 7.

MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Bristol, UK.

The human proteome is a major source of therapeutic targets. Recent genetic association analyses of the plasma proteome enable systematic evaluation of the causal consequences of variation in plasma protein levels. Here we estimated the effects of 1,002 proteins on 225 phenotypes using two-sample Mendelian randomization (MR) and colocalization. Of 413 associations supported by evidence from MR, 130 (31.5%) were not supported by results of colocalization analyses, suggesting that genetic confounding due to linkage disequilibrium is widespread in naïve phenome-wide association studies of proteins. Combining MR and colocalization evidence in cis-only analyses, we identified 111 putatively causal effects between 65 proteins and 52 disease-related phenotypes ( https://www.epigraphdb.org/pqtl/ ). Evaluation of data from historic drug development programs showed that target-indication pairs with MR and colocalization support were more likely to be approved, evidencing the value of this approach in identifying and prioritizing potential therapeutic targets.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41588-020-0682-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7610464PMC
October 2020

Genome-wide association meta-analyses and fine-mapping elucidate pathways influencing albuminuria.

Nat Commun 2019 09 11;10(1):4130. Epub 2019 Sep 11.

Department of Medicine, Division of Nephrology and Hypertension, University of Utah, Salt Lake City, UT, USA.

Increased levels of the urinary albumin-to-creatinine ratio (UACR) are associated with higher risk of kidney disease progression and cardiovascular events, but underlying mechanisms are incompletely understood. Here, we conduct trans-ethnic (n = 564,257) and European-ancestry specific meta-analyses of genome-wide association studies of UACR, including ancestry- and diabetes-specific analyses, and identify 68 UACR-associated loci. Genetic correlation analyses and risk score associations in an independent electronic medical records database (n = 192,868) reveal connections with proteinuria, hyperlipidemia, gout, and hypertension. Fine-mapping and trans-Omics analyses with gene expression in 47 tissues and plasma protein levels implicate genes potentially operating through differential expression in kidney (including TGFB1, MUC1, PRKCI, and OAF), and allow coupling of UACR associations to altered plasma OAF concentrations. Knockdown of OAF and PRKCI orthologs in Drosophila nephrocytes reduces albumin endocytosis. Silencing fly PRKCI further impairs slit diaphragm formation. These results generate a priority list of genes and pathways for translational research to reduce albuminuria.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41467-019-11576-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6739370PMC
September 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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41588-018-0321-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6397078PMC
March 2019

Interleukin-6 Receptor Signaling and Abdominal Aortic Aneurysm Growth Rates.

Circ Genom Precis Med 2019 02;12(2):e002413

Division of Cardiovascular Medicine (M.C., F.L., J.R., C.G., A.F., J.H., Z.M.), University of Cambridge, United Kingdom.

Background: The Asp358Ala variant (rs2228145; A>C) in the IL (interleukin)-6 receptor ( IL6R) gene has been implicated in the development of abdominal aortic aneurysms (AAAs), but its effect on AAA growth over time is not known. We aimed to investigate the clinical association between the IL6R-Asp358Ala variant and AAA growth and to assess the effect of blocking the IL-6 signaling pathway in mouse models of aortic aneurysm rupture or dissection.

Methods: Using data from 2863 participants with AAA from 9 prospective cohorts, age- and sex-adjusted mixed-effects linear regression models were used to estimate the association between the IL6R-Asp358Ala variant and annual change in AAA diameter (mm/y). In a series of complementary randomized trials in mice, the effect of blocking the IL-6 signaling pathways was assessed on plasma biomarkers, systolic blood pressure, aneurysm diameter, and time to aortic rupture and death.

Results: After adjusting for age and sex, baseline aneurysm size was 0.55 mm (95% CI, 0.13-0.98 mm) smaller per copy of the minor allele [C] of the Asp358Ala variant. Change in AAA growth was -0.06 mm per year (-0.18 to 0.06) per copy of the minor allele; a result that was not statistically significant. Although all available worldwide data were used, the genetic analyses were not powered for an effect size as small as that observed. In 2 mouse models of AAA, selective blockage of the IL-6 trans-signaling pathway, but not combined blockage of both, the classical and trans-signaling pathways, was associated with improved survival ( P<0.05).

Conclusions: Our proof-of-principle data are compatible with the concept that IL-6 trans-signaling is relevant to AAA growth, encouraging larger-scale evaluation of this hypothesis.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1161/CIRCGEN.118.002413DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6383754PMC
February 2019

ProGeM: a framework for the prioritization of candidate causal genes at molecular quantitative trait loci.

Nucleic Acids Res 2019 01;47(1):e3

MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK.

Quantitative trait locus (QTL) mapping of molecular phenotypes such as metabolites, lipids and proteins through genome-wide association studies represents a powerful means of highlighting molecular mechanisms relevant to human diseases. However, a major challenge of this approach is to identify the causal gene(s) at the observed QTLs. Here, we present a framework for the 'Prioritization of candidate causal Genes at Molecular QTLs' (ProGeM), which incorporates biological domain-specific annotation data alongside genome annotation data from multiple repositories. We assessed the performance of ProGeM using a reference set of 227 previously reported and extensively curated metabolite QTLs. For 98% of these loci, the expert-curated gene was one of the candidate causal genes prioritized by ProGeM. Benchmarking analyses revealed that 69% of the causal candidates were nearest to the sentinel variant at the investigated molecular QTLs, indicating that genomic proximity is the most reliable indicator of 'true positive' causal genes. In contrast, cis-gene expression QTL data led to three false positive candidate causal gene assignments for every one true positive assignment. We provide evidence that these conclusions also apply to other molecular phenotypes, suggesting that ProGeM is a powerful and versatile tool for annotating molecular QTLs. ProGeM is freely available via GitHub.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1093/nar/gky837DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6326795PMC
January 2019

Author Correction: Genome-wide mapping of plasma protein QTLs identifies putatively causal genes and pathways for cardiovascular disease.

Nat Commun 2018 09 18;9(1):3853. Epub 2018 Sep 18.

Framingham Heart Study, Framingham, 01702, MA, USA.

In the originally published version of this Article, financial support was not fully acknowledged. The sentence "KS was supported by the 'Biomedical Research Program' funds at Weill Cornell Medicine in Qatar, a program funded by the Qatar Foundation" has been added to the acknowledgement section in both the PDF and HTML versions of the Article.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41467-018-06231-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6143533PMC
September 2018

Genome-wide mapping of plasma protein QTLs identifies putatively causal genes and pathways for cardiovascular disease.

Nat Commun 2018 08 15;9(1):3268. Epub 2018 Aug 15.

Framingham Heart Study, Framingham, 01702, MA, USA.

Identifying genetic variants associated with circulating protein concentrations (protein quantitative trait loci; pQTLs) and integrating them with variants from genome-wide association studies (GWAS) may illuminate the proteome's causal role in disease and bridge a knowledge gap regarding SNP-disease associations. We provide the results of GWAS of 71 high-value cardiovascular disease proteins in 6861 Framingham Heart Study participants and independent external replication. We report the mapping of over 16,000 pQTL variants and their functional relevance. We provide an integrated plasma protein-QTL database. Thirteen proteins harbor pQTL variants that match coronary disease-risk variants from GWAS or test causal for coronary disease by Mendelian randomization. Eight of these proteins predict new-onset cardiovascular disease events in Framingham participants. We demonstrate that identifying pQTLs, integrating them with GWAS results, employing Mendelian randomization, and prospectively testing protein-trait associations holds potential for elucidating causal genes, proteins, and pathways for cardiovascular disease and may identify targets for its prevention and treatment.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41467-018-05512-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6093935PMC
August 2018

Genomic atlas of the human plasma proteome.

Nature 2018 06 6;558(7708):73-79. Epub 2018 Jun 6.

MRL, Merck & Co., Inc., Kenilworth, NJ, USA.

Although plasma proteins have important roles in biological processes and are the direct targets of many drugs, the genetic factors that control inter-individual variation in plasma protein levels are not well understood. Here we characterize the genetic architecture of the human plasma proteome in healthy blood donors from the INTERVAL study. We identify 1,927 genetic associations with 1,478 proteins, a fourfold increase on existing knowledge, including trans associations for 1,104 proteins. To understand the consequences of perturbations in plasma protein levels, we apply an integrated approach that links genetic variation with biological pathway, disease, and drug databases. We show that protein quantitative trait loci overlap with gene expression quantitative trait loci, as well as with disease-associated loci, and find evidence that protein biomarkers have causal roles in disease using Mendelian randomization analysis. By linking genetic factors to diseases via specific proteins, our analyses highlight potential therapeutic targets, opportunities for matching existing drugs with new disease indications, and potential safety concerns for drugs under development.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41586-018-0175-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6697541PMC
June 2018

Mendelian randomization with fine-mapped genetic data: Choosing from large numbers of correlated instrumental variables.

Genet Epidemiol 2017 12 25;41(8):714-725. Epub 2017 Sep 25.

Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom.

Mendelian randomization uses genetic variants to make causal inferences about the effect of a risk factor on an outcome. With fine-mapped genetic data, there may be hundreds of genetic variants in a single gene region any of which could be used to assess this causal relationship. However, using too many genetic variants in the analysis can lead to spurious estimates and inflated Type 1 error rates. But if only a few genetic variants are used, then the majority of the data is ignored and estimates are highly sensitive to the particular choice of variants. We propose an approach based on summarized data only (genetic association and correlation estimates) that uses principal components analysis to form instruments. This approach has desirable theoretical properties: it takes the totality of data into account and does not suffer from numerical instabilities. It also has good properties in simulation studies: it is not particularly sensitive to varying the genetic variants included in the analysis or the genetic correlation matrix, and it does not have greatly inflated Type 1 error rates. Overall, the method gives estimates that are less precise than those from variable selection approaches (such as using a conditional analysis or pruning approach to select variants), but are more robust to seemingly arbitrary choices in the variable selection step. Methods are illustrated by an example using genetic associations with testosterone for 320 genetic variants to assess the effect of sex hormone related pathways on coronary artery disease risk, in which variable selection approaches give inconsistent inferences.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1002/gepi.22077DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5725678PMC
December 2017

Fifteen new risk loci for coronary artery disease highlight arterial-wall-specific mechanisms.

Nat Genet 2017 Jul 22;49(7):1113-1119. Epub 2017 May 22.

Charles Bronfman Institute for Personalized Medicine, Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

Coronary artery disease (CAD) is a leading cause of morbidity and mortality worldwide. Although 58 genomic regions have been associated with CAD thus far, most of the heritability is unexplained, indicating that additional susceptibility loci await identification. An efficient discovery strategy may be larger-scale evaluation of promising associations suggested by genome-wide association studies (GWAS). Hence, we genotyped 56,309 participants using a targeted gene array derived from earlier GWAS results and performed meta-analysis of results with 194,427 participants previously genotyped, totaling 88,192 CAD cases and 162,544 controls. We identified 25 new SNP-CAD associations (P < 5 × 10, in fixed-effects meta-analysis) from 15 genomic regions, including SNPs in or near genes involved in cellular adhesion, leukocyte migration and atherosclerosis (PECAM1, rs1867624), coagulation and inflammation (PROCR, rs867186 (p.Ser219Gly)) and vascular smooth muscle cell differentiation (LMOD1, rs2820315). Correlation of these regions with cell-type-specific gene expression and plasma protein levels sheds light on potential disease mechanisms.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/ng.3874DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5555387PMC
July 2017

PhenoScanner: a database of human genotype-phenotype associations.

Bioinformatics 2016 10 17;32(20):3207-3209. Epub 2016 Jun 17.

Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK NIHR Blood and Transplant Research Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK.

PhenoScanner is a curated database of publicly available results from large-scale genetic association studies. This tool aims to facilitate 'phenome scans', the cross-referencing of genetic variants with many phenotypes, to help aid understanding of disease pathways and biology. The database currently contains over 350 million association results and over 10 million unique genetic variants, mostly single nucleotide polymorphisms. It is accompanied by a web-based tool that queries the database for associations with user-specified variants, providing results according to the same effect and non-effect alleles for each input variant. The tool provides the option of searching for trait associations with proxies of the input variants, calculated using the European samples from 1000 Genomes and Hapmap.

Availability And Implementation: PhenoScanner is available at www.phenoscanner.medschl.cam.ac.uk CONTACT: jrs95@medschl.cam.ac.ukSupplementary information: Supplementary data are available at Bioinformatics online.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5048068PMC
http://dx.doi.org/10.1093/bioinformatics/btw373DOI Listing
October 2016

Conventional protein kinase C isoforms differentially regulate ADP- and thrombin-evoked Ca²⁺ signalling in human platelets.

Cell Calcium 2015 Dec 28;58(6):577-88. Epub 2015 Sep 28.

Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge CB2 3EG, United Kingdom; Institute for Science and Technology in Medicine, Keele University, Guy Hilton Research Centre, Thornburrow Drive, Hartshill, Stoke-on-Trent ST4 7QB, United Kingdom. Electronic address:

Rises in cytosolic Ca(2+) concentration ([Ca(2+)]cyt) are central in platelet activation, yet many aspects of the underlying mechanisms are poorly understood. Most studies examine how experimental manipulations affect agonist-evoked rises in [Ca(2+)]cyt, but these only monitor the net effect of manipulations on the processes controlling [Ca(2+)]cyt (Ca(2+) buffering, sequestration, release, entry and removal), and cannot resolve the source of the Ca(2+) or the transporters or channels affected. To investigate the effects of protein kinase C (PKC) on platelet Ca(2+) signalling, we here monitor Ca(2+) flux around the platelet by measuring net Ca(2+) fluxes to or from the extracellular space and the intracellular Ca(2+) stores, which act as the major sources and sinks for Ca(2+) influx into and efflux from the cytosol, as well as monitoring the cytosolic Na(+) concentration ([Na(+)]cyt), which influences platelet Ca(2+) fluxes via Na(+)/Ca(2+) exchange. The intracellular store Ca(2+) concentration ([Ca(2+)]st) was monitored using Fluo-5N, the extracellular Ca(2+) concentration ([Ca(2+)]ext) was monitored using Fluo-4 whilst [Ca(2+)]cyt and [Na(+)]cyt were monitored using Fura-2 and SFBI, respectively. PKC inhibition using Ro-31-8220 or bisindolylmaleimide I potentiated ADP- and thrombin-evoked rises in [Ca(2+)]cyt in the absence of extracellular Ca(2+). PKC inhibition potentiated ADP-evoked but reduced thrombin-evoked intracellular Ca(2+) release and Ca(2+) removal into the extracellular medium. SERCA inhibition using thapsigargin and 2,5-di(tert-butyl) l,4-benzohydroquinone abolished the effect of PKC inhibitors on ADP-evoked changes in [Ca(2+)]cyt but only reduced the effect on thrombin-evoked responses. Thrombin evokes substantial rises in [Na(+)]cyt which would be expected to reduce Ca(2+) removal via the Na(+)/Ca(2+) exchanger (NCX). Thrombin-evoked rises in [Na(+)]cyt were potentiated by PKC inhibition, an effect which was not due to altered changes in non-selective cation permeability of the plasma membrane as assessed by Mn(2+) quench of Fura-2 fluorescence. PKC inhibition was without effect on thrombin-evoked rises in [Ca(2+)]cyt following SERCA inhibition and either removal of extracellular Na(+) or inhibition of Na(+)/K(+)-ATPase activity by removal of extracellular K(+) or treatment with digoxin. These data suggest that PKC limits ADP-evoked rises in [Ca(2+)]cyt by acceleration of SERCA activity, whilst rises in [Ca(2+)]cyt evoked by the stronger platelet activator thrombin are limited by PKC through acceleration of both SERCA and Na(+)/K(+)-ATPase activity, with the latter limiting the effect of thrombin on rises in [Na(+)]cyt and so forward mode NCX activity. The use of selective PKC inhibitors indicated that conventional and not novel PKC isoforms are responsible for the inhibition of agonist-evoked Ca(2+) signalling.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.ceca.2015.09.005DOI Listing
December 2015