Publications
145 results found
Wheeler E, Leong A, Liu C-T, et al., 2017, Impact of common genetic determinants of Hemoglobin A1c on type 2 diabetes risk and diagnosis in ancestrally diverse populations: A transethnic genome-wide meta-analysis., PLoS Medicine, Vol: 14, ISSN: 1549-1277
BACKGROUND: Glycated hemoglobin (HbA1c) is used to diagnose type 2 diabetes (T2D) and assess glycemic control in patients with diabetes. Previous genome-wide association studies (GWAS) have identified 18 HbA1c-associated genetic variants. These variants proved to be classifiable by their likely biological action as erythrocytic (also associated with erythrocyte traits) or glycemic (associated with other glucose-related traits). In this study, we tested the hypotheses that, in a very large scale GWAS, we would identify more genetic variants associated with HbA1c and that HbA1c variants implicated in erythrocytic biology would affect the diagnostic accuracy of HbA1c. We therefore expanded the number of HbA1c-associated loci and tested the effect of genetic risk-scores comprised of erythrocytic or glycemic variants on incident diabetes prediction and on prevalent diabetes screening performance. Throughout this multiancestry study, we kept a focus on interancestry differences in HbA1c genetics performance that might influence race-ancestry differences in health outcomes. METHODS & FINDINGS: Using genome-wide association meta-analyses in up to 159,940 individuals from 82 cohorts of European, African, East Asian, and South Asian ancestry, we identified 60 common genetic variants associated with HbA1c. We classified variants as implicated in glycemic, erythrocytic, or unclassified biology and tested whether additive genetic scores of erythrocytic variants (GS-E) or glycemic variants (GS-G) were associated with higher T2D incidence in multiethnic longitudinal cohorts (N = 33,241). Nineteen glycemic and 22 erythrocytic variants were associated with HbA1c at genome-wide significance. GS-G was associated with higher T2D risk (incidence OR = 1.05, 95% CI 1.04-1.06, per HbA1c-raising allele, p = 3 × 10-29); whereas GS-E was not (OR = 1.00, 95% CI 0.99-1.01, p = 0.60). In Europeans and Asians, erythrocytic variants in aggregate had only modest effects on the diagnostic
Zhao W, Rasheed A, Tikkanen E, et al., 2017, Identification of new susceptibility loci for type 2 diabetes and shared etiological pathways with coronary heart disease, Nature Genetics, Vol: 49, Pages: 1450-+, ISSN: 1061-4036
To evaluate the shared genetic etiology of type 2 diabetes (T2D) and coronary heart disease (CHD), we conducted a genome-wide, multi-ancestry study of genetic variation for both diseases in up to 265,678 subjects for T2D and 260,365 subjects for CHD. We identify 16 previously unreported loci for T2D and 1 locus for CHD, including a new T2D association at a missense variant in HLA-DRB5 (odds ratio (OR) = 1.29). We show that genetically mediated increase in T2D risk also confers higher CHD risk. Joint T2D–CHD analysis identified eight variants—two of which are coding—where T2D and CHD associations appear to colocalize, including a new joint T2D–CHD association at the CCDC92 locus that also replicated for T2D. The variants associated with both outcomes implicate new pathways as well as targets of existing drugs, including icosapent ethyl and adipocyte fatty-acid-binding protein.
Graff M, Scott RA, Justice AE, et al., 2017, Correction: Genome-wide physical activity interactions in adiposity - A meta-analysis of 200,452 adults., PLoS Genetics, Vol: 13, ISSN: 1553-7390
[This corrects the article DOI: 10.1371/journal.pgen.1006528.].
Poulter NR, et al, 2017, Novel Blood Pressure Locus and Gene Discovery Using Genome-Wide Association Study and Expression Data Sets From Blood and the Kidney, Hypertension, Vol: 70, Pages: e4-e19, ISSN: 0194-911X
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 HSPB7, TNXB, LRP12, LOC283335, SEPT9, and AKT2, and provide new replication evidence for a further 2 signals in EBF2 and NFKBIA. 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.
Zillikens MC, Demissie S, Hsu Y-H, et al., 2017, Large meta-analysis of genome-wide association studies identifies five loci for lean body mass, NATURE COMMUNICATIONS, Vol: 8, ISSN: 2041-1723
Lean body mass, consisting mostly of skeletal muscle, is important for healthy aging. We performed a genome-wide association study for whole body (20 cohorts of European ancestry with n = 38,292) and appendicular (arms and legs) lean body mass (n = 28,330) measured using dual energy X-ray absorptiometry or bioelectrical impedance analysis, adjusted for sex, age, height, and fat mass. Twenty-one single-nucleotide polymorphisms were significantly associated with lean body mass either genome wide (p < 5 × 10−8) or suggestively genome wide (p < 2.3 × 10−6). Replication in 63,475 (47,227 of European ancestry) individuals from 33 cohorts for whole body lean body mass and in 45,090 (42,360 of European ancestry) subjects from 25 cohorts for appendicular lean body mass was successful for five single-nucleotide polymorphisms in/near HSD17B11, VCAN, ADAMTSL3, IRS1, and FTO for total lean body mass and for three single-nucleotide polymorphisms in/near VCAN, ADAMTSL3, and IRS1 for appendicular lean body mass. Our findings provide new insight into the genetics of lean body mass.
Tachmazidou I, Suveges D, Min JL, et al., 2017, Whole-genome sequencing coupled to imputation discovers genetic signals for anthropometric traits, American Journal of Human Genetics, Vol: 100, Pages: 865-884, ISSN: 0002-9297
Deep sequence-based imputation can enhance the discovery power of genome-wide association studies by assessing previously unexplored variation across the common- and low-frequency spectra. We applied a hybrid whole-genome sequencing (WGS) and deep imputation approach to examine the broader allelic architecture of 12 anthropometric traits associated with height, body mass, and fat distribution in up to 267,616 individuals. We report 106 genome-wide significant signals that have not been previously identified, including 9 low-frequency variants pointing to functional candidates. Of the 106 signals, 6 are in genomic regions that have not been implicated with related traits before, 28 are independent signals at previously reported regions, and 72 represent previously reported signals for a different anthropometric trait. 71% of signals reside within genes and fine mapping resolves 23 signals to one or two likely causal variants. We confirm genetic overlap between human monogenic and polygenic anthropometric traits and find signal enrichment in cis expression QTLs in relevant tissues. Our results highlight the potential of WGS strategies to enhance biologically relevant discoveries across the frequency spectrum.
Saleheen D, Zhao W, Young R, et al., 2017, Loss of Cardioprotective Effects at the ADAMTS7 Locus as a Result of Gene-Smoking Interactions, CIRCULATION, Vol: 135, Pages: 2336-+, ISSN: 0009-7322
Graff M, Scott RA, Justice AE, et al., 2017, Genome-wide physical activity interactions in adiposity. A meta-analysis of 200,452 adults, PLOS GENETICS, Vol: 13, ISSN: 1553-7404
Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423) or other ancestry (n = 20,029). We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by ~30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive to PA. In additional genome-wide meta-analyses adjusting for PA and interaction with PA, we identify 11 novel adiposity loci, suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discovery.
Justice AE, Winkler TW, Feitosa MF, et al., 2017, Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits, NATURE COMMUNICATIONS, Vol: 8, ISSN: 2041-1723
Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting for environment in genetic analyses. Our results suggest that tobacco smoking may alter the genetic susceptibility to overall adiposity and body fat distribution.
Böger CA, Gorski M, McMahon GM, et al., 2017, NFAT5 and SLC4A10 Loci Associate with Plasma Osmolality., Journal of the American Society of Nephrology, Vol: 28, ISSN: 1533-3450
Disorders of water balance, an excess or deficit of total body water relative to body electrolyte content, are common and ascertained by plasma hypo- or hypernatremia, respectively. We performed a two-stage genome-wide association study meta-analysis on plasma sodium concentration in 45,889 individuals of European descent (stage 1 discovery) and 17,637 additional individuals of European descent (stage 2 replication), and a transethnic meta-analysis of replicated single-nucleotide polymorphisms in 79,506 individuals (63,526 individuals of European descent, 8765 individuals of Asian Indian descent, and 7215 individuals of African descent). In stage 1, we identified eight loci associated with plasma sodium concentration at P<5.0 × 10(-6) Of these, rs9980 at NFAT5 replicated in stage 2 meta-analysis (P=3.1 × 10(-5)), with combined stages 1 and 2 genome-wide significance of P=5.6 × 10(-10) Transethnic meta-analysis further supported the association at rs9980 (P=5.9 × 10(-12)). Additionally, rs16846053 at SLC4A10 showed nominally, but not genome-wide, significant association in combined stages 1 and 2 meta-analysis (P=6.7 × 10(-8)). NFAT5 encodes a ubiquitously expressed transcription factor that coordinates the intracellular response to hypertonic stress but was not previously implicated in the regulation of systemic water balance. SLC4A10 encodes a sodium bicarbonate transporter with a brain-restricted expression pattern, and variant rs16846053 affects a putative intronic NFAT5 DNA binding motif. The lead variants for NFAT5 and SLC4A10 are cis expression quantitative trait loci in tissues of the central nervous system and relevant to transcriptional regulation. Thus, genetic variation in NFAT5 and SLC4A10 expression and function in the central nervous system may affect the regulation of systemic water balance.
Marouli E, Graff M, Medina-Gomez C, et al., 2017, Rare and low-frequency coding variants alter human adult height, Nature, Vol: 542, Pages: 186-190, ISSN: 0028-0836
Heightis a highly heritable, classic polygenic traitwith~700common associated variants identified so far through genome-wide association studies. Here,we report 83 height-associated codingvariants with lowerminor allele frequencies(range of0.1-4.8%)and effects ofup to 2 16cm/allele(e.g.in IHH, STC2, ARand CRISPLD2), >10timesthe average effect of common variants.In functional follow-upstudies,rare height-increasing allelesof STC2(+1-2 cm/allele) compromisedproteolytic inhibition of PAPP-A and increased cleavage of IGFBP-4in vitro, resulting in higher bioavailability of insulin-like growth factors.These 83height-associated variants overlapgenes mutated in monogenic growth disordersand highlight new biological candidates (e.g. ADAMTS3, IL11RA, NOX4) and pathways (e.g. proteoglycan/glycosaminoglycan synthesis)involved in growth.Our results demonstratethatsufficiently large sample sizescan uncoverrare and low-frequency variants of moderate to large effect associated with polygenic human phenotypes,andthat these variantsimplicate relevant genes and pathways.
Warren HR, Evangelou E, Cabrera CP, et al., 2017, Genome-wide association analysis identifies novel blood pressure loci and offers biological insights into cardiovascular risk, Nature Genetics, Vol: 49, Pages: 403-415, ISSN: 1546-1718
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.
Brænne I, Zeng L, Willenborg C, et al., 2017, Genomic correlates of glatiramer acetate adverse cardiovascular effects lead to a novel locus mediating coronary risk., PLoS One, Vol: 12
Glatiramer acetate is used therapeutically in multiple sclerosis but also known for adverse effects including elevated coronary artery disease (CAD) risk. The mechanisms underlying the cardiovascular side effects of the medication are unclear. Here, we made use of the chromosomal variation in the genes that are known to be affected by glatiramer treatment. Focusing on genes and gene products reported by drug-gene interaction database to interact with glatiramer acetate we explored a large meta-analysis on CAD genome-wide association studies aiming firstly, to investigate whether variants in these genes also affect cardiovascular risk and secondly, to identify new CAD risk genes. We traced association signals in a 200-kb region around genomic positions of genes interacting with glatiramer in up to 60 801 CAD cases and 123 504 controls. We validated the identified association in additional 21 934 CAD cases and 76 087 controls. We identified three new CAD risk alleles within the TGFB1 region on chromosome 19 that independently affect CAD risk. The lead SNP rs12459996 was genome-wide significantly associated with CAD in the extended meta-analysis (odds ratio 1.09, p = 1.58×10-12). The other two SNPs at the locus were not in linkage disequilibrium with the lead SNP and by a conditional analysis showed p-values of 4.05 × 10-10 and 2.21 × 10-6. Thus, studying genes reported to interact with glatiramer acetate we identified genetic variants that concordantly with the drug increase the risk of CAD. Of these, TGFB1 displayed signal for association. Indeed, the gene has been associated with CAD previously in both in vivo and in vitro studies. Here we establish genome-wide significant association with CAD in large human samples.
Wahl S, Drong A, Lehne B, et al., 2016, Epigenome-wide association study of body mass index, and the adverse outcomes of adiposity, Nature, Vol: 541, Pages: 81-+, ISSN: 0028-0836
Approximately 1.5 billion people worldwide are overweight oraffected by obesity, and are at risk of developing type 2 diabetes,cardiovascular disease and related metabolic and inflammatorydisturbances1,2. Although the mechanisms linking adiposity toassociated clinical conditions are poorly understood, recent studiessuggest that adiposity may influence DNA methylation3–6, a keyregulator of gene expression and molecular phenotype7. Here weuse epigenome-wide association to show that body mass index(BMI; a key measure of adiposity) is associated with widespreadchanges in DNA methylation (187 genetic loci with P<1×10−7,range P=9.2×10−8 to 6.0×10−46; n=10,261 samples). Geneticassociation analyses demonstrate that the alterations in DNAmethylation are predominantly the consequence of adiposity,rather than the cause. We find that methylation loci are enrichedfor functional genomic features in multiple tissues (P<0.05), andshow that sentinel methylation markers identify gene expressionsignatures at 38 loci (P < 9.0 × 10−6, range P = 5.5 × 10−6 to6.1×10−35, n=1,785 samples). The methylation loci identify genesinvolved in lipid and lipoprotein metabolism, substrate transportand inflammatory pathways. Finally, we show that the disturbancesin DNA methylation predict future development of type 2 diabetes(relative risk per 1 standard deviation increase in methylation riskscore: 2.3 (2.07–2.56); P=1.1×10−54). Our results provide newinsights into the biologic pathways influenced by adiposity, and mayenable development of new strategies for prediction and preventionof type 2 diabetes and other adverse clinical consequences of obesity
Schumann G, Liu C, O'Reilly P, et al., 2016, KLB is associated with alcohol drinking, and its gene product β-Klotho is necessary for FGF21 regulation of alcohol preference, Proceedings of the National Academy of Sciences of the United States of America, Vol: 113, Pages: 14372-14377, ISSN: 1091-6490
Alcohol is a widely consumed drug in western societies that can lead to addiction. A small shift in consumption can have dramatic consequences on public health. We performed the largest genome-wide association metaanalysis and replication study to date (>105,000 individuals) and identified a genetic basis for alcohol consumption during nonaddictive drinking. We found that a locus in the gene encoding β-Klotho is associated with alcohol consumption. β-Klotho is an essential receptor component for the endocrine FGFs, FGF19 and FGF21. Using mouse models and pharmacologic administration of FGF21, we show that β-Klotho in the brain controls alcohol drinking. These findings reveal a mechanism regulating alcohol consumption in humans that may be pharmacologically tractable for reducing alcohol intake.
Ried JS, Jeff JM, Chu AY, et al., 2016, A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape, Nature Communications, Vol: 7, ISSN: 2041-1723
Large consortia have revealed hundreds of genetic loci associated with anthropometric traits,one trait at a time. We examined whether genetic variants affect body shape as a compositephenotype that is represented by a combination of anthropometric traits. We developed anapproach that calculates averaged PCs (AvPCs) representing body shape derived fromsix anthropometric traits (body mass index, height, weight, waist and hip circumference,waist-to-hip ratio). The first four AvPCs explain499% of the variability, are heritable, andassociate with cardiometabolic outcomes. We performed genome-wide association analysesfor each body shape composite phenotype across 65 studies and meta-analysed summarystatistics. We identify six novel loci:LEMD2andCD47for AvPC1,RPS6KA5/C14orf159andGANABfor AvPC3, andARL15andANP32for AvPC4. Our findings highlight the value ofusing multiple traits to define complex phenotypes for discovery, which are not captured bysingle-trait analyses, and may shed light onto new pathways.
Loley C, Alver M, Assimes TL, et al., 2016, No association of coronary artery disease with X-chromosomal variants in comprehensive international meta-analysis, Scientific Reports, Vol: 6, ISSN: 2045-2322
In recent years, genome-wide association studies have identified 58 independent risk loci for coronary artery disease (CAD) on the autosome. However, due to the sex-specific data structure of the X chromosome, it has been excluded from most of these analyses. While females have 2 copies of chromosome X, males have only one. Also, one of the female X chromosomes may be inactivated. Therefore, special test statistics and quality control procedures are required. Thus, little is known about the role of X-chromosomal variants in CAD. To fill this gap, we conducted a comprehensive X-chromosome-wide meta-analysis including more than 43,000 CAD cases and 58,000 controls from 35 international study cohorts. For quality control, sex-specific filters were used to adequately take the special structure of X-chromosomal data into account. For single study analyses, several logistic regression models were calculated allowing for inactivation of one female X-chromosome, adjusting for sex and investigating interactions between sex and genetic variants. Then, meta-analyses including all 35 studies were conducted using random effects models. None of the investigated models revealed genome-wide significant associations for any variant. Although we analyzed the largest-to-date sample, currently available methods were not able to detect any associations of X-chromosomal variants with CAD.
van der Harst P, van Setten J, Verweij N, et al., 2016, 52 Genetic Loci Influencing Myocardial Mass, Journal of the American College of Cardiology, Vol: 68, Pages: 1435-1448, ISSN: 1558-3597
BackgroundMyocardial mass is a key determinant of cardiac muscle function and hypertrophy. Myocardial depolarization leading to cardiac muscle contraction is reflected by the amplitude and duration of the QRS complex on the electrocardiogram (ECG). Abnormal QRS amplitude or duration reflect changes in myocardial mass and conduction, and are associated with increased risk of heart failure and death.ObjectivesThis meta-analysis sought to gain insights into the genetic determinants of myocardial mass.MethodsWe carried out a genome-wide association meta-analysis of 4 QRS traits in up to 73,518 individuals of European ancestry, followed by extensive biological and functional assessment.ResultsWe identified 52 genomic loci, of which 32 are novel, that are reliably associated with 1 or more QRS phenotypes at p < 1 × 10−8. These loci are enriched in regions of open chromatin, histone modifications, and transcription factor binding, suggesting that they represent regions of the genome that are actively transcribed in the human heart. Pathway analyses provided evidence that these loci play a role in cardiac hypertrophy. We further highlighted 67 candidate genes at the identified loci that are preferentially expressed in cardiac tissue and associated with cardiac abnormalities in Drosophila melanogaster and Mus musculus. We validated the regulatory function of a novel variant in the SCN5A/SCN10A locus in vitro and in vivo.ConclusionsTaken together, our findings provide new insights into genes and biological pathways controlling myocardial mass and may help identify novel therapeutic targets.
Iotchkova V, Huang J, Morris JA, et al., 2016, Discovery and refinement of genetic loci associated with cardiometabolic risk using dense imputation maps, Nature Genetics, Vol: 48, Pages: 1303-1312, ISSN: 1061-4036
Large-scale whole genome sequence datasets offer novel opportunities to identify genetic variation underlying human traits. Here we apply genotype imputation based on whole genome sequence data from the UK10K and the 1000 Genomes Projects into 35,981 study participants of European ancestry, followed by association analysis with twenty quantitative cardiometabolic and hematologic traits. We describe 17 novel associations, including six rare (minor allele frequency [MAF]<1%) or low frequency variants (1%<MAF<5%) with platelet count (PLT), red cell indices (MCH, MCV) and high-density lipoprotein (HDL) cholesterol. Applying fine-mapping analysis to 233 known and novel loci associated with the twenty traits, we resolve associations of 59 loci to credible sets of 20 or less variants, and describe trait enrichments within regions of predicted regulatory function. These findings augment understanding of the allelic architecture of risk factors for cardiometabolic and hematologic diseases, and provide additional functional insights with the identification of potentially novel biological targets.
Zhang W, Jerneren F, Lehne BC, et al., 2016, Genome-wide association reveals that common genetic variation in the kallikrein-kinin system is associated with serum L-arginine levels, Thrombosis and Haemostasis, Vol: 116, Pages: 1041-1049, ISSN: 0340-6245
L-arginine is the essential precursor of nitric oxide, and is involved in multiple key physiological processes, including vascular and immune function. The genetic regulation of blood L-arginine levels is largely unknown. We performed a genome-wide association study (GWAS) to identify genetic factors determining serum L-arginine levels, amongst 901 Europeans and 1,394 Indian Asians. We show that common genetic variations at the KLKB1 and F12 loci are strongly associated with serum L-arginine levels. The G allele of single nucleotide polymorphism (SNP) rs71640036 (T/G) in KLKB1 is associated with lower serum L-arginine concentrations (10 µmol/l per allele copy, p=1×10–24), while allele T of rs2545801 (T/C) near the F12 gene is associated with lower serum L-arginine levels (7 µmol/l per allele copy, p=7×10–12). Together these two loci explain 7 % of the total variance in serum L-arginine concentrations. The associations at both loci were replicated in independent cohorts with plasma L-arginine measurements (p<0.004). The two sentinel SNPs are in nearly complete LD with the nonsynonymous SNP rs3733402 at KLKB1 and the 5’-UTR SNP rs1801020 at F12, respectively. SNPs at both loci are associated with blood pressure. Our findings provide new insight into the genetic regulation of L-arginine and its potential relationship with cardiovascular risk.
Surendran P, Drenos F, Young R, et al., 2016, Trans-ancestry meta-analyses identify rare and common variants associated with blood pressure and hypertension, Nature Genetics, Vol: 48, Pages: 1151-1161, ISSN: 1546-1718
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 ~192,000 individuals, and used ~155,063 samples for independent replication. We identified 31 novel blood pressure or hypertension associated genetic regions in the general population, including three rare missense variants in RBM47, COL21A1 and RRAS with larger effects (>1.5mmHg/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.
Ehret GB, Ferreira T, Chasman DI, et al., 2016, The genetics of blood pressure regulation and its target organs from association studies in 342,415 individuals, Nature Genetics, Vol: 48, Pages: 1171-1184, ISSN: 1546-1718
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.
Kanoni S, Masca NG, Stirrups KE, et al., 2016, Analysis with the exome array identifies multiple new independent variants in lipid loci., Human Molecular Genetics, Vol: 25, Pages: 4094-4106, ISSN: 1460-2083
It has been hypothesized that low frequency (1-5% minor allele frequency (MAF)) and rare (<1% MAF) variants with large effect sizes may contribute to the missing heritability in complex traits. Here, we report an association analysis of lipid traits (total cholesterol, LDL-cholesterol, HDL-cholesterol triglycerides) in up to 27 312 individuals with a comprehensive set of low frequency coding variants (ExomeChip), combined with conditional analysis in the known lipid loci. No new locus reached genome-wide significance. However, we found a new lead variant in 26 known lipid association regions of which 16 were >1000-fold more significant than the previous sentinel variant and not in close LD (six had MAF <5%). Furthermore, conditional analysis revealed multiple independent signals (ranging from 1 to 5) in a third of the 98 lipid loci tested, including rare variants. Addition of our novel associations resulted in between 1.5- and 2.5-fold increase in the proportion of heritability explained for the different lipid traits. Our findings suggest that rare coding variants contribute to the genetic architecture of lipid traits.
Fuchsberger C, Flannick J, Teslovich TM, et al., 2016, The genetic architecture of type 2 diabetes., Nature, Vol: 536, Pages: 41-47, ISSN: 0028-0836
The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of the heritability of this disease. Here, to test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole-genome sequencing in 2,657 European individuals with and without diabetes, and exome sequencing in 12,940 individuals from five ancestry groups. To increase statistical power, we expanded the sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support the idea that lower-frequency variants have a major role in predisposition to type 2 diabetes.
Winkler TW, Justice AE, Graff M, et al., 2016, Correction: The Influence of Age and Sex on Genetic Associations with Adult Body Size and Shape: A Large-Scale Genome-Wide Interaction Study, PLOS Genetics, Vol: 12, Pages: e1006166-e1006166, ISSN: 1553-7390
Scott WR, Zhang W, Loh M, et al., 2016, Investigation of Genetic Variation Underlying Central Obesity amongst South Asians, PLOS One, Vol: 11, ISSN: 1932-6203
ArticleAuthorsMetricsCommentsRelated ContentAbstractIntroductionMaterials and MethodsResultsDiscussion and ConclusionSupporting InformationAcknowledgmentsAuthor ContributionsReferencesReader Comments (0)Media Coverage (0)FiguresAbstractSouth Asians are 1/4 of the world’s population and have increased susceptibility to central obesity and related cardiometabolic disease. Knowledge of genetic variants affecting risk of central obesity is largely based on genome-wide association studies of common SNPs in Europeans. To evaluate the contribution of DNA sequence variation to the higher levels of central obesity (defined as waist hip ratio adjusted for body mass index, WHR) among South Asians compared to Europeans we carried out: i) a genome-wide association analysis of >6M genetic variants in 10,318 South Asians with focused analysis of population-specific SNPs; ii) an exome-wide association analysis of ~250K SNPs in protein-coding regions in 2,637 South Asians; iii) a comparison of risk allele frequencies and effect sizes of 48 known WHR SNPs in 12,240 South Asians compared to Europeans. In genome-wide analyses, we found no novel associations between common genetic variants and WHR in South Asians at P<5x10-8; variants showing equivocal association with WHR (P<1x10-5) did not replicate at P<0.05 in an independent cohort of South Asians (N = 1,922) or in published, predominantly European meta-analysis data. In the targeted analyses of 122,391 population-specific SNPs we also found no associations with WHR in South Asians at P<0.05 after multiple testing correction. Exome-wide analyses showed no new associations between genetic variants and WHR in South Asians, either individually at P<1.5x10-6 or grouped by gene locus at P<2.5x10−6. At known WHR loci, risk allele frequencies were not higher in South Asians compared to Europeans (P = 0.77), while effect sizes were unexpectedly smaller in South Asians than Europeans (P<5.0x10-8). Our find
Lehne B, Drong AW, Loh M, et al., 2016, Erratum to: A coherent approach for analysis of the Illumina HumanMethylation450 BeadChip improves data quality and performance in epigenome-wide association studies., Genome Biology, Vol: 17, ISSN: 1474-760X
Zhang W, Wang F, Wang Y, et al., 2016, pH and near-infrared light dual-stimuli responsive drug delivery using DNA-conjugated gold nanorods for effective treatment of multidrug resistant cancer cells., J Control Release, Vol: 232, Pages: 9-19
A thiolated pH-responsive DNA conjugated gold nanorod (GNR) was developed as a multifunctional nanocarrier for targeted, pH-and near infrared (NIR) radiation dual-stimuli triggered drug delivery. It was further passivated by a thiolated poly(ethylene glycol)-biotin to improve its cancer targeting ability by specific binding to cancer cell over-expressed biotin receptors. Doxorubicin (DOX), a widely used clinical anticancer drug, was conveniently loaded into nanocarrier by intercalating inside the double-stranded pH-responsive DNAs on the GNR surface to complete the construction of the multifunctional nanomedicine. The nanomedicine can rapidly and effectively release its DOX payload triggered by an acidic pH environment (pH~5) and/or applying an 808nm NIR laser radiation. Compared to free DOX, the biotin-modified nanomedicine displayed greatly increased cell uptake and significantly reduced drug efflux by model multidrug resistant (MDR) breast cancer cell lines (MCF-7/ADR). The application of NIR radiation further increased the DOX release and facilitated its nuclear accumulation. As a result, this new DNA-GNR based multifunctional nanomedicine exerted greatly increased potency (~67 fold) against the MDR cancer cells over free DOX.
van Leeuwen EM, Sabo A, Bis JC, et al., 2016, Meta-analysis of 49 549 individuals imputed with the 1000 Genomes Project reveals an exonic damaging variant in ANGPTL4 determining fasting TG levels, Journal of Medical Genetics, Vol: 53, Pages: 441-449, ISSN: 1468-6244
BACKGROUND: So far, more than 170 loci have been associated with circulating lipid levels through genome-wide association studies (GWAS). These associations are largely driven by common variants, their function is often not known, and many are likely to be markers for the causal variants. In this study we aimed to identify more new rare and low-frequency functional variants associated with circulating lipid levels. METHODS: We used the 1000 Genomes Project as a reference panel for the imputations of GWAS data from ∼60 000 individuals in the discovery stage and ∼90 000 samples in the replication stage. RESULTS: Our study resulted in the identification of five new associations with circulating lipid levels at four loci. All four loci are within genes that can be linked biologically to lipid metabolism. One of the variants, rs116843064, is a damaging missense variant within the ANGPTL4 gene. CONCLUSIONS: This study illustrates that GWAS with high-scale imputation may still help us unravel the biological mechanism behind circulating lipid levels.
Horikoshi M, Pasquali L, Wiltshire S, et al., 2016, Transancestral fine-mapping of four type 2 diabetes susceptibility loci highlights potential causal regulatory mechanisms, Human Molecular Genetics, Vol: 25, Pages: 2070-2081, ISSN: 1460-2083
To gain insight into potential regulatory mechanisms through which the effects of variants at four established type 2 diabetes (T2D) susceptibility loci (CDKAL1, CDKN2A-B, IGF2BP2 and KCNQ1) are mediated, we undertook transancestral fine-mapping in 22 086 cases and 42 539 controls of East Asian, European, South Asian, African American and Mexican American descent. Through high-density imputation and conditional analyses, we identified seven distinct association signals at these four loci, each with allelic effects on T2D susceptibility that were homogenous across ancestry groups. By leveraging differences in the structure of linkage disequilibrium between diverse populations, and increased sample size, we localised the variants most likely to drive each distinct association signal. We demonstrated that integration of these genetic fine-mapping data with genomic annotation can highlight potential causal regulatory elements in T2D-relevant tissues. These analyses provide insight into the mechanisms through which T2D association signals are mediated, and suggest future routes to understanding the biology of specific disease susceptibility loci.
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