Imperial College London

DrAbbasDehghan

Faculty of MedicineSchool of Public Health

Reader in Cardiometabolic Disease Epidemiology
 
 
 
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Contact

 

+44 (0)20 7594 3347a.dehghan CV

 
 
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Location

 

157Norfolk PlaceSt Mary's Campus

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Summary

 

Publications

Publication Type
Year
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270 results found

Bentham J, Di Cesare M, Stevens GA, Zhou B, Bixby H, Cowan M, Fortunato L, Bennett J, Danaei G, Hajifathalian K, Lu Y, Riley LM, Laxmaiah A, Kontis V, Paciorek CJ, Riboli E, Ezzati M, Chan Q, Elliott P, Gunter M, Hihtaniemi IT, Murphy N, Norat T, Riboli E, Vineis P, NCD Risk Factor Collaboration NCD-RisCet al., 2016, A century of trends in adult human height, eLife, Vol: 5, ISSN: 2050-084X

Being taller is associated with enhanced longevity, and higher education and earnings. We reanalysed 1472 population-based studies, with measurement of height on more than 18.6 million participants to estimate mean height for people born between 1896 and 1996 in 200 countries. The largest gain in adult height over the past century has occurred in South Korean women and Iranian men, who became 20.2 cm (95% credible interval 17.5–22.7) and 16.5 cm (13.3–19.7) taller, respectively. In contrast, there was little change in adult height in some sub-Saharan African countries and in South Asia over the century of analysis. The tallest people over these 100 years are men born in the Netherlands in the last quarter of 20th century, whose average heights surpassed 182.5 cm, and the shortest were women born in Guatemala in 1896 (140.3 cm; 135.8–144.8). The height differential between the tallest and shortest populations was 19-20 cm a century ago, and has remained the same for women and increased for men a century later despite substantial changes in the ranking of countries.

Journal article

Amin N, Jovanova O, Adams HHH, Dehghan A, Kavousi M, Vernooij MW, Peeters RP, de Vrij FMS, van der Lee SJ, van Rooij JGJ, van Leeuwen EM, Chaker L, Demirkan A, Hofman A, Brouwer RWW, Kraaij R, van Dijk KW, Hankemeier T, van Ijcken WFJ, Uitterlinden AG, Niessen WJ, Franco OH, Kushner SA, Ikram MA, Tiemeier H, van Duijn CMet al., 2016, Exome-sequencing in a large population-based study reveals a rare Asn396Ser variant in the LIPG gene associated with depressive symptoms, MOLECULAR PSYCHIATRY, Vol: 22, Pages: 537-543, ISSN: 1359-4184

Journal article

Dhana K, Nano J, Ligthart S, Peeters A, Hofman A, Nusselder W, Dehghan A, Franco OHet al., 2016, Obesity and Life Expectancy with and without Diabetes in Adults Aged 55 Years and Older in the Netherlands: A Prospective Cohort Study, PLoS Medicine, Vol: 13, ISSN: 1549-1277

BackgroundOverweight and obesity are associated with increased risk of type 2 diabetes. Limited evidenceexists regarding the effect of excess weight on years lived with and without diabetes.We aimed to determine the association of overweight and obesity with the number of yearslived with and without diabetes in a middle-aged and elderly population.Methods and FindingsThe study included 6,499 individuals (3,656 women) aged 55 y and older from the population-basedRotterdam Study. We developed a multistate life table to calculate life expectancyfor individuals who were normal weight, overweight, and obese and the difference inyears lived with and without diabetes. For life table calculations, we used prevalence, incidencerate, and hazard ratios (HRs) for three transitions (healthy to diabetes, healthy todeath, and diabetes to death), stratifying by body mass index (BMI) at baseline and adjustingfor confounders. During a median follow-up of 11.1 y, we observed 697 incident diabetesevents and 2,192 overall deaths. Obesity was associated with an increased risk of developingdiabetes (HR: 2.13 [p < 0.001] for men and 3.54 [p < 0.001] for women). Overweightand obesity were not associated with mortality in men and women with or without diabetes.Total life expectancy remained unaffected by overweight and obesity. Nevertheless, menwith obesity aged 55 y and older lived 2.8 (95% CI −6.1 to −0.1) fewer y without diabetesthan normal weight individuals, whereas, for women, the difference between obese and normalweight counterparts was 4.7 (95% CI −9.0 to −0.6) y. Men and women with obesity lived2.8 (95% CI 0.6 to 6.2) and 5.3 (95% CI 1.6 to 9.3) y longer with diabetes, respectively, comparedto their normal weight counterparts. Since the implications of these findings could be limited to middle-aged and older white European populations, our results need confirmationin other populations.ConclusionsObesity in the middle aged and elderly is associated with

Journal article

Pankratz N, Schick UM, Zhou Y, Zhou W, Ahluwalia TS, Allende ML, Auer PL, Bork-Jensen J, Brody JA, Chen M-H, Clavo V, Eicher JD, Grarup N, Hagedorn EJ, Hu B, Hunker K, Johnson AD, Leusink M, Lu Y, Lyytikainen L-P, Manichaikul A, Marioni RE, Nalls MA, Pazoki R, Smith AV, van Rooij FJA, Yang M-L, Zhang X, Zhang Y, Asselbergs FW, Boerwinkle E, Borecki IB, Bottinger EP, Cushman M, de Bakker PIW, Deary IJ, Dong L, Feitosa MF, Floyd JS, Franceschini N, Franco OH, Garcia ME, Grove ML, Gudnason V, Hansen T, Harris TB, Hofman A, Jackson RD, Jia J, Kahonen M, Launer LJ, Lehtimaki T, Liewald DC, Linneberg A, Liu Y, Loos RJF, Nguyen VM, Numans ME, Pedersen O, Psaty BM, Raitakari OT, Rich SS, Rivadeneira F, Di Sant AMR, Rotter JI, Starr JM, Taylor KD, Thuesen BH, Tracy RP, Uitterlinden AG, Wang J, Wang J, Dehghan A, Huo Y, Cupples LA, Wilson JG, Proia RL, Zon LI, O'Donnell CJ, Reiner AP, Ganesh SKet al., 2016, Meta-analysis of rare and common exome chip variants identifies S1PR4 and other loci influencing blood cell traits, NATURE GENETICS, Vol: 48, Pages: 867-+, ISSN: 1061-4036

Journal article

Tajuddin SM, Schick UM, Eicher JD, Chami N, Giri A, Brody JA, Hill WD, Kacprowski T, Li J, Lyytikäinen LP, Manichaikul A, Mihailov E, O'Donoghue ML, Pankratz N, Pazoki R, Polfus LM, Smith AV, Schurmann C, Vacchi-Suzzi C, Waterworth DM, Evangelou E, Yanek LR, Burt A, Chen MH, van Rooij FJ, Floyd JS, Greinacher A, Harris TB, Highland HM, Lange LA, Liu Y, Mägi R, Nalls MA, Mathias RA, Nickerson DA, Nikus K, Starr JM, Tardif JC, Tzoulaki I, Velez Edwards DR, Wallentin L, Bartz TM, Becker LC, Denny JC, Raffield LM, Rioux JD, Friedrich N, Fornage M, Gao H, Hirschhorn JN, Liewald DC, Rich SS, Uitterlinden A, Bastarache L, Becker DM, Boerwinkle E, de Denus S, Bottinger EP, Hayward C, Hofman A, Homuth G, Lange E, Launer LJ, Lehtimäki T, Lu Y, Metspalu A, O'Donnell CJ, Quarells RC, Richard M, Torstenson ES, Taylor KD, Vergnaud AC, Zonderman AB, Crosslin DR, Deary IJ, Dörr M, Elliott P, Evans MK, Gudnason V, Kähönen M, Psaty BM, Rotter JI, Slater AJ, Dehghan A, White HD, Ganesh SK, Loos RJ, Esko T, Faraday N, Wilson JG, Cushman M, Johnson AD, Edwards TL, Zakai NA, Lettre G, Reiner AP, Auer PLet al., 2016, Large-scale exome-wide association analysis identifies loci for white blood cell traits and pleiotropy with immune-mediated diseases, American Journal of Human Genetics, Vol: 99, Pages: 22-39, ISSN: 1537-6605

White blood cells play diverse roles in innate and adaptive immunity. Genetic association analyses of phenotypic variation in circulating white blood cell (WBC) counts from large samples of otherwise healthy individuals can provide insights into genes and biologic pathways involved in production, differentiation, or clearance of particular WBC lineages (myeloid, lymphoid) and also potentially inform the genetic basis of autoimmune, allergic, and blood diseases. We performed an exome array-based meta-analysis of total WBC and subtype counts (neutrophils, monocytes, lymphocytes, basophils, and eosinophils) in a multi-ancestry discovery and replication sample of ∼157,622 individuals from 25 studies. We identified 16 common variants (8 of which were coding variants) associated with one or more WBC traits, the majority of which are pleiotropically associated with autoimmune diseases. Based on functional annotation, these loci included genes encoding surface markers of myeloid, lymphoid, or hematopoietic stem cell differentiation (CD69, CD33, CD87), transcription factors regulating lineage specification during hematopoiesis (ASXL1, IRF8, IKZF1, JMJD1C, ETS2-PSMG1), and molecules involved in neutrophil clearance/apoptosis (C10orf54, LTA), adhesion (TNXB), or centrosome and microtubule structure/function (KIF9, TUBD1). Together with recent reports of somatic ASXL1 mutations among individuals with idiopathic cytopenias or clonal hematopoiesis of undetermined significance, the identification of a common regulatory 3' UTR variant of ASXL1 suggests that both germline and somatic ASXL1 mutations contribute to lower blood counts in otherwise asymptomatic individuals. These association results shed light on genetic mechanisms that regulate circulating WBC counts and suggest a prominent shared genetic architecture with inflammatory and autoimmune diseases.

Journal article

Eicher JD, Chami N, Kacprowski T, Nomura A, Chen MH, Yanek LR, Tajuddin SM, Schick UM, Slater AJ, Pankratz N, Polfus L, Schurmann C, Giri A, Brody JA, Lange LA, Manichaikul A, Hill WD, Pazoki R, Elliot P, Evangelou E, Tzoulaki I, Gao H, Vergnaud AC, Mathias RA, Becker DM, Becker LC, Burt A, Crosslin DR, Lyytikäinen LP, Nikus K, Hernesniemi J, Kähönen M, Raitoharju E, Mononen N, Raitakari OT, Lehtimäki T, Cushman M, Zakai NA, Nickerson DA, Raffield LM, Quarells R, Willer CJ, Peloso GM, Abecasis GR, Liu DJ, Global Lipids Genetics Consortium, Deloukas P, Samani NJ, Schunkert H, Erdmann J, CARDIoGRAM Exome Consortium, Myocardial Infarction Genetics Consortium, Fornage M, Richard M, Tardif JC, Rioux JD, Dube MP, de Denus S, Lu Y, Bottinger EP, Loos RJ, Smith AV, Harris TB, Launer LJ, Gudnason V, Velez Edwards DR, Torstenson ES, Liu Y, Tracy RP, Rotter JI, Rich SS, Highland HM, Boerwinkle E, Li J, Lange E, Wilson JG, Mihailov E, Mägi R, Hirschhorn J, Metspalu A, Esko T, Vacchi-Suzzi C, Nalls MA, Zonderman AB, Evans MK, Engström G, Orho-Melander M, Melander O, O'Donoghue ML, Waterworth DM, Wallentin L, White HD, Floyd JS, Bartz TM, Rice KM, Psaty BM, Starr JM, Liewald DC, Hayward C, Deary IJ, Greinacher A, Völker U, Thiele T, Völzke H, van Rooij FJ, Uitterlinden AG, Franco OH, Dehghan A, Edwards TL, Ganesh SK, Kathiresan S, Faraday N, Auer PL, Reiner AP, Lettre G, Johnson ADet al., 2016, Platelet-Related Variants Identified by Exomechip Meta-analysis in 157,293 Individuals, American Journal of Human Genetics, Vol: 99, Pages: 40-55, ISSN: 1537-6605

Platelet production, maintenance, and clearance are tightly controlled processes indicative of platelets' important roles in hemostasis and thrombosis. Platelets are common targets for primary and secondary prevention of several conditions. They are monitored clinically by complete blood counts, specifically with measurements of platelet count (PLT) and mean platelet volume (MPV). Identifying genetic effects on PLT and MPV can provide mechanistic insights into platelet biology and their role in disease. Therefore, we formed the Blood Cell Consortium (BCX) to perform a large-scale meta-analysis of Exomechip association results for PLT and MPV in 157,293 and 57,617 individuals, respectively. Using the low-frequency/rare coding variant-enriched Exomechip genotyping array, we sought to identify genetic variants associated with PLT and MPV. In addition to confirming 47 known PLT and 20 known MPV associations, we identified 32 PLT and 18 MPV associations not previously observed in the literature across the allele frequency spectrum, including rare large effect (FCER1A), low-frequency (IQGAP2, MAP1A, LY75), and common (ZMIZ2, SMG6, PEAR1, ARFGAP3/PACSIN2) variants. Several variants associated with PLT/MPV (PEAR1, MRVI1, PTGES3) were also associated with platelet reactivity. In concurrent BCX analyses, there was overlap of platelet-associated variants with red (MAP1A, TMPRSS6, ZMIZ2) and white (PEAR1, ZMIZ2, LY75) blood cell traits, suggesting common regulatory pathways with shared genetic architecture among these hematopoietic lineages. Our large-scale Exomechip analyses identified previously undocumented associations with platelet traits and further indicate that several complex quantitative hematological, lipid, and cardiovascular traits share genetic factors.

Journal article

Ghanbari M, Ikram MA, De Looper HWJ, Hofman A, Erkeland SJ, Franco OH, Dehghan Aet al., 2016, Genome-wide identification of microRNA-related variants associated with risk of Alzheimer's disease, Scientific Reports, Vol: 6, ISSN: 2045-2322

MicroRNAs (miRNAs) serve as key post-Transcriptional regulators of gene expression. Genetic variation in miRNAs and miRNA-binding sites may affect miRNA function and contribute to disease risk. Here, we investigated the extent to which variants within miRNA-related sequences could constitute a part of the functional variants involved in developing Alzheimer's disease (AD), using the largest available genome-wide association study of AD. First, among 237 variants in miRNAs, we found rs2291418 in the miR-1229 precursor to be significantly associated with AD (p-value = 6.8 × 10 â '5, OR = 1.2). Our in-silico analysis and in-vitro miRNA expression experiments demonstrated that the variant's mutant allele enhances the production of miR-1229-3p. Next, we found miR-1229-3p target genes that are associated with AD and might mediate the miRNA function. We demonstrated that miR-1229-3p directly controls the expression of its top AD-Associated target gene (SORL1) using luciferase reporter assays. Additionally, we showed that miR-1229-3p and SORL1 are both expressed in the human brain. Second, among 42,855 variants in miRNA-binding sites, we identified 10 variants (in the 3′ UTR of 9 genes) that are significantly associated with AD, including rs6857 that increases the miR-320e-mediated regulation of PVRL2. Collectively, this study shows that miRNA-related variants are associated with AD and suggests miRNA-dependent regulation of several AD genes.

Journal article

Prins BP, Abbasi A, Wong A, Vaez A, Nolte I, Franceschini N, Stuart PE, Guterriez Achury J, Mistry V, Bradfield JP, Valdes AM, Bras J, Shatunov A, PAGE Consortium, International Stroke Genetics Consortium, Systemic Sclerosis consortium, Treat OA consortium, DIAGRAM Consortium, CARDIoGRAMplusC4D Consortium, ALS consortium, International Parkinsons Disease Genomics Consortium, Autism Spectrum Disorder Working Group of the Psychiatric Genomics Consortium, CKDGen consortium, GERAD1 Consortium, International Consortium for Blood Pressure, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Inflammation Working Group of the CHARGE Consortium, Lu C, Han B, Raychaudhuri S, Bevan S, Mayes MD, Tsoi LC, Evangelou E, Nair RP, Grant SF, Polychronakos C, Radstake TR, van Heel DA, Dunstan ML, Wood NW, Al-Chalabi A, Dehghan A, Hakonarson H, Markus HS, Elder JT, Knight J, Arking DE, Spector TD, Koeleman BP, van Duijn CM, Martin J, Morris AP, Weersma RK, Wijmenga C, Munroe PB, Perry JR, Pouget JG, Jamshidi Y, Snieder H, Alizadeh BZet al., 2016, Investigating the Causal Relationship of C-Reactive Protein with 32 Complex Somatic and Psychiatric Outcomes: A Large-Scale Cross-Consortium Mendelian Randomization Study, PLOS Medicine, Vol: 13, ISSN: 1549-1277

BACKGROUND: C-reactive protein (CRP) is associated with immune, cardiometabolic, and psychiatric traits and diseases. Yet it is inconclusive whether these associations are causal. METHODS AND FINDINGS: We performed Mendelian randomization (MR) analyses using two genetic risk scores (GRSs) as instrumental variables (IVs). The first GRS consisted of four single nucleotide polymorphisms (SNPs) in the CRP gene (GRSCRP), and the second consisted of 18 SNPs that were significantly associated with CRP levels in the largest genome-wide association study (GWAS) to date (GRSGWAS). To optimize power, we used summary statistics from GWAS consortia and tested the association of these two GRSs with 32 complex somatic and psychiatric outcomes, with up to 123,865 participants per outcome from populations of European ancestry. We performed heterogeneity tests to disentangle the pleiotropic effect of IVs. A Bonferroni-corrected significance level of less than 0.0016 was considered statistically significant. An observed p-value equal to or less than 0.05 was considered nominally significant evidence for a potential causal association, yet to be confirmed. The strengths (F-statistics) of the IVs were 31.92-3,761.29 and 82.32-9,403.21 for GRSCRP and GRSGWAS, respectively. CRP GRSGWAS showed a statistically significant protective relationship of a 10% genetically elevated CRP level with the risk of schizophrenia (odds ratio [OR] 0.86 [95% CI 0.79-0.94]; p < 0.001). We validated this finding with individual-level genotype data from the schizophrenia GWAS (OR 0.96 [95% CI 0.94-0.98]; p < 1.72 × 10-6). Further, we found that a standardized CRP polygenic risk score (CRPPRS) at p-value thresholds of 1 × 10-4, 0.001, 0.01, 0.05, and 0.1 using individual-level data also showed a protective effect (OR < 1.00) against schizophrenia; the first CRPPRS (built of SNPs with p < 1 × 10-4) showed a statistically significant (p < 2.45 × 10-4) protective effect with

Journal article

van Loon J, Dehghan A, Tang W, Trompet S, McArdle WL, Asselbergs FW, Chen M-H, Lopez LM, Huffman JE, Leebeek FWG, Basu S, Stott DJ, Rumley A, Gansevoort RT, Davies G, Wilson JJF, Witteman JCM, Cao X, de Craen AJM, Bakker SJL, Psaty BM, Starr JM, Hofman A, Jukema JW, Deary IJ, Hayward C, van der Harst P, Lowe GDO, Folsom AR, Strachan DP, Smith N, de Maat MPM, O'Donnell Cet al., 2016, Genome-wide association studies identify genetic loci for low von Willebrand factor levels (vol 24, pg 1035, 2016), EUROPEAN JOURNAL OF HUMAN GENETICS, Vol: 24, Pages: 1096-1096, ISSN: 1018-4813

Journal article

Ligthart S, Vaez A, Hsu YH, Stolk R, Uitterlinden AG, Hofman A, Alizadeh BZ, Franco OH, Dehghan Aet al., 2016, Bivariate genome-wide association study identifies novel pleiotropic loci for lipids and inflammation, BMC Medical Genomics, Vol: 17, ISSN: 1755-8794

Background: Genome-wide association studies (GWAS) have identified multiple genetic loci for C-reactive protein (CRP) and lipids, of which some overlap. We aimed to identify genetic pleiotropy among CRP and lipids in order to better understand the shared biology of chronic inflammation and lipid metabolism. Results: In a bivariate GWAS, we combined summary statistics of published GWAS on CRP (n = 66,185) and lipids, including LDL-cholesterol, HDL-cholesterol, triglycerides, and total cholesterol (n = 100,184), using an empirical weighted linear-combined test statistic. We sought replication for novel CRP associations in an independent sample of 17,743 genotyped individuals, and performed in silico replication of novel lipid variants in 93,982 individuals. Fifty potentially pleiotropic SNPs were identified among CRP and lipids: 21 for LDL-cholesterol and CRP, 20 for HDL-cholesterol and CRP, 21 for triglycerides, and CRP and 20 for total cholesterol and CRP. We identified and significantly replicated three novel S NPs for CRP in or near CTSB/FDFT1 (rs10435719, P replication : 2.6 × 10 -5 ), STAG1/PCCB (rs7621025, P replication : 1.4 × 10 -3 ) and FTO (rs1558902, P replication : 2.7 × 10 -5 ). Seven pleiotropic lipid loci were replicated in the independent set of MetaboChip samples of the Global Lipids Genetics Consortium. Annotating the effect of replicated CRP SNPs to the expression of nearby genes, we observed an effect of rs10435719 on gene expression of FDFT1, and an effect of rs7621025 on PCCB. Conclusions: Our large scale combined GWAS analysis identified numerous pleiotropic loci for CRP and lipids providing further insight in the genetic interrelation between lipids and inflammation. In addition, we provide evidence for FDFT1, PCCB and FTO to be associated with CRP levels.

Journal article

Smith JG, Felix JF, Morrison AC, Kalogeropoulos A, Trompet S, Wilk JB, Gidlöf O, Wang X, Morley M, Mendelson M, Joehanes R, Ligthart S, Shan X, Bis JC, Wang YA, Sjögren M, Ngwa J, Brandimarto J, Stott DJ, Aguilar D, Rice KM, Sesso HD, Demissie S, Buckley BM, Taylor KD, Ford I, Yao C, Liu C, Sotoodehnia N, van der Harst P, Stricker BHC, Kritchevsky SB, Liu Y, Gaziano JM, Hofman A, Moravec CS, Uitterlinden AG, Kellis M, van Meurs JB, Margulies KB, Dehghan A, Levy D, Olde B, Psaty BM, Cupples LA, Jukema JW, Djousse L, Franco OH, Boerwinkle E, Boyer LA, Newton-Cheh C, Butler J, Vasan RS, Cappola TP, Smith NLet al., 2016, Discovery of Genetic Variation on Chromosome 5q22 Associated with Mortality in Heart Failure, PLoS Genetics, Vol: 12, ISSN: 1553-7390

Journal article

van Herpt TT, Dehghan A, van Hoek M, Ikram MA, Hofman A, Sijbrands EJ, Franco OHet al., 2016, The clinical value of metabolic syndrome and risks of cardiometabolic events and mortality in the elderly: the Rotterdam study., Cardiovasc Diabetol, Vol: 15, Pages: 69-69

BACKGROUND: To evaluate the clinical value of metabolic syndrome based on different definitions [American Heart Association/National Heart, Lung and Blood Institute (AHA/NHLBI), International Diabetes Federation (IDF) and European Group for the Study of Insulin Resistance (EGIR)] in middle-aged and elderly populations. METHODS: We studied 8643 participants from the Rotterdam study (1990-2012; mean age 62.7; 57.6 % female), a large prospective population-based study with predominantly elderly participants. We performed cox-proportional hazards models for different definitions, triads within definitions and each separate component for the risk of incident type 2 diabetes mellitus, coronary heart disease, stroke, cardiovascular- and all-cause mortality. RESULTS: In our population of 8643 subjects, metabolic syndrome was highly prevalent (prevalence between 19.4 and 42.4 %). Metabolic syndrome in general was associated with incident type 2 diabetes mellitus (median follow-up of 6.8 years, hazard ratios 3.13-3.78). The associations with coronary heart disease (median follow-up of 7.2 years, hazard ratios 1.08-1.32), stroke (median follow-up of 7.7 years, hazard ratios 0.98-1.32), cardiovascular mortality (median follow-up of 8.2 years, ratios 0.95-1.29) and all-cause mortality (median follow-up of 8.7 years, hazard ratios 1.05-1.10) were weaker. AHA/NHLBI- and IDF-definitions showed similar associations with clinical endpoints compared to the EGIR, which was only significantly associated with incident type 2 diabetes mellitus. All significant associations disappeared after correcting metabolic syndrome for its individual components. CONCLUSIONS: Large variability exists between and within definitions of the metabolic syndrome with respect to risk of clinical events and mortality. In a relatively old population the metabolic syndrome did not show an additional predictive value on top of its individual components. So, besides as a manner of easy identification of high risk

Journal article

Muka T, Nano J, Voortman T, Braun KVE, Ligthart S, Stranges S, Bramer WM, Troup J, Chowdhury R, Dehghan A, Franco OHet al., 2016, The role of global and regional DNA methylation and histone modifications in glycemic traits and type 2 diabetes: A systematic review, NUTRITION METABOLISM AND CARDIOVASCULAR DISEASES, Vol: 26, Pages: 553-566, ISSN: 0939-4753

Journal article

Zhou B, Lu Y, Hajifathalian K, Bentham J, Di Cesare M, Danaei G, Bixby H, Cowan MJ, Ali MK, Taddei C, Lo W-C, Reis-Santos B, Stevens GA, Riley LM, Miranda JJ, Bjerregaard P, Rivera JA, Fouad HM, Ma G, Mbanya JCN, McGarvey ST, Mohan V, Onat A, Ramachandran A, Ben Romdhane H, Paciorek CJ, Bennett JE, Ezzati M, Abdeen ZA, Kadir KA, Abu-Rmeileh NM, Acosta-Cazares B, Adams R, Aekplakorn W, Aguilar-Salinas CA, Agyemang C, Ahmadvand A, Al-Othman AR, Alkerwi A, Amouyel P, Amuzu A, Andersen LB, Anderssen SA, Anjana RM, Aounallah-Skhiri H, Aris T, Arlappa N, Arveiler D, Assah FK, Avdicova M, Azizi F, Balakrishna N, Bandosz P, Barbagallo CM, Barcelo A, Batieha AM, Baur LA, Ben Romdhane H, Benet M, Bernabe-Ortiz A, Bharadwaj S, Bhargava SK, Bi Y, Bjerregaard P, Bjertness E, Bjertness MB, Bjorkelund C, Blokstra A, Bo S, Boehm BO, Boissonnet CP, Bovet P, Brajkovich I, Breckenkamp J, Brenner H, Brewster LM, Brian GR, Bruno G, Bugge A, Cabrera de Leon A, Can G, Candido APC, Capuano V, Carlsson AC, Carvalho MJ, Casanueva FF, Casas J-P, Caserta CA, Castetbon K, Chamukuttan S, Chaturvedi N, Chen C-J, Chen F, Chen S, Cheng C-Y, Chetrit A, Chiou S-T, Cho Y, Chudek J, Cifkova R, Claessens F, Concin H, Cooper C, Cooper R, Costanzo S, Cottel D, Cowell C, Crujeiras AB, D'Arrigo G, Dallongeville J, Dankner R, Dauchet L, de Gaetano G, De Henauw S, Deepa M, Dehghan A, Deschamps V, Dhana K, Di Castelnuovo AF, Djalalinia S, Doua K, Drygas W, Du Y, Dzerve V, Egbagbe EE, Eggertsen R, El Ati J, Elosua R, Erasmus RT, Erem C, Ergor G, Eriksen L, Escobedo-de la Pena J, Fall CH, Farzadfar F, Felix-Redondo FJ, Ferguson TS, Fernandez-Berges D, Ferrari M, Ferreccio C, Feskens EJM, Finn JD, Foeger B, Foo LH, Forslund A-S, Fouad HM, Francis DK, Franco MDC, Franco OH, Frontera G, Furusawa T, Gaciong Z, Garnett SP, Gaspoz J-M, Gasull M, Gates L, Geleijnse JM, Ghasemian A, Ghimire A, Giampaoli S, Gianfagna F, Giovannelli J, Giwercman A, Gonzalez Gross M, Gonzalez Rivas JP, Bonet Gorbea M, Gottrand F, Grafnetteet al., 2016, Worldwide trends in diabetes since 1980: a pooled analysis of 751 population-based studies with 4·4 million participants, Lancet, Vol: 387, Pages: 1513-1530, ISSN: 1474-547X

BackgroundOne of the global targets for non-communicable diseases is to halt, by 2025, the rise in the age-standardised adult prevalence of diabetes at its 2010 levels. We aimed to estimate worldwide trends in diabetes, how likely it is for countries to achieve the global target, and how changes in prevalence, together with population growth and ageing, are affecting the number of adults with diabetes.MethodsWe pooled data from population-based studies that had collected data on diabetes through measurement of its biomarkers. We used a Bayesian hierarchical model to estimate trends in diabetes prevalence—defined as fasting plasma glucose of 7·0 mmol/L or higher, or history of diagnosis with diabetes, or use of insulin or oral hypoglycaemic drugs—in 200 countries and territories in 21 regions, by sex and from 1980 to 2014. We also calculated the posterior probability of meeting the global diabetes target if post-2000 trends continue.FindingsWe used data from 751 studies including 4 372 000 adults from 146 of the 200 countries we make estimates for. Global age-standardised diabetes prevalence increased from 4·3% (95% credible interval 2·4–7·0) in 1980 to 9·0% (7·2–11·1) in 2014 in men, and from 5·0% (2·9–7·9) to 7·9% (6·4–9·7) in women. The number of adults with diabetes in the world increased from 108 million in 1980 to 422 million in 2014 (28·5% due to the rise in prevalence, 39·7% due to population growth and ageing, and 31·8% due to interaction of these two factors). Age-standardised adult diabetes prevalence in 2014 was lowest in northwestern Europe, and highest in Polynesia and Micronesia, at nearly 25%, followed by Melanesia and the Middle East and north Africa. Between 1980 and 2014 there was little change in age-standardised diabetes prevalence in adult women in continental western Europe, although crude prevalenc

Journal article

Di Cesare M, Bentham J, Stevens GA, Zhou B, Danaei G, Lu Y, Bixby H, Cowan MJ, Riley LM, Hajifathalian K, Fortunato L, Taddei C, Bennett JE, Ikeda N, Khang Y-H, Kyobutungi C, Laxmaiah A, Li Y, Lin H-H, Miranda JJ, Mostafa A, Turley ML, Paciorek CJ, Gunter M, Ezzati M, Abdeen ZA, Hamid ZA, Abu-Rmeileh NM, Acosta-Cazares B, Adams R, Aekplakorn W, Aguilar-Salinas CA, Ahmadvand A, Ahrens W, Ali MM, Alkerwi A, Alvarez-Pedrerol M, Aly E, Amouyel P, Amuzu A, Andersen LB, Anderssen SA, Andrade DS, Anjana RM, Aounallah-Skhiri H, Ariansen I, Aris T, Arlappa N, Arveiler D, Assah FK, Avdicova M, Azizi F, Babu BV, Balakrishna N, Bandosz P, Banegas JR, Barbagallo CM, Barcelo A, Barkat A, Barros MV, Bata I, Batieha AM, Batista RL, Baur LA, Beaglehole R, Ben Romdhane H, Benet M, Bernabe-Ortiz A, Bernotiene G, Bettiol H, Bhagyalaxmi A, Bharadwaj S, Bhargava SK, Bhatti Z, Bhutta ZA, Bi H, Bi Y, Bjerregaard P, Bjertness E, Bjertness MB, Bjorkelund C, Blake M, Blokstra A, Bo S, Bobak M, Boddy LM, Boehm BO, Boeing H, Boissonnet CP, Bongard V, Bovet P, Braeckman L, Bragt MCE, Brajkovich I, Branca F, Breckenkamp J, Brenner H, Brewster LM, Brian GR, Bruno G, Bueno-de-Mesquita HBA, Bugge A, Burns C, Cabrera de Leon A, Cacciottolo J, Cama T, Cameron C, Camolas J, Can G, Candido APC, Capuano V, Cardoso VC, Carvalho MJ, Casanueva FF, Casas J-P, Caserta CA, Castetbon K, Chamukuttan S, Chan AW, Chan Q, Chaturvedi HK, Chaturvedi N, Chen C-J, Chen F, Chen H, Chen S, Chen Z, Cheng C-Y, Chetrit A, Chiolero A, Chiou S-T, Chirita-Emandi A, Cho Y, Christensen K, Chudek J, Cifkova R, Claessens F, Clays E, Concin H, Cooper C, Cooper R, Coppinger TC, Costanzo S, Cottel D, Cowell C, Craig CL, Crujeiras AB, D'Arrigo G, d'Orsi E, Dallongeville J, Damasceno A, Damsgaard CT, Danaei G, Dankner R, Dauchet L, De Backer G, De Bacquer D, de Gaetano G, De Henauw S, De Smedt D, Deepa M, Deev AD, Dehghan A, Delisle H, Delpeuch F, Dhana K, Di Castelnuovo AF, Dias-da-Costa JS, Diaz A, Djalalinia S, Do HTP, Dobson AJ, Doet al., 2016, Trends in adult body-mass index in 200 countries from 1975 to 2014: a pooled analysis of 1698 population-based measurement studies with 19.2 million participants, Lancet, Vol: 387, Pages: 1377-1396, ISSN: 1474-547X

BackgroundUnderweight and severe and morbid obesity are associated with highly elevated risks of adverse health outcomes. We estimated trends in mean body-mass index (BMI), which characterises its population distribution, and in the prevalences of a complete set of BMI categories for adults in all countries.MethodsWe analysed, with use of a consistent protocol, population-based studies that had measured height and weight in adults aged 18 years and older. We applied a Bayesian hierarchical model to these data to estimate trends from 1975 to 2014 in mean BMI and in the prevalences of BMI categories (<18·5 kg/m2 [underweight], 18·5 kg/m2 to <20 kg/m2, 20 kg/m2 to <25 kg/m2, 25 kg/m2 to <30 kg/m2, 30 kg/m2 to <35 kg/m2, 35 kg/m2 to <40 kg/m2, ≥40 kg/m2 [morbid obesity]), by sex in 200 countries and territories, organised in 21 regions. We calculated the posterior probability of meeting the target of halting by 2025 the rise in obesity at its 2010 levels, if post-2000 trends continue.FindingsWe used 1698 population-based data sources, with more than 19·2 million adult participants (9·9 million men and 9·3 million women) in 186 of 200 countries for which estimates were made. Global age-standardised mean BMI increased from 21·7 kg/m2 (95% credible interval 21·3–22·1) in 1975 to 24·2 kg/m2 (24·0–24·4) in 2014 in men, and from 22·1 kg/m2 (21·7–22·5) in 1975 to 24·4 kg/m2 (24·2–24·6) in 2014 in women. Regional mean BMIs in 2014 for men ranged from 21·4 kg/m2 in central Africa and south Asia to 29·2 kg/m2 (28·6–29·8) in Polynesia and Micronesia; for women the range was from 21·8 kg/m2 (21·4–22·3) in south Asia to 32·2 kg/m2 (31·5–32·8) in Polynesia and Micronesia. Over these four decades, age-standardised global prevalence of un

Journal article

van Leeuwen EM, Sabo A, Bis JC, Huffman JE, Manichaikul A, Smith AV, Feitosa MF, Demissie S, Joshi PK, Duan Q, Marten J, van Klinken JB, Surakka I, Nolte IM, Zhang W, Mbarek H, Li-Gao R, Trompet S, Verweij N, Evangelou E, Lyytikäinen LP, Tayo BO, Deelen J, van der Most PJ, van der Laan SW, Arking DE, Morrison A, Dehghan A, Franco OH, Hofman A, Rivadeneira F, Sijbrands EJ, Uitterlinden AG, Mychaleckyj JC, Campbell A, Hocking LJ, Padmanabhan S, Brody JA, Rice KM, White CC, Harris T, Isaacs A, Campbell H, Lange LA, Rudan I, Kolcic I, Navarro P, Zemunik T, Salomaa V, LifeLines Cohort Study, Kooner AS, Kooner JS, Lehne B, Scott WR, Tan ST, de Geus EJ, Milaneschi Y, Penninx BW, Willemsen G, de Mutsert R, Ford I, Gansevoort RT, Segura-Lepe MP, Raitakari OT, Viikari JS, Nikus K, Forrester T, McKenzie CA, de Craen AJ, de Ruijter HM, Pasterkamp G, Snieder H, Oldehinkel AJ, Slagboom PE, Cooper RS, Kähönen M, Lehtimäki T, Elliott P, van der Harst P, Jukema JW, Mook-Kanamori DO, Boomsma DI, Chambers JC, Swertz M, Ripatti S, Willems van Dijk K, Vitart V, Polasek O, Hayward C, Wilson JG, Wilson JF, Gudnason V, Rich SS, Psaty BM, Borecki IB, Boerwinkle E, Rotter JI, Cupples LA, van Duijn CMet 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.

Journal article

Joubert BR, Felix JF, Yousefi P, Bakulski KM, Just AC, Breton C, Reese SE, Markunas CA, Richmond RC, Xu CJ, Küpers LK, Oh SS, Hoyo C, Gruzieva O, Söderhäll C, Salas LA, Baïz N, Zhang H, Lepeule J, Ruiz C, Ligthart S, Wang T, Taylor JA, Duijts L, Sharp GC, Jankipersadsing SA, Nilsen RM, Vaez A, Fallin MD, Hu D, Litonjua AA, Fuemmeler BF, Huen K, Kere J, Kull I, Munthe-Kaas MC, Gehring U, Bustamante M, Saurel-Coubizolles MJ, Quraishi BM, Ren J, Tost J, Gonzalez JR, Peters MJ, Håberg SE, Xu Z, van Meurs JB, Gaunt TR, Kerkhof M, Corpeleijn E, Feinberg AP, Eng C, Baccarelli AA, Benjamin Neelon SE, Bradman A, Merid SK, Bergström A, Herceg Z, Hernandez-Vargas H, Brunekreef B, Pinart M, Heude B, Ewart S, Yao J, Lemonnier N, Franco OH, Wu MC, Hofman A, McArdle W, Van der Vlies P, Falahi F, Gillman MW, Barcellos LF, Kumar A, Wickman M, Guerra S, Charles MA, Holloway J, Auffray C, Tiemeier HW, Smith GD, Postma D, Hivert MF, Eskenazi B, Vrijheid M, Arshad H, Antó JM, Dehghan A, Karmaus W, Annesi-Maesano I, Sunyer J, Ghantous A, Pershagen G, Holland N, Murphy SK, DeMeo DL, Burchard EG, Ladd-Acosta C, Snieder H, Nystad W, Koppelman GH, Relton CL, Jaddoe VW, Wilcox A, Melén E, London SJet al., 2016, DNA Methylation in Newborns and Maternal Smoking in Pregnancy: Genome-wide Consortium Meta-analysis., Am J Hum Genet, Vol: 98, Pages: 680-696

Epigenetic modifications, including DNA methylation, represent a potential mechanism for environmental impacts on human disease. Maternal smoking in pregnancy remains an important public health problem that impacts child health in a myriad of ways and has potential lifelong consequences. The mechanisms are largely unknown, but epigenetics most likely plays a role. We formed the Pregnancy And Childhood Epigenetics (PACE) consortium and meta-analyzed, across 13 cohorts (n = 6,685), the association between maternal smoking in pregnancy and newborn blood DNA methylation at over 450,000 CpG sites (CpGs) by using the Illumina 450K BeadChip. Over 6,000 CpGs were differentially methylated in relation to maternal smoking at genome-wide statistical significance (false discovery rate, 5%), including 2,965 CpGs corresponding to 2,017 genes not previously related to smoking and methylation in either newborns or adults. Several genes are relevant to diseases that can be caused by maternal smoking (e.g., orofacial clefts and asthma) or adult smoking (e.g., certain cancers). A number of differentially methylated CpGs were associated with gene expression. We observed enrichment in pathways and processes critical to development. In older children (5 cohorts, n = 3,187), 100% of CpGs gave at least nominal levels of significance, far more than expected by chance (p value < 2.2 × 10(-16)). Results were robust to different normalization methods used across studies and cell type adjustment. In this large scale meta-analysis of methylation data, we identified numerous loci involved in response to maternal smoking in pregnancy with persistence into later childhood and provide insights into mechanisms underlying effects of this important exposure.

Journal article

Jovanova O, Luik AI, Leening MJG, Noordam R, Aarts N, Hofman A, Franco OH, Dehghan A, Tiemeier Het al., 2016, The long-term risk of recognized and unrecognized myocardial infarction for depression in older men, PSYCHOLOGICAL MEDICINE, Vol: 46, Pages: 1951-1960, ISSN: 0033-2917

Journal article

Muka T, Koromani F, Portilla E, O'Connor A, Bramer WM, Troup J, Chowdhury R, Dehghan A, Franco OHet al., 2016, The role of epigenetic modifications in cardiovascular disease: A systematic review, International Journal of Cardiology, Vol: 212, Pages: 174-183, ISSN: 0167-5273

© 2015 Elsevier Ireland Ltd. All rights reserved. Background Epigenetic modifications of the genome, such as DNA methylation and histone modifications, have been reported to play a role in processes underlying cardiovascular disease (CVD), including atherosclerosis, inflammation, hypertension and diabetes. Methods Eleven databases were searched for studies investigating the association between epigenetic marks (either global, site-specific or genome-wide methylation of DNA and histone modifications) and CVD. Results Of the 3459 searched references, 31 studies met our inclusion criteria (26 cross-sectional studies and 5 prospective studies). Overall, 12,648 individuals were included, with total of 4037 CVD events. The global DNA methylation assessed at long-interspersed nuclear element (LINE-1) was inversely associated with CVD, independent of established cardiovascular risk factors. Conversely, a higher degree of global DNA methylation measured at Alu repeats or by the LUMA method was associated with the presence of CVD. The studies reported epigenetic regulation of 34 metabolic genes (involved in fetal growth, glucose and lipid metabolism, inflammation, atherosclerosis and oxidative stress) in blood cells to be related with CVD. Among them, 5 loci were validated and methylation at F2RL3 was reported in two large prospective studies to predict cardiovascular disease beyond the traditional risk factors. Conclusions Current evidence supports an association between genomic DNA methylation and CVD. However, this review highlights important gaps in the existing evidences including lack of large-scale epigenetic investigations, needed to reliably identify genomic loci where DNA methylation is related to risk of CVD.

Journal article

Dehghan A, Bis JC, White CC, Smith AV, Morrison AC, Cupples LA, Trompet S, Chasman DI, Lumley T, Voelker U, Buckley BM, Ding J, Jensen MK, Folsom AR, Kritchevsky SB, Girman CJ, Ford I, Doerr M, Salomaa V, Uitterlinden AG, Eiriksdottir G, Vasan RS, Franceschini N, Carty CL, Virtamo J, Demissie S, Amouyel P, Arveiler D, Heckbert SR, Ferrieres J, Ducimetiere P, Smith NL, Wang YA, Siscovick DS, Rice KM, Wiklund P-G, Taylor KD, Evans A, Kee F, Rotter JI, Karvanen J, Kuulasmaa K, Heiss G, Kraft P, Launer LJ, Hofman A, Markus MRP, Rose LM, Silander K, Wagner P, Benjamin EJ, Lohman K, Stott DJ, Rivadeneira F, Harris TB, Levy D, Liu Y, Rimm EB, Jukema JW, Voelzke H, Ridker PM, Blankenberg S, Franco OH, Gudnason V, Psaty BM, Boerwinkle E, O'Donnell CJet al., 2016, Genome-wide association study for incident myocardial infarction and coronary heart disease in prospective cohort studies: The CHARGE Consortium, PLOS One, Vol: 11, ISSN: 1932-6203

BackgroundData are limited on genome-wide association studies (GWAS) for incident coronary heart disease (CHD). Moreover, it is not known whether genetic variants identified to date also associate with risk of CHD in a prospective setting.MethodsWe performed a two-stage GWAS analysis of incident myocardial infarction (MI) and CHD in a total of 64,297 individuals (including 3898 MI cases, 5465 CHD cases). SNPs that passed an arbitrary threshold of 5×10−6 in Stage I were taken to Stage II for further discovery. Furthermore, in an analysis of prognosis, we studied whether known SNPs from former GWAS were associated with total mortality in individuals who experienced MI during follow-up.ResultsIn Stage I 15 loci passed the threshold of 5×10−6; 8 loci for MI and 8 loci for CHD, for which one locus overlapped and none were reported in previous GWAS meta-analyses. We took 60 SNPs representing these 15 loci to Stage II of discovery. Four SNPs near QKI showed nominally significant association with MI (p-value<8.8×10−3) and three exceeded the genome-wide significance threshold when Stage I and Stage II results were combined (top SNP rs6941513: p = 6.2×10−9). Despite excellent power, the 9p21 locus SNP (rs1333049) was only modestly associated with MI (HR = 1.09, p-value = 0.02) and marginally with CHD (HR = 1.06, p-value = 0.08). Among an inception cohort of those who experienced MI during follow-up, the risk allele of rs1333049 was associated with a decreased risk of subsequent mortality (HR = 0.90, p-value = 3.2×10−3).ConclusionsQKI represents a novel locus that may serve as a predictor of incident CHD in prospective studies. The association of the 9p21 locus both with increased risk of first myocardial infarction and longer survival after MI highlights the importance of study design in investigating genetic determinants of complex disorders.

Journal article

Sedaghat S, Vernooij MW, Loehrer E, Mattace-Raso FUS, Hofman A, van der Lugt A, Franco OH, Dehghan A, Ikram MAet al., 2016, Kidney Function and Cerebral Blood Flow: The Rotterdam Study, JOURNAL OF THE AMERICAN SOCIETY OF NEPHROLOGY, Vol: 27, Pages: 715-721, ISSN: 1046-6673

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Muka T, de Jonge EAL, Kiefte-de Jong JC, Uitterlinden AG, Hofman A, Dehghan A, Zillikens MC, Franco OH, Rivadeneira Fet al., 2016, The Influence of Serum Uric Acid on Bone Mineral Density, Hip Geometry, and Fracture Risk: The Rotterdam Study, JOURNAL OF CLINICAL ENDOCRINOLOGY & METABOLISM, Vol: 101, Pages: 1113-1122, ISSN: 0021-972X

Journal article

Ghanbari M, Darweesh SKL, de Looper HWJ, van Luijn MM, Hofman A, Ikram MA, Franco OH, Erkeland SJ, Dehghan Aet al., 2016, Genetic Variants in MicroRNAs and Their Binding Sites Are Associated with the Risk of Parkinson Disease, HUMAN MUTATION, Vol: 37, Pages: 292-300, ISSN: 1059-7794

Journal article

Janki S, Klop KWJ, Kimenai HJAN, van de Wetering J, Weimar W, Massey EK, Dehghan A, Rizopoulos D, Voelzke H, Hofman A, Ijzermans JNMet al., 2016, LOng-term follow-up after liVE kidney donation (LOVE) study: a longitudinal comparison study protocol, BMC NEPHROLOGY, Vol: 17, ISSN: 1471-2369

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Joubert BR, den Dekker HT, Felix JF, Bohlin J, Ligthart S, Beckett E, Tiemeier H, van Meurs JB, Uitterlinden AG, Hofman A, Haberg SE, Reese SE, Peters MJ, Andreassen BK, Steegers EAP, Nilsen RM, Vollset SE, Midttun O, Ueland PM, Franco OH, Dehghan A, de Jongste JC, Wu MC, Wang T, Peddada SD, Jaddoe VWV, Nystad W, Duijts L, London SJet al., 2016, Maternal plasma folate impacts differential DNA methylation in an epigenome-wide meta-analysis of newborns, NATURE COMMUNICATIONS, Vol: 7, ISSN: 2041-1723

Journal article

Lu Y, Day FR, Gustafsson S, Buchkovich ML, Na J, Bataille V, Cousminer DL, Dastani Z, Drong AW, Esko T, Evans DM, Falchi M, Feitosa MF, Ferreira T, Hedman AK, Haring R, Hysi PG, Iles MM, Justice AE, Kanoni S, Lagou V, Li R, Li X, Locke A, Lu C, Magi R, Perry JRB, Pers TH, Qi Q, Sanna M, Schmidt EM, Scott WR, Shungin D, Teumer A, Vinkhuyzen AAE, Walker RW, Westra H-J, Zhang M, Zhang W, Zhao JH, Zhu Z, Afzal U, Ahluwalia TS, Bakker SJL, Bellis C, Bonnefond A, Borodulin K, Buchman AS, Cederholm T, Choh AC, Choi HJ, Curran JE, de Groot LCPGM, De Jager PL, Dhonukshe-Rutten RAM, Enneman AW, Eury E, Evans DS, Forsen T, Friedrich N, Fumeron F, Garcia ME, Gartner S, Han B-G, Havulinna AS, Hayward C, Hernandez D, Hillege H, Ittermann T, Kent JW, Kolcic I, Laatikainen T, Lahti J, Leach IM, Lee CG, Lee J-Y, Liu T, Liu Y, Lobbens S, Loh M, Lyytikainen L-P, Medina-Gomez C, Michaelsson K, Nalls MA, Nielson CM, Oozageer L, Pascoe L, Paternoster L, Polasek O, Ripatti S, Sarzynski MA, Shin CS, Narancic NS, Spira D, Srikanth P, Steinhagen-Thiessen E, Sung YJ, Swart KMA, Taittonen L, Tanaka T, Tikkanen E, van der Velde N, van Schoor NM, Verweij N, Wright AF, Yu L, Zmuda JM, Eklund N, Forrester T, Grarup N, Jackson AU, Kristiansson K, Kuulasmaa T, Kuusisto J, Lichtner P, Luan J, Mahajan A, Mannisto S, Palmer CD, Ried JS, Scott RA, Stancakova A, Wagner PJ, Demirkan A, Doring A, Gudnason V, Kiel DP, Kuhnel B, Mangino M, Mcknight B, Menni C, O'Connell JR, Oostra BA, Shuldiner AR, Song K, Vandenput L, van Duijn CM, Vollenweider P, White CC, Boehnke M, Boettcher Y, Cooper RS, Forouhi NG, Gieger C, Grallert H, Hingorani A, Jorgensen T, Jousilahti P, Kivimaki M, Kumari M, Laakso M, Langenberg C, Linneberg A, Luke A, Mckenzie CA, Palotie A, Pedersen O, Peters A, Strauch K, Tayo BO, Wareham NJ, Bennett DA, Bertram L, Blangero J, Bluher M, Bouchard C, Campbell H, Cho NH, Cummings SR, Czerwinski SA, Demuth I, Eckardt R, Eriksson JG, Ferrucci L, Franco OH, Froguel P, Gansevoort RT, Hansen T, Harriset al., 2016, New loci for body fat percentage reveal link between adiposity and cardiometabolic disease risk, NATURE COMMUNICATIONS, Vol: 7, ISSN: 2041-1723

Journal article

Ligthart S, Steenaard RV, Peters MJ, van Meurs JB, Sijbrands EJ, Uitterlinden AG, Bonder MJ, BIOS consortium, Hofman A, Franco OH, Dehghan Aet al., 2016, Tobacco smoking is associated with DNA methylation of diabetes susceptibility genes., Diabetologia, Vol: 59, Pages: 998-1006

AIMS/HYPOTHESIS: Tobacco smoking, a risk factor for diabetes, is an established modifier of DNA methylation. We hypothesised that tobacco smoking modifies DNA methylation of genes previously identified for diabetes. METHODS: We annotated CpG sites available on the Illumina Human Methylation 450K array to diabetes genes previously identified by genome-wide association studies (GWAS), and investigated them for an association with smoking by comparing current to never smokers. The discovery study consisted of 630 individuals (Bonferroni-corrected p = 1.4 × 10(-5)), and we sought replication in an independent sample of 674 individuals. The replicated sites were tested for association with nearby genetic variants and gene expression and fasting glucose and insulin levels. RESULTS: We annotated 3,620 CpG sites to the genes identified in the GWAS on type 2 diabetes. Comparing current smokers to never smokers, we found 12 differentially methylated CpG sites, of which five replicated: cg23161492 within ANPEP (p = 1.3 × 10(-12)); cg26963277 (p = 1.2 × 10(-9)), cg01744331 (p = 8.0 × 10(-6)) and cg16556677 (p = 1.2 × 10(-5)) within KCNQ1 and cg03450842 (p = 3.1 × 10(-8)) within ZMIZ1. The effect of smoking on DNA methylation at the replicated CpG sites attenuated after smoking cessation. Increased DNA methylation at cg23161492 was associated with decreased gene expression levels of ANPEP (p = 8.9 × 10(-5)). rs231356-T, which was associated with hypomethylation of cg26963277 (KCNQ1), was associated with a higher odds of diabetes (OR 1.06, p = 1.3 × 10(-5)). Additionally, hypomethylation of cg26963277 was associated with lower fasting insulin levels (p = 0.04). CONCLUSIONS/INTERPRETATION: Tobacco sm

Journal article

Pattaro C, Teumer A, Gorski M, Chu AY, Li M, Mijatovic V, Garnaas M, Tin A, Sorice R, Li Y, Taliun D, Olden M, Foster M, Yang Q, Chen MH, Pers TH, Johnson AD, Ko YA, Fuchsberger C, Tayo B, Nalls M, Feitosa MF, Isaacs A, Dehghan A, d'Adamo P, Adeyemo A, Dieffenbach AK, Zonderman AB, Nolte IM, van der Most PJ, Wright AF, Shuldiner AR, Morrison AC, Hofman A, Smith AV, Dreisbach AW, Franke A, Uitterlinden AG, Metspalu A, Tonjes A, Lupo A, Robino A, Johansson Å, Demirkan A, Kollerits B, Freedman BI, Ponte B, Oostra BA, Paulweber B, Krämer BK, Mitchell BD, Buckley BM, Peralta CA, Hayward C, Helmer C, Rotimi CN, Shaffer CM, Müller C, Sala C, van Duijn CM, Saint-Pierre A, Ackermann D, Shriner D, Ruggiero D, Toniolo D, Lu Y, Cusi D, Czamara D, Ellinghaus D, Siscovick DS, Ruderfer D, Gieger C, Grallert H, Rochtchina E, Atkinson EJ, Holliday EG, Boerwinkle E, Salvi E, Bottinger EP, Murgia F, Rivadeneira F, Ernst F, Kronenberg F, Hu FB, Navis GJ, Curhan GC, Ehret GB, Homuth G, Coassin S, Thun GA, Pistis G, Gambaro G, Malerba G, Montgomery GW, Eiriksdottir G, Jacobs G, Li G, Wichmann HE, Campbell H, Schmidt H, Wallaschofski H, Völzke H, Brenner H, Kroemer HK, Kramer H, Lin H, Mateo Leach I, Ford I, Guessous I, Rudan I, Prokopenko I, Borecki I, Heid IM, Kolcic I, Persico I, Jukema JW, Wilson JF, Felix JF, Divers J, Lambert JC, Stafford JM, Gaspoz JM, Smith JA, Faul JD, Wang JJ, Ding J, Hirschhorn JN, Attia J, Whitfield JB, Chalmers J, Viikari J, Coresh J, Denny JC, Karjalainen J, Fernandes JK, Endlich K, Butterbach K, Keene KL, Lohman K, Portas L, Launer LJ, Lyytikäinen LP, Yengo L, Franke L, Ferrucci L, Rose LM, Kedenko L, Rao M, Struchalin M, Kleber ME, Cavalieri M, Haun M, Cornelis MC, Ciullo M, Pirastu M, de Andrade M, McEvoy MA, Woodward M, Adam M, Cocca M, Nauck M, Imboden M, Waldenberger M, Pruijm M, Metzger M, Stumvoll M, Evans MK, Sale MM, Kähönen M, Boban M, Bochud M, Rheinberger M, Verweij N, Bouatia-Naji N, Martin NG, Hastie N, Probst-Hensch N, Soranzo N, Devuyst O Ret al., 2016, Genetic associations at 53 loci highlight cell types and biological pathways relevant for kidney function., Nat Commun, Vol: 7

Reduced glomerular filtration rate defines chronic kidney disease and is associated with cardiovascular and all-cause mortality. We conducted a meta-analysis of genome-wide association studies for estimated glomerular filtration rate (eGFR), combining data across 133,413 individuals with replication in up to 42,166 individuals. We identify 24 new and confirm 29 previously identified loci. Of these 53 loci, 19 associate with eGFR among individuals with diabetes. Using bioinformatics, we show that identified genes at eGFR loci are enriched for expression in kidney tissues and in pathways relevant for kidney development and transmembrane transporter activity, kidney structure, and regulation of glucose metabolism. Chromatin state mapping and DNase I hypersensitivity analyses across adult tissues demonstrate preferential mapping of associated variants to regulatory regions in kidney but not extra-renal tissues. These findings suggest that genetic determinants of eGFR are mediated largely through direct effects within the kidney and highlight important cell types and biological pathways.

Journal article

de Vries PS, Chasman DI, Sabater-Lleal M, Chen M-H, Huffman JE, Steri M, Tang W, Teumer A, Marioni RE, Grossmann V, Hottenga JJ, Trompet S, Mueller-Nurasyid M, Zhao JH, Brody JA, Kleber ME, Guo X, Wang JJ, Auer PL, Attia JR, Yanek LR, Ahluwalia TS, Lahti J, Venturini C, Tanaka T, Bielak LF, Joshi PK, Rocanin-Arjo A, Kolcic I, Navarro P, Rose LM, Oldmeadow C, Riess H, Mazur J, Basu S, Goel A, Yang Q, Ghanbari M, Willemsen G, Rumley A, Fiorillo E, de Craen AJM, Grotevendt A, Scott R, Taylor KD, Delgado GE, Yao J, Kifley A, Kooperberg C, Qayyum R, Lopez LM, Berentzen TL, Raikkonen K, Mangino M, Bandinelli S, Peyser PA, Wild S, Tregouet D-A, Wright AF, Marten J, Zemunik T, Morrison AC, Sennblad B, Tofler G, de Maat MPM, de Geus EJC, Lowe GD, Zoledziewska M, Sattar N, Binder H, Voelker U, Waldenberger M, Khaw K-T, Mcknight B, Huang J, Jenny NS, Holliday EG, Qi L, Mcevoy MG, Becker DM, Starr JM, Sarin A-P, Hysi PG, Hernandez DG, Jhun MA, Campbell H, Hamsten A, Rivadeneira F, Mcardle WL, Slagboom PE, Zeller T, Koenig W, Psaty BM, Haritunians T, Liu J, Palotie A, Uitterlinden AG, Stott DJ, Hofman A, Franco OH, Polasek O, Rudan I, Morange P-E, Wilson JF, Kardia SLR, Ferrucci L, Spector TD, Eriksson JG, Hansen T, Deary IJ, Becker LC, Scott RJ, Mitchell P, Maerz W, Wareham NJ, Peters A, Greinacher A, Wild PS, Jukema JW, Boomsma DI, Hayward C, Cucca F, Tracy R, Watkins H, Reiner AP, Folsom AR, Ridker PM, O'Donnell CJ, Smith NL, Strachan DP, Dehghan Aet al., 2016, A meta-analysis of 120 246 individuals identifies 18 new loci for fibrinogen concentration, HUMAN MOLECULAR GENETICS, Vol: 25, Pages: 358-370, ISSN: 0964-6906

Journal article

LeBlanc M, Zuber V, Andreassen BK, Witoelar A, Zeng L, Bettella F, Wang Y, McEvoy LK, Thompson WK, Schork AJ, Reppe S, Barrett-Connor E, Ligthart S, Dehghan A, Gautvik KM, Nelson CP, Schunkert H, Samani NJ, Ridker PM, Chasman DI, Aukrust P, Djurovic S, Frigessi A, Desikan RS, Dale AM, Andreassen OAet al., 2016, Identifying Novel Gene Variants in Coronary Artery Disease and Shared Genes With Several Cardiovascular Risk Factors, CIRCULATION RESEARCH, Vol: 118, Pages: 83-94, ISSN: 0009-7330

Journal article

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