Imperial College London

ProfessorPaulElliott

Faculty of MedicineSchool of Public Health

Chair in Epidemiology and Public Health Medicine
 
 
 
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Contact

 

+44 (0)20 7594 3328p.elliott Website

 
 
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Assistant

 

Miss Jennifer Wells +44 (0)20 7594 3328

 
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Location

 

154Norfolk PlaceSt Mary's Campus

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Summary

 

Publications

Publication Type
Year
to

616 results found

Turcot V, Lu Y, Highland HM, Schurmann C, Justice AE, Fine RS, Bradfield JP, Esko T, Giri A, Graff M, Guo X, Hendricks AE, Karaderi T, Lempradl A, Locke AE, Mahajan A, Marouli E, Sivapalaratnam S, Young KL, Alfred T, Feitosa MF, Masca NGD, Manning AK, Medina-Gomez C, Mudgal P, Ng MCY, Reiner AP, Vedantam S, Willems SM, Winkler TW, Abecasis G, Aben KK, Alam DS, Alharthi SE, Allison M, Amouyel P, Asselbergs FW, Auer PL, Balkau B, Bang LE, Barroso I, Bastarache L, Benn M, Bergmann S, Bielak LF, Bluher M, Boehnke M, Boeing H, Boerwinkle E, Boger CA, Bork-Jensen J, Bots ML, Bottinger EP, Bowden DW, Brandslund I, Breen G, Brilliant MH, Broer L, Brumat M, Burt AA, Butterworth AS, Campbell PT, Cappellani S, Carey DJ, Catamo E, Caulfield MJ, Chambers JC, Chasman DI, Chen Y-DI, Chowdhury R, Christensen C, Chu AY, Cocca M, Collins FS, Cook JP, Corley J, Galbany JC, Cox AJ, Crosslin DS, Cuellar-Partida G, D'Eustacchio A, Danesh J, Davies G, Bakker PIW, Groot MCH, Mutsert R, Deary IJ, Dedoussis G, Demerath EW, Heijer M, Hollander AI, Ruijter HM, Dennis JG, Denny JC, Di Angelantonio E, Drenos F, Du M, Dube M-P, Dunning AM, Easton DF, Edwards TL, Ellinghaus D, Ellinor PT, Elliott P, Evangelou E, Farmaki A-E, Farooqi IS, Faul JD, Fauser S, Feng S, Ferrannini E, Ferrieres J, Florez JC, Ford I, Fornage M, Franco OH, Franke A, Franks PW, Friedrich N, Frikke-Schmidt R, Galesloot TE, Gan W, Gandin I, Gasparini P, Gibson J, Giedraitis V, Gjesing AP, Gordon-Larsen P, Gorski M, Grabe H-J, Grant SFA, Grarup N, Griffiths HL, Grove ML, Gudnason V, Gustafsson S, Haessler J, Hakonarson H, Hammerschlag AR, Hansen T, Harris KM, Harris TB, Hattersley AT, Have CT, Hayward C, He L, Heard-Costa NL, Heath AC, Heid IM, Helgeland O, Hernesniemi J, Hewitt AW, Holmen OL, Hovingh GK, Howson JMM, Hu Y, Huang PL, Huffman JE, Ikram MA, Ingelsson E, Jackson AU, Jansson J-H, Jarvik GP, Jensen GB, Jia Y, Johansson S, Jorgensen ME, Jorgensen T, Jukema JW, Kahali B, Kahn RS, Kahonen M, Kamstrup PR, Kanoni S, Kapriet al., 2019, Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity, Nature Genetics, Vol: 51, Pages: 1191-1192, ISSN: 1061-4036

In the HTML version of this article initially published, the author groups ‘CHD Exome+ Consortium’, ‘EPIC-CVD Consortium’, ‘ExomeBP Consortium’, ‘Global Lipids Genetic Consortium’, ‘GoT2D Genes Consortium’, ‘EPIC InterAct Consortium’, ‘INTERVAL Study’, ‘ReproGen Consortium’, ‘T2D-Genes Consortium’, ‘The MAGIC Investigators’ and ‘Understanding Society Scientific Group’ appeared at the end of the author list but should have appeared earlier in the list, after author Krina T. Zondervan. The errors have been corrected in the HTML version of the article.

Journal article

Freni Sterrantino A, Elliott P, Blangiardo M, Hansell A, Ghosh R, Toledano M, Fecht Det al., 2019, Bayesian spatial modelling for quasi-experimental designs: an interrupted time series study of the opening of Municipal Waste Incinerators in relation to infant mortality and sex ratio, Environment International, Vol: 128, Pages: 109-115, ISSN: 0160-4120

BackgroundThere is limited evidence on potential health risks from Municipal Waste Incinerators (MWIs), and previous studies on birth outcomes show inconsistent results. Here, we evaluate whether the opening of MWIs is associated with infant mortality and sex ratio in the surrounding areas, extending the Interrupted Time Series (ITS) methodological approach to account for spatial dependencies at the small area level.MethodsWe specified a Bayesian hierarchical model to investigate the annual risks of infant mortality and sex-ratio (female relative to male) within 10 km of eight MWIs in England and Wales, during the period 1996–2012. We included comparative areas matched one-to-one of similar size and area characteristics.ResultsDuring the study period, infant mortality rates decreased overall by 2.5% per year in England. The opening of an incinerator in the MWI area was associated with −8 deaths per 100,000 infants (95% CI −62, 40) and with a difference in sex ratio of −0.004 (95% CI −0.02, 0.01), comparing the period after opening with that before, corrected for before-after trends in the comparator areas.ConclusionOur method is suitable for the analysis of quasi-experimental time series studies in the presence of spatial structure and when there are global time trends in the outcome variable. Based on our approach, we do not find evidence of an association of MWI opening with changes in risks of infant mortality or sex ratio in comparison with control areas.

Journal article

Evangelou E, Warren H, Mosen-Ansorena D, Mifsud B, Pazoki R, Gao H, Ntritsos G, Dimou N, Hellwege JN, Giri A, Esko T, Metspalu A, Hung AM, O'Donnell CJ, Edwards TL, Tzoulaki I, Barnes M, Wain LV, Elliott P, Caulfield Met al., 2019, Large-scale meta-analysis of GWAS in over one million individuals identifies more than 1,000 novel independent variants associated with blood pressure, 51st Conference of the European-Society-of-Human-Genetics (ESHG) in conjunction with the European Meeting on Psychosocial Aspects of Genetics (EMPAG), Publisher: NATURE PUBLISHING GROUP, Pages: 842-843, ISSN: 1018-4813

Conference paper

Pazoki R, Evangelou E, Mosen-Ansorena D, Pinto R, Karaman I, Blakeley P, Gill D, Zuber V, Elliott P, Tzoulaki I, Dehghan Aet al., 2019, PATHWAYS UNDERLYING URINARY SODIUM AND POTASSIUM EXCRETION AND THE LINK TO BLOOD PRESSURE AND CARDIOVASCULAR DISEASE, Journal of Hypertension, Vol: 37, Pages: e74-e74, ISSN: 0263-6352

Journal article

Zhou L, Stamler J, Chan Q, Van Horn L, Daviglus ML, Dyer AR, Miura K, Okuda N, Wu Y, Ueshima H, Elliott P, Zhao L, INTERMAP Research Groupet al., 2019, Salt intake and prevalence of overweight/obesity in Japan, China, the United Kingdom, and the United States: the INTERMAP Study, American Journal of Clinical Nutrition, Vol: 110, Pages: 34-40, ISSN: 1938-3207

BACKGROUND: Several studies have reported that dietary salt intake may be an independent risk factor for overweight/obesity, but results from previous studies are controversial, reflecting study limitations such as use of a single spot urine or dietary recall to estimate daily salt intake rather than 24-h urine collections, and population samples from only a single country or center. OBJECTIVE: The aim of this study was to use data from the International Study of Macro-/Micro-nutrients and Blood Pressure (INTERMAP Study) to explore the relation between dietary salt intake estimated from 2 timed 24-h urine collections and body mass index (BMI; in kg/m2) as well as prevalence of overweight/obesity in Japan, China, the United Kingdom, and the United States. METHODS: Data were from a cross-sectional study of 4680 men and women aged 40-59 y in Japan (n = 1145), China (n = 839), the United Kingdom (n = 501), and the United States (n = 2195). General linear models were used to obtain the regression coefficients (β) of salt intake associated with BMI. Multivariable logistic regression models were used to determine the ORs and 95% CIs of overweight/obesity associated with a 1-g/d higher dietary salt intake. RESULTS: After adjustment for potential confounding factors including energy intake, salt intake 1 g/d higher was associated with BMI higher by 0.28 in Japan, 0.10 in China, 0.42 in the United Kingdom, and 0.52 in the United States, all P values < 0.001. Salt intake 1 g/d higher was associated with odds of overweight/obesity 21% higher in Japan, 4% higher in China, 29% higher in the United Kingdom, and 24% higher in the United States, all P values < 0.05. CONCLUSIONS: Salt intake is positively associated with BMI and the prevalence of overweight/obesity in Japan, China, the United Kingdom, and the United States. This association needs to be further confirmed in well-designed prospective studies with re

Journal article

Gill D, Benyamin B, Moore LSP, Monori G, Zhou A, Fotios K, Evangelou E, Laffan M, Walker AP, Tsilidis KK, Dehghan A, Elliott P, Hyppönen E, Tzoulaki Iet al., 2019, Associations of genetically determined iron status across the phenome: a mendelian randomization study, PLoS Medicine, Vol: 16, ISSN: 1549-1277

BackgroundIron is integral to many physiological processes and variations in its levels, even within the normal range, can have implications for health. The objective of this study was to explore the broad clinical effects of varying iron status.Methods and FindingsGenome-wide association study summary data obtained from 48,972 European individuals (55% female) across 19 cohorts in the Genetics of Iron Status Consortium were used to identify three genetic variants (rs1800562 and rs1799945 in the hemochromatosis gene, and rs855791 in the transmembrane protease serine 6 gene) that associate with increased serum iron, ferritin and transferrin saturation, and decreased transferrin levels, thus serving as instruments for systemic iron status. Phenome-wide association study (PheWAS) of these instruments was performed on 415,482 European individuals (54% female) in the UK Biobank that were aged 40-69 years when recruited from 2006 to 2010, with their genetic data linked to Hospital Episode Statistics from April 1995 to March 2016. Two-sample summary data Mendelian randomization (MR) analysis was performed to investigate the effect of varying iron status on outcomes across the human phenome. MR-PheWAS analysis for the three iron status genetic instruments was performed separately and then pooled by meta-analysis. Correction was made for testing of multiple correlated phenotypes using a 5% false discovery rate threshold. Heterogeneity between MR estimates for different instruments was used to indicate possible bias due to effects of the genetic variants through pathways unrelated to iron status. There were 904 distinct phenotypes included in the MR-PheWAS analyses. After correcting for multiple testing, the three genetic instruments for systemic iron status demonstrated consistent evidence of a causal effect of higher iron status on decreasing risk of traits related to anemia (iron deficiency anemia: odds ratio [OR] scaled to a standard deviation increase in genetically dete

Journal article

de Vries PS, Brown MR, Bentley AR, Sung YJ, Winkler TW, Ntalla I, Schwander K, Kraja AT, Guo X, Franceschini N, Cheng C-Y, Sim X, Vojinovic D, Huffman JE, Musani SK, Li C, Feitosa MF, Richard MA, Noordam R, Aschard H, Bartz TM, Bielak LF, Deng X, Dorajoo R, Lohman KK, Manning AK, Rankinen T, Smith AV, Tajuddin SM, Evangelou E, Graff M, Alver M, Boissel M, Chai JF, Chen X, Divers J, Gandin I, Gao C, Goel A, Hagemeijer Y, Harris SE, Hartwig FP, He M, Horimoto ARVR, Hsu F-C, Jackson AU, Kasturiratne A, Komulainen P, Kühnel B, Laguzzi F, Lee JH, Luan J, Lyytikäinen L-P, Matoba N, Nolte IM, Pietzner M, Riaz M, Said MA, Scott RA, Sofer T, Stancáková A, Takeuchi F, Tayo BO, van der Most PJ, Varga TV, Wang Y, Ware EB, Wen W, Yanek LR, Zhang W, Zhao JH, Afaq S, Amin N, Amini M, Arking DE, Aung T, Ballantyne C, Boerwinkle E, Broeckel U, Campbell A, Canouil M, Charumathi S, Chen Y-DI, Connell JM, de Faire U, de Las Fuentes L, de Mutsert R, de Silva HJ, Ding J, Dominiczak AF, Duan Q, Eaton CB, Eppinga RN, Faul JD, Fisher V, Forrester T, Franco OH, Friedlander Y, Ghanbari M, Giulianini F, Grabe HJ, Grove ML, Gu CC, Harris TB, Heikkinen S, Heng C-K, Hirata M, Hixson JE, Howard BV, Ikram MA, InterAct Consortium, Jacobs DR, Johnson C, Jonas JB, Kammerer CM, Katsuya T, Khor CC, Kilpeläinen TO, Koh W-P, Koistinen HA, Kolcic I, Kooperberg C, Krieger JE, Kritchevsky SB, Kubo M, Kuusisto J, Lakka TA, Langefeld CD, Langenberg C, Launer LJ, Lehne B, Lemaitre RN, Li Y, Liang J, Liu J, Liu K, Loh M, Louie T, Mägi R, Manichaikul AW, McKenzie CA, Meitinger T, Metspalu A, Milaneschi Y, Milani L, Mohlke KL, Mosley TH, Mukamal KJ, Nalls MA, Nauck M, Nelson CP, Sotoodehnia N, O'Connell JR, Palmer ND, Pazoki R, Pedersen NL, Peters A, Peyser PA, Polasek O, Poulter N, Raffel LJ, Raitakari OT, Reiner AP, Rice TK, Rich SS, Robino A, Robinson JG, Rose LM, Rudan I, Schmidt CO, Schreiner PJ, Scott WR, Sever P, Shi Y, Sidney S, Sims M, Smith BH, Smith JA, Snieder H, Starr JM, Strauch K, Tan N, Taylor KDet al., 2019, Multi-ancestry genome-wide association study of lipid levels incorporating gene-alcohol interactions, American Journal of Epidemiology, Vol: 188, Pages: 1033-1054, ISSN: 1476-6256

An individual's lipid profile is influenced by genetic variants and alcohol consumption, but the contribution of interactions between these exposures has not been studied. We therefore incorporated gene-alcohol interactions into a multi-ancestry genome-wide association study of levels of high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides. We included 45 studies in Stage 1 (genome-wide discovery) and 66 studies in Stage 2 (focused follow-up), for a total of 394,584 individuals from five ancestry groups. Genetic main and interaction effects were jointly assessed by a 2 degrees of freedom (DF) test, and a 1 DF test was used to assess the interaction effects alone. Variants at 495 loci were at least suggestively associated (P < 1 × 10-6) with lipid levels in Stage 1 and were evaluated in Stage 2, followed by combined analyses of Stage 1 and Stage 2. In the combined analysis of Stage 1 and Stage 2, 147 independent loci were associated with lipid levels at P < 5 × 10-8 using 2 DF tests, of which 18 were novel. No genome-wide significant associations were found testing the interaction effect alone. The novel loci included several genes (PCSK5, VEGFB, and A1CF) with a putative role in lipid metabolism based on existing evidence from cellular and experimental models.

Journal article

Yu B, Zanetti KA, Temprosa M, Albanes D, Appel N, Barrera CB, Ben-Shlomo Y, Boerwinkle E, Casas JP, Clish C, Dale C, Dehghan A, Derkach A, Eliassen AH, Elliott P, Fahy E, Gieger C, Gunter MJ, Harada S, Harris T, Herr DR, Herrington D, Hirschhorn JN, Hoover E, Hsing AW, Johansson M, Kelly RS, Khoo CM, Kivimäki M, Kristal BS, Langenberg C, Lasky-Su J, Lawlor DA, Lotta LA, Mangino M, Le Marchand L, Mathé E, Matthews CE, Menni C, Mucci LA, Murphy R, Oresic M, Orwoll E, Ose J, Pereira AC, Playdon MC, Poston L, Price J, Qi Q, Rexrode K, Risch A, Sampson J, Seow WJ, Sesso HD, Shah SH, Shu X-O, Smith GCS, Sovio U, Stevens VL, Stolzenberg-Solomon R, Takebayashi T, Tillin T, Travis R, Tzoulaki I, Ulrich CM, Vasan RS, Verma M, Wang Y, Wareham NJ, Wong A, Younes N, Zhao H, Zheng W, Moore SCet al., 2019, The Consortium of Metabolomics Studies (COMETS): Metabolomics in 47 Prospective Cohort Studies, American Journal of Epidemiology, Vol: 188, Pages: 991-1012, ISSN: 1476-6256

The Consortium of Metabolomics Studies (COMETS) was established in 2014 to facilitate large-scale collaborative research on the human metabolome and its relationship with disease etiology, diagnosis, and prognosis. COMETS comprises 47 cohorts from Asia, Europe, North America, and South America that together include more than 136,000 participants with blood metabolomics data on samples collected from 1985 to 2017. Metabolomics data were provided by 17 different platforms, with the most frequently used labs being Metabolon, Inc. (14 cohorts), the Broad Institute (15 cohorts), and Nightingale Health (11 cohorts). Participants have been followed for a median of 23 years for health outcomes including death, cancer, cardiovascular disease, diabetes, and others; many of the studies are ongoing. Available exposure-related data include common clinical measurements and behavioral factors, as well as genome-wide genotype data. Two feasibility studies were conducted to evaluate the comparability of metabolomics platforms used by COMETS cohorts. The first study showed that the overlap between any 2 different laboratories ranged from 6 to 121 metabolites at 5 leading laboratories. The second study showed that the median Spearman correlation comparing 111 overlapping metabolites captured by Metabolon and the Broad Institute was 0.79 (interquartile range, 0.56–0.89).

Journal article

Wuttke M, Li Y, Li M, Sieber KB, Feitosa MF, Gorski M, Tin A, Wang L, Chu AY, Hoppmann A, Kirsten H, Giri A, Chai J-F, Sveinbjornsson G, Tayo BO, Nutile T, Fuchsberger C, Marten J, Cocca M, Ghasemi S, Xu Y, Horn K, Noce D, Van der Most PJ, Sedaghat S, Yu Z, Akiyama M, Afaq S, Ahluwalia TS, Almgren P, Amin N, Arnlov J, Bakker SJL, Bansal N, Baptista D, Bergmann S, Biggs ML, Biino G, Boehnke M, Boerwinkle E, Boissel M, Bottinger EP, Boutin TS, Brenner H, Brumat M, Burkhardt R, Butterworth AS, Campana E, Campbell A, Campbell H, Canouil M, Carroll RJ, Catamo E, Chambers JC, Chee M-L, Chee M-L, Chen X, Cheng C-Y, Cheng Y, Christensen K, Cifkova R, Ciullo M, Concas MP, Cook JP, Coresh J, Corre T, Sala CF, Cusi D, Danesh J, Daw EW, De Borst MH, De Grandi A, De Mutsert R, De Vries APJ, Degenhardt F, Delgado G, Demirkan A, Di Angelantonio E, Dittrich K, Divers J, Dorajoo R, Eckardt K-U, Ehret G, Elliott P, Endlich K, Evans MK, Felix JF, Foo VHX, Franco OH, Franke A, Freedman BI, Freitag-Wolf S, Friedlander Y, Froguel P, Gansevoort RT, Gao H, Gasparini P, Gaziano JM, Giedraitis V, Gieger C, Girotto G, Giulianini F, Gogele M, Gordon SD, Gudbjartsson DF, Gudnason V, Haller T, Hamet P, Harris TB, Hartman CA, Hayward C, Hellwege JN, Heng C-K, Hicks AA, Hofer E, Huang W, Hutri-Kahonen N, Hwang S-J, Ikram MA, Indridason OS, Ingelsson E, Ising M, Jaddoe VWV, Jakobsdottir J, Jonas JB, Joshi PK, Josyula NS, Jung B, Kahonen M, Kamatani Y, Kammerer CM, Kanai M, Kastarinen M, Kerr SM, Khor C-C, Kiess W, Kleber ME, Koenig W, Kooner JS, Korner A, Kovacs P, Kraja AT, Krajcoviechova A, Kramer H, Kramer BK, Kronenberg F, Kubo M, Kuhnel B, Kuokkanen M, Kuusisto J, La Bianca M, Laakso M, Lange LA, Langefeld CD, Lee JJ-M, Lehne B, Lehtimaki T, Lieb W, Lim S-C, Lind L, Lindgren CM, Liu J, Liu J, Loeffler M, Loos RJF, Lucae S, Lukas MA, Lyytikainen L-P, Magi R, Magnusson PKE, Mahajan A, Martin NG, Martins J, Marz W, Mascalzoni D, Matsuda K, Meisinger C, Meitinger T, Melander O, Metspalu A, Mikaelset al., 2019, A catalog of genetic loci associated with kidney function from analyses of a million individuals, Nature Genetics, Vol: 51, Pages: 957-972, ISSN: 1061-4036

Chronic kidney disease (CKD) is responsible for a public health burden with multi-systemic complications. Through trans-ancestry meta-analysis of genome-wide association studies of estimated glomerular filtration rate (eGFR) and independent replication (n = 1,046,070), we identified 264 associated loci (166 new). Of these, 147 were likely to be relevant for kidney function on the basis of associations with the alternative kidney function marker blood urea nitrogen (n = 416,178). Pathway and enrichment analyses, including mouse models with renal phenotypes, support the kidney as the main target organ. A genetic risk score for lower eGFR was associated with clinically diagnosed CKD in 452,264 independent individuals. Colocalization analyses of associations with eGFR among 783,978 European-ancestry individuals and gene expression across 46 human tissues, including tubulo-interstitial and glomerular kidney compartments, identified 17 genes differentially expressed in kidney. Fine-mapping highlighted missense driver variants in 11 genes and kidney-specific regulatory variants. These results provide a comprehensive priority list of molecular targets for translational research.

Journal article

Elliott P, Aresu M, Gao H, Vergnaud A-C, Heard A, McRobie D, Spear J, Singh D, Kongsgård HW, Mbema C, Muller DCet al., 2019, Use of TETRA personal radios and sickness absence in the Airwave Health Monitoring Study of the British police forces, Environmental Research, Vol: 175, Pages: 148-155, ISSN: 0013-9351

BackgroundTerrestrial Trunked Radio (TETRA) is used for radiocommunications among the British police forces.ObjectivesTo investigate association of personal radio use and sickness absence among police officers and staff from the Airwave Health Monitoring Study.MethodsParticipant-level sickness absence records for 26 forces were linked with personal radio use for 32,102 participants. We used multivariable logistic regression to analyse TETRA usage in year prior to enrolment and sickness absence (lasting more than 7 or 28 consecutive days) in the following year and a zero-inflated negative binomial model for analyses of number of sickness absence episodes of any duration (‘spells’) over the same period. In secondary analyses, we looked at an extended period of observation among a sub-cohort with linked data over time, using Cox proportional hazards regression.ResultsMedian personal radio use (year prior to enrolment) was 29.7 min per month (interquartile range 7.5, 64.7) among users. In the year following enrolment there were 25,655 sickness absence spells among 15,248 participants. There were similar risks of sickness absence lasting more than seven days among users and non-users, although among users risk was higher with greater use, odds ratio = 1.04 (95% confidence interval [CI] 1.02 to 1.06) per doubling of radio use. There was no association for sickness absence of more than 28 days. For sickness absence spells, risk was lower among users than non-users (incidence rate ratio = 0.91; 95% CI 0.75 to 1.11), again with higher risk among users for greater radio use. There was no association between radio use and sickness absence in secondary analyses.DiscussionThere were similar or lower risks of sickness absence in TETRA radio users compared with non-users. Among users, the higher risk of sickness absence with greater radio use may reflect working pattern differences among police personnel rather than effects of radiofrequency exposure.

Journal article

Bixby H, Bentham J, Zhou B, Di Cesare M, Paciorek CJ, Bennett JE, Taddei C, Stevens GA, Rodriguez-Martinez A, Carrillo-Larco RM, Khang Y-H, Soric M, Gregg E, Miranda JJ, Bhutta ZA, Savin S, Sophiea MK, Iurilli MLC, Solomon BD, Cowan MJ, Riley LM, Danaei G, Bovet P, Christa-Emandi A, Hambleton IR, Hayes AJ, Ikeda N, Kengne AP, Laxmaiah A, Li Y, McGarvey ST, Mostafa A, Neovius M, Starc G, Zainuddin AA, Ezzati Met al., 2019, Rising rural body-mass index is the main driver of the global obesity epidemic, Nature, Vol: 569, Pages: 260-264, ISSN: 0028-0836

Body-mass index (BMI) has increased steadily in most countries in parallel with a rise in the proportion of the population who live in cities1,2. This has led to a widely reported view that urbanization is one of the most important drivers of the global rise in obesity3,4,5,6. Here we use 2,009 population-based studies, with measurements of height and weight in more than 112 million adults, to report national, regional and global trends in mean BMI segregated by place of residence (a rural or urban area) from 1985 to 2017. We show that, contrary to the dominant paradigm, more than 55% of the global rise in mean BMI from 1985 to 2017—and more than 80% in some low- and middle-income regions—was due to increases in BMI in rural areas. This large contribution stems from the fact that, with the exception of women in sub-Saharan Africa, BMI is increasing at the same rate or faster in rural areas than in cities in low- and middle-income regions. These trends have in turn resulted in a closing—and in some countries reversal—of the gap in BMI between urban and rural areas in low- and middle-income countries, especially for women. In high-income and industrialized countries, we noted a persistently higher rural BMI, especially for women. There is an urgent need for an integrated approach to rural nutrition that enhances financial and physical access to healthy foods, to avoid replacing the rural undernutrition disadvantage in poor countries with a more general malnutrition disadvantage that entails excessive consumption of low-quality calories.

Journal article

Davies G, Lam M, Harris SE, Trampush JW, Luciano M, Hill WD, Hagenaars SP, Ritchie SJ, Marioni RE, Fawns-Ritchie C, Liewald DCM, Okely JA, Ahola-Olli AV, Barnes CLK, Bertram L, Bis JC, Burdick KE, Christoforou A, DeRosse P, Djurovic S, Espeseth T, Giakoumaki S, Giddaluru S, Gustavson DE, Hayward C, Hofer E, Ikram MA, Karlsson R, Knowles E, Lahti J, Leber M, Li S, Mather KA, Melle I, Morris D, Oldmeadow C, Palviainen T, Payton A, Pazoki R, Petrovic K, Reynolds CA, Sargurupremraj M, Scholz M, Smith JA, Smith AV, Terzikhan N, Thalamuthu A, Trompet S, van der Lee SJ, Ware EB, Windham BG, Wright MJ, Yang J, Yu J, Ames D, Amin N, Amouyel P, Andreassen OA, Armstrong NJ, Assareh AA, Attia JR, Attix D, Avramopoulos D, Bennett DA, Boehmer AC, Boyle PA, Brodaty H, Campbell H, Cannon TD, Cirulli ET, Congdon E, Conley ED, Corley J, Cox SR, Dale AM, Dehghan A, Dick D, Dickinson D, Eriksson JG, Evangelou E, Faul JD, Ford I, Freimer NA, Gao H, Giegling I, Gillespie NA, Gordon SD, Gottesman RF, Griswold ME, Gudnason V, Harris TB, Hartmann AM, Hatzimanolis A, Heiss G, Holliday EG, Joshi PK, Kahonen M, Kardia SLR, Karlsson I, Kleineidam L, Knopman DS, Kochan NA, Konte B, Kwok JB, Le Hellard S, Lee T, Lehtimaki T, Li S-C, Lill CM, Liu T, Koini M, London E, Longstreth WT, Lopez OL, Loukola A, Luck T, Lundervold AJ, Lundquist A, Lyytikainen L-P, Martin NG, Montgomery GW, Murray AD, Need AC, Noordam R, Nyberg L, Ollier W, Papenberg G, Pattie A, Polasek O, Poldrack RA, Psaty BM, Reppermund S, Riedel-Heller SG, Rose RJ, Rotter JI, Roussos P, Rovio SP, Saba Y, Sabb FW, Sachdev PS, Satizabal CL, Schmid M, Scott RJ, Scult MA, Simino J, Slagboom PE, Smyrnis N, Soumare A, Stefanis NC, Stott DJ, Straub RE, Sundet K, Taylor AM, Taylor KD, Tzoulaki I, Tzourio C, Uitterlinden A, Vitart V, Voineskos AN, Kaprio J, Wagner M, Wagner H, Weinhold L, Wen KH, Widen E, Yang Q, Zhao W, Adams HHH, Arking DE, Bilder RM, Bitsios P, Boerwinkle E, Chiba-Falek O, Corvin A, De Jager PL, Debette S, Donohoe G, Elliottet al., 2019, Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function (vol 9, 2098, 2018), NATURE COMMUNICATIONS, Vol: 10, ISSN: 2041-1723

Journal article

McCrory C, Leahy S, Ribeiro AI, Fraga S, Barros H, Avendano M, Vineis P, Layte R, Alenius H, Baglietto L, Bartley M, Bellone M, Berger E, Bochud M, Candiani G, Carmeli C, Carra L, Castagne R, Chadeau-Hyam M, Cima S, Costa G, Courtin E, Delpierre C, D'Errico A, Donkin A, Dugue P-A, Elliott P, Fagherazzi G, Fiorito G, Gandini M, Gares V, Gerbouin-Rerrolle P, Giles G, Goldberg M, Greco D, Guida F, Hodge A, Karimi M, Karisola P, Kelly M, Kivimaki M, Laine J, Lang T, Laurent A, Lepage B, Lorsch D, Machell G, Mackenbach J, Marmot M, Milne R, Muennig P, Nusselder W, Petrovic D, Polidoro S, Preisig M, Recalcati P, Reinhard E, Ribeiro AI, Ricceri F, Robinson O, Valverde JR, Severi G, Simmons T, Stringhini S, Terhi V, Than J, Vergnaud A-C, Vigna-Taglianti F, Vollenweider P, Zins Met al., 2019, Maternal educational inequalities in measured body mass index trajectories in three European countries, PAEDIATRIC AND PERINATAL EPIDEMIOLOGY, Vol: 33, Pages: 226-237, ISSN: 0269-5022

Journal article

Fiorito G, McCrory C, Robinson O, Carmeli C, Rosales CO, Zhang Y, Colicino E, Dugué P-A, Artaud F, McKay GJ, Jeong A, Mishra PP, Nøst TH, Krogh V, Panico S, Sacerdote C, Tumino R, Palli D, Matullo G, Guarrera S, Gandini M, Bochud M, Dermitzakis E, Muka T, Schwartz J, Vokonas PS, Just A, Hodge AM, Giles GG, Southey MC, Hurme MA, Young I, McKnight AJ, Kunze S, Waldenberger M, Peters A, Schwettmann L, Lund E, Baccarelli A, Milne RL, Kenny RA, Elbaz A, Brenner H, Kee F, Voortman T, Probst-Hensch N, Lehtimäki T, Elliot P, Stringhini S, Vineis P, Polidoro S, BIOS Consortium, Lifepath consortiumet al., 2019, Socioeconomic position, lifestyle habits and biomarkers of epigenetic aging: a multi-cohort analysis, Aging, Vol: 11, Pages: 2045-2070, ISSN: 1945-4589

Differences in health status by socioeconomic position (SEP) tend to be more evident at older ages, suggesting the involvement of a biological mechanism responsive to the accumulation of deleterious exposures across the lifespan. DNA methylation (DNAm) hasbeen proposed as a biomarker of biological aging that conserves memory of endogenous and exogenous stress during life. We examined the association of education level, as an indicator of SEP, and lifestyle-related variables with four biomarkers of age-dependent DNAm dysregulation: the total number of stochastic epigenetic mutations (SEMs) and three epigenetic clocks (Horvath, Hannum and Levine), in 18 cohorts spanning 12 countries. The four biological aging biomarkers were associated with education and different sets of risk factors independently,and themagnitude of the effectsdiffereddepending on the biomarker and the predictor. On average, the effect of low education on epigenetic aging was comparable with those of other lifestyle-related risk factors (obesity, alcohol intake), with the exception ofsmoking, which hada significantly stronger effect. Our study shows that low education is an independent predictor of accelerated biological (epigenetic) aging and that epigenetic clocks appear to be good candidates for disentangling the biological pathways underlying social inequalities in healthy aging and longevity.

Journal article

Piel F, Parkes B, Hambly P, Roca-Barcelo A, McCallion M, Leonardi G, Strosnider H, Yip F, Elliott P, Hansell Aet al., The Rapid Inquiry Facility 4.0: an open access tool for Environmental Public Health Tracking, International Journal of Epidemiology, ISSN: 1464-3685

The Rapid Inquiry Facility 4.0 (RIF) is a new user-friendly and open-access tool, developed by the UK Small Area Health Statistics Unit (SAHSU), to facilitate environment public health tracking (EPHT) or surveillance (EPHS). The RIF is designed to help public health professionals and academics to rapidly perform exploratory investigations of health and environmental data at the small-area level (e.g. postcode or detailed census areas) in order to identify unusual signals, such as disease clusters, and potential environmental hazards, whether localised (e.g. industrial site) or widespread (e.g. air and noise pollution). The RIF allows the use of advanced disease mapping methods, including Bayesian small-area smoothing, and complex risk analysis functionalities, while accounting for confounders. The RIF could be particularly useful to monitor spatio-temporal trends in mortality and morbidity associated with cardiovascular diseases, cancers, diabetes and chronic lung diseases, or to conduct local or national studies on air pollution, flooding, low-magnetic fields or nuclear powerplants.

Journal article

Bentley AR, Sung YJ, Brown MR, Winkler TW, Kraja AT, Ntalla I, Schwander K, Chasman D, Lim E, Deng X, Guo X, Liu J, Lu Y, Cheng C-Y, Sim X, Vojinovic D, Huffman JE, Musani SK, Li C, Feitosa MF, Richard MA, Noordam R, Baker J, Chen G, Aschard H, Bartz TM, Ding J, Dorajoo R, Manning AK, Rankinen T, Smith A, Tajuddin SM, Zhao W, Graff M, Alver M, Boissel M, Chai JF, Chen X, Divers J, Evangelou E, Gao C, Goel A, Hagemeijer Y, Harris SE, Hartwig FP, He M, Horimoto ARVR, Hsu F-C, Hung Y-J, Jackson AU, Kasturiratne A, Komulainen P, Kuehnel B, Leander K, Lin K-H, Luan J, Lyytikainen L-P, Matoba N, Nolte IM, Pietzner M, Prins B, Riaz M, Robino A, Said MA, Schupf N, Scott RA, Sofer T, Stancakova A, Takeuchi F, Tayo BO, van der Most PJ, Varga TV, Wang T-D, Wang Y, Ware EB, Wen W, Xiang Y-B, Yanek LR, Zhang W, Zhao JH, Adeyemo A, Afaq S, Amin N, Amini M, Arking DE, Arzumanyan Z, Aung T, Ballantyne C, Barr RG, Bielak LF, Boerwinkle E, Bottinger EP, Broeckel U, Brown M, Cade BE, Campbell A, Canouil M, Charumathi S, Chen Y-DI, Christensen K, Concas MP, Connell JM, de las Fuentes L, de Silva HJ, de Vries PS, Doumatey A, Duan Q, Eaton CB, Eppinga RN, Faul JD, Floyd JS, Forouhi NG, Forrester T, Friedlander Y, Gandin I, Gao H, Ghanbari M, Gharib SA, Gigante B, Giulianini F, Grabe HJ, Gu CC, Harris TB, Heikkinen S, Heng C-K, Hirata M, Hixson JE, Ikram MA, Jia Y, Joehanes R, Johnson C, Jonas JB, Justice AE, Katsuya T, Khor CC, Kilpelainen TO, Koh W-P, Kolcic I, Kooperberg C, Krieger JE, Kritchevsky SB, Kubo M, Kuusisto J, Lakka TA, Langefeld CD, Langenberg C, Launer LJ, Lehne B, Lewis CE, Li Y, Liang J, Lin S, Liu C-T, Liu J, Liu K, Loh M, Lohman KK, Louie T, Luzzi A, Magi R, Mahajan A, Manichaikul AW, McKenzie CA, Meitinger T, Metspalu A, Milaneschi Y, Milani L, Mohlke KL, Momozawa Y, Morris AP, Murray AD, Nalls MA, Nauck M, Nelson CP, North KE, O'Connell JR, Palmer ND, Papanicolau GJ, Pedersen NL, Peters A, Peyser PA, Polasek O, Poulter N, Raitakari OT, Reiner AP, Renstrom F, Rice TKet al., 2019, Multi-ancestry genome-wide gene-smoking interaction study of 387,272 individuals identifies new loci associated with serum lipids, Nature Genetics, Vol: 51, Pages: 636-648, ISSN: 1061-4036

The concentrations of high- and low-density-lipoprotein cholesterol and triglycerides are influenced by smoking, but it is unknown whether genetic associations with lipids may be modified by smoking. We conducted a multi-ancestry genome-wide gene–smoking interaction study in 133,805 individuals with follow-up in an additional 253,467 individuals. Combined meta-analyses identified 13 new loci associated with lipids, some of which were detected only because association differed by smoking status. Additionally, we demonstrate the importance of including diverse populations, particularly in studies of interactions with lifestyle factors, where genomic and lifestyle differences by ancestry may contribute to novel findings.

Journal article

Mireku MO, Barker MM, Mutz J, Shen C, Dumontheil I, Thomas MSC, Röösli M, Elliott P, Toledano MBet al., 2019, Processed data on the night-time use of screen-based media devices and adolescents’ sleep quality and health-related quality of life, Data in Brief, Vol: 23, ISSN: 2352-3409

The data presented in this article relate to the research article entitled “Night-time screen-based media device use and adolescents' sleep and health-related quality of life”. The present data reports findings from the investigation of the relationship between night-time screen-based media devices (SBMD) use and both sleep quality and health-related quality of life (HRQoL) among 11 to 12-year-olds. Baseline data from a large cohort of 6,616 adolescents from 39 schools in and around London, UK, participating in the Study of Cognition Adolescents and Mobile Phone (SCAMP) were analysed. Self-report data on adolescents’ use of any SBMD (mobile phone, tablet, laptop, television etc.) were the main exposures of interest. Mobile phone and television were the most commonly used portable and non-portable device, respectively. Sleep variables were derived from self-reported weekday and/or weekend bedtime, sleep onset latency (SOL) and wake time. Sleep quality was assessed using four standardised dimensions from the Swiss Health Survey. HRQoL was estimated using the KIDSCREEN-10 questionnaire.

Journal article

Wen X, Zhou L, Stamler J, Chan Q, Van Horn L, Daviglus ML, Dyer AR, Elliott P, Ueshima H, Miura K, Okuda N, Wu Y, Zhao Let al., 2019, Agreement between 24-h dietary recalls and 24-h urine collections for estimating sodium intake in China, Japan, UK, USA: the International Study of Macro- and Micro-nutrients and Blood Pressure, Journal of Hypertension, Vol: 37, Pages: 814-819, ISSN: 0263-6352

OBJECTIVE: The present study aims to compare 24-h dietary recalls with 24-h urine collections for the estimation of sodium intake at both population and individual levels in China, Japan, the United Kingdom (UK), and the United States of America (USA), using data from the International Study of Macro- and Micro-nutrients and Blood Pressure (INTERMAP). METHODS: Mean differences between 24-h dietary recalls and 24-h urine collections were calculated for their agreement in estimating sodium intake at the population level; relative and absolute differences as well as misclassification of salt intake groups (salt intake <6, 6-8.9, 9-11.9, 12-14.9, and ≥15 g/day) were used to determine the agreement at the individual level. RESULTS: The mean differences (95% CI) between dietary recalls and urine collections for China, Japan, UK, and USA were -54.0 (-59.8, -48.3), 3.9 (0.6, 7.2), 2.9 (-1.8, 7.6), and -3.5 (-5.8, -1.1) mmol/day, respectively. The proportions of individual relative differences beyond ±40% were 34.3% for China, 16.9% for Japan, 24.2% for UK, and 21.3% for USA; the proportions of individual absolute differences greater than 51.3 mmol/day (3 g salt) were 58.6% for China, 32.8% for Japan, 25.4% for UK, and 31.9% for USA. The rate for misclassification of salt intake groups at individual level for China, Japan, UK, and USA were 71.4, 60.9, 58.7, and 60.0%, respectively. CONCLUSION: The 24-h dietary recalls demonstrate greater agreement with the 24-h urine collections in estimating population sodium intake for Japan, UK, and USA, compared with China. The 24-h dietary recall has poor performance in assessing individual sodium intake in these four countries.

Journal article

Middeldorp CM, Felix JF, Mahajan A, McCarthy MI, EArly Genetics Lifecourse Epidemiology EAGLE consortium, Early Growth Genetics EGG, Rodriguez Aet al., 2019, The Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia: design, results and future prospects, European Journal of Epidemiology, Vol: 34, Pages: 279-300, ISSN: 0393-2990

The impact of many unfavorable childhood traits or diseases, such as low birth weight and mental disorders, is not limited to childhood and adolescence, as they are also associated with poor outcomes in adulthood, such as cardiovascular disease. Insight into the genetic etiology of childhood and adolescent traits and disorders may therefore provide new perspectives, not only on how to improve wellbeing during childhood, but also how to prevent later adverse outcomes. To achieve the sample sizes required for genetic research, the Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia were established. The majority of the participating cohorts are longitudinal population-based samples, but other cohorts with data on early childhood phenotypes are also involved. Cohorts often have a broad focus and collect(ed) data on various somatic and psychiatric traits as well as environmental factors. Genetic variants have been successfully identified for multiple traits, for example, birth weight, atopic dermatitis, childhood BMI, allergic sensitization, and pubertal growth. Furthermore, the results have shown that genetic factors also partly underlie the association with adult traits. As sample sizes are still increasing, it is expected that future analyses will identify additional variants. This, in combination with the development of innovative statistical methods, will provide detailed insight on the mechanisms underlying the transition from childhood to adult disorders. Both consortia welcome new collaborations. Policies and contact details are available from the corresponding authors of this manuscript and/or the consortium websites.

Journal article

Justice AE, Karaderi T, Highland HM, Young KL, Graff M, Lu Y, Turcot V, Auer PL, Fine RS, Guo X, Schurmann C, Lempradl A, Marouli E, Mahajan A, Winkler TW, Locke AE, Medina-Gomez C, Esko T, Vedantam S, Giri A, Lo KS, Alfred T, Mudgal P, Ng MCY, Heard-Costa NL, Feitosa MF, Manning AK, Willems SM, Sivapalaratnam S, Abecasis G, Alam DS, Allison M, Amouyel P, Arzumanyan Z, Balkau B, Bastarache L, Bergmann S, Bielak LF, Blüher M, Boehnke M, Boeing H, Boerwinkle E, Böger CA, Bork-Jensen J, Bottinger EP, Bowden DW, Brandslund I, Broer L, Burt AA, Butterworth AS, Caulfield MJ, Cesana G, Chambers JC, Chasman DI, Chen Y-DI, Chowdhury R, Christensen C, Chu AY, Collins FS, Cook JP, Cox AJ, Crosslin DS, Danesh J, de Bakker PIW, Denus SD, Mutsert RD, Dedoussis G, Demerath EW, Dennis JG, Denny JC, Angelantonio ED, Dörr M, Drenos F, Dubé M-P, Dunning AM, Easton DF, Elliott P, Evangelou E, Farmaki A-E, Feng S, Ferrannini E, Ferrieres J, Florez JC, Fornage M, Fox CS, Franks PW, Friedrich N, Gan W, Gandin I, Gasparini P, Giedraitis V, Girotto G, Gorski M, Grallert H, Grarup N, Grove ML, Gustafsson S, Haessler J, Hansen T, Hattersley AT, Hayward C, Heid IM, Holmen OL, Hovingh GK, Howson JMM, Hu Y, Hung Y-J, Hveem K, Ikram MA, Ingelsson E, Jackson AU, Jarvik GP, Jia Y, Jørgensen T, Jousilahti P, Justesen JM, Kahali B, Karaleftheri M, Kardia SLR, Karpe F, Kee F, Kitajima H, Komulainen P, Kooner JS, Kovacs P, Krämer BK, Kuulasmaa K, Kuusisto J, Laakso M, Lakka TA, Lamparter D, Lange LA, Langenberg C, Larson EB, Lee NR, Lee W-J, Lehtimäki T, Lewis CE, Li H, Li J, Li-Gao R, Lin L-A, Lin X, Lind L, Lindström J, Linneberg A, Liu C-T, Liu DJ, Luan J, Lyytikäinen L-P, MacGregor S, Mägi R, Männistö S, Marenne G, Marten J, Masca NGD, McCarthy MI, Meidtner K, Mihailov E, Moilanen L, Moitry M, Mook-Kanamori DO, Morgan A, Morris AP, Müller-Nurasyid M, Munroe PB, Narisu N, Nelson CP, Neville M, Ntalla I, O'Connell JR, Owen KR, Pedersen O, Peloso GM, Pennell CE, Perola M, Perry JA, Perry JRB, Pers THet al., 2019, Protein-coding variants implicate novel genes related to lipid homeostasis contributing to body-fat distribution, Nature Genetics, Vol: 51, Pages: 452-469, ISSN: 1061-4036

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

Journal article

Mireku MO, Barker M, Mutz J, Dumontheil I, Thomas MSC, Roosli M, Elliott P, Toledano Met al., 2019, Night-time screen-based media device use and adolescents’ sleep and health-related quality of life, Environment International, Vol: 124, Pages: 66-78, ISSN: 0160-4120

ObjectiveThe present study investigates the relationship between night-time screen-based media devices (SBMD) use, which refers to use within 1 h before sleep, in both lit and dark rooms, and sleep outcomes and health-related quality of life (HRQoL) among 11 to 12-year-olds.MethodsWe analysed baseline data from a large cohort of 6616 adolescents from 39 schools in and around London, United Kingdom, participating in the Study of Cognition Adolescents and Mobile Phone (SCAMP). Adolescents self-reported their use of any SBMD (mobile phone, tablet, laptop, television etc.). Sleep variables were derived from self-reported weekday and/or weekend bedtime, sleep onset latency (SOL) and wake time. Sleep quality was assessed using four standardised dimensions from the Swiss Health Survey. HRQoL was estimated using the KIDSCREEN-10 questionnaire.ResultsOver two-thirds (71.5%) of adolescents reported using at least one SBMD at night-time, and about a third (32.2%) reported using mobile phones at night-time in darkness. Night-time mobile phone and television use was associated with higher odds of insufficient sleep duration on weekdays (Odds Ratio, OR = 1.82, 95% Confidence Interval, CI [1.59, 2.07] and OR = 1.40, 95% CI [1.23, 1.60], respectively). Adolescents who used mobile phones in a room with light were more likely to have insufficient sleep (OR = 1.32, 95% CI [1.10, 1.60]) and later sleep midpoint (OR = 1.64, 95% CI [1.37, 1.95]) on weekends compared to non-users. The magnitude of these associations was even stronger for those who used mobile phones in darkness for insufficient sleep duration on weekdays (OR = 2.13, 95% CI [1.79, 2.54]) and for later sleep midpoint on weekdays (OR = 3.88, 95% CI [3.25, 4.62]) compared to non-users. Night-time use of mobile phones was associated with lower HRQoL and use in a dark room was associated with even lower KIDSCREEN-10 score (β = –1.18, 95% CI [–1.85, –0.52]) compared to no use.ConclusionsWe found consistent

Journal article

Müller CP, Chu C, Qin L, Liu C, Xu B, Gao H, Ruggeri B, Hieber S, Schneider J, Jia T, Tay N, Akira S, Satoh T, Banaschewski T, Bokde ALW, Bromberg U, Büchel C, Quinlan EB, Flor H, Frouin V, Garavan H, Gowland P, Heinz A, Ittermann B, Martinot J-L, Martinot M-LP, Artiges E, Lemaitre H, Nees F, Papadopoulos Orfanos D, Paus T, Poustka L, Millenet S, Fröhner JH, Smolka MN, Walter H, Whelan R, Bakalkin G, Liu Y, Desrivières S, Elliott P, Eulenburg V, Levy D, Crews F, Schumann Get al., 2019, The cortical neuroimmune regulator TANK affects emotional processing and enhances alcohol drinking: a translational study, Cerebral Cortex, Vol: 29, Pages: 1736-1751, ISSN: 1047-3211

Alcohol abuse is a major public health problem worldwide. Understanding the molecular mechanisms that control regular drinking may help to reduce hazards of alcohol consumption. While immunological mechanisms have been related to alcohol drinking, most studies reported changes in immune function that are secondary to alcohol use. In this report, we analyse how the gene "TRAF family member-associated NF-κB activator" (TANK) affects alcohol drinking behavior. Based on our recent discovery in a large GWAS dataset that suggested an association of TANK, SNP rs197273, with alcohol drinking, we report that SNP rs197273 in TANK is associated both with gene expression (P = 1.16 × 10-19) and regional methylation (P = 5.90 × 10-25). A tank knock out mouse model suggests a role of TANK in alcohol drinking, anxiety-related behavior, as well as alcohol exposure induced activation of insular cortex NF-κB. Functional and structural neuroimaging studies among up to 1896 adolescents reveal that TANK is involved in the control of brain activity in areas of aversive interoceptive processing, including the insular cortex, but not in areas related to reinforcement, reward processing or impulsiveness. Our findings suggest that the cortical neuroimmune regulator TANK is associated with enhanced aversive emotional processing that better protects from the establishment of alcohol drinking behavior.

Journal article

Toledano MB, Mutz J, Roosli M, Thomas MSC, Dumontheil I, Elliott Pet al., 2019, Cohort profile: the study of cognition, adolescents and mobile phones (SCAMP), International Journal of Epidemiology, Vol: 48, Pages: 25-26l, ISSN: 1464-3685

The Study of Cognition, Adolescents and Mobile Phones (SCAMP) is a prospective secondary school-based cohort study established to investigate whether use of mobile phones and other wireless devices that emit radio-frequency electromagnetic fields (RF-EMF) is associated with cognitive, behavioural, educational, physical and mental health outcomes during adolescence. Specifically, the principal aim is to discern whether any observed associations may be due to: (i) RF-EMF exposure from mobile phones; (ii) a combination of various RF-EMF sources (e.g. digital enhanced cordless technology phones or wireless internet); or (iii) other behavioural reasons associated with technology use for communication and entertainment, irrespective of exposure to RF-EMF.

Journal article

Kilpelainen TO, Bentley AR, Noordam R, Sung YJ, Schwander K, Winkler TW, Jakupovic H, Chasman DI, Manning A, Ntalla I, Aschard H, Brown MR, de las Fuentes L, Franceschini N, Guo X, Vojinovic D, Aslibekyan S, Feitosa MF, Kho M, Musani SK, Richard M, Wang H, Wang Z, Bartz TM, Bielak LF, Campbell A, Dorajoo R, Fisher V, Hartwig FP, Horimoto ARVR, Li C, Lohman KK, Marten J, Sim X, Smith AV, Tajuddin SM, Alver M, Amini M, Boissel M, Chai JF, Chen X, Divers J, Evangelou E, Gao C, Graff M, Harris SE, He M, Hsu F-C, Jackson AU, Zhao JH, Kraja AT, Kuehnel B, Laguzzi F, Lyytikainen L-P, Nolte IM, Rauramaa R, Riaz M, Robino A, Rueedi R, Stringham HM, Takeuchi F, van der Most PJ, Varga TV, Verweij N, Ware EB, Wen W, Li X, Yanek LR, Amin N, Arnett DK, Boerwinkle E, Brumat M, Cade B, Canouil M, Chen Y-DI, Concas MP, Connell J, de Mutsert R, de Silva HJ, de Vries PS, Demirkan A, Ding J, Eaton CB, Faul JD, Friedlander Y, Gabriel KP, Ghanbari M, Giulianini F, Gu CC, Gu D, Harris TB, He J, Heikkinen S, Heng C-K, Hunt SC, Ikram MA, Jonas JB, Koh W-P, Komulainen P, Krieger JE, Kritchevsky SB, Kutalik Z, Kuusisto J, Langefeld CD, Langenberg C, Launer LJ, Leander K, Lemaitre RN, Lewis CE, Liang J, Alizadeh BZ, Boezen HM, Franke L, Navis G, Rots M, Swertz M, Wolffenbuttel BHR, Wijmenga C, Liu J, Magi R, Manichaikul A, Meitinger T, Metspalu A, Milaneschi Y, Mohlke KL, Mosley TH, Murray AD, Nalls MA, Nang E-EK, Nelson CP, Nona S, Norris JM, Nwuba CV, O'Connell J, Palmer ND, Papanicolau GJ, Pazoki R, Pedersen NL, Peters A, Peyser PA, Polasek O, Porteous DJ, Poveda A, Raitakari OT, Rich SS, Risch N, Robinson JG, Rose LM, Rudan I, Schreiner PJ, Scott RA, Sidney SS, Sims M, Smith JA, Snieder H, Sofer T, Starr JM, Sternfeld B, Strauch K, Tang H, Taylor KD, Tsai MY, Tuomilehto J, Uitterlinden AG, van der Ende MY, van Heemst D, Voortman T, Waldenberger M, Wennberg P, Wilson G, Xiang Y-B, Yao J, Yu C, Yuan J-M, Zhao W, Zonderman AB, Becker DM, Boehnke M, Bowden DW, de Faire U, Deary IJ, Elliott Pet al., 2019, Multi-ancestry study of blood lipid levels identifies four loci interacting with physical activity, Nature Communications, Vol: 10, ISSN: 2041-1723

Many genetic loci affect circulating lipid levels, but it remains unknown whether lifestyle factors, such as physical activity, modify these genetic effects. To identify lipid loci interacting with physical activity, we performed genome-wide analyses of circulating HDL cholesterol, LDL cholesterol, and triglyceride levels in up to 120,979 individuals of European, African, Asian, Hispanic, and Brazilian ancestry, with follow-up of suggestive associations in an additional 131,012 individuals. We find four loci, in/near CLASP1, LHX1, SNTA1, and CNTNAP2, that are associated with circulating lipid levels through interaction with physical activity; higher levels of physical activity enhance the HDL cholesterol-increasing effects of the CLASP1, LHX1, and SNTA1 loci and attenuate the LDL cholesterol-increasing effect of the CNTNAP2 locus. The CLASP1, LHX1, and SNTA1 regions harbor genes linked to muscle function and lipid metabolism. Our results elucidate the role of physical activity interactions in the genetic contribution to blood lipid levels.

Journal article

Pazoki R, Dehghan A, Evangelou E, Warren H, Gao H, Caulfield M, Elliott P, Tzoulaki Iet al., 2019, Correction to: Genetic predisposition to high blood pressure and lifestyle factors: associations with midlife blood pressure levels and cardiovascular events, Circulation, Vol: 139, Pages: E2-E2, ISSN: 0009-7322

Background: High blood pressure (BP) is a major risk factor for cardiovascular diseases (CVDs), the leading cause of mortality worldwide. Both heritable and lifestyle risk factors contribute to elevated BP levels. We aimed to investigate the extent to which lifestyle factors could offset the effect of an adverse BP genetic profile and its effect on CVD risk.Methods: We constructed a genetic risk score for high BP by using 314 published BP loci in 277 005 individuals without previous CVD from the UK Biobank study, a prospective cohort of individuals aged 40 to 69 years, with a median of 6.11 years of follow-up. We scored participants according to their lifestyle factors including body mass index, healthy diet, sedentary lifestyle, alcohol consumption, smoking, and urinary sodium excretion levels measured at recruitment. We examined the association between tertiles of genetic risk and tertiles of lifestyle score with BP levels and incident CVD by using linear regression and Cox regression models, respectively.Results: Healthy lifestyle score was strongly associated with BP (P<10–320) for systolic and diastolic BP and CVD events regardless of the underlying BP genetic risk. Participants with a favorable in comparison with an unfavorable lifestyle (bottom versus top tertile lifestyle score) had 3.6, 3.5, and 3.6 mm Hg lower systolic BP in low, middle, and high genetic risk groups, respectively (P for interaction=0.0006). Similarly, favorable in comparison with unfavorable lifestyle showed 30%, 31%, and 33% lower risk of CVD among participants in low, middle, and high genetic risk groups, respectively (P for interaction=0.99).Conclusions: Our data further support population-wide efforts to lower BP in the population via lifestyle modification. The advantages and disadvantages of disclosing genetic predisposition to high BP for risk stratification needs careful evaluation.

Journal article

Erzurumluoglu AM, Chambers JC, Elliott P, Evangelou E, Kooner JS, Poulter N, Sever P, Zhang W, Howson JMM, Wells Jet al., 2019, Meta-analysis of up to 622,409 individuals identifies 40 novel smoking behaviour associated genetic loci, Molecular Psychiatry, ISSN: 1359-4184

Smoking is a major heritable and modifiable risk factor for many diseases, including cancer, common respiratory disorders and cardiovascular diseases. Fourteen genetic loci have previously been associated with smoking behaviour-related traits. We tested up to 235,116 single nucleotide variants (SNVs) on the exome-array for association with smoking initiation, cigarettes per day, pack-years, and smoking cessation in a fixed effects meta-analysis of up to 61 studies (up to 346,813 participants). In a subset of 112,811 participants, a further one million SNVs were also genotyped and tested for association with the four smoking behaviour traits. SNV-trait associations with P < 5 × 10−8 in either analysis were taken forward for replication in up to 275,596 independent participants from UK Biobank. Lastly, a meta-analysis of the discovery and replication studies was performed. Sixteen SNVs were associated with at least one of the smoking behaviour traits (P < 5 × 10−8) in the discovery samples. Ten novel SNVs, including rs12616219 near TMEM182, were followed-up and five of them (rs462779 in REV3L, rs12780116 in CNNM2, rs1190736 in GPR101, rs11539157 in PJA1, and rs12616219 near TMEM182) replicated at a Bonferroni significance threshold (P < 4.5 × 10−3) with consistent direction of effect. A further 35 SNVs were associated with smoking behaviour traits in the discovery plus replication meta-analysis (up to 622,409 participants) including a rare SNV, rs150493199, in CCDC141 and two low-frequency SNVs in CEP350 and HDGFRP2. Functional follow-up implied that decreased expression of REV3L may lower the probability of smoking initiation. The novel loci will facilitate understanding the genetic aetiology of smoking behaviour and may lead to the identification of potential drug targets for smoking prevention and/or cessation.

Journal article

Kraja AT, Liu C, Fetterman JL, Graff M, Have CT, Gu C, Yanek LR, Feitosa MF, Arking DE, Chasman D, Young K, Ligthart S, Hill WD, Weiss S, Luan J, Giulianini F, Li-Gao R, Hartwig FP, Lin SJ, Wang L, Richardson TG, Yao J, Fernandez EP, Ghanbari M, Wojczynski MK, Lee W-J, Argos M, Armasu SM, Barve RA, Ryan KA, An P, Baranski TJ, Bielinski SJ, Bowden DW, Broeckel U, Christensen K, Chu AY, Corley J, Cox SR, Uitterlinden AG, Rivadeneira F, Cropp CD, Daw EW, van Heemst D, de las Fuentes L, Gao H, Tzoulaki I, Ahluwalia TS, de Mutsert R, Emery LS, Erzurumluoglu AM, Perry JA, Fu M, Forouhi NG, Gu Z, Hai Y, Harris SE, Hemani G, Hunt SC, Irvin MR, Jonsson AE, Justice AE, Kernson ND, Larson NB, Lin K-H, Love-Gregory LD, Mathias RA, Lee JH, Nauck M, Noordam R, Ong KK, Pankow J, Patki A, Pattie A, Petersmann A, Qi Q, Ribel-Madsen R, Rohde R, Sandow K, Schnurr TM, Sofer T, Starr JM, Taylor AM, Teumer A, Timpson NJ, de Haan HG, Wang Y, Weeke PE, Williams C, Wu H, Yang W, Zeng D, Witte DR, Weir BS, Wareham NJ, Vestergaard H, Turner ST, Torp-Pedersen C, Stergiakouli E, Sheu WH-H, Rosendaal FR, Ikram MA, Franco OH, Ridker PM, Perls TT, Pedersen O, Nohr EA, Newman AB, Linneberg A, Langenberg C, Kilpelainen TO, Kardia SLR, Jorgensen ME, Jorgensen T, Sorensen TIA, Homuth G, Hansen T, Goodarzi MO, Deary IJ, Christensen C, Chen Y-DI, Chakravarti A, Brandslund I, Bonnelykke K, Taylor KD, Wilson JG, Rodriguez S, Davies G, Horta BL, Thyagarajan B, Rao DC, Grarup N, Davila-Roman VG, Hudson G, Guo X, Arnett DK, Hayward C, Vaidya D, Mook-Kanamori DO, Tiwari HK, Levy D, Loos RJF, Dehghan A, Elliott P, Malik AN, Scott RA, Becker DM, de Andrade M, Province MA, Meigs JB, Rotter J, North KEet al., 2019, Associations of mitochondrial and nuclear mitochondrial variants and genes with seven metabolic traits, American Journal of Human Genetics, Vol: 104, Pages: 112-138, ISSN: 0002-9297

Mitochondria (MT), the major site of cellular energy production, are under dual genetic control by 37 mitochondrial DNA (mtDNA) genes and numerous nuclear genes (MT-nDNA). In the CHARGEmtDNA+ Consortium, we studied genetic associations of mtDNA and MT-nDNA associations with body mass index (BMI), waist-hip-ratio (WHR), glucose, insulin, HOMA-B, HOMA-IR, and HbA1c. This 45-cohort collaboration comprised 70,775 (insulin) to 170,202 (BMI) pan-ancestry individuals. Validation and imputation of mtDNA variants was followed by single-variant and gene-based association testing. We report two significant common variants, one in MT-ATP6 associated (p ≤ 5E−04) with WHR and one in the D-loop with glucose. Five rare variants in MT-ATP6, MT-ND5, and MT-ND6 associated with BMI, WHR, or insulin. Gene-based meta-analysis identified MT-ND3 associated with BMI (p ≤ 1E−03). We considered 2,282 MT-nDNA candidate gene associations compiled from online summary results for our traits (20 unique studies with 31 dataset consortia’s genome-wide associations [GWASs]). Of these, 109 genes associated (p ≤ 1E−06) with at least 1 of our 7 traits. We assessed regulatory features of variants in the 109 genes, cis- and trans-gene expression regulation, and performed enrichment and protein-protein interactions analyses. Of the identified mtDNA and MT-nDNA genes, 79 associated with adipose measures, 49 with glucose/insulin, 13 with risk for type 2 diabetes, and 18 with cardiovascular disease, indicating for pleiotropic effects with health implications. Additionally, 21 genes related to cholesterol, suggesting additional important roles for the genes identified. Our results suggest that mtDNA and MT-nDNA genes and variants reported make important contributions to glucose and insulin metabolism, adipocyte regulation, diabetes, and cardiovascular disease.

Journal article

Gibson R, Lau C-HE, Chan Q, Chekmeneva E, Loo R, Ebbels TM, Dyer AR, Miura K, Ueshima H, Zhao L, Daviglus ML, Elliott P, Stamler J, Holmes E, Van Horn Let al., 2019, Cross-Sectional Investigation of the Relationship Between Fish Consumption and Its Urinary Biomarkers With Blood Pressure Across Asian and Western Populations: Results From the INTERMAP Study, Scientific Sessions of the American-Heart-Association on Epidemiology and Prevention/Lifestyle and Cardiometabolic Health, Publisher: LIPPINCOTT WILLIAMS & WILKINS, ISSN: 0009-7322

Conference paper

Yan L, Carter E, Fu Y, Xie G, Xie W, Kelly F, Elliott P, Yang X, Ezzati M, Baumgartner J, Zhao L, Wu Y, Chan Qet al., 2019, Changes of Blood Pressure and Urinary Sodium Over 18 Years in Rural China: Results From the INTERMAP China Prospective Study, Scientific Sessions of the American-Heart-Association on Epidemiology and Prevention/Lifestyle and Cardiometabolic Health, Publisher: LIPPINCOTT WILLIAMS & WILKINS, ISSN: 0009-7322

Conference paper

Chan Q, Lau C-HE, Gibson R, Chekmeneva E, Correia GDS, Loo R, Ebbels TM, Posma JM, Dyer AR, Miura K, Ueshima H, Zhao L, Daviglus ML, Elliott P, Stamler J, Holmes E, Van Horn Let al., 2019, Relationships of Dietary and Supplement Magnesium Intake and Its Urinary Metabolomic Biomarkers With Blood Pressure: The INTERMAP Study, Scientific Sessions of the American-Heart-Association on Epidemiology and Prevention/Lifestyle and Cardiometabolic Health, Publisher: LIPPINCOTT WILLIAMS & WILKINS, ISSN: 0009-7322

Conference paper

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