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
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616 results found

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, 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, Elliott P, Fitzpet al., 2018, Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function, Nature Communications, Vol: 9, ISSN: 2041-1723

General cognitive function is a prominent and relatively stable human trait that is associated with many important life outcomes. We combine cognitive and genetic data from the CHARGE and COGENT consortia, and UK Biobank (total N = 300,486; age 16–102) and find 148 genome-wide significant independent loci (P < 5 × 10−8) associated with general cognitive function. Within the novel genetic loci are variants associated with neurodegenerative and neurodevelopmental disorders, physical and psychiatric illnesses, and brain structure. Gene-based analyses find 709 genes associated with general cognitive function. Expression levels across the cortex are associated with general cognitive function. Using polygenic scores, up to 4.3% of variance in general cognitive function is predicted in independent samples. We detect significant genetic overlap between general cognitive function, reaction time, and many health variables including eyesight, hypertension, and longevity. In conclusion we identify novel genetic loci and pathways contributing to the heritability of general cognitive function.

Journal article

Campanella G, Gunter MJ, Polidoro S, Krogh V, Palli D, Panico S, Sacerdote C, Tumino R, Fiorito G, Guarrera S, Iacoviello L, Bergdahl IA, Melin B, Lenner P, de Kok TMCM, Georgiadis P, Kleinjans JCS, Kyrtopoulos SA, Bueno-de-Mesquita HB, Lillycrop KA, May AM, Onland-Moret NC, Murray R, Riboli E, Verschuren M, Lund E, Mode N, Sandanger TM, Fiano V, Trevisan M, Matullo G, Froguel P, Elliott P, Vineis P, Chadeau-Hyam Met al., 2018, Epigenome-wide association study of adiposity and future risk of obesity-related diseases, INTERNATIONAL JOURNAL OF OBESITY, Vol: 42, Pages: 2022-2035, ISSN: 0307-0565

Journal article

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, 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, Kaprio Jet al., 2018, Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity (vol 50, pg 765, 2017), NATURE GENETICS, Vol: 50, Pages: 765-766, ISSN: 1061-4036

Journal article

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., 2018, Publisher Correction: Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity (vol 50, pg 26, 2018), Nature Genetics, Vol: 50, Pages: 766-767, ISSN: 1061-4036

Journal article

Castagne R, Gares V, Karimi M, Chadeau-Hyam M, Vineis P, Delpierre C, Kelly-Irving Met al., 2018, Allostatic load and subsequent all-cause mortality: which biological markers drive the relationship? Findings from a UK birth cohort, European Journal of Epidemiology, Vol: 33, Pages: 441-458, ISSN: 0393-2990

The concept of allostatic load (AL) refers to the idea of a global physiological ‘wear and tear’ resulting from the adaptationto the environment through the stress response systems over the life span. The link between socioeconomic position (SEP)and mortality has now been established, and there is evidence that AL may capture the link between SEP and mortality. Inorder to quantitatively assess the role of AL on mortality, we use data from the 1958 British birth cohort including elevenyear mortality in 8,113 adults. Specifically, we interrogate the hypothesis of a cumulative biological risk (allostatic load)reflecting 4 physiological systems potentially predicting future risk of death (N = 132). AL was defined using 14biomarkers assayed in blood from a biosample collected at 44 years of age. Cox proportional hazard regression analysisrevealed that higher allostatic load at 44 years old was a significant predictor of mortality 11 years later [HR = 3.56 (2.3 to5.53)]. We found that this relationship was not solely related to early-life SEP, adverse childhood experiences and youngadulthood health status, behaviours and SEP [HR = 2.57 (1.59 to 4.15)]. Regarding the ability of each physiologicalsystem and biomarkers to predict future death, our results suggest that the cumulative measure was advantageous comparedto evaluating each physiological system sub-score and biomarker separately. Our findings add some evidence of a biologicalembodiment in response to stress which ultimately affects mortality.

Journal article

Aljuraiban G, Stamler J, Chan Q, van Horn L, Daviglus M, Elliott P, Oude Griep Let al., Relations between dairy product intake and blood pressure: the INTERMAP study, Journal of Hypertension, ISSN: 0263-6352

Background: epidemiologic evidence suggests that low-fat dairy consumption may lower risk of hypertension. Dairy products may be distinctly linked to health, due to differences in nutritional composition, but little is known about specific nutrients that contribute to the dairy-blood pressure (BP) association, nor to underlying kidney function. Methods: we examined cross-sectional associations to BP of dairy product intakes, total and by type, from the INTERnational study on MAcro/micronutrients and blood Pressure (INTERMAP) including 2,694 participants aged 40-59 years from the United Kingdom and the United States. Eight BP, four 24-hour dietary recalls and two 24-hour urine samples were collected during four visits. Linear regression models adjusted for lifestyle/dietary factors to estimate BP differences per 2SD higher intakes of total-and-individual-types of dairy were calculated.Results: multivariable linear regression coefficients were estimated and pooled. In contrast to total and whole-fat dairy, each 195 g/1000 kcal (2SD) greater low-fat dairy intake was associated with a lower systolic BP (SBP) -2.31 mmHg and diastolic BP (DBP) -2.27 mmHg. Significant associations attenuated with adjustment for dietary phosphorus, calcium, and lactose, but strengthened with urinary calcium adjustment. Stratification by median albumin-creatinine-ratio (ACR), (high ACR indicates impaired kidney function) showed strong associations between low-fat dairy and BP in participants with low ACR (SBP: -3.66; DBP: -2.15 mmHg), with no association in participants with high ACR. Conclusions: low-fat dairy consumption was associated with lower BP, especially among participants with low ACR. Dairy-rich nutrients including phosphorus and calcium may have contributed to the beneficial associations with BP.

Journal article

Eriksen R, Gibson R, Lamb K, McMeel Y, Vergnuad A-C, Aresu M, Spear J, Chan Q, Elliott P, Frost Get al., 2018, Nutrient profiling and adherence to components of the UK national dietary guidelines association with metabolic risk factors for cardiovascular diseases and diabetes: Airwave Health Monitoring Study, British Journal of Nutrition, Vol: 119, Pages: 695-705, ISSN: 1475-2662

CVD is the leading cause of death worldwide. Diet is a key modifiable component in the development of CVD. No official UK diet quality index exists for use in UK nutritional epidemiological studies. The aims of this study are to: (i) develop a diet quality index based on components of UK dietary reference values (DRV) and (ii) determine the association between the index, the existing UK nutrient profile (NP) model and a comprehensive range of cardiometabolic risk markers among a British adult population. A cross-sectional analysis was conducted using data from the Airwave Health Monitoring Study (n 5848). Dietary intake was measured by 7-d food diary and metabolic risk using waist circumference, BMI, blood lipid profile, glycated Hb (HbA1c) and blood pressure measurements. Diet quality was assessed using the novel DRV index and NP model. Associations between diet and cardiometabolic risk were analysed via multivariate linear models and logistic regression. A two-point increase in NP score was associated with total cholesterol (β −0·33 mmol/l, P<0·0001) and HbA1c (β −0·01 %, P<0·0001). A two-point increase in DRV score was associated with waist circumference (β −0·56 cm, P<0·0001), BMI (β −0·15 kg/m2, P<0·0001), total cholesterol (β −0·06 mmol/l, P<0·0001) and HbA1c (β −0·02 %, P=0·002). A one-point increase in DRV score was associated with type 2 diabetes (T2D) (OR 0·94, P=0·01) and obesity (OR 0·95, P<0·0001). The DRV index is associated with overall diet quality and risk factors for CVD and T2D, supporting its application in nutritional epidemiological studies investigating CVD risk in a UK population.

Journal article

Xie W, Zheng F, Evangelou E, Liu O, Yang Z, Chan Q, Elliott P, Wu Yet al., 2018, Blood pressure-lowering drugs and secondary prevention of cardiovascular disease: systematic review and meta-analysis., Journal of Hypertension, Vol: 36, Pages: 1256-1265, ISSN: 0263-6352

OBJECTIVE: To systematically evaluate the efficacy of five commonly used blood pressure-lowering drugs in reducing cardiovascular events among patients with nonacute cardiovascular disease, but without heart failure. METHODS: We searched PubMed, EMBASE, and Cochrane Central Register of Controlled Trials on 18 March 2017. The primary outcome was fatal and nonfatal cardiovascular events, and the secondary outcomes were all-cause death, fatal and nonfatal myocardial infarction, and stroke. Pooled risk ratios and corresponding 95% confidence intervals (CIs) were calculated using Mantel-Haenszel random-effects meta-analyses. RESULTS: Twenty-seven randomized controlled trials with 143 095 participants and a treatment duration of at least 12 months were included in our analyses. Fifteen trials enrolled patients with coronary artery disease, eight enrolled patients with cerebral artery disease, and four enrolled patients with cardiovascular disease. Of the 27 trials, 10 trials only included hypertensive patients. Compared with placebo, angiotensin-converting enzyme inhibitors (ACEIs) (risk ratio 0.85, 95% CI 0.78-0.92), angiotensin receptor blockers (risk ratio 0.92, 95% CI 0.87-0.98), and diuretics (risk ratio 0.77, 95% CI 0.66-0.90) significantly reduced the risk of cardiovascular events. Apart from this, ACEIs significantly reduced all secondary outcomes, calcium channel blockers, and diuretics reduced stroke significantly. No significant difference was found in head-to-head comparisons of each given drug class with any other class. CONCLUSIONS: Although only ACEIs have evidences showing its effect in reducing cardiovascular events and all secondary outcomes, head-to-head comparisons did not provide strong evidence in difference in the effects between these blood pressure-lowering drugs.

Journal article

Malik R, Kooner JS, Elliott P, Chambers J, Dichgans Met al., 2018, Multi-ancestry genome-wide association study of 520,000 subjects identifies 32 loci associated with stroke and stroke subtypes, Nature Genetics, Vol: 50, Pages: 524-537, ISSN: 1061-4036

Stroke has multiple etiologies, but the underlying genes and pathways are largely unknown. We conducted a multiancestry genome-wide-association meta-analysis in 521,612 individuals (67,162 cases and 454,450 controls) and discovered 22 new stroke risk loci, bringing the total to 32. We further found shared genetic variation with related vascular traits, including blood pressure, cardiac traits, and venous thromboembolism, at individual loci (n = 18), and using genetic risk scores and linkage-disequilibrium-score regression. Several loci exhibited distinct association and pleiotropy patterns for etiological stroke subtypes. Eleven new susceptibility loci indicate mechanisms not previously implicated in stroke pathophysiology, with prioritization of risk variants and genes accomplished through bioinformatics analyses using extensive functional datasets. Stroke risk loci were significantly enriched in drug targets for antithrombotic therapy.

Journal article

Stamler J, Chan Q, Daviglus M, Dyer A, van Horn L, Garside D, Miura K, Wu Y, Ueshima H, Zhao L, Elliott Pet al., 2018, Relation of dietary sodium (salt) to blood pressure and Its possible modulation by other dietary factors: the INTERMAP study, Hypertension, Vol: 71, Pages: 631-637, ISSN: 0194-911X

Available data indicate that dietary sodium (as salt) relates directly to blood pressure (BP). Most of these findings are from studies lacking dietary data; hence, it is unclear whether this sodium–BP relationship is modulated by other dietary factors. With control for multiple nondietary factors, but not body mass index, there were direct relations to BP of 24-hour urinary sodium excretion and the urinary sodium/potassium ratio among 4680 men and women 40 to 59 years of age (17 population samples in China, Japan, United Kingdom, and United States) in the INTERMAP (International Study on Macro/Micronutrients and Blood Pressure), and among its 2195 American participants, for example, 2 SD higher 24-hour urinary sodium excretion (118.7 mmol) associated with systolic BP 3.7 mm Hg higher. These sodium–BP relations persisted with control for 13 macronutrients, 12 vitamins, 7 minerals, and 18 amino acids, for both sex, older and younger, blacks, Hispanics, whites, and socioeconomic strata. With control for body mass index, sodium–BP—but not sodium/potassium–BP—relations were attenuated. Normal weight and obese participants manifested significant positive relations to BP of urinary sodium; relations were weaker for overweight people. At lower but not higher levels of 24-hour sodium excretion, potassium intake blunted the sodium–BP relation. The adverse association of dietary sodium with BP is minimally attenuated by other dietary constituents; these findings underscore the importance of reducing salt intake for the prevention and control of prehypertension and hypertension.

Journal article

Kaluarachchi M, Boulangé C, Karaman I, Lindon JC, Ebbels T, Elliott P, Tracy R, Olson NCet al., 2018, A comparison of human serum and plasma metabolites using untargeted 1H NMR spectroscopy and UPLC-MS, Metabolomics, Vol: 14, ISSN: 1573-3882

Introduction:Differences in the metabolite profiles between serum and plasma are incompletely understood.Objectives:To evaluate metabolic profile differences between serum and plasma and among plasma sample subtypes.Methods:We analyzed serum, platelet rich plasma (PRP), platelet poor plasma (PPP), and platelet free plasma (PFP), collected from 8 non-fasting apparently healthy women, using untargeted standard 1D and CPMG 1H NMR and reverse phase and hydrophilic (HILIC) UPLC-MS. Differences between metabolic profiles were evaluated using validated principal component and orthogonal partial least squares discriminant analysis.ResultsExplorative analysis showed the main source of variation among samples was due to inter-individual differences with no grouping by sample type. After correcting for inter-individual differences, lipoproteins, lipids in VLDL/LDL, lactate, glutamine, and glucose were found to discriminate serum from plasma in NMR analyses. In UPLC-MS analyses, lysophosphatidylethanolamine (lysoPE)(18:0) and lysophosphatidic acid(20:0) were higher in serum, and phosphatidylcholines (PC)(16:1/18:2, 20:3/18:0, O-20:0/22:4), lysoPC(16:0), PE(O-18:2/20:4), sphingomyelin(18:0/22:0), and linoleic acid were lower. In plasma subtype analyses, isoleucine, leucine, valine, phenylalanine, glutamate, and pyruvate were higher among PRP samples compared with PPP and PFP by NMR while lipids in VLDL/LDL, citrate, and glutamine were lower. By UPLC-MS, PE(18:0/18:2) and PC(P-16:0/20:4) were higher in PRP compared with PFP samples.Conclusions:Correction for inter-individual variation was required to detect metabolite differences between serum and plasma. Our results suggest the potential importance of inter-individual effects and sample type on the results from serum and plasma metabolic phenotyping studies.

Journal article

Cai Y, Hansell A, Hodgson S, Elliott P, Fecht D, Gulliver J, Key T, de Hoogh K, Hveem K, Morley D, Vienneau D, Blangiardo Met al., Road traffic noise, air pollution and incident cardiovascular disease: a joint analysis of the HUNT, EPIC-Oxford and UK Biobank cohorts, Environment International, ISSN: 0160-4120

Background: This study aimed to investigate the effects of long-term exposure to road traffic noiseand air pollutionon incident cardiovascular disease (CVD)in three large cohorts: HUNT, EPIC-Oxford and UK Biobank. Methods: In pooled complete-casesample of the three cohorts from Norway and the United Kingdom(N=355,732), 21,081 incident all CVD cases including 5,259ischemic heart disease (IHD)and 2,871cerebrovascular cases were ascertained between baseline (1993-2010)and end of follow-up (2008-2013)through medical recordlinkage. Annual mean 24-hour weighted road traffic noise(Lden) and air pollution (particulate matter with aerodynamic diameter ≤10 μm [PM10],≤2.5 μm [PM2.5]andnitrogen 39dioxide[NO2])exposure at baseline address was modelled using a simplified version of the Common Noise Assessment Methods in Europe (CNOSSOS-EU)and European-wide Land Use Regression models.Individual-level covariate data were harmonised and physically pooled across the three cohorts. Analysis was via Cox proportional hazard model with mutual adjustmentsforboth noise and air pollution andpotential confounders. Results: No significant associations were found between annual mean Ldenand incidentCVD,IHD or cerebrovascular disease in the overall populationexcept that the association withincident IHD was significantamong current-smokers.In the fully adjusted models including adjustmentfor Lden, an interquartile range (IQR) higher PM10(4.1μg/m3) or PM2.5(1.4μg/m3) was associated witha5.8% (95%CI: 2.5%-9.3%) and 3.7% (95%CI: 0.2%-7.4%) higherrisk for all incident CVD respectively. No significant associations were found between NO2and any of the CVD outcomes. Conclusions: We found suggestive evidence of a possible association between road traffic noise and incident IHD, consistent with current literature. Long-term particulate air pollution exposure, even at concentrations below current European air quality standards, w

Journal article

Posma JM, Garcia Perez I, Ebbels TMD, Lindon JC, Stamler J, Elliott P, Holmes E, Nicholson Jet al., 2018, Optimized phenotypic biomarker discovery and confounder elimination via covariate-adjusted projection to latent structures from metabolic spectroscopy data, Journal of Proteome Research, Vol: 17, Pages: 1586-1595, ISSN: 1535-3893

Metabolism is altered by genetics, diet, disease status, environment and many other factors. Modelling either one of these is often done without considering the effects of the other covariates. Attributing differences in metabolic profile to one of these factors needs to be done while controlling for the metabolic influence of the rest. We describe here a data analysis framework and novel confounder-adjustment algorithm for multivariate analysis of metabolic profiling data. Using simulated data we show that similar numbers of true associations and significantly less false positives are found compared to other commonly used methods. Covariate-Adjusted Projections to Latent Structures (CA-PLS) is exemplified here using a large-scale metabolic phenotyping study of two Chinese populations at different risks for cardiovascular disease. Using CA-PLS we find that some previously reported differences are actually associated with external factors and discover a number of previously unreported biomarkers linked to different metabolic pathways. CA-PLS can be applied to any multivariate data where confounding may be an issue and the confounder-adjustment procedure is translatable to other multivariate regression techniques.

Journal article

Sung YJ, Lehne B, Scott WR, Sever P, Chambers J, Froguel P, Kooner JS, Scott J, Elliott P, Chasman DIet al., 2018, A large-scale multi-ancestry genome-wide study accounting for smoking bahavior identifies multiple genome-wide significant loci for systolic and diastolic blood pressure, American Journal of Human Genetics, Vol: 102, Pages: 375-400, ISSN: 0002-9297

Genome-wide association analysis advanced understanding of blood pressure (BP), a major risk factor for vascular conditions such as coronary heart disease and stroke. Accounting for smoking behavior may help identify novel BP loci and extend our knowledge of its genetic architecture. We performed genome-wide association meta-analyses of systolic and diastolic BP incorporating gene-smoking interactionsin 610,091 individuals. Stage 1 analysis examined ~18.8 million SNPs and small insertion/deletion variants in 129,913 individuals from four ancestries (European, African, Asian, and Hispanic) with follow-upanalysis of promising variants in 480,178 additional individuals from five ancestries. Weidentified 15 new loci that were genome-wide significant (P < 5×10-8) in Stage 1 and formally replicated in Stage 2. A combined Stage 1 and 2 meta-analysis identified 66 additional genome-wide significant loci ( 13, 35, and 18 loci in European, African and trans-ancestry, respectively). A total of 56 known BP loci were also identified by our results (P < 5×10-8).O f the newly identified loci, 10 showed significant interaction with smoking status, but none of them were replicated in Stage 2. Several loci were identified in African ancestry, highlighting the importance of genetic studies in diverse populations. The identified loci show strong evidence for regulatory features and support shared pathophysiology with cardiometabolic and addiction traits. They also highlight a role in BP regulation for biological candidates such as modulators of vascular structure and function (CDKN1B, BCAR1-CFDP1, PXDN, EEA1), ciliopathies(SDCCAG8,RPGRIP1L), telomere maintenance (TNKS, PINX1, AKTIP), and central dopaminergic signaling (MSRA, EBF2)

Journal article

Gulliver J, Elliott P, Hansell A, Cai Y, McCrea A, Garwood K, Fecht D, Briggs Det al., 2018, Local- and regional-scale air pollution modelling (PM10) and exposure assessment for pregnancy trimesters, infancy, and childhood to age 15 years: Avon Longitudinal Study of Parents And Children (ALSPAC)., Environment International, Vol: 113, Pages: 10-19, ISSN: 0160-4120

We established air pollution modelling to study particle (PM10) exposures during pregnancy and infancy (1990–1993) through childhood and adolescence up to age ~15 years (1991–2008) for the Avon Longitudinal Study of Parents And Children (ALSPAC) birth cohort. For pregnancy trimesters and infancy (birth to 6 months; 7 to 12 months) we used local (ADMS-Urban) and regional/long-range (NAME-III) air pollution models, with a model constant for local, non-anthropogenic sources. For longer exposure periods (annually and the average of birth to age ~8 and to age ~15 years to coincide with relevant follow-up clinics) we assessed spatial contrasts in local sources of PM10 with a yearly-varying concentration for all background sources. We modelled PM10 (μg/m3) for 36,986 address locations over 19 years and then accounted for changes in address in calculating exposures for different periods: trimesters/infancy (n = 11,929); each year of life to age ~15 (n = 10,383). Intra-subject exposure contrasts were largest between pregnancy trimesters (5th to 95th centile: 24.4–37.3 μg/m3) and mostly related to temporal variability in regional/long-range PM10. PM10 exposures fell on average by 11.6 μg/m3 from first year of life (mean concentration = 31.2 μg/m3) to age ~15 (mean = 19.6 μg/m3), and 5.4 μg/m3 between follow-up clinics (age ~8 to age ~15). Spatial contrasts in 8-year average PM10 exposures (5th to 95th centile) were relatively low: 25.4–30.0 μg/m3 to age ~8 years and 20.7–23.9 μg/m3 from age ~8 to age ~15 years. The contribution of local sources to total PM10 was 18.5%–19.5% during pregnancy and infancy, and 14.4%–17.0% for periods leading up to follow-up clinics. Main roads within the study area contributed on average ~3.0% to total PM10 exposures in all periods; 9.5% of address locations were within 50 m of a main road. Exposure estimates will be used in a number of planned epidemiological studies.

Journal article

Flannick J, Fuchsberger C, Mahajan A, Teslovich TM, Agarwala V, Gaulton KJ, Caulkins L, Koesterer R, Ma C, Moutsianas L, McCarthy DJ, Rivas MA, Perry JRB, Sim X, Blackwell TW, Robertson NR, Rayner NW, Cingolani P, Locke AE, Tajes JF, Highland HM, Dupuis J, Chines PS, Lindgren CM, Hartl C, Jackson AU, Chen H, Huyghe JR, van de Bunt M, Pearson RD, Kumar A, Mueller-Nurasyid M, Grarup N, Stringham HM, Gamazon ER, Lee J, Chen Y, Scott RA, Below JE, Chen P, Huang J, Go MJ, Stitzel ML, Pasko D, Parker SCJ, Varga TV, Green T, Beer NL, Day-Williams AG, Ferreira T, Fingerlin T, Horikoshi M, Hu C, Huh I, Ikram MK, Kim B-J, Kim Y, Kim YJ, Kwon M-S, Lee J, Lee S, Lin K-H, Maxwell TJ, Nagai Y, Wang X, Welch RP, Yoon J, Zhang W, Barzilai N, Voight BF, Han B-G, Jenkinson CP, Kuulasmaa T, Kuusisto J, Manning A, Ng MCY, Palmer ND, Balkau B, Stancakova A, Abboud HE, Boeing H, Giedraitis V, Prabhakaran D, Gottesman O, Scott J, Carey J, Kwan P, Grant G, Smith JD, Neale BM, Purcell S, Butterworth AS, Howson JMM, Lee HM, Lu Y, Kwak S-H, Zhao W, Danesh J, Lam VKL, Park KS, Saleheen D, So WY, Tam CHT, Afzal U, Aguilar D, Arya R, Aung T, Chan E, Navarro C, Cheng C-Y, Palli D, Correa A, Curran JE, Rybin D, Farook VS, Fowler SP, Freedman BI, Griswold M, Hale DE, Hicks PJ, Khor C-C, Kumar S, Lehne B, Thuillier D, Lim WY, Liu J, Loh M, Musani SK, Puppala S, Scott WR, Yengo L, Tan S-T, Taylor HA, Thameem F, Wilson G, Wong TY, Njolstad PR, Levy JC, Mangino M, Bonnycastle LL, Schwarzmayr T, Fadista J, Surdulescu GL, Herder C, Groves CJ, Wieland T, Bork-Jensen J, Brandslund I, Christensen C, Koistinen HA, Doney ASF, Kinnunen L, Esko T, Farmer AJ, Hakaste L, Hodgkiss D, Kravic J, Lyssenko V, Hollensted M, Jorgensen ME, Jorgensen T, Ladenvall C, Justesen JM, Karajamaki A, Kriebel J, Rathmann W, Lannfelt L, Lauritzen T, Narisu N, Linneberg A, Melander O, Milani L, Neville M, Orho-Melander M, Qi L, Qi Q, Roden M, Rolandsson O, Swift A, Rosengren AH, Stirrups K, Wood AR, Mihailov E, Blancher C, Carneiroet al., 2018, Erratum: Sequence data and association statistics from 12,940 type 2 diabetes cases and controls, Scientific Data, Vol: 5, ISSN: 2052-4463

Journal article

Harada S, Hirayama A, Chan Q, Kurihara A, Fukai K, Iida M, Kato S, Sugiyama D, Kuwabara K, Takeuchi A, Akiyama M, Okamura T, Ebbels TMD, Elliott P, Tomita M, Sato A, Suzuki C, Sugimoto M, Soga T, Takebayashi Tet al., 2018, Reliability of plasma polar metabolite concentrations in a large-scale cohort study using capillary electrophoresis-mass spectrometry., PLoS ONE, Vol: 13, ISSN: 1932-6203

BACKGROUND: Cohort studies with metabolomics data are becoming more widespread, however, large-scale studies involving 10,000s of participants are still limited, especially in Asian populations. Therefore, we started the Tsuruoka Metabolomics Cohort Study enrolling 11,002 community-dwelling adults in Japan, and using capillary electrophoresis-mass spectrometry (CE-MS) and liquid chromatography-mass spectrometry. The CE-MS method is highly amenable to absolute quantification of polar metabolites, however, its reliability for large-scale measurement is unclear. The aim of this study is to examine reproducibility and validity of large-scale CE-MS measurements. In addition, the study presents absolute concentrations of polar metabolites in human plasma, which can be used in future as reference ranges in a Japanese population. METHODS: Metabolomic profiling of 8,413 fasting plasma samples were completed using CE-MS, and 94 polar metabolites were structurally identified and quantified. Quality control (QC) samples were injected every ten samples and assessed throughout the analysis. Inter- and intra-batch coefficients of variation of QC and participant samples, and technical intraclass correlation coefficients were estimated. Passing-Bablok regression of plasma concentrations by CE-MS on serum concentrations by standard clinical chemistry assays was conducted for creatinine and uric acid. RESULTS AND CONCLUSIONS: In QC samples, coefficient of variation was less than 20% for 64 metabolites, and less than 30% for 80 metabolites out of the 94 metabolites. Inter-batch coefficient of variation was less than 20% for 81 metabolites. Estimated technical intraclass correlation coefficient was above 0.75 for 67 metabolites. The slope of Passing-Bablok regression was estimated as 0.97 (95% confidence interval: 0.95, 0.98) for creatinine and 0.95 (0.92, 0.96) for uric acid. Compared to published data from other large cohort measurement platforms, reproducibility of metabolites common

Journal article

Pinto RC, Karaman I, Fussell JC, Evangelou E, Kelly FJ, Elliott P, Tzoulaki Iet al., 2018, Applications of metabolic phenotyping in epidemiology, The Handbook of Metabolic Phenotyping, Pages: 491-534, ISBN: 9780128122945

© 2019 Elsevier Inc. All rights reserved. Metabolic phenotyping is rapidly being adopted in epidemiological research as part of a systems biology approach to understand disease causes and mechanisms. Metabolic phenotyping provides complementary information to the genotype, gene expression profiles, or even the proteome of an individual and offers a powerful and innovative approach that captures, in extraordinarily high resolution, direct signatures of the end products of a wide range of physiological and pathophysiological processes. In this chapter, we will focus on the use and applications of metabolic phenotyping in epidemiology, evaluate its current status, discuss issues related to combining data across studies, and summarize its applications in the field. Within this latter summary, we will discuss separate strategies and objectives in five different subsections: diagnosis and prognosis of disease, disease pathways and mechanisms, environmental mechanisms of toxicity-focusing through a literature review on ambient air pollution, integration of different -omics, and clinical trials. We finish this chapter with a discussion on current trends and future directions of metabolic phenotyping in epidemiology.

Book chapter

Turcot V, Chambers J, Elliott P, Evangelou E, Kooner J, Zhang W, Loos Ret al., 2017, Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure underpinning obesity., Nature Genetics, Vol: 50, Pages: 26-41, ISSN: 1061-4036

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

Journal article

Flannick J, Froguel P, Prokopenko I, Lehne B, Kooner JS, Chambers J, Scott J, Loh M, Elliott P, Zhang W, Scott W, Nagai Yet al., 2017, Sequence data and association statistics from 12,940 type 2 diabetes cases and controls, Scientific Data, Vol: 4, ISSN: 2052-4463

To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1–5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (>80% of low-frequency coding variants in ~82 K Europeans via the exome chip, and ~90% of low-frequency non-coding variants in ~44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D.

Journal article

Márquez-Luna C, Loh P-R, South Asian Type 2 Diabetes SAT2D Consortium, SIGMA Type 2 Diabetes Consortium, Price ALet al., 2017, Multiethnic polygenic risk scores improve risk prediction in diverse populations., Genet Epidemiol, Vol: 41, Pages: 811-823

Methods for genetic risk prediction have been widely investigated in recent years. However, most available training data involves European samples, and it is currently unclear how to accurately predict disease risk in other populations. Previous studies have used either training data from European samples in large sample size or training data from the target population in small sample size, but not both. Here, we introduce a multiethnic polygenic risk score that combines training data from European samples and training data from the target population. We applied this approach to predict type 2 diabetes (T2D) in a Latino cohort using both publicly available European summary statistics in large sample size (Neff  = 40k) and Latino training data in small sample size (Neff  = 8k). Here, we attained a >70% relative improvement in prediction accuracy (from R2  = 0.027 to 0.047) compared to methods that use only one source of training data, consistent with large relative improvements in simulations. We observed a systematically lower load of T2D risk alleles in Latino individuals with more European ancestry, which could be explained by polygenic selection in ancestral European and/or Native American populations. We predict T2D in a South Asian UK Biobank cohort using European (Neff  = 40k) and South Asian (Neff  = 16k) training data and attained a >70% relative improvement in prediction accuracy, and application to predict height in an African UK Biobank cohort using European (N = 113k) and African (N = 2k) training data attained a 30% relative improvement. Our work reduces the gap in polygenic risk prediction accuracy between European and non-European target populations.

Journal article

Suzuki HS, Gao HG, Bai WB, Evangelou EE, Glocker BG, O'regan DO, Elliott PE, Matthews PMMet al., 2017, Abnormal brain white matter microstructure is associated withboth pre-hypertension and hypertension, PLoS ONE, Vol: 12, ISSN: 1932-6203

ObjectivesTo characterize effects of chronically elevated blood pressure on the brain, we tested for brain white matter microstructural differences associated with normotension, pre-hypertension and hypertension in recently available brain magnetic resonance imaging data from 4659 participants without known neurological or psychiatric disease (62.3±7.4 yrs, 47.0% male) in UK Biobank.MethodsFor assessment of white matter microstructure, we used measures derived from neurite orientation dispersion and density imaging (NODDI) including the intracellular volume fraction (an estimate of neurite density) and isotropic volume fraction (an index of the relative extra-cellular water diffusion). To estimate differences associated specifically with blood pressure, we applied propensity score matching based on age, sex, educational level, body mass index, and history of smoking, diabetes mellitus and cardiovascular disease to perform separate contrasts of non-hypertensive (normotensive or pre-hypertensive, N = 2332) and hypertensive (N = 2337) individuals and of normotensive (N = 741) and pre-hypertensive (N = 1581) individuals (p<0.05 after Bonferroni correction).ResultsThe brain white matter intracellular volume fraction was significantly lower, and isotropic volume fraction was higher in hypertensive relative to non-hypertensive individuals (N = 1559, each). The white matter isotropic volume fraction also was higher in pre-hypertensive than in normotensive individuals (N = 694, each) in the right superior longitudinal fasciculus and the right superior thalamic radiation, where the lower intracellular volume fraction was observed in the hypertensives relative to the non-hypertensive group.SignificancePathological processes associated with chronically elevated blood pressure are associated with imaging differences suggesting chronic alterations of white matter axonal structure that may affect cognitive functions even with pre-hypertension.

Journal article

Frazier-Wood AC, Tzoulaki I, Voortman T, Lindon J, Ebbels T, Elliot P, Boulange CL, Kaluarachchi M, Chekmeneva E, Karaman I, Franco OH, Greenland P, Tracy R, Herrington Det al., 2017, Untargeted Metabolomic Analyses Reveal Mechanistic Links Between a Mediterranean-Style Diet and Incident Cardiovascular Disease in the Multi-Ethnic Study of Atherosclerosis, Scientific Sessions of the American-Heart-Association / Resuscitation Science Symposium, Publisher: LIPPINCOTT WILLIAMS & WILKINS, ISSN: 0009-7322

Conference paper

Toledano MB, Mueller W, Fleming C, Chang I, Dumontheil I, Thomas MSC, Eeftens M, Elliott P, Mireku MO, Röösli Met al., 2017, Total recall in the SCAMP Cohort: Validation of self-reported mobile phone use in the smartphone era, Environmental Research, Vol: 161, Pages: 1-8, ISSN: 0013-9351

Mobile phone use, predominantly smartphones, is almost ubiquitous amongst both adults and children. However adults and children have different usage patterns. A major challenge with research on mobile phone use is the reliability of self-reported phone activity for accurate exposure assessment. We investigated the agreement between self-reported mobile phone use data and objective mobile operator traffic data in a subset of adolescents aged 11-12 years participating in the Study of Cognition, Adolescents and Mobile Phones (SCAMP) cohort. We examined self-reported mobile phone use, including call frequency, cumulative call time duration and text messages sent among adolescents from SCAMP and matched these data with records provided by mobile network operators (n = 350). The extent of agreement between self-reported mobile phone use and mobile operator traffic data use was evaluated using Cohen's weighted Kappa (ĸ) statistics. Sensitivity and specificity of self-reported low (< 1 call/day, ≤ 5min of call/day or ≤ 5 text messages sent/day) and high (≥ 11 calls/day, > 30min of call/day or ≥ 11 text messages sent /day) use were estimated. Agreement between self-reported mobile phone use and mobile operator traffic data was highest for the duration spent talking on mobile phones per day on weekdays (38.9%) and weekends (29.4%) compared to frequency of calls and number of text messages sent. Adolescents overestimated their mobile phone use during weekends compared to weekdays. Analysis of agreement showed little difference overall between the sexes and socio-economic groups. Weighted kappa between self-reported and mobile operator traffic data for call frequency during weekdays was κ = 0.12, 95% CI 0.06-0.18. Of the three modes of mobile phone use measured in the questionnaire, call frequency was the most sensitive for low mobile phone users on weekdays and weekends (77.1, 95% CI: 69.3-83.7 and 72.0, 95% CI: 65.0-78.4, respectively). Specificity was

Journal article

Kraja AT, Evangelou E, Tzoulaki I, Zhang W, Gao H, Chambers J, Jarvelin MR, Kooner J, Poulter N, Sever P, Vergnaud AC, Elliott P, CHARGE EXOME BP, CHD Exome, Exome BP, GoT2DT2DGenes Consortia, The UK Biobank Cardio-Metabolic Traits Consortium Blood Pressure Working Groupet al., 2017, New blood pressure associated loci identified in meta-analyses of 475,000 individuals, Circulation: Cardiovascular Genetics, Vol: 10, ISSN: 1942-325X

Background—Genome-wide association studies have recently identified >400 loci that harbor DNA sequence variants that influence blood pressure (BP). Our earlier studies identified and validated 56 single nucleotide variants (SNVs) associated with BP from meta-analyses of exome chip genotype data. An additional 100 variants yielded suggestive evidence of association.Methods and Results—Here, we augment the sample with 140 886 European individuals from the UK Biobank, in whom 77 of the 100 suggestive SNVs were available for association analysis with systolic BP or diastolic BP or pulse pressure. We performed 2 meta-analyses, one in individuals of European, South Asian, African, and Hispanic descent (pan-ancestry, ≈475 000), and the other in the subset of individuals of European descent (≈423 000). Twenty-one SNVs were genome-wide significant (P<5×10−8) for BP, of which 4 are new BP loci: rs9678851 (missense, SLC4A1AP), rs7437940 (AFAP1), rs13303 (missense, STAB1), and rs1055144 (7p15.2). In addition, we identified a potentially independent novel BP-associated SNV, rs3416322 (missense, SYNPO2L) at a known locus, uncorrelated with the previously reported SNVs. Two SNVs are associated with expression levels of nearby genes, and SNVs at 3 loci are associated with other traits. One SNV with a minor allele frequency <0.01, (rs3025380 at DBH) was genome-wide significant.Conclusions—We report 4 novel loci associated with BP regulation, and 1 independent variant at an established BP locus. This analysis highlights several candidate genes with variation that alter protein function or gene expression for potential follow-up.

Journal article

NCD Risk Factor Collaboration NCD-RisC, 2017, Worldwide trends in body-mass index, underweight, overweight, and obesity from 1975 to 2016: a pooled analysis of 2416 population-based measurement studies in 128·9 million children, adolescents, and adults., Lancet, Vol: 390, Pages: 2627-2642, ISSN: 0140-6736

BACKGROUND: Underweight, overweight, and obesity in childhood and adolescence are associated with adverse health consequences throughout the life-course. Our aim was to estimate worldwide trends in mean body-mass index (BMI) and a comprehensive set of BMI categories that cover underweight to obesity in children and adolescents, and to compare trends with those of adults. METHODS: We pooled 2416 population-based studies with measurements of height and weight on 128·9 million participants aged 5 years and older, including 31·5 million aged 5-19 years. We used a Bayesian hierarchical model to estimate trends from 1975 to 2016 in 200 countries for mean BMI and for prevalence of BMI in the following categories for children and adolescents aged 5-19 years: more than 2 SD below the median of the WHO growth reference for children and adolescents (referred to as moderate and severe underweight hereafter), 2 SD to more than 1 SD below the median (mild underweight), 1 SD below the median to 1 SD above the median (healthy weight), more than 1 SD to 2 SD above the median (overweight but not obese), and more than 2 SD above the median (obesity). FINDINGS: Regional change in age-standardised mean BMI in girls from 1975 to 2016 ranged from virtually no change (-0·01 kg/m(2) per decade; 95% credible interval -0·42 to 0·39, posterior probability [PP] of the observed decrease being a true decrease=0·5098) in eastern Europe to an increase of 1·00 kg/m(2) per decade (0·69-1·35, PP>0·9999) in central Latin America and an increase of 0·95 kg/m(2) per decade (0·64-1·25, PP>0·9999) in Polynesia and Micronesia. The range for boys was from a non-significant increase of 0·09 kg/m(2) per decade (-0·33 to 0·49, PP=0·6926) in eastern Europe to an increase of 0·77 kg/m(2) per decade (0·50-1·06, PP>0·9999) in Polynesia and Micronesia. Tre

Journal article

Schierding W, Antony J, Karhunen V, Vaarasmaki M, Franks S, Elliott P, Kajantie E, Sebert S, Blakemore A, Horsfield JA, Jarvelin MR, O'Sullivan J, Cutfield WSet al., 2017, GWAS on prolonged gestation (post-term birth): analysis of successive Finnish birth cohorts., Journal of Medical Genetics, Vol: 55, Pages: 55-63, ISSN: 1468-6244

Background Gestation is a crucial timepoint in human development. Deviation from a term gestational age correlates with both acute and long-term adverse health effects for the child. Both being born preterm and post-term, that is, having short and long gestational ages, are heritable and influenced by the prenatal and perinatal environment. Despite the obvious heritable component, specific genetic influences underlying differences in gestational age are poorly understood.Methods We investigated the genetic architecture of gestational age in 9141 individuals, including 1167 born post-term, across two Northern Finland cohorts born in 1966 or 1986.Results Here we identify one globally significant intronic genetic variant within the ADAMTS13 gene that is associated with prolonged gestation (p=4.85×10−8). Additional variants that reached suggestive levels of significance were identified within introns at the ARGHAP42 and TKT genes, and in the upstream (5’) intergenic regions of the B3GALT5 and SSBP2 genes. The variants near the ADAMTS13, B3GALT5, SSBP2 and TKT loci are linked to alterations in gene expression levels (cis-eQTLs). Luciferase assays confirmed the allele specific enhancer activity for the BGALT5 and TKT loci.Conclusions Our findings provide the first evidence of a specific genetic influence associated with prolonged gestation. This study forms a foundation for a better understanding of the genetic and long-term health risks faced by induced and post-term individuals. The long-term risks for induced individuals who have a previously overlooked post-term potential may be a major issue for current health providers.

Journal article

McCrory C, O'Leary N, Fraga S, Ribeiro AI, Barros H, Kartiosuo N, Raitakari O, Kivimaki M, Vineis P, Layte Ret al., 2017, Socioeconomic differences in children's growth trajectories from infancy to early adulthood: evidence from four European countries, JOURNAL OF EPIDEMIOLOGY AND COMMUNITY HEALTH, Vol: 71, Pages: 981-989, ISSN: 0143-005X

Journal article

Vineis P, Avendano-Pabon M, Barros H, Chadeau-Hyam M, Costa G, Dijmarescu M, Delpierre C, D'Errico A, Fraga S, Giles G, Goldberg M, Zins M, Kelly-Irving M, Kivimaki M, Lang T, Layte R, Mackenbach JP, Marmot M, McCrory C, Carmeli C, Milne RL, Muennig P, Nusselder W, Polidoro S, Ricceri F, Robinson O, Stringhini Set al., 2017, The biology of inequalities in health: the LIFEPATH project, Longitudinal and Life Course Studies, Vol: 8, Pages: 417-449, ISSN: 1757-9597

Socioeconomic differences in health have been consistently observed worldwide. Physical health deteriorates more rapidly with age among men and women with lower socioeconomic status (SES) than among those with higher SES. The biological processes underlying these differences are best understood by adopting a life-course approach. In this paper we introduce the pan-European LIFEPATH project which uses the revised Strachan-Sheikh (2004) model to describe ageing across the life-course. This model presents ageing as a phenomenon with two broad stages across life: build-up and decline. The ‘build-up’ stage, from conception and early intra-uterine life to late adolescence or early twenties, is characterised by rapid successions of developmentally and socially sensitive periods. The second stage, starting in early adulthood, is a period of 'decline' from maximum attained health to loss of function, overt disease and death.LIFEPATH adopts a study design that integrates social science and public health approaches with biology (including molecular epidemiology), using well-characterised population cohorts and omics measurements (particularly epigenomics). The specific objectives of the project are: (a) to show that healthy ageing is an achievable goal for society; (b) to improve the understanding of the mechanisms through which healthy ageing pathways diverge by SES, by investigating life-course biological pathways using omic technologies; (c) to examine the consequences of the current economic recession on health and the biology of ageing (and the consequent increase in social inequalities); (d) to provide updated, relevant and innovative evidence for healthy ageing policies (particularly “health in all policies”) using both observational studies and an experimental approach based on a reanalysis of data from a "conditional cash transfer" randomised experiment in New York and new data collected as part of an earned income tax credit randomis

Journal article

Warren HR, Evangelou E, Cabrera CP, Gao H, Ren M, Mifsud B, Ntalla I, Surendran P, Liu C, Cook JP, Kraja AT, Drenos F, Loh M, Verweij N, Marten J, Karaman I, Segura Lepe MP, O'Reilly PF, Knight J, Snieder H, Kato N, He J, Tai ES, Said MA, Porteous D, Alver M, Poulter N, Farrall M, Gansevoort RT, Padmanabhan S, Mägi R, Stanton A, Connell J, Bakker SJL, Metspalu A, Shields DC, Thom S, Brown M, Sever P, Esko T, Hayward C, van der Harst P, Saleheen D, Chowdhury R, Chambers JC, Chasman DI, Chakravarti A, Newton-Cheh C, Lindgren CM, Levy D, Kooner JS, Keavney B, Tomaszewski M, Samani NJ, Howson JMM, Tobin MD, Munroe PB, Ehret GB, Wain LV, International Consortium of Blood Pressure ICBP 1000G Analyses, The CHD Exome Consortium, The ExomeBP Consortium, The T2D-GENES Consortium, The GoT2DGenes Consortium, The Cohorts for Heart and Ageing Research in Genome Epidemiology CHARGE BP Exome Consortium, The International Genomics of Blood Pressure iGEN-BP Consortium, Barnes MR, Tzoulaki I, Caulfield MJ, Elliott P, UK Biobank CardioMetabolic Consortium BP working groupet al., 2017, Corrigendum: Genome-wide association analysis identifies novel blood pressure loci and offers biological insights into cardiovascular risk., Nat Genet, Vol: 49, Pages: 1558-1558

Journal article

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