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1,497 results on '"Lawlor, D"'

101. The effect of patient transfer on outcomes after rupture of an abdominal aortic aneurysm

Author

Hames, Heather, Forbes, Thomas L., Harris, Jeremy R., Lawlor, D. Kirk, DeRose, Guy, and Harris, Kenneth A.

Subjects
Abdominal aneurysm -- Patient outcomes, Abdominal aneurysm -- Risk factors, Patients -- Research
Abstract

Objective: Centralization of vascular surgery services has resulted in patients being transferred longer distances for treatment of life-threatening conditions. The purpose of this study was to determine whether patient transfer [...]

Published
2007

102. Evidence of detrimental effects of prenatal alcohol exposure on offspring birthweight and neurodevelopment from a systematic review of quasi-experimental studies

Author

Mamluk, L., Jones, T. (T.), Ijaz, S., Edwards, H., Savovic, J., Leach, V., Moore, T. (Tara), Hinke Kessler Scholder, S.M.L. (Stephanie) von, Lewis, S. (Suzan), Donovan, J. (Jenny), Lawlor, D, Davey-Smith, G. (George), Fraser, A, Zuccolo, L, Mamluk, L., Jones, T. (T.), Ijaz, S., Edwards, H., Savovic, J., Leach, V., Moore, T. (Tara), Hinke Kessler Scholder, S.M.L. (Stephanie) von, Lewis, S. (Suzan), Donovan, J. (Jenny), Lawlor, D, Davey-Smith, G. (George), Fraser, A, and Zuccolo, L

Abstract

Background: Systematic reviews of prenatal alcohol exposure effects generally only include conventional observational studies. However, estimates from such studie

Published
2020
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103. Epigenome-wide meta-analysis of blood DNA methylation in newborns and children identifies numerous loci related to gestational age

Author

Merid, S. K. (Simon Kebede), Novoloaca, A. (Alexei), Sharp, G. C. (Gemma C.), Kupers, L. K. (Leanne K.), Kho, A. T. (Alvin T.), Roy, R. (Ritu), Gao, L. (Lu), Annesi-Maesano, I. (Isabella), Jain, P. (Pooja), Plusquin, M. (Michelle), Kogevinas, M. (Manolis), Allard, C. (Catherine), Vehmeijer, F. O. (Florianne O.), Kazmi, N. (Nabila), Salas, L. A. (Lucas A.), Rezwan, F. I. (Faisal I.), Zhang, H. (Hongmei), Sebert, S. (Sylvain), Czamara, D. (Darina), Rifas-Shiman, S. L. (Sheryl L.), Melton, P. E. (Phillip E.), Lawlor, D. A. (Debbie A.), Pershagen, G. (Goran), Breton, C. V. (Carrie V.), Huen, K. (Karen), Baiz, N. (Nour), Gagliardi, L. (Luigi), Nawrot, T. S. (Tim S.), Corpeleijn, E. (Eva), Perron, P. (Patrice), Duijts, L. (Liesbeth), Nohr, E. A. (Ellen Aagaard), Bustamante, M. (Mariona), Ewart, S. L. (Susan L.), Karmaus, W. (Wilfried), Zhao, S. (Shanshan), Page, C. M. (Christian M.), Herceg, Z. (Zdenko), Jarvelin, M.-R. (Marjo-Riitta), Lahti, J. (Jari), Baccarelli, A. A. (Andrea A.), Anderson, D. (Denise), Kachroo, P. (Priyadarshini), Relton, C. L. (Caroline L.), Bergstrom, A. (Anna), Eskenazi, B. (Brenda), Soomro, M. H. (Munawar Hussain), Vineis, P. (Paolo), Snieder, H. (Harold), Bouchard, L. (Luigi), Jaddoe, V. W. (Vincent W.), Sorensen, T. I. (Thorkild I. A.), Vrijheid, M. (Martine), Arshad, S. H. (S. Hasan), Holloway, J. W. (John W.), Haberg, S. E. (Siri E.), Magnus, P. (Per), Dwyer, T. (Terence), Binder, E. B. (Elisabeth B.), DeMeo, D. L. (Dawn L.), Vonk, J. M. (Judith M.), Newnham, J. (John), Tantisira, K. G. (Kelan G.), Kull, I. (Inger), Wiemels, J. L. (Joseph L.), Heude, B. (Barbara), Sunyer, J. (Jordi), Nystad, W. (Wenche), Munthe-Kaas, M. C. (Monica C.), Raikkonen, K. (Katri), Oken, E. (Emily), Huang, R.-C. (Rae-Chi), Weiss, S. T. (Scott T.), Anto, J. M. (Josep Maria), Bousquet, J. (Jean), Kumar, A. (Ashish), Soderhall, C. (Cilla), Almqvist, C. (Catarina), Cardenas, A. (Andres), Gruzieva, O. (Olena), Xu, C.-J. (Cheng-Jian), Reese, S. E. (Sarah E.), Kere, J. (Juha), Brodin, P. (Petter), Solomon, O. (Olivia), Wielscher, M. (Matthias), Holland, N. (Nina), Ghantous, A. (Akram), Hivert, M.-F. (Marie-France), Felix, J. F. (Janine F.), Koppelman, G. H. (Gerard H.), London, S. J. (Stephanie J.), Melen, E. (Erik), Merid, S. K. (Simon Kebede), Novoloaca, A. (Alexei), Sharp, G. C. (Gemma C.), Kupers, L. K. (Leanne K.), Kho, A. T. (Alvin T.), Roy, R. (Ritu), Gao, L. (Lu), Annesi-Maesano, I. (Isabella), Jain, P. (Pooja), Plusquin, M. (Michelle), Kogevinas, M. (Manolis), Allard, C. (Catherine), Vehmeijer, F. O. (Florianne O.), Kazmi, N. (Nabila), Salas, L. A. (Lucas A.), Rezwan, F. I. (Faisal I.), Zhang, H. (Hongmei), Sebert, S. (Sylvain), Czamara, D. (Darina), Rifas-Shiman, S. L. (Sheryl L.), Melton, P. E. (Phillip E.), Lawlor, D. A. (Debbie A.), Pershagen, G. (Goran), Breton, C. V. (Carrie V.), Huen, K. (Karen), Baiz, N. (Nour), Gagliardi, L. (Luigi), Nawrot, T. S. (Tim S.), Corpeleijn, E. (Eva), Perron, P. (Patrice), Duijts, L. (Liesbeth), Nohr, E. A. (Ellen Aagaard), Bustamante, M. (Mariona), Ewart, S. L. (Susan L.), Karmaus, W. (Wilfried), Zhao, S. (Shanshan), Page, C. M. (Christian M.), Herceg, Z. (Zdenko), Jarvelin, M.-R. (Marjo-Riitta), Lahti, J. (Jari), Baccarelli, A. A. (Andrea A.), Anderson, D. (Denise), Kachroo, P. (Priyadarshini), Relton, C. L. (Caroline L.), Bergstrom, A. (Anna), Eskenazi, B. (Brenda), Soomro, M. H. (Munawar Hussain), Vineis, P. (Paolo), Snieder, H. (Harold), Bouchard, L. (Luigi), Jaddoe, V. W. (Vincent W.), Sorensen, T. I. (Thorkild I. A.), Vrijheid, M. (Martine), Arshad, S. H. (S. Hasan), Holloway, J. W. (John W.), Haberg, S. E. (Siri E.), Magnus, P. (Per), Dwyer, T. (Terence), Binder, E. B. (Elisabeth B.), DeMeo, D. L. (Dawn L.), Vonk, J. M. (Judith M.), Newnham, J. (John), Tantisira, K. G. (Kelan G.), Kull, I. (Inger), Wiemels, J. L. (Joseph L.), Heude, B. (Barbara), Sunyer, J. (Jordi), Nystad, W. (Wenche), Munthe-Kaas, M. C. (Monica C.), Raikkonen, K. (Katri), Oken, E. (Emily), Huang, R.-C. (Rae-Chi), Weiss, S. T. (Scott T.), Anto, J. M. (Josep Maria), Bousquet, J. (Jean), Kumar, A. (Ashish), Soderhall, C. (Cilla), Almqvist, C. (Catarina), Cardenas, A. (Andres), Gruzieva, O. (Olena), Xu, C.-J. (Cheng-Jian), Reese, S. E. (Sarah E.), Kere, J. (Juha), Brodin, P. (Petter), Solomon, O. (Olivia), Wielscher, M. (Matthias), Holland, N. (Nina), Ghantous, A. (Akram), Hivert, M.-F. (Marie-France), Felix, J. F. (Janine F.), Koppelman, G. H. (Gerard H.), London, S. J. (Stephanie J.), and Melen, E. (Erik)

Abstract

Background: Preterm birth and shorter duration of pregnancy are associated with increased morbidity in neonatal and later life. As the epigenome is known to have an important role during fetal development, we investigated associations between gestational age and blood DNA methylation in children. Methods: We performed meta-analysis of Illumina’s HumanMethylation450-array associations between gestational age and cord blood DNA methylation in 3648 newborns from 17 cohorts without common pregnancy complications, induced delivery or caesarean section. We also explored associations of gestational age with DNA methylation measured at 4–18 years in additional pediatric cohorts. Follow-up analyses of DNA methylation and gene expression correlations were performed in cord blood. DNA methylation profiles were also explored in tissues relevant for gestational age health effects: fetal brain and lung. Results: We identified 8899 CpGs in cord blood that were associated with gestational age (range 27–42 weeks), at Bonferroni significance, P < 1.06 × 10⁻⁷, of which 3343 were novel. These were annotated to 4966 genes. After restricting findings to at least three significant adjacent CpGs, we identified 1276 CpGs annotated to 325 genes. Results were generally consistent when analyses were restricted to term births. Cord blood findings tended not to persist into childhood and adolescence. Pathway analyses identified enrichment for biological processes critical to embryonic development. Follow-up of identified genes showed correlations between gestational age and DNA methylation levels in fetal brain and lung tissue, as well as correlation with expression levels. Conclusions: We identified numerous CpGs differentially methylated in relation to gestational age at birth that appear to reflect fetal developmental processes across tissues. These findings may contribute to understanding mechanisms linking gestational age to health effects.

Published
2020

104. Dissecting maternal and fetal genetic effects underlying the associations between maternal phenotypes, birth outcomes, and adult phenotypes:a mendelian-randomization and haplotype-based genetic score analysis in 10,734 mother–infant pairs

Author

Chen, J. (Jing), Bacelis, J. (Jonas), Sole-Navais, P. (Pol), Srivastava, A. (Amit), Juodakis, J. (Julius), Rouse, A. (Amy), Hallman, M. (Mikko), Teramo, K. (Kari), Melbye, M. (Mads), Feenstra, B. (Bjarke), Freathy, R. M. (Rachel M.), Smith, G. D. (George Davey), Lawlor, D. A. (Deborah A.), Murray, J. C. (Jeffrey C.), Williams, S. M. (Scott M.), Jacobsson, B. (Bo), Muglia, L. J. (Louis J.), Zhang, G. (Ge), Chen, J. (Jing), Bacelis, J. (Jonas), Sole-Navais, P. (Pol), Srivastava, A. (Amit), Juodakis, J. (Julius), Rouse, A. (Amy), Hallman, M. (Mikko), Teramo, K. (Kari), Melbye, M. (Mads), Feenstra, B. (Bjarke), Freathy, R. M. (Rachel M.), Smith, G. D. (George Davey), Lawlor, D. A. (Deborah A.), Murray, J. C. (Jeffrey C.), Williams, S. M. (Scott M.), Jacobsson, B. (Bo), Muglia, L. J. (Louis J.), and Zhang, G. (Ge)

Abstract

Background/Objectives: Many maternal traits are associated with a neonate’s gestational duration, birth weight, and birth length. These birth outcomes are subsequently associated with late-onset health conditions. The causal mechanisms and the relative contributions of maternal and fetal genetic effects behind these observed associations are unresolved. Methods and findings: Based on 10,734 mother–infant duos of European ancestry from the UK, Northern Europe, Australia, and North America, we constructed haplotype genetic scores using single-nucleotide polymorphisms (SNPs) known to be associated with adult height, body mass index (BMI), blood pressure (BP), fasting plasma glucose (FPG), and type 2 diabetes (T2D). Using these scores as genetic instruments, we estimated the maternal and fetal genetic effects underlying the observed associations between maternal phenotypes and pregnancy outcomes. We also used infant-specific birth weight genetic scores as instrument and examined the effects of fetal growth on pregnancy outcomes, maternal BP, and glucose levels during pregnancy. The maternal nontransmitted haplotype score for height was significantly associated with gestational duration (p = 2.2 × 10⁻⁴). Both maternal and paternal transmitted height haplotype scores were highly significantly associated with birth weight and length (p < 1 × 10⁻¹⁷). The maternal transmitted BMI scores were associated with birth weight with a significant maternal effect (p = 1.6 × 10⁻⁴). Both maternal and paternal transmitted BP scores were negatively associated with birth weight with a significant fetal effect (p = 9.4 × 10⁻³), whereas BP alleles were significantly associated with gestational duration and preterm birth through maternal effects (p = 3.3 × 10⁻² and p = 4.5 × 10⁻³, respectively). The nontransmitted haplotype score for FPG was strongly associated with birth weight (p = 4.7 × 10⁻⁶); however, the glucose-increasing alleles in the fetus were associated with reduced bi

Published
2020

105. The LifeCycle Project-EU Child Cohort Network:a federated analysis infrastructure and harmonized data of more than 250,000 children and parents

Author

Jaddoe, V. W. (Vincent W. V.), Felix, J. F. (Janine F.), Andersen, A. N. (Anne‑Marie Nybo), Charles, M. (Marie‑Aline), Chatzi, L. (Leda), Corpeleijn, E. (Eva), Donner, N. (Nina), Elhakeem, A. (Ahmed), Eriksson, J. G. (Johan G.), Foong, R. (Rachel), Grote, V. (Veit), Haakma, S. (Sido), Hanson, M. (Mark), Harris, J. R. (Jennifer R.), Heude, B. (Barbara), Huang, R. (Rae‑Chi), Inskip, H. (Hazel), Järvelin, M. (Marjo‑Riitta), Koletzko, B. (Berthold), Lawlor, D. A. (Deborah A.), Lindeboom, M. (Maarten), McEachan, R. R. (Rosemary R. C.), Mikkola, T. M. (Tuija M.), Nader, J. L. (Johanna L. T.), Pinot de Moira, A. (Angela), Pizzi, C. (Costanza), Richiardi, L. (Lorenzo), Sebert, S. (Sylvain), Schwalber, A. (Ameli), Sunyer, J. (Jordi), Swertz, M. A. (Morris A.), Vafeiadi, M. (Marina), Vrijheid, M. (Martine), Wright, J. (John), Duijts, L. (Liesbeth), L. P. (LifeCycle Project Group), Jaddoe, V. W. (Vincent W. V.), Felix, J. F. (Janine F.), Andersen, A. N. (Anne‑Marie Nybo), Charles, M. (Marie‑Aline), Chatzi, L. (Leda), Corpeleijn, E. (Eva), Donner, N. (Nina), Elhakeem, A. (Ahmed), Eriksson, J. G. (Johan G.), Foong, R. (Rachel), Grote, V. (Veit), Haakma, S. (Sido), Hanson, M. (Mark), Harris, J. R. (Jennifer R.), Heude, B. (Barbara), Huang, R. (Rae‑Chi), Inskip, H. (Hazel), Järvelin, M. (Marjo‑Riitta), Koletzko, B. (Berthold), Lawlor, D. A. (Deborah A.), Lindeboom, M. (Maarten), McEachan, R. R. (Rosemary R. C.), Mikkola, T. M. (Tuija M.), Nader, J. L. (Johanna L. T.), Pinot de Moira, A. (Angela), Pizzi, C. (Costanza), Richiardi, L. (Lorenzo), Sebert, S. (Sylvain), Schwalber, A. (Ameli), Sunyer, J. (Jordi), Swertz, M. A. (Morris A.), Vafeiadi, M. (Marina), Vrijheid, M. (Martine), Wright, J. (John), Duijts, L. (Liesbeth), and L. P. (LifeCycle Project Group)

Abstract

Early life is an important window of opportunity to improve health across the full lifecycle. An accumulating body of evidence suggests that exposure to adverse stressors during early life leads to developmental adaptations, which subsequently affect disease risk in later life. Also, geographical, socio-economic, and ethnic differences are related to health inequalities from early life onwards. To address these important public health challenges, many European pregnancy and childhood cohorts have been established over the last 30 years. The enormous wealth of data of these cohorts has led to important new biological insights and important impact for health from early life onwards. The impact of these cohorts and their data could be further increased by combining data from different cohorts. Combining data will lead to the possibility of identifying smaller effect estimates, and the opportunity to better identify risk groups and risk factors leading to disease across the lifecycle across countries. Also, it enables research on better causal understanding and modelling of life course health trajectories. The EU Child Cohort Network, established by the Horizon2020-funded LifeCycle Project, brings together nineteen pregnancy and childhood cohorts, together including more than 250,000 children and their parents. A large set of variables has been harmonised and standardized across these cohorts. The harmonized data are kept within each institution and can be accessed by external researchers through a shared federated data analysis platform using the R-based platform DataSHIELD, which takes relevant national and international data regulations into account. The EU Child Cohort Network has an open character. All protocols for data harmonization and setting up the data analysis platform are available online. The EU Child Cohort Network creates great opportunities for researchers to use data from different cohorts, during and beyond the LifeCycle Project duration. It

Published
2020

106. Genome wide association study of circulating interleukin 6 levels identifies novel loci

Author

Ahluwalia, T. S., Armstrong, N. J., Aslibekyan, S., Beekman, M., Cheng, Y., deGeus, E., Delgado, G. E., Marek, D., Kanoni, S., Nolte, I. M., Porcu, E., Seppala, I., Standl, M., Teumer, A., Thalamuthu, A., Trompet, S., Benjamin, E. J., Feitosa, M. F., Homuth, G., Lahti, J., Liu, Y., Timpson, N. J., Visvikis-Siest, S., Voelker, U., Baune, B. T., Boomsma, D., Deary, I. J., Evans, D. M., Ferreira, M. A., Gaunt, T., Gudnason, V., Hamsten, A., Humphries, S. E., Koeing, W., Kumari, M., Lawlor, D. A., Nauck, M., Price, J. F., Sorensen, T. I. A., Stacey, D., Stathopoulou, M. G., Tanaka, T., Wannamethee, S. G., Rotter, J. I., Dehghan, A., Boerwinkle, E., Sneider, H., Psaty, B. M., Prins, B. P., Alizadeh, B. Z., Ahluwalia, T. S., Armstrong, N. J., Aslibekyan, S., Beekman, M., Cheng, Y., deGeus, E., Delgado, G. E., Marek, D., Kanoni, S., Nolte, I. M., Porcu, E., Seppala, I., Standl, M., Teumer, A., Thalamuthu, A., Trompet, S., Benjamin, E. J., Feitosa, M. F., Homuth, G., Lahti, J., Liu, Y., Timpson, N. J., Visvikis-Siest, S., Voelker, U., Baune, B. T., Boomsma, D., Deary, I. J., Evans, D. M., Ferreira, M. A., Gaunt, T., Gudnason, V., Hamsten, A., Humphries, S. E., Koeing, W., Kumari, M., Lawlor, D. A., Nauck, M., Price, J. F., Sorensen, T. I. A., Stacey, D., Stathopoulou, M. G., Tanaka, T., Wannamethee, S. G., Rotter, J. I., Dehghan, A., Boerwinkle, E., Sneider, H., Psaty, B. M., Prins, B. P., and Alizadeh, B. Z.

Published
2020

112. Establishing reference intervals for triglyceride containing lipoprotein sub-fraction metabolites measured using nuclear magnetic resonance spectroscopy in a UK population

Author

Joshi, R., primary, Hingorani, A.D., additional, Engmann, J., additional, Dale, C., additional, Gaunt, T., additional, Jefferis, B., additional, Lawlor, D., additional, Price, J., additional, Papacosta, O., additional, Shah, T., additional, Tillin, T., additional, Chaturvedi, N., additional, Kivimaki, M., additional, Kuh, D., additional, Kumari, M., additional, Hughes, A., additional, Whincup, P., additional, Casas, J.P., additional, Humphries, S.E., additional, Schmidt, A.F., additional, and Wannamethee, S.G., additional

Published
2020
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114. Is intensive care necessary after elective abdominal aortic aneurysm repair?

Author

Lawlor, D. Kirk, Lovell, Marge B., DeRose, Guy, Forbes, Thomas L., and Harris, Kenneth A.

Subjects
Postoperative care -- Evaluation, Abdominal aneurysm -- Care and treatment, Intensive care nursing -- Evaluation
Abstract

Background: To review morbidity and mortality of patients undergoing elective, open repair of infrarenal abdominal aortic aneurysms and were admitted postoperatively to a surgical stepdown unit rather than routinely to [...]

Published
2004

129. Genome-wide association analysis of self-reported daytime sleepiness identifies 42 loci that suggest biological subtypes

Author

Wang, H., primary, Lane, J., additional, Jones, S., additional, Dashti, H., additional, Ollila, H., additional, Wood, A., additional, van Hees, V., additional, Brumpton, B., additional, Winsvold, B., additional, Kantojärvi, K., additional, Palviainen, T., additional, Cade, B., additional, Sofer, T., additional, Song, Y., additional, Patel, K., additional, Anderson, S., additional, Bechtold, D., additional, Bowden, J., additional, Emsley, R., additional, Kyle, S., additional, Little, M., additional, Loudon, A., additional, Scheer, F., additional, Purcell, S., additional, Richmond, R., additional, Spiegelhalder, K., additional, Tyrrell, J., additional, Zhu, X., additional, Hublin, C., additional, Kaprio, J., additional, Kristiansson, K., additional, Sulkava, S., additional, Paunio, T., additional, Hveem, K., additional, Nielsen, J., additional, Willer, C., additional, Zwart, J.-A., additional, Strand, L., additional, Frayling, T., additional, Ray, D., additional, Lawlor, D., additional, Rutter, M., additional, Weedon, M., additional, Redline, S., additional, and Saxena, R., additional

Published
2019
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143. Liver function and risk of type 2 diabetes:bidirectional Mendelian randomization study

Author

De Silva, N. M. (N. Maneka G.), Borges, M. C. (Maria Carolina), Hingorani, A. (Aroon), Engmann, J. (Jorgen), Shah, T. (Tina), Zhang, X. (Xiaoshuai), Luan, J. (Jian'an), Langenberg, C. (Claudia), Wong, A. (Andrew), Kuh, D. (Diana), Chambers, J. C. (John C), Zhang, W. (Weihua), Järvelin, M.-R. (Marjo-Ritta), Sebert, S. (Sylvain), Auvinen, J. (Juha), U. c. (UCLEB consortium), Gaunt, T. R. (Tom R), and Lawlor, D. A. (Deborah A)

Subjects
endocrine system diseases, nutritional and metabolic diseases, human activities, digestive system, digestive system diseases
Abstract

Liver dysfunction and type 2 diabetes (T2D) are consistently associated. However, it is currently unknown whether liver dysfunction contributes to, results from or is merely correlated with T2D due to confounding. We used Mendelian randomization (MR) to investigate the presence and direction of any causal relation between liver function and T2D risk including up to 64,094 T2D cases and 607,012 controls. Several biomarkers were used as proxies of liver function [i.e. alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), and gamma-glutamyl transferase (GGT)]. Genetic variants strongly associated with each liver function marker were used to investigate the effect of liver function on T2D risk. In addition, genetic variants strongly associated with T2D risk and with fasting insulin were used to investigate the effect of predisposition to T2D and insulin resistance, respectively, on liver function. Genetically predicted higher circulating ALT and AST were related to increased risk of T2D. There was a modest negative association of genetically predicted ALP with T2D risk and no evidence of association between GGT and T2D risk. Genetically predisposition to higher fasting insulin, but not to T2D, was related to increased circulating ALT. Since circulating ALT and AST are markers of NAFLD, these findings provide some support for insulin resistance resulting in NAFLD, which in turn increases T2D risk.

Published
2019

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