Reproductive and cardio-metabolic health
Lead Research Organisation:
University of Bristol
Department Name: UNLISTED
Abstract
We are trying to find out how to improve the success of in-vitro fertilisation (IVF) and make sure that women who have conceived by IVF or ‘naturally’ have a healthy pregnancy and birth.
IVF is common. In an average school class of 30 children 1 will have been born by IVF. New ways of using IVF might improve success rates but they need to be carefully evaluated.
Whether women conceive by IVF or naturally up to 40% will have one or more of pregnancy loss, high blood pressure or high blood sugar in pregnancy, a premature birth or an infant who is born unhealthily small or large. We do not know how to prevent these problems or predict which women will experience them.
We will use data from very large studies and new methods that help us to determine causes from ‘confounders’ (factors that fool us into thinking that something is a cause when it is not). This will allow us to work out how to improve IVF and prevent pregnancy problems. It will also improve our understanding of what risk factors in pregnancy affect children’s risk of being obese or having diabetes or heart problems later in their lives.
IVF is common. In an average school class of 30 children 1 will have been born by IVF. New ways of using IVF might improve success rates but they need to be carefully evaluated.
Whether women conceive by IVF or naturally up to 40% will have one or more of pregnancy loss, high blood pressure or high blood sugar in pregnancy, a premature birth or an infant who is born unhealthily small or large. We do not know how to prevent these problems or predict which women will experience them.
We will use data from very large studies and new methods that help us to determine causes from ‘confounders’ (factors that fool us into thinking that something is a cause when it is not). This will allow us to work out how to improve IVF and prevent pregnancy problems. It will also improve our understanding of what risk factors in pregnancy affect children’s risk of being obese or having diabetes or heart problems later in their lives.
Technical Summary
Our aim is to provide the evidence base that will improve treatment success with IVF and enable stratified and effective antenatal care in IVF and spontaneous conceptions (SC).
This is important because up to 40% or pregnancies are affected by one or more of miscarriage, stillbirth, hypertensive disorders of pregnancy, gestational diabetes, preterm birth or delivery or a small or large for gestational aged infant, but we do not know the best way of preventing these. IVF is now the commonest treatment for infertility with >250K IVF cycles completed per year in the UK and on average 1 in 30 primary school children were born as a result of in vitro fertilisation (IVF). Success rates vary by couple and treatment characteristics but are between 20-30%. There are suggestions that IVF per se, and pregnancy complications in IVF and SC have important adverse effects on future offspring cardio-metabolic health, but whether these associations are causal and if so their magnitude is unclear.
Our objectives are to accurately predict and identify causal paths for: (i) response to IVF; (ii) healthy pregnancy and perinatal outcomes in IVF and SC; and (iii) offspring cardio-metabolic health.
Methods
Our focus will primarily be on maternal smoking, physical activity, sleep patterns, adiposity, pregnancy metabolic profiles and fetal (cord-blood) DNA methylation as potential predictors or risk factors.
We will use data from detailed clinical and general pregnancy/birth cohorts. We will work with relevant consortia, including the EuroCHILD pan-European birth cohort that we are involved in establishing from 26 existing cohorts, early growth genetics (EGG) consortia, in which we co-lead maternal-offspring genetic analyses, the Genetics of Diabetes In Pregnancy (GENdip) consortia that we have recently developed, and the pregnancy/birth cohorts working group aligned to the Consortia Of METabolomics Studies (COMETS), which we lead, as well as the Pregnancy And Child Epigenetics (PACE) consortia, which we work closely with alongside Relton’s MRC Integrative Epidemiology Unit programme. We will triangulate results across the following analytical methods applied to these data sources: multivariable regression (MV), Mendelian randomization (MR), non-genetic instrumental variable (IV) analyses, within sibship and negative control studies.
Translation
Building on our successful impact on clinical guidelines in the first five-years of this programme, we will continue to work with relevant clinicians, patient groups and NICE guideline developers. For new methodological developments we will provide and share datasets and code and widely disseminate these.
This is important because up to 40% or pregnancies are affected by one or more of miscarriage, stillbirth, hypertensive disorders of pregnancy, gestational diabetes, preterm birth or delivery or a small or large for gestational aged infant, but we do not know the best way of preventing these. IVF is now the commonest treatment for infertility with >250K IVF cycles completed per year in the UK and on average 1 in 30 primary school children were born as a result of in vitro fertilisation (IVF). Success rates vary by couple and treatment characteristics but are between 20-30%. There are suggestions that IVF per se, and pregnancy complications in IVF and SC have important adverse effects on future offspring cardio-metabolic health, but whether these associations are causal and if so their magnitude is unclear.
Our objectives are to accurately predict and identify causal paths for: (i) response to IVF; (ii) healthy pregnancy and perinatal outcomes in IVF and SC; and (iii) offspring cardio-metabolic health.
Methods
Our focus will primarily be on maternal smoking, physical activity, sleep patterns, adiposity, pregnancy metabolic profiles and fetal (cord-blood) DNA methylation as potential predictors or risk factors.
We will use data from detailed clinical and general pregnancy/birth cohorts. We will work with relevant consortia, including the EuroCHILD pan-European birth cohort that we are involved in establishing from 26 existing cohorts, early growth genetics (EGG) consortia, in which we co-lead maternal-offspring genetic analyses, the Genetics of Diabetes In Pregnancy (GENdip) consortia that we have recently developed, and the pregnancy/birth cohorts working group aligned to the Consortia Of METabolomics Studies (COMETS), which we lead, as well as the Pregnancy And Child Epigenetics (PACE) consortia, which we work closely with alongside Relton’s MRC Integrative Epidemiology Unit programme. We will triangulate results across the following analytical methods applied to these data sources: multivariable regression (MV), Mendelian randomization (MR), non-genetic instrumental variable (IV) analyses, within sibship and negative control studies.
Translation
Building on our successful impact on clinical guidelines in the first five-years of this programme, we will continue to work with relevant clinicians, patient groups and NICE guideline developers. For new methodological developments we will provide and share datasets and code and widely disseminate these.
Organisations
- University of Bristol (Lead Research Organisation)
- University of Groningen (Collaboration)
- Norwegian University of Science and Technology (NTNU) (Collaboration)
- UNIVERSITY OF EDINBURGH (Collaboration)
- Leiden University Medical Center (Collaboration)
- Barcelona Institute for Global Health (Collaboration)
- Cardiff University (Collaboration)
- University of Bath (Collaboration)
- University of Auckland (Collaboration)
- University College Cork (Collaboration)
- Bradford Teaching Hospitals NHS Foundation Trust (Collaboration)
- Norwegian Institute of Public Health (Collaboration)
- University of Amsterdam (Collaboration)
- University of Queensland (Collaboration)
- University of Paris (Collaboration)
- University of Bristol (Collaboration)
- UNIVERSITY OF SOUTHAMPTON (Collaboration)
- HARVARD UNIVERSITY (Collaboration)
- Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium (CHARGE) (Collaboration)
- University of Copenhagen (Collaboration)
- GW4 (Collaboration)
- Federal University of Rio Grande (FURG) (Collaboration)
- University of Oulu (Collaboration)
- IMPERIAL COLLEGE LONDON (Collaboration)
- UNIVERSITY OF CAMBRIDGE (Collaboration)
- UNIVERSITY OF EXETER (Collaboration)
- University of Melbourne (Collaboration)
- University of Turin (Collaboration)
- UNIVERSITY OF GLASGOW (Collaboration)
- National University of Singapore (Collaboration)
- London School of Hygiene and Tropical Medicine (LSHTM) (Collaboration)
- Erasmus University Rotterdam (Collaboration)
- Federal University of Pelotas (UFPel) (Collaboration)
- KING'S COLLEGE LONDON (Collaboration)
People |
ORCID iD |
Debbie Lawlor (Principal Investigator) |
Publications
Houtepen L
(2018)
Childhood adversity and DNA methylation in two population-based cohorts
in Translational Psychiatry
O'Keeffe LM
(2018)
Sex-specific trajectories of measures of cardiovascular health during childhood and adolescence: A prospective cohort study.
in Atherosclerosis
Soares ALG
(2018)
Adverse Childhood Experiences (ACEs) and Adiposity in Adolescents: A Cross-Cohort Comparison.
in Obesity (Silver Spring, Md.)
Elhakeem A
(2019)
Association Between Age at Puberty and Bone Accrual From 10 to 25 Years of Age.
in JAMA network open
Bowden J
(2019)
Improving the accuracy of two-sample summary-data Mendelian randomization: moving beyond the NOME assumption.
in International journal of epidemiology
De Silva NMG
(2019)
Liver Function and Risk of Type 2 Diabetes: Bidirectional Mendelian Randomization Study.
in Diabetes
Hwang LD
(2019)
New insight into human sweet taste: a genome-wide association study of the perception and intake of sweet substances.
in The American journal of clinical nutrition
Bird PK
(2019)
Growing up in Bradford: protocol for the age 7-11 follow up of the Born in Bradford birth cohort.
in BMC public health
Related Projects
Project Reference | Relationship | Related To | Start | End | Award Value |
---|---|---|---|---|---|
MC_UU_00011/1 | 31/03/2018 | 30/03/2023 | £2,864,000 | ||
MC_UU_00011/2 | Transfer | MC_UU_00011/1 | 31/03/2018 | 30/03/2023 | £965,000 |
MC_UU_00011/3 | Transfer | MC_UU_00011/2 | 31/03/2018 | 30/03/2023 | £1,011,000 |
MC_UU_00011/4 | Transfer | MC_UU_00011/3 | 31/03/2018 | 30/03/2023 | £1,329,000 |
MC_UU_00011/5 | Transfer | MC_UU_00011/4 | 31/03/2018 | 30/03/2023 | £1,254,000 |
MC_UU_00011/6 | Transfer | MC_UU_00011/5 | 31/03/2018 | 30/03/2023 | £1,640,000 |
MC_UU_00011/7 | Transfer | MC_UU_00011/6 | 31/03/2018 | 30/03/2023 | £1,083,000 |
Description | DHSC consultation on women's health |
Geographic Reach | National |
Policy Influence Type | Contribution to a national consultation/review |
URL | https://www.gov.uk/government/consultations/womens-health-strategy-call-for-evidence |
Description | A longitudinal population-based study of the development of cardiovascular risk in early childhood |
Amount | $1,217,906 (AUD) |
Funding ID | APP1164212 |
Organisation | National Health and Medical Research Council |
Sector | Public |
Country | Australia |
Start | 09/2018 |
End | 09/2023 |
Description | Association of birthweight with perinatal, infant and maternal outcomes: A population linkage study |
Amount | £129,549 (GBP) |
Funding ID | RG2028 |
Organisation | Wellbeing of Women |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 03/2018 |
End | 02/2020 |
Description | BHF Accelerator award |
Amount | £1,000,000 (GBP) |
Funding ID | AA/18/7/34219 |
Organisation | British Heart Foundation (BHF) |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 03/2019 |
End | 03/2023 |
Description | BHF Chair of Cardiovascular Science and Clinical Epidemiology |
Amount | £508,351 (GBP) |
Funding ID | CH/F/20/90003 |
Organisation | British Heart Foundation (BHF) |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 04/2021 |
End | 04/2026 |
Description | Born in Bradford Age of Wonder |
Amount | £6,999,754 (GBP) |
Funding ID | 223601/Z/21/Z |
Organisation | Wellcome Trust |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 01/2022 |
End | 12/2028 |
Description | Born in Scotland in the 2020s - Pilot study |
Amount | £879,708 (GBP) |
Funding ID | MR/V034294/1 |
Organisation | Medical Research Council (MRC) |
Sector | Public |
Country | United Kingdom |
Start | 09/2021 |
End | 03/2024 |
Description | Cardiometabolic health of women with and without adverse pregnancy outcomes: An electronic health records study |
Amount | £249,879 (GBP) |
Funding ID | PG/19/21/34190 |
Organisation | British Heart Foundation (BHF) |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 01/2020 |
End | 12/2023 |
Description | Conception by artificial reproductive technologies and offspring health: ART-HEALTH |
Amount | € 2,499,951 (EUR) |
Funding ID | 101021566 |
Organisation | European Research Council (ERC) |
Sector | Public |
Country | Belgium |
Start | 12/2021 |
End | 11/2026 |
Description | Developing and Applying Statistical Genetics Methods to Elucidate the Developmental Origins of Health and Disease |
Amount | $327,387 (AUD) |
Funding ID | 1183074 |
Organisation | National Health and Medical Research Council |
Sector | Public |
Country | Australia |
Start | 01/2020 |
End | 12/2022 |
Description | Developing and applying new statistical models to test for transgenerational effects of environmental exposures in pregnancy |
Amount | kr 10,046,000 (NOK) |
Funding ID | 325640 |
Organisation | Research Council of Norway |
Sector | Public |
Country | Norway |
Start | 08/2021 |
End | 08/2024 |
Description | ESRC New Investigator Grant: Accumulative processes in health inequalities: the socioeconomic causes and consequences of mental and physical health comorbidity in adolescence |
Amount | £287,040 (GBP) |
Funding ID | ES/T013923/1 |
Organisation | Economic and Social Research Council |
Sector | Public |
Country | United Kingdom |
Start | 11/2020 |
End | 01/2023 |
Description | GW4 Generator Award |
Amount | £14,800 (GBP) |
Organisation | GW4 |
Sector | Academic/University |
Country | United Kingdom |
Start | 05/2021 |
End | 11/2021 |
Description | Healthy Lives Malawi: Intergenerational Cohort of Chronic Conditions. |
Amount | £4,930,605 (GBP) |
Funding ID | 217013/Z/19/Z |
Organisation | Wellcome Trust |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 09/2019 |
End | 09/2024 |
Description | Identifying maternal and fetal genetic determinants of infant birthweight and their relationship to offspring cardiometabolic risk |
Amount | $367,992 (AUD) |
Funding ID | APP1157714 |
Organisation | National Health and Medical Research Council |
Sector | Public |
Country | Australia |
Start | 11/2018 |
End | 10/2023 |
Description | Innovating behaviour and health surveillance for cardiovascular disease prevention in Malaysia |
Amount | £281,479 (GBP) |
Funding ID | MR/T018984/1 |
Organisation | Medical Research Council (MRC) |
Sector | Public |
Country | United Kingdom |
Start | 12/2019 |
End | 11/2021 |
Description | Management of complex congenital heart disease (CHD) - single ventricle focus |
Amount | £16,151 (GBP) |
Funding ID | 2019-Aut-06 |
Organisation | University Hospitals Bristol NHS Foundation Trust |
Department | Above and Beyond Grants |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 01/2020 |
End | 12/2021 |
Description | Mendelian randomization studies of metabolites on heart failure |
Amount | ฿539,000 (THB) |
Organisation | Thailand Research Fund |
Sector | Public |
Country | Thailand |
Start |
Description | Multimorbidity Mechanism and Therapeutics Research Collaborative |
Amount | £3,073,693 (GBP) |
Organisation | United Kingdom Research and Innovation |
Sector | Public |
Country | United Kingdom |
Start | 03/2021 |
End | 03/2024 |
Description | Prediction and prevention of adverse outcomes in pregnancies complicated by placental dysfunction |
Amount | £24,490 (GBP) |
Organisation | David Telling Charitable Trust |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 03/2018 |
End | 02/2019 |
Description | Rapid call, Longitudinal Population Studies Enhancement Award for Born in Bradford to add pregnancy proteomics data |
Amount | £771,566 (GBP) |
Funding ID | MR/N024397/1 |
Organisation | Medical Research Council (MRC) |
Sector | Public |
Country | United Kingdom |
Start | 01/2022 |
End | 04/2022 |
Description | SSCM conference fund scheme |
Amount | £500 (GBP) |
Organisation | University of Bristol |
Sector | Academic/University |
Country | United Kingdom |
Start | 07/2017 |
End | 08/2017 |
Description | Sleep disturbance: new insights into the clinical impact in diabetes |
Amount | £257,928 (GBP) |
Funding ID | 17/0005700 |
Organisation | Diabetes UK |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 03/2018 |
End | 03/2021 |
Description | The Avon Longitudinal Study of Parents and Children (ALSPAC): A multi-generation, longitudinal resource focusing on life course health and well-being. |
Amount | £8,327,295 (GBP) |
Funding ID | 217065/Z/19/Z |
Organisation | Wellcome Trust |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 07/2019 |
End | 08/2024 |
Description | The Born in Bradford COVID-19 Research Study: An adaptive mixed methods longitudinal study of the impact of COVID-19 on health inequalities in families living in Bradford |
Amount | £198,680 (GBP) |
Organisation | The Health Foundation |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 03/2020 |
End | 03/2021 |
Description | Vice-Chancellor's fellowship |
Amount | £227,000 (GBP) |
Organisation | University of Bristol |
Sector | Academic/University |
Country | United Kingdom |
Start | 03/2020 |
End | 03/2024 |
Title | Mendelian Randomization Dictionary |
Description | An only easily searchable dictionary of Mendelian randomization methods, which we keep up to date and have a facility for users to inform us of updates or corrects they feel should be in the Dictionary We are currently working on making a web interface that supports greater interaction with it by users and an app |
Type Of Material | Improvements to research infrastructure |
Year Produced | 2019 |
Provided To Others? | Yes |
Impact | Has been accessed over 4 million times; down loaded over 400 times & cited four times |
URL | https://osf.io/6yzs7/ |
Title | Additional file 1 of Investigating the relationships between unfavourable habitual sleep and metabolomic traits: evidence from multi-cohort multivariable regression and Mendelian randomization analyses |
Description | Additional file 1: Table S1. Characteristics of the study populations in the multivariable-adjusted regression analyses. Table S2. Genetic instruments for insomnia. Table S3. Genetic instruments for total sleep duration. Table S4. Genetic instruments for short sleep duration. Table S5. Genetic instruments for long sleep duration. Table S6. Genetic instruments for chronotype. Table S7. Multivariable-adjusted results for insomnia symptoms. Table S8. Mendelian Randomization results for insomnia symptoms. Table S9. Multivariable-adjusted results for total sleep duration. Table S10. Mendelian Randomization results for total sleep duration. Table S11. Multivariable-adjusted results for short sleep duration. Table S12. Mendelian Randomization results for short sleep duration. Table S13. Multivariable-adjusted results for long sleep duration. Table S14. Mendelian Randomization results for long sleep duration. Table S15. Multivariable-adjusted results for chronotype. Table S16. Mendelian Randomization results for chronotype. |
Type Of Material | Database/Collection of data |
Year Produced | 2021 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_1_of_Investigating_the_relation... |
Title | Additional file 1 of Investigating the relationships between unfavourable habitual sleep and metabolomic traits: evidence from multi-cohort multivariable regression and Mendelian randomization analyses |
Description | Additional file 1: Table S1. Characteristics of the study populations in the multivariable-adjusted regression analyses. Table S2. Genetic instruments for insomnia. Table S3. Genetic instruments for total sleep duration. Table S4. Genetic instruments for short sleep duration. Table S5. Genetic instruments for long sleep duration. Table S6. Genetic instruments for chronotype. Table S7. Multivariable-adjusted results for insomnia symptoms. Table S8. Mendelian Randomization results for insomnia symptoms. Table S9. Multivariable-adjusted results for total sleep duration. Table S10. Mendelian Randomization results for total sleep duration. Table S11. Multivariable-adjusted results for short sleep duration. Table S12. Mendelian Randomization results for short sleep duration. Table S13. Multivariable-adjusted results for long sleep duration. Table S14. Mendelian Randomization results for long sleep duration. Table S15. Multivariable-adjusted results for chronotype. Table S16. Mendelian Randomization results for chronotype. |
Type Of Material | Database/Collection of data |
Year Produced | 2021 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_1_of_Investigating_the_relation... |
Title | Additional file 1 of Mendelian randomization analysis of factors related to ovulation and reproductive function and endometrial cancer risk |
Description | Additional file 1: Table S1. Genome-wide significant independent SNPs for Body Mass Index in women (Pulit 2018). Table S2. Genome-wide significant independent SNPs for Years Ovulating (Hg19). Table S3. Genome-wide significant independent SNPs for age at menarche downloaded from the ReproGen Consortium Website (Perry et al., 2014; Hg19). Table S4. Genome-wide significant independent SNPs for age at menopause downloaded from the ReproGen Consortium Website (Hg19; Day et al., 2015). Table S5. Genome-wide significant independent SNPs for number of live births extracted from Warrington et al., 2021 (Hg19). TableS6. Genome-wide significant independent SNPs for age at last live birth (Hg19). Table S7. Genome-wide significant independent SNPs for Endometrial Cancer used in the bidirectional MR analyses (Hg19). Table S8. Overview of SNPs and possible pleiotropic effects (Hg19). The direction of the association with other traits in PhenoScanner (i.e. positive (+) or negative(-)) is indicated. Table S9. Basic characteristics of the study participants in UK Biobank. Table S10. Results from the multivariate observational analyses of reproductive risk factors and endometrial cancer risk. Table S11. Results from the multivariate observational analyses of number of live births and other reproductive risk factors on endometrial cancer risk. Table S12. Heterogeneity and Directional Pleiotropy tests from MR analysis of female fertility and risk of endometrial cancer. Table S13. Univariate Mendelian randomization results with only the SNPs included in the primary multivariable MR. Table S14. Results from two Multivariable Mendelian Randomization analyses including the exposures A) BMI, age at menarche, age at menopause and number of live births; and B) BMI, age at menarche, years ovulating and number of live births. Table S15. Overview of all SNPs (Hg19) and their association with the different traits included in the multivariable MR analysis. Table S16. Results from the Multivariable Mendelian Randomization analysis including the exposures age at menarche, age at menopause, years ovulating, number of live births and age at last live birth. Table S17. MR analysis of liability to endometrial cancer on number of live births. |
Type Of Material | Database/Collection of data |
Year Produced | 2022 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_1_of_Mendelian_randomization_an... |
Title | Additional file 1 of Mendelian randomization analysis of factors related to ovulation and reproductive function and endometrial cancer risk |
Description | Additional file 1: Table S1. Genome-wide significant independent SNPs for Body Mass Index in women (Pulit 2018). Table S2. Genome-wide significant independent SNPs for Years Ovulating (Hg19). Table S3. Genome-wide significant independent SNPs for age at menarche downloaded from the ReproGen Consortium Website (Perry et al., 2014; Hg19). Table S4. Genome-wide significant independent SNPs for age at menopause downloaded from the ReproGen Consortium Website (Hg19; Day et al., 2015). Table S5. Genome-wide significant independent SNPs for number of live births extracted from Warrington et al., 2021 (Hg19). TableS6. Genome-wide significant independent SNPs for age at last live birth (Hg19). Table S7. Genome-wide significant independent SNPs for Endometrial Cancer used in the bidirectional MR analyses (Hg19). Table S8. Overview of SNPs and possible pleiotropic effects (Hg19). The direction of the association with other traits in PhenoScanner (i.e. positive (+) or negative(-)) is indicated. Table S9. Basic characteristics of the study participants in UK Biobank. Table S10. Results from the multivariate observational analyses of reproductive risk factors and endometrial cancer risk. Table S11. Results from the multivariate observational analyses of number of live births and other reproductive risk factors on endometrial cancer risk. Table S12. Heterogeneity and Directional Pleiotropy tests from MR analysis of female fertility and risk of endometrial cancer. Table S13. Univariate Mendelian randomization results with only the SNPs included in the primary multivariable MR. Table S14. Results from two Multivariable Mendelian Randomization analyses including the exposures A) BMI, age at menarche, age at menopause and number of live births; and B) BMI, age at menarche, years ovulating and number of live births. Table S15. Overview of all SNPs (Hg19) and their association with the different traits included in the multivariable MR analysis. Table S16. Results from the Multivariable Mendelian Randomization analysis including the exposures age at menarche, age at menopause, years ovulating, number of live births and age at last live birth. Table S17. MR analysis of liability to endometrial cancer on number of live births. |
Type Of Material | Database/Collection of data |
Year Produced | 2022 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_1_of_Mendelian_randomization_an... |
Title | Additional file 1 of Role of circulating polyunsaturated fatty acids on cardiovascular diseases risk: analysis using Mendelian randomization and fatty acid genetic association data from over 114,000 UK Biobank participants |
Description | Additional file 1: Supplementary Tables S1-S11. |
Type Of Material | Database/Collection of data |
Year Produced | 2022 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_1_of_Role_of_circulating_polyun... |
Title | Additional file 1 of Role of circulating polyunsaturated fatty acids on cardiovascular diseases risk: analysis using Mendelian randomization and fatty acid genetic association data from over 114,000 UK Biobank participants |
Description | Additional file 1: Supplementary Tables S1-S11. |
Type Of Material | Database/Collection of data |
Year Produced | 2022 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_1_of_Role_of_circulating_polyun... |
Title | Additional file 2 of Association of the functional ovarian reserve with serum metabolomic profiling by nuclear magnetic resonance spectroscopy: a cross-sectional study of ~ 400 women |
Description | Additional file 2: Table S4. Adjusted associations of metabolites with AMH in original units. Table S5. Adjusted associations of metabolites with AFC in original units. |
Type Of Material | Database/Collection of data |
Year Produced | 2020 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_2_of_Association_of_the_functio... |
Title | Additional file 2 of Association of the functional ovarian reserve with serum metabolomic profiling by nuclear magnetic resonance spectroscopy: a cross-sectional study of ~ 400 women |
Description | Additional file 2: Table S4. Adjusted associations of metabolites with AMH in original units. Table S5. Adjusted associations of metabolites with AFC in original units. |
Type Of Material | Database/Collection of data |
Year Produced | 2020 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_2_of_Association_of_the_functio... |
Title | Additional file 2 of Identifying molecular mediators of the relationship between body mass index and endometrial cancer risk: a Mendelian randomization analysis |
Description | Additional file 2: Table S5. Information on genetic variants included as instruments for traits. |
Type Of Material | Database/Collection of data |
Year Produced | 2022 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_2_of_Identifying_molecular_medi... |
Title | Additional file 2 of Identifying molecular mediators of the relationship between body mass index and endometrial cancer risk: a Mendelian randomization analysis |
Description | Additional file 2: Table S5. Information on genetic variants included as instruments for traits. |
Type Of Material | Database/Collection of data |
Year Produced | 2022 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_2_of_Identifying_molecular_medi... |
Title | Additional file 2 of Identifying potential causal effects of age at menarche: a Mendelian randomization phenome-wide association study |
Description | Additional file 2. Analysis code. |
Type Of Material | Database/Collection of data |
Year Produced | 2020 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/Additional_file_2_of_Identifying_potential_causal_effec... |
Title | Additional file 2 of Identifying potential causal effects of age at menarche: a Mendelian randomization phenome-wide association study |
Description | Additional file 2. Analysis code. |
Type Of Material | Database/Collection of data |
Year Produced | 2020 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/Additional_file_2_of_Identifying_potential_causal_effec... |
Title | Additional file 3 of Characterisation of ethnic differences in DNA methylation between UK-resident South Asians and Europeans |
Description | Additional file 3. Table S1. EWAS results. |
Type Of Material | Database/Collection of data |
Year Produced | 2022 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_3_of_Characterisation_of_ethnic... |
Title | Additional file 3 of Characterisation of ethnic differences in DNA methylation between UK-resident South Asians and Europeans |
Description | Additional file 3. Table S1. EWAS results. |
Type Of Material | Database/Collection of data |
Year Produced | 2022 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_3_of_Characterisation_of_ethnic... |
Title | Additional file 3 of Identifying potential causal effects of age at menarche: a Mendelian randomization phenome-wide association study |
Description | Additional file 3:Table S1. Strength of the genetic instrument in predicting age at menarche in UK Biobank. Table S2. Findings from the main analysis of the genetic risk score for age at menarche. Table S3. Finding from the main analysis of the genetic risk score for age at menarche after additional adjustment for chip used for the genotyping. Table S4. Finding from the main analysis of the genetic risk score for age at menarche after Steiger filtering. Table S5. Findings from the sensitivity analysis of the genetic risk score for age at menarche excluding SNPs associated with childhood body-mass index. Table S6. Findings from the sensitivity analysis of the genetic risk score for age at menarche excluding SNPs associated with childhood and/or adult body-mass index. Table S7. MR-Egger intercept. Table S8. Results from MR-PRESSO global test for pleoitropy and distortion tests. Table S9. Strength of the genetic instrument in predicting age at menarche in ALSPAC. Table S10. Strength of the genetic instrument in predicting body-mass index and height in UK Biobank. Table S11. Findings from the multivariable mendelian randomization analysis further adjusting for body-mass index and height. Table S12. Post hoc power calculation analyses for the replication analyses. |
Type Of Material | Database/Collection of data |
Year Produced | 2020 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/Additional_file_3_of_Identifying_potential_causal_effec... |
Title | Additional file 3 of Identifying potential causal effects of age at menarche: a Mendelian randomization phenome-wide association study |
Description | Additional file 3:Table S1. Strength of the genetic instrument in predicting age at menarche in UK Biobank. Table S2. Findings from the main analysis of the genetic risk score for age at menarche. Table S3. Finding from the main analysis of the genetic risk score for age at menarche after additional adjustment for chip used for the genotyping. Table S4. Finding from the main analysis of the genetic risk score for age at menarche after Steiger filtering. Table S5. Findings from the sensitivity analysis of the genetic risk score for age at menarche excluding SNPs associated with childhood body-mass index. Table S6. Findings from the sensitivity analysis of the genetic risk score for age at menarche excluding SNPs associated with childhood and/or adult body-mass index. Table S7. MR-Egger intercept. Table S8. Results from MR-PRESSO global test for pleoitropy and distortion tests. Table S9. Strength of the genetic instrument in predicting age at menarche in ALSPAC. Table S10. Strength of the genetic instrument in predicting body-mass index and height in UK Biobank. Table S11. Findings from the multivariable mendelian randomization analysis further adjusting for body-mass index and height. Table S12. Post hoc power calculation analyses for the replication analyses. |
Type Of Material | Database/Collection of data |
Year Produced | 2020 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/Additional_file_3_of_Identifying_potential_causal_effec... |
Title | Additional file 4 of Characterisation of ethnic differences in DNA methylation between UK-resident South Asians and Europeans |
Description | Additional file 4. Table S2. DMR results. Table S3. Epigenetic age acceleration results. Table S4. Cell count differences. Table S5. Effects of adjustment for mQTL and allele frequency differences. Table S6. Effects of adjustment for mQTL and allele frequency differences. Table S7. ANNOVAR enrichment. Table S8. GO term enrichment. Table S9. LOLA enrichment. |
Type Of Material | Database/Collection of data |
Year Produced | 2022 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_4_of_Characterisation_of_ethnic... |
Title | Additional file 4 of Characterisation of ethnic differences in DNA methylation between UK-resident South Asians and Europeans |
Description | Additional file 4. Table S2. DMR results. Table S3. Epigenetic age acceleration results. Table S4. Cell count differences. Table S5. Effects of adjustment for mQTL and allele frequency differences. Table S6. Effects of adjustment for mQTL and allele frequency differences. Table S7. ANNOVAR enrichment. Table S8. GO term enrichment. Table S9. LOLA enrichment. |
Type Of Material | Database/Collection of data |
Year Produced | 2022 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_4_of_Characterisation_of_ethnic... |
Title | Ascertaining and classifying cases of congenital anomalies in the ALSPAC birth cohort |
Description | Provides details of how we have identified, coded and catalogued all cases of congenital anomalies in the initial children in the ALSPAC birth cohorts. Provides details of how to access and use these data - available to national and international researchers. |
Type Of Material | Database/Collection of data |
Year Produced | 2020 |
Provided To Others? | Yes |
Impact | Too early |
URL | https://wellcomeopenresearch.org/articles/5-231 |
Title | Metabolomics datasets in the Born in Bradford cohort |
Description | This provides full details of all of the metabolomics data in the Born in Bradford study including details of how researchers (national and international) can access and use these |
Type Of Material | Database/Collection of data |
Year Produced | 2020 |
Provided To Others? | Yes |
Impact | Too early for impact |
URL | https://wellcomeopenresearch.org/articles/5-264 |
Title | Supplement for Ulla Sovio, Neil Goulding, Nancy McBride, Emma Cook, Francesca Gaccioli, D. Stephen Charnock-Jones, Deborah A. Lawlor, Gordon C. S. Smith. A maternal serum metabolite ratio predicts large for gestational age infants at term: a... |
Description | Important : This dataset has been updated. Please go to https://doi.org/10.17863/CAM.76865 for the latest version This is a revised version of the original Supplement (https://doi.org/10.17863/CAM.54523). $$ \ $$ The Citation to this document according to the journal guidelines (https://academic.oup.com/jcem/pages/author_guidelines#extended_data) should read: Sovio U, Goulding N, McBride N, Cook E, Gaccioli F, Charnock-Jones DS, Lawlor DA, Smith GCS. Data from: A maternal serum metabolite ratio predicts large for gestational age infants at term: a prospective cohort study. Deposited 20 January 2021. https://doi.org/10.17863/CAM.63666 |
Type Of Material | Database/Collection of data |
Year Produced | 2021 |
Provided To Others? | Yes |
URL | https://www.repository.cam.ac.uk/handle/1810/316557 |
Title | Supplement for Ulla Sovio, Neil Goulding, Nancy McBride, Emma Cook, Francesca Gaccioli, D. Stephen Charnock-Jones, Deborah A. Lawlor, Gordon C. S. Smith. A maternal serum metabolite ratio predicts large for gestational age infants at term: a... |
Description | This is the current version of the Supplement which should be consulted (previous versions: https://doi.org/10.17863/CAM.54523 and https://doi.org/10.17863/CAM.63666). |
Type Of Material | Database/Collection of data |
Year Produced | 2021 |
Provided To Others? | Yes |
URL | https://www.repository.cam.ac.uk/handle/1810/329608 |
Title | The second generation of The Avon Longitudinal Study of Parents and Children (ALSPAC-G2): a cohort profile |
Description | Provides full details of the second generation of the ALSPAC cohort including how researchers can access and use these data |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
Impact | Increased use of dataset, including by international reearchers |
URL | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6971848/pdf/wellcomeopenres-4-17079.pdf |
Description | 4M consortium |
Organisation | Cardiff University |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Gemma Sharp established the Menarche, Menstruation, Menopause and Mental health (4M) consortium using funding from the GW4 Alliance (generator award: £14800). The consortium brings together researchers from different disciplines and institutions, with a shared interest in the intersection of menstrual and mental health. This includes researchers interested in using molecular epidemiological approaches to conduct research in this area. |
Collaborator Contribution | The 4M consortium includes partners from Bath, Cardiff and Exeter University, as well as external stakeholders from charities, patient groups, the NHS, government departments, and the United Nations Population Fund (UNFPA). |
Impact | We have run several workshops, including a three day in-person grant writing retreat. We have developed and submitted four grant applications for further funding. |
Start Year | 2021 |
Description | 4M consortium |
Organisation | GW4 |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Gemma Sharp established the Menarche, Menstruation, Menopause and Mental health (4M) consortium using funding from the GW4 Alliance (generator award: £14800). The consortium brings together researchers from different disciplines and institutions, with a shared interest in the intersection of menstrual and mental health. This includes researchers interested in using molecular epidemiological approaches to conduct research in this area. |
Collaborator Contribution | The 4M consortium includes partners from Bath, Cardiff and Exeter University, as well as external stakeholders from charities, patient groups, the NHS, government departments, and the United Nations Population Fund (UNFPA). |
Impact | We have run several workshops, including a three day in-person grant writing retreat. We have developed and submitted four grant applications for further funding. |
Start Year | 2021 |
Description | 4M consortium |
Organisation | University of Bath |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Gemma Sharp established the Menarche, Menstruation, Menopause and Mental health (4M) consortium using funding from the GW4 Alliance (generator award: £14800). The consortium brings together researchers from different disciplines and institutions, with a shared interest in the intersection of menstrual and mental health. This includes researchers interested in using molecular epidemiological approaches to conduct research in this area. |
Collaborator Contribution | The 4M consortium includes partners from Bath, Cardiff and Exeter University, as well as external stakeholders from charities, patient groups, the NHS, government departments, and the United Nations Population Fund (UNFPA). |
Impact | We have run several workshops, including a three day in-person grant writing retreat. We have developed and submitted four grant applications for further funding. |
Start Year | 2021 |
Description | 4M consortium |
Organisation | University of Exeter |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Gemma Sharp established the Menarche, Menstruation, Menopause and Mental health (4M) consortium using funding from the GW4 Alliance (generator award: £14800). The consortium brings together researchers from different disciplines and institutions, with a shared interest in the intersection of menstrual and mental health. This includes researchers interested in using molecular epidemiological approaches to conduct research in this area. |
Collaborator Contribution | The 4M consortium includes partners from Bath, Cardiff and Exeter University, as well as external stakeholders from charities, patient groups, the NHS, government departments, and the United Nations Population Fund (UNFPA). |
Impact | We have run several workshops, including a three day in-person grant writing retreat. We have developed and submitted four grant applications for further funding. |
Start Year | 2021 |
Description | AR- Health |
Organisation | National University of Singapore |
Country | Singapore |
Sector | Academic/University |
PI Contribution | We lead this collaboration which is establishing data sources and methods to determine the causal effects of different forms of medical Artificial Reproduction on Health (AR-Health). We have identified relevant studies, harmonised data across them and developed the appropriate methods for analysing these data. |
Collaborator Contribution | Partners are contributing data and expertise. |
Impact | The collaboration in multi-disciplinary, with expertise in epidemiology, biostatistics, data science, law, and clinicians from reproductive health, obstetrics and neonatology. This is a new collaboration and too new to have had impact or publication outputs yet. |
Start Year | 2020 |
Description | AR- Health |
Organisation | Norwegian Institute of Public Health |
Country | Norway |
Sector | Public |
PI Contribution | We lead this collaboration which is establishing data sources and methods to determine the causal effects of different forms of medical Artificial Reproduction on Health (AR-Health). We have identified relevant studies, harmonised data across them and developed the appropriate methods for analysing these data. |
Collaborator Contribution | Partners are contributing data and expertise. |
Impact | The collaboration in multi-disciplinary, with expertise in epidemiology, biostatistics, data science, law, and clinicians from reproductive health, obstetrics and neonatology. This is a new collaboration and too new to have had impact or publication outputs yet. |
Start Year | 2020 |
Description | AR- Health |
Organisation | University College Cork |
Country | Ireland |
Sector | Academic/University |
PI Contribution | We lead this collaboration which is establishing data sources and methods to determine the causal effects of different forms of medical Artificial Reproduction on Health (AR-Health). We have identified relevant studies, harmonised data across them and developed the appropriate methods for analysing these data. |
Collaborator Contribution | Partners are contributing data and expertise. |
Impact | The collaboration in multi-disciplinary, with expertise in epidemiology, biostatistics, data science, law, and clinicians from reproductive health, obstetrics and neonatology. This is a new collaboration and too new to have had impact or publication outputs yet. |
Start Year | 2020 |
Description | AR- Health |
Organisation | University of Amsterdam |
Country | Netherlands |
Sector | Academic/University |
PI Contribution | We lead this collaboration which is establishing data sources and methods to determine the causal effects of different forms of medical Artificial Reproduction on Health (AR-Health). We have identified relevant studies, harmonised data across them and developed the appropriate methods for analysing these data. |
Collaborator Contribution | Partners are contributing data and expertise. |
Impact | The collaboration in multi-disciplinary, with expertise in epidemiology, biostatistics, data science, law, and clinicians from reproductive health, obstetrics and neonatology. This is a new collaboration and too new to have had impact or publication outputs yet. |
Start Year | 2020 |
Description | AR- Health |
Organisation | University of Auckland |
Country | New Zealand |
Sector | Academic/University |
PI Contribution | We lead this collaboration which is establishing data sources and methods to determine the causal effects of different forms of medical Artificial Reproduction on Health (AR-Health). We have identified relevant studies, harmonised data across them and developed the appropriate methods for analysing these data. |
Collaborator Contribution | Partners are contributing data and expertise. |
Impact | The collaboration in multi-disciplinary, with expertise in epidemiology, biostatistics, data science, law, and clinicians from reproductive health, obstetrics and neonatology. This is a new collaboration and too new to have had impact or publication outputs yet. |
Start Year | 2020 |
Description | AR- Health |
Organisation | University of Copenhagen |
Country | Denmark |
Sector | Academic/University |
PI Contribution | We lead this collaboration which is establishing data sources and methods to determine the causal effects of different forms of medical Artificial Reproduction on Health (AR-Health). We have identified relevant studies, harmonised data across them and developed the appropriate methods for analysing these data. |
Collaborator Contribution | Partners are contributing data and expertise. |
Impact | The collaboration in multi-disciplinary, with expertise in epidemiology, biostatistics, data science, law, and clinicians from reproductive health, obstetrics and neonatology. This is a new collaboration and too new to have had impact or publication outputs yet. |
Start Year | 2020 |
Description | AR- Health |
Organisation | University of Paris |
Country | France |
Sector | Academic/University |
PI Contribution | We lead this collaboration which is establishing data sources and methods to determine the causal effects of different forms of medical Artificial Reproduction on Health (AR-Health). We have identified relevant studies, harmonised data across them and developed the appropriate methods for analysing these data. |
Collaborator Contribution | Partners are contributing data and expertise. |
Impact | The collaboration in multi-disciplinary, with expertise in epidemiology, biostatistics, data science, law, and clinicians from reproductive health, obstetrics and neonatology. This is a new collaboration and too new to have had impact or publication outputs yet. |
Start Year | 2020 |
Description | AR- Health |
Organisation | University of Southampton |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | We lead this collaboration which is establishing data sources and methods to determine the causal effects of different forms of medical Artificial Reproduction on Health (AR-Health). We have identified relevant studies, harmonised data across them and developed the appropriate methods for analysing these data. |
Collaborator Contribution | Partners are contributing data and expertise. |
Impact | The collaboration in multi-disciplinary, with expertise in epidemiology, biostatistics, data science, law, and clinicians from reproductive health, obstetrics and neonatology. This is a new collaboration and too new to have had impact or publication outputs yet. |
Start Year | 2020 |
Description | AR- Health |
Organisation | University of Turin |
Country | Italy |
Sector | Academic/University |
PI Contribution | We lead this collaboration which is establishing data sources and methods to determine the causal effects of different forms of medical Artificial Reproduction on Health (AR-Health). We have identified relevant studies, harmonised data across them and developed the appropriate methods for analysing these data. |
Collaborator Contribution | Partners are contributing data and expertise. |
Impact | The collaboration in multi-disciplinary, with expertise in epidemiology, biostatistics, data science, law, and clinicians from reproductive health, obstetrics and neonatology. This is a new collaboration and too new to have had impact or publication outputs yet. |
Start Year | 2020 |
Description | CHARGE consortium - Cross-platform metabolomics GWAS |
Organisation | Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium (CHARGE) |
Country | Global |
Sector | Academic/University |
PI Contribution | I am contributing to designing the study and analysing data. |
Collaborator Contribution | The CHARGE Metabolomics Working Group is responsible for planning, conducting and reporting this large ongoing collaborative effort. |
Impact | Meta-analysis of genome-wide association studies on human metabolome. This collaboration is multi-disciplinary, involving statisticians, genetic epidemiologists, epidemiologists and clinicians. |
Start Year | 2019 |
Description | Collaborations with Brazil |
Organisation | Federal University of Pelotas (UFPel) |
Country | Brazil |
Sector | Academic/University |
PI Contribution | In the partnership with UFPEL, I contributed with co-supervision of PhD student and revision and input on publications resulting from her work. In the partnership with FURG, I contributed with revision and input on publication. |
Collaborator Contribution | The collaborator at UFPEL is the main supervisor and contributed with daily supervision and leadership of the research. The collaborator at FURG is the principal investigator of the cohort and lead the research. |
Impact | • Gomes, Ana Paula, Bierhals, Isabel Oliveira, Vieira, Luna Strieder, Soares, Ana Luiza Gonçalves, Flores, Thaynã Ramos, Assunção, Maria Cecília Formoso, & Gonçalves, Helen. (2020). Padrões alimentares de idosos e seus determinantes: estudo de base populacional no sul do Brasil. Ciência & Saúde Coletiva, 25(6), 1999-2008. Epub June 03, 2020.https://doi.org/10.1590/1413-81232020256.20932018 • Loret de Mola, Christian, Blumenberg, Cauane, Martins, Rafaela C., Martins-Silva, Thais, Carpena, Marina X., Del-Ponte, Bianca, Pearson, Rebecca, Soares, Ana L., & Cesar, Juraci A.. (2021). Increased depression and anxiety during the COVID-19 pandemic in Brazilian mothers: a longitudinal study. Brazilian Journal of Psychiatry, Epub January 11, 2021.https://doi.org/10.1590/1516-4446-2020-1628 None of the collaborations is multidisciplinary, and most are focused in epidemiology. |
Start Year | 2016 |
Description | Collaborations with Brazil |
Organisation | Federal University of Rio Grande (FURG) |
Country | Brazil |
Sector | Academic/University |
PI Contribution | In the partnership with UFPEL, I contributed with co-supervision of PhD student and revision and input on publications resulting from her work. In the partnership with FURG, I contributed with revision and input on publication. |
Collaborator Contribution | The collaborator at UFPEL is the main supervisor and contributed with daily supervision and leadership of the research. The collaborator at FURG is the principal investigator of the cohort and lead the research. |
Impact | • Gomes, Ana Paula, Bierhals, Isabel Oliveira, Vieira, Luna Strieder, Soares, Ana Luiza Gonçalves, Flores, Thaynã Ramos, Assunção, Maria Cecília Formoso, & Gonçalves, Helen. (2020). Padrões alimentares de idosos e seus determinantes: estudo de base populacional no sul do Brasil. Ciência & Saúde Coletiva, 25(6), 1999-2008. Epub June 03, 2020.https://doi.org/10.1590/1413-81232020256.20932018 • Loret de Mola, Christian, Blumenberg, Cauane, Martins, Rafaela C., Martins-Silva, Thais, Carpena, Marina X., Del-Ponte, Bianca, Pearson, Rebecca, Soares, Ana L., & Cesar, Juraci A.. (2021). Increased depression and anxiety during the COVID-19 pandemic in Brazilian mothers: a longitudinal study. Brazilian Journal of Psychiatry, Epub January 11, 2021.https://doi.org/10.1590/1516-4446-2020-1628 None of the collaborations is multidisciplinary, and most are focused in epidemiology. |
Start Year | 2016 |
Description | Cross-cohort studies of GlycA and cardiometabolic phenotypes across the lifecourse |
Organisation | University of Melbourne |
Department | Faculty of Medicine, Dentistry & Health Sciences |
Country | Australia |
Sector | Academic/University |
PI Contribution | Neil Goulding performed a replication study in the ALSPAC cohort, investigating whether inflammatory glycoprotein acetyls are associated with vascular phenotypes in children and their parents. Deborah Lawlor helped write the paper. The other projects are at a preliminary stage. |
Collaborator Contribution | They performed the main analyses within their cohort for the 1st paper. |
Impact | 1 article is about to be submitted to a peer-review journal. |
Start Year | 2019 |
Description | Evans/Warrington Group (University of Queensland) |
Organisation | University of Queensland |
Country | Australia |
Sector | Academic/University |
PI Contribution | We are currently collaborating on 4 papers, which are expected to be submitted within 6 months. Tom Bond (postdoc in Lawlor group) is leading analyses and manuscript writing on these projects. Tom Bond is an associate advisor to a PhD student (Geng Wang) jointly supervised with Dave Evans and Nicole Warrington. |
Collaborator Contribution | Dave Evans, Nicole Warrington and their team members have provided methodological input to these projects |
Impact | Multi disciplinary- epidemiology, statistical genetics |
Start Year | 2020 |
Description | Imperial College London (Jarvelin Group) |
Organisation | Imperial College London |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | We are currently collaborating on 3 papers. Tom Bond (postdoc in Lawlor group) is leading analyses and manuscript writing on these projects |
Collaborator Contribution | Marjo-Riitta Jarvelin is providing intellectual input to these papers, and has provided access to datasets from the Northern Finland Birth Cohorts, Born in Bradford and Generation R studies (via data transfer agreements between these cohorts and Imperial College London) |
Impact | Not multi disciplinary |
Start Year | 2017 |
Description | Investigating the relationships between unfavorable habitual sleep and metabolomic traits: evidence from multi-cohort multivariable regression and Mendelian randomization analyses |
Organisation | Erasmus University Rotterdam |
Country | Netherlands |
Sector | Academic/University |
PI Contribution | I performed the Mendelian randomization analyses, made the figures for the paper and helped to write the article. Deborah Lawlor helped write the paper. |
Collaborator Contribution | They performed the multivariable regression analyses and helped to write the article. |
Impact | Yes |
Start Year | 2019 |
Description | Investigating the relationships between unfavorable habitual sleep and metabolomic traits: evidence from multi-cohort multivariable regression and Mendelian randomization analyses |
Organisation | Leiden University Medical Center |
Country | Netherlands |
Sector | Academic/University |
PI Contribution | I performed the Mendelian randomization analyses, made the figures for the paper and helped to write the article. Deborah Lawlor helped write the paper. |
Collaborator Contribution | They performed the multivariable regression analyses and helped to write the article. |
Impact | Yes |
Start Year | 2019 |
Description | Investigating the relationships between unfavorable habitual sleep and metabolomic traits: evidence from multi-cohort multivariable regression and Mendelian randomization analyses |
Organisation | University of Bristol |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | I performed the Mendelian randomization analyses, made the figures for the paper and helped to write the article. Deborah Lawlor helped write the paper. |
Collaborator Contribution | They performed the multivariable regression analyses and helped to write the article. |
Impact | Yes |
Start Year | 2019 |
Description | LifeCycle - IVF cohort |
Organisation | Barcelona Institute for Global Health |
Country | Spain |
Sector | Multiple |
PI Contribution | We are the central organisers of the collaboration. We draft analysis plans, share these with partners, undertake individual participant study analyses and meta-analyses of data across all studies. We will write the first draft of initial papers and redraft following in put from partners |
Collaborator Contribution | Partners: 1. Contribute to the development of analysis plans 2. Provide individual participant data or summary results 3. Contribute to drafting manuscripts |
Impact | Too early for outputs |
Start Year | 2018 |
Description | LifeCycle - IVF cohort |
Organisation | Bradford Teaching Hospitals NHS Foundation Trust |
Country | United Kingdom |
Sector | Public |
PI Contribution | We are the central organisers of the collaboration. We draft analysis plans, share these with partners, undertake individual participant study analyses and meta-analyses of data across all studies. We will write the first draft of initial papers and redraft following in put from partners |
Collaborator Contribution | Partners: 1. Contribute to the development of analysis plans 2. Provide individual participant data or summary results 3. Contribute to drafting manuscripts |
Impact | Too early for outputs |
Start Year | 2018 |
Description | LifeCycle - IVF cohort |
Organisation | Erasmus University Rotterdam |
Country | Netherlands |
Sector | Academic/University |
PI Contribution | We are the central organisers of the collaboration. We draft analysis plans, share these with partners, undertake individual participant study analyses and meta-analyses of data across all studies. We will write the first draft of initial papers and redraft following in put from partners |
Collaborator Contribution | Partners: 1. Contribute to the development of analysis plans 2. Provide individual participant data or summary results 3. Contribute to drafting manuscripts |
Impact | Too early for outputs |
Start Year | 2018 |
Description | LifeCycle - IVF cohort |
Organisation | Norwegian Institute of Public Health |
Country | Norway |
Sector | Public |
PI Contribution | We are the central organisers of the collaboration. We draft analysis plans, share these with partners, undertake individual participant study analyses and meta-analyses of data across all studies. We will write the first draft of initial papers and redraft following in put from partners |
Collaborator Contribution | Partners: 1. Contribute to the development of analysis plans 2. Provide individual participant data or summary results 3. Contribute to drafting manuscripts |
Impact | Too early for outputs |
Start Year | 2018 |
Description | LifeCycle - IVF cohort |
Organisation | University of Copenhagen |
Country | Denmark |
Sector | Academic/University |
PI Contribution | We are the central organisers of the collaboration. We draft analysis plans, share these with partners, undertake individual participant study analyses and meta-analyses of data across all studies. We will write the first draft of initial papers and redraft following in put from partners |
Collaborator Contribution | Partners: 1. Contribute to the development of analysis plans 2. Provide individual participant data or summary results 3. Contribute to drafting manuscripts |
Impact | Too early for outputs |
Start Year | 2018 |
Description | LifeCycle - IVF cohort |
Organisation | University of Groningen |
Country | Netherlands |
Sector | Academic/University |
PI Contribution | We are the central organisers of the collaboration. We draft analysis plans, share these with partners, undertake individual participant study analyses and meta-analyses of data across all studies. We will write the first draft of initial papers and redraft following in put from partners |
Collaborator Contribution | Partners: 1. Contribute to the development of analysis plans 2. Provide individual participant data or summary results 3. Contribute to drafting manuscripts |
Impact | Too early for outputs |
Start Year | 2018 |
Description | LifeCycle - IVF cohort |
Organisation | University of Southampton |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | We are the central organisers of the collaboration. We draft analysis plans, share these with partners, undertake individual participant study analyses and meta-analyses of data across all studies. We will write the first draft of initial papers and redraft following in put from partners |
Collaborator Contribution | Partners: 1. Contribute to the development of analysis plans 2. Provide individual participant data or summary results 3. Contribute to drafting manuscripts |
Impact | Too early for outputs |
Start Year | 2018 |
Description | LifeCycle - IVF cohort |
Organisation | University of Turin |
Country | Italy |
Sector | Academic/University |
PI Contribution | We are the central organisers of the collaboration. We draft analysis plans, share these with partners, undertake individual participant study analyses and meta-analyses of data across all studies. We will write the first draft of initial papers and redraft following in put from partners |
Collaborator Contribution | Partners: 1. Contribute to the development of analysis plans 2. Provide individual participant data or summary results 3. Contribute to drafting manuscripts |
Impact | Too early for outputs |
Start Year | 2018 |
Description | MR-PREG |
Organisation | Bradford Teaching Hospitals NHS Foundation Trust |
Country | United Kingdom |
Sector | Public |
PI Contribution | Our contributions are: 1. Draft analysis plans 2. Complete analyses 3. Draft papers 4. Support other partners to lead projects |
Collaborator Contribution | Partners contribute to: 1. Analysis plans. So far these have been initially written by my group but partners make important contributions to revising the first draft (before we begin analyses) and to any decisions about any revisions after analyses have started 2. Data provision and/or analyses. Participants provide individual participant data for analyses in Bristol and/or undertake analyses in their groups and provide summary results 3. Critical comments on drafted papers |
Impact | Analyses have been completed but no publications yet. |
Start Year | 2018 |
Description | MR-PREG |
Organisation | Harvard University |
Country | United States |
Sector | Academic/University |
PI Contribution | Our contributions are: 1. Draft analysis plans 2. Complete analyses 3. Draft papers 4. Support other partners to lead projects |
Collaborator Contribution | Partners contribute to: 1. Analysis plans. So far these have been initially written by my group but partners make important contributions to revising the first draft (before we begin analyses) and to any decisions about any revisions after analyses have started 2. Data provision and/or analyses. Participants provide individual participant data for analyses in Bristol and/or undertake analyses in their groups and provide summary results 3. Critical comments on drafted papers |
Impact | Analyses have been completed but no publications yet. |
Start Year | 2018 |
Description | MR-PREG |
Organisation | Imperial College London |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Our contributions are: 1. Draft analysis plans 2. Complete analyses 3. Draft papers 4. Support other partners to lead projects |
Collaborator Contribution | Partners contribute to: 1. Analysis plans. So far these have been initially written by my group but partners make important contributions to revising the first draft (before we begin analyses) and to any decisions about any revisions after analyses have started 2. Data provision and/or analyses. Participants provide individual participant data for analyses in Bristol and/or undertake analyses in their groups and provide summary results 3. Critical comments on drafted papers |
Impact | Analyses have been completed but no publications yet. |
Start Year | 2018 |
Description | MR-PREG |
Organisation | Norwegian Institute of Public Health |
Country | Norway |
Sector | Public |
PI Contribution | Our contributions are: 1. Draft analysis plans 2. Complete analyses 3. Draft papers 4. Support other partners to lead projects |
Collaborator Contribution | Partners contribute to: 1. Analysis plans. So far these have been initially written by my group but partners make important contributions to revising the first draft (before we begin analyses) and to any decisions about any revisions after analyses have started 2. Data provision and/or analyses. Participants provide individual participant data for analyses in Bristol and/or undertake analyses in their groups and provide summary results 3. Critical comments on drafted papers |
Impact | Analyses have been completed but no publications yet. |
Start Year | 2018 |
Description | MR-PREG |
Organisation | University of Copenhagen |
Country | Denmark |
Sector | Academic/University |
PI Contribution | Our contributions are: 1. Draft analysis plans 2. Complete analyses 3. Draft papers 4. Support other partners to lead projects |
Collaborator Contribution | Partners contribute to: 1. Analysis plans. So far these have been initially written by my group but partners make important contributions to revising the first draft (before we begin analyses) and to any decisions about any revisions after analyses have started 2. Data provision and/or analyses. Participants provide individual participant data for analyses in Bristol and/or undertake analyses in their groups and provide summary results 3. Critical comments on drafted papers |
Impact | Analyses have been completed but no publications yet. |
Start Year | 2018 |
Description | MR-PREG |
Organisation | University of Oulu |
Country | Finland |
Sector | Academic/University |
PI Contribution | Our contributions are: 1. Draft analysis plans 2. Complete analyses 3. Draft papers 4. Support other partners to lead projects |
Collaborator Contribution | Partners contribute to: 1. Analysis plans. So far these have been initially written by my group but partners make important contributions to revising the first draft (before we begin analyses) and to any decisions about any revisions after analyses have started 2. Data provision and/or analyses. Participants provide individual participant data for analyses in Bristol and/or undertake analyses in their groups and provide summary results 3. Critical comments on drafted papers |
Impact | Analyses have been completed but no publications yet. |
Start Year | 2018 |
Description | Metabolic profiling to identify potential targets which may influence IVF outcome |
Organisation | University of Glasgow |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Amy Taylor and Deborah Lawlor helped write the analysis plans. I completed statistical analyses that were started by Amy Taylor before she went on maternity leave. I made the figures for the papers and helped to write the articles. Deborah Lawlor helped write the papers. |
Collaborator Contribution | They set up the IVF cohort and helped to write the articles. |
Impact | 2 articles have been published: Al Rashid, K., Taylor, A., Lumsden, M.A., Goulding, N. J., Lawlor, D. A., Nelson, S. Association of the functional ovarian reserve with serum metabolomic profiling by nuclear magnetic resonance spectroscopy: a cross-sectional study of ~ 400 women. BMC Med 18, 247 (2020). https://doi.org/10.1186/s12916-020-01700-z Al Rashid, K., Taylor, A., Lumsden, M.A., Goulding, N. J., Lawlor, D. A., Nelson, S. Association of the serum metabolomic profile by nuclear magnetic resonance spectroscopy with sperm parameters: a cross-sectional study of 325 men. F&S Science 1, 2 (2020). https://doi.org/10.1016/j.xfss.2020.10.003. 2 further papers have been submitted to peer-review journals |
Start Year | 2017 |
Description | Metabolomic biomarkers for fetal growth |
Organisation | University of Cambridge |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Neil Goulding, Nancy McBride and Gemma Clayton performed several replication studies in the Born in Bradford cohort. Deborah Lawlor helped write the papers. |
Collaborator Contribution | They performed the main analyses within their POP cohort and they wrote the papers. |
Impact | 1 article has been published for which I have worked on: Sovio, U., Goulding, N., McBride, N. et al. A maternal serum metabolite ratio predicts fetal growth restriction at term. Nat Med 26, 348-353 (2020). https://doi.org/10.1038/s41591-020-0804-9 1 further paper is about to be submitted to a peer-review journal that I have personally been involved with. Nancy McBride has other articles published as a result of this collaboration and Gemma Clayton is currently working on another project as part of this collaboration. |
Start Year | 2018 |
Description | NTNU Trondheim |
Organisation | Norwegian University of Science and Technology (NTNU) |
Department | Department of Public Health and Nursing |
Country | Norway |
Sector | Academic/University |
PI Contribution | We are currently collaborating on 1 paper, with further papers expected to be submitted within 1 year. Tom Bond (postdoc in Lawlor group) is leading analyses and manuscript writing on these projects. |
Collaborator Contribution | Ben Brumpton, Bjorn-Olav Asvold and Laxmi Bhatta are running analyses in the HUNT cohort |
Impact | Multi disciplinary- epidemiology, clinical medicine |
Start Year | 2020 |
Description | Replication studies for CHARGE Metabolomics and COMETS consortia |
Organisation | University of Bristol |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Neil Goulding performed the following replication studies in the ALSPAC and/or Born in Bradford (BiB) cohort: a) 2 separate projects investigating associations between metabolites and blood pressure (one using data from ALSPAC parents (for CHARGE) and one using data from parents and young adults in ALSPAC and pregnant mothers in BiB (COMETS)) (b) Investigating associations between metabolites and liver function using data from ALSPAC young adults (CHARGE). Carolina Borges and Neil Goulding also performed a metabolomics GWAS in ALSPAC parents for CHARGE metabolomics. |
Collaborator Contribution | They performed the same analyses within their own cohorts. |
Impact | Full details of each should be reported under the relevant sections of the form. Articles will be submitted to peer-review journals, for which we will be co-authors. |
Start Year | 2019 |
Description | UCLEB |
Organisation | London School of Hygiene and Tropical Medicine (LSHTM) |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | One of the key partners Collaboration is concerned with the use of genetics in risk prediction and aetiology (Mendelian randomization) of cardiometabolic disease. Includes the use of metabolomics |
Collaborator Contribution | As above |
Impact | Large number of publications - See CV |
Start Year | 2007 |
Description | UCLEB |
Organisation | University of Edinburgh |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | One of the key partners Collaboration is concerned with the use of genetics in risk prediction and aetiology (Mendelian randomization) of cardiometabolic disease. Includes the use of metabolomics |
Collaborator Contribution | As above |
Impact | Large number of publications - See CV |
Start Year | 2007 |
Description | UPBEAT RCT |
Organisation | King's College London |
Department | Women's Health Academic Centre |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | I am a co-applicant on a recently obtained MRC grant related to adding metabolomics data to this RCT I will lead analyses of this RCT and the LIMIT RCT (see other entry) in relation to long term mother and offspring outcomes in particular adiposity and metabolomics outcomes. |
Collaborator Contribution | See entry for LIMIT RCT collaboration |
Impact | Successful grant Poston L, Lawlor DA, Nelson SM, Sattar N. The UPBEAT RCT mother-child study. Stratifying and treating obese pregnant women to prevent adverse pregnancy, perinatal and longer term outcomes. MRC £825, 398: February 2014 for 48 months Published book chapter: Fraser A, Lawlor DA. Long-term consequences of maternal obesity and gestational weight gain for offspring obesity and cardiovascular risk - intrauterine or shared familial mechanisms? In: Poston L, Gillman M (eds). Obesity and Pregnancy. Cambridge Press. 2012 |
Start Year | 2012 |
Description | Developmental origins offspring adiposity |
Form Of Engagement Activity | A press release, press conference or response to a media enquiry/interview |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Public/other audiences |
Results and Impact | Press release of research on the developmental origins of offspring adiposity, which gained international coverage in coventional media via large network of international scientists involved with the research. Was also re-twetted a lot. |
Year(s) Of Engagement Activity | 2022 |
Description | Discussing COVID-19 research with children in schools- Louise Millard |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Schools |
Results and Impact | IEU researchers have led online epidemiology sessions for students at two Bristol primary schools. Having outlined their own research, IEU researchers led the 11-year olds in devising their own epidemiology research questions about COVID-19 or the effects of the lockdown. Their questions included: Can eating chillies help prevent COVID-19? Can alcohol make COVID-19 worse? and Do people sleep more, less or the same in lockdown? The students then worked out how researchers might collect and process data to help them to work out the answers to their questions. Through so doing, they considered the challenges of working with incomplete data in rapid-response epidemiology. They also engaged with ideas of causality and the responsible communication of research findings. The 11-year olds greatly enjoyed the sessions, saying, "I enjoyed this experience because I learnt a lot about the process of how scientists study" and "It was good to meet scientists - I was inspired. |
Year(s) Of Engagement Activity | 2020 |
Description | I'm a scientist get me out of here |
Form Of Engagement Activity | Engagement focused website, blog or social media channel |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Schools |
Results and Impact | Organised by MRC Public Engagement about Science and a career in science |
Year(s) Of Engagement Activity | 2020 |
URL | https://www2.mrc-lmb.cam.ac.uk/news-and-events/public-engagement/supporting-education/im-a-scientist... |
Description | Meet the Scientist - Annie Herbert |
Form Of Engagement Activity | Engagement focused website, blog or social media channel |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Schools |
Results and Impact | Organised but University of Bristol Explaining what epidemiology was and how it helped understanding all aspects of COVID |
Year(s) Of Engagement Activity | 2020 |
Description | Neonatal Society Autumn Meeting (5th November 2020)- Neil Golding |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Several postgraduate and postdoctoral researchers from the University of Bristol (as well as other universities) presented their work at this meeting, which sparked questions and discussion afterwards. |
Year(s) Of Engagement Activity | 2020 |
URL | https://www.neonatalsociety.ac.uk/wp-content/uploads/2020/10/The_Neonatal_Society_Abstracts_Nov-2020... |
Description | Pilot study with 'We the Curious' and public scientific museum |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Public/other audiences |
Results and Impact | We the curious is a science museum in Bristol. We are doing a pilot project with them that will enable us to determine the youngest age (in children) at which it is feasible to capture data on capillary glycocalix through an imaging technology. The data assessment requires a probe to be placed under the child's tongue for 7-10 minutes to capture sufficient image data. We worked with We the Curious to agree the recruitment and data collection protocol. Older children / young adults (14-19 year old) will collect data and with our support do analyses. The results will provide the answer we need and all data will be destroyed once analyses are completed. We will use the results to decide the age groups in ALSPAC G2 and in other cohorts (e.g. in Bradford) in which we will collect these data. We the curious are keen to work on other projects with us and to build stronger links with the University for mutual benefit with respect to public engagement and involvement. This current project is the first project with them. Hopefully, it will lead to many further projects. |
Year(s) Of Engagement Activity | 2020 |
Description | Press release - childhood maltreatment and cardiovascular disease- Ana Soares |
Form Of Engagement Activity | A press release, press conference or response to a media enquiry/interview |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Media (as a channel to the public) |
Results and Impact | Sex differences in the association between childhood maltreatment and cardiovascular disease in the UK Biobank". This provided a wider reach of the research to the general public. |
Year(s) Of Engagement Activity | 2020 |
URL | http://www.bristol.ac.uk/news/2020/july/heart-study.html |
Description | Press release on smoking and congenital heart disease |
Form Of Engagement Activity | A press release, press conference or response to a media enquiry/interview |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Public/other audiences |
Results and Impact | Press release and interviews covered in national papers, TV and local radio and TV. Research led by BHF Student showing potential effect of maternal smoking in pregnancy on congenital heart disease |
Year(s) Of Engagement Activity | 2021 |
Description | Published a paper on environmental data collection in ALSPAC birth cohort with two ALSPAC participants as co-authors |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | This was a unique experience of real participant/public involvement - working with two of the study participants to document all of the environmental and social data in ALSPAC, priorities for new data and methods for collecting these. The participant co-authors contributed to all aspects of the paper, including describing the methods for collecting data (including burden on them) for existing data, advising on what they would consider key priorities for future data collection and the best methods for collecting those data. Publication is Boyd A, Thomas R, Hansell AL, Gulliver J, Hicks LM, Griggs R, Hey JV, Taylor CM, Morris T, Golding J, Doerner R, Fecht D, Henderson J, Lawlor DA, Timpson NJ, Macleod J, Data Resource Profile: The ALSPAC birth cohort as a platform to study the relationship of environment and health and social factors International Journal of Epidemiology 2019; doi: 10.1093/ije/dyz063 This experience forms a blueprint for further co-production research with other cohort participants |
Year(s) Of Engagement Activity | 2019 |
URL | https://academic.oup.com/ije/article/48/4/1038/5475780 |
Description | You-tube video describing the Avon Longitudinal Study of Parents and Children - Generation 2 cohort and its contribution to research |
Form Of Engagement Activity | A broadcast e.g. TV/radio/film/podcast (other than news/press) |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Media (as a channel to the public) |
Results and Impact | I produced a you-tube video with ALSPAC study participants and staff who collect data in ALSPAC, to inform a wide range of people about the value of the multi-generational ALSPAC study and the research it has contributed to. We also promoted the importance of population health studies such as ALSPAC in general. The video can be found here https://www.youtube.com/watch?v=sQtnmCNgmXI |
Year(s) Of Engagement Activity | 2019 |
URL | https://www.youtube.com/watch?v=sQtnmCNgmXI |