All thresholds of maternal hyperglycaemia from the WHO 2013 criteria for gestational diabetes identify women with a higher genetic risk for type 2 diabetes

This is the final version. Available from F1000Research via the DOI in this record.Data availability Underlying data Data is not freely available due to it consisting of potentially identifiable information, and as such is held securely to protect the interests of research participants in line with the guidance from the relevant ethics committees. However, the ethics committees will allow data analysed and generated in this study to be available to researchers through open collaboration. For access to the data used in this study please contact Dr Rachel Freathy ([email protected]) and Professor William Lowe Jr ([email protected]) in relation to HAPO and Dr Rachel Freathy and Professor Fidelma Dunne ([email protected]) in relation to Atlantic DIP. Requests will be reviewed as soon as possible on receipt and will be facilitated with an agreement to ensure that data is transferred and held securely and results of new analyses shared with the relevant study investigators. The websites describing the studies and other data available are https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000096.v4.p1 for HAPO and http://atlanticdipireland.com/for Atlantic DIP. Extended data Figshare: Extended data Wellcome Open Research 16097.pdf. https://doi.org/10.6084/m9.figshare.14180033 The file contains an extended data table with sensitivity analyses adjusting the genetic scores for maternal pre-pregnancy BMI and age and a figure with a directed acyclic graph (DAG) showing how the relationships between the genetic scores and GDM diagnostic category are not driven by maternal pre-pregnancy BMI or age.Background: Using genetic scores for fasting plasma glucose (FPG GS) and type 2 diabetes (T2D GS), we investigated whether the fasting, 1-hour and 2-hour glucose thresholds from the WHO 2013 criteria for gestational diabetes (GDM) have different implications for genetic susceptibility to raised fasting glucose and type 2 diabetes in women from the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) and Atlantic Diabetes in Pregnancy (DIP) studies. Methods: Cases were divided into three subgroups: (i) FPG ≥5.1 mmol/L only, n=222; (ii) 1-hour glucose post 75 g oral glucose load ≥10 mmol/L only, n=154 (iii) 2-hour glucose ≥8.5 mmol/L only, n=73; and (iv) both FPG ≥5.1 mmol/L and either of a 1-hour glucose ≥10 mmol/L or 2-hour glucose ≥8.5 mmol/L, n=172. We compared the FPG and T2D GS of these groups with controls (n=3,091) in HAPO and DIP separately. Results: In HAPO and DIP, the mean FPG GS in women with a FPG ≥5.1 mmol/L, either on its own or with 1-hour glucose ≥10 mmol/L or 2-hour glucose ≥8.5 mmol/L, was higher than controls (all P <0.01). Mean T2D GS in women with a raised FPG alone or with either a raised 1-hour or 2-hour glucose was higher than controls (all P <0.05). GDM defined by 1-hour or 2-hour hyperglycaemia only was also associated with a higher T2D GS than controls (all P <0.05). Conclusions: The different diagnostic categories that are part of the WHO 2013 criteria for GDM identify women with a genetic predisposition to type 2 diabetes as well as a risk for adverse pregnancy outcomes.Wellcome TrustNational Institute for Health ResearchEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Human Genome Research InstituteNational Institute of Diabetes and Digestive and Kidney DiseasesAmerican Diabetes AssociationIreland Health Research Boar

Associations between a fetal imprinted gene allele score and late pregnancy maternal glucose concentrations

$\textbf{Aim}$ We hypothesised that some of the genetic risk for gestational diabetes (GDM) is due to the fetal genome affecting maternal glucose concentrations. Previously, we found associations between fetal IGF2 gene variants and maternal glucose concentrations in late pregnancy. $\textbf{Methods}$ In the present study, we tested associations between SNP alleles from 15 fetal imprinted genes and maternal glucose concentrations in late pregnancy in the Cambridge Baby Growth and Wellbeing cohorts (1160 DNA trios). $\textbf{Results}$ Four fetal SNP alleles with the strongest univariate associations: paternally-transmitted IGF2 rs10770125 (P-value = 2 × 10$^{-4}$) and INS rs2585 (P-value = 7 × 10$^{-4}$), and maternally-transmitted KCNQ1(OT1) rs231841 (P-value = 1 × 10$^{-3}$) and KCNQ1(OT1) rs7929804 (P-value = 4 × 10$^{-3}$), were used to construct a composite fetal imprinted gene allele score which was associated with maternal glucose concentrations (P-value = 4.3 × 10$^{-6}$, n = 981, r$^{2}$ = 2.0%) and GDM prevalence (odds ratio per allele 1.44 (1.15, 1.80), P-value = 1 × 10$^{-3}$, n = 89 cases and 899 controls). Meta-analysis of the associations including data from 1367 Hyperglycaemia and Adverse Pregnancy Outcome Study participants confirmed the paternally-transmitted fetal IGF2/INS SNP associations (rs10770125, P-value = 3.2 × 10$^{-8}$, rs2585, P-value = 3.6 × 10$^{-5}$) and the composite fetal imprinted gene allele score association (P-value = 1.3 × 10$^{-8}$), but not the maternally-transmitted fetal KCNQ1(OT1) associations (rs231841, P-value = 0.4; rs7929804, P-value = 0.2). $\textbf{Conclusion}$ This study suggests that polymorphic variation in fetal imprinted genes, particularly in the IGF2/INS region, contribute a small but significant part to the risk of raised late pregnancy maternal glucose concentrations.This work was supported by the Evelyn Trust (grant number EW9035322); Diabetes UK (grant number 11/0004241); the Wellbeing of Women (the Royal College of Obstetricians and Gynaecologists, UK) (grant number RG1644); the Medical Research Council (grant number 7500001180); European Union Framework 5 (grant number QLK4-1999-01422); the Mothercare Charitable Foundation (grant number RG54608); Newlife Foundation for Disabled Children (grant number 07/20); the World Cancer Research Fund International (grant number 2004/03); and the National Institute for Health Research Cambridge Biomedical Research Centre. The HAPO Study work was supported by the National Institutes of Health (grant numbers HD-34242, HD-34243, HG-004415, and CA-141688); the Institutes of Health Research–INMD (grant number 110791); and by the American Diabetes Association

Higher maternal adiposity reduces offspring birthweight if associated with a metabolically favourable profile

This is the final version. Available on open access from Springer via the DOI in this recordData availability: The data for the genome-wide association studies (GWAS) of BMI are available at https://portals.broadinstitute.org/collaboration/giant/index.php/GIANT_consortium_data_files. The data for the GWAS of body fat percentage are available at https://walker05.u.hpc.mssm.edu.Aims/hypothesis Higher maternal BMI during pregnancy is associated with higher offspring birthweight, but it is not known whether this is solely the result of adverse metabolic consequences of higher maternal adiposity, such as maternal insulin resistance and fetal exposure to higher glucose levels, or whether there is any effect of raised adiposity through non-metabolic (e.g. mechanical) factors. We aimed to use genetic variants known to predispose to higher adiposity, coupled with a favourable metabolic profile, in a Mendelian randomisation (MR) study comparing the effect of maternal ‘metabolically favourable adiposity’ on offspring birthweight with the effect of maternal general adiposity (as indexed by BMI). Methods To test the causal effects of maternal metabolically favourable adiposity or general adiposity on offspring birthweight, we performed two-sample MR. We used variants identified in large, published genetic-association studies as being associated with either higher adiposity and a favourable metabolic profile, or higher BMI (n = 442,278 and n = 322,154 for metabolically favourable adiposity and BMI, respectively). We then extracted data on the metabolically favourable adiposity and BMI variants from a large, published genetic-association study of maternal genotype and offspring birthweight controlling for fetal genetic effects (n = 406,063 with maternal and/or fetal genotype effect estimates). We used several sensitivity analyses to test the reliability of the results. As secondary analyses, we used data from four cohorts (total n = 9323 mother–child pairs) to test the effects of maternal metabolically favourable adiposity or BMI on maternal gestational glucose, anthropometric components of birthweight and cord-blood biomarkers. Results Higher maternal adiposity with a favourable metabolic profile was associated with lower offspring birthweight (−94 [95% CI −150, −38] g per 1 SD [6.5%] higher maternal metabolically favourable adiposity, p = 0.001). By contrast, higher maternal BMI was associated with higher offspring birthweight (35 [95% CI 16, 53] g per 1 SD [4 kg/m2] higher maternal BMI, p = 0.0002). Sensitivity analyses were broadly consistent with the main results. There was evidence of outlier SNPs for both exposures; their removal slightly strengthened the metabolically favourable adiposity estimate and made no difference to the BMI estimate. Our secondary analyses found evidence to suggest that a higher maternal metabolically favourable adiposity decreases pregnancy fasting glucose levels while a higher maternal BMI increases them. The effects on neonatal anthropometric traits were consistent with the overall effect on birthweight but the smaller sample sizes for these analyses meant that the effects were imprecisely estimated. We also found evidence to suggest that higher maternal metabolically favourable adiposity decreases cord-blood leptin while higher maternal BMI increases it. Conclusions/interpretation Our results show that higher adiposity in mothers does not necessarily lead to higher offspring birthweight. Higher maternal adiposity can lead to lower offspring birthweight if accompanied by a favourable metabolic profile.National Institutes of Health (NIH)European Union FP7British Heart FoundationNational Institute for Health Research (NIHR)Medical Research Council (MRC)Wellcome TrustUniversity of Bristo

Fetal alleles predisposing to metabolically favourable adiposity are associated with higher birth weight

This is the final version. Available on open access from Oxford University Press via the DOI in this record Data Availability: Our study used both published summary results (i.e. taking results from published research papers and websites) and individual participant cohort data as follows: The data for the GWAS of BMI is available here. https://portals.broadinstitute.org/collaboration/giant/index.php/GIANT_consortium_data_files The data for the GWAS of body fat percentage is available here. https://walker05.u.hpc.mssm.edu The data for the GWAS of birth weight is available here. https://egg-consortium.org/birth-weight-2019.htm The references to those published data sources are provided in the main paper. We used individual participant data for the genetic association analyses from the UK Biobank, ALSPAC, BiB, EFSOCH and HAPO cohorts. The data in UK Biobank, ALSPAC and BiB are fully available, via managed systems, to any researchers. The managed system for both studies is a requirement of the study funders but access is not restricted on the basis of overlap with other applications to use the data or on the basis of peer review of the proposed science. UK Biobank. Full information on how to access these data can be found here - https://www.ukbiobank.ac.uk/using-the-resource/ ALSPAC. The ALSPAC data management plan (http://www.bristol.ac.uk/alspac/researchers/data-access/documents/alspac-data-managementplan.pdf ) describes in detail the policy regarding data sharing, which is through a system of managed open access. The steps below highlight how to apply for access to the data included in this paper and all other ALSPAC data. 27 1. Please read the ALSPAC access policy (PDF, 627kB) which describes the process of accessing the data and samples in detail, and outlines the costs associated with doing so. 2. You may also find it useful to browse the fully searchable ALSPAC research proposals database, which lists all research projects that have been approved since April 2011. 3. Please submit your research proposal for consideration by the ALSPAC Executive Committee. You will receive a response within 10 working days to advise you whether your proposal has been approved. If you have any questions about accessing data, please email [email protected]. BiB. Full information on how to access these data can be found here - https://borninbradford.nhs.uk/research/how-to-access-data/ HAPO. For access to the data used in this study, please contact Dr. Rachel Freathy ([email protected]) and Prof. William Lowe Jr ([email protected]). The website describing the study and other data available is https://www.ncbi.nlm.nih.gov/projects/gap/cgibin/study.cgi?study_id=phs000096.v4.p1 If you have further questions, please email Dr William Lowe at [email protected] EFSOCH. Requests for access to the original EFSOCH dataset should be made in writing in the first instance to the EFSOCH data team via the Exeter Clinical Research Facility [email protected]: Higher birthweight is associated with higher adult BMI. Alleles that predispose to greater adult adiposity might act in fetal life to increase fetal growth and birthweight. Whether there are fetal effects of recently identified adult metabolically favourable adiposity alleles on birthweight is unknown. Aim We aimed to test the effect on birthweight of fetal genetic predisposition to higher metabolically favourable adult adiposity and compare that with the effect of fetal genetic predisposition to higher adult BMI. METHODS: We used published GWAS data (n = upto 406 063) to estimate fetal effects on birthweight (adjusting for maternal genotype) of alleles known to raise metabolically favourable adult adiposity or BMI. We combined summary data across SNPs with random effects meta-analyses. We performed weighted linear regression of SNP-birthweight effects against SNP-adult adiposity effects to test for a dose-dependent association. RESULTS: Fetal genetic predisposition to higher metabolically favourable adult adiposity and higher adult BMI were both associated with higher birthweight (3grams per effect allele (95%CI, 1 to 5) averaged over 14 SNPs; p = 0.002; 0.5grams per effect allele (95%CI, 0 to 1) averaged over 76 SNPs; p = 0.042, respectively). SNPs with greater effects on metabolically favourable adiposity tended to have greater effects on birthweight (R2 = 0.2912, p = 0.027). There was no dose-dependent association for BMI (R2 = -0.0019, p = 0.602). CONCLUSIONS: Fetal genetic predisposition to both higher adult metabolically favourable adiposity and BMI is associated with birthweight. Fetal effects of metabolically favourable adiposity-raising alleles on birthweight are modestly proportional to their effects on future adiposity, but those of BMI-raising alleles are not.US National Institute of HealthEuropean Research Council (ERC)British Heart Foundatio

Fetal alleles predisposing to metabolically favourable adiposity are associated with higher birth weight

This is the final version. Available on open access from Oxford University Press via the DOI in this record Data Availability: Our study used both published summary results (i.e. taking results from published research papers and websites) and individual participant cohort data as follows: The data for the GWAS of BMI is available here. https://portals.broadinstitute.org/collaboration/giant/index.php/GIANT_consortium_data_files The data for the GWAS of body fat percentage is available here. https://walker05.u.hpc.mssm.edu The data for the GWAS of birth weight is available here. https://egg-consortium.org/birth-weight-2019.htm The references to those published data sources are provided in the main paper. We used individual participant data for the genetic association analyses from the UK Biobank, ALSPAC, BiB, EFSOCH and HAPO cohorts. The data in UK Biobank, ALSPAC and BiB are fully available, via managed systems, to any researchers. The managed system for both studies is a requirement of the study funders but access is not restricted on the basis of overlap with other applications to use the data or on the basis of peer review of the proposed science. UK Biobank. Full information on how to access these data can be found here - https://www.ukbiobank.ac.uk/using-the-resource/ ALSPAC. The ALSPAC data management plan (http://www.bristol.ac.uk/alspac/researchers/data-access/documents/alspac-data-managementplan.pdf ) describes in detail the policy regarding data sharing, which is through a system of managed open access. The steps below highlight how to apply for access to the data included in this paper and all other ALSPAC data. 27 1. Please read the ALSPAC access policy (PDF, 627kB) which describes the process of accessing the data and samples in detail, and outlines the costs associated with doing so. 2. You may also find it useful to browse the fully searchable ALSPAC research proposals database, which lists all research projects that have been approved since April 2011. 3. Please submit your research proposal for consideration by the ALSPAC Executive Committee. You will receive a response within 10 working days to advise you whether your proposal has been approved. If you have any questions about accessing data, please email [email protected]. BiB. Full information on how to access these data can be found here - https://borninbradford.nhs.uk/research/how-to-access-data/ HAPO. For access to the data used in this study, please contact Dr. Rachel Freathy ([email protected]) and Prof. William Lowe Jr ([email protected]). The website describing the study and other data available is https://www.ncbi.nlm.nih.gov/projects/gap/cgibin/study.cgi?study_id=phs000096.v4.p1 If you have further questions, please email Dr William Lowe at [email protected] EFSOCH. Requests for access to the original EFSOCH dataset should be made in writing in the first instance to the EFSOCH data team via the Exeter Clinical Research Facility [email protected]: Higher birthweight is associated with higher adult BMI. Alleles that predispose to greater adult adiposity might act in fetal life to increase fetal growth and birthweight. Whether there are fetal effects of recently identified adult metabolically favourable adiposity alleles on birthweight is unknown. Aim We aimed to test the effect on birthweight of fetal genetic predisposition to higher metabolically favourable adult adiposity and compare that with the effect of fetal genetic predisposition to higher adult BMI. METHODS: We used published GWAS data (n = upto 406 063) to estimate fetal effects on birthweight (adjusting for maternal genotype) of alleles known to raise metabolically favourable adult adiposity or BMI. We combined summary data across SNPs with random effects meta-analyses. We performed weighted linear regression of SNP-birthweight effects against SNP-adult adiposity effects to test for a dose-dependent association. RESULTS: Fetal genetic predisposition to higher metabolically favourable adult adiposity and higher adult BMI were both associated with higher birthweight (3grams per effect allele (95%CI, 1 to 5) averaged over 14 SNPs; p = 0.002; 0.5grams per effect allele (95%CI, 0 to 1) averaged over 76 SNPs; p = 0.042, respectively). SNPs with greater effects on metabolically favourable adiposity tended to have greater effects on birthweight (R2 = 0.2912, p = 0.027). There was no dose-dependent association for BMI (R2 = -0.0019, p = 0.602). CONCLUSIONS: Fetal genetic predisposition to both higher adult metabolically favourable adiposity and BMI is associated with birthweight. Fetal effects of metabolically favourable adiposity-raising alleles on birthweight are modestly proportional to their effects on future adiposity, but those of BMI-raising alleles are not.US National Institute of HealthEuropean Research Council (ERC)British Heart Foundatio

The impact of corporate social responsibility disclosure on financial performance : evidence from the GCC Islamic banking sector.

This paper examines the relationship between corporate social responsibility (CSR) and financial performance for Islamic banks in the Gulf Cooperation Council (GCC) region over the period 2000–2014 by generating CSR-related data through disclosure analysis of the annual reports of the sampled banks. The findings of this study indicate that there is a significant positive relationship between CSR disclosure and the financial performance of Islamic banks in the GCC countries. The results also show a positive relationship between CSR disclosure and the future financial performance of GCC Islamic banks, potentially indicating that current CSR activities carried out by Islamic banks in the GCC could have a long-term impact on their financial performance. Furthermore, despite demonstrating a significant positive relationship between the composite measure of the CSR disclosure index and financial performance, the findings show no statistically significant relationship between the individual dimensions of the CSR disclosure index and the current financial performance measure except for ‘mission and vision’ and ‘products and services’. Similarly, the empirical results detect a positive significant association only between ‘mission and vision’ dimension and future financial performance of the examined banks

Integrating multiple lines of evidence to assess the effects of maternal BMI on pregnancy and perinatal outcomes

This is the final version. Available from BMC via the DOI in this record. Availability of data and materials: In order to protect participant confdentiality, supporting data cannot be made openly available. Bona fide researchers can apply for access to study specifc executive committees. Summary association data for FinnGen is publicly available at https://www.fnngen.f/en/access_results. Researchers can apply for access to the UK Biobank data via the Access Management System (AMS) (https://www.ukbiobank.ac.uk/enable-your-research/apply-for-access).BACKGROUND: Higher maternal pre-pregnancy body mass index (BMI) is associated with adverse pregnancy and perinatal outcomes. However, whether these associations are causal remains unclear. METHODS: We explored the relation of maternal pre-/early-pregnancy BMI with 20 pregnancy and perinatal outcomes by integrating evidence from three different approaches (i.e. multivariable regression, Mendelian randomisation, and paternal negative control analyses), including data from over 400,000 women. RESULTS: All three analytical approaches supported associations of higher maternal BMI with lower odds of maternal anaemia, delivering a small-for-gestational-age baby and initiating breastfeeding, but higher odds of hypertensive disorders of pregnancy, gestational hypertension, preeclampsia, gestational diabetes, pre-labour membrane rupture, induction of labour, caesarean section, large-for-gestational age, high birthweight, low Apgar score at 1 min, and neonatal intensive care unit admission. For example, higher maternal BMI was associated with higher risk of gestational hypertension in multivariable regression (OR = 1.67; 95% CI = 1.63, 1.70 per standard unit in BMI) and Mendelian randomisation (OR = 1.59; 95% CI = 1.38, 1.83), which was not seen for paternal BMI (OR = 1.01; 95% CI = 0.98, 1.04). Findings did not support a relation between maternal BMI and perinatal depression. For other outcomes, evidence was inconclusive due to inconsistencies across the applied approaches or substantial imprecision in effect estimates from Mendelian randomisation. CONCLUSIONS: Our findings support a causal role for maternal pre-/early-pregnancy BMI on 14 out of 20 adverse pregnancy and perinatal outcomes. Pre-conception interventions to support women maintaining a healthy BMI may reduce the burden of obstetric and neonatal complications. FUNDING: Medical Research Council, British Heart Foundation, European Research Council, National Institutes of Health, National Institute for Health Research, Research Council of Norway, Wellcome Trust.Medical Research CouncilBritish Heart FoundationEuropean Research CouncilEuropean Research CouncilEuropean Union’s Horizon 2020National Institutes of HealthNational Institutes of HealthResearch Council of NorwayWellcome Trus