3,373 research outputs found

    Inter-individual variation of the human epigenome & applications

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    Prevalence and associated factors of severity levels of anemia among women of reproductive age in sub-Saharan Africa: a multilevel ordinal logistic regression analysis

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    BackgroundSub-Saharan Africa is the most anemia-prone region, with several of the sub-region’s countries having a substantial prevalence of the anemia among women of reproductive age. Nonetheless, no adequate study has been conducted to illustrate severity levels and associated factors of anemia among women of reproductive age. Therefore, this study presents the most recent estimates on the prevalence and severity levels of anemia and its associated factors among women of reproductive age in 21 Sub-Saharan Africa countries.MethodsThis study used the most recent Demographic Health Survey (DHS) datasets, which were collected in 21 sub-Saharan African countries between 2015 and 2022. A total of 171,348 women of reproductive age were included in the analysis. Multilevel (three-level) ordinal logistic regression was done to identify factors associated with severity levels of anemia.ResultsThe pooled prevalence of anemia was 41.74%. The pooled prevalence of mild, moderate and severe anemia was 23.45, 17.05 and 1.24, respectively. Women who were living at distance to a health facility (AOR = 1.07), women living in the poorest households (AOR = 1.49), women living in the households with unimproved toilet (AOR = 1.12) and in households that were using solid cooking fuel (AOR = 1.10), pregnant women (AOR = 1.72) and those who have given birth to more than one children within 3 years (AOR = 1.43) had greater odds of higher levels of anemia as compared to their counterparts. Women who were in the age groups of 20–24 (AOR = 0.81), 25–29 (AOR = 0.78), 30–34 (AOR = 0.79), 35–39 (AOR = 0.88), and 45–49 (AOR = 0.89), women who have attended primary school (AOR = 0.50), secondary (AOR = 0.57) and higher education (AOR = 0.76) and who were living in rural area (AOR = 1.07) had lower odds of higher levels of anemia as compared to their counterparts.ConclusionConsidering individual, household and community contexts is necessary while formulating and implementing anemia prevention and control policies. Adolescent women, and women who did not attend education and at a distance to a health facility should get especial attention while implementing anemia prevention and control programs

    Pregnancy and cardiac disease

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    Pregnancy and cardiac disease

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    Measuring the Health and Development of School-age Zimbabwean Children

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    Health, growth and development during mid-childhood (from 5 to 14 years) are poorly characterised, and this period has been termed the ‘missing middle’. This thesis describes the piloting and application of the School-Age Health, Activity, Resilience, Anthropometry and Neurocognitive (SAHARAN) toolbox to measure growth, cognitive and physical function amongst the SHINE cohort in rural Zimbabwe. The SHINE cluster-randomised trial tested the effects of a household WASH intervention and/or infant and young child feeding (IYCF) on child stunting and anaemia at age 18 months in rural Zimbabwe. SHINE showed that IYCF modestly increased linear growth and reduced stunting by age 18 months, while WASH had no effects. The SAHARAN toolbox was used to measure 1000 HIV-unexposed children (250 in each intervention arm), and 275 HIV-exposed children within the SHINE cohort to evaluate long-term outcomes. Children were re-enrolled at age seven years to evaluate growth, body composition, cognitive and physical function. Four main findings are presented from the SAHARAN toolbox measurements of this cohort. Firstly, child sex, growth and contemporary environmental conditions are associated with school-age physical and cognitive function at seven years. Secondly, early-life growth and baseline environmental conditions suggest the impact of early-life trajectories on multiple aspects of school-age growth, physical and cognitive function. Thirdly, the long-term impact of HIV-exposure in pregnancy is explored, which indicate reduced cognitive function, cardiovascular fitness and head circumference by age 7 years. Finally, associations with the SHINE trial early life interventions are explored, demonstrating that the SHINE early-life nutrition intervention has minimal impact by 7 years of age, except marginally stronger handgrip strength. The public health implications advocate that child interventions need to be earlier (including antenatal), broader (incorporating nurturing care), deeper (providing transformational WASH) and longer (supporting throughout childhood), as well as targeting particularly vulnerable groups such as children born HIV-free

    Inter-individual variation of the human epigenome & applications

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    Genome-wide association studies (GWAS) have led to the discovery of genetic variants influencing human phenotypes in health and disease. However, almost two decades later, most human traits can still not be accurately predicted from common genetic variants. Moreover, genetic variants discovered via GWAS mostly map to the non-coding genome and have historically resisted interpretation via mechanistic models. Alternatively, the epigenome lies in the cross-roads between genetics and the environment. Thus, there is great excitement towards the mapping of epigenetic inter-individual variation since its study may link environmental factors to human traits that remain unexplained by genetic variants. For instance, the environmental component of the epigenome may serve as a source of biomarkers for accurate, robust and interpretable phenotypic prediction on low-heritability traits that cannot be attained by classical genetic-based models. Additionally, its research may provide mechanisms of action for genetic associations at non-coding regions that mediate their effect via the epigenome. The aim of this thesis was to explore epigenetic inter-individual variation and to mitigate some of the methodological limitations faced towards its future valorisation.Chapter 1 is dedicated to the scope and aims of the thesis. It begins by describing historical milestones and basic concepts in human genetics, statistical genetics, the heritability problem and polygenic risk scores. It then moves towards epigenetics, covering the several dimensions it encompasses. It subsequently focuses on DNA methylation with topics like mitotic stability, epigenetic reprogramming, X-inactivation or imprinting. This is followed by concepts from epigenetic epidemiology such as epigenome-wide association studies (EWAS), epigenetic clocks, Mendelian randomization, methylation risk scores and methylation quantitative trait loci (mQTL). The chapter ends by introducing the aims of the thesis.Chapter 2 focuses on stochastic epigenetic inter-individual variation resulting from processes occurring post-twinning, during embryonic development and early life. Specifically, it describes the discovery and characterisation of hundreds of variably methylated CpGs in the blood of healthy adolescent monozygotic (MZ) twins showing equivalent variation among co-twins and unrelated individuals (evCpGs) that could not be explained only by measurement error on the DNA methylation microarray. DNA methylation levels at evCpGs were shown to be stable short-term but susceptible to aging and epigenetic drift in the long-term. The identified sites were significantly enriched at the clustered protocadherin loci, known for stochastic methylation in neurons in the context of embryonic neurodevelopment. Critically, evCpGs were capable of clustering technical and longitudinal replicates while differentiating young MZ twins. Thus, discovered evCpGs can be considered as a first prototype towards universal epigenetic fingerprint, relevant in the discrimination of MZ twins for forensic purposes, currently impossible with standard DNA profiling. Besides, DNA methylation microarrays are the preferred technology for EWAS and mQTL mapping studies. However, their probe design inherently assumes that the assayed genomic DNA is identical to the reference genome, leading to genetic artifacts whenever this assumption is not fulfilled. Building upon the previous experience analysing microarray data, Chapter 3 covers the development and benchmarking of UMtools, an R-package for the quantification and qualification of genetic artifacts on DNA methylation microarrays based on the unprocessed fluorescence intensity signals. These tools were used to assemble an atlas on genetic artifacts encountered on DNA methylation microarrays, including interactions between artifacts or with X-inactivation, imprinting and tissue-specific regulation. Additionally, to distinguish artifacts from genuine epigenetic variation, a co-methylation-based approach was proposed. Overall, this study revealed that genetic artifacts continue to filter through into the reported literature since current methodologies to address them have overlooked this challenge.Furthermore, EWAS, mQTL and allele-specific methylation (ASM) mapping studies have all been employed to map epigenetic variation but require matching phenotypic/genotypic data and can only map specific components of epigenetic inter-individual variation. Inspired by the previously proposed co-methylation strategy, Chapter 4 describes a novel method to simultaneously map inter-haplotype, inter-cell and inter-individual variation without these requirements. Specifically, binomial likelihood function-based bootstrap hypothesis test for co-methylation within reads (Binokulars) is a randomization test that can identify jointly regulated CpGs (JRCs) from pooled whole genome bisulfite sequencing (WGBS) data by solely relying on joint DNA methylation information available in reads spanning multiple CpGs. Binokulars was tested on pooled WGBS data in whole blood, sperm and combined, and benchmarked against EWAS and ASM. Our comparisons revealed that Binokulars can integrate a wide range of epigenetic phenomena under the same umbrella since it simultaneously discovered regions associated with imprinting, cell type- and tissue-specific regulation, mQTL, ageing or even unknown epigenetic processes. Finally, we verified examples of mQTL and polymorphic imprinting by employing another novel tool, JRC_sorter, to classify regions based on epigenotype models and non-pooled WGBS data in cord blood. In the future, we envision how this cost-effective approach can be applied on larger pools to simultaneously highlight regions of interest in the methylome, a highly relevant task in the light of the post-GWAS era.Moving towards future applications of epigenetic inter-individual variation, Chapters 5 and 6 are dedicated to solving some of methodological issues faced in translational epigenomics.Firstly, due to its simplicity and well-known properties, linear regression is the starting point methodology when performing prediction of a continuous outcome given a set of predictors. However, linear regression is incompatible with missing data, a common phenomenon and a huge threat to the integrity of data analysis in empirical sciences, including (epi)genomics. Chapter 5 describes the development of combinatorial linear models (cmb-lm), an imputation-free, CPU/RAM-efficient and privacy-preserving statistical method for linear regression prediction on datasets with missing values. Cmb-lm provide prediction errors that take into account the pattern of missing values in the incomplete data, even at extreme missingness. As a proof-of-concept, we tested cmb-lm in the context of epigenetic ageing clocks, one of the most popular applications of epigenetic inter-individual variation. Overall, cmb-lm offer a simple and flexible methodology with a wide range of applications that can provide a smooth transition towards the valorisation of linear models in the real world, where missing data is almost inevitable. Beyond microarrays, due to its high accuracy, reliability and sample multiplexing capabilities, massively parallel sequencing (MPS) is currently the preferred methodology of choice to translate prediction models for traits of interests into practice. At the same time, tobacco smoking is a frequent habit sustained by more than 1.3 billion people in 2020 and a leading (and preventable) health risk factor in the modern world. Predicting smoking habits from a persistent biomarker, such as DNA methylation, is not only relevant to account for self-reporting bias in public health and personalized medicine studies, but may also allow broadening forensic DNA phenotyping. Previously, a model to predict whether someone is a current, former, or never smoker had been published based on solely 13 CpGs from the hundreds of thousands included in the DNA methylation microarray. However, a matching lab tool with lower marker throughput, and higher accuracy and sensitivity was missing towards translating the model in practice. Chapter 6 describes the development of an MPS assay and data analysis pipeline to quantify DNA methylation on these 13 smoking-associated biomarkers for the prediction of smoking status. Though our systematic evaluation on DNA standards of known methylation levels revealed marker-specific amplification bias, our novel tool was still able to provide highly accurate and reproducible DNA methylation quantification and smoking habit prediction. Overall, our MPS assay allows the technological transfer of DNA methylation microarray findings and models to practical settings, one step closer towards future applications.Finally, Chapter 7 provides a general discussion on the results and topics discussed across Chapters 2-6. It begins by summarizing the main findings across the thesis, including proposals for follow-up studies. It then covers technical limitations pertaining bisulfite conversion and DNA methylation microarrays, but also more general considerations such as restricted data access. This chapter ends by covering the outlook of this PhD thesis, including topics such as bisulfite-free methods, third-generation sequencing, single-cell methylomics, multi-omics and systems biology.<br/

    Correlation between serum ferritin in early pregnancy and hypertensive disorders in pregnancy

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    ObjectiveTo explore the correlation between serum ferritin (SF) in early pregnancy and the risk of hypertensive disorders in pregnancy (HDP).MethodA retrospective cohort study was conducted on 43,421 pregnant women with singleton pregnancies who underwent antenatal checkups at Fujian Provincial Maternal and Child Health Hospital from January 2018 to December 2020. Based on pregnancy records, women were classified as non-hypertensive, having gestational hypertension, preeclampsia and preeclampsia with severe features according to the degree of the disease. General baseline data, and SF levels in the early (up to 12 gestational weeks) and late (after 28  weeks of gestation) stages of pregnancy were collected. The significance of the characteristic variables was assessed using a random forest algorithm, and the correlation between early pregnancy SF levels and the incidence of HDP was further analyzed using logistics regression adjusted for confounders. A generalized additive model (GAM) was fitted to a smoothed graph of the relationship between early pregnancy SF levels and HDP, and a threshold effect analysis was performed to find the threshold values of early pregnancy SF for iron supplementation therapy.ResultA total of 30,703 pregnant women were included. There were 1,103 women who were diagnosed with HDP. Of them, 418 had gestational hypertension, 12 had chronic hypertension without SPE, 332 - preeclampsia and 341 women had preeclampsia with severe features. Levels of SF in early and late pregnancy were significantly higher (p &lt; 0.001) in women with HDP compared to non-hypertensive women and the difference was more pronounced in early pregnancy. The random forest algorithm showed that early pregnancy SF was more effective in predicting HDP compared to late pregnancy SF levels and was also an independent risk factor for HDP (adjusted odds ratio (AOR) = 1.07, 95% CI [1.05,1.09]) after correction for confounding factors. Early pregnancy SF &gt;64.22  mg/l was associated with higher risk of developing hypertensive disorders.ConclusionRisk of pregnancy-related hypertensive disorders increases with increasing early pregnancy SF levels. SF levels may therefore be used to further develop guidelines for iron supplementation therapy in pregnant women

    Intrauterine and genetic risk factors for proliferative diabetic retinopathy

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    Diabetes is a complex progressive metabolic disorder characterized by hyperglycemia and caused by different etiopathogenic factors. Individuals with diabetes have heterogeneous clinical representation and increased risk of micro- and macrovascular complications. Diabetic retinopathy (DR) is the most frequent microvascular complication of diabetes and one of the leading causes of blindness. Currently, existing treatment modalities target a severe sight-threatening form of the disease, proliferative DR (PDR), and are characterized by significant side effects. The prevailing strategy for prevention or slowing down DR progression is glucose-lowering therapy, which is not efficient enough and might be harming to older groups of patients. Risk factors for PDR include duration of diabetes, hypertension, dyslipidemia, genetics and environment, and their interplay. The adverse intrauterine environment, particularly exposure to prenatal famine, was shown to play an important role in predisposition to diverse metabolic disorders in adults such as type 2 diabetes (T2D), hypertension, and cardiovascular diseases (CVD). In this Ph.D. thesis, we aimed to study novel diabetes subgroups based on pathophysiological characteristics of patients, highlighting subgroup(s) with an elevated risk of diabetic complications, particularly PDR. Further, we aimed to investigate the association of intrauterine exposure to famine with the risk of PDR in adult individuals with T2D. Finally, we wanted to study the molecular mechanisms linked to famine-related PDR. In paper 1, we performed a k-means cluster analysis to identify novel subgroups of individuals with new-onset and long-term diabetes, and estimated the risks of diabetic complications using logistic regression. In paper 2, we evaluated effect of intrauterine famine exposure on the risk of PDR in individuals with T2D using logistic regression adjusted for established risk factors such as age, sex, duration of diabetes and HbA1c. In paper 3, we performed candidate gene analysis using generalized estimation equation (GEE) to study the effect of interaction between SNPs and perinatal famine exposure on the risk of PDR. In paper 4, we performed genome-wide association (GWAS) and interaction (GWIS) studies using a linear mixed model (LMM) to investigate molecular underpinnings of famine-related PDR. In paper 1, we identified three subgroups with severe diabetes and two subgroups with mild diabetes. The highest risk of PDR was observed in the severe autoimmune diabetes (SAID) and severe insulin-deficient diabetes (SIDD) subgroups and the lowest in the insulin-resistant obesity-related diabetes 2 (IROD2) subgroup. In paper 2, we demonstrated that individuals with T2D, who were perinatally exposed to famine had an elevated risk of PDR in adult life. In paper 3, we demonstrated a significant association between famine-associated PDR and SNPs which were located in genes with neuronal function. In paper 4, we identified diverse pathways potentially linked to famine-related PDR, among them the most significant were lipid metabolism and inflammation pathways. In conclusion, we suggested that the altered development of neurovascular unit in the retina due to exposure to intrauterine famine may increase susceptibility to PDR later in life. Changes in metabolic adaptations during developmental programming induced by adverse early life events may affect insulin secretion and lipid metabolism, which consequently may increase predisposition to PDR under diabetes environment in adulthood. We suggested that drugs targeting these mechanisms in addition to glucose-lowering treatments may be beneficial for the prevention or slowing down the progression to PDR in the early stages of the disease.Diabetes er en kompleks progressiv metabolsk sykdom som kjennetegnes ved hyperglykemi og er forårsaket av forskjellige etiopatogenetiske faktorer. Personer med diabetes har heterogen klinisk representasjon og økt risiko for mikro- og makrovaskulære komplikasjoner. Diabetisk retinopati (DR) er den hyppigste mikrovaskulære komplikasjonen ved diabetes og en av de viktigste årsakene til blindhet. For tiden er eksisterende behandlingsmetoder rettet mot en alvorlig synstruende form av sykdommen, proliferativ DR (PDR), og medfører betydelige bivirkninger. Den rådende strategien for forebygging eller forsinking av DR-progresjon er glukosesenkende terapi, som ikke er effektiv nok og kan være skadelig for eldre pasienter. Risikofaktorer for PDR inkluderer varighet av diabetes, hypertensjon, dyslipidemi, genetikk og miljø, og deres samspill. Det ugunstige intrauterine miljøet, spesielt eksponering for prenatal hungersnød, ble vist å spille en viktig rolle i predisposisjon for ulike metabolske forstyrrelser hos voksne som type 2 diabetes (T2D), hypertensjon og kardiovaskulære sykdommer (CVD). I denne doktorgradsavhandlingen, har vi hatt som mål å studere nye diabetes-undergrupper basert på patofysiologiske egenskaper hos pasienter, og fremheve undergruppe(r) med økt risiko for diabetiske komplikasjoner, spesielt PDR. Videre hadde vi som mål å undersøke sammenheng mellom intrauterin eksponering for hungersnød og risikoen for utvikling av PDR hos voksne med T2D. Til slutt ønsket vi å studere de molekylære mekanismene knyttet til hungersnød-relatert PDR. I artikkel 1 utførte vi en k-means-klyngeanalyse for å identifisere nye undergrupper av individer med nyoppstått og langvarig diabetes, og estimerte risikoen for diabetiske komplikasjoner ved hjelp av logistisk regresjon. I artikkel 2 evaluerte vi effekten av eksponering for intrauterin hungersnød på risikoen for PDR hos individer med T2D ved bruk av logistisk regresjon justert for etablerte risikofaktorer som alder, kjønn, varighet av diabetes og HbA1c. I artikkel 3 utførte vi kandidatgenanalyse ved å bruke generalisert estimeringsligning (GEE) for å studere effekten av interaksjon mellom SNP-er og perinatal hungersnødeksponering på risikoen for PDR. I artikkel 4 utførte vi genomomfattende assosiasjonsstudier (GWAS) og interaksjonsstudier (GWIS) ved å bruke en lineær blandet modell (LMM) for å undersøke molekylært grunnlag for hungersnødrelatert PDR. I artikkel 1 identifiserte vi tre undergrupper med alvorlig diabetes og to undergrupper med mild diabetes. Den høyeste risikoen for PDR ble observert i undergruppene med alvorlig diabetes type 1 (SAID) og alvorlig diabetes type 2 (SIDD), og den laveste i undergruppen insulinresistent fedme-relatert diabetes 2 (IROD2). I artikkel 2 viste vi at personer med T2D, som ble perinatalt utsatt for hungersnød, hadde en forhøyet risiko for utvikling av PDR i voksenlivet. I artikkel 3 viste vi en signifikant sammenheng mellom hungersnødassosiert PDR og SNP-er som var lokalisert i gener med nevronal funksjon. I artikkel 4 identifiserte vi ulike veier som er potensielt knyttet til hungersnød-relatert PDR, blant dem var de mest betydningsfulle lipidmetabolisme og betennelsesveier. Avslutningsvis foreslo vi at den endrede utviklingen av nevrovaskulær kretsløp i netthinnen på grunn av eksponering for intrauterin hungersnød kan øke følsomheten for PDR senere i livet. Endringer i metabolske tilpasninger under utviklingsprogrammering indusert av uønskede hendelser i tidlig liv kan påvirke insulinsekresjon og lipidmetabolisme, som følgelig kan øke predisposisjon for PDR under diabetesmiljø i voksen alder. Vi foreslo at medikamenter som retter seg mot disse mekanismene i tillegg til glukosesenkende behandlinger kan være gunstig for forebygging eller forsinke progresjon til PDR i de tidlige stadiene av sykdommen.Doktorgradsavhandlin

    The Application of Simulation to Quantifying the Influence of Bias in Perinatal Epidemiology

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    Perinatal aetiological associations derived from observational data are susceptible to various types of bias. This thesis demonstrated the application of simulation methodologies to quantify the influence of bias in perinatal epidemiology through a series of simulation studies which quantified the magnitude and direction of bias mechanisms. A framework to guide epidemiologists in the development, implementation and reporting of simulation studies to quantify bias was developed. Simulation is a potent tool to the quantification of bias
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