The purpose of the proposed research is to identify and quantify the principal determinants of measures of immune

function of a wild mammal, Mus musculus. The immune function of wild animals, and its control, is very poorly

understood, despite the key role that immune function plays in their fitness. We do not know what immune responses wild

animals make, nor what affects and controls this.

Wild animals are continually exposed to infections, against which they make immune responses. This inter-play between

exposure to infection and retaliatory immune responses ultimately determines the fitness and survival of individual

animals. Animal immune function is also central to host-pathogen population dynamics. Immune responses are the key

link between, and mediator of, these processes but are poorly understood in the natural environment. Understanding

what controls immune function, and the effects of immune function, is central to understanding the consequences of

infection for wild animals (as well as for their pathogens). Our work will exploit the deep laboratory based knowledge and

understanding of murine immunology and use a wide range of validated tools to - for the first time - discover what immune

responses a wild animal makes and what controls this.

Laboratory studies have shown the many factors that may affect immune responses (sex, genetics, nutritional status, age,

infection status etc.) but which factors actually do affect immune function, nor their relative roles and importance, in wild

animals is not known.

In a pilot project that investigated the immune function of wild caught M. musculus, we found that the immune responses

of these animals differed substantially from each other (and differed markedly from laboratory mice).

We now to propose to undertake a full study of the immune function of wild mice and to partition the effect of different

intrinsic and extrinsic factors on M. musculus immune function. The specific objectives of the proposed work are to:

1. Make measures of immune function of wild M. musculus,

2. Quantify the effect of extrinsic and intrinsic factors on measures of immune function, and

3. Experimentally test causality of key explanatory factors of immune function.

To do this we will undertake a cross-sectional survey of wild M. musculus populations. We will assay the humoural and

cellular, innate and adaptive immune function of the mice. This will address objective 1. At the same time we shall

measure likely key intrinsic factors (sex, genetics, reproductive status, hormone status, body condition, infection status)

and extrinsic factors such as season and location. We will then seek to explain how the intrinsic and extrinsic factors (and

combinations of these factors) affect immune function, particularly using structural equation modelling. This will address

objective 2. To move from association to causality, we will then experimentally test these findings in wild mice, which will

address objective 3.

Understanding the control of immune responses and their relationship to other life-history aspects is central to ultimately

understanding fitness of wild animals. This information is key to understanding how wild animals deal with their existing

range of infection challenges and the effects that novel and emerging infections, or other changes in their environment,

will have on them. This is particularly pressing given the current high rate of environmental change.

Evidence increasingly suggests that mental health problems are associated with insults during critical times of brain development, and also by exposures over an individual's life course. These include in-utero exposures, which may lead to subtle neurobehavioral difficulties. Further, there is a body of evidence relating birth weight to cognitive function in childhood, though sibling-based analyses suggest the association is more likely to be due to fixed familial factors such as background socioeconomic position and behaviours/exposures that are similar for all siblings within a family. (1)

However, there is relatively little work on the role of early alcohol and tobacco exposure on the occurrence of a range of cognitive, behavioural and emotional difficulties. In-utero to these substances may cause a variety of adverse developmental outcomes. (2) Finally there is emerging evidence pointing to an association between alcohol and tobacco use in pregnancy and the development of addictive behaviours, such as addiction to alcohol and tobacco. (3-6)

The mechanisms underlying these associations are unclear. It is assumed that the effects are due to specific intrauterine exposure, but genetic factors and shared familial factors (including socioeconomic position, shared/learnt familiar behaviours) may well explain any link between maternal alcohol and tobacco consumption in pregnancy and later effects on offspring cognitive function and behaviour. One way to further explore this is to compare associations of maternal alcohol and tobacco use during pregnancy with offspring outcomes to the same associations with paternal alcohol and tobacco consumption. Analyses using these analytical techniques are needed to ascertain whether in-utero exposure to alcohol and tobacco consumption truly contributes to later developmental problems. If this is so it is also important to understand the mechanisms underlying these associations. To date only one study has done this and both George Davey Smith and I have been involved in preparing that paper (7).

In the previous paper published in 2008, we carried out comparisons of both alcohol and tobacco use with child's IQ at age 8 and found no important adverse effect of both moderate maternal alcohol and tobacco consumption on offspring IQ at age 8, though IQ scores were lower in children of mothers who reported greater quantity of 'binge'- like style of drinking. (7) Further to that study, a Welcome Trust project grant led by Dr Ron Grey, has allowed us to progress our work in this area and carry out maternal-offspring and paternal-offspring alcohol comparisons with a range of child's neuro-developmental outcomes, including cognitive abilities at age 11 (paper awaiting ALSPAC Exec approval).

The role of intra-uterine exposure to tobacco has not been investigated in this grant. Hence, we propose to examine the association between parental smoking and offspring cognitive abilities at age 11. Several studies have found an inverse association between parental (usually maternal) smoking during pregnancy and offspring IQ. Biological mechanisms involving in utero exposure to tobacco combustion products and their metabolites have been proposed however other evidence suggests that confounding by factors related to social position may be more important. [2,3] Unlike alcohol use, smoking at even relatively moderate levels may be a marker of adverse social environment in contemporary populations. This is likely to be particularly true of maternal smoking during pregnancy.

The aim of this proposal is to use ALSPAC data in order to determine whether intra-uterine exposure to tobacco consumption (assessed by maternal self-reports during pregnancy) is related to poorer academic abilities at age 11 (KS2 linked data). The association of maternal smoking during pregnancy with academic abilities will be compared to similar associations of paternal tobacco use (based on self-report by the partner of the mother, or where this is not available the mother's report of the fathers tobacco use, with restriction to those who define themselves as the biological father). This comparison will strengthen our ability to determine whether there is a true intrauterine effect, since if there is one, it should be only apparent with maternal tobacco use. Similar association between maternal and paternal tobacco use and child's cognitive skills would suggest that genetic factors and/or shared family environmental factors explain the association rather than specific intrauterine effects. We propose to examine the effect of maternal and paternal smoking during pregnancy and offspring KS2 scores at age 11, both before and after adjustment for covariates. I will conduct the analysis using the current Wellcome Trust dataset, and will need additional alcohol and tobacco variables in the postnatal period to include prenatal and postnatal parental effects in the analysis (see analysis used in the alcohol paper awaiting approval).

Background

Several recent cohort studies have reported inverse linear associations of adiposity measures (e.g. body mass index, BMI) with risk of completed suicide (Magnusson et al. 2006; Mukamal et al. 2007; Bjerkeset et al. 2008; Batty et al. 2010; Mukamal et al. 2010). Stepwise associations are found across the range of BMI - low BMI is associated with increased suicide risk, and raised BMI is associated with reduced suicide risk. These associations are robust to controlling for a range of possible confounding factors, including mental illness, and are seen regardless of suicide method. In contrast, results from studies of non-fatal suicide attempts have been markedly less consistent (Jiang et al. 1999; Carpenter et al. 2000; Falkner et al. 2001; Eaton et al. 2005; Brunner et al. 2006; Dong et al. 2006; Crow et al. 2008; Osler et al. 2008; Dave et al. 2009; Batty et al. 2010). Likewise, studies report inconsistent findings for the association of obesity with depression (Lawlor et al. 2007; Atlantis et al. 2008; Bjerkeset et al. 2008; Luppino et al. 2010).

Body weight fluctuates over time, and distinct patterns of its change have been shown to be associated with particular psychiatric outcomes. For example, a prospective study of a sample of American children found associations of chronic obesity with defiant oppositional defiant disorder in boys and girls and with depressive disorders in boys (Mustillo et al. 2003). A recent birth cohort study finds associations of mood symptoms with change in body mass index over the course between age 15 to 53 years but the relationship varies by sex and age at onset of symptoms (Gaysina et al. 2010). However, there have been no studies investigating the association of the growth or adiposity trajectories with risk of suicidal behaviours.

One possible explanation for the conflicting findings of the association of adiposity with non-fatal suicide attempts is that the relationship is subject to confounding by other risk factors for suicide (e.g. smoking, alcohol use, physical and mental illness and socioeconomic position), which are associated with both body weight and suicide (Mukamal et al. 2010). One possible approach to examining the causality of the observed adiposity-suicide relationship is Mendelian randomisation (Batty et al. 2010), which uses genetic variations as non-confounded proxies for environmental exposures (Davey Smith et al. 2003; Lawlor et al. 2008). The recent discovery of common markers of obesity such as FTO (Frayling et al. 2007) and MC4R (Loos et al. 2008) makes it possible to investigate the association of adiposity with suicide using such an approach.

Aims

We aim to investigate whether self-harm/suicidal behaviour is associated with body weight or distinct growth/adiposity patterns within the ALSPAC cohort. We also aim to explore the potential of using the ALSPAC to investigate the causality of any observed relationship between adiposity and self-harm/suicidal behaviour using the Mendelian randomisation approach.

As obesity is a powerful risk factor for a variety of diseases, this development represents a tremendous challenge to the healthcare systems worldwide. Such complications are particularly serious if obesity starts early in life and causes long term exposure of organs to excess body fat. There are convincing indications that early life weight gain is a strong influencing factor a later weight and thus contributes to the risk of developing obesity eventually already in childhood (Gillman et al, 2008; Stettler et al, 2010).

Although current knowledge about mechanisms which contribute to early childhood obesity is limited, there is some evidence that fatty acid status may influence the risk to become overweight or obese. Fatty acids influence adipogenesis by binding to PPARgamma and beta/(delta), which act as a regulator of fat cell formation (Spiegelman, 1998), thereby providing a molecular link between fatty acid status and fat cell development. Of particular importance for adipogenesis seems arachidonic acid, the major long chain polyunsaturated fatty acid of the linoleic acid derived n-6 series (Demmelmair et al, 1999). Arachidonic acid is converted into prostacyclin, which stimulates via cAMP production adipose differentiation of primary preadipocytes in cell culture studies (Massiera et al, 2003). In contrast, the n-3 fatty acids eicosapentaenoic acid and docosahexaenoic acid were found to inhibit the stimulatory effect of arachidonic acid on cAMP production (Massiera et al, 2003).

Based on these findings G. Alihaud developed the hypothesis that a high intake/availability of n-6 polyunsaturated fatty acids is a potent promoter of adipogenesis in vitro and adipose tissue development in vivo (Massiera et al, 2006; Ailhaud et al, 2004).

Although the observed increase of the intake of n-6 fatty acids during the last decades and the increase in childhood obesity agree with this hypothesis (Ailhaud et al, 2008), it has not been tested so far in birth cohorts. By now the importance of the influence of genetic variants of the fatty acid desaturases FADS1 and FADS2 on human fatty acid status primarily in respect to n-6, but also on n-3, long chain polyunsaturated fatty acids has been demonstrated (Glaser et al, 2010). Inclusion of FADS genotype into studies relating fatty acid status to weight development seems important, as this provides the opportunity to identify a relationship between FADS genotype and obesity risk..

Considering the numerous identified and potentially also unidentified factors, which determine anthropometry during infancy and child adequate statistical power has to be achieved. An ideal opportunity to investigate the hypothesis provides combination of several sizable, well characterized birth cohort for an individual subject based metaanalysis.

Aim

To test whether fatty acid status during early life and/or FADS genotype are related to growth during childhood in population based prospective birth cohorts considering further (e.g. diet, socioeconomic status) influencing factors.

Workplan

Data on fatty acid status at various time points during infancy, genotype, parental anthropometry, dietary intake and socioeconomic status shall be combined for analysis from birth cohorts: e.g. ALSPAC (Bristol, UK), Generation R (Rotterdam, NL),

Statistical modelling will start by applying latent cluster structure analyses techniques to study trajectories for height, weight, relative weight (z-scores), and overweight. Further factors will be considered as confounders and/or effect modifiers. Suitable models were described in a recent paper (Rzehak et al, 2009), which has also shown that a study of approximately 1000 subjects has sufficient power to detect small differences in weight gain due to the longitudinal modelling and the continuous outcome. Thus, it can be expected that even a small effect of fatty acid status on anthropometric development can be detected/excluded by studying more than 10 000 subjects, even if not fully standardized measurements of fatty acid status (age of sampling, analytical procedure) and corresponding modelling is needed.

Expected output

Scientific manuscript describing and discussing the relationship between the levels of fatty acids and genotype with infantile anthropometric development, with a focus on the incidence of overweight and obesity, until the age of 10 years.

References

(1) Gillman MW, Rifas-Shiman SL, Kleinman K, Oken E, Rich-Edwards JW, Taveras EM. Developmental origins of childhood overweight: potential public health impact. Obesity (Silver Spring) 16 (2008): 1651-6.

(2) Stettler N, Iotova V. Early growth patterns and long-term obesity risk. Curr Opin Clin Nutr Metab Care 13 (2010): 294-9.

(3) Spiegelman BM. PPAR-gamma: adipogenic regulator and thiazolidinedione receptor. Diabetes 47 (1998): 507-14.

(4) Demmelmair H, Iser B, Rauh-Pfeiffer A, Koletzko B. Comparison of bolus versus fractionated oral applications of [13C]-linoleic acid in humans. Eur J Clin Invest 29 (1999): 603-9.

(5) Massiera F, Saint-Marc P, Seydoux J, Murata T, Kobayashi T, Narumiya S, et al. Arachidonic acid and prostacyclin signaling promote adipose tissue development: a human health concern? J Lipid Res 44 (2003): 271-9.

(6) Massiera F, Guesnet P, Ailhaud G. The crucial role of dietary n-6 polyunsaturated fatty acids in excessive adipose tissue development: relationship to childhood obesity. Nestle Nutr Workshop Ser Pediatr Program 57 (2006): 235-42.

(7) Ailhaud G, Guesnet P. Fatty acid composition of fats is an early determinant of childhood obesity: a short review and an opinion. Obes Rev 5 (2004): 21-6.

(8) Ailhaud G, Guesnet P, Cunnane SC. An emerging risk factor for obesity: does disequilibrium of polyunsaturated fatty acid metabolism contribute to excessive adipose tissue development? Br J Nutr (2008): 1-10.

(9) Glaser C, Heinrich J, Koletzko B. Role of FADS1 and FADS2 polymorphisms in polyunsaturated fatty acid metabolism. Metabolism 59 (2010): 993-9.

(10) Rzehak P, Sausenthaler S, Koletzko S, Reinhardt D, von BA, Kramer U, et al. Short- and long-term effects of feeding hydrolyzed protein infant formulas on growth at less than or = 6 y of age: results from the German Infant Nutritional Intervention Study. Am J Clin Nutr 89 (2009): 1846-56.

As part of our ongoing research into the soluble form of the interleukin-2 receptor alpha (sIL-2RA) and

type 1 diabetes (T1D) risk, we would like to measure sIL-2RA in plasma or serum of ALSPAC children

aged 7, 9 and 11 years old. This would provide the sIL-2RA measurements that we currently lack in

controls subjects. We would measure sIL-2RA in all available samples, or at least 500 samples per age

group. In particular, we would like to measure sIL-2RA in the 500 ALSPAC children bled at the 7, 9 and

11 year clinics, as this would be informative about how well the levels of sIL-2RA tracked in children,

that is, are children in the lower quartile for levels of sIL-2RA at 7 years old, more likely to be in the

lower quartile at subsequent assessments?

We have measured concentrations of sIL-2RA in plasma of 6,000 T1D patient (almost all under age 17

yrs) and 6,000 adult control samples using a reproducible and sensitive immunoassay. In control

subjects, sIL-2RA concentration does not increase with age at sample acquisition (age range 17-69) and

we would like to know whether children have similar concentrations of sIL-2RA. Currently, our data

indicate that T1D children have higher levels of sIL-2RA than adults and this is associated with age-atdiagnosis.

The exciting possibility, which we want to explore further, is the circulating sIL-2RA

concentration maybe a biomarker of T1D diagnosis.

Concentrations of sIL-2RA will be estimated using a commercially available sIL-2RA immunoassay,

OptEIA(tm) Human sIL-2R ELISA (BD Biosciences), with dissociation-enhanced lanthanide

fluoroimmunoassay (DELFIA) detection reagents. Duplicate dilutions of plasma and sera will be assayed

on the same 96 well plate containing a standard curve of recombinant human sIL-2RA. A minimum of 24

micro-l of plasma or sera is required for each sIL-2RA concentration estimate. However, we would like to

receive greater than 30 micro-l to allow for dead volume. We would require information on sex, body mass index (BMI),

age at sample acquisition, T1D status and age at T1D diagnosis information. Also, if asthma/allergy

status is recorded on the questionnaire this might affect sIL-2RA levels.

We would also like to apply for access to the circulating levels of vitamin D [25(OH)D] measured in

ALSPAC children aged 7, 9 and 11 years. The repeat 25(OH)D measures in about 500 ALSPAC children

would be informative about how well levels of 25(OH)D tracked in children. Also, the levels of

25(OH)D in ALSPAC children would be a useful population reference for our T1D patients with

25(OH)D measured. In addition to the 25(OH)D measurements, we would require sex, BMI, age at

sample acquisition, month of sample acquisition, year of sample acquisition, T1D status and age at T1D

diagnosis information.

It is important to give mothers good advice on feeding their young children. Part of this advice should be about how much of each food to offer to their children. Very little information is available about this.

ALSPAC has collected diet diary information at 18 and 43 months which could be used to inform us about the amount of food that children are likely to eat on each meal occasion at these ages. We will use this data to give a mean, median and inter-quartile range for each food eaten on more than five occasions by the children. This data would not be linked to other ALSPAC variables .

We would like to use this analysis of portion sizes as a backup resource to support a web-based educational tool for health care professionals, carers and parents to access. The aim of this tool is to give guidance on suitable portion sizes to offer and reassurance that the amounts being eaten are appropriate. Part of the reason for this is that excessive portion sizes are likely to be contributing to the increases in obesity in children. This will be part of the Infant and Toddler Forum educational initiative website which Pauline has contributed to in the past. It is funded by an educational grant from Danone but is totally independent scientifically. http://www.infantandtoddlerforum.org/.

Fewer than twenty years ago, developmental psychopathologists and psychiatrists believed that there was little overlap between externalizing childhood psychiatric disorders, such as oppositional defiant disorder (ODD), and internalizing disorders, such as depression. There is now ample evidence from my own research (Boylan et al., 2007, 2010) and research of others (Copeland et al., 2009; Nock et al,.2007; Burke et al., 2010; Stringaris and Goodman, 2009), that childhood ODD shows significant concurrent and prospective associations or comorbidity with later depression. This discovery is changing the way we treat youths with ODD, and think about the causes of the disorder.

Despite these advances, important questions remain unanswered: Do all youths with ODD develop depression or will this only occur in sub-groups? What are the distinguishing characteristics of children belonging in one or other subgroups? The answers to these questions have profound clinical implications. If all youths with ODD develop depression, then perhaps we should begin prophylactic depression treatment, even before symptoms occur. On the other hand, if we can identify sub-groups of youths with ODD that develop depression, then prevention and treatment protocols can be applied in a more sophisticated and effective manner.

Based on my earlier work and the works of others which have demonstrated ODD symptoms cluster in various ways in the population , I propose that there are sub-groups of youths with ODD that will develop depression over time and the ability to identify and validate these groups is of substantial importance.

Study Aims:

(1) To determine whether oppositional symptom sub-groupings identified in previous factor analytic studies can be linked to groups of children who are oppositional.

(2) To determine whether these groups show differential risk for developing depression over time. If there is not strong evidence for person-based groupings, we will test how oppositional behaviours are associated with risk of depression across childhood.

Research objectives:

(1) To assess whether oppositional symptom subgroups identified by others (ie. a predominantly negative emotion and a predominantly antisocial symptom type) can be reliably identified in individual children using cross sectional and longitudinal data from an epidemiologic cohort sample.

(2) To determine if one, or more, of these groups is differentially associated with depression in late childhood and adolescence.

(3) To assess whether membership in these groups can be predicted on the basis of neurobiological and psychosocial risk factors that are associated with the ability to regulate negative emotions, in each of the following domains:

The child themselves (physiology of stress response, early life temperament, cognitive abilities, aggression, anxiety comorbidity)

The family context (family functioning, early attachment, parent discipline, family socioeconomic and family structure, parent mental health)

The peer and social context: peer relationships, school connectedness, social skills

Proposed methods:

We propose to use previously-collected questionnaire data for children from the ALSPAC study. The main outcome variables are the ODD and major depression and dysthymia symptoms from the DAWBA (at ages 7, 10 & 16) as reported by parents. Additional covariables, predominantly from questionnaire data, will be requested to distinguish the ODD groups and or predict relationships between ODD symptoms and depression based on study hypotheses. Longitudinal data on the DAWBA responses for the entire cohort will be requested to understand the impact of sample loss over time as complete data on DAWBA assessment periods is not necessary to conduct the analyses.

Analytic strategy:

Objective 1: A two step approach will test for the presence of groups of children with i) different types of ODD symptoms and ii) the stability (or reliability) of these prototypes/groups over time. The clustering of ODD symptoms will be identified from the DAWBA ODD symptoms data using factor analysis, followed by a confirmatory method (longitudinal confirmatory factor analysis). In step 2, we will test whether these (?#) identified ODD groups are developmentally distinct in that they can be distinguished based on the course of their symptom trajectory over time. To do this, we will use the group-based trajectory approach (with the Proc Traj procedure in SAS) which estimates the number and shape (course) of longitudinal trajectory groups in the sample, the proportion of children in each group and a probability for each child to belong to each group. Trajectories will be estimated for each ODD symptom cluster that is identified. Following this step, an extension of Proc Traj allows trajectory groups of one symptom cluster to be linked probabilistically to groups of another symptom cluster as joint trajectories to describe how the course of "comorbid" symptoms potentially overlap within individual children. As many children are likely to have both clusters of ODD symptoms over time, but most will have one or the other cluster (ie not have symptom overlap), assessing joint trajectories will establish how common these "comorbid" and non-comorbid children are. If comorbidity between ODD clusters is common, this suggests that there are not distinct ODD subtypes or subgroups.

In summary, the outputs of these analyses will identify: 1) are there likely ODD clusters? 2) how common are they? 3) how distinct are they from each other in terms of developmental course or how commonly do they overlap?

Objective 2: The identified joint oppositional symptom trajectory groups will be used to predict youth self-report of depression as an outcome at age 16 (measured as the youth DAWBA) using an extension in Proc Traj for this purpose. The output here will consist of a regression coefficient describing the strength of association between the various identified joint trajectory with the outcome of depression.

Objective 3: The same joint trajectory groups will be compared for their differential association with covariables (based on hypotheses which we do not outline here given space issues) as a means of exploring how they may differ etiologically from each other and how they may be differentially associated with risk of depression. Logistic regression will be conducted to examine if the prevalence rate of each covariate differs across trajectory groups.

Pre-eclampsia is a syndrome of pregnancy that is marked by proteinuria and hypertension. It is a leading cause of maternal mortality and is also associated with fetal growth restriction, placental abruption and perinatal death 1. Interestingly, there is a well-documented association between maternal smoking during pregnancy and reduced risk of pre-eclampsia. A recent review of epidemiological studies reported a total of 48 studies, consistently reporting a reduction in risk of pre-eclampsia in maternal smokers - up to 50% reduction in heavy smokers 2. However, ascertaining with certainty the causality of this association remains a challenge. Whilst the association has long been observed in the literature, the biological mechanisms for this relationship remain unknown. Indeed, many of the known effects of smoking suggest that prenatal smoking should increase the risk of pre-eclampsia, rather than decrease it.

Furthermore, whilst the association between maternal smoking and pre-eclampsia is well documented, associations with antenatal blood pressure per se are less well established. Few studies have reported on this, with some suggestion that smoking may be associated with increased systolic blood pressure3;4, in constrast to what might be expected from the observed associations with pre-eclampsia. Several of the proposed authors for this project (MacDonald-Wallis; Lawlor) have been analysing trajectories of blood pressure in pregnancy in the ALSPAC mothers, and have observed systematic differences in the trajectories of blood pressure amongst women who were nonsmokers, quitters and continued smokers during pregnancy (manuscript in progress). We would like to extend this work by analysing these trajectories with respect to a maternal genotype known to be associated with smoking during pregnancy, in order to better ascertain the extent of the causal mechanisms involved.

Research Questions:

1) Is maternal prenatal smoking status (as indexed by maternal CHRNA3 genotype) causally related to risk of pre-eclampsia

2)Is maternal prenatal smoking status (as indexed by maternal CHRNA3 genotype) causally related to trajectories of blood pressure during pregnancy.

(1) Sibai B, Dekker G, Kupferminc M. Pre-eclampsia. Lancet 2005; 365(9461):785-799.

(2) England L, Zhang J. Smoking and risk of preeclampsia: a systematic review. Front Biosci 2007; 12:2471-2483.

(3) Bakker R, Steegers EAP, Mackenbach JP, Hofman A, Jaddoe VWV. Maternal smoking and blood pressure in different trimesters of pregnancy: The Generation R Study. Journal of Hypertension 2010; 28.

(4) Matkin CC, Britton J, Samuels S, Esenazi B. Smoking and blood pressure patterns in normotensive pregnant women. Paediatr Perinat Epidemiol 1999; 13:22-34.

Background

Maternal anemia during pregnancy has previously been reported to be associated with elevated offspring blood pressure in later life1;2. However, this has only been reported in a small number of studies, with others failing to replicate this association3-5. Indeed, we previously explored this in ALSPAC6 and did not observe any consistent relationship between indicators of maternal iron status and offspring blood pressure at 7 years. A potential limitation of such studies is that assessing maternal iron status from haemoglobin measures is complicated by the tendency for low antenatal haemoglobin levels to reflect the natural haemodilution of pregnancy, rather than being indicative of pathological iron deficiency anemia. As such, there may be limited ability to identify causal effects of maternal iron deficiency anemia within such studies and this may have contributed to the inconsistent associations previously observed. We would like to build on our previous work carried out in ALSPAC by a) exploring maternal genetic variants affecting iron status as proxies for maternal iron, in order to better identify causal effects of maternal iron status and b) using trajectories of blood pressure across childhood and adolescence as the outcome measure, rather than one single measure of blood pressure. This will allow us to examine whether maternal iron status influences blood pressure across childhood or only at specific ages.

In contrast to the hypothesised adverse effects of maternal anemia during pregnancy, some have argued that iron depletion during pregnancy might in fact represent an adaptive physiological condition to prevent the adverse effects of oxidation, insulin resistance and thrombosis7. Indeed, whether iron supplementation in pregnancy is necessary, or even toxic, is still controversial and there is some evidence that maternal iron supplementation in pregnancy is associated with adverse outcomes such as increased risk of gestational diabetes and hypertensive disorders of pregnancy7;8. Thus, in addition to studying trajectories of child blood pressure, we would also like to assess the relationship between genetic variation in maternal iron status and trajectories of maternal blood pressure during pregnancy and gestational diabetes/glycosuria in ALSPAC.

Research Questions:

1) Is maternal iron status in pregnancy (as indicated by maternal iron genotypes) causally associated with offspring baseline BP at age 7 and BP trajectories between ages 7 and 15 years?

2) Is maternal iron status in pregnancy (as indicated by maternal iron genotypes) causally associated with maternal BP trajectories in pregnancy? For these analyses women with existing hypertension will be excluded.

3) Is maternal iron status in pregnancy (as indicated by maternal iron genotypes) causally associated with maternal gestational diabetes/glycosuria? This combined outcome will be used because there are too few cases of gestational diabetes alone for meaningful analyses; the use of glycosuria is justified by previous research in ALSPAC showing that it is associated with macrosomia9. For these analyses mothers with existing diabetes will be excluded.

Reference List

(1) Law CM, Barker DJ, Bull AR, Osmond C. Maternal and fetal influences on blood pressure. Arch Dis Child 1991; 66(11):1291-1295.

(2) Godfrey KM, Forrester T, Barker DJ, Jackson AA, Landman JP, Hall JS et al. Maternal nutritional status in pregnancy and blood pressure in childhood. Br J Obstet Gynaecol 1994; 101(5):398-403.

(3) Whincup P, Cook D, Papacosta O, Walker M, Perry I. Maternal factors and development of cardiovascular risk: evidence from a study of blood pressure in children. J Hum Hypertens 1994; 8(5):337-343.

(4) Bergel E, Haelterman E, Belizan J, Villar J, Carroli G. Perinatal factors associated with blood pressure during childhood. Am J Epidemiol 2000; 151(6):594-601.

(5) Belfort MB, Rifas-Shiman SL, Rich-Edwards JW, Kleinman KP, Oken E, Gillman MW. Maternal iron intake and iron status during pregnancy and child blood pressure at age 3 years. Int J Epidemiol 2008; 37(2):301-308.

(6) Brion MJ, Leary SD, Davey Smith G, McArdle HJ, Ness AR. Maternal anemia, iron intake in pregnancy, and offspring blood pressure in the Avon Longitudinal Study of Parents and Children. Am J Clin Nutr 2008; 88(4):1126-1133.

(7) Bo S, Menato G, Villois P, Gambino R, Cassader M, Cotrino I et al. Iron supplementation and gestational diabetes in midpregnancy. Am J Obstet Gynecol 2009; 201(2):158-6.

(8) Ziaei S, Norrozi M, Faghihzadeh S, Jafarbegloo E. A randomised placebo-controlled trial to determine the effect of iron supplementation on pregnancy outcome in pregnant women with haemoglobin greater than or = 13.2 g/dl. BJOG 2007; 114(6):684-688.

(9) Lawlor DA, Fraser A, Lindsay RS, Ness A, Dabelea D, Catalano P et al. Association of existing diabetes, gestational diabetes and glycosuria in pregnancy with macrosomia and offspring body mass index, waist and fat mass in later childhood: findings from a prospective pregnancy cohort. Diabetologia 2010; 53(1):89-97.