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Sleep disturbances are important symptoms to monitor in people with bipolar disorder (BD) but the precise longitudinal relationships between sleep and mood remain unclear. We aimed to examine associations between stable and dynamic aspects of sleep and mood in people with BD, and assess individual differences in the strength of these associations.
Participants (N = 649) with BD-I (N = 400) and BD-II (N = 249) provided weekly self-reports of insomnia, depression and (hypo)mania symptoms using the True Colours online monitoring tool for 21 months. Dynamic structural equation models were used to examine the interplay between weekly reports of insomnia and mood. The effects of clinical and demographic characteristics on associations were also assessed.
Increased variability in insomnia symptoms was associated with increased mood variability. In the sample as a whole, we found strong evidence of bidirectional relationships between insomnia and depressive symptoms but only weak support for bidirectional relationships between insomnia and (hypo)manic symptoms. We found substantial variability between participants in the strength of prospective associations between insomnia and mood, which depended on age, gender, bipolar subtype, and a history of rapid cycling.
Our results highlight the importance of monitoring sleep in people with BD. However, researchers and clinicians investigating the association between sleep and mood should consider subgroup differences in this relationship. Advances in digital technology mean that intensive longitudinal data on sleep and mood are becoming increasingly available. Novel methods to analyse these data present an exciting opportunity for furthering our understanding of BD.
Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.
To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.
Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.
Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.
AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.
Fetal growth restriction (FGR) can be defined as the failure of the fetus to meet its genetically predetermined growth potential  and is associated with significant fetal and perinatal morbidity and mortality. In addition, there is evidence to suggest a longer-term impact of FGR on childhood neurodevelopmental outcomes  and cardiovascular and metabolic diseases that manifest in adulthood . However, predicting FGR is not straightforward and methods for screening and diagnosis are imprecise. In the UK and USA, ultrasound scans in the second half of pregnancy are not performed routinely but targeted at women considered to be at risk for FGR, where high risk is identified by maternal characteristics (including anthropometry and pre-existing disease), the development of complications, or clinical suspicion based on being ‘small for dates’ on physical examination. For practical purposes, FGR may be suspected if biometric measurements are below a given threshold of the distribution in the population, typically <10th, 5th or 3rd centile for gestational age, or if there is a reduction in growth velocity (‘crossing centiles’) from previous scans . The difficulty with using biometry alone is that it does not differentiate between the growth-restricted fetus affected by placental insufficiency, and the healthy, constitutionally small fetus. Therefore, additional measures may be employed to diagnose placental dysfunction, such as Doppler studies of the fetal and uteroplacental circulation, and analysis of maternal serum biomarkers. At present, the only treatment available for FGR is to expedite delivery, but at preterm gestations this can also can cause harm. However, new genomics-based research could help us better understand the etiology of growth restriction and identify more accurate diagnostic biomarkers or potential therapeutic targets. This chapter will focus on current practice in screening for and intervention in FGR and will also consider new developments and the future of the field.
This chapter summarizes some of the most important aspects of current knowledge in relation to clinical assessment of placentation. Ultrasound allows the assessment of some physical characteristics of the placenta, such as thickness and, more recently using 3D methods, volume. Uterine artery Doppler flow velocimetry can be used to assess the resistance to blood flow in the uterine circulation. First-trimester maternal serum levels of pregnancy-associated plasma protein A (PAPP-A) have been widely studied in the assessment of Down's syndrome risk. Clinical manifestations of serious complications of pregnancy, such as growth restriction, pre-eclampsia and stillbirth are preceded by abnormalities in clinical biomarkers of placentation. Several large-scale prospective cohort studies are in progress which aims to improve on currently available methods for clinical detection of impaired placentation. Multiple lines of evidence indicate an important role for abnormal placentation in the pathophysiology of many of the most important complications of pregnancy.
At the time of the discovery of the physiological changes of spiral arteries in the pregnant uterus, Brosens and colleagues suggested that these changes result from the destructive action of the invading trophoblasts on the vascular smooth muscle and the elastic membrane. This chapter reiterates the main findings regarding the successive spiral artery remodeling steps. It seems appropriate to relate the time-course of the vascular remodeling process to the new insights in uteroplacental flow changes during this pregnancy period. In preeclampsia, trophoblast-associated remodeling is restricted to decidual spiral arteries throughout the placental bed. Spiral artery conversion is obviously important for safeguarding an adequate maternal blood supply to the placenta. Deep trophoblast invasion and spiral artery remodeling of the inner 'junctional zone' myometrium is a feature of normal human pregnancy, while in preeclampsia and maybe in other pregnancy complications this process may be seriously impaired.
Psychiatric phenotypes are currently defined according to sets of
descriptive criteria. Although many of these phenotypes are heritable, it
would be useful to know whether any of the various diagnostic categories
in current use identify cases that are particularly helpful for
To use genome-wide genetic association data to explore the relative
genetic utility of seven different descriptive operational diagnostic
categories relevant to bipolar illness within a large UK case–control
bipolar disorder sample.
We analysed our previously published Wellcome Trust Case Control
Consortium (WTCCC) bipolar disorder genome-wide association data-set,
comprising 1868 individuals with bipolar disorder and 2938 controls
genotyped for 276 122 single nucleotide polymorphisms (SNPs) that met
stringent criteria for genotype quality. For each SNP we performed a test
of association (bipolar disorder group v. control group) and used the
number of associated independent SNPs statistically significant at
P<0.00001 as a metric for the overall genetic
signal in the sample. We next compared this metric with that obtained
using each of seven diagnostic subsets of the group with bipolar
disorder: Research Diagnostic Criteria (RDC): bipolar I disorder; manic
disorder; bipolar II disorder; schizoaffective disorder, bipolar type;
DSM–IV: bipolar I disorder; bipolar II disorder; schizoaffective
disorder, bipolar type.
The RDC schizoaffective disorder, bipolar type (v.
controls) stood out from the other diagnostic subsets as having a
significant excess of independent association signals
(P<0.003) compared with that expected in samples of
the same size selected randomly from the total bipolar disorder group
data-set. The strongest association in this subset of participants with
bipolar disorder was at rs4818065 (P = 2.42 ×
10–7). Biological systems implicated included gamma
amniobutyric acid (GABA)A receptors. Genes having at least one
associated polymorphism at P<10–4 included
B3GALTS, A2BP1, GABRB1, AUTS2, BSN, PTPRG, GIRK2 and
Our findings show that individuals with broadly defined bipolar
schizoaffective features have either a particularly strong genetic
contribution or that, as a group, are genetically more homogeneous than
the other phenotypes tested. The results point to the importance of using
diagnostic approaches that recognise this group of individuals. Our
approach can be applied to similar data-sets for other psychiatric and
Early results from the SAGE-SMC (Surveying the Agents of Galaxy Evolution in the tidally-disrupted, low-metallicity Small Magellanic Cloud) Spitzer legacy program are presented. These early results concentrate on the SAGE-SMC MIPS observations of the SMC Tail region. This region is the high H i column density portion of the Magellanic Bridge adjacent to the SMC Wing. We detect infrared dust emission and measure the gas-to-dust ratio in the SMC Tail and find it similar to that of the SMC Body. In addition, we find two embedded cluster regions that are resolved into multiple sources at all MIPS wavelengths.
The immediate clinical consequences and associations of pre-eclampsia are the subject of intense study and are reviewed in depth throughout this volume. It is natural for any woman who experiences a hypertensive disorder in pregnancy to enquire what implications this has, if any, for her future health. While the long-term outcome of women who experience pre-eclampsia has been the subject of research, there are still major uncertainties regarding this area due to the inherent problems of long-term longitudinal clinical studies. The aim of this chapter is to summarize the recent evidence regarding the implications of pre-eclampsia occurring during pregnancy for a woman's health in later life. Moreover, methodological issues related to addressing this research question will also be reviewed both to assist interpretation of the existing literature and to provide guidance for how future studies might be conducted.
Methodological issues in determining long-term associations with pre-eclampsia
Epidemiological studies generally aim to quantify the association between developing a given disease and some characteristic in a population. The characteristic can take many forms, such as a blood test, environmental exposure or socio-economic factor. The first step in any study is to determine whether the outcome and exposure are associated to a degree which is greater than expected by chance. Any analysis assumes that a sufficient number of individuals were studied to allow detection of an association, were any to exist. Having demonstrated an association, the next step is to determine whether the association is likely to be causal.