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Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment.
To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder.
This study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi+Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework.
The best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data.
Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.
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.
In Europe, the incidence of psychotic disorder is high in certain migrant and minority ethnic groups (hence: ‘minorities’). However, it is unknown how the incidence pattern for these groups varies within this continent. Our objective was to compare, across sites in France, Italy, Spain, the UK and the Netherlands, the incidence rates for minorities and the incidence rate ratios (IRRs, minorities v. the local reference population).
The European Network of National Schizophrenia Networks Studying Gene–Environment Interactions (EU-GEI) study was conducted between 2010 and 2015. We analyzed data on incident cases of non-organic psychosis (International Classification of Diseases, 10th edition, codes F20–F33) from 13 sites.
The standardized incidence rates for minorities, combined into one category, varied from 12.2 in Valencia to 82.5 per 100 000 in Paris. These rates were generally high at sites with high rates for the reference population, and low at sites with low rates for the reference population. IRRs for minorities (combined into one category) varied from 0.70 (95% CI 0.32–1.53) in Valencia to 2.47 (95% CI 1.66–3.69) in Paris (test for interaction: p = 0.031). At most sites, IRRs were higher for persons from non-Western countries than for those from Western countries, with the highest IRRs for individuals from sub-Saharan Africa (adjusted IRR = 3.23, 95% CI 2.66–3.93).
Incidence rates vary by region of origin, region of destination and their combination. This suggests that they are strongly influenced by the social context.
The Northern Bald Ibis (NBI) Geronticus eremita, is an ‘Endangered’ bird species of which only very few wild breeding colonies have survived along the Atlantic coast of south-west Morocco. This paper analyses ecological conditions of the 72 breeding sites of the NBI that have been known since 1900 in Morocco. Characterisation of breeding sites is based on physical criteria (elevation above sea level, geomorphology, mean annual precipitation and types of landscape) as well as land use, vegetation cover, infrastructure and types of settlement within three perimeters (0–1 km, > 1–5 km and > 5–10(20) km) using Google Earth satellite images. Statistical analyses of the number of breeding pairs, fledglings and rainfall during different quarters of the year from 1994 to 2016 in the two remaining breeding sites in Souss-Massa National Park and Tamri showed expected patterns as well as unexpected differences between the two localities. Based on our findings and indications in the literature, we suggest general and specific recommendations for potential future translocation projects of the NBI. Based on the analysis of the 28 breeding colonies existing after 1977, two elements emerge as the most important prerequisites: a low level of disturbances at the breeding sites and adequate feeding areas at a reasonable distance of 5–15 km.
Passive seismology allows measurement of the structure of glaciers and ice sheets. However, most techniques used so far in this context are based on horizontally homogeneous media where parameters vary only with depth (1-D approximations), which are appropriate only for a subset of glaciers. Here, we analyze seismic noise records from three different types of glaciers (plateau, valley and avalanching glacier) to characterize the influence of the glacier geometry on the seismic wavefield. Using horizontal-to-vertical spectral ratios, polarization analysis and modal analysis, we show that the plateau glacier and the valley glacier can be seen as 1-D, whereas the relatively small avalanching glacier shows 3-D effects due to its bed topography and the deep crevasses. In principle, the techniques proposed here might allow monitoring such crevasses and their depth, and thus to constrain a key parameter of avalanching and calving glacier fronts.
The existence of multiple subclasses of type Ia supernovae (SNeIa) has been the subject of great debate in the last decade. In this work, we show how machine learning tools facilitate identification of subtypes of SNe Ia. Using Deep Learning for dimensionality reduction, we were capable of performing such identification in a parameter space of significantly lower dimension than its principal component analysis counterpart. This is evidence that the progenitor system and the explosion mechanism can be described with a small number of initial physical parameters. All tools used here are publicly available in the Python package DRACULA (Dimensionality Reduction And Clustering for Unsupervised Learning in Astronomy) and can be found within COINtoolbox (https://github.com/COINtoolbox/DRACULA).
This cross-sectional study seeks to (a) describe developmental correlates of sensory hyporesponsiveness to social and nonsocial stimuli, (b) determine whether hyporesponsiveness is generalized across contexts in children with autism relative to controls, and (c) test the associations between hyporesponsiveness and social communication outcomes. Three groups of children ages 11–105 months (N = 178; autism = 63, developmental delay = 47, typical development = 68) are given developmental and sensory measures including a behavioral orienting task (the Sensory Processing Assessment). Lab measures are significantly correlated with parental reports of sensory hyporesponsiveness. Censored regression models show that hyporesponsiveness decreased across groups with increasing mental age (MA). Group differences are significant but depend upon two-way interactions with MA and context (social and nonsocial). At a very young MA (e.g., 6 months), the autism group demonstrates more hyporesponsiveness to social and nonsocial stimuli (with larger effects for social) than developmental delay and typically developing groups, but at an older MA (e.g., 60 months) there are no significant differences. Hyporesponsiveness to social and nonsocial stimuli predicts lower levels of joint attention and language in children with autism. Generalized processes in attention disengagement and behavioral orienting may have relevance for identifying early risk factors of autism and for facilitating learning across contexts to support the development of joint attention and language.
Repeated administration of intravenous immunoglobulin (IVIG) to improve the course of multiple sclerosis (MS) has now been tested in almost all stages of the disease, although to a variable extent and with various study designs. To date, two clinical trials have tested the effects of IVIG on progressive forms of MS. The efficacy of IVIG has been explored in several stages and settings of MS ranging from attempts to ameliorate the acute attack via investigations on the effects of long term immunomodulation to attempts of restoration of fixed deficits. Due to the good tolerability of IVIG, it has been recommended as a possible means to lessen disease activity that may be seen after delivery in some MS patients. The side effects observed at lower dosages of IVIG have been uniformly minor and consisted primarily of headaches, malaise, or a transient rash.
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