372 research outputs found
Rare copy number variants: a point of rarity in genetic risk for bipolar disorder and schizophrenia
Context: Recent studies suggest that copy number variation in the human genome is extensive and may play an important role in susceptibility to disease, including neuropsychiatric disorders such as schizophrenia and autism. The possible involvement of copy number variants (CNVs) in bipolar disorder has received little attention to date.
Objectives: To determine whether large (>100 000 base pairs) and rare (found in <1% of the population) CNVs are associated with susceptibility to bipolar disorder and to compare with findings in schizophrenia.
Design: A genome-wide survey of large, rare CNVs in a case-control sample using a high-density microarray.
Setting: The Wellcome Trust Case Control Consortium.
Participants: There were 1697 cases of bipolar disorder and 2806 nonpsychiatric controls. All participants were white UK residents.
Main Outcome Measures: Overall load of CNVs and presence of rare CNVs.
Results: The burden of CNVs in bipolar disorder was not increased compared with controls and was significantly less than in schizophrenia cases. The CNVs previously implicated in the etiology of schizophrenia were not more common in cases with bipolar disorder.
Conclusions: Schizophrenia and bipolar disorder differ with respect to CNV burden in general and association with specific CNVs in particular. Our data are consistent with the possibility that possession of large, rare deletions may modify the phenotype in those at risk of psychosis: those possessing such events are more likely to be diagnosed as having schizophrenia, and those without them are more likely to be diagnosed as having bipolar disorder
First, do no harm: time for a systems approach to address the problem of health-care-derived pharmaceutical pollution.
Methylenetetrahydrofolate Reductase Gene Variant (MTHFR C677T) and Migraine: A Case Control Study and Meta-analysis
Extent: 9p.Background: Migraine is a common disorder that often coexists with depression. While a functional polymorphism in methyleneterahydrofolate reductase gene (MTHFR C677T) has been implicated in depression; the evidence to support an association of MTHFR with migraine has been inconclusive. We aim to investigate the effect of this variant on propensity for migraine and to perform a systematic review and meta-analysis of studies of MTHFR and migraine to date. Methods: Individuals with migraine (n = 447) were selected from the Depression Case Control (DeCC) study to investigate the association between migraine and MTHFR C677T single nucleotide polymorphism (SNP) rs1801133 using an additive model compared to non-migraineurs adjusting for depression status. A meta-analysis was performed and included 15 studies of MTHFR and migraine. Results: MTHFR C677T polymorphism was associated with migraine with aura (MA) (OR 1.31, 95% CI 1.01-1.70, p = 0.039) that remained significant after adjusting for age, sex and depression status. A meta-analysis of 15 case-control studies showed that T allele homozygosity is significantly associated with MA (OR = 1.42; 95% CI, 1.10-1.82) and total migraine (OR = 1.37; 95% CI, 1.07-1.76), but not migraine without aura (OR = 1.16; 95% CI, 0.36-3.76). In studies of non-Caucasian population, the TT genotype was associated with total migraine (OR= 3.46; 95% CI, 1.22-9.82), whereas in studies of Caucasians this variant was associated with MA only (OR = 1.28; 95% CI, 1.002-1.63). Conclusions: MTHFR C677T is associated with MA in individuals selected for depression study. A meta-analysis of 15 studies supports this association and demonstrated effects across ethnic groups.Zainab Samaan, Daria Gaysina, Sarah Cohen-Woods, Nick Craddock, Lisa Jones, Ania Korszun, Mike Owen, Andrew Mente, Peter McGuffin and Anne Farme
Respiratory Evolution Facilitated the Origin of Pterosaur Flight and Aerial Gigantism
Pterosaurs, enigmatic extinct Mesozoic reptiles, were the first vertebrates to achieve true flapping flight. Various lines of evidence provide strong support for highly efficient wing design, control, and flight capabilities. However, little is known of the pulmonary system that powered flight in pterosaurs. We investigated the structure and function of the pterosaurian breathing apparatus through a broad scale comparative study of respiratory structure and function in living and extinct archosaurs, using computer-assisted tomographic (CT) scanning of pterosaur and bird skeletal remains, cineradiographic (X-ray film) studies of the skeletal breathing pump in extant birds and alligators, and study of skeletal structure in historic fossil specimens. In this report we present various lines of skeletal evidence that indicate that pterosaurs had a highly effective flow-through respiratory system, capable of sustaining powered flight, predating the appearance of an analogous breathing system in birds by approximately seventy million years. Convergent evolution of gigantism in several Cretaceous pterosaur lineages was made possible through body density reduction by expansion of the pulmonary air sac system throughout the trunk and the distal limb girdle skeleton, highlighting the importance of respiratory adaptations in pterosaur evolution, and the dramatic effect of the release of physical constraints on morphological diversification and evolutionary radiation
The bipolar disorder risk allele at CACNA1C also confers risk of recurrent major depression and of schizophrenia
Molecular genetic analysis offers opportunities to advance our understanding of the nosological relationship between psychiatric diagnostic categories in general, and the mood and psychotic disorders in particular. Strong evidence (P=7.0 × 10−7) of association at the polymorphism rs1006737 (within CACNA1C, the gene encoding the α-1C subunit of the L-type voltage-gated calcium channel) with the risk of bipolar disorder (BD) has recently been reported in a meta-analysis of three genome-wide association studies of BD, including our BD sample (N=1868) studied within the Wellcome Trust Case Control Consortium. Here, we have used our UK case samples of recurrent major depression (N=1196) and schizophrenia (N=479) and UK non-psychiatric comparison groups (N=15316) to examine the spectrum of phenotypic effect of the bipolar risk allele at rs1006737. We found that the risk allele conferred increased risk for schizophrenia (P=0.034) and recurrent major depression (P=0.013) with similar effect sizes to those previously observed in BD (allelic odds ratio ∼1.15). Our findings are evidence of some degree of overlap in the biological underpinnings of susceptibility to mental illness across the clinical spectrum of mood and psychotic disorders, and show that at least some loci can have a relatively general effect on susceptibility to diagnostic categories, as currently defined. Our findings will contribute to a better understanding of the pathogenesis of major psychiatric illness, and such knowledge should be useful in providing an etiological rationale for shaping psychiatric nosology, which is currently reliant entirely on descriptive clinical data
Osteological and Soft-Tissue Evidence for Pneumatization in the Cervical Column of the Ostrich (Struthio camelus) and Observations on the Vertebral Columns of Non-Volant, Semi-Volant and Semi-Aquatic Birds
© 2015 Apostolaki et al. This is an open access article distributed under the terms of the Creative Commons Attribution License [4.0], which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. The attached file is the published version of the article
Inside Post-Socialist Courts: The Determinants of Adjudicatory Outcomes in Slovenian Commercial Disputes
Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data
Abstract: Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers
Genomewide Association Scan of Suicidal Thoughts and Behaviour in Major Depression
Background
Suicidal behaviour can be conceptualised as a continuum from suicidal ideation, to suicidal attempts to completed suicide. In this study we identify genes contributing to suicidal behaviour in the depression study RADIANT.
Methodology/Principal Findings
A quantitative suicidality score was composed of two items from the SCAN interview. In addition, the 251 depression cases with a history of serious suicide attempts were classified to form a discrete trait. The quantitative trait was correlated with younger onset of depression and number of episodes of depression, but not with gender. A genome-wide association study of 2,023 depression cases was performed to identify genes that may contribute to suicidal behaviour. Two Munich depression studies were used as replication cohorts to test the most strongly associated SNPs. No SNP was associated at genome-wide significance level. For the quantitative trait, evidence of association was detected at GFRA1, a receptor for the neurotrophin GDRA (p = 2e-06). For the discrete trait of suicide attempt, SNPs in KIAA1244 and RGS18 attained p-values of <5e-6. None of these SNPs showed evidence for replication in the additional cohorts tested. Candidate gene analysis provided some support for a polymorphism in NTRK2, which was previously associated with suicidality.
Conclusions/Significance
This study provides a genome-wide assessment of possible genetic contribution to suicidal behaviour in depression but indicates a genetic architecture of multiple genes with small effects. Large cohorts will be required to dissect this further
First, do no harm: time for a systems approach to address the problem of health-care-derived pharmaceutical pollution
This is the final version. Available on open access from Elsevier via the DOI in this recor
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