283 research outputs found
Distribution of hospital admissions in a middle-income country of the African region
Introduction: Few studies have reported the distribution of all hospital admissions at the entire country level in low and middle-income countries (LMICs). We examined this question in Seychelles, a rapidly developing small island state in the Africa region, in which access to health care is provided free of charge to all inhabitants through a national health system and all hospital admissions are routinely registered. Methods: Based on all admissions to all hospitals in Seychelles in 2005-2008, we calculated the distribution of hospital admissions, age at admission, length of stay and bed occupancy (i.e. cumulated number of patients * number of days spent in all hospitals) according to both hospital departments and broad causes of diseases (using codes of the ICD-10 classification of diseases). Results: Bed occupancy was largest in the surgical wards (36.7% of all days spent in all hospitals), followed by the medical wards (24.3%), gynecology/obstetrics wards (18.4%), pediatric wards (11.2%), and psychiatric wards (7.2%). According to broad causes of diseases/conditions, bed occupancy was highest for obstetrics/gynecology conditions (19.9% of all days spent at hospital), mental diseases (8.6%), cardiovascular diseases (8.1%), upper aerodigestive/pulmonary diseases (8%), infectious/parasitic diseases (8%), gastrointestinal diseases (7.2%), and urogenital diseases (6.7%). Adjusted to 100'000 population, 153 hospital beds are needed every day, including 31 for obstetrics/gynecologic conditions, 13 for mental diseases, 12 for cardiovascular diseases, 12 for upper aerodigestive diseases, 12 for infectious/parasitic diseases, and 11 for gastrointestinal diseases. Conclusion: Our findings give a good indication of the overall distribution of admissions according to both hospital departments and broad causes of diseases in a middle-income country. These findings provide important information for health care planning at the national leve
The genetics of the mood disorder spectrum: genome-wide association analyses of over 185,000 cases and 439,000 controls
The Genetics of the Mood Disorder Spectrum: Genome-wide Association Analyses of More Than 185,000 Cases and 439,000 Controls
Background:
Mood disorders (including major depressive disorder and bipolar disorder) affect 10% to 20% of the population. They range from brief, mild episodes to severe, incapacitating conditions that markedly impact lives. Multiple approaches have shown considerable sharing of risk factors across mood disorders despite their diagnostic distinction.
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Methods:
To clarify the shared molecular genetic basis of major depressive disorder and bipolar disorder and to highlight disorder-specific associations, we meta-analyzed data from the latest Psychiatric Genomics Consortium genome-wide association studies of major depression (including data from 23andMe) and bipolar disorder, and an additional major depressive disorder cohort from UK Biobank (total: 185,285 cases, 439,741 controls; nonoverlapping N = 609,424).
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Results:
Seventy-three loci reached genome-wide significance in the meta-analysis, including 15 that are novel for mood disorders. More loci from the Psychiatric Genomics Consortium analysis of major depression than from that for bipolar disorder reached genome-wide significance. Genetic correlations revealed that type 2 bipolar disorder correlates strongly with recurrent and single-episode major depressive disorder. Systems biology analyses highlight both similarities and differences between the mood disorders, particularly in the mouse brain cell types implicated by the expression patterns of associated genes. The mood disorders also differ in their genetic correlation with educational attainmentâthe relationship is positive in bipolar disorder but negative in major depressive disorder.
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Conclusions:
The mood disorders share several genetic associations, and genetic studies of major depressive disorder and bipolar disorder can be combined effectively to enable the discovery of variants not identified by studying either disorder alone. However, we demonstrate several differences between these disorders. Analyzing subtypes of major depressive disorder and bipolar disorder provides evidence for a genetic mood disorders spectrum
Time-dependent genetic effects on gene expression implicate aging processes
Gene expression is dependent on genetic and environmental factors. In the last decade, a large body of research has significantly improved our understanding of the genetic architecture of gene expression. However, it remains unclear whether genetic effects on gene expression remain stable over time. Here, we show, using longitudinal whole-blood gene expression data from a twin cohort, that the genetic architecture of a subset of genes is unstable over time. In addition, we identified 2213 genes differentially expressed across time points that we linked with aging within and across studies. Interestingly, we discovered that most differentially expressed genes were affected by a subset of 77 putative causal genes. Finally, we observed that putative causal genes and down-regulated genes were affected by a loss of genetic control between time points. Taken together, our data suggest that instability in the genetic architecture of a subset of genes could lead to widespread effects on the transcriptome with an aging signature
Cis and Trans Effects of Human Genomic Variants on Gene Expression
This work was funded by the Louis-Jeantet Foundation (http://www.jeantet.ch/), the European Research Council (Grant ID: 260927 http://erc.europa.eu/), the Swiss National Foundation (Grant ID: 130342 http://www.snf.ch), NCCR Frontiers In Genetics (http://www.frontiers-in-genetics.org), the UK Medical Research Council (http://www.mrc.ac.uk) and the Wellcome Trust (Grant ID: 092731).
Genetic identification of cell types underlying brain complex traits yields insights into the etiology of Parkinson's disease.
Genome-wide association studies have discovered hundreds of loci associated with complex brain disorders, but it remains unclear in which cell types these loci are active. Here we integrate genome-wide association study results with single-cell transcriptomic data from the entire mouse nervous system to systematically identify cell types underlying brain complex traits. We show that psychiatric disorders are predominantly associated with projecting excitatory and inhibitory neurons. Neurological diseases were associated with different cell types, which is consistent with other lines of evidence. Notably, Parkinson's disease was genetically associated not only with cholinergic and monoaminergic neurons (which include dopaminergic neurons) but also with enteric neurons and oligodendrocytes. Using post-mortem brain transcriptomic data, we confirmed alterations in these cells, even at the earliest stages of disease progression. Our study provides an important framework for understanding the cellular basis of complex brain maladies, and reveals an unexpected role of oligodendrocytes in Parkinson's disease
Coordinated effects of sequence variation on DNA binding, chromatin structure, and transcription.
DNA sequence variation has been associated with quantitative changes in molecular phenotypes such as gene expression, but its impact on chromatin states is poorly characterized. To understand the interplay between chromatin and genetic control of gene regulation, we quantified allelic variability in transcription factor binding, histone modifications, and gene expression within humans. We found abundant allelic specificity in chromatin and extensive local, short-range, and long-range allelic coordination among the studied molecular phenotypes. We observed genetic influence on most of these phenotypes, with histone modifications exhibiting strong context-dependent behavior. Our results implicate transcription factors as primary mediators of sequence-specific regulation of gene expression programs, with histone modifications frequently reflecting the primary regulatory event
Obesity remodels activity and transcriptional state of a lateral hypothalamic brake on feeding
The current obesity epidemic is a major worldwide health concern. Despite the consensus that the brain regulates energy homeostasis, the neural adaptations governing obesity are unknown. Using a combination of high-throughput single-cell RNA sequencing and longitudinal in vivo two-photon calcium imaging, we surveyed functional alterations of the lateral hypothalamic area (LHA) - a highly conserved brain region that orchestrates feeding - in a mouse model of obesity. The transcriptional profile of LHA glutamatergic neurons was affected by obesity, exhibiting changes indicative of altered neuronal activity. Encoding properties of individual LHA glutamatergic neurons were then tracked throughout obesity, revealing greatly attenuated reward responses.These data demonstrate how diet disrupts the function of an endogenous feeding suppression system to promote overeating and obesity
Comparative genomic evidence for the involvement of schizophrenia risk genes in antipsychotic effects
Genome-wide association studies (GWAS) for schizophrenia have identified over 100 loci encoding >500 genes. It is unclear whether any of these genes, other than dopamine receptor D 2, are immediately relevant to antipsychotic effects or represent novel antipsychotic targets. We applied an in vivo molecular approach to this question by performing RNA sequencing of brain tissue from mice chronically treated with the antipsychotic haloperidol or vehicle. We observed significant enrichments of haloperidol-regulated genes in schizophrenia GWAS loci and in schizophrenia-associated biological pathways. Our findings provide empirical support for overlap between genetic variation underlying the pathophysiology of schizophrenia and the molecular effects of a prototypical antipsychotic
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