After GWAS: Searching for Genetic Risk for Schizophrenia and Bipolar Disorder
ABSTRACT Ten years ago it was widely expected that the genetic basis of common disease would be resolved by genome-wide association studies (GWAS), large-scale studies in which the entire genome is covered by genetic markers. However, the bulk of heritable variance remains unexplained. The authors consider several alternative research strategies. For instance, whereas it has been hypothesized that a common disease is associated primarily with common genetic variants, it is now plausible that multiple rare variants each have a potent effect on disease risk and that they could accumulate to become a substantial component of common disease risk. This idea has become more appealing since the discovery that copy number variants (CNVs) are a substantial source of human mutations and are associated with multiple common diseases. CNVs are structural genomic variants consisting of microinsertions, microdeletions, and transpositions in the human genome. It has been argued that numerous rare CNVs are plausible causes of a substantial proportion of common disease, and rare CNVs have been found to be potent risk factors in schizophrenia and autism. Another approach is to "parse the genome," i.e., reanalyze subsets of current GWAS data, since the noise inherent in genome-wide approaches may be hiding valid associations. Lastly, technological advances and declining costs may allow large-scale genome-wide sequencing that would comprehensively identify all genetic variants. Study groups even larger than the 10,000 subjects in current meta-analyses would be required, but the outcomes may lead to resolution of our current dilemma in common diseases: Where is the missing heritability?
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ABSTRACT: Substantial evidence exists about emotion processing (EP) impairments in schizophrenia patients. However, whether these deficits are present primarily during psychosis (i.e., state dependent) or an integral part of the disorder (i.e., trait dependent) remains unclear. EP was assessed with the degraded facial affect recognition task in schizophrenia patients (N=521) and healthy controls (N=312) at baseline (T1) and after a three year follow-up (T2). In schizophrenia patients symptomatic remission was assessed with the Positive and Negative Syndrome Scale (PANSS) remission tool. Patients were divided into four groups: remission T1 and remission T2 (RR); remission T1 and non-remission T2 (RN); non-remission T1 and non-remission T2 (NN) and non-remission T1 and remission T2 (NR). Factorial repeated measures ANCOVA was used to compare EP performance over time between groups. Age, gender and general cognition were included as covariates. Schizophrenia patients performed worse than healthy controls on EP at T1 (p=0.001). The patients that were in symptomatic remission at both time points (the RR group) performed worse than the healthy controls at T2 (p<0.001). Significant group×time interactions were found between RR and RN (p=0.001), and between NR and RN (p=0.04), indicating a differential EP performance over time. No group×time interaction was found between NN and NR. The results show relatively poor EP performance in schizophrenia patients compared to healthy controls. EP performance in schizophrenia patients was associated with symptomatic remission. The results provide support for the hypothesis that EP deficits in schizophrenia are both state and trait dependent. Copyright © 2014 Elsevier B.V. All rights reserved.Schizophrenia Research 12/2014; 161(2-3). DOI:10.1016/j.schres.2014.11.027 · 4.43 Impact Factor
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ABSTRACT: Genomic research is one of the tools for elucidating the pathogenesis of diseases of global health relevance and paving the research dimension to clinical and public health translation. Recent advances in genomic research and technologies have increased our understanding of human diseases, genes associated with these disorders, and the relevant mechanisms. Genome-wide association studies (GWAS) have proliferated since the first studies were published several years ago and have become an important tool in helping researchers comprehend human variation and the role genetic variants play in disease. However, the need to expand the diversity of populations in GWAS has become increasingly apparent as new knowledge is gained about genetic variation. Inclusion of diverse populations in genomic studies is critical to a more complete understanding of human variation and elucidation of the underpinnings of complex diseases. In this review, we summarize the available data on GWAS in recent African ancestry populations within the western hemisphere (i.e. African Americans and peoples of the Caribbean) and continental African populations. Furthermore, we highlight ways in which genomic studies in populations of recent African ancestry have led to advances in the areas of malaria, HIV, prostate cancer, and other diseases. Finally, we discuss the advantages of conducting GWAS in recent African ancestry populations in the context of addressing existing and emerging global health conditions.Public Health Genomics 11/2014; 18(1). DOI:10.1159/000367962 · 2.46 Impact Factor
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ABSTRACT: Toxoplasma gondii is a widespread protozoan parasite infecting approximately one third of the world population. After proliferation of tachyzoites during the acute stage, the parasite forms tissue cysts in various anatomical sites including the Central Nervous tissue, and establishes a chronic infection. Clinical spectrum normally ranges from a completely asymptomatic infection to severe multi-organ involvement. Many studies have suggested T. gondii infection as a risk factor for the development of some neuropsychiatric disorders, particularly schizophrenia. During the last years, a potential link with other neurobiological diseases such as Parkinson disease and Alzheimer disease has also been suggested. This review will focus on neurobiological and epidemiological data relating infection with T. gondii to neuropsychiatric diseases. Copyright © 2015. Published by Elsevier B.V.Journal of the Neurological Sciences 02/2015; DOI:10.1016/j.jns.2015.02.028 · 2.26 Impact Factor