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      Evaluating Historical Candidate Genes for Schizophrenia

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          Abstract

          Prior to the genome-wide association era, candidate gene studies were a major approach in schizophrenia genetics. In this invited review, we consider the current status of 25 historical candidate genes for schizophrenia (e.g., COMT, DISC1, DTNBP1, and NRG1). The initial study for 24 of these genes explicitly evaluated common variant hypotheses about schizophrenia. Our evaluation included a meta-analysis of the candidate gene literature, incorporation of the results of the largest genomic study yet published for schizophrenia, ratings from informed researchers who have published on these genes, and ratings from 24 schizophrenia geneticists. On the basis of current empirical evidence and mostly consensual assessments of informed opinion, it appears that the historical candidate gene literature did not yield clear insights into the genetic basis of schizophrenia. A likely reason why historical candidate gene studies did not achieve their primary aims is inadequate statistical power. However, the considerable efforts embodied in these early studies unquestionably set the stage for current successes in genomic approaches to schizophrenia.

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          Most cited references67

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          Systematic meta-analyses of Alzheimer disease genetic association studies: the AlzGene database.

          The past decade has witnessed hundreds of reports declaring or refuting genetic association with putative Alzheimer disease susceptibility genes. This wealth of information has become increasingly difficult to follow, much less interpret. We have created a publicly available, continuously updated database that comprehensively catalogs all genetic association studies in the field of Alzheimer disease (http://www.alzgene.org). We performed systematic meta-analyses for each polymorphism with available genotype data in at least three case-control samples. In addition to identifying the epsilon4 allele of APOE and related effects, we pinpointed over a dozen potential Alzheimer disease susceptibility genes (ACE, CHRNB2, CST3, ESR1, GAPDHS, IDE, MTHFR, NCSTN, PRNP, PSEN1, TF, TFAM and TNF) with statistically significant allelic summary odds ratios (ranging from 1.11-1.38 for risk alleles and 0.92-0.67 for protective alleles). Our database provides a powerful tool for deciphering the genetics of Alzheimer disease, and it serves as a potential model for tracking the most viable gene candidates in other genetically complex diseases.
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            Effect of COMT Val108/158 Met genotype on frontal lobe function and risk for schizophrenia.

            Abnormalities of prefrontal cortical function are prominent features of schizophrenia and have been associated with genetic risk, suggesting that susceptibility genes for schizophrenia may impact on the molecular mechanisms of prefrontal function. A potential susceptibility mechanism involves regulation of prefrontal dopamine, which modulates the response of prefrontal neurons during working memory. We examined the relationship of a common functional polymorphism (Val(108/158) Met) in the catechol-O-methyltransferase (COMT) gene, which accounts for a 4-fold variation in enzyme activity and dopamine catabolism, with both prefrontally mediated cognition and prefrontal cortical physiology. In 175 patients with schizophrenia, 219 unaffected siblings, and 55 controls, COMT genotype was related in allele dosage fashion to performance on the Wisconsin Card Sorting Test of executive cognition and explained 4% of variance (P = 0.001) in frequency of perseverative errors. Consistent with other evidence that dopamine enhances prefrontal neuronal function, the load of the low-activity Met allele predicted enhanced cognitive performance. We then examined the effect of COMT genotype on prefrontal physiology during a working memory task in three separate subgroups (n = 11-16) assayed with functional MRI. Met allele load consistently predicted a more efficient physiological response in prefrontal cortex. Finally, in a family-based association analysis of 104 trios, we found a significant increase in transmission of the Val allele to the schizophrenic offspring. These data suggest that the COMT Val allele, because it increases prefrontal dopamine catabolism, impairs prefrontal cognition and physiology, and by this mechanism slightly increases risk for schizophrenia.
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              Meta-analysis of genetic association studies supports a contribution of common variants to susceptibility to common disease.

              Association studies offer a potentially powerful approach to identify genetic variants that influence susceptibility to common disease, but are plagued by the impression that they are not consistently reproducible. In principle, the inconsistency may be due to false positive studies, false negative studies or true variability in association among different populations. The critical question is whether false positives overwhelmingly explain the inconsistency. We analyzed 301 published studies covering 25 different reported associations. There was a large excess of studies replicating the first positive reports, inconsistent with the hypothesis of no true positive associations (P < 10(-14)). This excess of replications could not be reasonably explained by publication bias and was concentrated among 11 of the 25 associations. For 8 of these 11 associations, pooled analysis of follow-up studies yielded statistically significant replication of the first report, with modest estimated genetic effects. Thus, a sizable fraction (but under half) of reported associations have strong evidence of replication; for these, false negative, underpowered studies probably contribute to inconsistent replication. We conclude that there are probably many common variants in the human genome with modest but real effects on common disease risk, and that studies using large samples will convincingly identify such variants.
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                Author and article information

                Journal
                9607835
                20545
                Mol Psychiatry
                Mol. Psychiatry
                Molecular psychiatry
                1359-4184
                1476-5578
                7 January 2015
                10 March 2015
                May 2015
                01 November 2015
                : 20
                : 5
                : 555-562
                Affiliations
                [1 ]Center for Psychiatric Genomics, Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
                [2 ]Institute of Biological Psychiatry, MHC Sct. Hans, Mental Health Services Copenhagen, Denmark; Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark; The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Denmark
                [3 ]Division of Psychiatric Genomics, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Institute for Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
                [4 ]MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK; National Centre for Mental Health, Cardiff University, Cardiff, Wales
                [5 ]Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA; Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA, USA; Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, The Netherlands
                [6 ]Neuropsychiatric Genetics Research Group, Department of Psychiatry, Trinity College Dublin, Ireland
                [7 ]Division of Medical Genetics, Department of Biomedicine, University Basel, Basel, Switzerland, Institute of Human Genetics, University of Bonn, Bonn, Germany; Department of Genomics, Life and Brain Center, Bonn, Germany
                [8 ]Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
                Author notes
                Correspond with Dr Sullivan: Department of Genetics, CB#7264, 5097 Genomic Medicine, University of North Carolina, Chapel Hill, NC, 27599-7264, USA. Voice: +919-966-3358, FAX: +919-966-3630, pfsulliv@ 123456med.unc.edu
                Article
                NIHMS653267
                10.1038/mp.2015.16
                4414705
                25754081
                baebd23e-6c5b-48e2-a8f5-695f6fc46f33
                History
                Categories
                Article

                Molecular medicine
                schizophrenia,genetics,candidate gene,review,meta-analysis
                Molecular medicine
                schizophrenia, genetics, candidate gene, review, meta-analysis

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