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John Wemmie, MD, PhD, professor in the Department of Psychiatry at the University of Iowa, is interested in the role of brain pH and acid-sensing ion channels in brain function and behavior. This work has led to the discovery of critical roles for brain pH in synaptic plasticity, anxiety, and depression-related behaviors in mice. Current projects include investigating the synaptic mechanisms for acid-sensing ion channel action and also translating these discoveries to human behavior and brain function. For example, his laboratory is using non-invasive pH-sensitive magnetic resonance imaging to investigate the roles of brain pH in psychiatric illnesses such as panic disorder and bipolar affective disorder.
The Potash lab is interested in the DNA sequence and methylation variation that confer susceptibility to depression and bipolar disorder. Family, twin, and adoption studies have made it abundantly clear that these disorders are substantially heritable, but only a very small proportion of that heritability has thus far been explained molecularly. Similarly, the environment clearly plays a role in the etiology of depression, but the molecular basis of that role remains undefined. We are interested in determining the common and rare genetic variants involved in mood disorders risk. We are also investigating DNA methylation variation across the genome, looking for changes induced by stress that might play a role in depression.
The goal of research in the Wassink Laboratory is to identify genes that underlie susceptibility to a variety of psychiatric disorders, with our primary focus being autism. We use a variety of approaches in this endeavor, including positional cloning, sophisticated cytogenetic analyses, various microarray platforms, and candidate disease gene screening. We perform these studies in DNA obtained from numerous independent samples of families with multiple autistic individuals. We are also equipped to assess the function and expression of identified disease genes using an array of molecular and animal model techniques. We are also actively investigating the genetics of panic disorder and schizophrenia. The panic disorder work uses traditional positional cloning methods and a sample of moderate to large panic disorder pedigrees. The schizophrenia genetics research is performed in association with the Department of Psychiatry's Mental Health Clinical Research Center. We collect DNA from individuals with schizophrenia, their families, and psychiatrically normal control subjects. All of these individuals participate in protocols that gather data from a wide variety of research domains, including functional and structural brain imaging, cognitive testing, disease phenomenology, longitudinal progression of disease, etc. The goal with the schizophrenia sample, therefore, is to investigate relationships between genetic information and these other types of data. Extensive additional resources and expertise are available to us here at Iowa through our collaborations with the Center for Statistical Genetics, the UIHC Cytogenetics laboratory, and the Center for Bioinformatics and Computational Biology.
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The Pieper Laboratory focuses on the discovery of new treatment options for neuropsychiatric disease using pharamcologic approaches in animal models. This approach is characterized by the discovery of the P7C3-series of neuroprotective molecules, which offer mitchondrial protection in many preclinical models of neurodegeneration. The Pieper Laboratory is also investigating new treatment approaches for autism, anxiety, and obsessive compulsive disorder.
The primary goal of the Willour lab is to identify genetic and epigenetic risk factors for suicidal behavior. Family, twin, and adoption studies make clear that suicidal behavior has a substantial heritable component. While there is evidence that this heritability is accounted for in part by a liability to mood disorder, other evidence suggests an independent heritable facet that may cut across multiple psychiatric disorders. In an effort to better understand the biological basis of this behavior, we have conducted a genome-wide association study (GWAS) using attempted suicide as the phenotype, an effort that identified a promising association signal on 2p25 as well as candidate genes implicating the Wnt signaling pathway and excitatory neurotransmission. These findings have prompted us to launch a large-scale whole exome sequencing project, with the goal of identifying functional variants associated with suicidal behavior on 2p25 and throughout the genome. Environmental stressors, such as child abuse and early parental loss, are also known to play important roles in triggering suicidal behavior, likely through interaction with genetic vulnerability factors. With this in mind, we have begun an epigenetics project that involves assessing genome-wide methylation patterns in post-mortem brains of suicide completers and controls, with the goal of identifying differentially methylated candidate genes and regions associated with suicidal behavior.
The Shizhong Han Laboratory aims to dissect the genetic components of psychiatric disorders using cutting-edge genomic technologies, advanced statistical genetic methods, and multidisciplinary approaches. In addition to gene mapping efforts for psychiatric disorders, we are also interested in developing novel statistical methods and computational tools to meet the challenges arising from big data.
The focus of research in the Lutter Laboratory is the bi-directional relationship between psychiatric disorders and metabolic diseases. In recent years, it has become increasingly recognized that a relationship exists between the development of certain psychiatric disorders, such as Major Depression, Anorexia Nervosa, and Obsessive Compulsive Disorder, and metabolic disturbances. We combine approaches of biochemistry, neuroscience, and human genetics to answer fundamental questions about the causation and treatment of psychiatric disorders with an emphasis on metabolic signaling pathways.
The Michaelson lab investigates how variation in the genome affects the development and function of the mind. Our experience in genome informatics and statistical learning enables us to develop predictive models of gene-phenotype relationships based on high-throughput biological data sets. These models serve a dual purpose: 1) they improve our diagnostic/prognostic capabilities and 2) they illuminate the biological mechanisms that underlie psychiatric conditions. We have a particular interest in conditions that manifest themselves in childhood, such as autism spectrum disorders (ASD), attention deficit hyperactivity disorder (ADHD), specific language impairment (SLI), and developmental coordination disorder (DCD). These and other related conditions show striking comorbidity, and investigating their interrelationships will accelerate our understanding of their roots and potential treatments.