Ayla Arslan

Genes, Brains, and Behavior: Imaging Genetics for Neuropsychiatric Disorders

The majority of neuropsychiatric disorders show a strong degree of heritability, yet little is known about molecular factors involved in the pathophysiology of diseases like schizophrenia. After a brief historical introduction into the current understanding of neuropsychiatric disorders, the aim of this study is to discuss imaging genetics as a strategy to explore the pathophysiology of neuropsychiatric disorders. The candidate gene approach of imaging genetics is used for validation/replication studies of genes, whereas the hypothesis-free, noncandidate gene approach appears to be a tool for gene discovery. Besides, integration of environmental factors into neuroimaging begins to converge on neuroimaging studies of genetic variation. In the light of data from other avenues such as animal experimentation, these developments show a model of interdisciplinary research, which may lead to identifying markers for neuropsychiatric disorders.

Imaging genetics of schizophrenia in the post-GWAS era

ABSTRACT Imaging genetics is a research methodology studying the effect of genetic variation on brain structure, function, behavior, and risk for psychopathology. Since the early 2000s, imaging genetics has been increasingly used in the research of schizophrenia (SZ). SZ is a severe mental disorder with no precise knowledge of its underlying neurobiology, however, new genetic and neurobiological data generate a climate for new avenues. The accumulating data of genome wide association studies (GWAS) continuously decode SZ risk genes. Global neuroimaging consortia produce collections of brain phenotypes from tens of thousands of people. In this context, imaging genetics will be strategically important both for the validation and discovery of SZ related findings. Thus, the study of GWAS supported risk variants as candidate genes to validate by neuroimaging is one trend. The study of epigenetic differences in relation to variations of brain phenotypes and the study of large scale multivariate analysis of genome wide and brain wide associations are other trends. While these studies hold a big potential for understanding the neurobiology of SZ, the problem of reproducibility appears as a major challenge, which requires standardizations in study designs and compensations of methodological limitations such as sensitivity and specificity. On the other hand, advancements of neuroimaging, optical and electron microscopy along with the use of genetically encoded fluorescent probes and robust statistical approaches will not only catalyze integrative methodologies but also will help better design the imaging genetics studies. In this invited paper, I will discuss the current perspective of imaging genetics and emerging opportunities of SZ research.

Application of Neuroimaging in the Diagnosis and Treatment of Depression

Diagnosis of depression is based on clinical parameters which may be clinically reliable but lack biological validity leading to problems of differential diagnosis or treatment. Thus, there is a need for biologically relevant criteria for better diagnosis and treatment of depression. Accumulating neuroimaging studies suggest potential biomarkers such as metabolic activity and structural or functional connectivity within the limbic-cortical circuitries that may serve for this purpose. However, employment of such neuroimaging measures as biomarkers in a clinical setting still requires further investigation. While there are some converging results, a major challenge in the field is the inconsistencies across multiple studies. This is probably due to the heterogeneous patient groups used in these studies, the variety of tasks or methodologies used during neuroimaging, and the different types of treatments or problems associated with poor data quality, which require better statistical approaches. As these problems are likely addressed, neuroimaging biomarkers can be established in the future to facilitate significant improvements in the diagnosis and treatment of depression.

Distinct roles of gamma-aminobutyric acid type A receptor subtypes: A focus on phasic and tonic inhibition

channels responsible for the inhibitory transmission in the vertebrate central nervous system (reviewed in Lester et al., 2004; Unwin, 2005; Sine & Engel, 2006). These GABA-gated heteropentameric channels are permeable to HCO3and Clions (reviewed by Sieghart and Sperk 2002). Depending on the intracellular Clconcentration, GABAAR activation can lead to Clinflux or efflux. In adult neurons, upon activation of the receptor by GABA binding, Clusually moves into the cell, causing a strong inhibitory hyperpolarization (Kaila et al., 1997; Rivera, et al., 2005).

Effect of ovarian hormones on memory suppression

Several studies suggest that memory suppression in humans occur as an active process of executive control, mediated by regions of prefrontal cortex, which is a substrate for ovarian hormones. However the effect of ovarian hormones on this process is not known. In order to address this question, we utilized the quantitative analysis of ovarian hormones in combination with think (T) /no think (NT) paradigm in a within-subject design study. We compared the rate of memory control between the follicular (low estrogen and progesteron) and mid-luteal (high estrogen and progesteron) phases of regularly cycling healthy women. Our data demonstrate that during midluteal phase, 63.6 % of subjects are able to ‘suppress’ or actively forget (significantly less % recall below the baseline) previously learned word pairs in the ‘NT condition; i.e., not to think the target word associated with the cue word’. However during the follicular phase there was no effect of ‘NT condition’ on the active forgeting of word pairs below the baseline as assesed by the memory test applied after the T/NT procedure. Thus, our results indicate the modulatory effect of ovarian hormones during the process of active forgetting.

Specifying molecular determinants of the subcellular targeting of synaptic and extrasynaptic GABA A receptors

How GABA-A receptor subtypes segregate so precisely to different subcellular locations is not understood. In this study, I have expressed the recombinant g2 and d GABA-A receptor subunits in cultured hippocampal neurons to analyze the differential cell surface expression and sub-membrane segregation of synaptic and extrasynaptic GABA-A receptors. My data demonstrate that the synaptic targeting of g2-containing GABA-A receptors does not depend on the cytoplasmic TM3-TM4 domain of the g2 subunit. This result was actually surprising, until Alldred et al published their work last year (2005) showing that the synaptic localization of receptors with the g2 subunit requires the TM4 domain rather than the large TM3-TM4 cytoplasmic loop. The premise of our work, when we started, was that the loop region would be responsible. On the other hand, I showed here that the TM3-TM4 cytoplasmic domain of the d subunit is either a factor for the extra-synaptic clustering of the d containing GABAA receptors (this would be an active mechanism) or alternatively that this loop region may not contain any information at all on receptor targeting, and subunits with this domain may simply lack sufficient “information” to be placed in synapses (passive exclusion). I cannot currently distinguish between these two possibilities. Nevertheless, by comparing the d subunit TM3-TM4 loop amino acid sequences across the whole span of vertebrate evolution, I discovered that the loop was remarkably conserved. This would suggest that the loop’s tertiary structure and specific proteins that bind to it are important for some function(s)of d-containing receptors. A passive exclusion mechanism might have lead to a degeneration of the loop sequence.

Even black-and-white bananas look yellow

Experiment reveals how expectation interferes with perception.