The Future of Psychiatric Research: Genomes and Neural Circuits

Abstract

The burden of neuropsychiatric illnesses is enormous. These conditions, which include schizophrenia, mood disorders, and autism, affect thought, emotions, and a person's very sense of self. Together, they are the leading cause of disability in North America and Europe and constitute 40% of all years lost to disability. In the United States, the cost in lost earnings due to psychiatric disease is estimated conservatively to be $200 billion per year ([ 1 ][1]). The burden to individuals, families, and society is all the more tragic because these illnesses typically begin early in life, are life-long, and damage the affected individuals' self-perception, productivity, and ability to relate to others. Unfortunately, there have been no major breakthroughs in the treatment of schizophrenia in the last 50 years and no major breakthroughs in the treatment of depression in the last 20 years ([ 2 ][2]). Over the last few decades, drug treatments have emerged that help a subset of these patients ([ 3 ][3]), but a sizable proportion are resistant to all currently available treatments. This heterogeneity points to the complexity of the underlying biology and underscores the urgent need for a more sophisticated understanding of the causes of these illnesses. ![Figure][4] Diffusion tensor imaging (DTI) of a normal adult brain depicting white matter pathways (15 directions, b = 800 mm/s2). This tool can be used to assess changes in neural connectivity associated with brain disorders. CREDIT: COURTESY OF R. C. WELSH AND J.-K. ZUBIETA/UNIVERSITY OF MICHIGAN Psychiatric disorders present a unique challenge, even relative to other brain disorders, such as Alzheimer's, Huntington's, or Parkinson's diseases, because for psychiatric disorders we know much less about underlying genetic, molecular, and cellular causes or even the primary anatomical sites of the brain defects. This frustrating lack of progress requires us to confront the complexity of the brain, especially in the context of higher-order functions, such as cognition and mood. This calls for a new perspective and a combination of novel tools and analytical methods. Illnesses such as schizophrenia, autism, and mood disorders are likely the result of disruptions of neural circuits, the functional ensembles of brain cells that mediate thought, feelings, and behavior. A defect in the development, anatomical structure, functional integration, or dynamics of such a circuit can lead to a constellation of symptoms. Given the complexity of neural circuits, there are many possible ways to disrupt them ([ 4 ][5]). Thousands of genes are involved in regulating neural development and function. It is not surprising, therefore, that disturbances in the structure and function of one or several of these genes can lead to broad and complex neuropsychiatric phenotypes. This complexity explains the high prevalence of neuropsychiatric disorders. It also indicates that many genetic mutations, epigenetic changes, and other cellular and morphological brain lesions can converge on disturbing a given brain circuit and result in shared clinical manifestations (e.g., delusions and hallucinations) that lead to the same clinical diagnosis (e.g., schizophrenia). Thus, starting from a diagnosis and searching broadly for genetic causes that are commonly shared across all affected individuals is not likely to succeed, because a great deal of biological heterogeneity lies at the basis of circuit dysfunction. This does not mean, however, that these diseases are not genetically based and transmitted, nor does it suggest that the search for genetic causes will be fruitless. Indeed, ample evidence demonstrates the heritability of these disorders. For example, there is much greater concordance of diseased states in identical twins versus fraternal twins. In autism, in as many as 80% of families of identical twins, both display autistic features if one is affected ([ 5 ][6]). Concordance of schizophrenia is estimated to be ∼50% in identical twins, as opposed to ∼5 to 10% in fraternal twins ([ 6 ][7], [ 7 ][8]). In some persons, nongenetic factors—such as intrauterine infection, malnutrition, or stress—may also be required to trigger the illness ([ 8 ][9]). Because of these complexities, most of the genes involved in the major psychiatric illnesses have not yet been identified, and animal models for them are limited. Recent studies indicate that for many patients, psychiatric illnesses are due to genetic vulnerabilities that are shared by affected members of a given family, but vary across families, such that a given family has a unique, or “private,” mutational profile ([ 9 ][10]). It is therefore critical to focus on approaches that can detect private mutations and will take into account the genetic and neurobiological heterogeneity of psychiatric disorders. What is the best strategy for unraveling the biological causes of psychiatric illnesses? We suggest that their solution will require the integration of two general approaches that have matured dramatically in the last 3 years: Genomics and Circuit Analysis. Genomics is the combination of large-scale sequencing with systematic computational analysis of genomes. In the last 2 years, sequencing the human genome has become significantly faster and much less expensive. This makes it feasible to sequence the complete genome of many afflicted individuals to discover the genetic bases of these disorders within subjects and families. It is no longer necessary to target specific genes or chromosomal regions based on preconceived notions about the nature of the genetic defect. This approach has already proven useful in the analysis of X-linked mental retardation ([ 10 ][11]). New insight into the complex genetic basis of psychiatric disease comes from recent analysis of gene copy number variants present in patients with autism, schizophrenia, and bipolar disorder ([ 11 ][12]). Some of these mutations are...