Revolution stalled Hyman, Steven E
Science translational medicine,
2012-Oct-10, Letnik:
4, Številka:
155
Journal Article
Recenzirano
Drug discovery is at a near standstill for treating psychiatric disorders such as schizophrenia, bipolar disorder, depression, and common forms of autism. Despite high prevalence and unmet medical ...need, major pharmaceutical companies are deemphasizing or exiting psychiatry, thus removing significant capacity from efforts to discover new medicines. In this Commentary, I develop a view of what has gone wrong scientifically and ask what can be done to address this parlous situation.
An epochal opportunity to elucidate the pathogenic mechanisms of psychiatric disorders has emerged from advances in genomic technology, new computational tools and the growth of international ...consortia committed to data sharing. The resulting large-scale, unbiased genetic studies have begun to yield new biological insights and with them the hope that a half century of stasis in psychiatric therapeutics will come to an end. Yet a sobering picture is coming into view; it reveals daunting genetic and phenotypic complexity portending enormous challenges for neurobiology. Successful exploitation of results from genetics will require eschewal of long-successful reductionist approaches to investigation of gene function, a commitment to supplanting much research now conducted in model organisms with human biology, and development of new experimental systems and computational models to analyse polygenic causal influences. In short, psychiatric neuroscience must develop a new scientific map to guide investigation through a polygenic terra incognita.
This article is part of a discussion meeting issue ‘Of mice and mental health: facilitating dialogue between basic and clinical neuroscientists’.
A pressing need for interrater reliability in the diagnosis of mental disorders emerged during the mid-twentieth century, prompted in part by the development of diverse new treatments. The Diagnostic ...and Statistical Manual of Mental Disorders (DSM), third edition answered this need by introducing operationalized diagnostic criteria that were field-tested for interrater reliability. Unfortunately, the focus on reliability came at a time when the scientific understanding of mental disorders was embryonic and could not yield valid disease definitions. Based on accreting problems with the current DSM-fourth edition (DSM-IV) classification, it is apparent that validity will not be achieved simply by refining criteria for existing disorders or by the addition of new disorders. Yet DSM-IV diagnostic criteria dominate thinking about mental disorders in clinical practice, research, treatment development, and law. As a result, the modern DSM system, intended to create a shared language, also creates epistemic blinders that impede progress toward valid diagnoses. Insights that are beginning to emerge from psychology, neuroscience, and genetics suggest possible strategies for moving forward.
Genetics provides two major opportunities for understanding human disease—as a transformative line of etiological inquiry and as a biomarker for heritable diseases. In psychiatry, biomarkers are very ...much needed for both research and treatment, given the heterogenous populations identified by current phenomenologically based diagnostic systems. To date, however, useful and valid biomarkers have been scant owing to the inaccessibility and complexity of human brain tissue and consequent lack of insight into disease mechanisms. Genetic biomarkers are therefore especially promising for psychiatric disorders. Genome-wide association studies of common diseases have matured over the last decade, generating the knowledge base for increasingly informative individual-level genetic risk prediction. In this review, we discuss fundamental concepts involved in computing genetic risk with current methods, strengths and weaknesses of various approaches, assessments of utility, and applications to various psychiatric disorders and related traits. Although genetic risk prediction has become increasingly straightforward to apply and common in published studies, there are important pitfalls to avoid. At present, the clinical utility of genetic risk prediction is still low; however, there is significant promise for future clinical applications as the ancestral diversity and sample sizes of genome-wide association studies increase. We discuss emerging data and methods aimed at improving the value of genetic risk prediction for disentangling disease mechanisms and stratifying subjects for epidemiological and clinical studies. For all applications, it is absolutely critical that polygenic risk prediction is applied with appropriate methodology and control for confounding to avoid repeating some mistakes of the candidate gene era.
If neurobiology is ultimately to contribute to the development of successful treatments for drug addiction, researchers must discover the molecular mechanisms by which drug-seeking behaviors are ...consolidated into compulsive use, the mechanisms that underlie the long persistence of relapse risk, and the mechanisms by which drug-associated cues come to control behavior. Evidence at the molecular, cellular, systems, behavioral, and computational levels of analysis is converging to suggest the view that addiction represents a pathological usurpation of the neural mechanisms of learning and memory that under normal circumstances serve to shape survival behaviors related to the pursuit of rewards and the cues that predict them. The author summarizes the converging evidence in this area and highlights key questions that remain.
Addiction is a state of compulsive drug use; despite treatment and other attempts to control drug taking, addiction tends to persist. Clinical and laboratory observations have converged on the ...hypothesis that addiction represents the pathological usurpation of neural processes that normally serve reward-related learning. The major substrates of persistent compulsive drug use are hypothesized to be molecular and cellular mechanisms that underlie long-term associative memories in several forebrain circuits (involving the ventral and dorsal striatum and prefrontal cortex) that receive input from midbrain dopamine neurons. Here we review progress in identifying candidate mechanisms of addiction.
Understanding the pathogenesis of neuropsychiatric disorders is a substantial challenge for neurobiologists. It has long been hoped that identifying alleles that confer increased risk of such ...disorders would provide clues for neurobiological investigation. But this quest has been stymied by a lack of validated biological markers for characterizing and distinguishing the different disorders and by the genetic complexity underpinning these diseases. Now, modern genomic technologies have begun to facilitate the discovery of relevant genes.
The potential use of drugs to enhance cognition, emotion, and executive function has engendered controversy despite the fact that few such agents exist today. Here, I provide a context for ...discussions based on medical, regulatory, and ethical concerns that have been raised by the possibility that enhancers will emerge from current efforts to discover drugs for neuropsychiatric disorders.
Advances in genome analysis, accompanied by the assembly of large patient cohorts, are making possible successful genetic analyses of polygenic brain disorders. If the resulting molecular clues, ...previously hidden in the genomes of affected individuals, are to yield useful information about pathogenesis and inform the discovery of new treatments, neurobiology will have to rise to many difficult challenges. Here we review the underlying logic of the genetic investigations, describe in more detail progress in schizophrenia and autism, and outline the challenges for neurobiology that lie ahead. We argue that technologies at the disposal of neuroscience are adequately advanced to begin to study the biology of common and devastating polygenic disorders.
A revolution in genomic technologies has brought new light to the genes that contribute to diseases of the nervous system. Steven Hyman and Steven McCarroll argue that the next step of translating these genetic discoveries into biological insights and therapies will be a major challenge but one that the field is poised to meet.
In the face of growing controversy about the utility of genetic mouse models of human disease, Rothwell et al. report on a shared mechanism by which two different neuroligin-3 mutations, associated ...with autism spectrum disorders in humans, produce an enhancement in motor learning. The open question is how much we can learn about human ills from such models.
In the face of growing controversy about the utility of genetic mouse models of human disease, Rothwell et al. report on a shared mechanism by which two different neuroligin-3 mutations, associated with autism spectrum disorders in humans, produce an enhancement in motor learning. The open question is how much we can learn about human ills from such models.
PDF
