Introduction

Psychiatry draws widely upon insights from many realms ranging from public health, the social sciences, and the humanities. As psychiatric disorders affect mood, cognition, perception, emotion, and behavior, brain science is recognized as foundational to understanding their pathophysiology. Along with the disciplines of neurology, neurosurgery, and neuroradiology, psychiatry is often regarded as one of the clinical neurosciences.

Although the clinical interview and observation of behavior continue to remain the mainstay for diagnosis of psychiatric disorders, growing insights about the pathophysiology of psychiatric conditions are likely to inform the assessment, treatment, and classification of psychiatric disorders in the coming years. A circuit-based understanding of brain function, the establishment of biomarkers for early identification and intervention, and genetic tools to stratify an individual’s risk of disease and predict response to different treatment modalities promise to become increasingly integral to clinical psychiatry. As the field of psychiatry moves away from inefficient “trial-and-error” based approaches, toward precision medicine grounded in knowledge about individual variation in brain biology, fluency in neuroscience will be essential preparation for clinical practice.

This chapter will provide a general overview of neuroscience relevant to psychiatry. As progress is rapid, our focus is on neuroscientific concepts relevant to psychiatry, as well as on current efforts to identify clues about the underlying causes of psychiatric disorders, and discover promising targets for novel treatments.

Historical Context

In contemporary Western medicine, the impetus to link specific clinical syndromes to pathology in the brain dates to nineteenth-century Europe. The then-nascent field of neurology, led by notable physician-scientists, including Jean-Martin Charcot, Joseph Babinsky, Paul Broca, and Karl Wernicke, began to associate speech, motor, and cognitive abnormalities with lesions in particular brain regions. Preliminary attempts to explain emotional phenomena in terms of brain function were also made by Benjamin Rush in the United States and Wilhelm Griesinger in Germany.

One prominent clinician who believed that psychiatric symptoms could be explained neurologically was Sigmund Freud. Though best known for developing the field of psychoanalysis, focused on unconscious impulses and fears driving emotions and behavior, Freud was trained as a neurophysiologist and neurologist and was confident that psychological processes had neurophysiologic correlates yet to be discovered. As psychoanalysis was further elaborated between the late 1800s through the mid-1900s, becoming a leading force in psychiatry, the field increasingly diverged from brain science, though in recent years clinical practitioners and researchers of psychoanalytically based psychotherapies have shown renewed interest in neuroimaging and other methods for revisiting Freud’s earlier vision.

In the latter part of the twentieth century, the discovery of effective pharmacological treatments for major psychiatric disorders, including antipsychotics and antidepressants, also brought renewed interest in the biology of psychiatric disease. These medications targeted neurochemical systems, particularly the so-called monoamines – dopamine, serotonin, and norepinephrine – which were being actively mapped in the brain during this same period. Their efficacy led to the monoamine hypothesis of psychiatric illness, the idea that alterations involving the levels or function of this group of neurotransmitters caused specific symptoms (e.g., depressed mood, anxiety, and psychosis). But without direct access to the brain in living individuals, more comprehensive approaches to understand the biology of mental illness were not yet possible. Scientists turned to animal models in order to probe the inner workings of individual cells and circuits in awake and behaving organisms, though their translational relevance to human psychiatric illness remains a considerable limitation. The development of functional brain imaging techniques in the 1990s enabled for the first time the study of altered brain function in vivo, and in conjunction with other advances in translational neuroscience, which will be discussed later, has revolutionized our understanding of mental illness as underlying brain and even whole-body disorders.

A New Neuroscience-Based Framework for Nosology

While the Diagnostic and Statistical Manual (DSM) remains the gold standard for clinical diagnosis in psychiatry, efforts to recategorize psychiatric disorders using neuroscience may ultimately reshape the way we think about psychiatric assessment. One such initiative is the Research Domain Criteria (RDoC) framework, championed in 2011 by Tom Insel, a psychiatrist, neuroscientist, and then- director of the National Institute of Mental Health (NIMH). Rather than using the DSM’s distinct categories and checklists of symptoms and symptom duration for mental disorders, RDoC uses six domains of psychological processes that show a continuous range of variation across the entire population (see Figure 2.1). These domains are not meant to be exclusive or finite but open to change with new research. They are also meant to be studied in multiple models from cells to human behavior. Extremes along these continua, perhaps in specific combinations, may underlie psychiatric symptoms that bridge across conventional diagnostic categories. Though RDoC was developed to help guide neuroscientific research into complex human behavior and mental disorders, it is hypothesized that these dimensions of psychopathology will more closely represent underlying variation in brain physiology compared to DSM-based diagnoses, and can be more directly mapped onto mechanistic models in both humans and other animals. It remains the work of clinicians and researchers to integrate RDoC and DSM categorization and determine if a more dimensional framework better advances meaningful research and clinical innovation.

Figure 2.1 The Research Domain Criteria is a research framework developed by the National Institute of Mental Health (NIMH) to examine psychological processes based on seven levels of information.

The image is reprinted from the NIMH website. www.nimh.nih.gov/research/research-funded-by-nimh/rdoc/.shtml

In the RDoC framework, there are different hierarchical units of analysis used to investigate these constructs: genes, molecules, cells, circuits, physiology, behaviors, and self-reports. This chapter will take an analogous approach using the first five constructs to introduce the concepts and principles of neuroscience as related to psychiatric disorders. We will start with genetics and epigenetics; move on to receptors, neurotransmitters, and various immune and endocrinologic molecules; and conclude with neural circuits. We will discuss the studies within human, computational, and translational models and recommend Suggested Reading for further study of other promising model systems such as nonhuman primates and inducible pluripotent stem cells (iPSCs).

Organization of the Human Genome: Rare Variants Are Rare in Psychiatric Genetics

The human genome is composed of twenty-three pairs of chromosomes, each harboring millions of linearly arranged nucleotides, or bases. If a nucleotide sequence is in a region that codes for a protein, it is considered part of a gene, the functional unit of heredity. The physical location of a gene on a chromosome is termed a locus. Because chromosomes are inherited in pairs (one from each parent), most genetic loci have two copies that may be identical or different. The different loci that exist in a population are termed alleles, and the combination of alleles at a locus is referred to as a genotype.

Humans share 99.9 percent of their genome, with the remaining 0.1 percent accounting for all variation between individuals. To find genetic clues into why certain people develop mental illness and others do not, we need to understand the different types of variation that exist in our genomes, which can range from the duplication or deletion of an entire chromosome down to a change in a single letter of the DNA code.

Variation in the number of chromosomes present, termed aneuploidy, is relatively rare, but can be associated with profound effects in behavior and cognition as well as with substantial medical comorbidity. Down syndrome, for example, results from inheriting an extra copy of chromosome 21, and nearly all patients have some level of neuropsychiatric phenotype, namely intellectual disability. These chromosomal abnormalities can be detected by visualizing whole chromosomes using a simple light microscope to create what is called a karyotype.

Other large-scale variations can be caused by a deletion, duplication, or translocation of portions of the chromosome, which are large and easily detectable with current molecular techniques. A genetic variation with one of the largest effect sizes for developing mental illness is a large deletion of more than one million base pairs (nucleotides) encompassing several genes from the long arm of chromosome 22. This deletion can lead to a wide range of abnormalities including cardiac defects, immune deficiencies, and distinct facial features, and is most accurately referred to as 22q11.2 deletion syndrome, though other names have been used in the past (e.g., DiGeorge syndrome or velocardiofacial syndrome). Interestingly, 22q11.2 deletion syndrome carries an absolute risk of schizophrenia of approximately 30 percent, and patients already diagnosed with schizophrenia have a ten- to twenty-times higher prevalence of carrying this deletion. Despite the large effect size, 22q11.2 deletion still accounts for a very small portion of those diagnosed with schizophrenia due to the relative rarity of this variant (1 in 4,000). Large duplications have also been shown to increase the risk of psychiatric pathology. For example, duplications of a portion of chromosome 15 significantly increase the risk of developing autism and are found in 1–2 percent of cases. These large changes in DNA structure are often thought to have a causal effect on neuropsychiatric phenotypes; however, the deletion or addition of ten to a thousand genes only provides an incomplete glimpse into our understanding of the genetic basis of these disorders. Neuroscientists hope that by studying the mechanism by which 22q11.2 deletion influences schizophrenia-risk, or chromosome 15 duplication influences autism-risk, they will gain insights that will be helpful to a broader population.

Small variants with large effect can also cause substantial neuropsychiatric morbidity, with well-known examples, including Huntington disease (HD) and Fragile X. Both disorders are caused by an expansion of trinucleotide repeats (CAG, CCG) within a single gene; once the number of repeats crosses over a certain threshold, these small DNA variants have near 100 percent penetrance, meaning all carriers of the expansions express the disease. The genetic cause of these disorders was discovered in the last 30 years using the classic technique of linkage analysis, tracking increasingly smaller pieces of DNA that segregate in carriers of the disorder versus controls, eventually narrowing down to a single region or gene. More recently, a technique called exome sequencing, where the entire protein-coding sequence of DNA (exons) is determined, has been applied to psychiatric disorders and has started to find rare, novel mutations with large effects in single genes linked to disorders such as schizophrenia. While these inroads are exciting and important, it is equally important to recognize that even for disorders like HD and Fragile X linked to single genes the timeline for moving from genetics to clinical therapeutics has been much slower than most scientists and physicians originally anticipated.

Searching for Common Variants with Small Effects

Early genetic studies attempted to find “the gene” for a given mental illness. However, these monogenic investigations were largely unsuccessful in accounting for the strong heritability in developing these disorders. To address this so-called missing heritability, geneticists studying mental illness – as well as other common, complex human phenotypes such as diabetes and hypertension – have changed their focus from rare variation with large effect sizes toward common differences in the genome with subtle effects, and are generating promising results. These common variants, which include copy number variants (CNVs) and single nucleotide polymorphisms (SNPs), are present in large numbers in every individual. In general, common variants confer only minimal effects on most phenotypes in isolation; however, the aggregate effects of thousands can be substantial.

CNVs are duplications or deletions at the gene level, usually in the range of thousands of base pairs at a time. CNVs are common, making up an estimated 10 percent of the entire genome, and are thought to allow for additional genetic variation within a population. The cytochrome p450 system provides a good example of how these genetic variations can relate to psychiatry. The cytochrome P450 system contains enzymes that metabolize most psychiatric and other medications, and alterations in these enzymes can affect drug levels in the blood. CNVs in the gene encoding CYP2D6 can increase or decrease the number of copies of this gene and change the amount of enzyme present, therefore affecting the ability of a patient to metabolize medications by this enzyme. Thus, if a patient has a CNV deletion at this site, they will have fewer enzymes. If this patient is prescribed a medication metabolized by this enzyme such as an antidepressant, they will be at higher risk for toxic side effects given higher medication levels. If, on the other hand, a patient has a CNV with additional copies of the gene, they will have more enzymes. If this patient is prescribed an antipsychotic metabolized by this enzyme, it is less likely to be effective at its usual doses due to lower levels. The field looking at how genetic variation influences medications is called pharmacogenomics while the field that studies how medications interact with receptors is called pharmacodynamics. Pharmacogenomic tests are already commercially available, although the field is nascent. Much remains to be learned about the genes most relevant for explaining the tolerability, safety, and effectiveness of most medications used in psychiatry.

The most common types of variation in the genome are single nucleotide polymorphisms, or SNPs. SNPs are single-base differences spread throughout the genome, with low-frequency variants occurring in less than 1 percent of the population and high-frequency variants occurring in more than 1 percent. Each individual has an estimated 4 million SNPs in their genome, and more than 100 million have been identified worldwide. The majority of SNPs occur outside of the coding region of genes and have no known functional relevance. The few SNPs with functional relevance are located in regulatory or protein-coding regions and likely can change the expression level of the gene or structure of the protein, respectively. In some cases, such as cystic fibrosis, SNPs can be devastating. It has become clear, though, that SNPs with this magnitude of an effect are infrequent in psychiatry; however, their ubiquitous and variable nature makes them powerful markers to locate regions of a chromosome that are implicated in disease. How does this work?

During meiosis, before the paired chromosomes split apart, they swap some of their genetic material in a process called recombination. The closer genes or SNPs are to one another on a chromosome, the more likely they will undergo recombination together and remain together across multiple generations. These sections that stick together are called haplotypes. If a certain version (allele) of one of the genes in the haplotype is related to disease, the particular SNP on a different part of the same haplotype may be a marker for the disease allele as it is likely to be transmitted along with it. In addition, the locations where recombination takes place do not occur completely randomly: some SNPs are inherited together at a higher or lower frequency than expected by chance, which is referred to as SNPs existing in linkage disequilibrium. These factors allow geneticists to track down SNPs found with higher frequency in patients with schizophrenia compared to controls, and identify a nearby SNP or gene that may have a causal relationship to the disease. Thus SNPs can point to a region of the genome that confers risk for a disease, which can be a first step toward understanding the biology of an illness.

Genome-Wide Association Studies (GWAS) Deliver Promising Leads

The sequencing of the first human genome was completed in 2001 after more than a decade of work and a total project cost of $2.7 billion. Rapid breakthroughs in sequencing technologies now allow sequencing of a whole genome in a matter of days for around $1,000; similarly, a complete SNP analysis can cost as low as $50 per person. These technologies give geneticists the power to sequence a huge number of patients and controls at a relatively low cost to find both rare variants with large effects (whole genome and whole exome sequencing) and common variants with small effects (GWAS; genome-wide association studies).

In 2014, the Psychiatric Genomics Consortium published GWAS results from ~37,000 patients with schizophrenia and 110,000 controls, identifying 108 independent loci associated with the disorder. The findings of GWAS are commonly presented as a so-called Manhattan plot, given the resemblance to a city skyline (Figure 2.2). Each SNP is plotted on the x-axis and its corresponding p-value plotted on the y-axis – any SNP above the dotted line is significantly associated with the disorder. Though these results still only account for a fraction of the total heritability of schizophrenia (<10 percent), they provide an exciting and unprecedented avenue for exploration into the mechanism of disease. Evidence supporting the decades-old hypotheses of dysregulated neurotransmitter signaling was supported by the genetic associations of the dopamine D2 receptor (DRD2), the primary site of action for nearly all antipsychotic medications, and several glutamate receptors (GRIA1, GRIN2A, GRM3). Perhaps more interesting, novel clues of disease pathogenesis have started to emerge from the results. For example, the strongest GWAS association for schizophrenia was in the major histocompatibility complex (MHC) locus and regulates the expression of a protein commonly used by the immune system, complement component 4 (C4). Changes in the expression of C4 were subsequently shown to effect synaptic pruning in the mouse brain, and for the first time, a disease-associated genetic variant was connected to a biological pathway implicated in schizophrenia. This finding has sparked interest in the potential immunologic etiology of mental illnesses including schizophrenia and will hopefully lead to new drug targets through pharmaceutical research.

Figure 2.2 Manhattan plot from a large genome wide association study that found 108 genetic loci associated with schizophrenia. The x axis indicates the location of the SNP and the y axis indicates the significance of the association, where the red line shows the cutoff for genome-wide significance.Reprinted from:Schizophrenia Working Group of the Psychiatric Genomics Consortium., Ripke, S., Neale, B. et al. Biological insights from 108 schizophrenia-associated genetic loci. Nature 511, 421–427 (2014)

Another powerful use of GWAS data is predicting an individual’s risk for developing a phenotype by summing the effect size of every measured SNP in a single person, generating a polygenic risk score (PRS). Though predictive validity has not yet been demonstrated, the hope is that PRSs can aid in screening and early detection, similar to the Framingham score predicting cardiac events, allowing for early and targeted interventions for those at highest risk. One current limitation to PRS is that GWAS are overwhelmingly performed in populations of European descent, limiting their applicability to only individuals of the same genetic background. However, as the Psychiatric Genomics Consortium continues to grow and analyze an increasing number of patients from diverse populations, additional disease-associated genes will be identified, and tools such as PRS will become more and more powerful.

Further studies in different mental illnesses have started to reveal shared genetic architecture and overlapping risk loci between certain psychiatric illnesses. For example, bipolar disorder and schizophrenia share considerable genetic overlap, as do autism spectrum disorder and ADHD, leading to new hypotheses about common biological bases of these disorders. Of note, the RDoC format accounts for some of this cross-disease relatedness. For example, these disorders all share phenotype dysregulation in the cognitive domain and genetic risk in genes encoding neurotransmitter receptors.

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