Advances in the Neurobiology of Mental Illness

Resources

Manji

World Health Organization — Global Burden of Disease

The Global Economic Burden of Noncommunicable Diseases

Choi SH, Kim YH, D'Avanzo C, et al. Recapitulating amyloid β and tau pathology in human neural cell culture models: clinical implications. US Neurol. 2015 Fall;11(2):102-105.

Deisseroth K. Optogenetics: 10 years of microbial opsins in neuroscience. Nat Neurosci. 2015 Sep;18(9):1213-25.

Delorme R, Ey E, Toro R, et al. Progress toward treatments for synaptic defects in autism. Nat Med. 2013 Jun;19(6):685-94.

Jackson AC, Nicoll RA. The expanding social network of ionotropic glutamate receptors: TARPs and other transmembrane auxiliary subunits. Neuron. 2011 Apr 28;70(2):178-99.

Schizophrenia Working Group of the Psychiatric Genomics Consortium. Biological insights from 108 schizophrenia-associated genetic loci. Nature. 2014 Jul 24;511(7510):421-7.

Krishnan

Grigoleit JS, Kullmann JS, Wolf OT, et al. Dose-dependent effects of endotoxin on neurobehavioral functions in humans. PLoS One. 2011;6(12):e28330.

Hughes MM, Connor TJ, Harkin A. Stress-related immune markers in depression: implications for treatment. Int J Neuropsychopharmacol. 2016 Jan 16. pii: pyw001.

Konsman JP, Parnet P, Dantzer R. Cytokine-induced sickness behaviour: mechanisms and implications. Trends Neurosci. 2002 Mar;25(3):154-9.

Raison CL, Rutherford RE, Woolwine BJ, et al. A randomized controlled trial of the tumor necrosis factor antagonist infliximab for treatment-resistant depression: the role of baseline inflammatory biomarkers. JAMA Psychiatry. 2013 Jan;70(1):31-41.

Reichenberg A, Yirmiya R, Schuld A, et al. Cytokine-associated emotional and cognitive disturbances in humans. Arch Gen Psychiatry. 2001 May;58(5):445-52.

Cannon

Cannon TD, Chung Y, He G, et al. Progressive reduction in cortical thickness as psychosis develops: a multisite longitudinal neuroimaging study of youth at elevated clinical risk. Biol Psychiatry. 2015 Jan 15;77(2):147-57.

Cannon TD, Yu C, Addington J, et al. An individualized risk calculator for research in prodromal psychosis. Am J Psychiatry. 2016 Oct 1;173(10):980-988.

Fusar-Poli P, Borgwardt S, Bechdolf A, et al. The psychosis high-risk state: a comprehensive state-of-the-art review. JAMA Psychiatry. 2013 Jan;70(1):107-20.

Perkins DO, Jeffries CD, Addington J, et al. Towards a psychosis risk blood diagnostic for persons experiencing high-risk symptoms: preliminary results from the NAPLS project. Schizophr Bull. 2015 Mar;41(2):419-28.

Zarate

Cornwell BR, Salvadore G, Furey M, et al. Synaptic potentiation is critical for rapid antidepressant response to ketamine in treatment-resistant major depression. Biol Psychiatry. 2012 Oct 1;72(7):555-61.

Duncan WC, Sarasso S, Ferrarelli F, et al. Concomitant BDNF and sleep slow wave changes indicate ketamine-induced plasticity in major depressive disorder. Int J Neuropsychopharmacol. 2013 Mar;16(2):301-11.

Niciu MJ, Mathews DC, Nugent AC, Ionescu DF, et al. Developing biomarkers in mood disorders research through the use of rapid-acting antidepressants. Depress Anxiety. 2014 Apr;31(4):297-307.

Singh JB, Fedgchin M, Daly EJ, et al. A double-blind, randomized, placebo-controlled, dose-frequency study of intravenous ketamine in patients with treatment-resistant depression. Am J Psychiatry. 2016 Aug 1;173(8):816-26.

Zanos P, Moaddel R, Morris PJ, et al. NMDAR inhibition-independent antidepressant actions of ketamine metabolites. Nature. 2016 May 4;533(7604):481-6.

Zarate CA Jr, Singh JB, Carlson PJ, et al. A randomized trial of an N-methyl-D-aspartate antagonist in treatment-resistant major depression. Arch Gen Psychiatry. 2006 Aug;63(8):856-64.

Dawson

Dawson G, Rogers S, Munson J, et al. Randomized, controlled trial of an intervention for toddlers with autism: the Early Start Denver Model. Pediatrics. 2010 Jan;125(1):e17-23.

Dawson G, Jones EJ, Merkle K, et al. Early behavioral intervention is associated with normalized brain activity in young children with autism. J Am Acad Child Adolesc Psychiatry. 2012 Nov;51(11):1150-9.

Orekhova EV, Elsabbagh M, Jones EJ, et al. EEG hyper-connectivity in high-risk infants is associated with later autism. J Neurodev Disord. 2014;6(1):40.

Young AM, Chakrabarti B, Roberts D, et al. From molecules to neural morphology: understanding neuroinflammation in autism spectrum condition. Mol Autism. 2016 Jan 20;7:9.

Autism Biomarkers Consortium for Clinical Trials

European Autism Interventions

Pine

Bar-Haim Y, Lamy D, Pergamin L, et al. Threat-related attentional bias in anxious and nonanxious individuals: a meta-analytic study. Psychol Bull. 2007 Jan;133(1):1-24.

Bar-Haim Y, Holoshitz Y, Eldar S, et al. Life-threatening danger and suppression of attention bias to threat. Am J Psychiatry. 2010 Jun;167(6):694-8.

Hardee JE, Benson BE, Bar-Haim Y, et al. Patterns of neural connectivity during an attention bias task moderate associations between early childhood temperament and internalizing symptoms in young adulthood. Biol Psychiatry. 2013 Aug 15;74(4):273-9.

Pérez-Edgar K, McDermott JN, Korelitz K, et al. Patterns of sustained attention in infancy shape the developmental trajectory of social behavior from toddlerhood through adolescence. Dev Psychol. 2010 Nov;46(6):1723-30.

LeDoux JE, Pine DS. Using neuroscience to help understand fear and anxiety: a two-system framework. Am J Psychiatry. 2016 Nov 1;173(11):1083-1093.

Shechner T, Britton JC, Pérez-Edgar K, et al. Attention biases, anxiety, and development: toward or away from threats or rewards? Depress Anxiety. 2012 Apr;29(4):282-94.

Walsh

Foerde K, Steinglass JE, Shohamy D, Walsh BT. Neural mechanisms supporting maladaptive food choices in anorexia nervosa. Nat Neurosci. 2015 Nov;18(11):1571-3.

Graybiel AM. Habits, rituals, and the evaluative brain. Annu Rev Neurosci. 2008;31:359-87.

Hare TA, Camerer CF, Rangel A. Self-control in decision-making involves modulation of the vmPFC valuation system. Science. 2009 May 1;324(5927):646-8.

Walsh BT. The enigmatic persistence of anorexia nervosa. Am J Psychiatry. 2013 May;170(5):477-84.

Narayan

Grande I, Berk M, Birmaher B, Vieta E. Bipolar disorder. Lancet. 2016 Apr 9;387(10027):1561-72.

Kaye J, Mattek N, Dodge HH, et al. Unobtrusive measurement of daily computer use to detect mild cognitive impairment. Alzheimers Dement. 2014 Jan;10(1):10-7.

Manji HK, Insel TR, Narayan VA. Harnessing the informatics revolution for neuroscience drug R&D. Nat Rev Drug Discov. 2014 Aug;13(8):561-2.

Manning JS, Ahmed S, McGuire HC, Hay DP. Mood disorders in family practice: beyond unipolarity to bipolarity. Prim Care Companion J Clin Psychiatry. 2002 Aug;4(4):142-150.

Martínez-Pérez B, de la Torre-Díez I, López-Coronado M. Mobile health applications for the most prevalent conditions by the World Health Organization: review and analysis. J Med Internet Res. 2013 Jun 14;15(6):e120.

Villemagne VL, Burnham S, Bourgeat P, et al. Australian Imaging Biomarkers and Lifestyle (AIBL) Research Group. Amyloid β deposition, neurodegeneration, and cognitive decline in sporadic Alzheimer's disease: a prospective cohort study. Lancet Neurol. 2013 Apr;12(4):357-67.

Yu L, Boyle PA, Leurgans S, Schneider JA, Bennett DA. Disentangling the effects of age and APOE on neuropathology and late life cognitive decline. Neurobiol Aging. 2014 Apr;35(4):819-26.

Highlights

Mental illness has a demonstrably negative impact on many health conditions, such as heart disease, cancer, type 2 diabetes, and osteoporosis.

Inflammation has been proposed as one connection between medical illness and mental illness.

Antagonists of pro-inflammatory cytokines may treat depression in a subset of patients who experience inflammation.

The state of the science in mental illness

Mental illness takes an enormous toll on individuals and populations worldwide, said Husseini Manji of Janssen Research & Development. According to the World Health Organizations' Global Burden of Disease study, major depression is the number one cause of disability in the western world today, and it is projected to become the number one cause worldwide by 2030. The global economic burden of mental illness is estimated to be a staggering $2.5 to 8.5 trillion in lost productivity. Because these conditions generally strike in adolescence and young adulthood, they rob society of its members' most productive years.

Several new and powerful techniques have emerged for visualizing brain structure and function in unprecedented detail.

The body and brain are not separate, said Manji—mental illness has an enormously deleterious effect on many health conditions. People are several-fold times more likely to die in the six months following a heart attack if they are depressed than if they are not; depression is also a predictor of disease progression in cancer, type 2 diabetes, osteoporosis, and many other conditions.

Despite the magnitude of medical need, the National Institutes of Health is underinvesting in neuroscience, and few pharmaceutical companies currently maintain neuroscience programs. That may be because brain disorders are seemingly more complex and therefore more daunting than other conditions.

Manji noted, however, that neuroscience today is progressing at a spectacular rate and that this progress must be harnessed to identify novel therapies. Mental illness is far more heritable than other common conditions, such as breast cancer, hypertension and lung disease, and gene studies powered by the falling cost of sequencing are identifying key signaling pathways involved in brain disease pathology. Researchers are also beginning to understand the environmental contributions to mental illness and to identify so-called epigenetic targets for treatment, Manji said. New tools for visualizing and manipulating brain function are emerging, and the ability to make patient-specific cells with the help of induced pluripotent cell techniques is providing the means to test disease and treatment hypotheses in human tissue.

Highlights

Risk calculators predicting the onset of psychosis are improving, but treatments for preventing the condition do not yet exist.

Next generation antidepressants such as ketamine can elicit effects within hours, unlike the 6–8 week timeframe of current antidepressants.

Prediction and prevention of psychosis

Current approaches for treating people with schizophrenia do not address the underlying disease process or prevent future psychotic episodes and often carry significant side effects. The ability to predict and prevent the onset of psychosis would fill a great unmet medical need, said Tyrone D. Cannon of Yale University.

Several groups have attempted to develop tools that identify people at imminent risk of psychosis by pinpointing early symptoms that precede their first psychotic episode—a so-called prodrome. This might include deterioration of social or scholastic function or an up-ramp in psychotic thoughts. Early work showed that in people age 15–25 who showed prodromal symptoms, about 15% converted to full-blown psychotic disorder within one year and 25% converted within two years. Most such patients develop schizophrenia, while others develop a mood disorder with psychotic features.

Highlights

Researchers are identifying biomarkers for autism to identify children with the disorder as early as possible and to use as measures for determining therapeutic efficacy in clinical trials.

Video games that train a person's instantaneous reflexive response to threat can help treat anxiety disorder.

Innovative biomarkers and clinical indicators in autism spectrum disorder

Autism wears many faces—from individuals who don't speak and require constant care, to those employed as university professors. Yet people with the condition share a struggle to navigate the social world. Drugs to treat core symptoms of the disorder are on the horizon, said Geraldine Dawson of Duke University School of Medicine. But to develop them, the field needs better outcome measures and a better infrastructure for clinical trials.

Autism researchers are on the hunt for biomarkers of the condition.

Several ongoing projects are looking for biomarkers in infant siblings of children with autism, who are at high risk of developing the condition. Early detection may make interventions more effective. In one study of 14-month old children, Dawson and her colleagues used high-density electroencephalography (EEG) to identify a pattern of hyperconnectivity in the brains of babies who went on to develop autism. Other findings suggest that reduced connectivity between specific brain areas thought to mediate speech, so the brain in children with autism appear to not be specializing normally. Electrophysiological signals called event-related potentials (ERPs) offer another promising predictive biomarker. In children with autism, ERP response to faces is disrupted, and in a recent study Dawson and her colleagues compared ERPs to faces versus objects to predict autism diagnoses in 6-month-old high-risk infants.

Biomarkers can help evaluate interventions in clinical trials. A 2-year study in high-risk children starting at 2.5 years of age that included behavioral and electrophysiological outcome measures showed that children who received an intensive behavioral intervention called the Early Start Denver Model showed improved IQ, language, social abilities and adaptive behavior compared to those that received the control condition of standard community intervention. Another study showed that early intensive behavioral intervention can normalize brain activity in children with autism, and that such changes correlate with improvements in social behavior. Early intervention in young children can thus bring them back to the social world, Dawson said.

Even with the best behavioral interventions, however, a significant percentage of children with autism still have significant impairments. For example, 30% of children with autism never learn to speak. Therefore, medicinal interventions are also key. Dawson and her colleagues recently completed a phase I open-label trial of autologous cord blood to treat autism in 25 children. Evidence suggests that neuroinflammation plays a role in the disorder, and umbilical cord blood has been shown to reduce microglial activation and stimulate myelin repair, perhaps through anti-inflammatory or neurotrophic mechanisms. The study evaluated eye-tracking, EEG, and magnetic resonance imaging, and found promising improvements in social behavior at 6 months and 12 months after infusion.

Dawson also described several novel techniques for measuring behavior that can collect a so-called digital phenotype of a child, providing objective, quantitative, continuous and scalable data. One such tool, LENA, is a small computer worn in a child's pocket that records her and her parents' vocalizations at home and measures who speaks and how often. Another approach, called EthoVision, tracks how often a child approaches a parent or objects in the lab. A third tool measures facial expressions in babies and children.

Researchers are developing a range of new methods for obtaining so-called digital phenotypes of participants in clinical trials.

A handful of consortia have formed to identify and validate biomarkers and to develop ways of using such technology-based measures. Dawson and her team are members of the Janssen Autism Knowledge Engine, which is creating tools including a phenotyping portal for parents and clinicians, a new measure that allows parents to monitor autism-related symptoms on their smartphones, and a biosensor worn by the child that collects sleep, heart rate and other data that can be correlated to behavior. Other efforts include the NIH Autism Biomarkers Consortium for Clinical Trials and the European Autism Interventions Consortium. "These large-scale efforts will be critical for companies coming into this space to have confidence in which biomarkers they should be incorporating into their clinical trials," Dawson said.

Using neuroscience to inform clinical thinking in pediatric anxiety

Mental illnesses are currently classified by symptom, but researchers must begin understand them based on brain function, said Daniel S. Pine of the U.S. National Institute of Mental Health. Unraveling the relationship between clinically relevant behaviors and brain processes in the lab can provide clinical insight, he said.

Anxiety is a good starting point for this approach because its brain-behavior relationship is strongly conserved across species and can therefore be compared in humans versus nonhuman organisms. Understanding how different aspects of anxiety relate to different brain perturbations and differentiating risk from disorder can help improve treatment.

Highlights

In anorexia nervosa, dieting becomes habitual, and treatment thus requires breaking the habit.

Digital apps and technologies are providing ecologically valid, continuous data that can be used to monitor central nervous system disease.

The emerging neurobiology of anorexia nervosa

Anorexia nervosa, which affects about 1% of women, is extremely difficult to treat. B. Timothy Walsh of New York State Psychiatric Institute, Columbia University described a cognitive neuroscience-based approach to understanding the behaviors driving the illness and their underlying neural circuitry.

The brain circuit for goal-directed learning (red) shifts to more dorsal and lateral regions (orange) of the prefrontal cortex and the striatum.

Treating anorexia nervosa is deceptively simple: simply get people to eat. Upon being admitted to Walsh's treatment facility, patients are asked to partake of a buffet lunch, where most consume about 300 self-chosen calories. After 2–3 months of treatment they improve, eating closer to 500 self-chosen calories. However, that does not approach control subjects' caloric intake of 800 calories. Clinicians know that people with anorexia nervosa avoid foods containing fat, and that recovery is associated with eating a greater variety of foods with higher fat content. The persistence of dieting is thus the condition's core behavior.

To better understand its persistence, Walsh and his colleagues turned to the neural basis of making choices. Persistent behavior that we are not born with is learned via one of two processes: Goal-directed learning, in which a behavior is repeated because it elicits a reward, and habit-formation, in which the behavior becomes fixed through overtraining, and begins to occur automatically, dissociated from the reward. "Habits are very powerful mechanisms that we as mammals are very prone to develop with training," Walsh said.

The circuit governing goal-directed learning includes the amygdala, the ventral striatum, and the prefrontal cortex. But as a behavior becomes more habitual, the circuit shifts toward more dorsal and lateral regions of the striatum and frontal cortex. Walsh's team hypothesized that anorexia nervosa, initially a learned behavior in young girls who feel good dieting, becomes habitual—explaining the condition's persistence and why it can be so hard to treat.

The team tested the hypothesis with a food choice task that examines the neural mechanism for self-control. They showed subjects a series of food pictures, asking them to rate how healthy, then how tasty, each item was. Then, a computer program chose a food the viewer judged neutral in both health and taste, and paired that image consecutively with all the other foods.

Subjects with anorexia nervosa generally reported food to be less healthy than controls did, but both they and control subjects deemed low-fat food healthier than high-fat food. However, for anorexia subjects, the higher the fact content, the less tasty they considered a food to be. When subjects were offered a choice, controls picked tasty foods while anorexia subjects selected healthy foods, going for high fat foods just 20% of the time. Finding high-fat foods less tasty thus reduced the need to exert self-control in not eating them. But when self-control was called upon, anorexia subjects were much better at it, exercising it 50–60% of the time while control subjects did so less than 20% of the time.

The researchers examined the eating preferences of people with anorexia nervosa with a food choice task including high-fat and low-fat foods.

When the researchers conducted the study in a functional magnetic resonance imaging scanner, controls engaged the ventral striatum while subjects with anorexia engaged the dorsal striatum, supporting the hypothesis that habit underlies their diet behavior. What's more, this connectivity pattern was correlated with how much they ate the next day. This task thus provides a tool for probing a habitualized behavior and its underlying neural circuitry. Better understanding of these circuits may point the way to helping people change this and other maladaptive behaviors, Walsh said.

Mobile and sensor technology for brain and CNS diseases

Medicine is on the cusp of a technological revolution, and neuroscience is the therapeutic area best positioned to take advantage of it, said Vaibhav Narayan of Janssen Research & Development. He discussed the promise and the challenge of harnessing continuous monitoring technologies for central nervous system disorders in an evidence-based and clinically-relevant manner.

These technologies could be applied to two types of disorders—neurodegenerative, in which change happens slowly over a lifetime, and neuropsychiatric, which is much more dynamic in nature and inconsistent in timescale.

In a neurodegenerative disease such as Alzheimer's, pathology takes root in the brain decades before symptoms appear, and the trajectory of memory and cognitive loss from mild cognitive impairment and dementia diverges from that in normal aging. Two studies in which people were followed for 15–20 years until their death suggested that a decline in verbal episodic memory is caused by the disease. Numerous apps and technologies now exist for capturing these markers in an ecologically valid, continuous, and often passive way. Narayan and his colleagues, for example, developed an app that automates a widely-used test for verbal episodic memory, performing as well as a trained psychologist.

Many apps and tools are being developed to continuously measure episodic memory.

Functional tasks such as ability to take medication or handle everyday finances can also be used as markers. Even something as simple as computer use can track the disorder: In people who had mild cognitive impairment, amount of daily computer use plummeted month by month, presumably because it taxed cognitive functions like episodic memory, executive function, and attention. Narayan and his colleagues are also investigating whether performance on an immersive video game correlates with known markers of Alzheimer's disease in people who report memory complaints. Such serious, validated tests will soon be available on our smart phones and computers to help determine whether the decline a person experiences is normal or disease-driven.

Digital tools are also useful for neuropsychiatric disorders, which are marked by a long prodromal period as well as precipitous events like depressive or manic episodes over days or weeks. This dynamic paradigm offers opportunities to improve outcome by intervening both presymptomatically and during relapses if they can be detected. Risk factors include constants, such as family history, as well as changing ones such as circadian rhythm, mood, sleep, and psychosocial functioning that can be tracked through a cell phone.

Narayan's group is currently conducting a study following more than 300 people with major depressive disorder for 12 months, continuously collecting data on sleep, activity cycle, and speech to look for a detectable technology-driven signature of relapse. Ultimately, he says, such data will have to be well-integrated with clinical information gleaned from medical visits. It must also be collected longitudinally, so that each person can be their own control.

Thousands of apps are being developed to monitor mood, predict disease-related events, and even offer therapeutic intervention, but so far, the number of them backed by science is miniscule. In 2013, for example, more than 1500 apps related to depression could be found in commercial app stores, but there were just 32 published research studies about them. Reputable companies can thrive in this space only if researchers can ensure the validity of such measures, Narayan said. The learning engine for developing such technologies starts out with controlled studies, clinical validation, and replication studies, and then involves the use of scalable IT platforms and testing in real-world populations. Ultimately, he said, the algorithm will be able to learn from the population as a whole and to make predictions for individuals.

Finally, Narayan said, with data from people's daily lives being used to make medical decisions, "we would have to make very clear that the owners of these data are the patients themselves—it's they who should decide how these data are shared and utilized." Janssen is leading a consortium of 24 organizations that span computer companies, biotech and medical device companies, patient advocates, and ethics experts to address how these technologies should navigate ethics and privacy concerns.

How will drugs that treat inflammation stand up as therapies for depression, and how can researchers identify the subset of patients most likely to respond to them?

What role do microglia play in the disease process of psychosis?

How can blood biomarkers be used to predict schizophrenia and other mental illnesses?

What kinds of continuous monitoring tools that collect a so-called digital phenotype of patients will be most helpful in clinical trials?

How should attentional training be used therapeutically to alleviate anxiety?

Can understanding the neural circuitry of core behaviors in mental illness point to new therapies?

How can digital monitoring tools be translated into use in the real world while maintaining patient privacy?

Might glutamate targets besides ketamine, such as some ketamine metabolites, also have therapeutic possibilities as fast-acting antidepressants?