Goal 2: Examine Mental Illness Trajectories Across the Lifespan

Examine Mental Illness Trajectories Across the Lifespan

Many mental illnesses present in childhood, adolescence, and young and late adulthood, yet mental illnesses are likely the late behavioral manifestations of changes that began years earlier. These early alterations may influence the course of brain and behavioral development and aging and establish the trajectories of mental illnesses.

Multi-level approaches will be critical in clarifying the complex relationships between biological and behavioral processes, social determinants of health, and environmental influences. At the level of individual factors, examining biological and behavioral processes across the lifespan will transform our understanding of the origins and progression of mental illnesses. Research to identify the earliest markers or signs that distinguish typical from atypical brain and/or functional development and maturation will be instrumental in predicting illness trajectories and outcomes later in life. NIMH encourages deep characterization across multiple levels of investigation (e.g., molecules, cells, circuits, networks, behavior) and integrative approaches to correlate their developmental patterns.

At the level of contextual factors, examining how social determinants and environmental factors impact risk and resilience to mental illnesses, burden of disease, access to care, and mental health outcomes will advance our understanding of mental health disparities. NIMH encourages community-engaged approaches to help identify the mechanisms by which social determinants of health and environmental factors impact mental health and ensure that the identification and interpretation of findings reflect the priorities and experiences of populations participating in and impacted by research.

As we chart developmental and aging trajectories across the lifespan, it is important to identify sensitive periods—critical timepoints to intervene to reduce risk for and to prevent the onset of mental illnesses and improve outcomes. These sensitive periods may be meaningful because they represent stages of rapid brain maturation, physiological or epigenetic processes, and significant life experiences. Interpreting trajectories and identifying sensitive periods for intervention will be enhanced through a life course perspective that considers developmental events as they are impacted by the complex interplay of individual and contextual factors. Unraveling these complexities will be key to developing novel therapeutic and prevention strategies that hold the promise of reducing both the burdens of mental illness and disparities in mental health outcomes.

To better understand developmental and aging trajectories and the progression of mental illnesses, NIMH will support research that employs the following Strategies:

Across the lifespan, the brain and the cognitive, behavioral, and affective functioning it supports undergo dramatic changes, in part as a result of diverse experiences. Yet, our understanding of how different experiences interact with biology and psychological development interact to affect brain development and maturation—and, ultimately, healthy and maladaptive behavioral outcomes—is still incomplete. Discoveries through basic and translational research further our fundamental understanding of how mental illnesses develop early or later in life and through the course of illness. By characterizing the trajectories of typical and atypical brain, cognitive, affective, and social development across the lifespan and a range of populations and contexts, we can identify factors that protect from, increase risk for, or give rise to mental illnesses. Greater understanding is needed to determine periods when the brain is at increased sensitivity to biological and environmental influences and optimal periods for intervention. Exposures during sensitive periods may include viruses and toxins; stressful life events or adversity; environmental factors such as light, temperature, or noise; and, social factors such as violence, discrimination, or harassment. It is important to also consider the dynamic and non-linear nature of brain development and aging, account for cumulative effects of risk and protective factors, simultaneously evaluate multiple domains of function, and incorporate life course perspectives.

To better understand developmental and aging trajectories and the progression of mental illnesses, NIMH will support research that employs the following Strategies:

Strategy 2.1.A Elucidating the mechanisms contributing to the trajectories of brain development and behavior

Interest areas include:

  1. Characterizing the interdependence and functional development of simultaneously occurring, yet unevenly progressing, trajectories in different brain regions and circuits across the lifespan.
  2. Determining the biological (e.g., epigenetic processes, neuroinflammation, allostatic load, and hormonal changes in puberty, pregnancy, and menopause) and psychological mechanisms by which experience, social determinants, and natural and built environment affect neural and behavioral development.
  3. Examining individual differences and the inter-relatedness of biological, behavioral, and environmental (including natural and built, social, cultural, and structural) contributors to heterogeneity in risk for and resilience from mental illnesses across the lifespan, trajectories of illnesses, prevention, and treatment interventions. Studies may use multi-level modeling to incorporate an intersectionality framework in mental health research.
  4. Developing novel statistical, computational, and analytical techniques to integrate behavioral, genomic, multi-modal neuroimaging, clinical, environmental, and other data types across repeated assessments and across independent datasets.
  5. Utilizing digital health technologies (e.g., biosensors, wearable devices, analysis of social media use patterns, digital diaries or prompts) to measure behavior, mood, and physiology in real-world environments, including social interactions and social networks.
  6. Understanding the impact of widespread and complex syndemics (e.g., COVID-19, the youth mental health crisis) on increasing risk for mental illness or exacerbating clinical symptoms and poor outcomes for individuals with mental illnesses.

Strategy 2.1.B Characterizing the emergence and progression of mental illnesses, and identifying sensitive periods for optimal intervention

Interest areas include:

  1. Conducting longitudinal studies that track changes in behavior, cognition, and affect; brain maturation, psychosocial and physical development; and, environmental exposures, to characterize the progression from early signs of alterations to subsequent impairment in these domains of functioning. NIMH encourages the use of large and diverse samples, adequately sampled and with sufficient power to examine mediators and moderators.
  2. Identifying the biological mechanisms (e.g., molecular, cellular, circuit) involved in healthy and dysfunctional neurodevelopmental and aging trajectories throughout life, including sex differences in incidence, age of onset, and severity of mental illnesses.
  3. Identifying and characterizing sensitive periods for brain, cognitive, social, and affective development and aging during which core facets of functioning (e.g., RDoC constructs, including social and environmental influences) can be targeted for optimal intervention to prevent, pre-empt, and/or effectively treat mental illnesses across diverse populations.
  4. Translating knowledge about sensitive periods and their critical mechanisms to manipulate developmental and aging trajectories of neural circuits and associated behaviors, to prevent or minimize illness trajectories and promote optimal outcomes, or to provide evidence to inform policies directed at social and environmental determinants of health associated with mental illness risk and severity.

The best time to address a mental illness is before the appearance of symptoms. Preventive interventions will rely on biomarkers and other indicators that give health care providers the ability to predict the onset of illness for individuals, not just populations, at risk. Currently, the mental health field lacks predictors that could inform a diagnosis, guide intervention, or predict response to intervention and the future course of illness. Further, understanding the mechanisms involved in risk and protective factors may shed light on novel intervention targets. Targets can include molecular processes; synaptic- and circuit-level regions or networks; neural systems; intrapersonal factors (e.g., psychological, cognitive, emotional, behavioral); interpersonal processes; and, environmental factors. We need to identify clinically useful biomarkers, behavioral indicators, and measures of social-environmental exposures with high predictive value to guide the use of preventive interventions across diverse populations, environments, and developmental and aging processes.

To lay the foundation for predicting outcomes and optimizing preventive and treatment interventions, NIMH will support research that employs the following Strategies:

Strategy 2.2.A Determining early risk and protective factors, and related mechanisms, to serve as novel intervention targets

Interest areas include:

  1. Identifying early manifestations of core functional domains (see RDoC framework ) particularly during infancy, early childhood, adolescence, and other life periods of rapid change (e.g., menopause transition, aging) that predict the onset and course of mental illnesses.
  2. Examining neurobehavioral mechanisms of sequential, additive, and/or interactive combinations of risk, resilience, and protective factors that span modalities and units of analysis and predict progression along the illness trajectory.
  3. Identifying novel intervention targets based on knowledge of neurobehavioral, psychological, and contextual mechanisms and trajectories, and the optimal time points for intervention.
  4. Demonstrating that putative targets are mutable and potentially modifiable.
  5. Using qualitative and mixed methods approaches to identify risk and protective factors, especially community and cultural strengths, that could be engaged by preventive and treatment interventions.

Strategy 2.2.B Developing reliable and robust biomarkers and assessment tools to predict illness onset and course across diverse populations

Interest areas include:

  1. Identifying specific, clinically relevant, life stage appropriate, culturally appropriate, and validated biomarkers of risk, onset, progression, recovery, and relapse phases of illnesses.
  2. Using multiple modalities and standardized methods to identify robust mediators, moderators, and predictors of resilience, illness course, and differential trajectories.
  3. Harnessing computational approaches to define and refine biomarkers, and to demonstrate potential clinical utility.
  4. Utilizing mobile and digital health technologies to capture dynamic changes in mood, behavior, and physiology in real-world environments and identify and promptly address increased clinical symptoms or risk for harm.
  5. Capitalizing on big data and computational approaches to identify the existence and potential drivers of mental health disparities and to quantify population-attributable risk for social-environmental factors.
  6. Developing fine-grained, objective, and quantitative behavioral assessment tools in animals and humans to evaluate dysfunction in domains relevant to the trajectories of mental illnesses.
  7. Developing evidence-based risk assessment instruments that encompass multiple domains, are sensitive to developmental and aging stages, and have high predictive power for the onset or recurrence of mental illnesses.
  8. Developing, testing, and refining tools and methodologies that integrate multimodal clinical, behavioral, and biological risk factors to prevent the onset of chronic conditions and optimize outcome.

Progress for Goal 2

Learn about the progress NIMH has made toward Goal 2 of the NIMH Strategic Plan for Research: Examine Mental Illness Trajectories Across the Lifespan.

Smartphone Data May Not Reliably Predict Depression Risk in Diverse Groups
NIMH-supported research suggests AI tools built on smartphone data may struggle to predict clinical outcomes like depression in large and diverse groups of people.

Increases Found in Preteen Suicide Rate
Researchers at the National Institutes of Health (NIH) found that rates of preteen suicide (ages 8-12) have been increasing by approximately 8% annually since 2008.

Disparities in Psychotic Disorder Diagnoses and Other Negative Health Outcomes
NIMH researchers found racial and ethnic disparities in rates of psychotic disorders, which were associated with co-occurring medical conditions and negative health outcomes.

Combined, High Maternal Stress and Prenatal COVID-19 Infection May Affect Attention Span in Infants
Prenatal COVID-19 infection increased the risk for impaired attention and delayed socioemotional and cognitive functioning among infants of mothers who experienced high psychosocial stress during their pregnancy.

Mothers' Difficult Childhoods Impact Their Children’s Mental Health
In this NIMH-funded study, researchers examined how trauma gets passed from one generation to the next.

Youth Suicide Rates Increased During the COVID-19 Pandemic
In one of the first studies to examine national youth suicide rates during the COVID-19 pandemic, researchers showed that the pandemic increased youth suicide rates and the impact varied by sex, age, and race and ethnicity.

Population Study Finds Depression Is Different Before, During, and After Pregnancy
New NIMH-funded research tracked population-level rates of postpartum depression among new mothers before, during, and after pregnancy.

Infants’ Health Record Data May Improve Early Autism Screening
Research supported by NIMH suggests that children’s health records may yield some promising insights that could improve the accuracy of early autism screening.

Attention to Geometric Images May Offer Biomarker for Some Toddlers with Autism
An NIMH-supported study shows that preference for geometric images may be robust enough to serve as a biomarker for identifying some young children with autism.

COVID-19 Pandemic Associated With Worse Mental Health and Accelerated Brain Development in Adolescents
An NIMH-supported study suggests that adolescents living through the COVID-19 pandemic may be experiencing more anxiety and depression symptoms and accelerated brain aging.

Family-Based Intervention Lowers Long-Term Suicide Risk in Youth
In a recent study supported by the National Institute of Mental Health, researchers examined the impact of a family-based intervention on suicide risk in youth and found risk-reduction benefits up to 10 years later.

Computational Methods Identify Psychosis Symptoms in Spoken Language
Researchers used computational methods to automatically detect abnormalities in spoken language that could be used to predict symptoms of psychotic disorders including schizophrenia.

Toddlers’ Responses to “Baby Talk” Linked to Social, Cognitive, Language Abilities
In an NIMH-supported study, researchers found that toddlers respond to emotionally expressive speech in different ways, and these varied responses are linked with their social, linguistic, and cognitive abilities.

Low Motivation for Social Bonding May Signal Behavior Problems in Early Childhood
In an NIMH-supported study, researchers found that low social affiliation—low motivation for social engagement and bonding—may be a precursor that identifies children as early as age 2 who are likely to develop callous-unemotional behaviors.

Adult “Picky Eaters” Recall Helpful Parent Feeding Strategies
Researchers asked a group of self-identified adult “picky eaters” to reflect on their parents’ feeding strategies to better understand which strategies were helpful and which weren’t.

Feelings of Detachment After Trauma May Signal Worse Mental Health Outcomes
A new NIMH-supported study shows that experiencing persistent feelings of detachment following trauma is an early psychological and biological marker of worse mental health outcomes.

Study Furthers Understanding of Disparities in School Discipline
A new NIMH-supported analysis shows that disciplinary disparities occur as early as preschool and that their effects can negatively influence how well students do in later years.

Machine Learning Study Sheds Light on Gaze Patterns in Adults With Autism
NIMH researchers examine what people with ASD and people without ASD look at when viewing a social scene.

Persistent, Distressing Psychotic-like Experiences Associated with Impairment in Youth
In this NIMH-funded study, researchers examined the association between distressing and persistent psychotic-like experiences in youth and important risk factors for psychopathology.

Brain Activity Patterns After Trauma May Predict Long-Term Mental Health
The way a person’s brain responds to stress following a traumatic event, such as a car accident, may help to predict their long-term mental health outcomes, according to NIMH-supported research.

Mapping ‘Imbalance’ in Brain Anatomy Across the Lifespan
Researchers in the NIMH Intramural Research Program have developed a new way to measure the degree to which the proportions of an individual person’s brain differ from the proportions typically seen in the broader population. This technique yields new insights into brain development and offers tools for further study.

Study Identifies Risk Factors for Elevated Anxiety in Young Adults During COVID-19 Pandemic
A new study has identified early risk factors that predicted heightened anxiety in young adults during the coronavirus pandemic.

NIMH Part of Collaborative Effort to Advance Early Intervention for Individuals at Risk of Developing Schizophrenia
NIMH has joined with other NIH Institutes in launching an new Accelerating Medicines Partnership focused on advancing the development of better ways to identify and treat those at clinical high risk for psychosis.

Outdoor Light Linked with Teens’ Sleep and Mental Health
A large-scale study of U.S. teens shows associations between outdoor, artificial light at night and health outcomes.

Transforming Mental Health Care Through ALACRITY
In 2018, 11.4 million adults in the United States experienced a serious mental illness, such as schizophrenia-spectrum disorders, severe bipolar disorder, and severe depression.

Combined Electroconvulsive Therapy and Venlafaxine a Well-Tolerated Depression Treatment for Older Adults
The use of right unilateral ultrabrief pulse (RUL-UB) electroconvulsive therapy (ECT) in combination with the antidepressant venlafaxine to treat depression in elderly patients is well tolerated and results in minimal neurocognitive side effects, according to a new NIH-funded study published in the American Journal of Geriatric Psychiatry.

Using Technology to Help Predict Binge and Purge Episodes in People with Eating Disorders
In binge-eating disorder and bulimia nervosa, people experience recurrent and frequent episodes in which they eat unusually large amounts of food and feel a sense of loss of control.

Identifying Practices for Reducing Incarceration of Those with Mental Illnesses—A Study of “Stepping Up”
According to a 2017 report by the Bureau of Justice Statistics, approximately two-thirds of female inmates in prisons and jails and around a third of men in prisons and jails report having been diagnosed as having mental health disorder by a mental health professional.