Bipolar Disorder Vulnerability

Perspectives from Pediatric and High-Risk Populations

Jair Soares, Consuelo Walss-Bass, Paolo Brambilla

• Publisher: Academic Press
• Year: 2018
• Print ISBN: 9780128123478
• eBook ISBN: 9780128125601
• Topic: Ciencias biológicas
• Subtopic: Neurociencia

Bipolar Disorder Vulnerability: Perspectives from Pediatric and High-Risk Populations synthesizes our current understanding of high-risk and pediatric populations to aid readers in identifying markers of vulnerability for the development of bipolar disorder, with an ultimate goal of the development of drug targets and other therapies for early diagnosis and treatment. The book provides readers with an understanding of biological and environmental factors influencing disease manifestation that will aid them in defining discrete clinical stages and, importantly, establish an empirical basis for the application of novel therapeutics in a phase of illness during which specific treatments could more effectively alter disease course.Whereas most of the literature available on the pathophysiological mechanisms of bipolar disorder focuses on chronically ill adult individuals, this represents the only book that specifically examines pediatric and high-risk populations. An estimated 30 to 60 percent of adult bipolar disorder patients have their disease onset during childhood, with early-onset cases representing a particularly severe and genetically loaded form of the illness.- Highlights diverse translational methodologies, including functional and structural neuroimaging, neuropsychological testing and integrated genomics- Examines molecular trajectories in youth with bipolar disorder and unaffected youth at high risk for developing bipolar disorder- Explores the interaction between genomic and environmental influences that shape behavior

Chapter 1

The bipolar prodrome

Danella M. Hafeman; Boris Birmaher Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States

Abstract

Converging evidence suggests that the onset of bipolar disorder is usually preceded by a prodromal period lasting months to years. In this chapter, we review studies that point to this prodrome, including family risk studies, studies of individuals with depression or cyclothymia, community studies, and retrospective studies. We review assessments used to predict bipolar disorder, as well as a risk calculator for predicting new-onset bipolar disorder. While each study design has its limitations, taken together, the literature begins to point to an initial nonspecific prodrome, including symptoms such as anxiety, depression, and mood lability. Closer to disorder onset, subthreshold manic symptoms become more prominent, and characterize a more specific prodrome. A better understanding of a staged prodrome is crucial to inform clinical management of individuals at familial or symptomatic risk of bipolar disorder, and aid in the selection of an “ultra-high-risk” population for future studies of biomarkers and therapeutics.

Keywords

Bipolar disorder; Prodrome; At-risk; Risk calculator; Study design; Questionnaires

Chapter Outline

• Introduction
• Methods
  • Study Design: Challenges and Strategies
  • Questionnaires/Assessments
• Results
  • Family Studies
  • Depressed Samples
  • Cyclothymia/BD-NOS Samples
  • Community Samples
  • Retrospective Studies: Metaanalyses and Reviews
  • Staging Models
  • Risk Calculator
• Summary and Future Directions
• References

Introduction

It has long been recognized that bipolar disorder rarely comes “out of the blue,” but rather is usually preceded by a period of time, lasting at least a month and up to several years of prodromal symptoms (Correll, Hauser, et al., 2014). A better understanding of prodromal bipolar disorder is essential for several reasons. First, there are often delays in diagnosis and treatment of bipolar disorder lasting an average of 10 years, leading to increased morbidity and poor function (Lish, Dime-Meenan, Whybrow, Price, & Hirschfeld, 1994). Second, even when individuals are identified early, it is often unclear how to treat them, due to concern that some medications (such as antidepressants) might exacerbate their symptoms. A better understanding of the bipolar prodrome might allow us to identify ultra-high-risk individuals, conduct studies to understand the neural correlates of bipolar risk, and test the effects of various classes of medications and/or psychotherapies in this population. In this chapter, we review what is currently known about the bipolar prodrome, from both retrospective and longitudinal studies. We first describe the methods that have been used to assess the bipolar prodrome, including study design and assessment tools. Next, we describe findings from individual studies that shed light on the course and characteristics of this prodrome. Finally, we describe recent directions to integrate these findings (e.g., staged model, risk calculator), and we present a current model for the prodrome based on the extant literature.

Methods

Study Design: Challenges and Strategies

There are significant challenges with studying prodromal symptoms of a relatively rare disorder like bipolar disorder. It would simply be impractical to well-characterize a sample from the general population, and follow them long enough to have a sufficient number develop bipolar disorder. Thus, there are a variety of strategies that have been used to shed light on this topic, each with its own strengths and limitations. Each provides a different view on this prodromal period, although, encouragingly, the findings from different strategies are quite similar, as we will discuss later. What we know about the bipolar prodrome comes from the following types of studies:

• • Family studies: There are several longitudinal studies of offspring of parents with bipolar disorder, which have well-characterized these at-risk offspring in childhood and adolescence, and prospectively followed them to assess new-onset disorders, including bipolar disorder (Birmaher, Axelson, Monk, et al., 2009; Duffy, Alda, Crawford, Milin, & Grof, 2007; Egeland et al., 2003; Hillegers et al., 2005). Because the onset of bipolar disorder is much more prevalent in individuals at familial risk, there are sufficient converters to evaluate clinical characteristics that might precede new-onset disorder. In addition, these individuals are at higher risk of other disorders as well, and have high levels of subsyndromal symptoms, so they also represent a clinically at-risk population that is important to characterize and better understand. There are some limitations to this approach, however. First, we don’t know that the course of the bipolar prodrome is similar in individuals with vs. without a first-degree relative with bipolar disorder, so it is unclear the degree to which these findings are generalizable to individuals without such family risk. Second, the prevalence of syndromal bipolar disorder (bipolar-I/II) in offspring is still fairly low (e.g., 8.4% in BIOS, though not all participants have passed the risk period), so large samples are required to have sufficient new-onset cases to make inference about predictors (Axelson et al., 2015). To handle this limitation, some groups have instead assessed less stringent outcomes, including bipolar spectrum disorder (which includes bipolar disorder, not otherwise specified) and “mood disorder” (which includes unipolar or bipolar depression). Another approach is to identify high-risk samples within the offspring of parents with bipolar disorder, based on the presence of mood, anxiety, and/or mood lability symptoms. Third, there is the important issue of comorbidity in the bipolar parents, and whether differences observed in offspring are related to the family history of bipolar disorder, per se, or a comorbidity. For example, in the Pittsburgh Bipolar Offspring Study, Attention-Deficit/Hyperactivity Disorder (ADHD) was higher in at-risk offspring than community controls. However, after adjusting for confounders (including nonbipolar psychopathology in both biological parents), this difference was no longer significant (Birmaher, Axelson, Monk, et al., 2009). Studies that recruit healthy controls (as opposed to including parents with nonbipolar psychiatric disorders) cannot necessarily conclude that a particular difference in at-risk vs offspring of healthy parents is due to the bipolar disorder (vs higher rates of ADHD, for example). Fourth, another critical issue when carrying out family risk studies is blinding. If the interviewer knows that a parent has bipolar disorder, ratings might be elevated due to expectations of worse outcomes. Most studies discussed here were blinded, except for the Dutch study, which only included offspring of parents with bipolar disorder (Mesman, Nolen, Reichart, Wals, & Hillegers, 2013). Fifth, when using parent report to assess a child’s psychiatric symptoms, it is important to take into account the current mood state of the reporting parent, since this can impact symptom ratings (Maoz, Goldstein, Goldstein, et al., 2014). This is especially crucial in family risk studies where, by definition, at least one parent has bipolar disorder, and thus over-reporting of symptomatology could bias parent-report measures of child psychopathology. Sixth, depending on the age range, participants might not have reached the peak period of conversion to bipolar disorder; thus, there is the possibility that some of the nonconverters might still develop the disorder. These issues have been summarized in previous reviews (DelBello & Geller, 2001; Hauser & Correll, 2013; Hunt, Schwarz, Nye, & Frazier, 2016).
• • Unipolar depression studies: An episode of unipolar depression, particularly with earlier age of onset and psychotic features, sharply increases the risk of new-onset bipolar disorder (Akiskal, Maser, Zeller, et al., 1995; Kovacs, 1996; Strober & Carlson, 1982). Thus investigators have prospectively assessed depressed individuals, to determine symptom predictors of conversion from unipolar depression to bipolar disorder. The strengths of this approach are the fact that it is prospective, and using a select population with conversion rates that allow for adequate cases of new-onset bipolar disorder, at least over a long follow-up (e.g., 19.6% over a mean follow-up period of 17.5 years) (Fiedorowicz et al., 2011). However, there are also some limitations. First, the rate of conversion is still relatively low over shorter periods of follow-up, thus necessitating a longer follow-up period or larger sample for adequate converters. One way that investigators have handled this is to narrow the selection criteria to participants with depression with psychotic features, thus increasing the base rate for developing bipolar disorder; however, this also makes recruitment more difficult. Second, as with the family studies, there is also the possibility that participants who have not passed the peak age of conversion might be misclassified as nonconverting. Third, selection of a sample based on unipolar depression means that the results might be specific to individuals that debut with a major depressive episode, and not necessarily generalize to those who have a different presentation (e.g., cyclothymia or initial mania/hypomania).
• • Cyclothymia/bipolar disorder-not otherwise specified (BD-NOS) samples: One of the strongest predictors of new-onset bipolar disorder is subthreshold manic episodes (see below for specific findings), and thus several studies have assessed the clinical variables that predict progression from BD-NOS to BD-I/II (Akiskal, Djenderedjian, Rosenthal, & Khani, 1977; Alloy, Urošević, et al., 2012; Axelson et al., 2011). Significant strengths of this approach are that conversion is high (30%–50% in ...

Table of contents

• Cover image
• Title page
• Table of Contents
• Copyright
• Contributors
• Foreword
• Chapter 1: The bipolar prodrome
• Chapter 2: Staging models and neuroprogression in bipolar disorder
• Chapter 3: Influence of early childhood trauma on risk for bipolar disorder
• Chapter 4: Gene-environment interactions in high-risk populations
• Chapter 5: Genetic risk in adult family members of patients with bipolar disorder
• Chapter 6: Neurobiological markers of stress in youth at risk for bipolar disorder
• Chapter 7: Neuroimaging findings in youth at risk for bipolar disorder
• Chapter 8: Neurocognitive findings in youth at high risk for bipolar disorder: Potential endophenotypes?
• Chapter 9: Neuropsychological and social cognitive function in young people at genetic risk of bipolar disorder
• Chapter 10: Cognitive and neural basis of hypomania: Perspectives for early detection of bipolar disorder
• Chapter 11: Early pharmacological interventions in youth
• Chapter 12: Psychological interventions in offspring of parents with bipolar disorder
• Chapter 13: Summary and integration of current findings: A model for bipolar disorder development
• Index