Biomarkers of Postpartum Psychiatric Disorders

Biomarkers of Postpartum Psychiatric Disorders provides an up-to-date reference on the current research relating to biomarkers in psychiatric disorders, including major depressive disorder, OCD and bipolar disorder in the immediate postpartum time-period. It is the only reference on the market that synthesizes and interprets available data and reviews clinical phenotypes. Topics cover hormonal contributions, immunology, epigenetics and neuroimaging. While the risk of psychiatric illness during pregnancy appears to be equivalent to the risk at any other time in a woman’s life, the risk in the immediate postpartum time period is dramatically increased, hence the importance of the discussions in this title.

• Identifies epigenetic, hormonal, immunological and neuroimaging biomarkers
• Provides biomarkers for depression, OCD and psychosis
• Includes clinical phenotypes for psychiatric disorders
• Discusses future research and directions in the field

• Language: English
• Publisher: Academic Press
• Release date: Sep 28, 2019
• ISBN: 9780128158364

Book preview

Biomarkers of Postpartum Psychiatric Disorders

Editors

Jennifer L. Payne

Johns Hopkins University, Baltimore, MD, United States

Lauren M. Osborne

Johns Hopkins University, Baltimore, MD, United States

Table of Contents

Cover image

Title page

Copyright

Contributors

Preface

Chapter 1. Clinical phenotypes of peripartum depression and time of onset: The PACT Consortium

Introduction

Rationale and creation of the PACT Consortium

Approach

Specific research aims of the PACT Consortium

Summary and future directions

Chapter 2. Genetic basis for postpartum depression

Introduction

General approach to genetic studies

Heritability and familial aggregation of PPD

Heritability of PPD versus nonpostpartum MDES

PPD and bipolar disorder

Genome-wide linkage and association studies

Candidate gene studies

Moving forward: approaches for identifyng the genetic basis of PPD

Conclusions

Chapter 3. Epigenetic biomarkers of postpartum depression

Introduction

Estrogen-based epigenetic studies in postpartum depression

Oxytocin receptor epigenetic studies of postpartum depression

Conclusions

Chapter 4. Potential hormonal and neurochemical biomarkers for postpartum depression

Introduction

Neuroactive steroid hormones

The HPA axis

Thyroid hormones

The monoamines

Brain-derived Neurotrophic factor

The microbiome

Conclusions

Chapter 5. Immunological biomarkers of postpartum depression

Introduction

Early work

Interleukin 6

Other cytokines

More complex immune markers and associations

Discussion

Chapter 6. Phenomenology of perinatal obsessive–compulsive disorder

Introduction

Clinical phenomenology

Comorbidity and differential diagnoses

Prevalence and incidence

Maintaining factors

Case vignette

Summary and conclusions

Chapter 7. Genetics of perinatal obsessive–compulsive disorder: A focus on past genetic studies to inform future inquiry

Introduction

Family and twin studies

Linkage studies

Genome-wide association studies

Candidate genes

Conclusion

Chapter 8. Hormonal contributions to perinatal obsessive–compulsive disorder

Introduction

Evidence for contribution by specific hormones

The hypothalamic–pituitaryadrenal axis and cortisol

Challenges

Future directions

Chapter 9. Immunological biomarkers of postpartum obsessive–compulsive disorder

Introduction

Autoantibodies and OCD

Inflammatory biomarkers and OCD

Leukocyte subpopulations and OCD

Treatment effects on immune parameters

OCD in the perinatal period: future directions for immune research

Chapter 10. Clinical phenotypes of postpartum psychosis

Introduction

Terminology

Epidemiology

Risk factors

Clinical presentation

Assessment and diagnosis

Differential diagnosis

Screening and prevention

Chapter 11. Genetic basis for postpartum psychosis

Introduction

Clinical and epidemiological studies

Molecular genetic studies

Future directions

Chapter 12. Hormonal and immunological factors in postpartum psychosis

Introduction

Hormonal changes associated with postpartum psychosis

Immunological changes associated with postpartum psychosis

Conclusions

Chapter 13. Functional MRI biomarkers of peripartum psychiatric disorders

Introduction

Methods

Results

Discussion

Chapter 14. Synthesis and future directions

Because the rate of psychiatric illness increases in the immediate postpartum time period, this period represents a unique research opportunity to identify the biological causes of psychiatric illness more generally

There is much more research on postpartum depression than other postpartum psychiatric illnesses

Timing of onset of illness may matter

It remains unclear if perinatal psychiatric illness is biologically distinct from psychiatric illness outside of the peripartum

Sensitivity to times of hormonal change may be present in a subset of women with psychiatric illness

In most areas, it is premature to talk about biomarkers

It is likely that a combination of factors, including genetics, hormonal changes, and immune system changes, underlie the pathogeneisis of postpartum psychiaric illness

Index

Copyright

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Contributors

Jonathan S. Abramowitz,     Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States of America

Jennifer L. Buchholz,     Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States of America

Kristina M. Deligiannidis

Women's Behavioral Health, Department of Psychiatry, Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY, United States of America

Departments of Psychiatry and Obstetrics & Gynecology, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, United States of America

Feinstein Institute for Medical Research, Manhasset, NY, United States of America

Arianna Di Florio

Cardiff University, Cardiff, United Kingdom

University of North Carolina at Chapel Hill, Chapel Hill, NC, United States of America

Christy Duan,     Department of Psychiatry, Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY, United States of America

Jerry Guintivano,     Department of Psychiatry, University of North Carolina at Chapel Hill, NC, United States of America

Liisa Hantsoo,     Department of Psychiatry, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States of America

Megan Hare,     Department of Psychology, Florida International University, Miami, FL, United States of America

Samantha N. Hellberg,     Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States of America

Zachary Kaminsky,     DIFD Mach-Gaensslen Chair of Suicide Prevention Research, The Royal's Institute of Mental Health Research (IMHR), Associate Professor of Cellular and Molecular Medicine, University of Ottawa, Ottawa, Ontario, Canada

Mary Kimmel,     Department of Psychiatry, University of North Carolina School of Medicine, Chapel Hill, NC, United States of America

Jamie Maguire,     Tufts University School of Medicine, Department of Neuroscience, Boston, MA, United States of America

Katherine McEvoy,     Perinatal Psychiatry, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America

Samantha Meltzer-Brody,     Department of Psychiatry, University of North Carolina at Chapel Hill, NC, United States of America

Gerald Nestadt,     Department of Psychiatry and Behavioral Sciences at Johns Hopkins Medical Institutions, Baltimore, Maryland, United States of America

Lauren M. Osborne

Department of Psychiatry & Behavioral Sciences, The Johns Hopkins University School of Medicine, Baltimore, MD, United States of America

Department of Gynecology & Obstetrics, The Johns Hopkins University School of Medicine, Baltimore, MD, United States of America

Women's Mood Disorders Center, The Johns Hopkins University School of Medicine, Baltimore, MD, United States of America

Jennifer L. Payne

Department of Psychiatry & Behavioral Sciences, The Johns Hopkins University School of Medicine, Baltimore, MD, United States of America

Department of Gynecology & Obstetrics, The Johns Hopkins University School of Medicine, Baltimore, MD, United States of America

Women's Mood Disorders Center, The Johns Hopkins University School of Medicine, Baltimore, MD, United States of America

Karen T. Putnam,     Department of Psychiatry, University of North Carolina at Chapel Hill, NC, United States of America

Jack Samuels,     Department of Psychiatry and Behavioral Sciences at Johns Hopkins Medical Institutions, Baltimore, Maryland, United States of America

Lindsay R. Standeven,     Department of Psychiatry and Behavioral Sciences at Johns Hopkins Medical Institutions, Baltimore, Maryland, United States of America

Patrick F. Sullivan

Department of Psychiatry, University of North Carolina at Chapel Hill, NC, United States of America

Department of Genetics, University of North Carolina at Chapel Hill, NC, United States of America

Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden

Preface

For the last several years, the academic medical world has been abuzz about personalized medicine—the tailoring of medical treatment to characteristics that, if not unique, are specific to individuals. This approach assumes that many medical disorders may carry a single name but in reality be heterogeneous disorders, with many pathways toward a common end. To create truly personalized medicine, we need to have a full understanding of the varied processes—from genes, to gene expression, to environmental influences, to changes at the molecular and cellular level—that go into creating the symptoms of a disorder in any particular individual.

One hallmark of that understanding is the search for biomarkers, quantifiable biological parameters (Selleck, Senthil, & Wall, 2017) that can indicate the presence of disease or response to treatment. Some of the earliest biomarkers in medicine were noticed nearly 200  years ago, though with little understanding of their actual function, and the NIH now defines many types of biomarkers across most fields of medicine (FDA-NIH Biomarker Working Group, 2016). Biomarkers can serve many functions—they can help to diagnose a condition (as with hemoglobin A1c for type 2 diabetes), or to monitor a known condition (as with prostate-specific antigen [PSA] for those with prostate cancer). They can measure the response to treatment (for example, blood pressure for patients with hypertension given an antihypertensive treatment) or predict the likelihood of response to an exposure (for example, BRCA1 and 2 to evaluate which women will respond to certain ovarian cancer treatments). They can also be prognostic—identifying the likelihood of a clinical event or recurrence (BRCA1 and 2 to predict who will develop a second breast cancer) or the likelihood of disease developing among those currently without disease (again, BRCA1 and 2).

The idea of the biomarker of risk is enormously appealing—a liquid biopsy (Selleck et al., 2017) would allow those with a high likelihood of disease to get serial monitoring that is noninvasive, simple, and far less expensive than many monitoring techniques (such as imaging). The reality, though, is that in many fields biomarkers are still in the world of research and have not yet made it to a clinically useful stage. To be clinically useful, a biomarker must give us more information than whatever we currently use to predict risk and must be specific to the disease in question. It is not useful to find a protein that is elevated in people who will go on to develop a particular disease if that protein is also elevated in those who will not develop the disease. Nor is it useful to find a biological means to predict disease if it does not increase our prediction ability above means we already have, or by means of a test so expensive that it cannot be used by the majority of people. When we apply these criteria, we realize that while many purported biomarkers have been discovered through exploratory scientific approaches, few have been replicated in diverse populations and developed into clinically meaningful tests.

Nowhere is this more true than in psychiatry. Other fields of medicine have at least a smattering of somewhat useful biomarkers—again, think BRCA1 and 2 in cancer—but the search in psychiatry has proved elusive. The search itself has been energizing, with researchers employing many fields and techniques (genetics, epigenetics, neuroimaging, electrophysiology, the inflammatory system, and others). Moreover, the appeal of a biomarker in psychiatry is perhaps greater than in other fields of medicine, for we have no uniform objective means to diagnose psychiatric illness. Our current methods, which rely on the Diagnostic and Statistical Manual to categorize related groups of symptoms into heterogeneous diagnostic categories, are insufficient, and the allure of a specific biological test is mighty—yet the very nature of our diseases, and the complex roots of their causes blending biology with environment, has made this search elusive. There are no currently accepted specific biomarkers in psychiatry (Lozupone et al., 2019).

So if there are no biomarkers in psychiatry, why this book? This book exists because we view the perinatal period as potentially the most useful timepoint in the life course to search for these elusive biomarkers, and we wanted a chance to collect here the current state of that search. The two of us came at our interest in perinatal mental illness, and our conviction of the unique usefulness of this period for scientific discovery, from two very different perspectives. One of us (JLP) came from a neuroscience background, and spent her early training years wondering what the broken part might be in mood disorders, including major depression and bipolar disorder. By that time, it had become clear that research was not going to identify a single genetic or biological etiology for either major depression or bipolar disorder, that these illnesses were likely the result of polygenetic vulnerabilities plus environmental influences, and further, that these illnesses were likely to have multiple underlying biological broken parts. As she thought further about how to try to identify more homogenous subgroups that might allow us to study the underlying biology, she suddenly realized that postpartum psychiatric illnesses, which certainly appeared to be triggered by the massive hormonal changes that accompany delivery, might be one such group. The predictable timing of the postpartum time period would allow us to study a group with a known timeframe for developing disease, and the insights thus gleaned could then be applied back to other psychiatric illnesses. The other of us (LMO) came from an obstetrics and gynecology background, looking at perinatal mental illness as a morbidity of pregnancy. She realized early in her training that there are vast bodies of research on how pregnancy affects many bodily systems, from research on preeclampsia and gestational diabetes to that on the behavior of autoimmune disease in pregnancy, and more. We have at least diagnostic (if not predictive) biomarkers for some of those entities (as in elevated glucose for diabetes and protein in the urine for preeclampsia), but very little understanding of how the biological and psychosocial changes of pregnancy and the postpartum create changes in the brain—hence a search for biomarkers that came from the idea of treating perinatal mental illness as an obstetrical morbidity.

This book, then, is not a catalog of existing biomarkers, but rather an attempt to gather together in one place what is currently known about biomarkers that are predictive of or reflective of postpartum psychiatric illness including (but not limited to) postpartum depression, postpartum obsessive–compulsive disorder (OCD), and postpartum psychosis. The reader will note that there are large gaps in knowledge—more is known about postpartum depression, for example, than postpartum OCD, and there are whole areas that have just begun to be explored, including immunological and imaging biomarkers. The newer fields of proteomics and metabolomics are only beginning to be applied to perinatal mental illness, and there is not enough research on these areas yet to catalog them here. It is our hope that this work will serve as a road map for future researchers to fill in these gaps.

This book would not be possible without the research and writing of all those who have contributed, nor without the efforts of other collaborators whose work is not represented here, the hundreds of research staff members who have helped us accomplish this work, and the thousands of research participants who have volunteered their time and their brains and bodies. Progress in science is a team sport, and we have been honored to work with such outstanding colleagues. It is our hope that we will revisit this book again in the future and be able to fill in many of the gaps that now exist with data and answers that are sorely needed. Enjoy!

Lauren M. Osborne, MD

Jennifer L. Payne, MD

Editors

References

FDA-NIH Biomarker Working Group. BEST (Biomarkers, EndpointS, and other Tools) resource. Silver Spring (MD): Food and Drug Administration (US); 2016.

Lozupone M, La Montagna M, D'Urso F, Daniele A, Greco A, Seripa D, … Panza F. The role of biomarkers in psychiatry. Advances in Experimental Medicine & Biology. 2019;1118:135–162. doi: 10.1007/978-3-030-05542-4_7.

Selleck M.J, Senthil M, Wall N.R. Making meaningful clinical use of biomarkers. Biomarker Insights. 2017;12 doi: 10.1177/1177271917715236 1177271917715236.

Chapter 1

Clinical phenotypes of peripartum depression and time of onset

The PACT Consortium

Jerry Guintivano¹, Karen T. Putnam¹, Patrick F. Sullivan¹,²,³, and Samantha Meltzer-Brody¹     ¹Department of Psychiatry, University of North Carolina at Chapel Hill, NC, United States of America     ²Department of Genetics, University of North Carolina at Chapel Hill, NC, United States of America     ³Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden

Abstract

The Postpartum Depression: Action Towards Causes and Treatment (PACT) Consortium was created to increase our understanding of the heterogeneity of the perinatal period and to address the gaps in knowledge. This international research consortium subscribes to successful models of team science, whereby collaboration and sharing of clinical phenotypic and genetic data allows for the attainment of the large sample sizes needed to answer some of the challenging questions facing the field and move it forward. This chapter describes the development and work of the PACT Consortium to date and maps out the plans for next steps with a focus on improving outcomes for women and their families that suffer from PPD.

Keywords

Consortium; Genetics; GWAS; Heterogeneity; Peripartum; Personalized medicine; Phenotypes; Postpartum depression

Introduction

The perinatal period is well documented as a high-risk time for onset of psychiatric disorders, including postpartum depression (PPD) and is associated with significant morbidity for mother, infant, and family (Meltzer-Brody et al., 2018). This manifests as an observed increased risk for low birth weight and prematurity, impaired mother–infant attachment, and infant malnutrition during the first year of life (Gavin et al., 2005; Parsons, Young, Rochat, Kringelbach, & Stein, 2012). Perhaps most concerning, maternal suicide in the postpartum period has been identified as a leading cause of maternal mortality (Johannsen et al., 2016). Perinatal depression (PND), broadly defined by the World Health Organization as onset of a major depressive episode during pregnancy or across the first 12  months postpartum, has a lifetime prevalence of 10%–15% (Gavin et al., 2005) in industrialized countries and higher risk in lower-income countries (Sawyer, Ayers, & Smith, 2010). The greatest point prevalence for onset of symptoms is the acute postpartum period (Munk-Olsen, Laursen, Pedersen, Mors, & Mortensen, 2006), but there is growing evidence that many women have onset of symptoms during pregnancy (Biaggi, Conroy, Pawlby, & Pariante, 2016). The public health importance of identifying women who suffer with PND was highlighted by new recommendations of the United States Preventive Services Task Force for depression screening during both pregnancy and postpartum (McKinney, Keyser, Clinton, & Pagliano, 2018; O'Connor, Rossom, Henninger, Groom, & Burda, 2016; O'Connor, Senger, Henninger, Coppola, & Gaynes, 2019). This is also consistent with international guidelines from the United Kingdom (National Institute for Health and Clinical Excellence, 2014), Australia (Australian Government Department of Health, 2013), and the World Health Organization recommendations (World Health Organization, 2015).

The Postpartum Depression: Action Towards Causes and Treatment (PACT; www.pactforthecure.com) Consortium was created to increase our understanding of the heterogeneity of the perinatal period and to address the gaps in knowledge about this important illness. This international research consortium subscribes to successful models of team science, whereby collaboration and sharing of data allows for the attainment of the large sample sizes needed to answer some of the challenging questions facing the field. The PACT Consortium has been focused on elucidating the causes of peripartum psychiatric illness so that tailored prevention is possible and personalized effective treatments are developed. This work is vital given the morbidity associated with PND. Women who experience perinatal psychiatric episodes are at higher mortality risk compared with mothers without psychiatric diagnoses, and the first year after diagnosis represents a time of particularly high relative risk for suicide in this vulnerable group (Johannsen et al., 2016).

Rationale and creation of the PACT Consortium

There is a great need to increase our understanding of the phenotypic differences, course, and prognosis for PND. The past decade has seen significant progress in terms of documentation of the prevalence and has considered hot button questions that elicit discussion within the field, namely: (1) is PPD a distinct disorder that is fundamentally different from major depression outside of the perinatal period or is it a subtype of major depression? (2) Is childbirth a trigger for the onset of postpartum psychiatric illness? (3) What is the most scientifically logical approach to define postpartum depression? Specifically, should the definition of PPD refer only to onset of symptoms in the immediate postpartum period, or should the definition be broadened to also include onset of symptoms