Stevenson

Transdisciplinary Translational Science and The Case of Preterm Birth Supplement

David K. Stevenson MD1, Gary M. Shaw DrPH1, Paul H. Wise MD, MPH1, Mary E. Norton MD1, Maurice L. Druzin MD1, Hannah A. Valantine, MD1 and Daniel A. McFarland PhD2 on behalf of the March of Dimes Prematurity Research Center at Stanford University School of Medicine 1 Stanford University School of Medicine 2 Stanford University School of Education

Corresponding author: David K. Stevenson, MD Stanford University School of Medicine 750 Welch Road, Suite 315 Palo Alto CA 94304 Phone: 650-724-6966 Fax: 650-498-4072 Email: [email protected]

The March of Dimes Foundation and Stanford University School of Medicine provided grant support for March of Dimes Prematurity Research Center at Stanford University School of Medicine.

Conflict of interest The authors declare no conflict of interest.

Efforts to Bring About Intellectual Integration

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Ontological Focus

The mere establishment of the Center and attraction of members has created a shared identity and greater interpersonal awareness of members’ common interests. However, the problem of preterm birth is complex, and most of these researchers focus on a narrow feature of it. To facilitate broader dialogue and integration of knowledge, the Center is conducting its knowledge integration efforts in stages, beginning locally, and then spanning greater intellectual distances. In the first stage, it has created sub-topical areas of inquiry and the development of shared datasets that span these areas. Topical areas provide a local basis for intellectual integration, and use of shared datasets attempts to draw wider sets of more distantly related scholars together.

The sub-topics, or areas of inquiry, were formed on the basis of several criteria. First, the areas represent research arenas that experts believed would most advance preterm birth research. Second, the areas involve complex mechanisms likely to benefit from intense cross- disciplinary interaction. Third, the areas were chosen to take advantage of advanced expertise and capabilities that exist at Stanford University and the Center’s affiliated research, clinical, and public health institutions. Although the number and focus of the Center’s Areas of Inquiry are expected to grow, evolve, or be “sun-setted,” four were developed to serve as the initial foundation for Center research activities. Each area brings scholars from multiple disciplines and clinical fields together to share their expertise on a phenomenon at a level of specificity with which they are familiar. Each area is provided renewable research funds for engaging in heterogeneous, multi-lab collaborations. This encourages local mixing, and is believed to form points of agreement that will become a foundation for more general discussions across areas, methodologies and causal factors. More detail on these areas of inquiry follows.

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Pattern Recognition Discovery Area: This group - composed of mathematicians,

systems engineers, computer scientists, economists, demographers, epidemiologists

and clinicians – is directed at generating new etiologic hypotheses for preterm birth by

exploring space/time patterns of preterm birth in the US in relation to a broad set of

factors including seasonal, weather, geographical, and regional health risks as well as

other indicators using artificial intelligence and other nontraditional, analytic techniques.

The clinicians are the ones who can actually give meaning to any observed significant

trends, while the mathematicians, systems engineers and computer scientists introduce

novel methods to identify relationships that might suggest previously unrecognized

contributing causes of preterm birth that can be studied.

Bioinformatics Gene-Environment Discovery Area: This group – composed of

bioinformaticians, geneticists, epidemiologists, and pediatricians - identifies candidate

genes, gene-environment interactions, and novel maternal biomarkers for preterm birth

by integrating large-scale bioinformatics platforms with a variety of clinical and

sociodemographic datasets.

Infection/Stress/Inflammation Discovery Area: This group – composed of

immunologists, obstetricians, geneticists, and more - explores the contribution of the

human microbiome and host immune response during pregnancy in relation to a variety

of human stressors in shaping patterns of preterm birth.

Placental Implantation/Function Discovery Area: This group – composed of

geneticists, pathologists, obstetricians, pediatricians, and more - explores morphologic,

histologic, genetic and epigenetic placental features and abnormalities, and their

associations with preterm birth. This area is already being integrated into other areas

and core resources.

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The accrual, linking, and use of large datasets are a core activity of the Center. The breadth and heterogeneity of information compiled by the Center reflects an expanded ontological boundary to the phenomenon of preterm birth. Two data collection efforts are underway, one for large populations, and another for biologic material.

Compiling data for large populations has, in part, involved capitalizing on a number of extant databases, some of which are unique to California. These include: a) California

Perinatal and Maternal Quality Care Collaborative (CPQCC and CMQCC) datasets (1); b) Office of Statewide Health Planning and Development Patient Discharge and Emergency

Department (OSHPD) dataset (2); c) United States Standard Certificates of Live Birth (NCHS) dataset; d) Air Quality System (AQS) dataset, and e) Meteorological dataset from United

States Environmental Protection Agency. In addition to the selected linkage across these datasets, the Center is also developing an extensive, prospective database, which will include clinical, sociodemographic, and attitudinal data, and be linked to a biobank of existing maternal and newborn specimens. These resources are intended to provide unprecedented opportunities to generate insight into complex interactions of biologic, clinical, and social factors in shaping the risk for preterm birth.

A second collection effort is underway to prospectively collect biospecimens related to preterm birth, including placenta, cord blood, and maternal blood. In addition, the Center is recruiting patients for a longitudinal microbiome sample collection where biospecimens are being collected for several months starting before the patient becomes pregnant. The development of a data protocol for biospecimens involved members of both the infection/inflammation and placenta inquiry areas and the Spectrum Child Health component of

Stanford’s CTSA. In practice, personnel from multiple inquiry areas were brought together to

TransdisciplinaryTranslational ScienceSupplement Stevenson hear each other’s empirical needs and learn of competing as well as shared interests. Thus, the collaboration forged a larger integration of views.

Methodological Focus

A second point of intellectual focus concerns the development of new methods and approaches that the Center’s members can share. With this larger, more integrated corpus of information, researchers cannot fall back on their traditional, disciplinary methods of inquiry.

Just as the phenomenon of preterm birth extends beyond any one disciplinary lens, so are the methods applicable to it.

In order to generate methodological familiarity and understanding, various subgroups in the center have begun methodological discussions. For example, in the data group focused on compiling population data, they are trying to share expertise on the methods used by different individuals. In this manner, participants have commenced a multi-disciplinary conversation on methods so as to get a sense for how the participants analyze their data differently. The leader of the group has called these brief introductions and explanations of methods, “speed- geeking”, partly in jest. In some sense, these discussions are a first step towards transdisciplinary collaboration.

The Center is taking further steps toward interdisciplinary and transdisciplinary integration of methods by discussing the development of new methods and tools that have the potential to reveal insights into the causes of preterm birth. Some of the methodological development is necessarily focused on data linkage techniques including both sequential deterministic and multistage probabilistic linkage methods with validation cycles. However, given that the data entail massively multivariate longitudinal information, the Center has begun to consider a variety of novel analytical approaches that are less familiar to current medical research. Some of these approaches can be found in cutting edge statistical techniques like TransdisciplinaryTranslational ScienceSupplement Stevenson latent class and growth mixture modeling techniques (3, 4) that identify clusters of variables that change in similar patterns. It is possible that irregularities in normal gene-environment dynamics correspond with the incidence of preterm birth. The project is also putting a significant amount of effort into methodological approaches that integrate gene-environment and epigenetic mechanisms associated with preterm birth.

All of these methodological concerns are relevant to each area of inquiry and are implemented to assist in the interrelation of the Center and the creation of larger integrative models. The Center is planning a variety of events where these methodological discussions can be had within and across inquiry areas. The project is also bringing in biostatisticians and methodologists to work with the Center’s domain experts and develop approaches that meet shared needs and empirical concerns.

Epistemological Focus

Disciplinary silos establish narrow boundaries not only for the phenomenon in question and the methods to study it, but also for the concepts, language, and explanatory theories used to explain it. To overcome intellectual balkanization and to promote transdisciplinary science, the

Center has commenced a variety of efforts to forge a shared epistemology, or set of shared terms and concepts, as well as integrative theories.

Perhaps the most obvious and difficult means to forging shared language and understanding is to meet often as a research team. For large groups of heterogeneous faculty that are spread across a university, this is a difficult task. The Center has partly addressed this by successfully scheduling regular meetings in the same location where participants present and discuss shared work (e.g., every Wednesday). This has helped researchers schedule their time and consistently participate in a sustained dialogue. Initially, participants talked past one another, but over time, they have come to comprehend each other’s “language” –e.g., the data TransdisciplinaryTranslational ScienceSupplement Stevenson and unit of analysis they focus on, the concepts and methods they use, but also their modes of inference.

The Center has begun another means of forging a shared epistemology by forming a shared knowledge base. The Center attempts to do this by summarizing and cataloguing prior preterm birth research. The cataloguing and curation of prior work is more of an epistemological effort than an ontological one because it identifies findings, explanations and understandings of a phenomenon, while ontological efforts concern the phenomenon as it is

(e.g., data on preterm birth).

The Center charged a sub-committee with the task of summarizing prior literature in a format that is digestible to members of all fields involved in the Center. Initial efforts began with seminal reports on preterm birth (5) and expanded to identify a corpus of over 5000 publications. Two types of bibliographic databases are being formed. The first database utilizes all these documents in an automated fashion and allows users to input a hypothetical research abstract so as to learn what texts they should cite (6). The procedure uses available text and meta-data (e.g., authors, citations, subject categories) associated with each publication and uses machine learning to identify texts that are most related to each other. The procedure calibrates the weighting of article features (e.g., author networks, co-citation, citation, subject category usage, rare term usage and even sublanguages) according to expert opinions, and thereby outperforms other database search procedures. The second effort is a curation project focused on the most central empirical papers in the preterm birth corpus (7).

The curation project entails manual coding of various features: data cohorts investigated and their characteristics (age, sex, etc); definitions used in the papers; laboratory methods, models and measures used; etc. The database itself will also serve as a substrate for discovery using

TransdisciplinaryTranslational ScienceSupplement Stevenson meta-analysis tools to identify potentially unrecognized patterns in the published literature that could further inform investigational paths or topics.

The Center is also attempting to develop shared theories that members can draw upon in their explanations of preterm birth. For example, stressors that are described from a social science perspective might also be understood simultaneously from genetic, epigenetic or signaling perspectives. Thus, stress could be understood in social terms as well as biologic terms and the solution to reducing stress might involve simultaneously integrated or coordinated social or pharmacological interventions.

Ecological and systems theory perspectives are also being drawn upon as models for interpreting multi-level effects (8, 9). There, arguments and statistical procedures have been developed for assessing direct, indirect, and cross-level effects. The point is not the particular method, but rather the Center’s concerted effort to develop multi-level, integrated understandings of how preterm birth may arise more for say African Americans due to poverty, and corresponding available diets and lifestyles, as well as stress. This then may lead to an imbalanced microbiome and their genetic response is one of placental inflammation, and in turn, preterm birth, or preeclampsia. This causal pathway is, of course, largely hypothetical at this stage, but the point is that the Center is taking steps to develop an integrated, holistic understanding of this complex problem.

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E. References

1. Gould JB. The role of regional collaboratives: the California Perinatal Quality Care

Collaborative model. ClinPerinatol2010; 37:71-86.

2. Chamberlain LJ, Chan J, Mahlow P, Huffman LC, Chan K, Wise PH. Variation in

specialty care hospitalization for children with chronic conditions in California: A total-

population study. Pediatr2010; 125(6): 1190-1199.

3. Collins LM. Analysis of Longitudinal Data: The Integration of Theoretical Model,

Temporal Design, and Statistical Model. Annu Rev Psychol2006; 57: 505–28.

4. Jung T, Wickrama KAS. An Introduction to Latent Class Growth Analysis and Growth

Mixture Modeling. Social and Personality Psychology Compass2008;2(1): 302–317.

5. Behrman RE, Butler AS, Eds. Preterm Birth: Causes, Consequences, and

PreventionInstitute of Medicine of the National Academies, Committee on

Understanding Premature Birth and Assuring Healthy Outcomes. National Academies

Press: Washington DC, 2007.

6. Bethard S, Jurafsky D. Who should I cite? Learning literature search models from

citation behavior. Proceedings of the 19th Association for Computing Machinery

International Conference on Information and Knowledge Management, Association for

Computing Machinery, Toronto, ON, Canada, October 26-30, 2010. Association for

Computing Machinery, New York, NY, 2010.

7. Liu Y, Coulet A, LePendu P, Shah NH. Using ontology-based annotation to profile

disease research. J Am Med Inform Assoc2012; e-pub ahead of print 11 April 2012;

doi:10.1136/amiajnl-2011-000631.

8. Blakely TA, Woodward AJ. Ecological Effects in Multi-Level Studies. Journal of

Epidemiology and Community Health2000; 54: 367-374.

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9. Simon HA.The Sciences of the Artificial. MIT Press: Cambridge, MA, ed. 3, 1996.

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Acknowledgments: The March of Dimes Foundation and Stanford University School of

Medicine provided grant support for March of Dimes Prematurity Research Center at

Stanford University School of Medicine. The Principal Investigator and Director of the

Center is David Stevenson, MD and the Co-Principal Investigators are Maurice L. Druzin,

MD, Gary M. Shaw, DrPH and Paul H. Wise, MD, MPH

The following investigators, in addition to those listed as authors participate in the

development, inquiry and reporting on the Center:

Pattern Recognition Discovery: Rich Mahoney, PhD (SRI International), John Byrnes,

PhD, Ciaran Phibbs, PhD, David Hill, David Stevenson, MD, Jeffrey Gould, MD, MPH,

James Jones, PhD, Joyce Fu, MD, Mark Johnson, Mary Norton, MD, Mark Taslimi, MD,

Pablo Garcia, MD, Paul Wise, MD

Bioinformatics and Gene Environment Discovery: Atul Butte, MD, PhD, Robert

Tibshirani, PhD, Stephen Quake, PhD, Hank Greely, PhD, Michael Snyder, PhD,

Yasser El-Sayed, MD, Jeff Gould, MD, MPH, David Stevenson, MD

Infection and Inflammation Discovery: David Relman, MD Robert Sapolsky, PhD, Russ

Altman, PhD, Christopher H. Contag, PhD, Mildred Cho, PhD, Anna A. Penn, MD, PhD,

Gary M. Shaw, DrPH, Paul H. Wise, MD, MPH, Deirdre Lyell, MD

Placental Implantation and Function Discovery: Julie Baker, PhD, Amy McKenney, MD,

Anna A. Penn, MD, PhD, Elliott Main, MD, Henry Lowe, MD, Gary Shaw, DrPH, Theo

Palmer, MD, Carlos D. Bustamante, MD, Peter Parham, PhD, Rich Mahoney, PhD

Transdisciplinary Evaluation: Karen S. Cook, PhD, Daniel McFarland, PhD,

ElinaMakinen, Chris John Frank

Data Resource: Jeffrey B. Gould, MD, MPH, Henry Lowe, MD, Susan Weber, PhD and

Vandana Sundaram, MS

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