Validation of PhenX measures in the personalized medicine research project for use in gene/environment studies

Toward standardization, harmonization, and integration of social determinants of health data: A Texas Clinical and Translational Science Award institutions collaboration

Introduction

The focus on social determinants of health (SDOH) and their impact on health outcomes is evident in U.S. federal actions by Centers for Medicare & Medicaid Services and Office of National Coordinator for Health Information Technology. The disproportionate impact of COVID-19 on minorities and communities of color heightened awareness of health inequities and the need for more robust SDOH data collection. Four Clinical and Translational Science Award (CTSA) hubs comprising the Texas Regional CTSA Consortium (TRCC) undertook an inventory to understand what contextual-level SDOH datasets are offered centrally and which individual-level SDOH are collected in structured fields in each electronic health record (EHR) system potentially for all patients.

Methods

Hub teams identified American Community Survey (ACS) datasets available via their enterprise data warehouses for research. Each hub's EHR analyst team identified structured fields available in their EHR for SDOH using a collection instrument based on a 2021 PCORnet survey and conducted an SDOH field completion rate analysis.

Results

One hub offered ACS datasets centrally. All hubs collected eleven SDOH elements in structured EHR fields. Two collected Homeless and Veteran statuses. Completeness at four hubs was 80%-98%: Ethnicity, Race; < 10%: Education, Financial Strain, Food Insecurity, Housing Security/Stability, Interpersonal Violence, Social Isolation, Stress, Transportation.

Conclusion

Completeness levels for SDOH data in EHR at TRCC hubs varied and were low for most measures. Multiple system-level discussions may be necessary to increase standardized SDOH EHR-based data collection and harmonization to drive effective value-based care, health disparities research, translational interventions, and evidence-based policy.

Why Is the Electronic Health Record So Challenging for Research and Clinical Care?

BACKGROUND

 The electronic health record (EHR) has become increasingly ubiquitous. At the same time, health professionals have been turning to this resource for access to data that is needed for the delivery of health care and for clinical research. There is little doubt that the EHR has made both of these functions easier than earlier days when we relied on paper-based clinical records. Coupled with modern database and data warehouse systems, high-speed networks, and the ability to share clinical data with others are large number of challenges that arguably limit the optimal use of the EHR OBJECTIVES:  Our goal was to provide an exhaustive reference for those who use the EHR in clinical and research contexts, but also for health information systems professionals as they design, implement, and maintain EHR systems.

METHODS

 This study includes a panel of 24 biomedical informatics researchers, information technology professionals, and clinicians, all of whom have extensive experience in design, implementation, and maintenance of EHR systems, or in using the EHR as clinicians or researchers. All members of the panel are affiliated with Penn Medicine at the University of Pennsylvania and have experience with a variety of different EHR platforms and systems and how they have evolved over time.

RESULTS

 Each of the authors has shared their knowledge and experience in using the EHR in a suite of 20 short essays, each representing a specific challenge and classified according to a functional hierarchy of interlocking facets such as usability and usefulness, data quality, standards, governance, data integration, clinical care, and clinical research.

CONCLUSION

 We provide here a set of perspectives on the challenges posed by the EHR to clinical and research users.

The individual, interactive, and syndemic effect of substance use, depression, education, and ethnicity on retention in HIV care

In this study, we sought to assess the individual, syndemic, and interactive associations between individual-level factors and retention in care. The sample was derived from the Miami Adult Studies on human immunodeficiency virus (HIV)/ acquired immune deficiency syndrome (AIDS) cohort from 2009 to 2014. The variables were entered into a multiple logistic regression with retention as the outcome. Backward regression, adjusting for all main effects, was conducted to determine which two-way interactions were associated with retention. Multivariable logistic regression was used to test which number of factors were associated with retention. Non-Hispanic Black race/ethnicity was associated with improved retention (odds ratio [OR] = 2.44, 95% confidence interval [CI]: 1.06-5.75, p ≤ 0.05) when compared to Non-Hispanic White persons. Black-Hispanic and Other racial/ethnic identities were associated with increased retention (OR = 4.84, 95%CI: 1.16-25.79, p ≤ 0.05 and OR = 7.24, 95%CI: 1.54-54.05, p ≤ 0.05, respectively) when compared to Non-Hispanic White persons. The interaction between depressive symptoms and Alcohol Use Disorder Identification Test (AUDIT, a test that assesses alcohol use disorder) score was significantly and negatively associated with retention in HIV care (OR = 0.14, 95%CI: 0.01-1.11, p ≤ 0.10). The interaction between age and male gender was also negatively associated with retention (OR = 0.95, 95%CI: 0.88-1.01, p ≤ 0.10), and the interaction between male gender and depression was positively associated with retention (OR = 7.17, 95%CI: 0.84-98.49, p ≤ 0.10). In conclusion, multiple races/ethnicities, specifically Non-Hispanic Black, Black-Hispanic, and Other racial/ethnic identification, were associated with increased odds of retention. Multiple interactions, specifically depressive symptoms * alcohol use disorder and male gender * age, were negatively associated with retention. The male gender * depression interaction was positively associated with retention in HIV care.

PLATO software provides analytic framework for investigating complexity beyond genome-wide association studies

Genome-wide, imputed, sequence, and structural data are now available for exceedingly large sample sizes. The needs for data management, handling population structure and related samples, and performing associations have largely been met. However, the infrastructure to support analyses involving complexity beyond genome-wide association studies is not standardized or centralized. We provide the PLatform for the Analysis, Translation, and Organization of large-scale data (PLATO), a software tool equipped to handle multi-omic data for hundreds of thousands of samples to explore complexity using genetic interactions, environment-wide association studies and gene–environment interactions, phenome-wide association studies, as well as copy number and rare variant analyses. Using the data from the Marshfield Personalized Medicine Research Project, a site in the electronic Medical Records and Genomics Network, we apply each feature of PLATO to type 2 diabetes and demonstrate how PLATO can be used to uncover the complex etiology of common traits.

Centralized infrastructure to support analyses involving complexity beyond genome-wide association studies is broadly needed. Here, Ritchie and colleagues develop PLATO, a software tool to process and integrate various methods for this task.

Addictions Neuroclinical Assessment: A Neuroscience-Based Framework for Addictive Disorders

This article proposes a heuristic framework for the Addictions Neuroclinical Assessment that incorporates key functional domains derived from the neurocircuitry of addiction. We review how addictive disorders (ADs) are presently diagnosed and the need for new neuroclinical measures to differentiate patients who meet clinical criteria for addiction to the same agent while differing in etiology, prognosis, and treatment response. The need for a better understanding of the mechanisms provoking and maintaining addiction, as evidenced by the limitations of current treatments and within-diagnosis clinical heterogeneity, is articulated. In addition, recent changes in the nosology of ADs, challenges to current classification systems, and prior attempts to subtype individuals with ADs are described. Complementary initiatives, including the Research Domain Criteria project, that have established frameworks for the neuroscience of psychiatric disorders are discussed. Three domains-executive function, incentive salience, and negative emotionality-tied to different phases in the cycle of addiction form the core functional elements of ADs. Measurement of these domains in epidemiologic, genetic, clinical, and treatment studies will provide the underpinnings for an understanding of cross-population and temporal variation in addictions, shared mechanisms in addictive disorders, impact of changing environmental influences, and gene identification. Finally, we show that it is practical to implement such a deep neuroclinical assessment using a combination of neuroimaging and performance measures. Neuroclinical assessment is key to reconceptualizing the nosology of ADs on the basis of process and etiology, an advance that can lead to improved prevention and treatment.

Unravelling the human genome-phenome relationship using phenome-wide association studies

Advances in genotyping technology have, over the past decade, enabled the focused search for common genetic variation associated with human diseases and traits. With the recently increased availability of detailed phenotypic data from electronic health records and epidemiological studies, the impact of one or more genetic variants on the phenome is starting to be characterized both in clinical and population-based settings using phenome-wide association studies (PheWAS). These studies reveal a number of challenges that will need to be overcome to unlock the full potential of PheWAS for the characterization of the complex human genome-phenome relationship.

Cognitive, emotion control, and motor performance of adolescents in the NCANDA study: Contributions from alcohol consumption, age, sex, ethnicity, and family history of addiction

OBJECTIVE

To investigate development of cognitive and motor functions in healthy adolescents and to explore whether hazardous drinking affects the normal developmental course of those functions.

METHOD

Participants were 831 adolescents recruited across 5 United States sites of the National Consortium on Alcohol and NeuroDevelopment in Adolescence 692 met criteria for no/low alcohol exposure, and 139 exceeded drinking thresholds. Cross-sectional, baseline data were collected with computerized and traditional neuropsychological tests assessing 8 functional domains expressed as composite scores. General additive modeling evaluated factors potentially modulating performance (age, sex, ethnicity, socioeconomic status, and pubertal developmental stage).

RESULTS

Older no/low-drinking participants achieved better scores than younger ones on 5 accuracy composites (general ability, abstraction, attention, emotion, and balance). Speeded responses for attention, motor speed, and general ability were sensitive to age and pubertal development. The exceeds-threshold group (accounting for age, sex, and other demographic factors) performed significantly below the no/low-drinking group on balance accuracy and on general ability, attention, episodic memory, emotion, and motor speed scores and showed evidence for faster speed at the expense of accuracy. Delay Discounting performance was consistent with poor impulse control in the younger no/low drinkers and in exceeds-threshold drinkers regardless of age.

CONCLUSIONS

Higher achievement with older age and pubertal stage in general ability, abstraction, attention, emotion, and balance suggests continued functional development through adolescence, possibly supported by concurrently maturing frontal, limbic, and cerebellar brain systems. Determination of whether low scores by the exceeds-threshold group resulted from drinking or from other preexisting factors requires longitudinal study. (PsycINFO Database Record

From Data to Action: Neuroepidemiology Informs Implementation Research for Global Stroke Prevention and Treatment

As a scientific field of study, neuroepidemiology encompasses more than just the descriptive study of the frequency, distribution, determinants and outcomes of neurologic diseases in populations. It also includes experimental aspects that span the full spectrum of clinical and population science research. As such, neuroepidemiology has a strong potential to inform implementation research for global stroke prevention and treatment. This review begins with an overview of the progress that has been made in descriptive and experimental neuroepidemiology over the past quarter century with emphasis on standards for evidence generation, critical appraisal of that evidence and impact on clinical and public health practice at the national, regional and global levels. Specific advances made in high-income countries as well as in low- and middle-income countries are presented. Gaps in implementation as well as evidence gaps in stroke research, stroke burden, clinical outcomes and disparities between developed and developing countries are then described. The continuing need for high quality neuroepidemiologic data in low- and middle-income countries is highlighted. Additionally, persisting disparities in stroke burden and care by sex, race, ethnicity, income and socioeconomic status are discussed. The crucial role that national stroke registries have played in neuroepidemiologic research is also addressed. Opportunities presented by new directions in comparative effectiveness and implementation research are discussed as avenues for turning neuroepidemiological insights into action to maximize health impact and to guide further biomedical research on neurological diseases.

Phenome-Wide Association Studies: Embracing Complexity for Discovery

The inherent complexity of biological systems can be leveraged for a greater understanding of the impact of genetic architecture on outcomes, traits, and pharmacological response. The genome-wide association study (GWAS) approach has well-developed methods and relatively straight-forward methodologies; however, the bigger picture of the impact of genetic architecture on phenotypic outcome still remains to be elucidated even with an ever-growing number of GWAS performed. Greater consideration of the complexity of biological processes, using more data from the phenome, exposome, and diverse -omic resources, including considering the interplay of pleiotropy and genetic interactions, may provide additional leverage for making the most of the incredible wealth of information available for study. Here, we describe how incorporating greater complexity into analyses through the use of additional phenotypic data and widespread deployment of phenome-wide association studies may provide new insights into genetic factors influencing diseases, traits, and pharmacological response.

The detection and characterization of pleiotropy: discovery, progress, and promise

The impact of a single genetic locus on multiple phenotypes, or pleiotropy, is an important area of research. Biological systems are dynamic complex networks, and these networks exist within and between cells. In humans, the consideration of multiple phenotypes such as physiological traits, clinical outcomes and drug response, in the context of genetic variation, can provide ways of developing a more complete understanding of the complex relationships between genetic architecture and how biological systems function in health and disease. In this article, we describe recent studies exploring the relationships between genetic loci and more than one phenotype. We also cover methodological developments incorporating pleiotropy applied to model organisms as well as humans, and discuss how stepping beyond the analysis of a single phenotype leads to a deeper understanding of complex genetic architecture.

Using PhenX toolkit measures and other tools to assess urban/rural differences in health behaviors: recruitment methods and outcomes

Background

The overall study was designed to examine how vacation behavior affects rural and urban Minnesotans and North Dakotans. The purpose of this substudy was to describe the method for sampling, follow-up and response rate by gender and urban/rural location to help inform future studies in this population.

Methods

Essentia health primary care patients (n = 1344) were sent a 21-page self-administered questionnaire. The questionnaire included questions on demographics, work history, perceived stress, work productivity, depression and mania screeners, tobacco use, dietary information, vacation habits, and technology use. Participants were offered $10 to complete the questionnaire.

Results

The overall response to the three mailings to 1344 adults aged 25–64 was 38.8% for a final sample size of 522 completed surveys. Despite the oversampling of males, the total number of responses from males was lower than for females. The response rates between urban and rural locations were nearly identical for the males (33.3% and 33.0% respectively) but higher for rural females than urban females (47.2% and 42.6% respectively). Seventy-eight percent were currently employed. Sixty-nine percent of the participants reported being married, 5.4% were living with a partner, 14% were divorced widowed or separated and 11% were never married. Forty-seven percent of our population had an associate degree or some college, 29% had a Bachelor’s degree or higher, 17% had their diploma or equivalent and 2% had not completed high school.

Conclusions

The goal of the sampling frame and recruitment strategy for this study was to assemble a cohort of approximately 1000 working adults, represented equally by age, gender and rural location. We ended up with a smaller cohort than desired. The law of diminishing returns was observed, although the third mailing was more effective for men than women.

Electronic supplementary material

The online version of this article (doi:10.1186/1756-0500-7-847) contains supplementary material, which is available to authorized users.

eMERGEing progress in genomics-the first seven years

The electronic MEdical Records & GEnomics (eMERGE) network was established in 2007 by the National Human Genome Research Institute (NHGRI) of the National Institutes of Health (NIH) in part to explore the utility of electronic medical records (EMRs) in genome science. The initial focus was on discovery primarily using the genome-wide association paradigm, but more recently, the network has begun evaluating mechanisms to implement new genomic information coupled to clinical decision support into EMRs. Herein, we describe this evolution including the development of the individual and merged eMERGE genomic datasets, the contribution the network has made toward genomic discovery and human health, and the steps taken toward the next generation genotype-phenotype association studies and clinical implementation.

PhenX RISING: real world implementation and sharing of PhenX measures

Background

The purpose of this manuscript is to describe the PhenX RISING network and the site experiences in the implementation of PhenX measures into ongoing population-based genomic studies.

Methods

Eighty PhenX measures were implemented across the seven PhenX RISING groups, thirty-three of which were used at more than two sites, allowing for cross-site collaboration. Each site used between four and 37 individual measures and five of the sites are validating the PhenX measures through comparison with other study measures. Self-administered and computer-based administration modes are being evaluated at several sites which required changes to the original PhenX Toolkit protocols. A network-wide data use agreement was developed to facilitate data sharing and collaboration.

Results

PhenX Toolkit measures have been collected for more than 17,000 participants across the PhenX RISING network. The process of implementation provided information that was used to improve the PhenX Toolkit. The Toolkit was revised to allow researchers to select self- or interviewer administration when creating the data collection worksheets and ranges of specimens necessary to run biological assays has been added to the Toolkit.

Conclusions

The PhenX RISING network has demonstrated that the PhenX Toolkit measures can be implemented successfully in ongoing genomic studies. The next step will be to conduct gene/environment studies.