The PhenX Toolkit: get the most from your measures

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.

Addressing gaps on risk and resilience factors for alcohol use outcomes in sexual and gender minority populations

ISSUES

In 2011, the Institute of Medicine released a report that constituted the first comprehensive effort by a federal body to understand the current state of science pertinent to the health needs of sexual and gender minority populations. This mini-review summarises recent empirical, methodological and theoretical advances in alcohol-related research among to lesbian, gay, bisexual and transgender (LGBT) populations and highlights progress towards addressing gaps, with a particular interest in those identified by the Institute of Medicine report.

APPROACH

Articles published since 2011 were identified from PsycINFO and PubMed database searches, using various combinations of keyword identifiers (alcohol, alcohol abuse, substance abuse, LGBT, lesbian, gay, bisexual, transgender). Reference sections of included articles were also examined for additional citations.

KEY FINDINGS

Recent empirical work has contributed to a greater understanding of sub-group differences within this diverse population. Evidence has supported theorised influences that can account for alcohol-related disparities, yet important gaps remain. Studies that examine the role of gender identity and its intersection with sexual identity within transgender and gender non-conforming sub-populations are lacking. Methodological advances in this literature have begun to allow for examinations of how minority-specific and general risk factors of alcohol misuse may contribute to patterns of alcohol involvement over time and within social-relational contexts

CONCLUSIONS

The recommendations made in the current mini-review are meant to facilitate future collaborative efforts, scale development, thoughtful methodological design and analysis and theoretically driven nuanced hypotheses to better understand, and ultimately address, alcohol-related disparities among sexual and gender minority populations. [Talley AE, Gilbert PA, Mitchell J, Goldbach J, Marshall BDL, Kaysen D. Addressing gaps on risk and resilience factors for alcohol use outcomes in sexual and gender minority populations. Drug Alcohol Rev 2016;35:484-493].

Comparison of Puff Volume With Cigarettes per Day in Predicting Nicotine Uptake Among Daily Smokers

The role of inhalation behaviors as predictors of nicotine uptake was examined in the Pennsylvania Adult Smoking Study (2012-2014), a study of 332 adults whose cigarette smoking was measured in a naturalistic environment (e.g., at home) with portable handheld topography devices. Piecewise regression analyses showed that levels of salivary cotinine, trans-3'-hydroxycotinine, and total salivary nicotine metabolites (cotinine + trans-3'-hydroxycotinine) increased linearly up to a level of about 1 pack per day (20 cigarettes per day (CPD)) (P < 0.01). Total daily puff volume (TDPV; in mL) (P < 0.05) and total daily number of puffs (P < 0.05), but not other topographical measures, increased linearly with CPD up to a level of about 1 pack per day. The mean level of cotinine per cigarette did not change above 20 CPD and was 36% lower in heavy smokers (≥20 CPD) than in lighter smokers (<20 CPD) (15.6 ng/mL vs. 24.5 ng/mL, respectively; P < 0.01). Mediation models showed that TDPV accounted for 43%-63% of the association between CPD and nicotine metabolites for smokers of <20 CPD. TDPV was the best predictor of nicotine metabolite levels in light-to-moderate smokers (1-19 CPD). In contrast, neither CPD, total daily number of puffs, nor TDPV predicted nicotine metabolite levels above 20 CPD (up to 40 CPD). Finally, although light smokers are traditionally considered less dependent on nicotine, these findings suggest that they are exposed to more nicotine per cigarette than are heavy smokers due to more frequent, intensive puffing.

Prepubertal children exposed to concentrated disadvantage: An exploratory analysis of inflammation and metabolic dysfunction

OBJECTIVE

It is unclear whether physiologic and metabolic biomarkers are associated with chronic stressors evidenced during early childhood.

METHODS

Cross-sectional data were obtained from a cohort of healthy, prepubertal (Tanner stage < 2) children (n = 96; age: 8.06 [7.8] years; M = 51 [53%]; F = 45 [47%]; African-American = 26 [27%]; Caucasian = 70 [73%]; with obesity = 21 [22%]; without obesity = 75 [78%]) from the MET study. Body mass index z-score (z_BMI), total body fat (BF), visceral adipose tissue (VAT), intrahepatic and intramyocellular lipids, and insulin resistance (HOMA-IR) were measured. Chronic stress was assessed using neighborhood concentrated disadvantage index (CDI) for the U.S. Census tracts in which participants resided. Spearman's rank correlations were used to examine relationships, accounting for sex and race.

RESULTS

CDI was not positively associated with inflammatory and metabolic markers of dysfunction. However, z_BMI (-0.234, P = 0.023), BF (-0.228, P = 0.028, n = 95), and VAT (-0.241, P = 0.042, n = 74) were significantly negatively associated with CDI. When stratifying by race, these relationships remained significant in Caucasian children only.

CONCLUSIONS

These findings suggest chronic stress during early childhood is not associated with inflammatory and metabolic biomarkers, typically observed in adults. Therefore, exposure to stress during this critical developmental period may remain latent and emerge during a later developmental stage.

The Role of Cannabinoids in Neuroanatomic Alterations in Cannabis Users

The past few decades have seen a marked change in the composition of commonly smoked cannabis. These changes primarily involve an increase of the psychoactive compound ∆(9)-tetrahydrocannabinol (THC) and a decrease of the potentially therapeutic compound cannabidiol (CBD). This altered composition of cannabis may be linked to persistent neuroanatomic alterations typically seen in regular cannabis users. In this review, we summarize recent findings from human structural neuroimaging investigations. We examine whether neuroanatomic alterations are 1) consistently observed in samples of regular cannabis users, particularly in cannabinoid receptor-high areas, which are vulnerable to the effects of high circulating levels of THC, and 2) associated either with greater levels of cannabis use (e.g., higher dosage, longer duration, and earlier age of onset) or with distinct cannabinoid compounds (i.e., THC and CBD). Across the 31 studies selected for inclusion in this review, neuroanatomic alterations emerged across regions that are high in cannabinoid receptors (i.e., hippocampus, prefrontal cortex, amygdala, cerebellum). Greater dose and earlier age of onset were associated with these alterations. Preliminary evidence shows that THC exacerbates, whereas CBD protects from, such harmful effects. Methodologic differences in the quantification of levels of cannabis use prevent accurate assessment of cannabis exposure and direct comparison of findings across studies. Consequently, the field lacks large "consortium-style" data sets that can be used to develop reliable neurobiological models of cannabis-related harm, recovery, and protection. To move the field forward, we encourage a coordinated approach and suggest the urgent development of consensus-based guidelines to accurately and comprehensively quantify cannabis use and exposure in human studies.

Proceedings of a Sickle Cell Disease Ontology workshop - Towards the first comprehensive ontology for Sickle Cell Disease

Sickle cell disease (SCD) is a debilitating single gene disorder caused by a single point mutation that results in physical deformation (i.e. sickling) of erythrocytes at reduced oxygen tensions. Up to 75% of SCD in newborns world-wide occurs in sub-Saharan Africa, where neonatal and childhood mortality from sickle cell related complications is high. While SCD research across the globe is tackling the disease on multiple fronts, advances have yet to significantly impact on the health and quality of life of SCD patients, due to lack of coordination of these disparate efforts. Ensuring data across studies is directly comparable through standardization is a necessary step towards realizing this goal. Such a standardization requires the development and implementation of a disease-specific ontology for SCD that is applicable globally. Ontology development is best achieved by bringing together experts in the domain to contribute their knowledge.

The SCD community and H3ABioNet members joined forces at a recent SCD Ontology workshop to develop an ontology covering aspects of SCD under the classes: phenotype, diagnostics, therapeutics, quality of life, disease modifiers and disease stage. The aim of the workshop was for participants to contribute their expertise to development of the structure and contents of the SCD ontology. Here we describe the proceedings of the Sickle Cell Disease Ontology Workshop held in Cape Town South Africa in February 2016 and its outcomes. The objective of the workshop was to bring together experts in SCD from around the world to contribute their expertise to the development of various aspects of the SCD ontology.

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.

Changes in negative urgency, positive urgency, and sensation seeking across adolescence

The development and potential co-development of traits related to impulsivity and sensation seeking across adolescence has garnered substantial attention within the extant literature. Some prior research suggests that facets show distinct patterns of change across adolescence and that intraindividual changes in these traits may be unrelated. However, the extant literature is somewhat hampered by measurement issues and inconsistent findings. Using an accelerated longitudinal design in a sample of adolescents (n = 1018; ages 11-16), changes in negative urgency, positive urgency, and sensation seeking were examined. The three facets showed similar trajectories across time (i.e., increasing during early adolescence before leveling off). Across all facets, there was strong evidence of correlated change, suggesting these traits are, developmentally, strongly related phenomena.

Does drinking refusal self-efficacy mediate the impulsivity-problematic alcohol use relation?

There is consistent evidence that impulsivity-like traits relate to problematic alcohol involvement; however, identifying mechanisms that account for this relation remains an important area of research. Drinking refusal self-efficacy (or a person's ability to resist alcohol; DRSE) has been shown to predict alcohol use among college students and may be a relevant mediator of the impulsivity-alcohol relation. The current study examined the indirect effect of various constructs related to impulsivity (i.e., urgency, sensation seeking, and deficits in conscientiousness) via several facets of DRSE (i.e., social pressure, opportunistic, and emotional relief) on alcohol-related problems among a large sample of college students (N=891). Overall, results indicated that certain DRSE facets were significant mediators of the relation between impulsivity-related constructs and alcohol problems. More specifically, emotional-relief DRSE was a mediator for the respective relations between urgency and deficits in conscientiousness and alcohol problems, whereas social-DRSE was a significant mediator of the respective relations between urgency and sensation seeking with alcohol problems. Results from this study suggest particular types of DRSE are important mediators of the relations between specific impulsivity constructs and alcohol-related problems. These findings support prevention and intervention efforts that seek to enhance drinking refusal self-efficacy skills of college students, particularly those high in certain personality features, in order to reduce alcohol-related problems among this population.

Translation of an Action Learning Collaborative Model Into a Community-Based Intervention to Promote Physical Activity and Healthy Eating

Action Learning Collaboratives (ALCs), whereby teams apply quality improvement (QI) tools and methods, have successfully improved patient care delivery and outcomes. We adapted and tested the ALC model as a community-based obesity prevention intervention focused on physical activity and healthy eating.

METHOD

The intervention used QI tools (e.g., progress monitoring) and team-based activities and was implemented in three communities through nine monthly meetings. To assess process and outcomes, we used a longitudinal repeated-measures and mixed-methods triangulation approach with a quasi-experimental design including objective measures at three time points.

RESULTS

Most of the 97 participants were female (85.4%), White (93.8%), and non-Hispanic/Latino (95.9%). Average age was 52 years; 28.0% had annual household income of $20,000 or less; and mean body mass index was 35. Through mixed-effects models, we found some physical activity outcomes improved. Other outcomes did not significantly change. Although participants favorably viewed the QI tools, components of the QI process such as sharing goals and data on progress in teams and during meetings were limited. Participants' requests for more education or activities around physical activity and healthy eating, rather than progress monitoring and data sharing required for QI activities, challenged ALC model implementation.

CONCLUSIONS

An ALC model for community-based obesity prevention may be more effective when applied to preexisting teams in community-based organizations.

Neurobiological model of the persistence of anorexia nervosa

Anorexia Nervosa (AN) is characterized by the maintenance of an undernourished, or starved, state. Persistent restrictive eating, or the recurrent intake of a diet that is inadequate to sustain a healthy weight, is the central behavior maintaining AN. To understand this disturbance, we need to understand the neural mechanisms that allow or promote the persistent choice of inadequate caloric intake. While a range of neural disturbances have been reported in AN, abnormalities in systems relevant to reward processing and the development of habit systems have been consistently described in both structural and functional neuroimaging studies. Most recently, brain and behavior have been directly examined by investigating the neural underpinnings of restrictive food choice. These recent data suggest that, among individuals with AN, dorsal frontostriatal circuits play a greater role in guiding decisions regarding what to eat than among healthy individuals. This line of research attempts to leverage advances in the field of cognitive neuroscience to further our understanding of persistent maladaptive choices of individuals with AN, in the hope that such advances will help in the development of novel treatments for this potentially fatal disorder.

The Cooperative Health Research in South Tyrol (CHRIS) study: rationale, objectives, and preliminary results

The Cooperative Health Research In South Tyrol (CHRIS) study is a population-based study with a longitudinal lookout to investigate the genetic and molecular basis of age-related common chronic conditions and their interaction with life style and environment in the general population. All adults of the middle and upper Vinschgau/Val Venosta are invited, while 10,000 participants are anticipated by mid-2017. Family participation is encouraged for complete pedigree reconstruction and disease inheritance mapping. After a pilot study on the compliance with a paperless assessment mode, computer-assisted interviews have been implemented to screen for conditions of the cardiovascular, endocrine, metabolic, genitourinary, nervous, behavioral, and cognitive system. Fat intake, cardiac health, and tremor are assessed instrumentally. Nutrient intake, physical activity, and life-course smoking are measured semi-quantitatively. Participants are phenotyped for 73 blood and urine parameters and 60 aliquots per participant are biobanked (cryo-preserved urine, DNA, and whole and fractionated blood). Through liquid-chromatography mass-spectrometry analysis, metabolite profiling of the mitochondrial function is assessed. Samples are genotyped on 1 million variants with the Illumina HumanOmniExpressExome array and the first data release including 4570 fully phenotyped and genotyped samples is now available for analysis. Participants’ follow-up is foreseen 6 years after the first visit. The target population is characterized by long-term social stability and homogeneous environment which should both favor the identification of enriched genetic variants. The CHRIS cohort is a valuable resource to assess the contribution of genomics, metabolomics, and environmental factors to human health and disease. It is awaited that this will result in the identification of novel molecular targets for disease prevention and treatment.

Representation of Drug Use in Biomedical Standards, Clinical Text, and Research Measures

Drug misuse is a prominent cause of morbidity and mortality in the United States. Recent focus on behavioral and social domains in the electronic health record (EHR) has highlighted the need for comprehensive examination of social history information, such as drug use. In this study, representation of drug use was examined in three types of sources: (1) standards from HL7 and openEHR, (2) clinical text from publicly accessible clinical notes and a local EHR, and (3) research measures from the PhenX Toolkit and CDE Browser. In total, 27 elements were identified across the examined sources, revealing a diverse set of values that were found to be associated with drug use type, frequency, method, time frame, and amount. The findings of this study provide insight into the representation of drug use information that may contribute to efforts for standardizing collection and use of these data to support clinical care and research.

Pilot randomised trial of a healthy eating behavioural intervention in uncontrolled asthma

Rigorous research on the benefit of healthy eating patterns for asthma control is lacking.We randomised 90 adults with objectively confirmed uncontrolled asthma and a low-quality diet (Dietary Approaches to Stop Hypertension (DASH) scores <6 out of 9) to a 6-month DASH behavioural intervention (n=46) or usual-care control (n=44). Intention-to-treat analyses used repeated-measures mixed models.Participants were middle-aged, 67% female and multiethnic. Compared with controls, intervention participants improved on DASH scores (mean change (95% CI) 0.6 (0, 1.1) versus -0.3 (-0.8, 0.2); difference 0.8 (0.2, 1.5)) and the primary outcome, Asthma Control Questionnaire scores (-0.2 (-0.5, 0) versus 0 (-0.3, 0.3); difference -0.2 (-0.5, 0.1)) at 6 months. The mean group differences in changes in Mini Asthma Quality of Life Questionnaire overall and subdomain scores consistently favoured the intervention over the control group: overall 0.4 (95% CI 0, 0.8), symptoms 0.5 (0, 0.9), environment 0.4 (-0.1, 1.0), emotions 0.4 (-0.2, 0.9) and activities 0.3 (0, 0.7). These differences were modest, but potentially clinical significant.The DASH behavioural intervention improved diet quality with promising clinical benefits for better asthma control and functional status among adults with uncontrolled asthma. A full-scale efficacy trial is warranted.

Data Collection and Harmonization in HIV Research: The Seek, Test, Treat, and Retain Initiative at the National Institute on Drug Abuse

Large-scale, multisite data sets offer the potential for exploring the public health benefits of biomedical interventions. Data harmonization is an emerging strategy to increase the comparability of research data collected across independent studies, enabling research questions to be addressed beyond the capacity of any individual study. The National Institute on Drug Abuse recently implemented this novel strategy to prospectively collect and harmonize data across 22 independent research studies developing and empirically testing interventions to effectively deliver an HIV continuum of care to diverse drug-abusing populations. We describe this data collection and harmonization effort, collectively known as the Seek, Test, Treat, and Retain Data Collection and Harmonization Initiative, which can serve as a model applicable to other research endeavors.

Enhancing Coordination Among the U.S. Preventive Services Task Force, Agency for Healthcare Research and Quality, and National Institutes of Health

This paper focuses on the relationships among the U.S. Preventive Services Task Force (USPSTF); Agency for Healthcare Research and Quality (AHRQ); and NIH. After a brief description of the Task Force, AHRQ, NIH, and an example of how they interact, we describe the steps that have been taken recently by NIH to enhance their coordination. We also discuss several challenges that remain and consider potential remedies that NIH, AHRQ, and investigators can take to provide the USPSTF with the data it needs to make recommendations, particularly those pertaining to behavioral interventions.

Study design, intervention, and baseline characteristics of a group randomized trial involving a faith-based healthy eating and physical activity intervention (Walk by Faith) to reduce weight and cancer risk among overweight and obese Appalachian adults

BACKGROUND

Increased prevalence of overweight and obesity among Appalachian residents may contribute to increased cancer rates in this region. This manuscript describes the design, components, and participant baseline characteristics of a faith-based study to decrease overweight and obesity among Appalachian residents.

METHODS

A group randomized study design was used to assign 13 churches to an intervention to reduce overweight and obesity (Walk by Faith) and 15 churches to a cancer screening intervention (Ribbons of Faith). Church members with a body mass index (BMI) ?25 were recruited from these churches in Appalachian counties in five states to participate in the study. A standard protocol was used to measure participant characteristics at baseline. The same protocol will be followed to obtain measurements after completion of the active intervention phase (12months) and the sustainability phase (24months). Primary outcome is change in BMI from baseline to 12months. Secondary outcomes include changes in blood pressure, waist-to-hip ratio, and fruit and vegetable consumption, as well as intervention sustainability.

RESULTS

Church members (n=664) from 28 churches enrolled in the study. At baseline 64.3% of the participants were obese (BMI?30), less than half (41.6%) reported regular exercise, and 85.5% reported consuming less than 5 servings of fruits and vegetables per day.

CONCLUSIONS

Church members recruited to participate in a faith-based study across the Appalachian region reported high rates of unhealthy behaviors. We have demonstrated the feasibility of developing and recruiting participants to a faith-based intervention aimed at improving diet and increasing exercise among underserved populations.

Harmonising and linking biomedical and clinical data across disparate data archives to enable integrative cross-biobank research

A wealth of biospecimen samples are stored in modern globally distributed biobanks. Biomedical researchers worldwide need to be able to combine the available resources to improve the power of large-scale studies. A prerequisite for this effort is to be able to search and access phenotypic, clinical and other information about samples that are currently stored at biobanks in an integrated manner. However, privacy issues together with heterogeneous information systems and the lack of agreed-upon vocabularies have made specimen searching across multiple biobanks extremely challenging. We describe three case studies where we have linked samples and sample descriptions in order to facilitate global searching of available samples for research. The use cases include the ENGAGE (European Network for Genetic and Genomic Epidemiology) consortium comprising at least 39 cohorts, the SUMMIT (surrogate markers for micro- and macro-vascular hard endpoints for innovative diabetes tools) consortium and a pilot for data integration between a Swedish clinical health registry and a biobank. We used the Sample avAILability (SAIL) method for data linking: first, created harmonised variables and then annotated and made searchable information on the number of specimens available in individual biobanks for various phenotypic categories. By operating on this categorised availability data we sidestep many obstacles related to privacy that arise when handling real values and show that harmonised and annotated records about data availability across disparate biomedical archives provide a key methodological advance in pre-analysis exchange of information between biobanks, that is, during the project planning phase.

Social resources, health promotion behavior, and quality of life in adults living with HIV

PURPOSE

To describe the associations among three social resource variables (social belonging, social support networks, and social capital) and two health promotion behaviors, HIV medication adherence and physical activity, and quality of life among persons living with HIV (PLHIV).

METHOD

We conducted a cross-sectional analysis in 102 adult PLHIV. Social resource variables and quality of life were assessed using validated and widely-used instruments. Physical activity was assessed using a daily physical activity diary and medication adherence was abstracted from the participant's medical record. Spearman correlations and descriptive statistics were used to analyze associations among variables.

RESULTS

Fifty-four participants (54%) were male and most were African American (84%), single (69%), and living in poverty (82%). Participants had been living with HIV for an average of 13.6 years (+/-7) and most were living with at least one non-AIDS comorbidity (80%). Social belonging was significantly associated with HIV medication adherence (ρ=0.25, p=0.02), overall functioning (ρ=0.48, p<0.01) and life satisfaction quality of life (ρ=0.50, p<0.01). Social capital was also associated with HIV medication adherence (ρ=0.17, p=0.10) and life satisfaction quality of life (ρ=0.29, p<0.01).

CONCLUSIONS

We found that there are distinctions among various, widely-used social resource constructs. By describing these unique associations and distinctions, our study helps identify which social resources should be targeted in the development of interventions to improve health promotion and the quality of life of members of this marginalized population.

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.

Trajectories of psychopathology and risky behaviors associated with childhood abuse and neglect in low-income urban African American girls

The current study examined patterns of psychopathology, drug and alcohol use, and sexual behavior associated with childhood abuse and neglect in a high-risk sample of low-income African American girls seeking mental health treatment. Participants (N=177) were African American girls recruited from mental health clinics serving low-income communities in Chicago, IL and followed over six waves of data collection (T1-T6) reflecting early (mean age 14) to late (mean age 17) adolescence. Child abuse and neglect history was determined from adolescent and caregiver reports. Latent curve modeling examined patterns of internalizing and externalizing psychopathology, drug and alcohol use, sexual experience, and risky sexual behavior reported by girls and associations with reported child abuse and neglect. Overall, these trajectories indicated a decrease in internalizing and externalizing symptoms, stability of drug and alcohol use, and an increase in sexual experience and risky sexual behaviors over time. Child abuse and neglect was associated with increased internalizing symptoms and sexual experience at baseline and with externalizing symptoms and risky sexual behavior both at baseline and the final point. Child abuse and neglect was not significantly associated with alcohol or drug use. This study adds to the literature on the long-term consequences of child abuse and neglect by demonstrating patterns of psychopathology and risky behavior that persist over time in a high-risk group of girls with self or parent reported histories of abuse and neglect. Interventions that address externalizing problems and health risk behaviors may be of particular importance for this population.

Oral Health in a Sample of Pregnant Women from Northern Appalachia (2011-2015)

Background. Chronic poor oral health has a high prevalence in Appalachia, a large region in the eastern USA. The Center for Oral Health Research in Appalachia (COHRA) has been enrolling pregnant women and their babies since 2011 in the COHRA2 study of genetic, microbial, and environmental factors involved in oral health in Northern Appalachia. Methods. The COHRA2 protocol is presented in detail, including inclusion criteria (healthy, adult, pregnant, US Caucasian, English speaking, and nonimmunocompromised women), recruiting (two sites: Pittsburgh, Pennsylvania, and West Virginia, USA), assessments (demographic, medical, dental, psychosocial/behavioral, and oral microbial samples and DNA), timelines (longitudinal from pregnancy to young childhood), quality control, and retention rates. Results. Preliminary oral health and demographic data are presented in 727 pregnant women, half from the greater Pittsburgh region and half from West Virginia. Despite similar tooth brushing and flossing habits, COHRA2 women in West Virginia have significantly worse oral health than the Pittsburgh sample. Women from Pittsburgh are older and more educated and have less unemployment than the West Virginia sample. Conclusions. We observed different prevalence of oral health and demographic variables between pregnant women from West Virginia (primarily rural) and Pittsburgh (primarily urban). These observations suggest site-specific differences within Northern Appalachia that warrant future studies.

The effects of electronic medical record phenotyping details on genetic association studies: HDL-C as a case study

Background

Biorepositories linked to de-identified electronic medical records (EMRs) have the potential to complement traditional epidemiologic studies in genotype-phenotype studies of complex human diseases and traits. A major challenge in meeting this potential is the use of EMR-derived data to extract phenotypes and covariates for genetic association studies. Unlike traditional epidemiologic data, EMR-derived data are collected for clinical care and are therefore highly variable across patients. The variability of clinical data coupled with the challenges associated with searching unstructured clinical notes requires the development of algorithms to extract phenotypes for analysis. Given the number of possible algorithms that could be developed for any one EMR-derived phenotype, we explored here the impact algorithm decision logic has on genetic association study results for a single quantitative trait, high density lipoprotein cholesterol (HDL-C).

Results

We used five different algorithms to extract HDL-C from African American subjects genotyped on the Illumina Metabochip (n = 11,519) as part of Epidemiologic Architecture for Genes Linked to Environment (EAGLE). Tests of association between HDL-C and genetic risk scores for HDL-C associated variants suggest that the genetic effect size does not vary substantially across the five HDL-C definitions.

Conclusions

These data collectively suggest that, at least for this quantitative trait, algorithm decision logic and phenotyping details do not appreciably impact genetic association study test statistics.

Solar exposure and residential geographic history in relation to exfoliation syndrome in the United States and Israel

IMPORTANCE

Residential (geographic) history and extent of solar exposure may be important risk factors for exfoliation syndrome (XFS) but, to our knowledge, detailed lifetime solar exposure has not been previously evaluated in XFS.

OBJECTIVE

To assess the relation between residential history, solar exposure, and XFS.

DESIGN, SETTING, AND PARTICIPANTS

This clinic-based case-control study was conducted in the United States and Israel. It involved XFS cases and control individuals (all ≥ 60-year-old white individuals) enrolled from 2010 to 2012 (United States: 118 cases and 106 control participants; Israel: 67 cases and 72 control participants).

MAIN OUTCOMES AND MEASURES

Weighted lifetime average latitude of residence and average number of hours per week spent outdoors as determined by validated questionnaires.

RESULTS

In multivariable analyses, each degree of weighted lifetime average residential latitude away from the equator was associated with 11% increased odds of XFS (pooled odds ratio [OR], 1.11; 95% CI, 1.05-1.17; P < .001). Furthermore, every hour per week spent outdoors during the summer, averaged over a lifetime, was associated with 4% increased odds of XFS (pooled OR, 1.04; 95% CI, 1.00-1.07; P = .03). For every 1% of average lifetime summer time between 10 am and 4 pm that sunglasses were worn, the odds of XFS decreased by 2% (OR, 0.98; 95% CI, 0.97-0.99; P < .001) in the United States but not in Israel (OR, 1.00; 95% CI, 0.99-1.01; P = .92; P for heterogeneity = .005). In the United States, after controlling for important environmental covariates, history of work over water or snow was associated with increased odds of XFS (OR, 3.86; 95% CI, 1.36-10.9); in Israel, there were too few people with such history for analysis. We did not identify an association between brimmed hat wear and XFS (P > .57).

CONCLUSIONS AND RELEVANCE

Lifetime outdoor activities may contribute to XFS. The association with work over snow or water and the lack of association with brimmed hat wear suggests that ocular exposure to light from reflective surfaces may be an important type of exposure in XFS etiology.

Genetic susceptibility to dental caries differs between the sexes: a family-based study

Many of the factors affecting susceptibility to dental caries are likely influenced by genetics. In fact, genetics accounts for up to 65% of inter-individual variation in dental caries experience. Sex differences in dental caries experience have been widely reported, with females usually exhibiting a higher prevalence and severity of disease across all ages. The cause for this sex bias is currently uncertain, although it may be partly due to the differential effects of genetic factors between the sexes: gene-by-sex interactions. In this family based study (N = 2,663; 740 families; ages 1-93 years), we assessed dental caries via intra-oral examination and generated six indices of caries experience (DMFS, dfs, and indices of both pit-and-fissure surface caries and smooth surface caries in both primary and permanent dentitions). We used likelihood-based methods to model the variance in caries experience conditional on the expected genetic sharing among relatives in our sample. This modeling framework allowed us to test two lines of evidence for gene-by-sex interactions: (1) whether the magnitude of the cumulative effect of genes differs between the sexes, and (2) whether different genes are involved. We observed significant evidence of gene-by-sex interactions for caries experience in both the primary and permanent dentitions. In the primary dentition, the magnitude of the effect of genes was greater in males than females. In the permanent dentition, different genes may play important roles in each of the sexes. Overall, this study provides the first direct evidence that sex differences in dental caries experiences may be explained, in part, by gene-by-sex interactions.

Extending the coverage of phenotypes in SNOMED CT through post-coordination

OBJECTIVES

To extend the coverage of phenotypes in SNOMED CT through post-coordination.

METHODS

We identify frequent modifiers in terms from the Human Phenotype Ontology (HPO), which we associate with templates for post-coordinated expressions in SNOMED CT.

RESULTS

We identified 176 modifiers, created 12 templates, and generated 1,617 post-coordinated expressions.

CONCLUSIONS

Through this novel approach, we can increase the current number of mappings by 50%.

Measures of exposure impact genetic association studies: an example in vitamin K levels and VKORC1

Studies assessing the impact of gene-environment interactions on common human diseases and traits have been relatively few for many reasons. One often acknowledged reason is that it is difficult to accurately measure the environment or exposure. Indeed, most large-scale epidemiologic studies use questionnaires to assess and measure past and current exposure levels. While questionnaires may be cost-effective, the data may or may not accurately represent the exposure compared with more direct measurements (e.g., self-reported current smoking status versus direct measurement for cotinine levels). Much like phenotyping, the choice in how an exposure is measured may impact downstream tests of genetic association and gene-environment interaction studies. As a case study, we performed tests of association between five common VKORC1 SNPs and two different measurements of vitamin K levels, dietary (n=5,725) and serum (n=348), in the Third National Health and Nutrition Examination Studies (NHANES III). We did not replicate previously reported associations between VKORC1 and vitamin K levels using either measure. Furthermore, the suggestive associations and estimated genetic effect sizes identified in this study differed depending on the vitamin K measurement. This case study of VKORC1 and vitamin K levels serves as a cautionary example of the downstream consequences that the type of exposure measurement choices will have on genetic association and possibly gene-environment studies.

Candidate gene-environment interaction research: reflections and recommendations

Studying how genetic predispositions come together with environmental factors to contribute to complex behavioral outcomes has great potential for advancing the understanding of the development of psychopathology. It represents a clear theoretical advance over studying these factors in isolation. However, research at the intersection of multiple fields creates many challenges. We review several reasons why the rapidly expanding candidate gene-environment interaction (cG×E) literature should be considered with a degree of caution. We discuss lessons learned about candidate gene main effects from the evolving genetics literature and how these inform the study of cG×E. We review the importance of the measurement of the gene and environment of interest in cG×E studies. We discuss statistical concerns with modeling cG×E that are frequently overlooked. Furthermore, we review other challenges that have likely contributed to the cG×E literature being difficult to interpret, including low power and publication bias. Many of these issues are similar to other concerns about research integrity (e.g., high false-positive rates) that have received increasing attention in the social sciences. We provide recommendations for rigorous research practices for cG×E studies that we believe will advance its potential to contribute more robustly to the understanding of complex behavioral phenotypes.

Finding our way through phenotypes

Despite a large and multifaceted effort to understand the vast landscape of phenotypic data, their current form inhibits productive data analysis. The lack of a community-wide, consensus-based, human- and machine-interpretable language for describing phenotypes and their genomic and environmental contexts is perhaps the most pressing scientific bottleneck to integration across many key fields in biology, including genomics, systems biology, development, medicine, evolution, ecology, and systematics. Here we survey the current phenomics landscape, including data resources and handling, and the progress that has been made to accurately capture relevant data descriptions for phenotypes. We present an example of the kind of integration across domains that computable phenotypes would enable, and we call upon the broader biology community, publishers, and relevant funding agencies to support efforts to surmount today's data barriers and facilitate analytical reproducibility.

Project INTEGRATE: An integrative study of brief alcohol interventions for college students

This article provides an overview of a study that synthesizes multiple, independently collected alcohol intervention studies for college students into a single, multisite longitudinal data set. This research embraced innovative analytic strategies (i.e., integrative data analysis or meta-analysis using individual participant-level data), with the overall goal of answering research questions that are difficult to address in individual studies such as moderation analysis, while providing a built-in replication for the reported efficacy of brief motivational interventions for college students. Data were pooled across 24 intervention studies, of which 21 included a comparison or control condition and all included one or more treatment conditions. This yielded a sample of 12,630 participants (42% men; 58% first-year or incoming students). The majority of the sample identified as White (74%), with 12% Asian, 7% Hispanic, 2% Black, and 5% other/mixed ethnic groups. Participants were assessed 2 or more times from baseline up to 12 months, with varying assessment schedules across studies. This article describes how we combined individual participant-level data from multiple studies, and discusses the steps taken to develop commensurate measures across studies via harmonization and newly developed Markov chain Monte Carlo (MCMC) algorithms for 2-parameter logistic item response theory models and a generalized partial credit model. This innovative approach has intriguing promises, but significant barriers exist. To lower the barriers, there is a need to increase overlap in measures and timing of follow-up assessments across studies, better define treatment and control groups, and improve transparency and documentation in future single intervention studies.

Genetic relationship between the addiction diagnosis in adults and their childhood measure of addiction liability

Transmissible liability index (TLI), developed employing a high-risk design and item response theory, enables quantification of the latent trait of liability to drug use disorders (DUD) in children. TLI has been shown to have high heritability and predict DUD in young adulthood. This study extends prior research and determines the genetic contribution of DUD liability measured by TLI to adult liability as indexed by DUD diagnosis. The study utilizes data from a twin sample tracked from age 11 to age 25. In addition to confirming TLI's high heritability and predictive validity, it shows that the genetic component of variance in TLI assessed in childhood accounts for over half of the genetic variance in DUD diagnosis and the entire phenotypic relationship between the two liability measures. This validates TLI as an early measure of DUD liability and supports its utility in early-age genetic and other mechanistic studies of DUD.

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.

Implementing common data elements across studies to advance research

Challenges arise in building the knowledge needed for evidence-based practice partially because obtaining clinical research data is expensive and complicated, and many studies have small sample sizes. Combining data from several studies may have the advantage of increasing the impact of the findings or expanding the population to which findings may be generalized. The use of common data elements will allow this combining and, in turn, create big data, which is an important approach that may accelerate knowledge development. This article discusses the philosophy of using common data elements across research studies and illustrates their use by the processes in a developmental center grant funded by the National Institutes of Health. The researchers identified a set of data elements and used them across several pilot studies. Issues that need to be considered in the adoption and implementation of common data elements across pilot studies include theoretical framework, purpose of the common measures, respondent burden, teamwork, managing large data sets, grant writing, and unintended consequences. We describe these challenges and solutions that can be implemented to manage them.

Expert panel workshop consensus statement on the role of the environment in the development of autoimmune disease

Autoimmune diseases include 80 or more complex disorders characterized by self-reactive, pathologic immune responses in which genetic susceptibility is largely insufficient to determine disease onset. In September 2010, the National Institute of Environmental Health Sciences (NIEHS) organized an expert panel workshop to evaluate the role of environmental factors in autoimmune diseases, and the state of the science regarding relevant mechanisms, animal models, and human studies. The objective of the workshop was to analyze the existing data to identify conclusions that could be drawn regarding environmental exposures and autoimmunity and to identify critical knowledge gaps and areas of uncertainty for future study. This consensus document summarizes key findings from published workshop monographs on areas in which “confident” and “likely” assessments were made, with recommendations for further research. Transcribed notes and slides were reviewed to synthesize an overview on exposure assessment and questions addressed by interdisciplinary panels. Critical advances in the field of autoimmune disease research have been made in the past decade. Collaborative translational and interdisciplinary research is needed to elucidate the role of environmental factors in autoimmune diseases. A focus on exposure assessment methodology is needed to improve the effectiveness of human studies, and more experimental studies are needed to focus on causal mechanisms underlying observed associations of environmental factors with autoimmune disease in humans.

Data compatibility in the addiction sciences: an examination of measure commonality

The need for comprehensive analysis to compare and combine data across multiple studies in order to validate and extend results is widely recognized. This paper aims to assess the extent of data compatibility in the substance abuse and addiction (SAA) sciences through an examination of measure commonality, defined as the use of similar measures, across grants funded by the National Institute on Drug Abuse (NIDA) and the National Institute on Alcohol Abuse and Alcoholism (NIAAA). Data were extracted from applications of funded, active grants involving human-subjects research in four scientific areas (epidemiology, prevention, services, and treatment) and six frequently assessed scientific domains. A total of 548 distinct measures were cited across 141 randomly sampled applications. Commonality, as assessed by density (range of 0-1) of shared measurement, was examined. Results showed that commonality was low and varied by domain/area. Commonality was most prominent for (1) diagnostic interviews (structured and semi-structured) for substance use disorders and psychopathology (density of 0.88), followed by (2) scales to assess dimensions of substance use problems and disorders (0.70), (3) scales to assess dimensions of affect and psychopathology (0.69), (4) measures of substance use quantity and frequency (0.62), (5) measures of personality traits (0.40), and (6) assessments of cognitive/neurologic ability (0.22). The areas of prevention (density of 0.41) and treatment (0.42) had greater commonality than epidemiology (0.36) and services (0.32). To address the lack of measure commonality, NIDA and its scientific partners recommend and provide common measures for SAA researchers within the PhenX Toolkit.

Identifying the appropriate comparison group for HIV-infected individuals

PURPOSE OF REVIEW

HIV-infected individuals are living longer as a result of effective treatment. Age-related comorbidities now account for the majority of morbidity and mortality among treated HIV-infected adults. Previous findings regarding the age at, and risk of, these comorbidities have been mixed, sparking debate in the field. Discerning potential differences in the occurrence and burden of age-related comorbidities among treated HIV-infected adults as compared with uninfected adults of the same age requires careful selection of the appropriate uninfected comparison group.

RECENT FINDINGS

The validity of comparisons with HIV-uninfected populations is threatened when differences in demographic, clinical, and lifestyle characteristics between HIV-infected and uninfected adults are not considered. Identifying a pool of HIV-uninfected individuals from existing secondary data resources and employing selection methodologies may be a novel approach to reduce threats to internal validity. Issues related to identifying data sources, understanding inclusion criteria, determining measurement error, and threats to inference are discussed.

SUMMARY

The development of clinical interventions targeting age-related comorbidities will rely on deriving valid inferences from appropriate comparison groups. The use of secondary data resources and selection methodology to create the appropriate uninfected comparison group is an attractive approach in the setting of finite resources, but are not without limitations.

Sharing behavioral data through a grid infrastructure using data standards

OBJECTIVE

In an effort to standardize behavioral measures and their data representation, the present study develops a methodology for incorporating measures found in the National Cancer Institute's (NCI) grid-enabled measures (GEM) portal, a repository for behavioral and social measures, into the cancer data standards registry and repository (caDSR).

METHODS

The methodology consists of four parts for curating GEM measures into the caDSR: (1) develop unified modeling language (UML) models for behavioral measures; (2) create common data elements (CDE) for UML components; (3) bind CDE with concepts from the NCI thesaurus; and (4) register CDE in the caDSR.

RESULTS

UML models have been developed for four GEM measures, which have been registered in the caDSR as CDE. New behavioral concepts related to these measures have been created and incorporated into the NCI thesaurus. Best practices for representing measures using UML models have been utilized in the practice (eg, caDSR). One dataset based on a GEM-curated measure is available for use by other systems and users connected to the grid.

CONCLUSIONS

Behavioral and population science data can be standardized by using and extending current standards. A new branch of CDE for behavioral science was developed for the caDSR. It expands the caDSR domain coverage beyond the clinical and biological areas. In addition, missing terms and concepts specific to the behavioral measures addressed in this paper were added to the NCI thesaurus. A methodology was developed and refined for curation of behavioral and population science data.

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.

A web-portal for interactive data exploration, visualization, and hypothesis testing

Clinical research studies generate data that need to be shared and statistically analyzed by their participating institutions. The distributed nature of research and the different domains involved present major challenges to data sharing, exploration, and visualization. The Data Portal infrastructure was developed to support ongoing research in the areas of neurocognition, imaging, and genetics. Researchers benefit from the integration of data sources across domains, the explicit representation of knowledge from domain experts, and user interfaces providing convenient access to project specific data resources and algorithms. The system provides an interactive approach to statistical analysis, data mining, and hypothesis testing over the lifetime of a study and fulfills a mandate of public sharing by integrating data sharing into a system built for active data exploration. The web-based platform removes barriers for research and supports the ongoing exploration of data.

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.

Psychometric support of the school climate measure in a large, diverse sample of adolescents: a replication and extension

BACKGROUND

The School Climate Measure (SCM) was developed and validated in 2010 in response to a dearth of psychometrically sound school climate instruments. This study sought to further validate the SCM on a large, diverse sample of Arizona public school adolescents (N = 20,953).

METHODS

Four SCM domains (positive student-teacher relationships, academic support, order and discipline, and physical environment) were available for the analysis. Confirmatory factor analysis and structural equation modeling were established to construct validity, and criterion-related validity was assessed via selected Youth Risk Behavior Survey (YRBS) school safety items and self-reported grade (GPA) point average.

RESULTS

Analyses confirmed the 4 SCM school climate domains explained approximately 63% of the variance (factor loading range .45-.92). Structural equation models fit the data well χ(2) = 14,325 (df = 293, p < .001), comparative fit index (CFI) = .951, Tuker-Lewis index (TLI) = .952, root mean square error of approximation (RMSEA) = .05). The goodness-of-fit index was .940. Coefficient alphas ranged from .82 to .93. Analyses of variance with post hoc comparisons suggested the SCM domains related in hypothesized directions with the school safety items and GPA.

CONCLUSIONS

Additional evidence supports the validity and reliability of the SCM. Measures, such as the SCM, can facilitate data-driven decisions and may be incorporated into evidenced-based processes designed to improve student outcomes.

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

Background

The purpose of this paper is to describe the data collection efforts and validation of PhenX measures in the Personalized Medicine Research Project (PMRP) cohort.

Methods

Thirty-six measures were chosen from the PhenX Toolkit within the following domains: demographics; anthropometrics; alcohol, tobacco and other substances; cardiovascular; environmental exposures; cancer; psychiatric; neurology; and physical activity and physical fitness. Eligibility criteria for the current study included: living PMRP subjects with known addresses who consented to future contact and were not currently living in a nursing home, available GWAS data from eMERGE I for subjects where age-related cataract, HDL, dementia and resistant hypertension were the primary phenotypes, thus biasing the sample to the older PMRP participants. The questionnaires were mailed twice. Data from the PhenX measures were compared with information from PMRP questionnaires and data from Marshfield Clinic electronic medical records.

Results

Completed PhenX questionnaires were returned by 2271 subjects for a final response rate of 70%. The mean age reported on the PhenX questionnaire (73.1 years) was greater than the PMRP questionnaire (64.8 years) because the data were collected at different time points. The mean self-reported weight, and subsequently calculated BMI, were less on the PhenX survey than the measured values at the time of enrollment into PMRP (PhenX means 173.5 pounds and BMI 28.2 kg/m² versus PMRP 182.9 pounds and BMI 29.6 kg/m²). There was 95.3% agreement between the two questionnaires about having ever smoked at least 100 cigarettes. 139 (6.2%) of subjects indicated on the PhenX questionnaire that they had been told they had a stroke. Of them, only 15 (10.8%) had no electronic indication of a prior stroke or TIA. All of the age-and gender-specific 95% confidence limits around point estimates for major depressive episodes overlap and show that 31% of women aged 50–64 reported symptoms associated with a major depressive episode.

Conclusions

The approach employed resulted in a high response rate and valuable data for future gene/environment analyses. These results and high response rate highlight the utility of the PhenX Toolkit to collect valid phenotypic data that can be shared across groups to facilitate gene/environment studies.

Environment-wide association study (EWAS) for type 2 diabetes in the Marshfield Personalized Medicine Research Project Biobank

Environment-wide association studies (EWAS) provide a way to uncover the environmental mechanisms involved in complex traits in a high-throughput manner. Genome-wide association studies have led to the discovery of genetic variants associated with many common diseases but do not take into account the environmental component of complex phenotypes. This EWAS assesses the comprehensive association between environmental variables and the outcome of type 2 diabetes (T2D) in the Marshfield Personalized Medicine Research Project Biobank (Marshfield PMRP). We sought replication in two National Health and Nutrition Examination Surveys (NHANES). The Marshfield PMRP currently uses four tools for measuring environmental exposures and outcome traits: 1) the PhenX Toolkit includes standardized exposure and phenotypic measures across several domains, 2) the Diet History Questionnaire (DHQ) is a food frequency questionnaire, 3) the Measurement of a Person's Habitual Physical Activity scores the level of an individual's physical activity, and 4) electronic health records (EHR) employs validated algorithms to establish T2D case-control status. Using PLATO software, 314 environmental variables were tested for association with T2D using logistic regression, adjusting for sex, age, and BMI in over 2,200 European Americans. When available, similar variables were tested with the same methods and adjustment in samples from NHANES III and NHANES 1999-2002. Twelve and 31 associations were identified in the Marshfield samples at p<0.01 and p<0.05, respectively. Seven and 13 measures replicated in at least one of the NHANES at p<0.01 and p<0.05, respectively, with the same direction of effect. The most significant environmental exposures associated with T2D status included decreased alcohol use as well as increased smoking exposure in childhood and adulthood. The results demonstrate the utility of the EWAS method and survey tools for identifying environmental components of complex diseases like type 2 diabetes. These high-throughput and comprehensive investigation methods can easily be applied to investigate the relation between environmental exposures and multiple phenotypes in future analyses.

Standardizing economic analysis in prevention will require substantial effort

It is exceedingly difficult to compare results of economic analyses across studies due to variations in assumptions, methodology, and outcome measures, a fact which surely decreases the impact and usefulness of prevention-related economic research. Therefore, Crowley et al. (Prevention Science, 2013) are precisely correct in their call for increased standardization and have usefully highlighted the issues that must be addressed. However, having made the need clear, the questions become what form the solution should take, and how should it be implemented. The present discussion outlines the rudiments of a comprehensive framework for promoting standardized methodology in the estimation of economic outcomes, as encouraged by Crowley et al. In short, a single, standard, reference case approach should be clearly articulated, and all economic research should be encouraged to apply that standard approach, with results from compliant analyses being reported in a central archive. Properly done, the process would increase the ability of those without specialized training to contribute to the body of economic research pertaining to prevention, and the most difficult tasks of predicting and monetizing distal outcomes would be readily completed through predetermined models. These recommendations might be viewed as somewhat forcible, insomuch as they advocate for prescribing the details of a standard methodology and establishing a means of verifying compliance. However, it is unclear that the best practices proposed by Crowley et al. will be widely adopted in the absence of a strong and determined approach.

No evidence of interaction between known lipid-associated genetic variants and smoking in the multi-ethnic PAGE population

Genome-wide association studies (GWAS) have identified many variants that influence high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and/or triglycerides. However, environmental modifiers, such as smoking, of these known genotype-phenotype associations are just recently emerging in the literature. We have tested for interactions between smoking and 49 GWAS-identified variants in over 41,000 racially/ethnically diverse samples with lipid levels from the Population Architecture Using Genomics and Epidemiology (PAGE) study. Despite their biological plausibility, we were unable to detect significant SNP × smoking interactions.