The All of Us Research Program: Data quality, utility, and diversity.

The All of Us Research Program seeks to engage at least one million diverse participants to advance precision medicine and improve human health. We describe here the cloud-based Researcher Workbench that uses a data passport model to democratize access to analytical tools and participant information including survey, physical measurement, and electronic health record (EHR) data. We also present validation study findings for several common complex diseases to demonstrate use of this novel platform in 315,000 participants, 78% of whom are from groups historically underrepresented in biomedical research, including 49% self-reporting non-White races. Replication findings include medication usage pattern differences by race in depression and type 2 diabetes, validation of known cancer associations with smoking, and calculation of cardiovascular risk scores by reported race effects. The cloud-based Researcher Workbench represents an important advance in enabling secure access for a broad range of researchers to this large resource and analytical tools.

Leveraging the health information technology infrastructure to advance federal research priorities.

Ensuring that federally funded health research keeps pace with the explosion of health data depends on better information technology (IT), access to high-quality electronic health data, and supportive policies. Because it prominently funds and conducts health research, the U.S. federal government needs health IT to rapidly evolve and has the ability to drive that evolution. The Office of the National Coordinator for Health Information Technology developed the National Health IT Priorities for Research: A Policy and Development Agenda (the Agenda) that identifies health IT priorities for research in consultation with relevant federal agencies. This article describes support for the Agenda from the Food and Drug Administration, the National Institutes of Health, and the Veterans Health Administration. Advancing the Agenda will benefit these agencies and support their missions as well as the entire ecosystem leveraging the health IT infrastructure or using data from health IT systems for research.

Working Together to Address Women's Health in Research and Drug Development: Summary of the 2017 Women's Health Congress Preconference Symposium.

Historically, women have been underrepresented in clinical research, requiring physicians to extrapolate medical recommendations for women from clinical research done in cohorts consisting predominantly of male participants. While government-funded clinical research has achieved gender parity in phase-3 clinical trials across many biomedical disciplines, improvements are still needed in several facets of women's health research, such as the inclusion of women in early-phase clinical trials, the inclusion of pregnant women and women with physical and intellectual disabilities, the consideration of sex as a biological variable in preclinical research, and the analysis and reporting of sex and gender differences across the full biomedical research continuum. The National Institutes of Health (NIH) Office of Research on Women's Health and the Office of Women's Health of the U.S. Food and Drug Administration (FDA) cosponsored a preconference symposium at the 25th Annual Women's Health Congress, held in Arlington, VA in April, 2017, to highlight gains made and remaining needs regarding the representation of women in clinical research, to introduce innovative procedures and technologies, and to outline revised policy for future studies. Six speakers presented information on a range of subjects related to the representation of women in clinical research and federal initiatives to advance precision medicine. Topics included the following: the return on investment from the NIH-funded Women's Health Initiative; progress in including women in clinical trials for FDA-approved drugs and products; the importance of clinical trials in pregnant women; FDA initiatives to report drug safety during pregnancy; the NIH-funded All of Us Research Program; and efforts to enhance FDA transparency and communications, including the introduction of Drug Trials Snapshots. This article summarizes the major points of the presentations and the discussions that followed.

A Survey of U.S Adults' Opinions about Conduct of a Nationwide Precision Medicine Initiative® Cohort Study of Genes and Environment.

OBJECTIVES: A survey of a population-based sample of U.S adults was conducted to measure their attitudes about, and inform the design of the Precision Medicine Initiative's planned national cohort study. METHODS: An online survey was conducted by GfK between May and June of 2015. The influence of different consent models on willingness to share data was examined by randomizing participants to one of eight consent scenarios. RESULTS: Of 4,777 people invited to take the survey, 2,706 responded and 2,601 (54% response rate) provided valid responses. Most respondents (79%) supported the proposed study, and 54% said they would definitely or probably participate if asked. Support for and willingness to participate in the study varied little among demographic groups; younger respondents, LGBT respondents, and those with more years of education were significantly more likely to take part if asked. The most important study incentive that the survey asked about was learning about one's own health information. Willingness to share data and samples under broad, study-by-study, menu and dynamic consent models was similar when a statement about transparency was included in the consent scenarios. Respondents were generally interested in taking part in several governance functions of the cohort study. CONCLUSIONS: A large majority of the U.S. adults who responded to the survey supported a large national cohort study. Levels of support for the study and willingness to participate were both consistent across most demographic groups. The opportunity to learn health information about one's self from the study appears to be a strong motivation to participate.

Noninvasive fetal sex determination using cell-free fetal DNA: a systematic review and meta-analysis.

CONTEXT: Noninvasive prenatal determination of fetal sex using cell-free fetal DNA provides an alternative to invasive techniques for some heritable disorders. In some countries this testing has transitioned to clinical care, despite the absence of a formal assessment of performance. OBJECTIVE: To document overall test performance of noninvasive fetal sex determination using cell-free fetal DNA and to identify variables that affect performance. DATA SOURCES: Systematic review and meta-analysis with search of PubMed (January 1, 1997-April 17, 2011) to identify English-language human studies reporting primary data. References from review articles were also searched. STUDY SELECTION AND DATA EXTRACTION: Abstracts were read independently to identify studies reporting primary data suitable for analysis. Covariates included publication year, sample type, DNA amplification methodology, Y chromosome sequence, and gestational age. Data were independently extracted by 2 reviewers. RESULTS: From 57 selected studies, 80 data sets (representing 3524 male-bearing pregnancies and 3017 female-bearing pregnancies) were analyzed. Overall performance of the test to detect Y chromosome sequences had the following characteristics: sensitivity, 95.4% (95% confidence interval [CI], 94.7%-96.1%) and specificity, 98.6% (95% CI, 98.1%-99.0%); diagnostic odds ratio (OR), 885; positive predictive value, 98.8%; negative predictive value, 94.8%; area under curve (AUC), 0.993 (95% CI, 0.989-0.995), with significant interstudy heterogeneity. DNA methodology and gestational age had the largest effects on test performance. Methodology test characteristics were AUC, 0.988 (95% CI, 0.979-0.993) for polymerase chain reaction (PCR) and AUC, 0.996 (95% CI, 0.993-0.998) for real-time quantitative PCR (RTQ-PCR) (P = .02). Gestational age test characteristics were AUC, 0.989 (95% CI, 0.965-0.998) (<7 weeks); AUC, 0.994 (95% CI, 0.987-0.997) (7-12 weeks); AUC, 0.992 (95% CI, 0.983-0.996) (13-20 weeks); and AUC, 0.998 (95% CI, 0.990-0.999) (>20 weeks) (P = .02 for comparison of diagnostic ORs across age ranges). RTQ-PCR (sensitivity, 96.0%; specificity, 99.0%) outperformed conventional PCR (sensitivity, 94.0%; specificity, 97.3%). Testing after 20 weeks (sensitivity, 99.0%; specificity, 99.6%) outperformed testing prior to 7 weeks (sensitivity, 74.5%; specificity, 99.1%), testing at 7 through 12 weeks (sensitivity, 94.8%; specificity, 98.9%), and 13 through 20 weeks (sensitivity, 95.5%; specificity, 99.1%). CONCLUSIONS: Despite interstudy variability, performance was high using maternal blood. Sensitivity and specificity for detection of Y chromosome sequences was greatest using RTQ-PCR after 20 weeks' gestation. Tests using urine and tests performed before 7 weeks' gestation were unreliable.

Characterization of the ZBTB42 gene in humans and mice.

A 12 kb haplotype upstream of the key signaling protein gene, AKT1, has been associated with insulin resistance and metabolic syndrome (Devaney et al. 2010). The region contains the first exon and promoter sequences of AKT1, but also includes the complete transcript unit for a highly conserved yet uncharacterized zinc finger-containing protein (ZBTB42). One of the component SNPs of the 12 kb haplotype metabolic syndrome haplotype changes a conserved amino acid in the predicted ZBTB42 protein, increasing the potential significance of the ZBTB42 transcript unit for contributing to disease risk. Using RT-PCR of human and mouse cells, we verified that the two exon ZBTB42 was expressed and correctly spliced in human skeletal muscle, and murine C2C12 cells. Production of peptide antibodies showed the expected protein in human (47 kD) and mouse (49 kD) immunoblots, and murine tissue distribution showed strongest expression in muscle and ovary. Immunostaining showed nuclear localization of the ZBTB42 protein in human muscle. Confocal imaging analyses of murine muscle showed ZBTB42 distributed in the nucleoplasm, with particular enrichment in nuclei underlying the neuromuscular junctions. The genetic association data of metabolic syndrome, coupled with the molecular characterization of the ZBTB42 transcript unit and encoded protein presented here, suggests that ZBTB42 may be involved in metabolic syndrome phenotypes.

AKT1 polymorphisms are associated with risk for metabolic syndrome.

Converging lines of evidence suggest that AKT1 is a major mediator of the responses to insulin,insulin-like growth factor 1 (IGF1), and glucose. AKT1 also plays a key role in the regulation of both muscle cell hypertrophy and atrophy. We hypothesized that AKT1 variants may play a role in the endophenotypes that makeup metabolic syndrome. We studied a 12-kb region including the first exon of the AKT1 gene for association with metabolic syndrome-related phenotypes in four study populations [FAMUSS cohort (n = 574; age 23.7 ± 5.7 years), Strong Heart Study (SHS) (n = 2,134; age 55.5 ± 7.9 years), Dynamics of Health, Aging and Body Composition (Health ABC) (n = 3,075; age 73.6 ± 2.9 years), and Studies of a Targeted Risk Reduction Intervention through Defined Exercise (STRRIDE)(n = 175; age 40­65 years)]. We identified a three SNP haplotype that we call H1, which represents the ancestral alleles eles at the three loci and H2, which represents the derived alleles at the three loci. In young adult European Americans (FAMUSS), H1 was associated with higher fasting glucose levels in females. In middle age Native Americans (SHS), H1 carriers showed higher fasting insulin and HOMA in males, and higher BMI in females. Inolder African-American and European American subjects(Health ABC) H1 carriers showed a higher incidence of metabolic syndrome. Homozygotes for the H1 haplotype showed about twice the risk of metabolic syndrome in both males and females (p < 0.001). In middle-aged European Americans with insulin resistance (STRRIDE) studied by intravenous glucose tolerance test (IVGTT), H1 carriers showed increased insulin resistance due to the Sg component (p = 0.021). The 12-kb haplotype is a risk factor for metabolic syndrome and insulin resistance that needs to be explored in further populations.

Functional characterization of a haplotype in the AKT1 gene associated with glucose homeostasis and metabolic syndrome.

A small 12-kb haplotype upstream of the AKT1 gene has been found to be associated with insulin resistance phenotypes. We sought to define the functional consequences of the three component polymorphic loci (rs1130214, rs10141867, rs33925946) on AKT1 and the upstream ZBTB42 gene. 5' RACE analysis of AKT1 transcripts in human skeletal muscle biopsies showed the predominant promoter to be 2.5 kb upstream of exon 2, and distinct from those promoters previously reported in rat. We then studied the effect of each of the three haplotype polymorphisms in transcriptional reporter assays in muscle, bone, and fat cell culture models, and found that each modulated enhancer and repressor activity are in a cell-specific and differentiation-specific manner. Our results in promoter assays are consistent with the human phenotype data; we found an anabolic effect on muscle and bone with increased mRNA expression of AKT1, and catabolic effect on fat with decreased expression. To test the hypothesis that rs10141867 affects transcription levels of the novel zinc finger protein ZBTB42 in vivo, we developed the allele-specific expression assay using Taqman technology to test for allelic differences within heterozygotes. The allele containing the derived polymorphism (haplotype H2) showed a 1.75-fold increase in expression in human skeletal muscle. Our data show a particularly complex effect of the component polymorphisms of a single haplotype on cells and tissues, suggesting that the coordination of different tissue-specific effects may have driven selection for the H2 haplotype. In light of the recent abundance of SNP association studies, our approach can serve as a method for exploring the biological function of polymorphisms that show significant genotype/phenotype associations.