Using clinical information obtained from patients (types of symptoms, severity of symptoms, exercise-related symptoms, day versus night symptoms, prednisone use, hospitalization, ED visit, etc.), determine if there is a relationship between these patient reported symptoms and clinical data (FEV1, FeNO, peak flow, O2 saturation, etc.).
We already know that things like hair color, eye color, height, and weight are strongly heritable. There is tremendous anatomical variability among the population, but we do NOT have a good understanding of genetic predictors of this variability. By integrating cross-sectional imaging data (e.g. CT) with AoU, and integrating advanced computer segmentation algorithms to help define normal anatomical structures, we can ...more »
We can identify people who are at high risk for many diseases. However, not all high-risk people develop the disease. This study would follow people in high-risk groups longitudinally and identify specific genomic, physiological, clinical, and exposure factors that are either predictive or protective of transition to disease. This should focus on a diverse set of people (ethnicity, gender/sex, age, SES, rural/urban, ...more »
This case study focuses on symptoms not identifiable as a "disease" or indication, and based on the risk factors captured in that subset's data, identify what can be done with tailored prevention and primary care prevent the symptoms from becoming syndromes. A participant subset with similar complaints, race/ethn, geographical factors, genetic, and SDH factors might sort out syndromes and treatment that are undiagnosed ...more »
Complex diseases are a result of a complex interplay of genetic, environmental, host and societal factors operating over a prolonged time. Many factors associated with disease onset or progression have been elucidated using a silo-ed approach which fails to adequately assess interplay between factors. Longitudinal measures and more sophisticated analytical methods are needed to support comprehensive (e.g. systems or computational ...more »
Biological, psychological & social domains interact at multiple levels (genes, human & environment microbiomes, stress, behavior, broad SES & environment) outlined by the biopsychosocial ecological model (BPSEM). The BPSEM specifies pathways aligned with the AoU pillars of biology, lifestyle, & environment. Simultaneous examination of the interacting domains and levels of the BPSEM is now computationally possible and ...more »
With all feasible tools (diary, receipts, credit card records, third party validation), record all expenses (real and in-kind) from self and all payers, related to personal health, fitness, and illness on a representative subset of cohort (ethnic, geographic, income, education, gender, age, etc). Correlate with acute, intermediate, and long-time health outcomes, and track for a decade. Keep within the high priority category ...more »
Modifiable risk factors interact with genes to predict rheumatoid arthritis (RA). Antibodies can be detected in pre-RA, up to 10 years before symptoms. Goal: Conduct RCT to reduce RA risk factors and delay/prevent RA onset Methods.Find high risk subjects (+CCP, high polygenetic risk score), monitor for early sx (mHealth), conduct RCT based on motivational interviewing/health coaching vs. basic info intervention to modify ...more »
Currently, section 7.4 (Biospecimens) of the All of Us protocol does not emphasize "repeated collection over time," It may be useful to encourage experimentation with - multiple methods to collect biospecimens (blood, urine) repeatedly over time, including 'old' methods but also new technologies (perhaps wearable) and new methods for monitoring substances in the blood (like glucose can be monitored now). Like Galileo, ...more »
Clinical evidence suggests that cancer survivors, people living with HIV/AIDS, and diabetics may age prematurely from treatment toxicity. The All of Us study could be used to study these observatons over time by comparing aging trajectories and risk factors for individuals with and without systemic therapy use and investigate the mechanisms that cause alterations in the rate or way individuals age.
Combining genome-wide genetic/epigenetic variation and gene/protein expression with clinical, behavioral, imaging, environmental, and molecular data, in the large and diverse All of Us cohort will enhance our understanding of disease risk factors and subtypes, relevant biological processes, and targeted treatments. Methods involved include: genomic data generation, storage and sharing; data integration, visualization, ...more »
We propose to investigate risk of developing cancer in a cohort of 100,000 AoU participants using NCIs Activities Completed over Time in 24-hours (ACT24) recall system (doi.org/10.1249/MSS.0000000000001428), and research grade accelerometers. Cases of incident cancer will be captured via linkage to state cancer registries.
Goals: To determine genetics of response to biologic drugs in RA Methods: Define RA with EHR algorithm, use mHealth app to record RA symptoms (RADAI), current/new meds + adherence Outcome: daily RA disease activity after drug start Data: EHR meds, ESR, CRP; PPI confounders, demographics, smoking, exercise. Limitations of prior studies: small samples, no adherence or confounder info, sparse outcome data Expected outcomes: ...more »
The purpose of this study is to understand reasons for minimal participation of urban community residents in longitudinal research. The study will also explore expectations of urban community residents as a result of participating in longitudinal research. The study will use qualitative focus group approach of urban community residents in the Midwest.
“Why a genetic disease in my child?” Clinician Collins told parents, “She has a spontaneous DNA change.” Scientist Collins knows everything has a cause. Despite expectations, no environment agent is a proven germ cell mutagen, not radiation, A-bombs, nor chemotherapy. Design is sequencing family trios of either 1) a prospective cohort of survivors of mutagenic exposures (like for cancer); or 2) a retrospective group ...more »