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There has been a growing emphasis on the relationship between inflammatory responses, gut microbiota and the immune system, and their influence on mental health outcomes. Stress can influence the composition of gut microbiota which, in turn, influences the central nervous systems response to future stressors. C‐Reactive Protein (CRP) is a biomarker for inflammation that has been linked to depression, anxiety disorders and PTSD that is released in response to pro‐inflammatory cytokines. The goal of this study was to test a direct association between behavior profiles such as anxiety and depression, the composition of the gut microbiota, basal levels of CRP and cytokines, cortisol and genetic predisposition. Measures of anxiety, depression, PTSD, substance use and overall health were obtained from adults with no recent illness or surgery, or exposure to antibiotics. Biological measures focused on pro‐ and anti‐inflammatory cytokines from plasma, cortisol levels from hair, and gut microbiome; as well as single nucleotide polymorphisms (SNPs) were assayed. Using factor analysis we determined a shared mental health panel including depression, anxiety and PTSD measures that was negatively correlated to related cytokines. Regression modeling was used to related quantitative traits to demographic and genetic factors, revealing significant relationships between inflammatory markers and mental health. Understanding these relationships will help to determine direct future research in assessing causal direction between all of these factors that can promote mental well‐being, and could in the future be used as biomarkers for vulnerability to mental illness, and even help re‐think how we treat mental health disorders. Support or Funding Information The project described was supported by the National Institute Of General Medical Sciences, 1U54GM115458‐01; The Center for Brain and Behavior Research (CBBRe), USD; Basic Biomedical Sciences, USD; and the South Dakota Governor’s Center for Genetics and Behavioral Health.

several sources of real world data available to researchers. METHODS: We compare and contrast the pros and cons of data available from administrative (payment) databases, electronic medical record (EMR) databases, and surveys. RESULTS: Administrative claims databases provide fully-integrated, all-encounter patient data on diagnoses, procedures, and payments. However, data quality varies depending upon whether particular fields are required for provider payment. Data on lab and test values are typically lacking. Prescriptions that are written, but not filled by the patient, are usually not captured. Medical record data overlap, to a certain extent, with administrative data. While information on payments for services may not be included, detailed information on test results and lab values are usually captured in the EMR. Data are included on written prescriptions, but the researcher will not know whether the prescription was filled by the patient. Depending upon the clinical system covered, only some encounters (e.g., ambulatory care in the outpatient setting) may be available. Both administrative and EMR data hold the potential to provide longitudinal patient information that is not subject to recall or social desirability biases that often affect survey data. However, information on satisfaction with care, quality of life, activities of daily living, and many other metrics, may only be captured with survey data. CONCLUSIONS: Several sources of rich, longitudinal patient data are available to provide real world evidence on drug effectiveness and cost. In some cases, data may be combined to overcome limitations of a single source. With care, data may be found that will produce generalizable findings for the population of interest.

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