Dissecting heritability, environmental risk, and air pollution causal effects using > 50 million individuals in MarketScan.

Large national-level electronic health record (EHR) datasets offer new opportunities for disentangling the role of genes and environment through deep phenotype information and approximate pedigree structures. Here we use the approximate geographical locations of patients as a proxy for spatially correlated community-level environmental risk factors. We develop a spatial mixed linear effect (SMILE) model that incorporates both genetics and environmental contribution. We extract EHR and geographical locations from 257,620 nuclear families and compile 1083 disease outcome measurements from the MarketScan dataset. We augment the EHR with publicly available environmental data, including levels of particulate matter 2.5 (PM2.5), nitrogen dioxide (NO2), climate, and sociodemographic data. We refine the estimates of genetic heritability and quantify community-level environmental contributions. We also use wind speed and direction as instrumental variables to assess the causal effects of air pollution. In total, we find PM2.5 or NO2 have statistically significant causal effects on 135 diseases, including respiratory, musculoskeletal, digestive, metabolic, and sleep disorders, where PM2.5 and NO2 tend to affect biologically distinct disease categories. These analyses showcase several robust strategies for jointly modeling genetic and environmental effects on disease risk using large EHR datasets and will benefit upcoming biobank studies in the era of precision medicine.

An appraisal of lung computer tomography in very early anti-inflammatory treatment of two different ovine ARDS phenotypes.

Mortality and morbidity of Acute Respiratory Distress Syndrome (ARDS) are largely unaltered. A possible new approach to treatment of ARDS is offered by the discovery of inflammatory subphenotypes. In an ovine model of ARDS phenotypes, matching key features of the human subphenotypes, we provide an imaging characterization using computer tomography (CT). Nine animals were randomized into (a) OA (oleic acid, hypoinflammatory; n = 5) and (b) OA-LPS (oleic acid and lipopolysaccharides, hyperinflammatory; n = 4). 48 h after ARDS induction and anti-inflammatory treatment, CT scans were performed at high (H) and then low (L) airway pressure. After CT, the animals were euthanized and lung tissue was collected. OA-LPS showed a higher air fraction and OA a higher tissue fraction, resulting in more normally aerated lungs in OA-LPS in contrast to more non-aerated lung in OA. The change in lung and air volume between H and L was more accentuated in OA-LPS, indicating a higher recruitment potential. Strain was higher in OA, indicating a higher level of lung damage, while the amount of lung edema and histological lung injury were largely comparable. Anti-inflammatory treatment might be beneficial in terms of overall ventilated lung portion and recruitment potential, especially in the OA-LPS group.