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The Use of Protein-Protein Interactions for the Analysis of the Associations between PM2.5 and Some Diseases.

ABSTRACT: Nowadays, pollution levels are rapidly increasing all over the world. One of the most important pollutants is PM2.5. It is known that the pollution environment may cause several problems, such as greenhouse effect and acid rain. Among them, the most important problem is that pollutants can induce a number of serious diseases. Some studies have reported that PM2.5 is an important etiologic factor for lung cancer. In this study, we extensively investigate the associations between PM2.5 and 22 disease classes recommended by Goh et al., such as respiratory diseases, cardiovascular diseases, and gastrointestinal diseases. The protein-protein interactions were used to measure the linkage between disease genes and genes that have been reported to be modulated by PM2.5. The results suggest that some diseases, such as diseases related to ear, nose, and throat and gastrointestinal, nutritional, renal, and cardiovascular diseases, are influenced by PM2.5 and some evidences were provided to confirm our results. For example, a total of 18 genes related to cardiovascular diseases are identified to be closely related to PM2.5, and cardiovascular disease relevant gene DSP is significantly related to PM2.5 gene JUP.

SUBMITTER: Zhang Q

PROVIDER: S-EPMC4875974 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background: The link between body weight status and spinal diseases has been suggested by a number of cross-sectional and cohort studies with a limited range of patient populations. No population-representative samples have been used to examine the link between obesity and spinal diseases. The present study is based on a nationally representative sample drawn from the Medical Expenditure Panel Survey. Methods: Using the cross-sectional sample of the 2014 Medical Expenditure Panel Study, we built four weighted logistic regression analyses of the associations between body weight status and the following four spinal diseases: low back pain, spondylosis, other cervical disorders and intervertebral disc disorder (IDD). Each respondent's body weight status was used as the key independent variable with three categories: normal/underweight, overweight, and obese. We controlled for marital status, gender, age, smoking status, household income, health insurance coverage, educational attainment and the use of health services for other major categories of diseases. Results: A total sample of 23,048 respondents was used in our analysis. Overweight and obese respondents, as compared to normal/underweight respondents, were more likely to develop lower back problems (Overweight: logged odds = 0.218, p < 0.01; Obese: logged odds = 0.395, p < 0.001) and IDD (Overweight: logged odds = 0.441, p < 0.05; Obese: logged odds = 0.528, p < 0.001). The associations between bodyweight status and spondylitis were statistically insignificant (Overweight: logged odds = 0.281, p = 0.442; Obese: logged odds = 0.680, p = 0.104). The associations between body weight status and other cervical disorders (Overweight: logged odds = -0.116, p = 0.304; Obese: logged odds = -0.160, p = 0.865) were statistically insignificant. Conclusions: As the first study using a national sample to study bodyweight and spinal diseases, our paper supports the hypothesis that obesity adds to the burden of low back pain and IDD. Longitudinal and interventional studies are needed to understand the specific mechanisms behind these positive associations.

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The Use of Protein-Protein Interactions for the Analysis of the Associations between PM2.5 and Some Diseases.

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