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Developing a synthetic psychosocial stress measure and harmonizing CVD-risk data: a way forward to GxE meta- and mega-analyses.

Publication ,  Journal Article
Singh, A; Babyak, MA; Brummett, BH; Kraus, WE; Siegler, IC; Hauser, ER; Williams, RB
Published in: BMC Res Notes
July 24, 2018

OBJECTIVES: Among many challenges in cardiovascular disease (CVD) risk prediction are interactions of genes with stress, race, and/or sex and developing robust estimates of these interactions. Improved power with larger sample size contributed by the accumulation of epidemiological data could be helpful, but integration of these datasets is difficult due the absence of standardized phenotypic measures. In this paper, we describe the details of our undertaking to harmonize a dozen datasets and provide a detailed account of a number of decisions made in the process. RESULTS: We harmonized candidate genetic variants and CVD-risk variables related to demography, adiposity, hypertension, lipodystrophy, hypertriglyceridemia, hyperglycemia, depressive symptom, and chronic psychosocial stress from a dozen studies. Using our synthetic stress algorithm, we constructed a synthetic chronic psychosocial stress measure in nine out of twelve studies where a formal self-rated stress measure was not available. The mega-analytic partial correlation between the stress measure and depressive symptoms while controlling for the effect of study variable in the combined dataset was significant (Rho = 0.27, p < 0.0001). This evidence of the validity and the detailed account of our data harmonization approaches demonstrated that it is possible to overcome the inconsistencies in the collection and measurement of human health risk variables.

Duke Scholars

Published In

BMC Res Notes

DOI

EISSN

1756-0500

Publication Date

July 24, 2018

Volume

11

Issue

1

Start / End Page

504

Location

England

Related Subject Headings

  • Stress, Psychological
  • Statistics as Topic
  • Sample Size
  • Hypertension
  • Humans
  • Genetic Variation
  • Demography
  • Bioinformatics
  • 32 Biomedical and clinical sciences
  • 1199 Other Medical and Health Sciences
 

Citation

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Chicago
ICMJE
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Singh, A., Babyak, M. A., Brummett, B. H., Kraus, W. E., Siegler, I. C., Hauser, E. R., & Williams, R. B. (2018). Developing a synthetic psychosocial stress measure and harmonizing CVD-risk data: a way forward to GxE meta- and mega-analyses. BMC Res Notes, 11(1), 504. https://doi.org/10.1186/s13104-018-3595-z
Singh, Abanish, Michael A. Babyak, Beverly H. Brummett, William E. Kraus, Ilene C. Siegler, Elizabeth R. Hauser, and Redford B. Williams. “Developing a synthetic psychosocial stress measure and harmonizing CVD-risk data: a way forward to GxE meta- and mega-analyses.BMC Res Notes 11, no. 1 (July 24, 2018): 504. https://doi.org/10.1186/s13104-018-3595-z.
Singh A, Babyak MA, Brummett BH, Kraus WE, Siegler IC, Hauser ER, et al. Developing a synthetic psychosocial stress measure and harmonizing CVD-risk data: a way forward to GxE meta- and mega-analyses. BMC Res Notes. 2018 Jul 24;11(1):504.
Singh, Abanish, et al. “Developing a synthetic psychosocial stress measure and harmonizing CVD-risk data: a way forward to GxE meta- and mega-analyses.BMC Res Notes, vol. 11, no. 1, July 2018, p. 504. Pubmed, doi:10.1186/s13104-018-3595-z.
Singh A, Babyak MA, Brummett BH, Kraus WE, Siegler IC, Hauser ER, Williams RB. Developing a synthetic psychosocial stress measure and harmonizing CVD-risk data: a way forward to GxE meta- and mega-analyses. BMC Res Notes. 2018 Jul 24;11(1):504.
Journal cover image

Published In

BMC Res Notes

DOI

EISSN

1756-0500

Publication Date

July 24, 2018

Volume

11

Issue

1

Start / End Page

504

Location

England

Related Subject Headings

  • Stress, Psychological
  • Statistics as Topic
  • Sample Size
  • Hypertension
  • Humans
  • Genetic Variation
  • Demography
  • Bioinformatics
  • 32 Biomedical and clinical sciences
  • 1199 Other Medical and Health Sciences