Key result
Latent HHD traits detect genetic associations in three PPAR genes missed by standard clinical indicators.
Why the study?
Does independent component analysis of latent phenotypes improve the detection of genetic associations in hypertensive heart disease compared to original clinical indicators?
Cohort
Does independent component analysis of latent phenotypes improve the detection of genetic associations in hypertensive heart disease compared to original clinical indicators?
The use of independent component analysis to extract latent phenotypes enhances the detection of genetic associations in hypertensive heart disease that are missed by standard clinical indicators.
Latent HHD traits via ICA may aid genetic discovery; leaves open clinical translation pending replication in independent cohorts.
Hypertension and hypertensive heart disease (HHD) are inter-related phenotypes frequently observed with other comorbidities such as diabetes, obesity, and dyslipidemia, which probably reflect the complex gene-gene and/or gene-environment interactions resulting in HHD. The complexity of HHD led us to examine intermediate phenotypes (e.g., echocardiographically-derived measures) for simpler clues to the genetic underpinnings of the disease. We applied the method of independent component analysis to a prospective study of the metabolic predictors of left ventricular hypertrophy and extracted latent traits of HHD from panels of multi-dimensional anthropomorphic, hemodynamic echocardiographic and metabolic data. Based on the latent trait values, classification of subjects into different risk groups for HHD captured meaningful subtypes of the disease as reflected in the distributions of primary clinical indicators. Furthermore, we detected genetic associations of the latent HHD traits with single nucleotide polymorphisms in three candidate genes in the peroxisome proliferator-activated receptors complex, for which no significant association was found with the original clinical indicators of HHD. Consensus analysis of the results from repeated independent component analysis runs showed satisfactory robustness and estimated about 3-4 separate unseen sources for the observed HHD-related outcomes.
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Gu et al. (2008) conducted a cohort in Hypertensive heart disease. Latent traits of HHD derived via independent component analysis vs. Original clinical indicators of HHD was evaluated on Genetic associations with single nucleotide polymorphisms in three candidate genes in the peroxisome proliferator-activated receptors complex. Latent traits of HHD derived via independent component analysis detected genetic associations with SNPs in three candidate genes in the PPAR complex not found using original clinical indicators.
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