Original Article

International Journal of Obesity (2008) 32, 1799–1806; doi:10.1038/ijo.2008.194; published online 21 October 2008

Latent common genetic components of obesity traits

B O Tayo1, R Harders1, A Luke1, X Zhu2 and R S Cooper1

  1. 1Department of Preventive Medicine and Epidemiology, Loyola University Chicago, Stritch School of Medicine, Maywood, IL, USA
  2. 2Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA

Correspondence: Dr BO Tayo, Department of Preventive Medicine and Epidemiology, Loyola University Medical Center, 2106 South First Avenue, Bldg 105, Maywood, IL 60153, USA. E-mail: btayo@lumc.edu

Received 13 May 2008; Revised 14 September 2008; Accepted 21 September 2008; Published online 21 October 2008.

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Abstract

Background:

 

Obesity is rapidly becoming a global epidemic. Unlike many complex human diseases, obesity is defined not just by a single trait or phenotype, but jointly by measures of anthropometry and metabolic status.

Methods:

 

We applied maximum likelihood factor analysis to identify common latent factors underlying observed covariance in multiple obesity-related measures. Both the genetic components and the mode of inheritance of the common factors were evaluated. A total of 1775 participants from 590 families for whom measures on obesity-related traits were available were included in this study.

Results:

 

The average age of participants was 37 years, 39% of the participants were obese (body mass index greater than or equal to30.0 kg/m2) and 26% were overweight (body mass index 25.0–29.9 kg/m2). Two latent common factors jointly accounting for over 99% of the correlations among obesity-related traits were identified. Complex segregation analysis of the age- and sex-adjusted latent factors provide evidence for a Mendelian mode of inheritance of major genetic effect with heritability estimates of 40.4 and 47.5% for the first and second factors, respectively.

Conclusions:

 

These findings provide a support for multivariate-based approach for investigating pleiotropic effects on obesity-related traits, which can be applied in both genetic linkage and association mapping.

Keywords:

heritability, latent genetic component, maximum likelihood factor analysis, obesity trait, pleiotropic, segregation analysis

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