Model of genetic variation in human social networks
- aDepartment of Political Science, University of California, San Diego, CA 92093; and
- bDepartment of Health Care Policy, Harvard Medical School, and Department of Sociology, Harvard University, Cambridge, MA 02138
-
Edited by Colin F. Camerer, California Institute of Technology, Pasadena, CA, and accepted by the Editorial Board November 29, 2008 (received for review July 15, 2008)
Abstract
Social networks exhibit strikingly systematic patterns across a wide range of human contexts. Although genetic variation accounts for a significant portion of the variation in many complex social behaviors, the heritability of egocentric social network attributes is unknown. Here, we show that 3 of these attributes (in-degree, transitivity, and centrality) are heritable. We then develop a “mirror network” method to test extant network models and show that none account for observed genetic variation in human social networks. We propose an alternative “Attract and Introduce” model with two simple forms of heterogeneity that generates significant heritability and other important network features. We show that the model is well suited to real social networks in humans. These results suggest that natural selection may have played a role in the evolution of social networks. They also suggest that modeling intrinsic variation in network attributes may be important for understanding the way genes affect human behaviors and the way these behaviors spread from person to person.
Footnotes
- 1To whom correspondence should be addressed. E-mail: jhfowler{at}ucsd.edu
-
Author contributions: J.H.F. and N.A.C. designed research; J.H.F., C.T.D., and N.A.C. performed research; J.H.F. and C.T.D. analyzed data; and J.H.F., C.T.D., and N.A.C. wrote the paper.
-
The authors declare no conflict of interest.
-
This article is a PNAS Direct Submission. C.F.C is a guest editor invited by the Editorial Board.
-
See Commentary on page 1687.
-
This article contains supporting information online at www.pnas.org/cgi/content/full/0806746106/DCSupplemental.
- © 2009 by The National Academy of Sciences of the USA
