Is craniofacial morphology and body composition related by common genes: Comparative analysis of two ethnically diverse populations.

OBJECTIVES: The overarching hypothesis of the present paper is that ethnically and/or genetically diverse human populations may exhibit similarity in correlations between various aspects of human phenotypes due to the morphological integration process during the ontogenetic stages. To test this we investigated whether an association between craniofacial (CF) features and body composition (BC) variations is present in humans and the extent to which such possible associations are comparable in different populations. Furthermore, the paper examines the contribution of common genetic (additive) and shared familial environmental factors in assessing the correlation between CF and BC characteristics in humans. MATERIALS AND METHODS: Two pedigree-based samples were collected from two distinct populations, including India (Santhal) and Europe (Chuvash). Canonical correlation analysis was used to compare the association between CF and BC characteristics in the two studied samples. The contribution of genetic and familial environmental factors on the correlation between CF and BC features was analyzed through variance decomposition analysis by implementing the Mendelian Analysis package (MAN). RESULTS: Our study suggests that CF morphology is significantly (p < 0.001) associated with BC variation in both samples. CF characteristics and BC phenotypes revealed a consistent trend in both samples where condensed and broad CF morphology was significantly associated with increased fat accumulation, with slight variations between the Santhal and Chuvash samples. Despite the variations observed between the samples, the heritability estimates were impressively equivalent for traits like total facial height (55.6%Santhal vs.56.1%Chuvash ) and nasal index (42.8%Santhal vs. 43.3%Chuvash ). DISCUSSION: The genetic contribution of CF morphology appeared to be extensive and the contribution of common genetic and shared family environmental correlations between CF and BC measures were suggestively substantial. Accordingly, these correlations were consistently observed across ethnically diverse populations, despite drastic morphological differences between the samples under comparison.

Meta-analysis of genome-wide scans for human adult stature identifies novel Loci and associations with measures of skeletal frame size.

Recent genome-wide (GW) scans have identified several independent loci affecting human stature, but their contribution through the different skeletal components of height is still poorly understood. We carried out a genome-wide scan in 12,611 participants, followed by replication in an additional 7,187 individuals, and identified 17 genomic regions with GW-significant association with height. Of these, two are entirely novel (rs11809207 in CATSPER4, combined P-value = 6.1x10(-8) and rs910316 in TMED10, P-value = 1.4x10(-7)) and two had previously been described with weak statistical support (rs10472828 in NPR3, P-value = 3x10(-7) and rs849141 in JAZF1, P-value = 3.2x10(-11)). One locus (rs1182188 at GNA12) identifies the first height eQTL. We also assessed the contribution of height loci to the upper- (trunk) and lower-body (hip axis and femur) skeletal components of height. We find evidence for several loci associated with trunk length (including rs6570507 in GPR126, P-value = 4x10(-5) and rs6817306 in LCORL, P-value = 4x10(-4)), hip axis length (including rs6830062 at LCORL, P-value = 4.8x10(-4) and rs4911494 at UQCC, P-value = 1.9x10(-4)), and femur length (including rs710841 at PRKG2, P-value = 2.4x10(-5) and rs10946808 at HIST1H1D, P-value = 6.4x10(-6)). Finally, we used conditional analyses to explore a possible differential contribution of the height loci to these different skeletal size measurements. In addition to validating four novel loci controlling adult stature, our study represents the first effort to assess the contribution of genetic loci to three skeletal components of height. Further statistical tests in larger numbers of individuals will be required to verify if the height loci affect height preferentially through these subcomponents of height.