Evidence for a major role of genetic factors in the determination of body mass index (BMI) comes from studies of related individuals. However, heritability estimates for BMI vary widely between studies and the reasons for this remain unclear. While some variation is natural due to differences between populations and settings, study design factors may also explain some of the heterogeneity. We performed a systematic review that identified eighty-eight independent estimates of BMI heritability from twin studies (total 140,525 twins) and twenty-seven estimates from family studies (42,968 family members). BMI heritability estimates from twin studies ranged from 0.47 to 0.90 (5th/50th/95th centiles: 0.58/0.75/0.87) and were generally higher than those from family studies (range: 0.24-0.81; 5th/50th/95th centiles: 0.25/0.46/0.68). Meta-regression of the results from twin studies showed that BMI heritability estimates were 0.07 (P=0.001) higher in children than in adults; estimates increased with mean age among childhood studies (+0.012 per year, P=0.002), but decreased with mean age in adult studies (-0.002 per year, P=0.002). Heritability estimates derived from AE twin models (which assume no contribution of shared environment) were 0.12 higher than those from ACE models (P<0.001), whilst lower estimates were associated with self-reported versus DNA-based determination of zygosity (-0.04, P=0.02), and with self-reported versus measured BMI (-0.05, P=0.03). Together, the above factors explained 47% of the heterogeneity in estimates of BMI heritability from twin studies. In summary, while some variation in BMI heritability is expected due to population-level differences, study design factors explained nearly half the heterogeneity reported in twin studies. The genetic contribution to BMI appears to vary with age and may have a greater influence during childhood than adult life.

Variability in the Heritability of Body Mass Index: A Systematic Review and Meta-Regression

Quantitative craniometrical traits have been successfully incorporated into population genetic methods to provide insight into human population structure. However, little is known about the degree of genetic and non-genetic influences on the phenotypic expression of functionally based traits. Many studies have assessed the heritability of craniofacial traits, but complex patterns of correlation among traits have been disregarded. This is a pitfall as the human skull is strongly integrated. Here we reconsider the evolutionary potential of craniometric traits by assessing their heritability values as well as their patterns of genetic and phenotypic correlation using a large pedigree-structured skull series from Hallstatt (Austria). The sample includes 355 complete adult skulls that have been analysed using 3D geometric morphometric techniques. Heritability estimates for 58 cranial linear distances were computed using maximum likelihood methods. These distances were assigned to the main functional and developmental regions of the skull. Results showed that the human skull has substantial amounts of genetic variation, and a t-test showed that there are no statistically significant differences among the heritabilities of facial, neurocranial and basal dimensions. However, skull evolvability is limited by complex patterns of genetic correlation. Phenotypic and genetic patterns of correlation are consistent but do not support traditional hypotheses of integration of the human shape, showing that the classification between brachy- and dolicephalic skulls is not grounded on the genetic level. Here we support previous findings in the mouse cranium and provide empirical evidence that covariation between the maximum widths of the main developmental regions of the skull is the dominant factor of integration in the human skull.

/pdf/heritability-of-human-cranial-dimensions-comparing-the-m5edvsn8dd.pdf

Heritability of human cranial dimensions: comparing the evolvability of different cranial regions

This study presents univariate narrow-sense heritability estimates for 33 common craniometric dimensions, calculated using the maximum likelihood variance components method on a skeletal sample of 298 pedigreed individuals from Hallstatt, Austria Quantitative genetic studies that use skeletal cranial measurements as a basis for inferring microevolutionary processes in human populations usually employ heritability estimates to represent the genetic variance of the population The heritabilities used are often problematic: most come from studies of living humans, and/or they were calculated using statistical techniques or assumptions violated by human groups Most bilateral breadth measures in the current study show low heritability estimates, while cranial length and height measures have heritability values ranging between 0102-0729 There appear to be differences between the heritabilities calculated from crania and those from anthropometric studies of living humans, suggesting that the use of the latter in quantitative genetic models of skeletal data may be inappropriate The univariate skeletal heritability estimates seem to group into distinct regions of the cranium, based on their relative values The most salient group of measurements is for the midfacial/orbital region, with a number of measures showing heritabilities less than 030 Several possible reasons behind this pattern are examined Given the fact that heritabilities calculated on one population should not be applied to others, suggestions are made for the use of the data presented

Maximum likelihood estimation of human craniometric heritabilities.

Human populations across the world vary greatly in cranial morphology It is highly debated to what extent this variability has accumulated through neutral processes (genetic drift) or through natural selection driven by climate By taking advantage of recent work showing that geographic distance along landmasses is an excellent proxy for neutral genetic differentiation, we quantify the relative role of drift versus selection in an exceptionally large dataset of human skulls We show that neutral processes have been much more important than climate in shaping the human cranium We further demonstrate that a large proportion of the signal for natural selection comes from populations from extremely cold regions More generally, we show that, if drift is not explicitly accounted for, the effect of natural selection can be greatly overestimated

The relative role of drift and selection in shaping the human skull.

http://www.larspenke.eu/pdfs/Miller_&_Penke_2007_-_Evolution_of_human_intelligence.pdf

The evolution of human intelligence and the coefficient of additive genetic variance in human brain size

6 Abstract In this study, we used anthropometric data from six Andhra caste populations to examine heritability patterns of 23 anthropometric phe- notypes (linear, craniofacial, and soft tissue measures) with special reference to caste differences. We obtained anthropometric data from 342 nuclear fam- ilies from Brahmin, Reddy, Telaga, Nagara, Ag. Kshatriya, and Mala castes of Visakhapatnam, India. These caste groups represent the existing hierarchi- cal stratification of Indian populations. We used a variance components ap- proach to determine the heritability (h 2 ) of these 23 anthropometric pheno- types (height, weight, BMI, etc.). The sample consisted of 1918 individuals ranging in age from 6 to 72 years (mean = 21.5, S.D. = 13.8). The heritabili- ties (h 2 ± S.E.) for all anthropometric traits for the entire sample were signif- icant ( p < 0.0001) and varied from 0.25 ± 0.05 (BMI) to 0.61 ± 0.05 (bizy- gomatic breadth) after accounting for sex, age, and caste effects. Since data on socioeconomic and nutritional covariates were available for a subset of families, we repeated the genetic analyses using this subset, which has yield- ed higher heritabilities ranging from 0.21 ± 0.16 (head breadth) to 0.72 ± 0.18 (nasal breadth). In general, craniofacial measurements exhibited higher h 2 compared to linear measures. Breadth measurements and circumferences yielded more or less similar heritabilities. Age and sex effects were signifi- cant ( p < 0.0001) for most of the traits, while the effects of caste, socioeco- nomic status, and nutritional status were inconsistent across the traits. In con- clusion, anthropometric phenotypes examined in this study are under appreciable additive genetic influences.

https://kuscholarworks.ku.edu/bitstream/handle/1808/16192/Crawford_HB_74(3)325.pdf;sequence=1

Saileela Modem

Papers

Heritability of anthropometric phenotypes in caste populations of Visakhapatnam, India.