As you know lactase persistence (LP), which confers the ability to digest lactose sugar as an adult, is an evolutionarily recent development. On the order of 1/3 of the human population exhibits LP, due to a variety of genetic mutations which seem to arise in the cultural background of the domestication of cattle. Some have asked about the possible associations between LP & height & weight before. A new paper in Human Molecular Genetics looks at just that, European lactase persistence genotype shows evidence of association with increase in body mass index:
The global prevalence of obesity has increased significantly in recent decades, mainly due to excess calorie intake and increasingly sedentary lifestyle. Here, we test the association between obesity measured by body mass index (BMI) and one of the best-known genetic variants showing strong selective pressure: the functional variant in the cis-regulatory element of the lactase gene. We tested this variant since it is presumed to provide nutritional advantage in specific physical and cultural environments. We genetically defined lactase persistence (LP) in 31 720 individuals from eight European population-based studies and one family study by genotyping or imputing the European LP variant (rs4988235). We performed a meta-analysis by pooling the β-coefficient estimates of the relationship between rs4988235 and BMI from the nine studies and found that the carriers of the allele responsible for LP among Europeans showed higher BMI (P = 7.9 x 10-5). Since this locus has been shown to be prone to population stratification, we paid special attention to reveal any population substructure which might be responsible for the association signal. The best evidence of exclusion of stratification came from the Dutch family sample which is robust for stratification. In this study, we highlight issues in model selection in the genome-wide association studies and problems in imputation of these special genomic regions.
They focused primarily on Finnish cohorts, but also looked as some other populations, in addition to performing a meta-analysis. Here’s a figure which shows the various beta-values combined with the confidence intervals around them by study:
It turns out that in some of their populations LCT explains about the same proportion of the variance in BMI as FTO, an “obesity gene.” The discussion goes into why LCT might have been picked up in earlier studies:
There are several possible explanations as to why the LP association with BMI may have remained undetected in rest of the GWA analyses. First, the functional variant is not included in any currently used SNP arrays and the power has been reduced due to insufficient linkage disequilibrium (LD). The recently published GWASs were genotyped either by Affymetrix 5.0 or Illumina array which has less coverage in this area than the HumanHap 650 array…We found that the strongest LD (r2) with the LCT C/T-13910 and any marker within 500 000 bp in the HapMap CEPH (Utah residents with ancestry from northern and western Europe) sample included in the Illumina HumanHap 650 or Affymetrix 5.0 array was 0.78 (rs309160)…Second, the first four GWASs had used an additive model, which given the dominant inheritance model of LP and based on what we show here is inappropriate, and results in a considerable decrease in power as shown in Table 2. The strength of evidence of association was also reduced in our data set when the incorrect model was used (additive P = 0.001 versus dominant P = 1.5 x 10-5). Third, the imputation accuracy might be compromised in this region as was shown by our Finnish sample. Together, the incomplete tagging or inaccurate imputation combined with the use of an inappropriate genetic model may explain why this association has remained undetected. Furthermore, the association of LP with milk consumption varies between populations, being stronger in settings of intermediate allele frequency than when one allele is rare…One cannot reject cultural influences on milk consumption overriding the generally rather minor discomfort consequent on milk ingestion by non-persistent individuals and lead to the expectation that the association of LP genotype with BMI will be context-specific…The effect size of this variant may be large in Finland where dairy product consumption is very common and there is a correlation with liquid dairy product consumption and the LP variant…Further, the effect size may have been overestimated in the initial Finnish discovery sample.
The mechanism by which LP affects body composition may be related to the more restricted diet the lactase non-persistent individuals may choose or perhaps the negative symptoms such as diarrhoea after using lactose-containing food products play some role. This finding may also reflect the positive selection the LP allele has been subject to in recent history. Our study highlights the fact that the recent GWASs have not exhaustively revealed the common variants affecting BMI. Although explanation at a functional level is a matter for future studies and finding is not significant in the GWAS established genome-wide level of significance, we propose that the European variant behind LP, and perhaps other variants affecting the regulatory region of LCT, contributes to human obesity.
It doesn’t look like there are common variants of large effect size. The best they could find was that LCT explained ~0.2% of the BMI variance, with a 1 kg & 0.3 kg/m2 higher BMI across the two classes. They also observe in the study that height is not predicted in many modern populations once you correct for population stratification (that is, correct for ethnic origin. Though in the case of many very tall populations, and East Asian populations, I assume they are monomorphic in phenotype). I specify modern because I suspect the phenotypic correlations between LP & the genes which control it would have been very different 4,000 years ago in Denmark, when the LP conferring genotypes were probably at much lower frequencies, and nutritional substitutions for raw milk were less abundant.
Citation: Human Molecular Genetics 2010 19(6):1129-1136; doi:10.1093/hmg/ddp561