A genome-wide meta-analysis identifies 22 loci associated with eight hematological parameters in the HaemGen consortium:

The number and volume of cells in the blood affect a wide range of disorders including cancer and cardiovascular, metabolic, infectious and immune conditions. We consider here the genetic variation in eight clinically relevant hematological parameters, including hemoglobin levels, red and white blood cell counts and platelet counts and volume. We describe common variants within 22 genetic loci reproducibly associated with these hematological parameters in 13,943 samples from six European population-based studies, including 6 associated with red blood cell parameters, 15 associated with platelet parameters and 1 associated with total white blood cell count. We further identified a long-range haplotype at 12q24 associated with coronary artery disease and myocardial infarction in 9,479 cases and 10,527 controls. We show that this haplotype demonstrates extensive disease pleiotropy, as it contains known risk loci for type 1 diabetes, hypertension and celiac disease and has been spread by a selective sweep specific to European and geographically nearby populations.

In ScienceDaily:

By comparing human data with genetic data from chimpanzees, the team were able to conclude that the genetic variant was the result of a selection event favouring variants that increase the risk of heart disease, coeliac disease and type 1 diabetes in European populations 3,400 years ago. The authors suggest that the risk factors were positively selected for because they gave carriers an increased protection against infection.

"The study of blood traits is challenging because of the difficulty of teasing apart biological processes underlying the origin of blood cells," explains Dr Christian Gieger, Head of the Genetic Epidemiology research unit at the Helmholtz Zentrum and co-lead of the HaemGen consortium. "Until now, few genome-wide association studies have looked beyond single traits. But, through a systematic analysis of correlated traits we can begin to discover such shared genetic variants, forming the basis for understanding how these processes interact to influence health and disease.

This sort of disease-based pleiotropy is of course interesting because disease really bites. On the other hand, I think other many interesting phenotypes are out there which probably emerged due to pleiotropy. East Asian hair and European eye color are two guesses. Looking for these clusters of traits associated with one genotype might be a nice way to crank-down the probability of an adaptive-story.

Labels: Population genetics