Human populations inhabit a broad range of environments. Certainly one of the most challenging of these environments is the high altitude region of the world's highest mountain ranges. It has been of considerable scientific interest to determine if populations long residing at these high altitudes have accommodated the stress of reduced oxygen pressure biologically during their sojourn in these regions. While many previous studies have evaluated the biological variation and adaptation of populations living at high altitude, the question of whether these groups are characterizied by genetic adaptations to the stresses of altitude has proven difficult to resolve. Recent research indicates that among the Tibetan population of the Autonomous Region of China residing in villages above 4,000m, a single major gene may act to enhance oxygen saturation of arterial hemoglobin in carriers. Moreover, preliminary data also suggest that individuals possessing this gene not only exhibit greater oxygen saturation of blood, but are characterized by greater reproductive fitness. This research project is aimed at testing the hypothesis that Tibetan women from high altitude populations who possess at least one copy of the putative high oxygen saturation gene also exhibit higher reproductive rates than those who do not. The project will also test the hypothesis of better adaptive integration of oxygen transport, immune and endocrine system function in Tibetan populations living at different high altitude elevations. This research expands the focus on oxygen transport at high altitude to measure the consequences of genetically influenced variation in physiological response to lowered oxygen pressure in terms of demographic and biological outcomes. It will provide the first detailed profile of the immune, endocrine, and cardiorespiratory systems and their integration from adolescence through old age among people living under hypoxic stress. The proposed research also broadens the study of human genetic adaptation by using formal analytic models for quantitative adaptive traits. The application of statistical genetic analytical techniques analyzes a hypothetically adaptive trait by decomposing its underlying genetic determinants and formally testing its association with fitness and function.
