On a general level, our study also provides a framework for linking serum derived molecular markers not only with clinical endpoints, but also with the more subtle intermediate phenotypes, as derived from medical imaging, of potential pathophysiological relevance.
Our study provides a framework for linking serum derived molecular markers not only with clinical endpoints, but also with the more subtle intermediate phenotypes, as derived from medical imaging, of potential pathophysiological relevance.
The reverse is true for HIV-1-specific CD8+ T cells, which are enriched for a more intermediate memory phenotype.
To create more detailed and accurate models of pathogenesis, it is important to look in more detail at the potential intermediate phenotypes, for example, by measuring concentrations of cellular products and enzymes that underlie the processes of disease.
Given these limiting factors, we will also discuss another hypothesis-driven strategy to uncover genetic risk: the use of quantitative measures (intermediate phenotypes) within more specific neurobiological mechanisms.
Families with intermediate phenotypes are more likely to be heterozygous, exhibiting large variances (for resistance) within each family.
Since most of these DNA sequences are located in non-coding regulatory regions, such alterations would be more likely to result in intermediate phenotypes in hybrids than in purely recessive traits.
Endophenotypes, or intermediate phenotypes, represent heritable phenotypic constructs that are, presumably, more directly affected by genes than clinical symptoms or disease categories (Gottesman and Gould 2003; Szatmari et al. 2007a; Walters and Owen 2007).
Another approach could be the use of intermediate phenotypes that resemble more closely the underlying disease pathogenesis and more directly interact with the genetic risk variance.
In addition, compared to the dichotomous clinical diagnosis, quantitative intermediate phenotypes can capture more of the underlying heritable trait variation, further enhancing statistical power.
