Quantitative trait loci for peripheral blood cell counts: a study in baboons
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Increasingly, baseline peripheral blood cell counts are implicated as risk factors for common complex diseases. While genetic influences on these hematologic parameters are firmly established, the genetic architecture of the blood counts is still poorly understood. In this article we used data from 582 healthy pedigreed baboons and variance components methods to localize quantitative trait loci (QTLs) influencing complete blood count variables. Besides performing genome-wide linkage scans for each trait individually, we conducted bivariate linkage analyses for all pairwise trait combinations to also identify pleiotropic QTLs influencing several blood counts. While significant and suggestive QTLs were localized throughout the genome (LOD range: 1.5–3.5), chromosomal regions associated with the expression of various hematologic parameters stand out. In particular, our results provide significant and consistent evidence for a QTL on the orthologous human chromosome 1p that is shared by several blood counts, mainly erythrocyte parameters. In addition, multiple suggestive evidence of linkage was detected on the orthologous human chromosomes 10 (near the q-terminus) and 19 (centromeric section). Future studies should help identify the genes responsible for these QTL and elucidate their role on baseline variation in hematologic indicators of health and disease.
KeywordsGenetic Correlation Mean Platelet Volume Mean Corpuscular Volume Additive Genetic Effect Inverse Gaussian Normalization
The authors thank D. Winnier and two anonymous reviewers for constructive comments on an earlier version of the manuscript and D. Newman for outstanding technical assistance. This work was supported by grants from the National Institutes of Health (NIH): R01 HL068922 (OSP), R01 HL054141 (MCM), P01 HL028972 (JLV, MCM, JR), P51 RR013086 (JLV, MCM, JR), and R01 RR08781 (JR). This investigation was conducted in facilities constructed with support from Research Facilities Improvement Program Grant Number C06 RR13556 from the National Center for Research Resources, National Institutes of Health.
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