The human insulin-resistance syndromes, type 2 diabetes, obesity, combined hyperlipidaemia and essential hypertension, are complex disorders whose genetic basis is unknown. The spontaneously hypertensive rat (SHR) is insulin resistant and a model of these human syndromes. Quantitative trait loci (QTLs) for SHR defects in glucose and fatty acid metabolism, hypertriglyceridaemia and hypertension map to a single locus on rat chromosome 4. Here we combine use of cDNA microarrays, congenic mapping and radiation hybrid (RH) mapping to identify a defective SHR gene, Cd36 (also known as Fat, as it encodes fatty acid translocase), at the peak of linkage to these QTLs. SHR Cd36 cDNA contains multiple sequence variants, caused by unequal genomic recombination of a duplicated ancestral gene. The encoded protein product is undetectable in SHR adipocyte plasma membrane. Transgenic mice overexpressing Cd36 have reduced blood lipids. We conclude that Cd36 deficiency underlies insulin resistance, defective fatty acid metabolism and hypertriglyceridaemia in SHR and may be important in the pathogenesis of human insulin-resistance syndromes.

Integration of genome-wide expression profiling with linkage analysis is a new approach to identifying genes underlying complex traits. We applied this approach to the regulation of gene expression in the BXH/HXB panel of rat recombinant inbred strains, one of the largest available rodent recombinant inbred panels and a leading resource for genetic analysis of the highly prevalent metabolic syndrome. In two tissues important to the pathogenesis of the metabolic syndrome, we mapped cis- and trans-regulatory control elements for expression of thousands of genes across the genome. Many of the most highly linked expression quantitative trait loci are regulated in cis, are inherited essentially as monogenic traits and are good candidate genes for previously mapped physiological quantitative trait loci in the rat. By comparative mapping we generated a data set of 73 candidate genes for hypertension that merit testing in human populations. Mining of this publicly available data set is expected to lead to new insights into the genes and regulatory pathways underlying the extensive range of metabolic and cardiovascular disease phenotypes that segregate in these recombinant inbred strains.

To identify renally expressed genes that influence risk for hypertension, we integrated expression quantitative trait locus (QTL) analysis of the kidney with genome-wide correlation analysis of renal expression profiles and blood pressure in recombinant inbred strains derived from the spontaneously hypertensive rat (SHR). This strategy, together with renal transplantation studies in SHR progenitor, transgenic and congenic strains, identified deficient renal expression of Cd36 encoding fatty acid translocase as a genetically determined risk factor for spontaneous hypertension.

Abstract-Recent advances in molecular biology and technology have made it possible to monitor the expression levels of virtually all genes simultaneously. As the tools for gene expression profiling have become more widely available, the number of investigators applying this technology in hypertension research, as in other fields of biomedical research, has grown rapidly. At the same time, numerous articles have been published that discuss the technical aspects of gene profiling and its promise for advancing research on the pathogenesis and treatment of multiple clinical disorders. However, much of the research carried out with gene expression profiling has been of a correlational or descriptive nature, and the true value of this technology is unclear. Despite the initial wave of enthusiasm for gene expression profiling, its actual utility for studying multifactorial disorders like hypertension remains to be established. In this review, we offer a critical perspective on the use of gene expression profiling in hypertension research and discuss some emerging strategies for taking this technology beyond the limits of correlational and descriptive studies.