title: A cladistic model of ACE sequence variation with implications for myocardial infarction, Alzheimer disease and obesity.
abstract: Sequence variation in ACE, which encodes angiotensin I converting enzyme, contributes to a large proportion of variability in plasma ACE levels, but the extent to which this impacts upon human disease is unresolved. Most efforts to associate ACE with other heritable traits have involved a single Alu insertion/deletion polymorphism, despite the probable existence of other functional sequence variants with effects that may not be consistently detectable by solely typing the Alu indel. Here, utilizing single nucleotide polymorphisms (SNPs) that differentiate major ACE clades in European populations, we demonstrate a number of significant phenotype associations across more than 4000 Swedish individuals. In a systematic analysis of metabolic phenotypes, effects were detected upon several traits, including fasting plasma glucose levels, insulin levels and measures of obesity (P-values ranging from 0.046 to 8.4 x 10(-6)). Extending cladistic models to the study of myocardial infarction and Alzheimer disease, significant associations were observed with greater effect sizes than those typically obtained in large-scale meta-analyses based on the Alu indel. Population frequencies of ACE genotypes were also found to change with age, congruent with previous data suggesting effects upon longevity. Clade models consistently outperformed those based upon single markers, reinforcing the importance of taking into consideration the possible confounding effects of allelic heterogeneity in this genomic region. Utilizing computational tools, potential functional variants are highlighted that may underlie phenotypic variability, which is discussed along with the broader implications these results may have for studies attempting to link variation in ACE to human disease.
authors.affiliation: Center for Genomics and Bioinformatics, Karolinska Institute, Berzelius väg 35 171 77, Stockholm, Sweden.
authors.forename: Hagit
authors.initials: H
authors.lastname: Katzov
authors.forename: Anna M
authors.initials: AM
authors.lastname: Bennet
authors.forename: Patrick
authors.initials: P
authors.lastname: Kehoe
authors.forename: Björn
authors.initials: B
authors.lastname: Wiman
authors.forename: Margaret
authors.initials: M
authors.lastname: Gatz
authors.forename: Kaj
authors.initials: K
authors.lastname: Blennow
authors.forename: Boris
authors.initials: B
authors.lastname: Lenhard
authors.forename: Nancy L
authors.initials: NL
authors.lastname: Pedersen
authors.forename: Ulf
authors.initials: U
authors.lastname: de Faire
authors.forename: Jonathan A
authors.initials: JA
authors.lastname: Prince
mesh_terms: D000544:Alzheimer Disease / Q000235:genetics*; D001786:Blood Glucose / Q000032:analysis; D016022:Case-Control Studies; D019295:Computational Biology; D005260:Female; D031541:Fluorescence Resonance Energy Transfer; D005819:Genetic Markers; D014644:Genetic Variation; D015894:Genome, Human; D006239:Haplotypes; D006801:Humans; D007328:Insulin / Q000032:analysis; D015810:Linkage Disequilibrium; D008297:Male; D008875:Middle Aged; D008957:Models, Genetic; D009203:Myocardial Infarction / Q000235:genetics*; D009765:Obesity / Q000235:genetics*; D007703:Peptidyl-Dipeptidase A / Q000235:genetics*; D020641:Polymorphism, Single Nucleotide
chemical_list: D001786:Blood Glucose; D005819:Genetic Markers; D007328:Insulin; D007703:Peptidyl-Dipeptidase A