Increased serum lipoprotein(a) concentrations and low molecular weight phenotypes of apolipoprotein(a) are associated with symptomatic peripheral arterial disease. 2007

Benjamin Dieplinger, and Arno Lingenhel, and Nadja Baumgartner, and Werner Poelz, and Hans Dieplinger, and Meinhard Haltmayer, and Florian Kronenberg, and Thomas Mueller
Department of Laboratory Medicine, Konventhospital Barmherzige Brueder Linz, Linz, Austria.

BACKGROUND Increased concentrations of lipoprotein(a) [Lp(a)] have been considered a genetically determined risk factor for coronary artery and cerebrovascular disease. Only 2 small and conflicting studies have investigated the possibility of an association of peripheral arterial disease (PAD) with high serum Lp(a) concentrations and low molecular weight (LMW) phenotypes of apolipoprotein(a) [apo(a)]. METHODS We measured serum concentrations of Lp(a) and apo(a) phenotypes in 213 patients with symptomatic PAD and 213 controls matched for sex, age (within 2 years), and presence of diabetes. RESULTS Patients with PAD showed significantly higher median serum concentrations of Lp(a) (76 vs 47 mg/L; P = 0.003) and a higher frequency of LMW apo(a) phenotypes (41% vs 26%; P = 0.002) than controls. After adjustment for several potential confounders, increased Lp(a) concentrations (>195 mg/L, i.e., 75th percentile of the entire study sample) and LMW apo(a) phenotypes were significant predictors of PAD, with odds ratios of 3.73 (95% CI 2.08-6.67; P <0.001) and 2.21 (95% CI 1.33-3.67; P = 0.002), respectively. CONCLUSIONS In this study sample, both increased serum concentrations of Lp(a) and the presence of LMW apo(a) phenotypes were associated with the presence of symptomatic PAD independent of traditional and nontraditional cardiovascular risk factors. Because PAD is considered an indicator of systemic atherosclerotic disease, our results suggest a possible role of Lp(a) as a genetically determined marker for systemic atherosclerosis.

UI MeSH Term Description Entries
D008297 Male Males
D008875 Middle Aged An adult aged 45 - 64 years. Middle Age
D008970 Molecular Weight The sum of the weight of all the atoms in a molecule. Molecular Weights,Weight, Molecular,Weights, Molecular
D010641 Phenotype The outward appearance of the individual. It is the product of interactions between genes, and between the GENOTYPE and the environment. Phenotypes
D005260 Female Females
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000368 Aged A person 65 years of age or older. For a person older than 79 years, AGED, 80 AND OVER is available. Elderly
D015415 Biomarkers Measurable and quantifiable biological parameters (e.g., specific enzyme concentration, specific hormone concentration, specific gene phenotype distribution in a population, presence of biological substances) which serve as indices for health- and physiology-related assessments, such as disease risk, psychiatric disorders, ENVIRONMENTAL EXPOSURE and its effects, disease diagnosis; METABOLIC PROCESSES; SUBSTANCE ABUSE; PREGNANCY; cell line development; EPIDEMIOLOGIC STUDIES; etc. Biochemical Markers,Biological Markers,Biomarker,Clinical Markers,Immunologic Markers,Laboratory Markers,Markers, Biochemical,Markers, Biological,Markers, Clinical,Markers, Immunologic,Markers, Laboratory,Markers, Serum,Markers, Surrogate,Markers, Viral,Serum Markers,Surrogate Markers,Viral Markers,Biochemical Marker,Biologic Marker,Biologic Markers,Clinical Marker,Immune Marker,Immune Markers,Immunologic Marker,Laboratory Marker,Marker, Biochemical,Marker, Biological,Marker, Clinical,Marker, Immunologic,Marker, Laboratory,Marker, Serum,Marker, Surrogate,Serum Marker,Surrogate End Point,Surrogate End Points,Surrogate Endpoint,Surrogate Endpoints,Surrogate Marker,Viral Marker,Biological Marker,End Point, Surrogate,End Points, Surrogate,Endpoint, Surrogate,Endpoints, Surrogate,Marker, Biologic,Marker, Immune,Marker, Viral,Markers, Biologic,Markers, Immune
D016015 Logistic Models Statistical models which describe the relationship between a qualitative dependent variable (that is, one which can take only certain discrete values, such as the presence or absence of a disease) and an independent variable. A common application is in epidemiology for estimating an individual's risk (probability of a disease) as a function of a given risk factor. Logistic Regression,Logit Models,Models, Logistic,Logistic Model,Logistic Regressions,Logit Model,Model, Logistic,Model, Logit,Models, Logit,Regression, Logistic,Regressions, Logistic
D016022 Case-Control Studies Comparisons that start with the identification of persons with the disease or outcome of interest and a control (comparison, referent) group without the disease or outcome of interest. The relationship of an attribute is examined by comparing both groups with regard to the frequency or levels of outcome over time. Case-Base Studies,Case-Comparison Studies,Case-Referent Studies,Matched Case-Control Studies,Nested Case-Control Studies,Case Control Studies,Case-Compeer Studies,Case-Referrent Studies,Case Base Studies,Case Comparison Studies,Case Control Study,Case Referent Studies,Case Referrent Studies,Case-Comparison Study,Case-Control Studies, Matched,Case-Control Studies, Nested,Case-Control Study,Case-Control Study, Matched,Case-Control Study, Nested,Case-Referent Study,Case-Referrent Study,Matched Case Control Studies,Matched Case-Control Study,Nested Case Control Studies,Nested Case-Control Study,Studies, Case Control,Studies, Case-Base,Studies, Case-Comparison,Studies, Case-Compeer,Studies, Case-Control,Studies, Case-Referent,Studies, Case-Referrent,Studies, Matched Case-Control,Studies, Nested Case-Control,Study, Case Control,Study, Case-Comparison,Study, Case-Control,Study, Case-Referent,Study, Case-Referrent,Study, Matched Case-Control,Study, Nested Case-Control

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