ABSTRACT
BACKGROUND: A "BeadChip" array permits reliable simultaneous DNA typing of single-nucleotide polymorphisms for minor blood groups. A high-throughput DNA analysis was studied as a routine method of phenotype prediction and software was developed to interpret and analyze the large volume of data points. STUDY DESIGN AND METHODS: DNA was extracted from whole blood of donors of known phenotypes and self-identified ethnicity. Analysis of single-nucleotide polymorphisms (SNPs) associated with 24 antigens of 10 blood group systems was performed with BeadChips (BioArray Solutions), and the results were compared to historical serologic typings. Phenotypes were predicted for individual samples, and phenotype prevalence was determined for ethnicities. The BeadChip was expanded to incorporate SNPs that silence the S antigen, validated, and tested with 369 DNA samples. A time-motion analysis was conducted. RESULTS: Results of BeadChip analyses were concordant with prediction of antigen negativity for 4,510 antigens. Eight discordant results were due to silencing of GYPB(S) and 16 were likely errors in recording serological results or data entry. The analyses produced 19,457 antigen-negative typings not serologically defined, identified 21 rare donors (Co(a-b+) [n = 1], Jo(a-) [n = 6], S-s-[n = 12], and K+k-[n = 2]), and determined allele frequencies and antigen prevalence for four ethnicities. The expanded panel detected 30 SS, 235 ss, 100 Ss, and 4 U- samples. The format processes 192 DNA samples (two plates) per 8-hour shift per technician, including automated data analysis and report generation. CONCLUSION: DNA analysis with BeadChip format, combined with computerized data entry and analysis, permits the prediction of minor blood group antigens.
Subject(s)
Blood Donors , Blood Group Antigens/genetics , DNA/genetics , Algorithms , Alleles , DNA/isolation & purification , Erythrocytes , Gene Frequency , Genotype , Haplotypes , Humans , Mutation , Phenotype , Polymorphism, Single Nucleotide , Sequence Analysis, DNA/methodsABSTRACT
INTRODUCTION AND OBJECTIVES: To compare two equations for evaluating coronary risk, the Framingham-Wilson equation and the Framingham equation adjusted for the Spanish population (REGICOR), in a group of dyslipidemic patients in our healthcare area. In addition, the therapeutic implications of using the 2 methods were also evaluated. PATIENTS AND METHOD: The study included 815 dyslipidemic patients, aged 35-74 years, from our healthcare area. Coronary risk was determined using the 2 equations and subjects were categorized as either low-risk (0%-9%), moderate-risk (10%-19%), or high-risk (> or =20%). To compare the application of the 2 equations, we evaluated differences in derived scores, coronary risk category, and the number of patients regarded as potentially treatable with hypolipidemic drugs. RESULTS: The best correlation observed between the 2 methods was for quantitative scores (r=0.983; P<.001). The correlation was poorer when coronary risk categories were compared (r=0.489; P<.001). Overall, the concordance was poor (kappa=0.06), and was only acceptable for low-risk patients (kappa=0.53). The coronary risk estimates derived from the Wilson table were 2.4 times higher than those obtained using REGICOR. The main differences were for moderate and high-risk patients. In addition, the number of patients regarded as potentially treatable with hypolipidemic drugs was five times higher when the Wilson equation was used. CONCLUSIONS: The overestimate of coronary risk obtained using the Framingham-Wilson equation leads to a greater number of patients being regarded as candidates for hypolipidemic treatment. Our data show the importance of using tables adjusted for the Spanish population.
Subject(s)
Cardiovascular Diseases/epidemiology , Cardiovascular Diseases/prevention & control , Hypercholesterolemia/drug therapy , Hypolipidemic Agents/therapeutic use , Adult , Aged , Data Interpretation, Statistical , Female , Humans , Hypercholesterolemia/complications , Male , Middle Aged , Risk Assessment , Risk Factors , Spain/epidemiologyABSTRACT
Introducción y objetivos. Comparar dos ecuaciones de valoración del riesgo coronario (RC), Framingham de Wilson y REGICOR, en una muestra poblacional de sujetos dislipémicos de nuestra área sanitaria. Valorar las posibles repercusiones terapéuticas derivadas de las mediciones obtenidas por ambos métodos. Pacientes y método. La muestra poblacional estaba constituida por 815 pacientes dislipémicos de 35-74 años. Se determinó el RC mediante ambas ecuaciones y se compararon las puntuaciones obtenidas, la clasificación en las categorías de RC a los 10 años y el número de sujetos potencialmente tratables con medicación hipolipemiante en función de los resultados obtenidos con ambas escalas. Resultados. Se observó una óptima correlación entre ambas mediciones al tener en cuenta los valores cuantitativos (r = 0,983; p < 0,001), aunque ésta disminuyó al valorar los resultados por categorías de RC (p = 0,489; p < 0,001). La concordancia fue mala en su conjunto (κ = 0,06) y sólo fue aceptable en el grupo de riesgo bajo (κ = 0,53). La tabla de Wilson proporcionó unos valores de RC global 2,4 veces superiores a los obtenidos con la calibración de REGICOR, y las diferencias se presentaran principalmente en las categorías de RC moderado y alto. El número de candidatos a ser tratados con hipolipemiantes fue 5 veces superior según la ecuación de Wilson que con la de REGICOR. Conclusiones. La sobrevaloración que se obtiene al calcular el RC mediante la función de Framingham implica un mayor porcentaje de pacientes potencialmente tratables con fármacos hipolipemiantes. Este hecho apoya la necesidad de disponer de tablas de RC ajustadas para nuestra población
Introduction and objectives. To compare two equations for evaluating coronary risk, the Framingham-Wilson equation and the Framingham equation adjusted for the Spanish population (REGICOR), in a group of dyslipidemic patients in our healthcare area. In addition, the therapeutic implications of using the 2 methods were also evaluated. Patients and method. The study included 815 dyslipidemic patients, aged 35-74 years, from our healthcare area. Coronary risk was determined using the 2 equations and subjects were categorized as either low-risk (0%- 9%), moderate-risk (10%-19%), or high-risk (≥20%). To compare the application of the 2 equations, we evaluated differences in derived scores, coronary risk category, and the number of patients regarded as potentially treatable with hypolipidemic drugs. Results. The best correlation observed between the 2 methods was for quantitative scores (r=0.983; P<.001). The correlation was poorer when coronary risk categories were compared (r=0.489; P<.001). Overall, the concordance was poor (κ=0.06), and was only acceptable for low-risk patients (κ=0.53). The coronary risk estimates derived from the Wilson table were 2.4 times higher than those obtained using REGICOR. The main differences were for moderate and high-risk patients. In addition, the number of patients regarded as potentially treatable with hypolipidemic drugs was five times higher when the Wilson equation was used. Conclusions. The overestimate of coronary risk obtained using the Framingham-Wilson equation leads to a greater number of patients being regarded as candidates for hypolipidemic treatment. Our data show the importance of using tables adjusted for the Spanish population
