Dense genotyping of candidate gene loci identifies variants associated with high-density lipoprotein cholesterol.

BACKGROUND: Plasma levels of high-density lipoprotein cholesterol (HDL-C) are known to be heritable, but only a fraction of the heritability is explained. We used a high-density genotyping array containing single-nucleotide polymorphisms (SNPs) from HDL-C candidate genes selected on known biology of HDL-C metabolism, mouse genetic studies, and human genetic association studies. SNP selection was based on tagging SNPs and included low-frequency nonsynonymous SNPs. METHODS AND RESULTS: Association analysis in a cohort containing extremes of HDL-C (case-control, n=1733) provided a discovery phase, with replication in 3 additional populations for a total meta-analysis in 7857 individuals. We replicated the majority of loci identified through genome-wide association studies and present on the array (including ABCA1, APOA1/C3/A4/A5, APOB, APOE/C1/C2, CETP, CTCF-PRMT8, FADS1/2/3, GALNT2, LCAT, LILRA3, LIPC, LIPG, LPL, LRP4, SCARB1, TRIB1, ZNF664) and provide evidence that suggests an association in several previously unreported candidate gene loci (including ABCG1, GPR109A/B/81, NFKB1, PON1/2/3/4). There was evidence for multiple, independent association signals in 5 loci, including association with low-frequency nonsynonymous variants. CONCLUSIONS: Genetic loci associated with HDL-C are likely to harbor multiple, independent causative variants, frequently with opposite effects on the HDL-C phenotype. Cohorts comprising subjects at the extremes of the HDL-C distribution may be efficiently used in a case-control discovery of quantitative traits

The EORTC CAT Core - The computer adaptive version of the EORTC QLQ-C30 questionnaire

Background To optimise measurement precision, relevance to patients and flexibility, patient-reported outcome measures (PROMs) should ideally be adapted to the individual patient/study while retaining direct comparability of scores across patients/studies. This is achievable using item banks and computerised adaptive tests (CATs). The European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire Core 30 (QLQ-C30) is one of the most widely used PROMs in cancer research and clinical practice. Here we provide an overview of the research program to develop CAT versions of the QLQ-C30's 14 functional and symptom domains. Methods The EORTC Quality of Life Group's strategy for developing CAT item banks consists of: literature search to identify potential candidate items; formulation of new items compatible with the QLQ-C30 item style; expert evaluations and patient interviews; field-testing and psychometric analyses, including factor analysis, item response theory calibration and simulation of measurement properties. In addition, software for setting up, running and scoring CAT has been developed. Results Across eight rounds of data collections, 9782 patients were recruited from 12 countries for the field-testing. The four phases of development resulted in a total of 260 unique items across the 14 domains. Each item bank consists of 7–34 items. Psychometric evaluations indicated higher measurement precision and increased statistical power of the CAT measures compared to the QLQ-C30 scales. Using CAT, sample size requirements may be reduced by approximately 20–35% on average without loss of power. Conclusions The EORTC CAT Core represents a more precise, powerful and flexible measurement system than the QLQ-C30. It is currently being validated in a large independent, international sample of cancer patients

The EORTC CAT Core�The computer adaptive version of the EORTC QLQ-C30 questionnaire

Background: To optimise measurement precision, relevance to patients and flexibility, patient-reported outcome measures (PROMs) should ideally be adapted to the individual patient/study while retaining direct comparability of scores across patients/studies. This is achievable using item banks and computerised adaptive tests (CATs). The European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire Core 30 (QLQ-C30) is one of the most widely used PROMs in cancer research and clinical practice. Here we provide an overview of the research program to develop CAT versions of the QLQ-C30's 14 functional and symptom domains. Methods: The EORTC Quality of Life Group's strategy for developing CAT item banks consists of: literature search to identify potential candidate items; formulation of new items compatible with the QLQ-C30 item style; expert evaluations and patient interviews; field-testing and psychometric analyses, including factor analysis, item response theory calibration and simulation of measurement properties. In addition, software for setting up, running and scoring CAT has been developed. Results: Across eight rounds of data collections, 9782 patients were recruited from 12 countries for the field-testing. The four phases of development resulted in a total of 260 unique items across the 14 domains. Each item bank consists of 7�34 items. Psychometric evaluations indicated higher measurement precision and increased statistical power of the CAT measures compared to the QLQ-C30 scales. Using CAT, sample size requirements may be reduced by approximately 20�35% on average without loss of power. Conclusions: The EORTC CAT Core represents a more precise, powerful and flexible measurement system than the QLQ-C30. It is currently being validated in a large independent, international sample of cancer patients.</p