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- Haghighi, Mona, et al.
(författare)
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A Comparison of Rule-based Analysis with Regression Methods in Understanding the Risk Factors for Study Withdrawal in a Pediatric Study
- 2016
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Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 6
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Tidskriftsartikel (refereegranskat)abstract
- Regression models are extensively used in many epidemiological studies to understand the linkage between specific outcomes of interest and their risk factors. However, regression models in general examine the average effects of the risk factors and ignore subgroups with different risk profiles. As a result, interventions are often geared towards the average member of the population, without consideration of the special health needs of different subgroups within the population. This paper demonstrates the value of using rule-based analysis methods that can identify subgroups with heterogeneous risk profiles in a population without imposing assumptions on the subgroups or method. The rules define the risk pattern of subsets of individuals by not only considering the interactions between the risk factors but also their ranges. We compared the rule-based analysis results with the results from a logistic regression model in The Environmental Determinants of Diabetes in the Young (TEDDY) study. Both methods detected a similar suite of risk factors, but the rule-based analysis was superior at detecting multiple interactions between the risk factors that characterize the subgroups. A further investigation of the particular characteristics of each subgroup may detect the special health needs of the subgroup and lead to tailored interventions.
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| 2. |
- Söderholm, M, et al.
(författare)
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Exome array analysis of ischaemic stroke : results from a southern Swedish study
- 2016
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Ingår i: European Journal of Neurology. - : Wiley. - 1351-5101 .- 1468-1331. ; 23:12, s. 1722-1728
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND AND PURPOSE: Genome-wide association (GWA) studies have identified a few risk loci for ischaemic stroke, but these variants explain only a small part of the genetic contribution to the disease. Coding variants associated with amino acid substitutions or premature termination of protein synthesis could have a large effect on disease risk. We performed an exome array analysis for ischaemic stroke.METHODS: Patients with ischaemic stroke (n = 2385) and control subjects (n = 6077) from three Swedish studies were genotyped with the Illumina HumanOmniExpressExome BeadChip. Single-variant association analysis and gene-based tests were performed of exome variants with minor allele frequency of < 5%. A separate GWA analysis was also performed, based on 700 000 genotyped common markers and subsequent imputation.RESULTS: No exome variant or gene was significantly associated with all ischaemic stroke after Bonferroni correction (all P > 1.8 × 10(-6) for single-variant and >4.15 × 10(-6) for gene-based analysis). The strongest association in single-variant analysis was found for a missense variant in the DNAH11 gene (rs143362381; P = 5.01 × 10(-6) ). In gene-based tests, the strongest association was for the ZBTB20 gene (P = 7.9 × 10(-5) ). The GWA analysis showed that the sample was homogenous (median genomic inflation factor = 1.006). No genome-wide significant association with overall ischaemic stroke risk was found. However, previously reported associations for the PITX2 and ZFHX3 gene loci with cardioembolic stroke subtype were replicated (P = 7 × 10(-15) and 6 × 10(-3) ).CONCLUSIONS: This exome array analysis did not identify any single variants or genes reaching the pre-defined significance level for association with ischaemic stroke. Further studies on exome variants should be performed in even larger, well-defined and subtyped samples.
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