| 1. |
- Li, Jian-Liang, et al.
(författare)
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A genome scan for modifiers of age at onset in Huntington disease : The HD MAPS study.
- 2003
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Ingår i: American Journal of Human Genetics. - : Elsevier BV. - 0002-9297 .- 1537-6605. ; 73:3, s. 682-7
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Tidskriftsartikel (refereegranskat)abstract
- Huntington disease (HD) is caused by the expansion of a CAG repeat within the coding region of a novel gene on 4p16.3. Although the variation in age at onset is partly explained by the size of the expanded repeat, the unexplained variation in age at onset is strongly heritable (h2=0.56), which suggests that other genes modify the age at onset of HD. To identify these modifier loci, we performed a 10-cM density genomewide scan in 629 affected sibling pairs (295 pedigrees and 695 individuals), using ages at onset adjusted for the expanded and normal CAG repeat sizes. Because all those studied were HD affected, estimates of allele sharing identical by descent at and around the HD locus were adjusted by a positionally weighted method to correct for the increased allele sharing at 4p. Suggestive evidence for linkage was found at 4p16 (LOD=1.93), 6p21-23 (LOD=2.29), and 6q24-26 (LOD=2.28), which may be useful for investigation of genes that modify age at onset of HD.
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| 2. |
- Djoussé, Luc, et al.
(författare)
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Evidence for a modifier of onset age in Huntington disease linked to the HD gene in 4p16.
- 2004
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Ingår i: Neurogenetics. - : Springer Science and Business Media LLC. - 1364-6745 .- 1364-6753. ; 5:2, s. 109-14
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Tidskriftsartikel (refereegranskat)abstract
- Huntington disease (HD) is a neurodegenerative disorder caused by the abnormal expansion of CAG repeats in the HD gene on chromosome 4p16.3. A recent genome scan for genetic modifiers of age at onset of motor symptoms (AO) in HD suggests that one modifier may reside in the region close to the HD gene itself. We used data from 535 HD participants of the New England Huntington cohort and the HD MAPS cohort to assess whether AO was influenced by any of the three markers in the 4p16 region: MSX1 (Drosophila homeo box homologue 1, formerly known as homeo box 7, HOX7), Delta2642 (within the HD coding sequence), and BJ56 ( D4S127). Suggestive evidence for an association was seen between MSX1 alleles and AO, after adjustment for normal CAG repeat, expanded repeat, and their product term (model P value 0.079). Of the variance of AO that was not accounted for by HD and normal CAG repeats, 0.8% could be attributed to the MSX1 genotype. Individuals with MSX1 genotype 3/3 tended to have younger AO. No association was found between Delta2642 (P=0.44) and BJ56 (P=0.73) and AO. This study supports previous studies suggesting that there may be a significant genetic modifier for AO in HD in the 4p16 region. Furthermore, the modifier may be present on both HD and normal chromosomes bearing the 3 allele of the MSX1 marker.
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| 3. |
- Jones, Richard W., et al.
(författare)
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Computerised anaesthesia monitoring using fuzzy trend templates
- 2001
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Ingår i: Artificial Intelligence in Medicine. - 0933-3657 .- 1873-2860. ; 21:1-3, s. 247-251
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Tidskriftsartikel (refereegranskat)abstract
- The task of administering anaesthesia requires the clinician to be vigilant for long periods of time to detect the onset of adverse conditions. Large amounts of data must be analysed in real-time and, if a problem is detected, it must be diagnosed as a matter of urgency, this being done while other management protocols are being carried out. For these reasons it would be of benefit if automated decision support could be provided for anaesthesia monitoring, to lighten the cognitive load on the anaesthetist. The Sentinel anaesthesia monitor has been developed with this objective in mind. It uses a fuzzy time-domain pattern matching technique, termed fuzzy trend templates, to detect vaguely specified patterns in multiple physiological data streams. These patterns are representative of symptoms associated with undesirable patient states. The system is capable of detecting trends and states such as 'significant rise' and 'high', and associating vague duration and temporal intervals with individual trends. Fuzzy trend templates have proven to be quite intuitive to specify, given linguistic (anaesthetists') knowledge about the problem domain. Sentinel's implementation of fuzzy trend templates also uses an extension to fuzzy logic based on the theory of evidence, to handle situations where desired information is not available, for example, when sensors are not being used. In off-line testing, Sentinel has achieved sensitivity and specificity of above 90% in the diagnosis of seven common or serious conditions that can arise during anaesthesia
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| 4. |
- Lowe, Andrew, et al.
(författare)
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The graphical presentation of decision support information in an intelligent anaesthesia monitor
- 2001
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Ingår i: Artificial Intelligence in Medicine. - 0933-3657 .- 1873-2860. ; 22:2, s. 173-191
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Tidskriftsartikel (refereegranskat)abstract
- This contribution examines the graphical presentation of decision support information generated by an intelligent monitor, named SENTINEL, developed for use during anaesthesia. Clinicians make diagnoses in real-time during operations by examining clinically significant trends in multiple signals. SENTINEL attempts to mimic this decision process by using a system of fuzzy trend templates. SENTINEL's implementation of fuzzy trend templates is capable of providing the dual fuzzy measures of belief and plausibility, which are derived from the theory of evidence. It is thus capable of generating fairly rich diagnostic decision support information. However, for SENTINEL to be effective, the visual presentation of this information must be intuitive to the anaesthetist, who may not be familiar with the theory of evidence.This paper discusses techniques that are being evaluated to meet the requirements of the SENTINEL anaesthesia monitor. Specifically, the paper presents methods for highlighting clinically significant trends in physiological (or derived) signals by superimposing a coloured band on the signal that reflects fuzzy output from the intelligent monitor. This paper also discusses the intuitive graphical presentation of binary diagnostic fuzzy measures, including their further interpretation and presentation as crisp 'alarm' and 'warning' conditions
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