Biomedical subjects

Jonathan Taylor

Publications and source records attributed to Jonathan Taylor.

5 recordsLinked to original sources

PubMed2003

Lack of detectable human immunodeficiency virus type 1 superinfection during 1072 person-years of observation.

We examined consecutive protease (PR) and reverse transcriptase (RT) sequences from human immunodeficiency virus (HIV) type 1-infected individuals, to distinguish changes resulting from sequence evolution due to possible superinfection. Between July 1997 and December 2001, >/=2 PR and RT samples from 718 persons were sequenced at Stanford University Hospital. Thirty-seven persons had highly divergent sequence pairs characterized by a nucleotide distance of >4.5% in PR or >3.0% in RT. In 16 of 37 sequence pairs, divergence resulted from the loss of mutations during a treatment interruption or from the gain of mutations with reinstitution of treatment. tat and/or gag sequencing of HIV-1 from cryopreserved plasma samples could be performed on 15 of the 21 divergent isolate pairs from persons without a treatment interruption. The sequences of these genes, unaffected by selective drug pressure, were monophyletic. Although HIV-1 PR and RT genes from treated persons may become highly divergent, these changes usually are the result of sequence evolution, rather than superinfection.

California↗

PubMed2003

Extended spectrum of HIV-1 reverse transcriptase mutations in patients receiving multiple nucleoside analog inhibitors.

OBJECTIVE: To characterize reverse transcriptase (RT) mutations by their association with extent of nucleoside RT inhibitor (NRTI) therapy. To identify mutational clusters in RT sequences from persons receiving multiple NRTI. DESIGN: A total of 1210 RT sequences from persons with known antiretroviral therapy were analyzed: 641 new sequences were performed at Stanford University Hospital; 569 were previously published. METHODS: Chi-square tests and logistic regression were done to identify associations between mutations and NRTI therapy. Correlation studies were done to identify mutational clusters. The Benjamini-Hochberg procedure was used to correct for multiple comparisons. RESULTS: Mutations at 26 positions were significantly associated with NRTI including 17 known resistance mutations (positions 41, 44, 62, 65, 67, 69, 70, 74, 75, 77, 116, 118, 151, 184, 210, 215, 219) and nine previously unreported mutations (positions 20, 39, 43, 203, 208, 218, 221, 223, 228). The nine new mutations correlated linearly with number of NRTI; 777 out of 817 (95%) instances occurred with known drug resistance mutations. Positions 203, 208, 218, 221, 223, and 228 were conserved in untreated persons; positions 20, 39, and 43 were polymorphic. Most NRTI-associated mutations clustered into three groups: (i) 62, 65, 75, 77, 115, 116, 151; (ii) 41, 43, 44, 118, 208, 210, 215, 223; (iii) 67, 69, 70, 218, 219, 228. CONCLUSIONS: Mutations at nine previously unreported positions are associated with NRTI therapy. These mutations are probably accessory because they occur almost exclusively with known drug resistance mutations. Most NRTI mutations group into one of three clusters, although several (e.g., M184V) occur in multiple mutational contexts.

Base Sequence↗

PubMed2003

Deformation-based surface morphometry applied to gray matter deformation.

We present a unified statistical approach to deformation-based morphometry applied to the cortical surface. The cerebral cortex has the topology of a 2D highly convoluted sheet. As the brain develops over time, the cortical surface area, thickness, curvature, and total gray matter volume change. It is highly likely that such age-related surface changes are not uniform. By measuring how such surface metrics change over time, the regions of the most rapid structural changes can be localized. We avoided using surface flattening, which distorts the inherent geometry of the cortex in our analysis and it is only used in visualization. To increase the signal to noise ratio, diffusion smoothing, which generalizes Gaussian kernel smoothing to an arbitrary curved cortical surface, has been developed and applied to surface data. Afterward, statistical inference on the cortical surface will be performed via random fields theory. As an illustration, we demonstrate how this new surface-based morphometry can be applied in localizing the cortical regions of the gray matter tissue growth and loss in the brain images longitudinally collected in the group of children and adolescents.

Adolescent↗

PubMed2003

Statistical mapping analysis of lesion location and neurological disability in multiple sclerosis: application to 452 patient data sets.

In multiple sclerosis (MS), the correlation between disability and the volume of white matter lesions on magnetic resonance imaging (MRI) is usually weak. This may be because lesion location also influences the extent and type of functional disability. We applied an automatic lesion-detection algorithm to 452 MRI scans of patients with relapsing-remitting MS to identify the regions preferentially responsible for different types of clinical deficits. Statistical parametric maps were generated by performing voxel-wise linear regressions between lesion probability and different clinical disability scores. There was a clear distinction between lesion locations causing physical and cognitive disability. Lesion likelihood correlated with the Expanded Disability Status Scale (EDSS) in the left internal capsule and in periventricular white matter mostly in the left hemisphere. Pyramidal deficits correlated with only one area in the left internal capsule that was also present in the EDSS correlation. Cognitive dysfunction correlated with lesion location at the grey-white junction of associative, limbic, and prefrontal cortex. Coordination impairment correlated with areas in interhemispheric and pyramidal periventricular white matter tracts, and in the inferior and superior longitudinal fascicles. Bowel and bladder scores correlated with lesions in the medial frontal lobes, cerebellum, insula, dorsal midbrain, and pons, areas known to be involved in the control of micturition. This study demonstrates for the first time a relationship between the site of lesions and the type of disability in large scale MRI data set in MS.

Adult↗

PubMed2003

Mutation patterns and structural correlates in human immunodeficiency virus type 1 protease following different protease inhibitor treatments.

Although many human immunodeficiency virus type 1 (HIV-1)-infected persons are treated with multiple protease inhibitors in combination or in succession, mutation patterns of protease isolates from these persons have not been characterized. We collected and analyzed 2,244 subtype B HIV-1 isolates from 1,919 persons with different protease inhibitor experiences: 1,004 isolates from untreated persons, 637 isolates from persons who received one protease inhibitor, and 603 isolates from persons receiving two or more protease inhibitors. The median number of protease mutations per isolate increased from 4 in untreated persons to 12 in persons who had received four or more protease inhibitors. Mutations at 45 of the 99 amino acid positions in the protease-including 22 not previously associated with drug resistance-were significantly associated with protease inhibitor treatment. Mutations at 17 of the remaining 99 positions were polymorphic but not associated with drug treatment. Pairs and clusters of correlated (covarying) mutations were significantly more likely to occur in treated than in untreated persons: 115 versus 23 pairs and 30 versus 2 clusters, respectively. Of the 115 statistically significant pairs of covarying residues in the treated isolates, 59 were within 8 A of each other-many more than would be expected by chance. In summary, nearly one-half of HIV-1 protease positions are under selective drug pressure, including many residues not previously associated with drug resistance. Structural factors appear to be responsible for the high frequency of covariation among many of the protease residues. The presence of mutational clusters provides insight into the complex mutational patterns required for HIV-1 protease inhibitor resistance.

Drug Resistance, Viral↗