HIV Mutation Detail Information

Virus Mutation HIV Mutation I84V


Basic Characteristics of Mutations
Mutation Site I84V
Mutation Site Sentence Table 2. Description of HIV drug resistance prior to TCE stratified by cohort.
Mutation Level Amino acid level
Mutation Type Nonsynonymous substitution
Gene/Protein/Region PR
Standardized Encoding Gene gag-pol  
Genotype/Subtype HIV-1
Viral Reference HXB2
Functional Impact and Mechanisms
Disease HIV Infections    
Immune -
Target Gene -
Clinical and Epidemiological Correlations
Clinical Information Y
Treatment PIs
Location UK
Literature Information
PMID 22110581
Title Can linear regression modeling help clinicians in the interpretation of genotypic resistance data? An application to derive a lopinavir-score
Author Cozzi-Lepri A,Prosperi MC,Kjaer J,Dunn D,Paredes R,Sabin CA,Lundgren JD,Phillips AN,Pillay D
Journal PloS one
Journal Info 2011;6(11):e25665
Abstract BACKGROUND: The question of whether a score for a specific antiretroviral (e.g. lopinavir/r in this analysis) that improves prediction of viral load response given by existing expert-based interpretation systems (IS) could be derived from analyzing the correlation between genotypic data and virological response using statistical methods remains largely unanswered. METHODS AND FINDINGS: We used the data of the patients from the UK Collaborative HIV Cohort (UK CHIC) Study for whom genotypic data were stored in the UK HIV Drug Resistance Database (UK HDRD) to construct a training/validation dataset of treatment change episodes (TCE). We used the average square error (ASE) on a 10-fold cross-validation and on a test dataset (the EuroSIDA TCE database) to compare the performance of a newly derived lopinavir/r score with that of the 3 most widely used expert-based interpretation rules (ANRS, HIVDB and Rega). Our analysis identified mutations V82A, I54V, K20I and I62V, which were associated with reduced viral response and mutations I15V and V91S which determined lopinavir/r hypersensitivity. All models performed equally well (ASE on test ranging between 1.1 and 1.3, p = 0.34). CONCLUSIONS: We fully explored the potential of linear regression to construct a simple predictive model for lopinavir/r-based TCE. Although, the performance of our proposed score was similar to that of already existing IS, previously unrecognized lopinavir/r-associated mutations were identified. The analysis illustrates an approach of validation of expert-based IS that could be used in the future for other antiretrovirals and in other settings outside HIV research.
Sequence Data -
Mutation Information
Note
Basic Characteristics of Mutations
  • Mutation Site: The specific location in a gene or protein sequence where a change occurs.
  • Mutation Level: The level at which a mutation occurs, including the nucleotide or amino acid level.
  • Mutation Type: The nature of the mutation, such as missense mutation, nonsense mutation, synonymous mutation, etc.
  • Gene/Protein/Region: Refers to the specific region of the virus where the mutation occurs. Including viral genes, viral proteins, or a specific viral genome region. If the article does not specifically indicate the relationship between the mutation and its correspondence, the main
  • Gene/Protein/Region studied in the article is marked.
  • Genotype/Subtype: Refers to the viral genotype or subtype where the mutation occurs. If the article does not specifically indicate the relationship between the mutation and its correspondence, the main Genotype/Subtype studied in the article is marked.
  • Viral Reference: Refers to the standard virus strain used to compare and analyze viral sequences.
Functional Impact and Mechanisms
  • Disease: An abnormal physiological state with specific symptoms and signs caused by viral infection.
  • Immune: The article focuses on the study of mutations and immune.
  • Target Gene: Host genes that viral mutations may affect.
Clinical and Epidemiological Correlations
  • Clinical Information: The study is a clinical or epidemiological study and provides basic information about the population.
  • Treatment: The study mentioned a certain treatment method, such as drug resistance caused by mutations. If the study does not specifically indicate the relationship between mutations and their correspondence treatment, the main treatment studied in the article is marked.
  • Location: The source of the research data.
Literature Information
  • Sequence Data: The study provides the data accession number.