Re evaluating the Categorization of HIV Progression in Subjects Based on CD4 T cell Decline Rates

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Re evaluating the Categorization of HIV
Progression in Subjects Based on CD4 T cell
Decline Rates

• Angela Garibaldi Ryan Willhite
• Loyola Marymount University
• BIOL 398-01/S10
• March 2, 2010

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Outline

• Review of the Markham method of labeling compared
  with CD4 T cell decline rate categorization of
  progressors.
• Selection Process
• Prediction
• Statistical Approach
• Results
• Discussion/ Comparison to More Recent Studies
• References

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Categorizing Progressors by CD4 T cell Count

• Patterns of HIV-1 evolution in individuals with
  differing rates if CD4 T cell decline
• Rapid Progressors
• Fewer than 200 CD4 T cells, within 2 years of
  seroconversion
• Moderate Progressors
• CD4 T cell levels 200-650 during 4 year period
• Non-progressors
• CD4 T cell levels above 650

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Selecting Subjects to Analyze
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Selecting Subject Clones

• Selected the most recent visits that had
  sequenced clones. (Many had 0 clones for last 3
  visits)
• Utilized only Distinct Sequences

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What we predict

• Subj. 6 (Moderate Test) and 13 (Non-Progressor)
  will be less divergent and have less diversity
  than when 6 is compared to another Moderate (5,7)
  
• Subj. 7 (Moderate Test) and 10 (Rapid-Progressor)
  will be less divergent and have less diversity
  than when 7 is compared to another Moderate (5,6)
• Subj. 6 and 7 will be more divergent and have
  higher diversity in comparison to values
  generated in the above.

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Statistical Approach

• Utilized BedRock
• Conduct Clustdist multiple sequence alignment for
  comparison and frequency values used to
• Calculate
• ''S''
• ''Theta to measure Divergence
• ''Minimum'' and ''Maximum
• S/Number of clones to interpret Diversity

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Results
Subject Number of Clones S Theta Min difference Max difference Range
6 vs 13 53 93 20.48 38 50 12
7 vs 10 62 96 20.43 27 42 15
6 vs 7 53 93 20.48 26 41 15
6 vs 5 49 90 20.18 23 42 19
7 vs 5 48 83 18.69 34 49 15
10 vs 5 59 103 22.15 30 48 12
13 vs 5 43 79 18.22 34 46 12
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Divergence

• Min. and Max. values show that 6 and 10 are most
  divergent
• Considers Frequencies

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Divergence using Theta Values
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Diversity shows a clearer picture

• Diversity similarities between (6,5) (13,5)

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Revisiting the Results

• Divergence does not prove to be an accurate
  method of categorizing
• Theta did not deliver insight
• Diversity levels are similar in certain
  categories

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Implications of using CD4 Tcell Decline Rate to
Categorize

• This method is
• Better than Markhams method of categorization
• Especially in categorizing moderates from rapids
• Not as successful
• without a larger sample size
• Not much success in comparing all
• In the future
• Find a way to calculate the significance
• A larger sample size
• Use a program that would allow a comparison with
  higher number of clones
• Few clones available from subjects may complicate
  the reliability.
• Focus on most recent visits and acquire clones
  for these visits

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More Recent Study

• Nucleotide and amino acid mutations in human
  immunodeficiency virus corresponding to CD4
  decline
• M. D. Hill and W. Hernandez
• Ponce School of Medicine, Ponce, Puerto Rico
• Published online January 3, 2006 _c
  Springer-Verlag 2006

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Comparing our findings to more recent studies

• Change in diversity of nucleotide sequences among
  HIV forms within individuals as their CD4 counts
  progressed
• There is a trend for the average distance to
  increase with dropping CD4 values
• Among all progressors, 94.1 of subjects
  demonstrated increased diversity
• The rapid progressors had a statistically
  significant higher loop charge
• Four of the rapid progressors had T-tropism

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How Does this Compare?

• Found that progression is easier to evaluate than
  non-progression in terms of diversity
• The moderate and rapid progressor were most
  divergent
• Therefore there is an accumulation of differences
  over a period of time
• Perhaps there needs to be further investigation
  in
• RNA and DNA sequences
• A closer look at regions described in paper such
  as loop charge

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References

• Markham RB, Wang WC, Weisstein AE, Wang Z, Munoz
  A, Templeton A, Margolick J, Vlahov D, Quinn T,
  Farzadegan H, and Yu XF. Patterns of HIV-1
  evolution in individuals with differing rates of
  CD4 T cell decline. Proc Natl Acad Sci U S A 1998
  Oct 13 95(21) 12568-73. pmid9770526.
• Hill MD and Hern?ndez W. Nucleotide and amino
  acid mutations in human immunodeficiency virus
  corresponding to CD4 decline. Arch Virol 2006
  Jun 151(6) 1149-58. doi10.1007/s00705-005-0693-8
  pmid16385396. PubMed HubMed PubGet Paper1
• HIV project handout for statistical analysis info