Re evaluating the Categorization of HIV Progression in Subjects Based on CD4 T cell Decline Rates Angela Garibaldi & Ryan Willhite Loyola Marymount University BIOL /S10 March 2, 2010 Angela Garibaldi & Ryan Willhite Loyola Marymount University BIOL /S10 March 2, 2010

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  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

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 during 4 year period  Non-progressors  CD4 T cell levels above 650  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 during 4 year period  Non-progressors  CD4 T cell levels above 650

Selecting Subjects to Analyze

Selecting Subject Clones  Selected the most recent visits that had sequenced clones. (Many had 0 clones for last 3+ visits)  Utilized only “Distinct Sequences”  Selected the most recent visits that had sequenced clones. (Many had 0 clones for last 3+ visits)  Utilized only “Distinct Sequences”

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.  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.

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  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

Results SubjectNumber of Clones SThetaMin difference Max difference Range 6 vs vs vs vs vs vs vs

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

Divergence using Theta Values

Diversity shows a clearer picture  Diversity similarities between (6,5) & (13,5)

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

Implications of using CD4 Tcell Decline Rate to Categorize  This method is  Better than Markham’s 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  This method is  Better than Markham’s 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

More Recent Study  Nucleotide and amino acid mutations in human immunodeficiency virus corresponding to CD4+ decline M. D. Hill and W. Hern´andez Ponce School of Medicine, Ponce, Puerto Rico  Published online January 3, 2006 _c Springer-Verlag 2006  Nucleotide and amino acid mutations in human immunodeficiency virus corresponding to CD4+ decline M. D. Hill and W. Hern´andez Ponce School of Medicine, Ponce, Puerto Rico  Published online January 3, 2006 _c Springer-Verlag 2006

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  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

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  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

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) pmid:  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) doi: /s pmid: PubMed HubMed PubGet [Paper1]  HIV project handout for statistical analysis info  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) pmid:  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) doi: /s pmid: PubMed HubMed PubGet [Paper1]  HIV project handout for statistical analysis info