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

Rates

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

Rates

Angela Garibaldi & Ryan WillhiteLoyola Marymount University

BIOL 398-01/S10

March 2, 2010

Angela Garibaldi & Ryan WillhiteLoyola Marymount University

BIOL 398-01/S10

March 2, 2010

Outline 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

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

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

Selecting Subjects to AnalyzeSelecting Subjects to Analyze

Selecting Subject ClonesSelecting 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…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 ApproachStatistical 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

ResultsResults

Subject Number of Clones

S Theta Min difference

Max difference

Range

6 vs 13 53 93 20.48 38 50 127 vs 10 62 96 20.43 27 42 156 vs 7 53 93 20.48 26 41 156 vs 5 49 90 20.18 23 42 197 vs 5 48 83 18.69 34 49 1510 vs 5 59 103 22.15 30 48 1213 vs 5 43 79 18.22 34 46 12

DivergenceDivergence 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 ValuesDivergence using Theta Values

Diversity shows a clearer pictureDiversity shows a clearer picture

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

Revisiting the ResultsRevisiting 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

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 StudyMore 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

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?…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

ReferencesReferences

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. pmid:9770526.

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. doi:10.1007/s00705-005-0693-8 pmid:16385396. 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) 12568-73. pmid:9770526.

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. doi:10.1007/s00705-005-0693-8 pmid:16385396. PubMed HubMed PubGet [Paper1]

HIV project handout for statistical analysis info