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Predicting the Onset of AIDS Robert Arnold, Alex Cardenas, Zeb Russo LMU Biology Department 10/5/2011.

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Presentation on theme: "Predicting the Onset of AIDS Robert Arnold, Alex Cardenas, Zeb Russo LMU Biology Department 10/5/2011."— Presentation transcript:

1 Predicting the Onset of AIDS Robert Arnold, Alex Cardenas, Zeb Russo LMU Biology Department 10/5/2011

2 Outline What causes a subject to develop AIDS from HIV and what separates AIDS from HIV? Focusing on dS/dN ratio The definition of AIDS, the subjects affected, and their similarities, ALIVE information New hypothesis involving the division of subjects into those with AIDS, trending towards AIDS, and AIDS free trending away Research comparison, proving assumptions incorrect Further comparisons between the subjects with AIDS and those without Comparing our results with our paper

3 dS/dN ratio related to AIDS development determined that low dS/dN ratios, subjects that select either for nonsynonymous mutation or not against it were the subjects to develop AIDS The subjects picked were 4, 9, 11, and 14, all with 0.0 dS/dN ratios along with subject 10 with a 0.2 and subject 1 with a 0.3

4 Outline What causes a subject to develop AIDS from HIV and what separates AIDS from HIV? Focusing on dS/dN ratio The definition of AIDS, the subjects affected, and their similarities, ALIVE information New hypothesis involving the division of subjects into those with AIDS, trending towards AIDS, and AIDS free trending away Research comparison, proving assumptions incorrect Further comparisons between the subjects with AIDS and those without Comparing our results with our paper

5 AIDS and CD4 counts CDC definition of AIDS is a CD4 count below 200 Once diagnosed, cannot be reversed Makes our first hypothesis irrelevant since all ‘rapid progressors’ drop below 200, AKA all 6 have AIDS –Subjects 1, 3, 4, 10, 11, 15

6 Outline What causes a subject to develop AIDS from HIV and what separates AIDS from HIV? Focusing on dS/dN ratio The definition of AIDS, the subjects affected, and their similarities, ALIVE information New hypothesis involving the division of subjects into those with AIDS, trending towards AIDS, and AIDS free trending away Research comparison, proving assumptions incorrect Further comparisons between the subjects with AIDS and those without

7 Revised hypothesis separating those with AIDS from others Separated into 3 categories –Those with AIDS: 1, 3, 4, 10, 11, 15 –Those trending to AIDS: 7, 8, 9, 14 –Those free of and trending away from AIDS: 2, 5, 6, 12, 13 New vision; which subjects developed AIDS? Began to focus on ALIVE research to go beyond Markham’s 4 year period

8 Development of two new questions Since we can tell who has AIDS, we would now like to determine whether there are any similar clones of the env gene across the AIDS subjects Does a median ds/dn ratio below 1.0 or lower determine whether you will get AIDS or not?

9 Outline What causes a subject to develop AIDS from HIV and what separates AIDS from HIV? Focusing on dS/dN ratio The definition of AIDS, the subjects affected, and their similarities, ALIVE information New hypothesis involving the division of subjects into those with AIDS, trending towards AIDS, and AIDS free trending away Research comparison, proving assumptions incorrect Further comparisons between the subjects with AIDS and those without Comparing our results with our paper

10 Our division of the Patients

11 Random clonal comparison To determine whether there were any similarities between clones of those who developed AIDS during the study and those at risk, we performed a ClustalW on a random selection of two clones from each subject

12 2 Clones Rooted Tree

13 Comparison of dS/dN SubjectNo. of observationsCD4 Median intravisit nucleotide differences among clones Virus copy number (×103) Annual rate of CD4 T cell decline Slope of change in intravisit nucleotide differences per clone per year Slope of divergence (% nucleotides mutated from baseline consensus sequence per year)Median dS/dN AIDS Subject 441,0280.96.8−5934.642.090 Subject 1058331.7199.3−3633.1610.2 Subject 1147532.2762.2−3631.110.320 Subject 15470715.16171−362−2.940.680.7 Subject 358191.82302.5−2940.530.741 Subject 134645.64307.6−1175.11.550.3 At Risk Subject 751,0722.27317.6−392−0.791.351.3 Subject 875381.24209−921.681.160.5 Subject 984899.49265−111.581.210 Subject 149523150.9−511.690.60 Not at Risk Subject 257151.6421.6301.320.491.8 Subject 557492.5260.6−410.060.51.4 Subject 674052.82321.4521.920.820.4 Subject 1267722.85.1440.620.130.9 Subject 1356710.871.7530.530.283.5

14 Neither Assumption is correct Using the original data from the Bedrock website, we determined who actually developed AIDS over the full study 1, 3, 4, 6, 7, 8, 9, 10, 11, 14, 15 Only 2, 5, 12 and 13 avoided the progression to AIDS over the course of the study

15 Outline What causes a subject to develop AIDS from HIV and what separates AIDS from HIV? Focusing on dS/dN ratio The definition of AIDS, the subjects affected, and their similarities, ALIVE information New hypothesis involving the division of subjects into those with AIDS, trending towards AIDS, and AIDS free trending away Research comparison, proving assumptions incorrect Further comparisons between the subjects with AIDS and those without Comparing our results with our paper

16 2 Clones Rooted Tree Redux

17 Comparison of dS/dN SubjectNo. of observationsCD4 Median intravisit nucleotide differences among clones Virus copy number (×103) Annual rate of CD4 T cell decline Slope of change in intravisit nucleotide differences per clone per year Slope of divergence (% nucleotides mutated from baseline consensus sequence per year)Median dS/dN AIDS Subject 441,0280.96.8−5934.642.090 Subject 1058331.7199.3−3633.1610.2 Subject 1147532.2762.2−3631.110.320 Subject 15470715.16171−362−2.940.680.7 Subject 358191.82302.5−2940.530.741 Subject 134645.64307.6−1175.11.550.3 At Risk Subject 751,0722.27317.6−392−0.791.351.3 Subject 875381.24209−921.681.160.5 Subject 984899.49265−111.581.210 Subject 149523150.9−511.690.60 Not at Risk Subject 257151.6421.6301.320.491.8 Subject 557492.5260.6−410.060.51.4 Subject 674052.82321.4521.920.820.4 Subject 1267722.85.1440.620.130.9 Subject 1356710.871.7530.530.283.5

18 Immune Relaxation Hypothesis Evolutionary rates slow due to disrupting immune function In relation to our claims, the virus infects specific CD4+ T cell count. –The immune system is the positive selecting agent in C2-V5 region of env. In relation to Aids, the immune effectors and the virus can alter the course of evolution. Lower dS/dN ratios were observed in a single patient –Even out to equilibrium CD4+ T Cells disrupted by infection respond to epitopes coded by env and in driving env sequence evolution.

19 Non-synonymous divergence stabilizes –Seems to coincide with disease progression Synonymous divergence does not seem to stabilize Phylogenetic methods can’t be used per say in this paper –No recombination is generally assumed –And studies show that recombination rate in HIV populations in vivo is high Divergence

20 dN/dS ratios > 1 indicates widespread adaptive evolution –Most common among data sets, indicative of positive selection < 1 some sites are selectively constrained For our studies, 1 indicated no AIDs Ratios

21 CD4+ T Cells In direct correlation with distinguishing AIDs –Subjects < 300  AIDs –Related it back to < 200 from previous graphs and tables. “Feedback loop” in play. Virus impairs HIV specific responses

22 Findings 11/15  AIDs CD4 T Cell Count dN/dS ratio New ?’s

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