predicting the onset of aids

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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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Predicting the Onset of AIDS. Robert Arnold, Alex Cardenas, Zeb Russo LMU Biology Department 10/5/2011. Outline. What causes a subject to develop AIDS from HIV and what separates AIDS from HIV? Focusing on dS / dN ratio - PowerPoint PPT Presentation

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Page 1: Predicting the Onset of AIDS

Predicting the Onset of AIDS

Robert Arnold, Alex Cardenas, Zeb RussoLMU Biology Department

10/5/2011

Page 2: Predicting the Onset of AIDS

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

Page 3: Predicting the Onset of AIDS

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

Page 4: Predicting the Onset of AIDS

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

Page 5: Predicting the Onset of AIDS

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

Page 6: Predicting the Onset of AIDS

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

Page 7: Predicting the Onset of AIDS

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

Page 8: Predicting the Onset of AIDS

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?

Page 9: Predicting the Onset of AIDS

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

Page 10: Predicting the Onset of AIDS

Our division of the Patients

Page 11: Predicting the Onset of AIDS

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

Page 12: Predicting the Onset of AIDS

2 Clones Rooted Tree

Page 13: Predicting the Onset of AIDS

Comparison of dS/dN

Subject No. of observations CD4

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 4 4 1,028 0.9 6.8 −593 4.64 2.09 0

Subject 10 5 833 1.71 99.3 −363 3.16 1 0.2

Subject 11 4 753 2.27 62.2 −363 1.11 0.32 0

Subject 15 4 707 15.16 171 −362 −2.94 0.68 0.7

Subject 3 5 819 1.82 302.5 −294 0.53 0.74 1

Subject 1 3 464 5.64 307.6 −117 5.1 1.55 0.3

At Risk                

Subject 7 5 1,072 2.27 317.6 −392 −0.79 1.35 1.3

Subject 8 7 538 1.24 209 −92 1.68 1.16 0.5

Subject 9 8 489 9.49 265 −11 1.58 1.21 0

Subject 14 9 523 1 50.9 −51 1.69 0.6 0

Not at Risk                

Subject 2 5 715 1.64 21.6 30 1.32 0.49 1.8

Subject 5 5 749 2.5 260.6 −41 0.06 0.5 1.4

Subject 6 7 405 2.82 321.4 52 1.92 0.82 0.4

Subject 12 6 772 2.8 5.1 44 0.62 0.13 0.9

Subject 13 5 671 0.87 1.7 53 0.53 0.28 3.5

Page 14: Predicting the Onset of AIDS

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

Page 15: Predicting the Onset of AIDS

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

Page 16: Predicting the Onset of AIDS

2 Clones Rooted Tree Redux

Page 17: Predicting the Onset of AIDS

Comparison of dS/dN

Subject No. of observations CD4

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 4 4 1,028 0.9 6.8 −593 4.64 2.09 0

Subject 10 5 833 1.71 99.3 −363 3.16 1 0.2

Subject 11 4 753 2.27 62.2 −363 1.11 0.32 0

Subject 15 4 707 15.16 171 −362 −2.94 0.68 0.7

Subject 3 5 819 1.82 302.5 −294 0.53 0.74 1

Subject 1 3 464 5.64 307.6 −117 5.1 1.55 0.3

At Risk                

Subject 7 5 1,072 2.27 317.6 −392 −0.79 1.35 1.3

Subject 8 7 538 1.24 209 −92 1.68 1.16 0.5

Subject 9 8 489 9.49 265 −11 1.58 1.21 0

Subject 14 9 523 1 50.9 −51 1.69 0.6 0

Not at Risk                

Subject 2 5 715 1.64 21.6 30 1.32 0.49 1.8

Subject 5 5 749 2.5 260.6 −41 0.06 0.5 1.4

Subject 6 7 405 2.82 321.4 52 1.92 0.82 0.4

Subject 12 6 772 2.8 5.1 44 0.62 0.13 0.9

Subject 13 5 671 0.87 1.7 53 0.53 0.28 3.5