A new wild-type in the era of transmitted drug resistance

Transcription

1 A new wild-type in the era of transmitted drug resistance EHR 2018 Rome KU Leuven 1

2 A new wild-type in the era of transmitted drug resistance? KU Leuven 2

3 Measurably evolving viruses Evolutionary rate (nucleotide substitutions/site/year) HBV HTLV RNA viruses including HIV and HCV Mammalian mitochondrial DNA Drosophila nuclear DNA E. Coli and Salmonella enterica bacteria Mammalian nuclear DNA Plant chloroplast DNA Lemey et al.,

4 Measurably evolving viruses 10% Divergence 8% 6% 4% 2% Years Post Seroconversion 4 Shankarappa et al., 1999

5 High rates of evolutionary changes Inefficient RT enzyme (3.4 x 10-5 mutations/bp/replication cycle) 5 Rambaut et al., 2004

6 High rates of evolutionary changes Short generation time ( 1.5 days) 6 Rambaut et al., 2004

7 High rates of evolutionary changes Large progeny number ( new viral particles each day) 7 Rambaut et al., 2004

8 High rates of evolutionary changes Frequent recombination events (3 x 10-4 events/site/replication cycle) 8 Rambaut et al., 2004

9 Early spread and epidemic ignition (group M) Current pandemic originated from a virus that entered the human population ~ 100 years ago 9 Faria et al., 2014

10 Population viral diversity and identity Extensive genetic diversity naturally present globally - defining feature of the virus - key to the current pandemic 65% Env protein identity ~ median 78% between protein orthologs of humans and mice over 90 million years Implications of diversity extensively investigated founder effects incomplete sampling 0.1 Rambaut et al., 2004 Introduction 10 Abecasis et al., 2007

11 Global expansion of HIV-1 11 Tebit & Arts., 2010

12 A new wild type in the era of transmitted drug resistance HIV can evolve rapidly, leading to heterogenous set of genetic variants - different epidemiological scales - time and space - to what extent is this potential exploited? Transmission of drug resistance as a marker of population adaptation - easy to observe, strong selective pressure on the virus - increased risk of virological failure and cause of mortality - genotype testing integral part of management 12

13 A new wild type in the era of other drivers Multiple selective and neutral forces at play - drift and other stochastic events (subtypes) - adaptation to the host immune system (HLA, ab) - virulence and the rate of disease progression (transmission) Importance to monitor how HIV evolves at population level - confounding effect of subtypes (DRM E138A) - TDR strains ~ single or multiple independent episodes - persist in absence of pressure - mitigation by reducing risk of VF - transmission of genotype ~ transmission of phenotype - vaccine development (pre-adaptation, bottleneck) - variability in HIV-1 set-point viral load (30%) 13

14 Exploring HIV s potential to adapt and circulate globally 14

15 Exploring HIV s potential to adapt Theoretical considerations & Reports of intra inter host adaptation 15

16 An evolutionary perspective Population diversity is an intrinsic reflection of transmission dynamics - but virus and host genetics also impact between-host dynamics As a result, complex interplay of multi-scale evolutionary processes - selective advantage of viral traits differs as conflicting forces apply - viral spread in a population -> select traits maximise transmission efficiency - viral strategies favoring within-host fitness do not necessarily benefit epidemiological fitness A delicate evolutionary trade-off between virulence and transmission - high virulence shortening host survival - allowing faster transmission 16

17 Linking within and between host evolution Connection between HIV-1 with-host evolution and transmission dynamics at the epidemiological level? - direct relationship? - different or similar dynamics? 17

18 Linking within and between host evolution Connection between HIV-1 with-host evolution and transmission dynamics at the epidemiological level? - evolution racing at different speeds A B 18

19 Linking within and between host evolution Connection between HIV-1 with-host evolution and transmission dynamics at the epidemiological level? - comparable nucleotide frequencies 19 Zanini et al., 2015

20 Linking within and between host evolution Connection between HIV-1 with-host evolution and transmission dynamics at the epidemiological level? - comparable nucleotide frequencies 20 Theys et al., PLoS Genetics, 2018

21 Linking within and between host evolution Reconcile HIV-1 with-host evolution with transmission dynamics at the epidemiological level? Recent experimental and theoretical work bridging different scales Three stages [1] processes that shape viral evolution in a host 21

22 Linking within and between host evolution Reconcile between HIV-1 with-host evolution and transmission dynamics at the epidemiological level? Recent experimental and theoretical work bridging different scales Three stages [1] processes that shape viral evolution in a host [2] the bottleneck transmission event 22

23 Linking within and between host evolution Reconcile between HIV-1 with-host evolution and transmission dynamics at the epidemiological level? Recent experimental and theoretical work bridging different scales Three stages [1] processes that shape viral evolution in a host [2] the bottleneck transmission event [3] translation at the population level 23

24 1. Within-host evolutionary dynamics Evidence of viral traits that directly promote HIV-1 transmission from one host to another is limited But, viral strains differ in their transmissibility - consequence of their effect on the different stages of disease progression. Different aspects impact the ability to transmit [1] transmission probability per contact is closely related to the viral load [2] adaptation to selective pressure and associated fitness defects [3] lack of evolution (donor imprint, reservoirs) 24

25 1. Within-host evolutionary dynamics transmission probability per contact is closely related to the viral load [1] HIV-1 infectiousness is not constant over the time of infection - acute phase as an important time window: P(Trans) ~ VL - spvl as indicator of the rate of disease progression and per-contact transmission rate 25 Fraser et al., 2014

26 1. Within-host evolutionary dynamics adaptation to selective pressure and associated fitness defects [2] Coinciding with increasing VL, virus replication during chronic phase continuously drives a diversifying and diverging virus population - evolutionary dynamics are governed by competitive fitness. - sequence space limited by functional and immunological constraints [2] Escape mutations generally imply a cost on replicative capacity - implications for viral load and transmissibility of mutated strains 26

27 1. Within-host evolutionary dynamics lack of evolution (donor imprint, reservoirs) [3] Evolutionary imprints that are transmitted from the donor - immune (HLA mismatch) or treatment adaptation - modulate viral load in the recipient - reversion of transmitted escape variants hindered by local fitness optima - potential transitory effect on population-level viral load / diversity [3] Long-lived reservoirs of latently infected CD4+ T cells - established early in infection - transient release of ancestral viruses associated with lower viral loads 27

28 1. Within-host evolutionary dynamics Within-host evolution of HIV-1 is short-sighted* - evolutionary change that is adaptive within a host - but limits the ability of the virus to transmit to new hosts. Competition between strains during the course of infection - maximize viral fitness - resulting in increased virulence 28

29 2. Selective bottlenecks in HIV-1 transmission Impact size of within-host evolution on between-host transmission [1] social dynamics of the host population [2] biological processes defining the transmission event [1] Time intervals between transmission events - events in early infection limit time window for host adaptation - longer time intervals allow for increasing viral evolution 29 Lythgoe et al., 2017

30 2. Selective bottlenecks in HIV-1 transmission Impact size of within-host evolution on between-host transmission [1] social dynamics of the host population [2] biological processes defining the transmission event [1] Which time point contributes most? - infectiousness peaks during acute infection, accounting for most infections - relative contribution of transmissions however varies between studies - TDR and TasP effectiveness indicate transmission beyond acute infection 30

31 2. Selective bottlenecks in HIV-1 transmission Impact size of within-host evolution on between-host transmission [1] social dynamics of the host population [2] biological processes defining the transmission event [2] Immunological and physical barriers in both donor and recipient 31 Kariuki et al. 2017

32 2. Selective bottlenecks in HIV-1 transmission Impact size of within-host evolution on between-host transmission [1] social dynamics of the host population [2] biological processes defining the transmission event [2] Immunological and physical barriers in both donor and recipient - low probability of transmission per contact act - strong genetic bottleneck shown by a genetically homogeneous virus population in recipients shortly after infection - systemic infection is mainly established from the propagation of a single variant; the transmitted/founder (T/F) virus. 32

33 2. Selective bottlenecks in HIV-1 transmission Impact size of within-host evolution on between-host transmission [1] social dynamics of the host population [2] biological processes defining the transmission event [2] Strength of selection during the bottleneck event - viral traits are advantageous and determine which variants survive - transmitted variants are to some extent determined by stochastic effects - comparative studies on virus diversity in recipients versus donors - specific strains are preferentially transmitted - genetic, immunological and phenotypic signatures associated with increased transmission success 33

34 2. Selective bottlenecks in HIV-1 transmission Impact size of within-host evolution on between-host transmission [1] social dynamics of the host population [2] biological processes defining the transmission event [2] Envelope signatures associated with transmission efficiency - shorter variable loop lengths and fewer N-linked glycosylation sites - CXCR4-utilizing viruses are associated with reduced transmissibility [2] Non-envelope signatures associated with transmission efficiency - selection bias favouring viruses with higher transmission potential - strength bias ~ the transmission risk associated with the specific barrier (microbicide versus genital inflammation) - transmission fitness linked to the similarity of the T/F virus to the HIV-1 consensus sequence ~ ancestral donor strain). 34

35 3.Evolutionary paradox between host and population level Existence of a transmission potential - evolution shaped by constraints within the host and during a single transmission process, but also at the population level. - viral genotypes with intermediate virulence are naturally selected by transmission Short-sighted evolution is bypassed and viruses with high transmission potential are favoured? - theories to reconcile observed adaptation patterns between levels - the preferential transmission of ancestral viruses with an inherent transmission advantage, either early in infection or transiently released from long-lived latent reservoirs - one strategy to minimize the impact of host adaptation 35

36 3.Evolutionary paradox between host and population level 36 Lythgoe et al., 2017

37 Exploring HIV s potential to adapt Theoretical considerations & Evidence of intra inter host adaptation - Natural diversity - Drug resistance - Immune escape - Disease progression 37

38 1. Natural diversity What is wild-type? - HXB2 vs consensus (what is consensus) - subtypes are independent sub-epidemics of HIV-1 (wild-type) - confounding effect of epidemiology (RT E138A) Abecasis et al., 2015 T1 N1 T2 N2 T3 T4 N3 N4 38 N5 N6 N7 Theys et al., 2010

39 1. Natural diversity Evolution of natural diversity (subtypes) - the viable pathways in the virus past evolution. - modest increase in sequence diversity over time ( ~20 years) - limited choice by evolutionary constraints - exploration of fixed' trajectories of sequence space Direct relationship between within-host fitness and global conservation - Zanini et al, diversity within patients matches diversity across group M - reversion rates towards consensus / ancestral (1/3 of changes) - global group M consensus sequence presents an optimal sequence 39

40 1. Natural diversity Evolutionary dynamics of polymorphisms in integrase of HIV-1 - time trends in frequency of covarying amino acid variants - ongoing adaptation of integrase 40 Meixenberger et al., 2017

41 2. Adaptation ~ drug escape Spatio-temporal trends of TDR ( ) - similar over calendar time - Tsampling ~ recent infection vs unknown duration of infection - region- & subtype specific (Rhee et al., 2015, Zazzi et al., 2018) - stabilising decreasing trend of TDR in HIC (Hofstra et al, 2016) - emergence of acquired DR has stopped - rising trend in LMIC (Paraskevis et al. 2017, Pham et al. 2014) - due to ART rollout 41

42 2. Adaptation ~ drug escape 42 Olson et al., 2018

43 2. Adaptation ~ drug escape 43 Fabeni et al., 2017

44 2. Adaptation ~ drug escape Usually singletons and associated with a single drug class - TAMs, L90M, K103N - limited effect on efficacy except for NNRTI 44 Vercauteren et al., 2006

45 2. Adaptation ~ drug escape Dynamics of TDR flow - Phylogenetically: 70% of TDR had a treatment-naive source. 45 Mourad et al., 2015

46 2. Adaptation ~ drug escape Statistically PI SDRMs Subtype B NNRTI SDRMs Subtype B 1.5 R-square: 0.52 Intercept: [95% CI, ] Slope: [95% CI, ] 90 3 R-Square: 0.68 Intercept: [95% CI, ] Slope: [95% CI, ] prevalence in DN (%) prevalence in DN (%) prevalence in PI-TR (%) prevalence in NNRTI-TR (%) 46 Winand et al., 2015

47 2. Adaptation ~ drug escape Statistically 47 Mourad et al., 2015

48 2. Adaptation ~ drug escape Significant onward transmission from untreated patients - explain substantial proportion of TDR - self-sustaining drug resistance lineages - most common mutations are not representative for mutations seen in treatment failure in current patients - long TDR transmission chains, pointing to slow rates of reversion 48

49 2. Adaptation ~ drug escape Fitness cost of mutations ~ limiting further spread 49 Castro et al., 2013

50 2. Adaptation ~ drug escape Fitness cost of mutations ~ reversal or persistence 50 Mourad et al., 2015

51 3. Adaptation ~ immune escape CTL response major driving force of host HIV-1 adaptation - extensive maps of location and pathways of CTL escape - list of (other) HLA-associated polymorphisms Analogues to negative effect of TDR on ART - gradual spread in the population as the epidemic progresses - extent of accumulation is incompletely understood - alle prevalence vs allele restrictiveness Challenge to vaccine development when composition of CTL epitopes differs among regions 51

52 3. Adaptation ~ immune escape 52 Kawashima et al., 2009

53 3. Ada pt at io n ~ i mmu ne e s c a p e HLA pressures drive HIV pol sequence diversification Kinloch et al.,

54 3. Adaptation ~ immune escape HLA-associated polymorphisms have spread during the epidemic - ~2.5 fold increase in sequence diversity and polymorphism frequency Kinloch et al.,

55 3. Adaptation ~ immune escape pre-adaptation of circulating HIV sequence to the host -average circulating HIV sequence ~ HLA-specific polymorphisms - extent of adaptation remains relatively low Kinloch et al.,

56 3. Adaptation ~ immune escape Preadaptation of circulating HIV sequence to the host - no shift in population HIV-1 consensus - absolute value of increases generally modest Tempo and impact of population-level adaptation - host genetic, virus and epidemic specific factors Impact of HLA-driven HIV adaptation on virulence - diminish protective capacity of certain HLA alleles over time - accelerated rates of disease progression 56

57 4. Adaptation ~ disease progression CD4 count and viral load as predictive markers for disease progression 57

58 4. Adaptation ~ disease progression Variability in rate of disease progression Langford et al.,

59 4. Adaptation ~ disease progression Variability of set point viral load (spvl) Fraser et al.,

60 4. Adaptation ~ disease progression Transmissibility of spvl: the viral factor Patients in a transmission cluster have more often a similar set point viral load compared to non-linked patients Fraser et al.,

61 4. Adaptation ~ disease progression Virologic factors influencing disease progression - polymerase gene replication capacity (pol RC), coreceptor tropism switch, deletions in the nef gene, CCR5-tropic virus only Kaplan Meier curves for clinical progression to AIDS (P <.001) Harbouring also CXCR4- tropic virus Daar et al., Arts et al., 2012

62 4. Adaptation ~ disease progression 62

63 4. Adaptation ~ disease progression A CRF linked to faster progression CRF 19_cpx all rapid progress ors Subtype A Subtype D Subtype G AIDS rapid progressors (<3 years) Asymptomatic at 3 years Chronic-AIDS (>3years) Kouri et al.,

64 4. Adaptation ~ disease progression A CRF linked to faster progression Higher RANTES 66 AIDS-RP Not subtype B Oral Candidiasis Not always using condoms 58 Non-AIDS Lower Neopterin 35 CRF19_cpx 50 Anal Contact Heterosexual Lower VL at Sampling Higher protease fitness score CXCR4 Co-receptor use Subtype A Lower MCP Lower IP Lower B2 Microglobulin Subtype D Kouri et al.,

65 4. Adaptation ~ disease progression Intersubtype differences in disease progression: - aa substitutions correlated with increased pol RC and disease progression Ng et al.,

66 Conclusion HIV diversifies within and between host - origin of the epidemic - different factors at play - modest impact on diversity at population level - constraints and reversion towards an optimal sequence Need for continued monitoring - individual sites and combinations 66

67 FWO G , EC6FP SPREAD QLRT , EC7FP CHAIN , FCT SFRH/BD/64530/2009, CNPQ (Science without borders) The VIROGENESIS project receives funding from the European Union s Horizon 2020 research and innovation program under grant agreement N o