Molecular Markers of AQ and SP Resistance in Sub-Saharan Africa
Explore the prevalence and importance of molecular markers of resistance to antimalarial drugs AQ and SP in various African countries, with objectives to measure change over time and assess protective efficacy. Learn about sampling methods, background markers, and the significance of monitoring drug efficacy.
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Presentation Transcript
Baseline molecular markers of AQ and Baseline molecular markers of AQ and SP in Sub SP in Sub- -Saharan Saharan A Africa frica Burkina Faso: IRSS Chad: CSSI Gambia: MRC Guinea: UGANC Mali: MRTC Nigeria: JEDIMA Niger: CERMES Jean Bosco OUEDRAOGO IRSS-DRO, Bobo-Dioulasso
Overview 1. Background 2. Samples and methods 3. Prevalence of AQ markers 4. Prevalence of SP markers 5. Summary
Objectives Objectives Measure the prevalence of molecular markers associated with resistance to SP and AQ before SMC in the community in children under 5yrs in older age groups too old for SMC Importance of standardised methods of sampling, DNA extraction Importance of adequate sample size Measure the change in the prevalence of these markers at intervals (2-3 years) in SMC areas Measure protective efficacy of SMC treatments (using case control studies)
Background:Molecular markers of AQSP M74IN75E CVMNK CVIET SVMNT C72S K76T pfcrt AQ D1246Y N86Y F184Y NFD NYD YYY pfmdr1 N51I C59R S108N VCS IRN (Triple) pfdhfr SP I431V S436A K540E A437G A581G A631S/T SK GE (Double) pfdhps
Sampling locations for molecular marker surveys Community surveys in 2015 in areas that had not started SMC (except Gambia which had started SMC in 2014) Representative sampling of two age groups after the end of the transmission season: <5years 10-30 years Household surveys in villages selected with PPS 2000 individuals in each age group Total target sample size of 28,000 Powered to detect odds ratio of 2.5 in each country and an odds ratio of 1.4 in pooled analysis
Why Monitoring efficacy of SMC drugs? provide reassurance about efficacy after 2yrs SMC establish baseline for future monitoring monitor factors that may limit selection for resistance: avoid missed months adherence to daily doses diagnosis by RDT + prompt treatment of breakthrough cases withdrawal of ASAQ from SMC areas avoid under-dosing: dosing by age; exclusion of children >5yrs
Monitoring of molecular markers of resistance finger-prick samples -> dried blood spots on filter paper detection PCR on all samples Pfdhps 437,540; Pfdhfr 108,59,51; PfCRT 76T; PfMDR1-86Y on positive samples analyses in London using standardised methods
Case-control studies 250 cases+controls in each site Molecular marker survey sites
Methods DNA extraction using robotic platform Pfcrt genotyping using real-time PCR using Hydrolysis probes CVMNK, CVIET, SVMNT Direct sequencing Pfmdr1 (86 and 184) and 1246 Dhfr ( 51, 59 and 108) Dhps (431, 436, 437, 540,581 and 613)
Samples Total samples 30268 Extracted 15,337 Tested 15,337 3118 (20.3%) Positive Sequenced 2324
Samples by country Country Nigeria Guinea Niger Chad Gambia Burkina Faso 4560 Mali 4009 3977 4470 4392 4460 Total samples 4400 Extracted 1440 2880 2880 2880 1728 2304 2880 Tested 960 2880 2880 2880 1728 2304 2880 110 61 627 (21.8%) 813 (28.2%) 713 (24.8%) 118 (6.8%) 768 (26.7%) Positive (11.5%) (2.60%) 0 576 Sequenced 480 713 96 0 480
Prevalence of Pfcrt in Sub-Saharan Africa NIGER 100% CVMNK CVMNK/CVIET (n=423) Mix 80% Wildtype Mutant 100% 60% 80% 40% 60% 20% 40% 0% 20% Nigeria (n=713) Niger (n= 813) Burkina Faso (n=86) Mali (n=768) Guinea (n=627) Chad (n=118) Gambia (n=19) 0% 4 samples (0.14%), all from Niger, carried pfmdr1_YY but only one had CVMNK/CVIET
Baseline Prevalence of dhfr Mutations Mali Niger Nigeria Guinea Chad Wildtype Mix Mutant Wildtype Mix Mutant Wildtype Mix Mutant Wildtype Mix Mutant Wildtype Mix Mutant 100% 100% 100% 100% 100% 80% 80% 80% 80% 80% 60% 60% 60% 60% 60% 40% 40% 40% 40% 40% 20% 20% 20% 20% 20% 0% 0% 0% 0% 0%
Baseline Prevalence of dhps Mutations Nigeria Guinea Niger Chad Mali Wildtype Mix Mutant Wildtype Mix Mutant Wildtype Mix Mutant Wildtype Mix Mutant Wildtype Mix Mutant 100% 100% 100% 100% 100% 80% 80% 80% 80% 80% 60% 60% 60% 60% 60% 40% 40% 40% 40% 40% 20% 20% 20% 20% 20% 0% 0% 0% 0% 0% dhps-431 dhps-436 dhsp-437 dhsp-540 dhsp-581 dhsp-613 dhsp-613 dhps-431 dhps-436 dhsp-437 dhsp-540 dhsp-581 dhsp-581 dhps-431 dhps-436 dhsp-437 dhsp-540 dhsp-613 dhps-431 dhps-436 dhsp-437 dhsp-540 dhsp-581 dhsp-613 dhps-436 dhps-431 dhsp-437 dhsp-540 dhsp-581 dhsp-613
Example: Baseline Prevalence of Molecular Markers in Niger Example: Baseline Prevalence of Molecular Markers in Niger n= 412 (n=423) Mutant n= 444 CVMNK CVMNK/CVIET CVIET n= 376 (n=444) (n=412) 100% 100% 100% Mutant Wildtype Mix 100% 100% 100% 100% 80% 80% 80% 80% 80% 80% 80% 60% 60% 60% 60% 60% 60% 60% 40% 40% 40% 40% 40% 40% 40% 20% 20% 20% 20% 20% 20% 20% 0% 0% 0% 0% 0% 0% 0% dhfr-108 dhfr-51 dhfr-59 Pfcrt (n=480) Key findings: pfmdr1_YY (1%) were observed. (1%) were observed. Low frequency of Low frequency of pfcrt_cviet Low frequency of quadruple mutation (53%) were found. Low frequency of quadruple mutation (53%) were found. Low frequency (0.2 %) of mutations associated with SP ( Low frequency (0.2 %) of mutations associated with SP (triple_ but none of these carried the AQ resistance ( but none of these carried the AQ resistance (pfcrt pfcrt_cviet (11%) and (11%) and pfmdr1_YY triple_dhfr pfmdr1_YY) haplotypes. _YY) haplotypes. dhfr + + double_ double_dhps dhps) were found ) were found pfcrt_civet _civet + + pfmdr1
Summary Large scale survey in 7 countries before scale-up of SMC, showed low frequencies of mutations associated with SP resistance, and no samples with AQ resistant genotypes Prevalence of AQ markers reflects the drug combinations most used for first line malaria treatment in recent years The results are consistent with the high clinical efficacy observed in case control studies in Gambia, Mali and Senegal Repeat surveys in the same locations using the same sampling methods will be done at the end of the 2017 transmission season, to assess effects after 2 years of SMC at scale
Timings, Timings, intrepretation intrepretation, and longer longer- -term monitoring term monitoring , and Timings: mid 2016 results from baseline available mid 2018 results from post SMC survey available Evidence for loss of efficacy will be if: Increased frequency of markers Reduced efficacy or shortened duration of efficacy from case-control studies Reduced impact in sentinel surveillance Longer-term monitoring: Regional coordination, Methods standardisation, Finance
Jean-Pierre Gami Hamit Kessely BOURKOU Kadidja Gamougam Jean Bosco Ouedraogo Issaka Zongo Ogboi Sonny Johnbull Tony Eloike Ceesay Serign Jawo Kalifa Bojang Jane Achan Maman Laminou Ibrahim Abdoulaye Djimde Alassane Dicko Issaka Sagara Aliou Traore Kovana Marcel Loua Fassou Rene Abdoulaye Diallo Jean Louis Ndiaye Funder Corinne Merle Partners Colin Sutherland Julian Muwanguzi Johanna Nader Leslie Choi Inke Lubis Ryan Henrici Paul Milligan Paul Snell Matthew Cairns
