ICMR-National Institute of Malaria Research, New Delhi, India.
WorldWide Antimalarial Resistance Network, Oxford, United Kingdom.
Am J Trop Med Hyg. 2024 Apr 2;110(5):910-920. doi: 10.4269/ajtmh.23-0631. Print 2024 May 1.
Surveillance for genetic markers of resistance can provide valuable information on the likely efficacy of antimalarials but needs to be targeted to ensure optimal use of resources. We conducted a systematic search and review of publications in seven databases to compile resistance marker data from studies in India. The sample collection from the studies identified from this search was conducted between 1994 and 2020, and these studies were published between 1994 and 2022. In all, Plasmodium falciparum Kelch13 (PfK13), P. falciparum dihydropteroate synthase, and P. falciparum dihydrofolate reductase (PfDHPS) genotype data from 2,953, 4,148, and 4,222 blood samples from patients with laboratory-confirmed malaria, respectively, were extracted from these publications and uploaded onto the WorldWide Antimalarial Resistance Network molecular surveyors. These data were fed into hierarchical geostatistical models to produce maps with a predicted prevalence of the PfK13 and PfDHPS markers, and of the associated uncertainty. Zones with a predicted PfDHPS 540E prevalence of >15% were identified in central, eastern, and northeastern India. The predicted prevalence of PfK13 mutants was nonzero at only a few locations, but were within or adjacent to the zones with >15% prevalence of PfDHPS 540E. There may be a greater probability of artesunate-sulfadoxine-pyrimethamine failures in these regions, but these predictions need confirmation. This work can be applied in India and elsewhere to help identify the treatments most likely to be effective for malaria elimination.
对耐药性遗传标志物进行监测可以为抗疟药物的疗效提供有价值的信息,但需要有针对性,以确保资源的最佳利用。我们在七个数据库中进行了系统检索和综述,以编译来自印度研究的耐药标志物数据。从这次搜索中确定的研究样本采集工作于 1994 年至 2020 年进行,这些研究于 1994 年至 2022 年发表。总共从 2953 份、4148 份和 4222 份确诊为疟疾的患者血液样本中提取了恶性疟原虫 Kelch13(PfK13)、恶性疟原虫二氢叶酸合成酶和恶性疟原虫二氢叶酸还原酶(PfDHPS)基因型数据,并将这些数据上传到世界抗疟耐药网络分子监测员。将这些数据输入分层地质统计学模型,生成了 PfK13 和 PfDHPS 标志物以及相关不确定性的预测流行率地图。在印度中部、东部和东北部地区确定了 PfDHPS 540E 预测流行率>15%的区域。PfK13 突变体的预测流行率仅在少数几个地点为非零值,但在 PfDHPS 540E 流行率>15%的区域内或附近。在这些地区,青蒿琥酯-磺胺多辛-乙胺嘧啶失败的可能性更大,但这些预测需要确认。这项工作可以在印度和其他地方应用,以帮助确定最有可能有效用于消除疟疾的治疗方法。