Childhood tuberculosis: Integrating tools for improved diagnosis and vaccines

结核病仍然在世界上许多国家造成严重残疾和死亡，包括每年50万儿童死亡。儿童结核病的诊断更加困难，因为它通常不能通过“黄金标准”方法来确认，这意味着在患者体内(通常是在他们的痰中)显示出结核杆菌的存在。这在儿童中是不可能的，因为他们的细菌更少，经常不会咳出痰来，而且仍然会生病。他们经常得不到及时的治疗，或者根本不接受治疗。因此，除了寻找结核杆菌外，我们还使用其他更间接的工具进行诊断，包括观察社区中的结核病病例，以及通过皮肤测试证明宿主的免疫系统已接触结核病(患者)。现在有一些新技术可以应用于患者的血液样本，以查看他们的免疫系统是否表达了结核病的特征“特征”。然而，这些药物还没有用于儿童。结核病通常发生在家庭中，这是儿童特别可能从受感染的成年人那里感染结核病的地方。但并不是每个人都会患上咳嗽“指示病例”，也就是患有活动性肺结核的咳嗽患者。这很可能是许多因素造成的，比如有问题的生物体、家庭的状况以及个别儿童的免疫系统的反应。我们对结核病的传播、敏感性以及需要什么样的免疫力来抵御结核病细菌的理解存在很大差距。这就是为什么我们到目前为止未能研制出比目前的卡介苗更好的疫苗，卡介苗不是完全具有保护作用的。如果我们了解易感性和保护的机制，这将对任何新疫苗的试验非常有用，而且对于诊断也是非常有用的，因为我们可以寻找与结核病和保护相关的特定标志物。这种标记物也可以用于疫苗或治疗试验，而不是像目前的方法那样，纯粹依靠细菌学确认的病例。这种方法非常昂贵，因为它需要非常大量的儿童参与疫苗或治疗试验，因为他们中的大多数永远不会出现在细菌确认的情况下，但却会感染我们认为是结核病的疾病。在我们的项目中，我们将在微生物学和免疫学实验室使用新方法来开发和测试新方法，并聚集了一支强大的内部和外部专家团队，能够使用所有最先进的可用方法。特别是，我们希望评估一些新技术，以根据结核病在人体内留下的“签名”来诊断结核病，并使用统计学方法将构成儿童结核病诊断的拼图的各个部分组合在一起。我们还将研究在家庭中接触杆菌后感染和未感染结核病的儿童，因为没有感染疾病或感染的群体可能掌握着真正预防结核病的关键。这些知识对于制造一种基本上可以模仿这种保护机制的改进疫苗将非常重要。借助对所有有助于结核病诊断的因素进行更先进的统计分析，我们希望提出与黄金标准一样好或几乎一样好的诊断算法。我们希望在仍有大量结核病的冈比亚开展这一项目。多亏了冈比亚的医疗资源中心单位，我们受益于实验室和现场的所有工具，以收集样本和数据，对每个病例进行非常全面的评估。我们这个项目的长期目标是使研究界能够开发一种更好的儿童结核病诊断方法，并了解我们应该如何设计理想的结核病疫苗。

Tuberculosis still causes significant disability and death in many countries in the world, including half a million deaths in children each year. The diagnosis of TB is more difficult in children, as often it cannot be confirmed by "gold standard" methodology, which means showing presence of the TB bacilli in a patient, usually in their sputum. This is rarely possible in children, since they have fewer bacteria, often don't cough up sputum and still get very sick. They often don't receive treatment in time or not at all. Apart from looking for the TB bacilli, we hence use other more indirect tools to make a diagnosis, including observations of TB cases in the community and evidence that the host's immune system has been exposed to TB (patient) by doing a skin test. There are new technologies which can now be applied to blood samples of patients to see if their immune system expresses a characteristic "signature" of TB. However, these have not been used in children yet.TB often occurs in households, which is where children are particularly likely to catch it from an infected adult. But not everyone gets it when exposed to a coughing "index case", which is the coughing person with active TB. It is likely that many factors like the organism in question, the conditions of the household and also the responses of the immune system of the individual child play a role. We have a large gap in our understanding of the transmission, susceptibility and what kind of immunity is needed to fend off the TB bacteria. This is why we have so far failed to make a better vaccine than the current vaccine, BCG, which is not fully protective. If we understand the mechanisms that underlie susceptibility and protection, this would be very useful for any trials of new vaccines, but also for the diagnosis, as we could look for specific markers associated with TB disease and protection. Such markers could also be used in vaccine or treatment trials, instead of purely relying on the bacteriologically confirmed cases, which is the current approach. This approach is very costly since it needs a very large number of children to participate in vaccine or treatment trials, as most of them will never show up with confirmation by bacteria and yet get sick with what we think is TB.In our project, we will develop and test novel approaches by using new methods in the microbiology and immunology laboratory and have brought together a strong team of internal and external experts to be able to use all the state-of-the art available methodology.In particular, we want to evaluate some of the new technologies to diagnose TB on the "signature" it leaves in the body and to use a statistical approach to bring together the individual pieces of the jigsaw that makes up TB diagnosis in children. We will also study children who do and do not get TB after exposure to the bacillus in their household, as the group who does not contract the disease or infection might hold the key to what is really protective against TB. This knowledge will be very important for making an improved vaccine, which can essentially mimic such protective mechanisms. With the help of more advanced statistical analysis of all the factors that contribute to a TB diagnosis we would like to come up with algorithms for the diagnosis that are just or nearly as good as the gold standard. We wish to conduct this project in the Gambia, where there is still a lot of TB. Thanks to the MRC Unit in The Gambia, we benefit from all the tools in the lab and field to collect samples and data for a very comprehensive assessment of every case. Our long-term goal with this project is to enable the research community to develop a better diagnostic approach to childhood TB and understand how we should design the ideal vaccine against TB.