III: Medium: Private Identification of Relatives and Private GWAS: First Steps in the New Field of CryptoGenomics

人类遗传学领域在过去10年中经历了一场革命，出现了高通量基因组技术，可以以低成本测量人类变异。 这些技术的旗舰应用是全基因组关联研究（GWAS），其中从数十万个体收集遗传变异信息，其中一部分患有特定疾病，另一部分是健康个体。 遗传变异与疾病状态之间的相关性的鉴定已经导致鉴定出涉及数十种人类疾病的数百个新基因。 这些技术的所有应用，包括GWAS，都需要个人“分享”他们的基因数据。 在今天典型的GWAS中，成千上万的个人必须同意收集他们的遗传信息并将其纳入数据库，该数据库还包含有关其疾病状态的信息。 不幸的是，一个人的基因数据是非常敏感的，因为它被认为是关于一个人的医疗信息。 在这项提案中，该团队通过利用密码学的最新突破，解决了隐私和个人基因组技术应用之间的自然紧张关系。 他们提出了一种新的技术方法来保持一个人的遗传数据的私密性，但充分利用遗传信息-以保护隐私的方式，通过利用最近在广泛称为安全计算的领域开发的几种技术，这些技术解决了允许一组个人计算一些依赖于他们所有输入的输出的问题，而不必向彼此透露它们各自的输入。 该方案的核心是将安全计算应用于个人基因组学中的两个具体问题：第一个问题是从遗传变异信息中识别亲属，同时保护遗传物质的隐私。第二，是在不牺牲个体患者的遗传隐私的情况下识别致病变异。本提案中提出的技术的发展将对个人基因组学和遗传学领域产生深远的影响，原因有几个。 首先，隐私担忧的缓解将降低参与个人基因组学的主要障碍，这可能会增加公众对遗传和基因组技术最新进展的利用。 这种利用率的提高将加速这些技术的医疗效益。 其次，目前的想法是，在个人基因组学中保护隐私是不可能的，这个项目的结果将使该领域的许多人感到惊讶，从而导致对如何处理遗传研究中的隐私的重新思考。 最后，该研究方向可能会为密码学研究界带来新的问题和研究方向，并促进遗传学研究人员、密码学家和数学家之间的新合作，该项目还有助于培养下一代跨学科科学家。 研究人员都教授遗传学和密码学的高级本科课程，并且很可能本提案中开发的主题将包括在课程的课程中。 此外，参与这项建议的研究生将获得遗传学和计算机科学理论的跨学科培训。

The field of human genetics has undergone a revolution in the past 10 years with the advent of high-throughput genomic technologies which can measure human variation at low cost. The flagship application of these technologies has been the genome-wide association study (GWAS) where genetic variation information is collected from hundreds of thousands of individuals, a portion of which have a specific disease and a portion of which are healthy individuals. Identification of correlation between genetic variants with disease status has led to the identification of hundreds of new genes involved in dozens of human diseases. All applications of these technologies, including GWAS, require individuals to "share" their genetic data. In today's typical GWAS, thousands of individuals must consent to have their genetic information collected and incorporated into a database which also contains information on their disease status. Unfortunately, an individual's genetic data is extremely sensitive as it is considered medical information about an individual. In this proposal, the team addresses the natural tension between privacy and the application of personal genomics technologies by capitalizing on recent breakthroughs in cryptography. They present a novel technological approach to keep one's genetic data private, yet taking full advantage of genetic information - in a privacy-preserving way, by taking advantage of several techniques that have been recently developed in an area broadly referred to as secure computing, which address the problem of allowing a collection of individuals to compute some output that depends on all their inputs, without having to reveal their individual inputs to each other. The core of this proposal focuses on the application of secure computing to two specific problems in personal genomics: The first is the problem of identification of relatives from genetic variation information while preserving privacy of genetic material. The second, is the identification of disease causing variants without sacrificing individual patient's genetic privacy.The development of the techniques presented in this proposal will have a profound impact on personal genomics and the field of genetics in general for several reasons. First, the easing of privacy fears will drop a major barrier to participation in personal genomics likely increasing the utilization of recent advances in genetic and genomic technologies for the public. This increased utilization will accelerate the medical benefits of these technologies. Second, the current thinking is that it is impossible to protect privacy in personal genomics and the results of this project will surprise many in the field, leading to a rethinking of the how to handle privacy in genetic studies. Finally, this research direction will likely lead to new problems and research directions for the cryptography research community and foster new collaborations between genetics researchers, cryptographers and mathematicians.This project also contributes to training the next generation of interdisciplinary scientists. The investigators all teach advanced undergraduate courses in both genetics and cryptography and it is likely that the topics developed in this proposal will be included in the curriculum of the courses. In addition, the graduate students involved in this proposal will obtain interdisciplinary training in both genetics and computer science theory.