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

在过去的10年里，随着高通量基因组技术的出现，人类遗传学领域经历了一场革命，这种技术可以低成本地测量人类变异。这些技术的旗舰应用是全基因组关联研究(Gwas)，其中从数十万人收集遗传变异信息，其中一部分人患有特定疾病，另一部分人是健康人。基因变异与疾病状态之间的相关性的识别导致了与数十种人类疾病有关的数百个新基因的识别。这些技术的所有应用，包括全球气候变化研究，都需要个人“分享”他们的基因数据。在当今典型的全球遗传信息系统中，数以千计的人必须同意收集他们的基因信息，并将其纳入一个数据库，该数据库也包含有关他们疾病状况的信息。不幸的是，个人的基因数据是极其敏感的，因为它被认为是关于个人的医疗信息。在这项提案中，该团队通过利用最近在密码学方面的突破来解决隐私和个人基因组技术应用之间的天然紧张关系。他们提出了一种新的技术方法，使一个人的基因数据保持隐私，同时以保护隐私的方式充分利用遗传信息，方法是利用最近在一个被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依赖于他们所有输入的某些输出的问题，而不必向彼此透露他们单独的输入。这项建议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：第一个问题是在保护遗传物质隐私的同时从基因变异信息中识别亲属的问题。第二，是在不牺牲患者个体遗传隐私的情况下识别引起疾病的变异。这项提议中提出的技术的发展将对个人基因组学和整个遗传学领域产生深远的影响，原因有几个。首先，隐私担忧的缓解将消除参与个人基因组学的一个主要障碍，这可能会增加公众对遗传和基因组技术最新进展的利用。这种更高的利用率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，这个项目的结果将让该领域的许多人感到惊讶，导致人们重新思考如何在基因研究中处理隐私。最后，这一研究方向可能会给密码学研究界带来新的问题和研究方向，促进遗传学研究人员、密码学家和数学家之间的新合作，也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，这项提案中开发的主题很可能会包括在课程的课程中。此外，参与这项提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.