The role of DNA methylation in stratifying and understanding paediatric nephrotic syndrome - a combined bioinformatics and CRISPR-cas9 approach

肾病综合征：肾病综合征（NS）是一种以肾脏向尿液中泄漏大量蛋白质、明显的液体潴留和血液中蛋白质水平低为特征的疾病。患有NS的儿童可能发展为肾衰竭，需要终生治疗；因此，这种情况对他们的生活产生了巨大的影响。我们对神经性肾病的了解正在增加，我们现在认识到它不是一种单一的疾病，这就解释了为什么患有神经性肾病的人对同样的治疗会表现出明显不同的反应，为什么有些人在肾移植后会复发，而另一些人则不会。研究结果表明，NS由4种情况（亚组）组成，每个亚组的疾病可能由不同的机制驱动。遗传学的最新进展已经确定，在一个亚群中，对肾脏功能重要的基因的异常DNA序列是NS的原因。然而，在其余3个亚组中，NS的原因尚不清楚，没有临床有用的方法来确定患者属于哪个亚组。DNA甲基化：DNA甲基化（DNAm）是人体开关基因的分子机制之一。一个人的dna特征可能会随着他们的行为和环境而改变。因此，dna可能在疾病发展中起重要作用。脱氧核糖核酸谱在区分不同的疾病亚群方面显示出巨大的希望，例如，脱氧核糖核酸谱可用于准确分类患有不同类型脑肿瘤的患者。我研究了105名NS患者的血液dna谱，以探索这种机制在NS中是否重要。我很着迷地发现，4个NS亚组的人有不同的dna模式；此外，这些差异还指向了一些特定的基因，这些基因可能在神经症中起重要作用，但此前尚未被研究过。我将通过研究280名NS患者的dna图谱和遗传数据，并使用尖端的计算机科学和实验室技术，在这些发现的基础上进一步研究。我研究的目的和重要性：我的工作旨在通过使用他们的血液dna谱将NS患者分为4个NS亚组。血液测试可以确定患者属于哪个亚组，这是个性化NS治疗的第一步；它将允许患有NS的儿童避免无效和潜在危险的药物治疗方案，并专注于有益的治疗。它还可以用来预测哪些患者在肾移植后可能会发生NS，哪些不会。通过研究NS患者的分子图谱，我也将对每个亚组的单独疾病途径有新的认识，这可能会导致新的靶向NS治疗。我的研究分为三个阶段：使用血液dna谱来分离4个NS亚组。我将使用复杂的机器学习技术来确定血液dna模式是否可以一致准确地将患者分为4个亚组。2. 检查dna的差异是否可能导致NS。我将比较4个NS亚组的人的血液dna谱。通过分析dna档案和遗传数据，我将梳理出哪些dna差异更有可能导致NS；这对于确定不同dna的哪些特定位点最有可能成为治疗目标至关重要。在血液细胞系中以有针对性的方式改变dna。我将在第2阶段确定的5个最有希望的DNAm位点改变血细胞中的DNAm，并研究这对基因调控和蛋白质产生的影响。为了做到这一点，我将学习高度专业化的实验室技术，利用基因编辑技术。最终，这项工作是朝着创造针对DNAm的新NS治疗迈出的第一步。

Nephrotic syndrome: Nephrotic syndrome (NS) is a condition characterised by the kidneys leaking huge amounts of protein into the urine, significant fluid retention and low protein levels in the blood. Children who suffer from NS can develop kidney failure and require lifelong treatment; therefore, this condition has a drastic impact on their lives. Our knowledge of NS is increasing and we now recognise that it is not one single disease, which explains why people with NS can exhibit markedly different responses to the same treatment and why some people's NS will return after they have had a kidney transplant, but for others it will not. Findings from research studies suggest that NS consists of 4 conditions (subgroups) and that the disease may be driven by a different mechanism in each subgroup. Recent advances in genetics have identified that abnormal DNA sequences in genes which are important for kidney function are the cause of NS in one of the subgroups. However, the causes of NS in the 3 remaining subgroups are unknown and there is no clinically useful method to identify which subgroup a patient belongs to.DNA methylation: DNA methylation (DNAm) is one of the body's molecular mechanisms for switching genes on and off. A person's DNAm profile can change throughout their lifetime in response to their behaviour and their environment. Therefore, DNAm may play an important role in disease development. DNAm profiles have shown great promise in distinguishing between different disease subgroups, for example, DNAm profiles can be used to accurately classify patients with different types of brain tumours. I studied blood DNAm profiles from 105 people with NS to explore whether this mechanism may be important in NS. I was fascinated to find that people in the 4 NS subgroups had different DNAm patterns; also, the differences pointed to specific genes which could be important in NS but have not previously been examined. I will build on these findings by studying DNAm profiles and genetic data from 280 NS patients and by using cutting-edge computer science and laboratory techniques. The aim and importance of my research: My work aims to classify NS patients into the 4 NS subgroups by using their blood DNAm profiles. A blood test that can identify which subgroup a patient belongs to is the first step towards personalised NS treatment; it would allow children with NS to avoid futile and potentially dangerous medication regimes and focus on beneficial treatments. It could also be used to predict which patients may develop NS after kidney transplantation and which would not. By studying the molecular profiles of people with NS, I will also gain a new understanding of the separate disease pathways of each subgroup, which could lead to novel targeted NS treatments. There are 3 stages to my research:1. Use blood DNAm profiles to segregate the 4 NS subgroups.I will use sophisticated machine learning techniques to determine whether blood DNAm patterns can consistently and accurately segregate patients into the 4 subgroups. 2. Examine whether differences in DNAm are likely to cause NS.I will compare blood DNAm profiles between people in the 4 NS subgroups. By analysing DNAm profiles alongside genetic data I will tease out which DNAm differences are more likely to be causing NS; this is crucial for prioritising which specific sites of differing DNAm have the most potential to become treatment targets.3. Alter DNAm in a targeted manner in blood cell lines.I will alter DNAm in blood cells at the 5 most promising DNAm sites identified in stage 2 and study the effect that this has on gene regulation and protein production. To do this, I will learn highly specialised laboratory techniques which utilise gene editing technology. Ultimately, this work is the first step towards creating new NS treatments which target DNAm.