Identification and characterization of rare coding variants modulating the rate of disease progression in pre-dementia stages of Alzheimer's disease.

阿尔茨海默病（AD）在痴呆症诊断前几年就开始了，有临床前阶段和轻度认知障碍（MCI）阶段。然而，预测哪些轻度认知障碍患者会发展为痴呆是一个重大挑战，而且疾病进展的生物学决定因素尚不清楚。MCI患者疾病进展的遗传学研究目前尚处于起步阶段。为了改变这种情况，我们在过去几年中招募了欧洲最大的纵向评估MCI病例样本，具有全基因组基因型数据（约9000），其中约4000个dna存储在Ramirez博士的实验室。在初步研究中，我们发现只有两个ad相关基因座与痴呆相关，而多基因风险评分（PRS）无法预测。这就提出了一种可能性，即只有已确定的阿尔茨海默病基因的一个子集与阿尔茨海默病高危期的症状进展有关，而且仍有新的变体有待发现。重要的是，抗阿尔茨海默病韧性的生物学过程可能只有在病理存在的情况下才有效，因此在高危人群中最容易检测到。与此一致，我们可以证明PLCG2中ad相关的罕见编码变体p.P522R降低了MCI患者的认知能力下降率，但在一般人群中没有，并且其对tau病理生物标志物的影响取决于淀粉样蛋白病理的存在。虽然一些资助的项目（包括我们的）专注于常见变异（次要等位基因频率（minor allele frequency， MAF）小于5%）的研究，但很少有团队关注罕见变异（MAF<1%）的研究。然而，逐个生成每个候选变量的数据是一种非常耗时和昂贵的方法。因此，我们在此申请资助，对2500个MCI样本进行全外显子组测序（WES）数据，其中包括广泛的神经心理学和生物标志物数据，包括长达15年的几次随访评估。WES数据将与纵向数据结合使用最先进的方法来分析认知能力下降。我们将首先关注来自AD和GWAS中描述的与恢复力（即智力和教育）相关结构的位点的候选基因，以便更好地了解它们的生物学相关性。同时，我们将优化该方法，将罕见变异的分析扩展到全基因组水平。我们还将构建一个结合本文中发现的罕见变异和来自AD遗传学国际联盟最新GWAS更新的常见变异的PRS。总之，我们的建议将测试现有的候选基因，并确定减缓MCI疾病进展的新基因。我们的研究结果可能会转化为改进的临床预测（精准医学），并使未来干预的目标优先化，特别是与AD的MCI阶段相关。此外，该建议将改进现有的工具来分析纵向表型中的罕见变异。

Alzheimer’s disease (AD) starts years before dementia diagnosis with a preclinical stage and the mild cognitive impairment (MCI) stage. Predicting, however, which MCI patient will progress to dementia is a major challenge and biological determinates of disease progression are poorly understood. Genetic research on disease progression of MCI patients is currently in its infancy. To change this, we have recruited during the last years the largest sample of longitudinally assessed MCI cases in Europe with genome-wide genotype data (~9000), of which ~4000 DNAs are stored at Dr. Ramirez' laboratory. In preliminary work, we showed that only two AD-associated loci were associated with conversion to dementia while a polygenic risk score (PRS) enabled no prediction. This raises the possibility that only a subset of the identified AD loci is related to symptom progression in at-risk-stages of AD and there are still novel variants to discover. Importantly, biological processes underlying resilience against AD may only become effective in the presence of pathology and are therefore best detectable in at-risk populations. In line with this, we could show that the AD-associated rare coding variant p.P522R in PLCG2 reduces the rate of cognitive decline in patients with MCI but not in the general population and that its effect on biomarkers of tau pathology depended on the presence of amyloid pathology. While several funded initiatives (including ours) focus on research on common variants (minor allele frequency (MAF) >5%), few groups have focused their research on rare variants (MAF<1%). However, generating data of each candidate variant one by one is an extremely time consuming and expensive approach. Therefore, we here apply for funding to generate whole exome sequencing (WES) data on 2500 MCI samples with extensive neuropsychological and biomarker data, including several follow-ups assessments over up to 15 years. The WES data will be combined with the longitudinal data using state-of-the-art methods to analyze cognitive decline. We will initially focus on candidate genes derived from loci described in AD and GWAS of constructs related to resilience (i.e. intelligence and education) in order to gain enhanced insight into their biological relevance. In parallel, we will optimize the approach to expand the analysis of rare variants to the genome-wide level. We will also construct a PRS combining rare variants identified herein with common variants derived from the latest GWAS update from the international consortia on AD genetics. In conclusion, our proposal will test existing candidate genes and identify new one that moderates disease progression in MCI. Our findings will likely translate into an improved clinical prediction (precision medicine) and enable prioritization of targets for future interventions specifically relevant to the MCI stage of AD. Furthermore, this proposal will refine existing tools to analyze rare variants in longitudinal phenotypes.