Abstract：
BACKGROUND: Growth associated protein-43 (GAP-43) and neurofilaments light (NFL) are biomarkers of synaptic and axonal injury, and are associated with cognitive decline in Alzheimer\'s disease (AD) contiuum. We investigated whether Polygenic Hazard Score (PHS) is associated with specific biomarkers and cognitive measures, and if it can predict the relationship between GAP-43, NFL, and cognitive decline in AD.
METHODS: We enrolled 646 subjects: 93 with AD, 350 with mild cognitive impairment (MCI), and 203 cognitively normal controls. Variables included GAP-43, plasma NFL, and PHS. A PHS of 0.21 or higher was considered high risk while a PHS below this threshold was considered low risk. A subsample of 190 patients with MCI with four years of follow-up cognitive assessments were selected for longitudinal analysis . We assessed the association of the PHS with AD biomarkers and cognitive measures, as well as the predictive power of PHS on cognitive decline and the conversion of MCI to AD.
RESULTS: PHS showed high diagnostic accuracy in distinguishing AD, MCI, and controls. At each follow-up point, high risk MCI patients showed higher level of cognitive impairment compared to the low risk group. GAP-43 correlated with all follow-up cognitive tests in high risk MCI patients which was not detected in low risk MCI patients. Moreover, high risk MCI patients progressed to dementia more rapidly compared to low risk patients.
CONCLUSIONS: PHS can predict cognitive decline and impacts the relationship between neurodegenerative biomarkers and cognitive impairment in AD contiuum. Categorizing patients based on PHS can improve the prediction of cognitive outcomes and disease progression.
METHODS: We enrolled 646 subjects: 93 with AD, 350 with mild cognitive impairment (MCI), and 203 cognitively normal controls. Variables included GAP-43, plasma NFL, and PHS. A PHS of 0.21 or higher was considered high risk while a PHS below this threshold was considered low risk. A subsample of 190 patients with MCI with four years of follow-up cognitive assessments were selected for longitudinal analysis . We assessed the association of the PHS with AD biomarkers and cognitive measures, as well as the predictive power of PHS on cognitive decline and the conversion of MCI to AD.
RESULTS: PHS showed high diagnostic accuracy in distinguishing AD, MCI, and controls. At each follow-up point, high risk MCI patients showed higher level of cognitive impairment compared to the low risk group. GAP-43 correlated with all follow-up cognitive tests in high risk MCI patients which was not detected in low risk MCI patients. Moreover, high risk MCI patients progressed to dementia more rapidly compared to low risk patients.
CONCLUSIONS: PHS can predict cognitive decline and impacts the relationship between neurodegenerative biomarkers and cognitive impairment in AD contiuum. Categorizing patients based on PHS can improve the prediction of cognitive outcomes and disease progression.
摘要：
背景：生长相关蛋白-43（GAP-43）和神经丝光（NFL）是突触和轴突损伤的生物标志物，并与阿尔茨海默病（AD）的认知能力下降有关。我们调查了多基因危险评分(PHS)是否与特定的生物标志物和认知指标相关。如果它能预测GAP-43，NFL，和AD的认知能力下降。
方法：我们登记了646名受试者：93名患有AD，350患有轻度认知障碍（MCI），和203个认知正常对照。变量包括GAP-43，等离子NFL，和PHS。0.21或更高的PHS被认为是高风险，而低于该阈值的PHS被认为是低风险。选择了190例MCI患者的子样本，并进行了四年的随访认知评估，以进行纵向分析。我们评估了PHS与AD生物标志物和认知测量的关联，以及PHS对认知能力下降和MCI转化为AD的预测能力。
结果：PHS在区分AD方面显示出较高的诊断准确性，MCI和控件。在每个随访点，与低危组相比,高危MCI患者的认知障碍水平更高.GAP-43与高危MCI患者的所有后续认知测试相关，而在低危MCI患者中未检测到。此外，与低风险患者相比,高风险MCI患者进展为痴呆的速度更快.
结论：PHS可以预测认知功能下降，并影响AD中神经退行性生物标志物与认知功能损害之间的关系。基于PHS对患者进行分类可以改善对认知结果和疾病进展的预测。
方法：我们登记了646名受试者：93名患有AD，350患有轻度认知障碍（MCI），和203个认知正常对照。变量包括GAP-43，等离子NFL，和PHS。0.21或更高的PHS被认为是高风险，而低于该阈值的PHS被认为是低风险。选择了190例MCI患者的子样本，并进行了四年的随访认知评估，以进行纵向分析。我们评估了PHS与AD生物标志物和认知测量的关联，以及PHS对认知能力下降和MCI转化为AD的预测能力。
结果：PHS在区分AD方面显示出较高的诊断准确性，MCI和控件。在每个随访点，与低危组相比,高危MCI患者的认知障碍水平更高.GAP-43与高危MCI患者的所有后续认知测试相关，而在低危MCI患者中未检测到。此外，与低风险患者相比,高风险MCI患者进展为痴呆的速度更快.
结论：PHS可以预测认知功能下降，并影响AD中神经退行性生物标志物与认知功能损害之间的关系。基于PHS对患者进行分类可以改善对认知结果和疾病进展的预测。
