Torres Elizabeth B, Varkey Hannah, Vero Joe, London Eric, Phan Ha, Kittler Phyllis, Gordon Anne, Delgado Rafael E, Delgado Christine F, Simpson Elizabeth A
Psychology Department, Rutgers University, 152 Frelinghuysen Rd., Piscataway, NJ 08854, USA.
Rutgers University Center for Cognitive Science, 152 Frelinghuysen Rd., Piscataway, NJ 08854, USA.
PNAS Nexus. 2023 Feb 14;2(2):pgac315. doi: 10.1093/pnasnexus/pgac315. eCollection 2023 Feb.
Neurodevelopmental disorders are on the rise worldwide, with diagnoses that detect derailment from typical milestones by 3 to 4.5 years of age. By then, the circuitry in the brain has already reached some level of maturation that inevitably takes neurodevelopment through a different course. There is a critical need then to develop analytical methods that detect problems much earlier and identify targets for treatment. We integrate data from multiple sources, including neonatal auditory brainstem responses (ABR), clinical criteria detecting autism years later in those neonates, and similar ABR information for young infants and children who also received a diagnosis of autism spectrum disorders, to produce the earliest known digital screening biomarker to flag neurodevelopmental derailment in neonates. This work also defines concrete targets for treatment and offers a new statistical approach to aid in guiding a personalized course of maturation in line with the highly nonlinear, accelerated neurodevelopmental rates of change in early infancy.
神经发育障碍在全球范围内呈上升趋势,其诊断依据是在3至4.5岁时发现偏离典型发育里程碑的情况。到那时,大脑中的神经回路已经达到了一定程度的成熟,这不可避免地使神经发育走上了不同的道路。因此,迫切需要开发能够更早检测出问题并确定治疗靶点的分析方法。我们整合了来自多个来源的数据,包括新生儿听觉脑干反应(ABR)、多年后检测这些新生儿自闭症的临床标准,以及同样被诊断为自闭症谱系障碍的幼儿和儿童的类似ABR信息,以生成已知最早用于标记新生儿神经发育偏离的数字筛查生物标志物。这项工作还确定了具体的治疗靶点,并提供了一种新的统计方法,以帮助根据婴儿早期高度非线性、加速的神经发育变化率,指导个性化的成熟过程。