自闭症谱系障碍（ASD）是一种神经发育障碍，其影响范围广泛，主要涉及行为、沟通和社交技能。ASD 曾被视为一种罕见疾病，20 世纪 70 年代的记录显示其患病率为万分之三至四。目前，据估计全球约有 1% 的人口患有自闭症。这表明在过去几十年中，患病率增加了 20 到 30 倍。
目前的研究正致力于探究这一增长背后的驱动因素，其中可能包括诊断标准的变化、意识与筛查的普及，甚至环境因素。发现与 ASD 相关的生物标志物是辅助诊断的一个关键领域。生物标志物为识别和测量生物学差异提供了一种客观方法，可用于多种诊断目的，并能预测治疗潜力。
虽然 ASD 的诊断方法随着时间的推移不断演变，但《精神疾病诊断与统计手册》第 5 版（DSM-5）中使用的标准仍然主要基于行为，且往往具有主观性。此外，鉴于症状和病情严重程度的差异性，确定有效的治疗方法也是一项挑战（图 2）。
研究人员指出，各种生物标志物在 癌症早期检测 以及 阿尔茨海默病 和帕金森病等神经退行性疾病的识别中发挥着重要作用。他们目前发现，与自闭症相关的生物标志物可用于筛查高风险患者，辅助早期诊断以实现更有效的干预，并将患者分为不同亚组，从而更好地预测对不同药物的反应。这些进展能为临床医生提供关键见解，并为患者提供更好的整体护理。
我们查阅了 CAS 内容合集TM（全球最大的人工标引科学信息库），发现过去十年中有关 ASD 生物标志物的出版物显著增加（见图 3）。
哪些类型的生物标志物可用于识别自闭症？
ASD 生物标志物可分为非分子生物标志物和分子生物标志物。如图 4 所示，分子生物标志物在文献中更为常见（占总文献的 92%），而非分子生物标志物所占比例较小（8%）。非分子生物标志物被认为是主观的，而分子生物标志物则更具客观性和可测量性。
图 3 展示了已识别的自闭症相关生物标志物的文献发表趋势。我们还观察到大量与潜在生物标志物相关的文献，这些标志物尚需通过更全面的研究在未来确认为 ASD 生物标志物。
自闭症的分子生物标志物
Numerous types of molecular ASD biomarkers are being researched. Let’s examine the groupings based on their prominence in the literature, via the CAS Content Collection:
- Genetic biomarkers: ASD appears to have high heritability, and as a result, researchers are investigating many potential genetic biomarkers. Studies have shown that genetic factors can be traced to more than 50% of autism cases, and to date over 400 genes have been reported as associated with ASD phenotypes. We identified leading genes associated with ASD publications in the CAS Content Collection (see Figure 5)
The gene most associated with ASD is the FMR-1 gene (fragile X mental retardation 1 gene), which is connected to Fragile X syndrome (FXS). About 50% of the FXS males and 20% of the FXS females meet the DSM-5 diagnostic criteria for ASD. Single nucleotide polymorphisms (SNPs) in exons 5, 10, and 11 are also shown to be associated with ASD. Some other key genes linked to ASD include PTCHD1, HOX, CHD2, CHD8, FOXP2, SHANK3, OXTR, PTEN, CHD2, and NL3. These genes play various roles in brain development and function, influencing the behavioral, communicative, and cognitive abilities of individuals with ASD.
The complexity of autism genetics suggests there may be multiple pathways contributing to it. This implies not just a simple inheritance pattern but complex interactions between different genes and environmental factors. There is now increasing evidence suggesting that the bulk of genetic risk associated with ASD may be due to SNPs and copy number variants, rather than specific single-gene mutations or other monogenic syndromes. Genetic markers are promising early diagnostic tools and may identify genetic pathways to target pharmacological interventions. Furthermore, SNPs can potentially be used to stratify ASD patients based on symptom severity.
- Immunologic biomarkers: Several meta-analysis studies have identified predictive markers like maternal fetal brain-directed autoantibodies and folate receptor alpha autoantibody. Researchers have also discovered elevated levels of inflammatory markers in ASD individuals like interferon-γ, interleukin-1β, interleukin-6, tumor necrosis factor-α, and chemokines. Nonetheless, it is still not clear whether neuroinflammation is a causative factor of ASD or a downstream effect due to other biological processes, such as oxidative stress.
- Metabolic biomarkers: ASD is associated with many variations in metabolism, but the exact correlations of these metabolic disturbances with pathophysiology of the disorder are not fully understood. However, a number of metabolic markers are emerging as potential diagnostics.
Several large-scale liquid chromatography/mass spectrometry-based metabolomic studies have shown that individuals with ASD have altered purine metabolism, ATP-related purinergic signaling, fatty acid oxidation, and increased physiologic stress molecules like lactate, glycerol, cholesterol, and ceramides. Changes in metabolic pathways related to energy, neurotransmitters, and branched-chain amino acids (BCAA), as well as aminoacyl-tRNA biosynthesis are also shown to be associated with ASD severity. Abnormal activities of the electron transport chain and impaired energy metabolism, owing to dysfunctional mitochondrial metabolism, also contributes to ASD.
Recent efforts in the field are focused on identifying the relationship between metabolic biomarker clusters, their inter-connectivity, and using them in autism sub-grouping. Metabolomic studies are focused on using certain molecules, such as suramin (CAS RN: 145-63-1) or sulforaphane (CAS RN: 4478-93-7), as pharmacological interventions to treat ASD. Metabolomic studies can also help determine therapy approaches in ASD individuals; for example, preliminary evidence suggests that children with low carnitine or low BCAA-associated phenotypes may benefit from carnitine or BCAA supplementation.
- Oxidative stress biomarkers: Several studies have established a correlation between ASD and physiological abnormalities linked to oxidative stress, such as increased concentration of lipid peroxidation products and reduced glutathione reserve capacity in brain tissue. Subsequently, byproducts of lipid peroxidation like malondialdehyde (MDA; CAS RN: 542-78-9), 4-hydroxy-2-nonenal (CAS RN: 75899-68-2), and F2-isoprostane are emerging as potential biomarkers for early diagnosis of ASD.
There is also a possible positive correlation between elevated plasma MDA levels and ASD severity. Another important and dependable emerging ASD biomarker with high sensitivity and repeatability for ASD is the GSH/GSSG redox ratio. These potential biomarkers could be used for early diagnosis and evaluation , as well as assistance in pharmacological or nutritional treatment interventions. By enhancing the functionality of the antioxidant enzyme system, it is possible to lessen the oxidative stress damage experienced by ASD patients, thereby potentially reducing symptom severity.
- Epigenetic biomarkers: Along with genetic components, it is equally important to understand the role of epigenetic regulators in ASD. Studies have indicated an association between differential DNA methylation patterns and ASD-related genes. Another histone acetylome-wide association study has identified a collective acetylome signature in ≥68% of ASD cases in the prefrontal and temporal cortex. Cell-free circulating microRNAs have been associated with levels of ASD behaviors are now being evaluated as diagnostic ASD markers thanks to in-depth profiling.
- Gut microbiome biomarkers: In the past few years, understanding the role of gut microbiota in ASD pathogenesis has become a prominent area of research. Studies have indicated that there is a dysregulation in the composition of gut microbiota in ASD individuals like an increase in Bacteroidetes phylum or Firmicutes phylum or a decrease in Coprococcus and Bifidobacterium genera. Notably, within the Bacteroides family and Lachnospiraceae, the reduced microbial quantities correlate with neurodevelopmental levels and behavioral symptoms like social impairment in patients with ASD.
The activity of the gut microbiota generates various metabolites which play a crucial role in regulating brain function, such as short-chain fatty acids and propionic acid. Furthermore, research has revealed a close relationship between the gut microbiota composition and neurotransmitters like gamma-aminobutyric acid (GABA; CAS RN: 56-12-2), serotonin (CAS RN: 50-67-9), and dopamine (CAS RN: 51-61-6). The imbalance in gut microbiota composition hence has a vital role in pathogenesis of ASD.
Non-molecular biomarkers of autism
While there are fewer non-molecular biomarkers being researched, these measurements can provide a well-rounded examination and assist in ASD diagnosis:
- Neuroimaging biomarkers: There are two types of neuroimaging biomarkers that can help with ASD diagnosis. The first is structural imaging. Multiple longitudinal MRI studies have identified connections between ASD and structural variations in the brain like excessive expansion of cortical surface at 6–12 months or anomalies in Broca’s area and Wernicke’s area. Such studies provide prospective imaging biomarkers for early diagnosis.
The other type of neuroimaging biomarker is functional imaging. Resting-state functional MRI (fMRI) plays a pivotal role in capturing the functional connectivity and activity within the brain in the presence or absence of specific tasks, thereby providing an in-depth insight into the neural mechanisms of ASD. Like structural imaging, functional imaging may also be utilized for early diagnosis.
- Neurophysiological biomarkers: Electroencephalography (EEG) is the most used tool to detect brain activity and analyze neurophysiological conditions. Certain frequencies or patterns and features on EEG readings were shown to be correlated with ASD diagnoses done by clinicians. These studies suggest that EEG measurements can be used to derive certain helpful digital biomarkers which can serve as early diagnosis markers of ASD.
- Eye tracking biomarkers: These refer to a method of identifying indicators of ASD by observing and analyzing individuals’ eye movement patterns while they view, focus, and track visual stimuli. Several studies have indicated different patterns of visual attention in ASD individuals compared to control groups. These differences are also closely correlated with the social impairments in ASD individuals.
临床试验有望在自闭症生物标志物领域取得突破
截至2024年11月，针对自闭症谱系障碍（ASD）生物标志物的观察性试验共有59项，干预性试验共有107项。在干预性试验中，40项处于第一或第二阶段，3项已进入后期阶段：
表1： ASD生物标志物的后期临床试验。数据来源： ClinicalTrials.gov。
临床认可的生物标志物或许很快就能得到更广泛的应用。然而，ASD生物标志物面临的最大挑战在于，由于ASD患者群体的高度异质性，研究结果的可重复性一直难以保证。
为研究确定儿童对照组也存在困难。生物标志物研究的理想对照组应为与ASD队列年龄相同、但患有非ASD相关发育迟缓的儿童。通常，此类研究纳入的对照组为非同胞、发育正常的儿童，这在临床上的相关性往往不足。
克服这些临床研究障碍需要时间和努力，但关于ASD生物标志物的现有数据表明，更好的诊断和治疗方案已指日可待。鉴于ASD诊断率正以令人担忧且尚待完全解读的速度增长，研究人员和临床医生必须找到更有效的ASD诊断方法，并确定适合不同患者的治疗方案。生物标志物的可量化特性或将为临床医生提供实现这一目标的关键工具。
