Duarte Igor, Hoffmann Mauricio Scopel, Salum Giovanni A, Leffa Douglas Teixeira, Belangero Sintia, Santoro Marcos, Ota Vanessa Kiyomi, Ito Lucas Toshio, Pan Pedro M, Farhat Luis C, Murray Aja Louise, Miguel Euripedes C, Kieling Christian, Rohde Luis Augusto, Caye Arthur
Graduate Program in Psychiatry and Behavioral Sciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil.
Attention-Deficit/Hyperactivity Disorders Program (ProDAH), Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil.
Eur Child Adolesc Psychiatry. 2025 Jul;34(7):2107-2117. doi: 10.1007/s00787-024-02622-4. Epub 2024 Dec 3.
Translation of biomarkers to clinical practice is hindered by the significant overlap in neurobiological measures between ADHD cases and controls. A risk-informed design can enhance the utility and validation of ADHD biomarkers by highlighting differences between individuals with ADHD and those without at differential risk. Participants were 2511 children and adolescents (aged 6 to 14 years) from the Brazilian High Risk Cohort for Mental Conditions. We calculated risk for ADHD among unaffected individuals using a multivariable clinical and sociodemographic risk model. We compared measures of three proposed ADHD biomarkers (polygenic scores, subcortical volumes, and executive function) between participants with vs. without ADHD, and ADHD vs. without ADHD with a high- vs. low-risk loading for ADHD. Compared to the unaffected group, children and adolescents with ADHD had higher ADHD polygenic scores (cohen's d = 0.17), smaller subcortical volumes (d = - 0.25), and poorer executive function (d = - 0.22). Separating the unaffected group into low- and high-risk subgroups revealed more pronounced differences (Cohen's d = 0.20 to 0.60) and nearly doubled the overlap-free area for these three neurobiological measures between the low-risk group and the other two groups. Upon adjustment for the number of ADHD symptoms, simple ADHD vs. without ADHD differences vanished, while the risk-informed analyses remained significant. Here, we demonstrate that a risk-based design increases effect sizes when comparing candidate biomarkers for ADHD. Our study provides a model that may hold promise for evaluating similar contrasts in other mental disorders and samples.
注意力缺陷多动障碍（ADHD）病例与对照在神经生物学测量上存在显著重叠，这阻碍了生物标志物向临床实践的转化。基于风险的设计可以通过突出ADHD患者与无ADHD但处于不同风险的个体之间的差异，提高ADHD生物标志物的实用性和验证性。参与者为来自巴西精神疾病高危队列的2511名儿童和青少年（年龄在6至14岁之间）。我们使用多变量临床和社会人口统计学风险模型计算未受影响个体患ADHD的风险。我们比较了三组人群中三种ADHD生物标志物（多基因评分、皮质下体积和执行功能）的测量结果，这三组人群分别为：患有ADHD与未患有ADHD的参与者，以及ADHD高风险与低风险负荷的患有ADHD与未患有ADHD的参与者。与未受影响组相比，患有ADHD的儿童和青少年具有更高的ADHD多基因评分（科恩d值 = 0.17）、更小的皮质下体积（d值 = -0.25）以及更差的执行功能（d值 = -0.22）。将未受影响组分为低风险和高风险亚组后，差异更为明显（科恩d值 = 0.20至0.60），并且这三种神经生物学测量在低风险组与其他两组之间的无重叠区域几乎增加了一倍。在对ADHD症状数量进行调整后，简单的ADHD与未患ADHD之间的差异消失，而基于风险的分析仍然显著。在此，我们证明基于风险的设计在比较ADHD候选生物标志物时会增加效应量。我们的研究提供了一个模型，有望用于评估其他精神障碍和样本中的类似对比。
