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Last Posted: Mar 19, 2024
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Connecting clinical and genetic heterogeneity in ADHD.
Chloe X Yap et al. Nat Genet 2024 2

From the abstract: "Understanding clinical heterogeneity in attention deficit hyperactivity disorder (ADHD) is important for improving personalized care and long-term outcomes. A recent study exploits the large scale and breadth of phenotyping of the iPSYCH cohort to link clinical heterogeneity to genetic heterogeneity in ADHD. "

Validity of Diagnostic Support Model for Attention Deficit Hyperactivity Disorder: A Machine Learning Approach
KC Chu et al, JPM, October 25, 2023

From the abstract: "An accurate and early diagnosis of attention deficit hyperactivity disorder can improve health outcomes and prevent unnecessary medical expenses. This study developed a diagnostic support model using a machine learning approach to effectively screen individuals for attention deficit hyperactivity disorder. Three models were developed: a logistic regression model, a classification and regression tree (CART), and a neural network. The models were assessed by using a receiver operating characteristic analysis. In total, 74 participants were enrolled into the disorder group, while 21 participants were enrolled in the control group. "

FASDetect as a machine learning-based screening app for FASD in youth with ADHD
L Ehrig et al, NPJ Digital Medicine, July 19, 2023

Fetal alcohol-spectrum disorder (FASD) is underdiagnosed and often misdiagnosed as attention-deficit/hyperactivity disorder (ADHD). Here, we develop a screening tool for FASD in youth with ADHD symptoms. To develop the prediction model, medical record data from a University outpatient unit are assessed including 275 patients aged 0–19 years old with FASD with or without ADHD and 170 patients with ADHD without FASD aged 0–19 years old. We train 6 machine learning models based on 13 selected variables and evaluate their performance.

Evaluation of Birth Weight and Neurodevelopmental Conditions Among Monozygotic and Dizygotic Twins.
Johan Isaksson et al. JAMA Netw Open 2023 6 (6) e2321165

After adjustment for genetic factors, is birth weight associated with neurodevelopmental conditions? In this case-control study of 393 twins in Sweden, the twin with a lower birth weight in monozygotic twin pairs, but not dizygotic pairs, had more autism and attention-deficit/hyperactivity disorder (ADHD) symptoms, lower IQ ratings, and higher odds of having a diagnosis of autism and ADHD compared with their co-twin. These findings suggest that birth weight contributes to neurodevelopmental conditions when adjusting for genetic factors.

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Disclaimer: Articles listed in the Public Health Genomics and Precision Health Knowledge Base are selected by the CDC Office of Public Health Genomics to provide current awareness of the literature and news. Inclusion in the update does not necessarily represent the views of the Centers for Disease Control and Prevention nor does it imply endorsement of the article's methods or findings. CDC and DHHS assume no responsibility for the factual accuracy of the items presented. The selection, omission, or content of items does not imply any endorsement or other position taken by CDC or DHHS. Opinion, findings and conclusions expressed by the original authors of items included in the update, or persons quoted therein, are strictly their own and are in no way meant to represent the opinion or views of CDC or DHHS. References to publications, news sources, and non-CDC Websites are provided solely for informational purposes and do not imply endorsement by CDC or DHHS.

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