Genetics of ADHD

Team: 19

School: Santa Fe Preparatory Sch

Area of Science: Biochemistry

Interim: Problem Definition: Mental health, a widespread issue, warrants more research and regard. Among the vast array of mental disorders, Attention Deficit Hyperactivity Disorder (ADHD), disproportionately affects youth our age, with around 2.8% of adults and 9.4% of youth in the US diagnosed(ADDitude). The symptoms of ADHD include hyperactivity, impulsive behavior, and difficulty paying attention, affecting both learning and daily life. Additionally, many studies demonstrate strong correlations between genetics and ADHD, and likely ADHD is an inherited disorder (“Attention deficit hyperactivity disorder (ADHD) - Causes.”). Many issues have arisen within the accuracy of diagnosis of ADHD and the efficiency of analyzing gene sequences without technology that would identify variations in the genomes correlating with ADHD. Several studies have suggested that, “​​Doctors can misdiagnose ADHD in children due to their age”(ADHD Misdiagnosis). Others have highlighted the similarities of symptoms between bipolar disorder and ADHD, revealing yet another shortcoming in diagnosis. Thus our project, through genetic analysis, has found systematic solutions to these problems. Through gene sequencing technology our program will analyze genomic variations for ADHD and aid in diagnosis.


Solution: We plan on analyzing areas of the genome, of certain chromosomes, to find these variations by using genomes from genome databases. Our program would use an Artificial Neural Network or ANN to analyze data from the OMIM and Blast databases and build a predictive model that helps diagnose patients with ADHD (Blast). The ANN would employ an architecture that uses a certain set of genes, that we have established a strong correlation to ADHD and use the weights of these genes to help develop our model to become a working technology that accurately predicts ADHD in patients. In our novel approach that helps identify ADHD genetics from an analytical standpoint rather than a symptom-based one (as has been the most prevalent mode of diagnosis), our model will offer new insights into ADHD identification.

Progress to Date: We have worked towards completing research on the most widely affected chromosomes and sections of the genome that are known to be related to ADHD, as well as narrowing down our research to a specific type of ADHD. Our findings have demonstrated that many of the genetic markers for ADHD are on various chromosomes (Faraone). We have found evidence of ADHD on chromosomes 4, 7, 10, 11, 12, and 18 (Kniffin). Some specific locus that we have found are DUSP6, FOXP2, and SORCS3 (Demontis).

Expected Results: Once we are able to find data to robustly support the main few variations that correlate with ADHD, the process of writing a program to identify variations will begin. We plan on executing this by writing a program that will incorporate data from various ADHD patients and genetic variations corresponding to the disorder to help craft a neural network model that will provide accurate diagnoses. Understanding where these variations are most prevalent will help us not only isolate genetic variations, but focus on a specific type of ADHD. These focused areas will help us narrow down the variations which we must look for in the genome within the sets of genomes in the databases OMIM and Blast.


Team Members: Greta Swanson, Nandita Ganesan, Camila Carreon, Luke Rand

Sponsoring Teacher: Jocelyne Comstock

Mentor: Juergen Eckert

Works Cited
“ADHD Misdiagnosis: Why Might It Happen?” Medical News Today, MediLexicon
International, https://www.medicalnewstoday.com/articles/325595#:~:text=Doctors%20can%20misdiagnose%2n.d.HD%20in,approximate%2020%25%20difference%20in%20age.

“Attention deficit hyperactivity disorder (ADHD) - Causes.” NHS, https://www.nhs.uk/conditions/attention-deficit-hyperactivity-disorder-adhd/causes/. Accessed 9 January 2023.
“Blast: Basic Local Alignment Search Tool.” National Center for Biotechnology Information, U.S. National Library of Medicine, https://blast.ncbi.nlm.nih.gov/Blast.cgi.

Demontis, Ditte et al. “Discovery of the first genome-wide significant risk loci for attention deficit/hyperactivity disorder.” Nature genetics vol. 51,1 (2019): 63-75. doi:10.1038/s41588-018-0269-7

Editors, ADDitude. “ADHD Statistics: New Add Facts and Research.” ADDitude, ADDitude, 13
July 2022, https://www.additudemag.com/statistics-of-adhd/.

Faraone, Stephen, et al. “The First Robust Genetic Markers for ADHD Are Reported.” Brain & Behavior Research Foundation |, 11 July 2019, https://www.bbrfoundation.org/content/first-robust-genetic-markers-adhd-are-reported. Accessed 9 January 2023.

Kniffin, Cassandra, and Victor McKusick. “Entry - #143465 - ATTENTION DEFICIT-HYPERACTIVITY DISORDER; ADHD.” OMIM, 26 February 2013, https://www.omim.org/entry/143465#phenotypeMap. Accessed 9 January 2023.

Team Members:

  Greta Swanson
  Luke Rand
  Camila Carreon
  Nandita Ganesan

Sponsoring Teacher: Jocelyne Comstock

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