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The Virginia Commonwealth University Center for Biomarker and Precision Medicine Research announced a new to study published in Molecular Psychiatry showing how the combination of artificial intelligence (AI) and genomics can produce DNA biomarkers that predict mental health problems nearly 17 years after exposure to childhood trauma.
Childhood trauma was assessed from events that meet DSM mail-traumatic stress disorder criteria in children and adolescents Psychiatric (CAPA) and the Young Adult Psychiatric Assessment (YAPA) of hundreds of children ages 9 to 13 who participated in the 30-year study initiated by Duke University and the North Carolina Department of Health and Human Services called the Study Great Smoky Mountain (GSMS). Bloodstain samples and clinical data were collected in each wave.
More than 970 blood spot samples from more than 480 participants who provided more than 670 samples before their 21st birthday were used, along with a subset of more than 300 participants who provided a sample in adulthood.
“We predicted adult outcome from DNA methylation,” said the study’s lead author, Edwin van den Oord, PhD, a Dutch psychiatric geneticist, professor and director of the Virginia Commonwealth University Center for Precision Medicine and Biomarker Research. . “We found a wide range of outcomes as adults depression, anxiety, Alcohol abuse, nicotine addictionpoverty, social problems and medical problems”.
Neuropsychiatric diseases and cancer have been linked to changes in DNA methylation. In the human genome there are 28 million sites where van den Oord methylation can occur.
“We know where all the SNPs (single nucleotide polymorphisms) are,” van den Oord said. “We took the human reference genome from the Human Genome Project and searched for CG sites, and then entered all the SNPs.”
Genetics is the branch of biology that studies genes, genetic variation, and heredity in living organisms. DNA, deoxyribonucleic acid, is the hereditary material in humans and most organisms where information is stored as a code consisting of four chemical bases: adenine (A), guanine (G), cytosine (C) and thymine (T).
DNA can be modified by environmental factors, a epigenetic change, which can alter gene expression. DNA methylation, the process of adding methyl groups to DNA bases, is an epigenetic modification. Since methylation frequently occurs at CpG or CG sites, the researchers determined the areas of the human genome where these sites exist. Specifically, they identified regions of DNA where a cytosine nucleotide is followed by a guanine nucleotide.
To determine all possible sites that can be methylated in most people, the researchers began by identifying CpG sites in the human reference genome from the Human Genome Project.
“We fragment the DNA and make it into little pieces like 100 base pairs, and then we sequence it,” van den Oord said. “And now we know the sequence of all these little fragments. And then we need to align it to the reference genome. If something lines up with a location that has a CpG, then we calculate for that site how much methylation is going on.”
The scientists calculated methylation risk scores using artificial intelligence (AI) machine learning. In AI, Linear Elastic Net regression is a method that combines the Lasso (Least Absolute Contraction and Selection Operator) and Ridge regression methods.
The predictive ability of the methylation risk scores generated by the AI algorithm was “higher than that of reported trauma and could not be explained by reported trauma, correlations with demographic variables, or continuity of predicted health problems from childhood to adulthood”.
According to the researchers, methylation risk scores predicted a wide range of adverse outcomes and have the potential to serve as a clinical biomarker to assess health risks from trauma exposure.
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