This 2019 UK/Canada/Germany human study investigated thirteen developmental disorders to identify genes that changed aspects of the epigenetic clock:

“Sotos syndrome accelerates epigenetic aging [+7.64 years]. Sotos syndrome is caused by loss-of-function mutations in the NSD1 gene, which encodes a histone H3 lysine 36 (H3K36) methyltransferase.

This leads to a phenotype which can include:

• Prenatal and postnatal overgrowth,
• Facial gestalt,
• Advanced bone age,
• Developmental delay,
• Higher cancer predisposition, and, in some cases,
• Heart defects.

Many of these characteristics could be interpreted as aging-like, identifying Sotos syndrome as a potential human model of accelerated physiological aging.

This research will shed some light on the different processes that erode the human epigenetic landscape during aging and provide a new hypothesis about the mechanisms behind the epigenetic aging clock.”

“Proposed model that highlights the role of H3K36 methylation maintenance on epigenetic aging:

• The H3K36me2/3 mark allows recruiting de novo DNA methyltransferases DNMT3A (in green) and DNMT3B (not shown).
• DNA methylation valleys (DMVs) are conserved genomic regions that are normally found hypomethylated.
• During aging, the H3K36 methylation machinery could become less efficient at maintaining the H3K36me2/3 landscape.
• This would lead to a relocation of de novo DNA methyltransferases from their original genomic reservoirs (which would become hypomethylated) to other non-specific regions such as DMVs (which would become hypermethylated and potentially lose their normal boundaries),
• With functional consequences for the tissues.”

The researchers improved methodologies of several techniques:

1. “Previous attempts to account for technical variation have used the first 5 principal components estimated directly from the DNA methylation data. However, this approach potentially removes meaningful biological variation. For the first time, we have shown that it is possible to use the control probes from the 450K array to readily correct for batch effects in the context of the epigenetic clock, which reduces the error associated with the predictions and decreases the likelihood of reporting a false positive.
2. We have confirmed the suspicion that Horvath’s model underestimates epigenetic age for older ages and assessed the impact of this bias in the screen for epigenetic age acceleration.
3. Because of the way that the Horvath epigenetic clock was trained, it is likely that its constituent 353 CpG sites are a low-dimensional representation of the different genome-wide processes that are eroding the epigenome with age. Our analysis has shown that these 353 CpG sites are characterized by a higher Shannon entropy when compared with the rest of the genome, which is dramatically decreased in the case of Sotos patients.”

https://genomebiology.biomedcentral.com/articles/10.1186/s13059-019-1753-9 “Screening for genes that accelerate the epigenetic aging clock in humans reveals a role for the H3K36 methyltransferase NSD1”