Back

Progressive decline in the levels of six miRNAs from parents to children in autism

Mehmetbeyoglu, E.; Yilmaz, Z.; Taheri, S.; Ozkul, Y.; Rassoulzadegan, M.

2022-10-22 genetics
10.1101/2022.10.20.512859 bioRxiv
Show abstract

The growing burden of a gradual increase in births of children with autism has placed it at the center of the concerns of major laboratories. We have previously detected a decrease in the levels of six miRNAs (miR-19a-3p, miR-361-5p, miR-3613-3p, miR-150-5p, miR-126-3p, and miR-499a-5p) in parents and their children inherited at a lower level. Here, we suggest that down-regulation of each of these six miRNAs inherited from parents contributes to the development of children with autism. We compare their levels of distribution in each family between the autistic child and siblings. We find that the distribution of levels of these miRNAs in siblings (undiagnosed as autism) is not always higher than in autistic children, but it is at varying levels. These data support a model in which autistic behavior relies on low levels of the six miRNAs expressed in children potentially associated with autistic syndrome (ASD). The intimate link between miRNAs levels and behavioral characteristics suggests possibilities for understanding the basic circuitry involved in autism and thus advancing partial knowledge of brain functions. An early diagnosis of autism helps provide children an environment conducive to their development. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=100 SRC="FIGDIR/small/512859v1_ufig1.gif" ALT="Figure 1"> View larger version (14K): org.highwire.dtl.DTLVardef@176d6f4org.highwire.dtl.DTLVardef@11a4ebforg.highwire.dtl.DTLVardef@280f67org.highwire.dtl.DTLVardef@b3659_HPS_FORMAT_FIGEXP M_FIG C_FIG

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.