RESUMEN
Several efforts in basic and clinical research have been contributing to unveiling the genetics behind autism spectrum disorders (ASD). However, despite these advancements, many individuals diagnosed with ASD and related neuropsychiatric conditions have been genetically investigated without elucidative results. The enormous genetic complexity of ASD-related conditions makes it a significant challenge to achieve, with a growing number of genes (close to a thousand) involved, belonging to different molecular pathways and presenting distinct genetic variations. Next-generation sequencing (NGS) is the approach most used in genetic research related to ASD, identifying de novo mutation, which is closely related to more severe clinical phenotypes, especially when they affect constrained and loss-of-function intolerant genes. On the other hand, de novo mutation findings contribute to a small percentage of the ASD population, since most of the cases and genetic variants associated with neuropsychiatric conditions are inherited and phenotypes are results of additive polygenic models, which makes statistical efforts more difficult. As a result, NGS investigation can sound vainly or unsuccessful, and new mutations on genes already related with ASD are classified as variants of unknown significance (VUS), hampering their endorsement to a clinical phenotype. This review is focused on currently available strategies to clarify the impact of VUS and to describe the efforts to identify more pieces of evidence throughout clinical interpretation and genetic curation process.
RESUMEN
BACKGROUND: Formalin fixation (FF) is the standard and most common method for preserving postmortem brain tissue. FF stabilizes cellular morphology and tissue architecture, and can be used to study the distinct morphologic and genetic signatures of different cell types. Although the procedure involved in FF degrades messenger RNA over time, an alternative approach is to use small RNAs (sRNAs) for genetic analysis associated with cell morphology. Although genetic analysis is carried out on fresh or frozen tissue, there is limited availability or impossibility on targeting specific cell populations, respectively. NEW METHOD: The goal of this study is to detect miRNA and other classes of sRNA stored in formalin or in paraffin embedded for over decades. Two brain samples, one formed by a mixed population of cortical and subcortical cells, and one formed by pyramidal shaped cells collected by laser-capture microdissection, were subjected to sRNA sequencing. RESULTS: Performing bioinformatics analysis over the sequenced sRNA from brain tissue, we detected several classes of sRNA, such as miRNAs that play key roles in brain neurodevelopmental and maintenance pathways, and hsa-mir-155 expression in neurons. Comparison with existing method: Our method is the first to combine the approaches for: laser-capture of pyramidal neurons from long-term formalin-fixed brain; extract sRNA from laser-captured pyramidal neurons; apply a suite of bioinformatics tools to detect miRNA and other classes of sRNAs on sequenced samples having high levels of RNA degradation. CONCLUSION: This is the first study to show that sRNA can be rescued from laser-captured FF pyramidal neurons.