Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Pathways with Genomic Variation in Family DNA Microarrays Linked to Autism Risk Inheritance

Version 1 : Received: 30 October 2020 / Approved: 10 November 2020 / Online: 10 November 2020 (12:33:35 CET)

How to cite: Wall, D.; Esteban, F.; Tonellato, P. Pathways with Genomic Variation in Family DNA Microarrays Linked to Autism Risk Inheritance. Preprints 2020, 2020110311 (doi: 10.20944/preprints202011.0311.v1). Wall, D.; Esteban, F.; Tonellato, P. Pathways with Genomic Variation in Family DNA Microarrays Linked to Autism Risk Inheritance. Preprints 2020, 2020110311 (doi: 10.20944/preprints202011.0311.v1).

Abstract

The genetic heterogeneity of autism has stymied the search for causes and cures. Whole-genomic studies on large numbers of families have helped identify combinations of inherited and de novo signal. In the present work, we re-analyze DNA microarrays using a novel strategy that takes prior knowledge of genetic relationships into account and that was designed to boost signal important to our understanding of the molecular basis of autism. Our strategy was designed to identify significant genomic variation within a priori defined biological concepts and improves signal detection while lessening the severity of multiple test correction seen in standard analysis of genome-wide association data. Upon application of our approach using 3,244 biological concepts, we detected genomic variation in 68 biological concepts with significant association to autism in comparison to family-based controls. These concepts clustered naturally into a total of 19 classes, principally including cell adhesion, cancer, and immune response. The top-ranking concepts contained high percentages of genes already suspected to play roles in autism or in a related neurological disorder. In addition, many of the sets associated with autism at the DNA level also proved to be predictive of changes in gene expression within a separate population of autistic cases, suggesting that the signature of genomic variation may also be detectable in blood-based transcriptional profiles. This cross-validation with gene expression data from individuals with autism coupled with the enrichment within autism-related neurological disorders supported the possibility that the mutations play important roles in the onset of autism and should be given priority for further study. Our work provides new leads into the genetic underpinnings of autism and highlights the importance of reanalysis of genomic studies of complex disease using prior knowledge of genetic organization.

Subject Areas

autism genetics; family microarrays; pathway enrichment; network biology

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