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Overlapping genetic risk in the spectrum of sudden death

University of British Columbia

Sudden Infant Death Syndrome (SIDS) is a sudden death occurring during sleep in infants below 1 year of old, which devastates the impacted families. By nature, SIDS deaths are those where all alternative causes of death, like suffocation or strangulation are eliminated, leaving families with few answers. While SIDS impacts infants, a spectrum of Sudden Death disorders exists across all age ranges and with comorbid syndromes, many of which occur sudden and unexpectedly during sleep. There is genetic overlap in risk genes in these disorders, and most notably between SIDS, Sudden Unexpected Death in Epilepsy (SUDEP), and Sudden Unexpected Death (SUD). Known and suspected Sudden Death (SD) genes are alternatively spliced in the developing brain in age and region dependent patterns, which may explain the differential timing of sudden death disorders despite their shared molecular risk factors. The objective of my project was to identify genes associated with sudden death and determine the timing of their alternative splicing. A literature search followed by an integrated pathway analysis generated a Sudden Death (SD) candidate genes (N=248). Analysis of whole exome sequences for eight (8) sudden death probands (SIDS (N=4), SUDEP (N=3) and SUD (N=1) samples was performed and Variant Effector Predictor was used to annotate the variants. The overall number of variants in the exomes for the SIDS individuals ranged from 40869-69978, SUDEP ranged from 19162-63954, and SUD contained 63217. Within the SD candidate genes, the number of variants in SIDS (707-1160), SUDEP (379-1078), and SUD (1026) did not allow for distinguishing between cohorts. All probands regardless of age carried multiple pathogenic variants in genes associated with disorders with high incidences of sudden death such as Long QT Syndrome, Dilated Cardiomyopathy, Dravet Syndrome, and Infantile Epileptic Encephalopathy many of which impacted one or more gene isoforms. The expression patterns of these genes of interest were evaluated using the Allen Brain Atlas for the Developing Mouse Brain to identify when, and what form each gene product is expressed. These patterns of personal genetic risk can be used to identify potential targets for molecular diagnostic screening and prevention.

Text

2017-10-30

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/60211

Pharmaceutical Sciences

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/