@article {6325, title = {Common variation in fatty acid metabolic genes and risk of incident sudden cardiac arrest.}, journal = {Heart Rhythm}, volume = {11}, year = {2014}, month = {2014 Mar}, pages = {471-7}, abstract = {

BACKGROUND: There is limited information on genetic factors associated with sudden cardiac arrest (SCA).

OBJECTIVE: To assess the association of common variation in genes in fatty acid pathways with SCA risk.

METHODS: We selected 85 candidate genes and 1155 single nucleotide polymorphisms (SNPs) tagging common variation in each gene. We investigated the SNP associations with SCA in a population-based case-control study. Cases (n = 2160) were from a repository of SCA in the greater Seattle area. Controls (n = 2615), frequency-matched on age and sex, were from the same area. We used linear logistic regression to examine SNP associations with SCA. We performed permutation-based p-min tests to account for multiple comparisons within each gene. The SNP associations with a corrected P value of <.05 were then examined in a meta-analysis of these SNP associations in 9 replication studies totaling 2129 SCA cases and 23,833 noncases.

RESULTS: Eight SNPs in or near 8 genes were associated with SCA risk in the discovery study, one of which was nominally significant in the replication phase (rs7737692, minor allele frequency 36\%, near the LPCAT1 gene). For each copy of the minor allele, rs7737692 was associated with 13\% lower SCA risk (95\% confidence interval -21\% to -5\%) in the discovery phase and 9\% lower SCA risk (95\% confidence interval -16\% to -1\%) in the replication phase.

CONCLUSIONS: While none of the associations reached significance with Bonferroni correction, a common genetic variant near LPCAT1, a gene involved in the remodeling of phospholipids, was nominally associated with incident SCA risk. Further study is needed to validate this observation.

}, keywords = {1-Acylglycerophosphocholine O-Acyltransferase, Aged, Algorithms, Alleles, Case-Control Studies, Death, Sudden, Cardiac, Fatty Acids, Female, Genetic Predisposition to Disease, Genetic Variation, Genotype, Humans, Male, Polymorphism, Single Nucleotide, Risk Factors}, issn = {1556-3871}, doi = {10.1016/j.hrthm.2014.01.008}, author = {Lemaitre, Rozenn N and Johnson, Catherine O and Hesselson, Stephanie and Sotoodehnia, Nona and Sotoodhenia, Nona and McKnight, Barbara and Sitlani, Colleen M and Rea, Thomas D and King, Irena B and Kwok, Pui-Yan and Mak, Angel and Li, Guo and Brody, Jennifer and Larson, Eric and Mozaffarian, Dariush and Psaty, Bruce M and Huertas-Vazquez, Adriana and Tardif, Jean-Claude and Albert, Christine M and Lyytik{\"a}inen, Leo-Pekka and Arking, Dan E and K{\"a}{\"a}b, Stefan and Huikuri, Heikki V and Krijthe, Bouwe P and Eijgelsheim, Mark and Wang, Ying A and Reinier, Kyndaron and Lehtim{\"a}ki, Terho and Pulit, Sara L and Brugada, Ramon and M{\"u}ller-Nurasyid, Martina and Newton-Cheh, Chris H and Karhunen, Pekka J and Stricker, Bruno H and Goyette, Philippe and Rotter, Jerome I and Chugh, Sumeet S and Chakravarti, Aravinda and Jouven, Xavier and Siscovick, David S} } @article {8100, title = {Systematic analysis of dark and camouflaged genes reveals disease-relevant genes hiding in plain sight.}, journal = {Genome Biol}, volume = {20}, year = {2019}, month = {2019 05 20}, pages = {97}, abstract = {

BACKGROUND: The human genome contains "dark" gene regions that cannot be adequately assembled or aligned using standard short-read sequencing technologies, preventing researchers from identifying mutations within these gene regions that may be relevant to human disease. Here, we identify regions with few mappable reads that we call dark by depth, and others that have ambiguous alignment, called camouflaged. We assess how well long-read or linked-read technologies resolve these regions.

RESULTS: Based on standard whole-genome Illumina sequencing data, we identify 36,794 dark regions in 6054 gene bodies from pathways important to human health, development, and reproduction. Of these gene bodies, 8.7\% are completely dark and 35.2\% are >= 5\% dark. We identify dark regions that are present in protein-coding exons across 748 genes. Linked-read or long-read sequencing technologies from 10x Genomics, PacBio, and Oxford Nanopore Technologies reduce dark protein-coding regions to approximately 50.5\%, 35.6\%, and 9.6\%, respectively. We present an algorithm to resolve most camouflaged regions and apply it to the Alzheimer{\textquoteright}s Disease Sequencing Project. We rescue a rare ten-nucleotide frameshift deletion in CR1, a top Alzheimer{\textquoteright}s disease gene, found in disease cases but not in controls.

CONCLUSIONS: While we could not formally assess the association of the CR1 frameshift mutation with Alzheimer{\textquoteright}s disease due to insufficient sample-size, we believe it merits investigating in a larger cohort. There remain thousands of potentially important genomic regions overlooked by short-read sequencing that are largely resolved by long-read technologies.

}, keywords = {Genetic Predisposition to Disease, Genome, Human, Humans, Mutation}, issn = {1474-760X}, doi = {10.1186/s13059-019-1707-2}, author = {Ebbert, Mark T W and Jensen, Tanner D and Jansen-West, Karen and Sens, Jonathon P and Reddy, Joseph S and Ridge, Perry G and Kauwe, John S K and Belzil, Veronique and Pregent, Luc and Carrasquillo, Minerva M and Keene, Dirk and Larson, Eric and Crane, Paul and Asmann, Yan W and Ertekin-Taner, Nilufer and Younkin, Steven G and Ross, Owen A and Rademakers, Rosa and Petrucelli, Leonard and Fryer, John D} }