Myocardial infarction (MI) is the leading cause of death in the developed world. Low-density lipoprotein cholesterol (LDL-C) is a causal risk factor for the disease. Despite aggressive use of LDL-C-lowering medications such as statins, many individuals do not achieve the LDL-C levels recommended by clinical guidelines. There remains a need for additional methods of reducing LDL-C and MI risk. In rare families, extremely low or high LDL-C segregates in a Mendelian fashion and the study of such families has transformed our understanding of LDL biology and has suggested new therapeutic targets. However, in many such families, sequencing of known causal genes has failed to identify mutations. Recently, there has emerged a powerful and efficient method to discover genes underlying rare Mendelian disorders, namely exome sequencing. Exome sequencing refers to the sequencing and analysis of all protein-coding regions in the human genome. We hypothesize that: (1) additional novel genes responsible for Mendelian forms of low or high LDL-C exist;(2) the causal gene and mutation(s) in each family may be discovered with exome analysis of just a few affected individuals in each pedigree;and (3) the newly discovered genes can be demonstrated to relate not only to LDL-C but also to MI risk in the population. To test these hypotheses, we propose the following Specific Aims: (1) To perform sequencing of the exome in 2-4 affected individuals from each of 11 families with familial hypobetalipoproteinemia (FHBL) and discover the causal gene and mutation specific to each family. FHBL is a disorder characterized by extremely low levels of plasma LDL-C. We will only study families where known causes of FHBL (e.g., APOB and PCSK9) have been ruled out;(2) To perform sequencing of the exome in 2-4 affected individuals from each of 10 families with severe hypercholesterolemia and discover the causal gene and mutation specific to each family. We will study families where known causes of hypercholesterolemia (e.g., APOB, PCSK9, and LDLR) have been ruled out;and (3) To perform targeted sequencing of novel genes mapped in Aims 1 and 2, discover intermediate frequency variants with large effect on LDL-C, and test these variants for association with MI risk in the population. Successful completion of this proposal should have three major impacts on biomedical research. First, we will discover a set of novel genes that when perturbed in humans lead to dramatically high or low LDL-C. Second, we will know which of these genes change not only plasma LDL-C but also MI risk. This information will allow for rational selection among potential molecular targets for those most likely to successfully produce effective and safe therapeutics. Finally, gene discovery should fuel additional mechanistic studies that can provide new insights into LDL-C metabolism and MI risk.
Higher blood levels of low-density lipoprotein (LDL) cholesterol cause heart attack and new therapies are needed to lower blood LDL cholesterol. In some families, extremely high blood LDL cholesterol or extremely low blood LDL cholesterol tracks as if a single gene is defective. Here, we propose to identify the causal genes in such families by using a newly developed technique where all of the protein coding genes in the genome - """"""""the exome""""""""- can be sequenced in one experiment. After identifying the causal genes in families, we will test whether these genes influence risk for heart attack in the general population.
| Elbitar, Sandy; Susan-Resiga, Delia; Ghaleb, Youmna et al. (2018) New Sequencing technologies help revealing unexpected mutations in Autosomal Dominant Hypercholesterolemia. Sci Rep 8:1943 |
| Saleheen, Danish; Natarajan, Pradeep; Armean, Irina M et al. (2017) Human knockouts and phenotypic analysis in a cohort with a high rate of consanguinity. Nature 544:235-239 |
| Lacy, Mary E; Wellenius, Gregory A; Sumner, Anne E et al. (2017) Association of Sickle Cell Trait With Hemoglobin A1c in African Americans. JAMA 317:507-515 |
| Stitziel, Nathan O; Kathiresan, Sekar (2017) Leveraging human genetics to guide drug target discovery. Trends Cardiovasc Med 27:352-359 |
| Musunuru, Kiran; Kathiresan, Sekar (2016) Surprises From Genetic Analyses of Lipid Risk Factors for Atherosclerosis. Circ Res 118:579-85 |
| Clapham, Katharine R; Chu, Audrey Y; Wessel, Jennifer et al. (2016) A null mutation in ANGPTL8 does not associate with either plasma glucose or type 2 diabetes in humans. BMC Endocr Disord 16:7 |
| Chami, Nathalie; Chen, Ming-Huei; Slater, Andrew J et al. (2016) Exome Genotyping Identifies Pleiotropic Variants Associated with Red Blood Cell Traits. Am J Hum Genet 99:8-21 |
| Lek, Monkol; Karczewski, Konrad J; Minikel, Eric V et al. (2016) Analysis of protein-coding genetic variation in 60,706 humans. Nature 536:285-91 |
| Myocardial Infarction Genetics and CARDIoGRAM Exome Consortia Investigators; Stitziel, Nathan O; Stirrups, Kathleen E et al. (2016) Coding Variation in ANGPTL4, LPL, and SVEP1 and the Risk of Coronary Disease. N Engl J Med 374:1134-44 |
| Patel, Aniruddh P; Peloso, Gina M; Pirruccello, James P et al. (2016) Targeted exonic sequencing of GWAS loci in the high extremes of the plasma lipids distribution. Atherosclerosis 250:63-8 |
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