Beth Levine in memoriam

Beth Levine was born on 7 April 1960 in Newark, New Jersey. She went to college at Brown University where she received an A.B. Magna Cum Laude, and she attended medical school at Cornell University Medical College, receiving her MD in 1986. She completed her internship and residency in Internal Medicine at Mount Sinai Hospital in New York, and her fellowship in Infectious Diseases at The Johns Hopkins Hospital. Most recently, Beth was a Professor of Internal Medicine and Microbiology, Director of the Center for Autophagy Research, and holder of the Charles Sprague Distinguished Chair in Biomedical Science at the University of Texas Southwestern Medical Center in Dallas. Beth died on 15 June 2020 from cancer. Beth is survived by her husband, Milton Packer, and their two children, Rachel (26 years old) and Ben (25 years old). Dr. Levine was as an international leader in the field of autophagy research. Her laboratory identified the mammalian autophagy gene BECN1/beclin 1; identified conserved mechanisms underlying the regulation of autophagy (e.g. BCL2-BECN1 complex formation, insulin-like signaling, EGFR, ERBB2/HER2 and AKT1-mediated BECN1 phosphosphorylation); and provided the first evidence that autophagy genes are important in antiviral host defense, tumor suppression, lifespan extension, apoptotic corpse clearance, metazoan development, Na,K-ATPase-regulated cell death, and the beneficial metabolic effects of exercise. She developed a potent autophagy-inducing cell permeable peptide, Tat-beclin 1, which has potential therapeutic applications in a range of diseases. She was a founding Associate Editor of the journal Autophagy and an editorial board member of Cell and Cell Host & Microbe. She has received numerous awards/honors in recognition of her scientific achievement, including: The American Cancer Society Junior Faculty Research Award (1994); election into the American Society of Clinical Investigation (2000); the Ellison Medical Foundation Senior Scholars Award in Global Infectious Diseases (2004); elected member, American Association of Physicians (2005); appointment as a Howard Hughes Medical Institute Investigator (2008); Edith and Peter O’Donnell Award in Medicine (2008); elected fellow, American Association for the Advancement of Science (2012); election into the National Academy of Sciences (2013); election into the Academy of Medicine, Engineering and Science of Texas (2013); the ASCI Stanley J. Korsmeyer Award (2014); Phyllis T. Bodel Women in Medicine Award, Yale University School of Medicine (2018); recipient, Barcroft Medal, Queen’s University Belfast (2018).Fil: An, Zhenyi. No especifíca;Fil: Ballabi, Andrea. No especifíca;Fil: Bennett, Lynda. No especifíca;Fil: Boya, Patricia. No especifíca;Fil: Cecconi, Francesco. No especifíca;Fil: Chiang, Wei Chung. No especifíca;Fil: Codogno, Patrice. No especifíca;Fil: Colombo, Maria Isabel. No especifíca;Fil: Cuervo, Ana Maria. No especifíca;Fil: Debnath, Jayanta. No especifíca;Fil: Deretic, Vojo. No especifíca;Fil: Dikic, Ivan. No especifíca;Fil: Dionne, Keith. No especifíca;Fil: Dong, Xiaonan. No especifíca;Fil: Elazar, Zvulun. No especifíca;Fil: Galluzzi, Lorenzo. No especifíca;Fil: Gentile, Frank. No especifíca;Fil: Griffin, Diane E.. No especifíca;Fil: Hansen, Malene. No especifíca;Fil: Hardwick, J. Marie. No especifíca;Fil: He, Congcong. No especifíca;Fil: Huang, Shu Yi. No especifíca;Fil: Hurley, James. No especifíca;Fil: Jackson, William T.. No especifíca;Fil: Jozefiak, Cindy. No especifíca;Fil: Kitsis, Richard N.. No especifíca;Fil: Klionsky, Daniel J.. No especifíca;Fil: Kroemer, Guido. No especifíca;Fil: Meijer, Alfred J.. No especifíca;Fil: Meléndez, Alicia. No especifíca;Fil: Melino, Gerry. No especifíca;Fil: Mizushima, Noboru. No especifíca;Fil: Murphy, Leon O.. No especifíca;Fil: Nixon, Ralph. No especifíca;Fil: Orvedahl, Anthony. No especifíca;Fil: Pattingre, Sophie. No especifíca;Fil: Piacentini, Mauro. No especifíca;Fil: Reggiori, Fulvio. No especifíca;Fil: Ross, Theodora. No especifíca;Fil: Rubinsztein, David C.. No especifíca;Fil: Ryan, Kevin. No especifíca;Fil: Sadoshima, Junichi. No especifíca;Fil: Schreiber, Stuart L.. No especifíca;Fil: Scott, Frederick. No especifíca;Fil: Sebti, Salwa. No especifíca;Fil: Shiloh, Michael. No especifíca;Fil: Shoji, Sanae. No especifíca;Fil: Simonsen, Anne. No especifíca;Fil: Smith, Haley. No especifíca;Fil: Sumpter, Kathryn M.. No especifíca;Fil: Thompson, Craig B.. No especifíca;Fil: Thorburn, Andrew. No especifíca;Fil: Thumm, Michael. No especifíca;Fil: Tooze, Sharon. No especifíca;Fil: Vaccaro, Maria Ines. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Bioquímica y Medicina Molecular. Universidad de Buenos Aires. Facultad Medicina. Instituto de Bioquímica y Medicina Molecular; ArgentinaFil: Virgin, Herbert W.. No especifíca;Fil: Wang, Fei. No especifíca;Fil: White, Eileen. No especifíca;Fil: Xavier, Ramnik J.. No especifíca;Fil: Yoshimori, Tamotsu. No especifíca;Fil: Yuan, Junying. No especifíca;Fil: Yue, Zhenyu. No especifíca;Fil: Zhong, Qing. No especifíca

Evaluation of mitochondrial DNA copy number estimation techniques.

Mitochondrial DNA copy number (mtDNA-CN), a measure of the number of mitochondrial genomes per cell, is a minimally invasive proxy measure for mitochondrial function and has been associated with several aging-related diseases. Although quantitative real-time PCR (qPCR) is the current gold standard method for measuring mtDNA-CN, mtDNA-CN can also be measured from genotyping microarray probe intensities and DNA sequencing read counts. To conduct a comprehensive examination on the performance of these methods, we use known mtDNA-CN correlates (age, sex, white blood cell count, Duffy locus genotype, incident cardiovascular disease) to evaluate mtDNA-CN calculated from qPCR, two microarray platforms, as well as whole genome (WGS) and whole exome sequence (WES) data across 1,085 participants from the Atherosclerosis Risk in Communities (ARIC) study and 3,489 participants from the Multi-Ethnic Study of Atherosclerosis (MESA). We observe mtDNA-CN derived from WGS data is significantly more associated with known correlates compared to all other methods (p < 0.001). Additionally, mtDNA-CN measured from WGS is on average more significantly associated with traits by 5.6 orders of magnitude and has effect size estimates 5.8 times more extreme than the current gold standard of qPCR. We further investigated the role of DNA extraction method on mtDNA-CN estimate reproducibility and found mtDNA-CN estimated from cell lysate is significantly less variable than traditional phenol-chloroform-isoamyl alcohol (p = 5.44x10-4) and silica-based column selection (p = 2.82x10-7). In conclusion, we recommend the field moves towards more accurate methods for mtDNA-CN, as well as re-analyze trait associations as more WGS data becomes available from larger initiatives such as TOPMed

Evaluation of mitochondrial DNA copy number estimation techniques.

Mitochondrial DNA copy number (mtDNA-CN), a measure of the number of mitochondrial genomes per cell, is a minimally invasive proxy measure for mitochondrial function and has been associated with several aging-related diseases. Although quantitative real-time PCR (qPCR) is the current gold standard method for measuring mtDNA-CN, mtDNA-CN can also be measured from genotyping microarray probe intensities and DNA sequencing read counts. To conduct a comprehensive examination on the performance of these methods, we use known mtDNA-CN correlates (age, sex, white blood cell count, Duffy locus genotype, incident cardiovascular disease) to evaluate mtDNA-CN calculated from qPCR, two microarray platforms, as well as whole genome (WGS) and whole exome sequence (WES) data across 1,085 participants from the Atherosclerosis Risk in Communities (ARIC) study and 3,489 participants from the Multi-Ethnic Study of Atherosclerosis (MESA). We observe mtDNA-CN derived from WGS data is significantly more associated with known correlates compared to all other methods (p < 0.001). Additionally, mtDNA-CN measured from WGS is on average more significantly associated with traits by 5.6 orders of magnitude and has effect size estimates 5.8 times more extreme than the current gold standard of qPCR. We further investigated the role of DNA extraction method on mtDNA-CN estimate reproducibility and found mtDNA-CN estimated from cell lysate is significantly less variable than traditional phenol-chloroform-isoamyl alcohol (p = 5.44x10-4) and silica-based column selection (p = 2.82x10-7). In conclusion, we recommend the field moves towards more accurate methods for mtDNA-CN, as well as re-analyze trait associations as more WGS data becomes available from larger initiatives such as TOPMed

Evaluation of mitochondrial DNA copy number estimation techniques

Mitochondrial DNA copy number (mtDNA-CN), a measure of the number of mitochondrial genomes per cell, is a minimally invasive proxy measure for mitochondrial function and has been associated with several aging-related diseases. Although quantitative real-time PCR (qPCR) is the current gold standard method for measuring mtDNA-CN, mtDNA-CN can also be measured from genotyping microarray probe intensities and DNA sequencing read counts. To conduct a comprehensive examination on the performance of these methods, we use known mtDNA-CN correlates (age, sex, white blood cell count, Duffy locus genotype, incident cardiovascular disease) to evaluate mtDNA-CN calculated from qPCR, two microarray platforms, as well as whole genome (WGS) and whole exome sequence (WES) data across 1,085 participants from the Atherosclerosis Risk in Communities (ARIC) study and 3,489 participants from the Multi-Ethnic Study of Atherosclerosis (MESA). We observe mtDNA-CN derived from WGS data is significantly more associated with known correlates compared to all other methods (p \u3c 0.001). Additionally, mtDNA-CN measured from WGS is on average more significantly associated with traits by 5.6 orders of magnitude and has effect size estimates 5.8 times more extreme than the current gold standard of qPCR. We further investigated the role of DNA extraction method on mtDNA-CN estimate reproducibility and found mtDNA-CN estimated from cell lysate is significantly less variable than traditional phenol-chloroform-isoamyl alcohol (p = 5.44x10-4) and silica-based column selection (p = 2.82x10-7). In conclusion, we recommend the field moves towards more accurate methods for mtDNA-CN, as well as re-analyze trait associations as more WGS data becomes available from larger initiatives such as TOPMed

Mitochondrial DNA copy number can influence mortality and cardiovascular disease via methylation of nuclear DNA CpGs

Background: Mitochondrial DNA copy number (mtDNA-CN) has been associated with a variety of aging-related diseases, including all-cause mortality. However, the mechanism by which mtDNA-CN influences disease is not currently understood. One such mechanism may be through regulation of nuclear gene expression via the modification of nuclear DNA (nDNA) methylation. Methods: To investigate this hypothesis, we assessed the relationship between mtDNA-CN and nDNA methylation in 2507 African American (AA) and European American (EA) participants from the Atherosclerosis Risk in Communities (ARIC) study. To validate our findings, we assayed an additional 2528 participants from the Cardiovascular Health Study (CHS) (N = 533) and Framingham Heart Study (FHS) (N = 1995). We further assessed the effect of experimental modification of mtDNA-CN through knockout of TFAM, a regulator of mtDNA replication, via CRISPR-Cas9. Results: Thirty-four independent CpGs were associated with mtDNA-CN at genome-wide significance (P \u3c 5 × 10-8). Meta-analysis across all cohorts identified six mtDNA-CN-associated CpGs at genome-wide significance (P \u3c 5 × 10-8). Additionally, over half of these CpGs were associated with phenotypes known to be associated with mtDNA-CN, including coronary heart disease, cardiovascular disease, and mortality. Experimental modification of mtDNA-CN demonstrated that modulation of mtDNA-CN results in changes in nDNA methylation and gene expression of specific CpGs and nearby transcripts. Strikingly, the neuroactive ligand receptor interaction KEGG pathway was found to be highly overrepresented in the ARIC cohort (P = 5.24 × 10-12), as well as the TFAM knockout methylation (P = 4.41 × 10-4) and expression (P = 4.30 × 10-4) studies. Conclusions: These results demonstrate that changes in mtDNA-CN influence nDNA methylation at specific loci and result in differential expression of specific genes that may impact human health and disease via altered cell signaling

A Polynesian-specific missense CETP variant alters the lipid profile

Summary: Identifying population-specific genetic variants associated with disease and disease-predisposing traits is important to provide insights into the genetic determinants of health and disease between populations, as well as furthering genomic justice. Various common pan-population polymorphisms at CETP associate with serum lipid profiles and cardiovascular disease. Here, sequencing of CETP identified a missense variant rs1597000001 (p.Pro177Leu) specific to Māori and Pacific people that associates with higher HDL-C and lower LDL-C levels. Each copy of the minor allele associated with higher HDL-C by 0.236 mmol/L and lower LDL-C by 0.133 mmol/L. The rs1597000001 effect on HDL-C is comparable with CETP Mendelian loss-of-function mutations that result in CETP deficiency, consistent with our data, which shows that rs1597000001 lowers CETP activity by 27.9%. This study highlights the potential of population-specific genetic analyses for improving equity in genomics and health outcomes for population groups underrepresented in genomic studies