Julie A Lynch

Dr. Julie A Lynch

orcid

Research Focus & Metrics

Academic Career Length

14Years (2013-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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15 June 2020 in Nature Genetics
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MVMarijana Vujkovic
Marijana Vujkovic
JKJacob M. Keaton
Jacob M. Keaton
JLJulie A Lynch
Julie A Lynch
DMDonald R. Miller
Donald R. Miller
JZJin Zhou
Jin Zhou
DSDanish Saleheen
Danish Saleheen
We investigated type 2 diabetes (T2D) genetic susceptibility via multi-ancestry meta-analysis of 228,499 cases and 1,178,783 controls in the Million Veteran Program (MVP), DIAMANTE, Biobank Japan and other studies. We report 568 associations, including 286 autosomal, 7 X-chromosomal and 25 identified in ancestry-specific analyses that were previously unreported. Transcriptome-wide association analysis detected 3,568 T2D associations with genetically predicted gene expression in 687 novel genes; of these, 54 are known to interact with FDA-approved drugs. A polygenic risk score (PRS) was strongly associated with increased risk of T2D-related retinopathy and modestly associated with chronic kidney disease (CKD), peripheral artery disease (PAD) and neuropathy. We investigated the genetic etiology of T2D-related vascular outcomes in the MVP and observed statistical SNP–T2D interactions at 13 variants, including coronary heart disease (CHD), CKD, PAD and neuropathy. These findings may help to identify potential therapeutic targets for T2D and genomic pathways that link T2D to vascular outcomes.

1 August 2022 in Nature Medicine
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CTCatherine Tcheandjieu
Catherine Tcheandjieu
XZXiang Zhu
Xiang Zhu
AHAustin T. Hilliard
Austin T. Hilliard
SCShoa L. Clarke
Shoa L. Clarke
Valerio NapolioniValerio Napolioni
Valerio Napolioni
MPMillion Veteran Program
Million Veteran Program

8 July 2019 in Nature Medicine
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Journal Article
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VPVa Million Veteran Program
Va Million Veteran Program
DKDerek Klarin
Derek Klarin
JLJulie A Lynch
Julie A Lynch
KAKrishna Aragam
Krishna Aragam
MCMark Chaffin
Mark Chaffin
SDScott M. Damrauer
Scott M. Damrauer

1 November 2019 in Nature Genetics
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ICINVENT Consortium
INVENT Consortium
DKDerek Klarin
Derek Klarin
VPVeterans Affairs’ Million Veteran Program
Veterans Affairs’ Million Veteran Program
EBEmma Busenkell
Emma Busenkell
RJRenae Judy
Renae Judy
PNPradeep Natarajan
Pradeep Natarajan

2 June 2022 in Nature Genetics
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Journal Article
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MVMarijana Vujkovic
Marijana Vujkovic
SRShweta Ramdas
Shweta Ramdas
KLKim M. Lorenz
Kim M. Lorenz
XGXiuqing Guo
Xiuqing Guo
RDRebecca Darlay
Rebecca Darlay
KCKyong-Mi Chang
Kyong-Mi Chang

29 December 2022 in Nature Communications
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JHJie Huang
Jie Huang
JHJennifer E. Huffman
Jennifer E. Huffman
YHYunfeng Huang
Yunfeng Huang
IVItalo Faria do Valle
Italo Faria do Valle
TAThemistocles L. Assimes
Themistocles L. Assimes
COChristopher J. O’donnell
Christopher J. O’donnell
Elevated body mass index (BMI) is heritable and associated with many health conditions that impact morbidity and mortality. The study of the genetic association of BMI across a broad range of common disease conditions offers the opportunity to extend current knowledge regarding the breadth and depth of adiposity-related diseases. We identify 906 (364 novel) and 41 (6 novel) genome-wide significant loci for BMI among participants of European (N~1.1 million) and African (N~100,000) ancestry, respectively. Using a BMI genetic risk score including 2446 variants, 316 diagnoses are associated in the Million Veteran Program, with 96.5% showing increased risk. A co-morbidity network analysis reveals seven disease communities containing multiple interconnected diseases associated with BMI as well as extensive connections across communities. Mendelian randomization analysis confirms numerous phenotypes across a breadth of organ systems, including conditions of the circulatory (heart failure, ischemic heart disease, atrial fibrillation), genitourinary (chronic renal failure), respiratory (respiratory failure, asthma), musculoskeletal and dermatologic systems that are deeply interconnected within and across the disease communities. This work shows that the complex genetic architecture of BMI associates with a broad range of major health conditions, supporting the need for comprehensive approaches to prevent and treat obesity.