Genetic correlation analysis

VL Vasiliki Lagou
LJ Longda Jiang
AU Anna Ulrich
LZ Liudmila Zudina
KG Karla Sofia Gutiérrez González
ZB Zhanna Balkhiyarova
AF Alessia Faggian
JM Jared G. Maina
SC Shiqian Chen
PT Petar V. Todorov
SS Sodbo Sharapov
AD Alessia David
LM Letizia Marullo
RM Reedik Mägi
RR Roxana-Maria Rujan
EA Emma Ahlqvist
GT Gudmar Thorleifsson
ΗG Ηe Gao
ΕΕ Εvangelos Εvangelou
BB Beben Benyamin
RS Robert A. Scott
AI Aaron Isaacs
JZ Jing Hua Zhao
SW Sara M. Willems
TJ Toby Johnson
CG Christian Gieger
HG Harald Grallert
CM Christa Meisinger
MM Martina Müller-Nurasyid
RS Rona J. Strawbridge
AG Anuj Goel
DR Denis Rybin
EA Eva Albrecht
AJ Anne U. Jackson
HS Heather M. Stringham
IJ Ivan R. Corrêa, Jr.
EF Eric Farber-Eger
VS Valgerdur Steinthorsdottir
AU André G. Uitterlinden
PM Patricia B. Munroe
MB Morris J. Brown
JS Julian Schmidberger
OH Oddgeir Holmen
BT Barbara Thorand
KH Kristian Hveem
TW Tom Wilsgaard
KM Karen L. Mohlke
ZW Zhe Wang
AS Aleksey Shmeliov
MH Marcel den Hoed
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We investigate the shared genetic component between RG and other traits, including glycemic ones, by performing genetic correlation analysis using the bivariate LD score regression method (LDSC v1.0.0)91. To reduce multiple testing burden, only the GWAS results of the AS20 + AST20 model were used. We used GWAS summary statistics available in LDhub92 and the Meta-Analysis of Glucose and Insulin-related Traits Consortium (MAGIC) website (https://www.magicinvestigators.org) for several traits including FG/FI64, HOMA-B/HOMA-IR93. In total, 228 different traits were included in the genetic correlation analysis with RG. We considered P ≤ 2.2 × 104 (Bonferroni correction for 228 traits) as the statistical significant level and P ≤ 0.05 as the nominal level.

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