TY - JOUR
T1 - Determinants of penetrance and variable expressivity in monogenic metabolic conditions across 77,184 exomes
AU - AMP-T2D-GENES Consortia
AU - Goodrich, Julia K.
AU - Singer-Berk, Moriel
AU - Son, Rachel
AU - Sveden, Abigail
AU - Wood, Jordan
AU - England, Eleina
AU - Cole, Joanne B.
AU - Weisburd, Ben
AU - Watts, Nick
AU - Caulkins, Lizz
AU - Dornbos, Peter
AU - Koesterer, Ryan
AU - Zappala, Zachary
AU - Zhang, Haichen
AU - Maloney, Kristin A.
AU - Dahl, Andy
AU - Aguilar-Salinas, Carlos A.
AU - Atzmon, Gil
AU - Barajas-Olmos, Francisco
AU - Barzilai, Nir
AU - Blangero, John
AU - Boerwinkle, Eric
AU - Bonnycastle, Lori L.
AU - Bottinger, Erwin
AU - Bowden, Donald W.
AU - Centeno-Cruz, Federico
AU - Chambers, John C.
AU - Chami, Nathalie
AU - Chan, Edmund
AU - Chan, Juliana
AU - Cheng, Ching Yu
AU - Cho, Yoon Shin
AU - Contreras-Cubas, Cecilia
AU - Córdova, Emilio
AU - Correa, Adolfo
AU - DeFronzo, Ralph A.
AU - Duggirala, Ravindranath
AU - Dupuis, Josée
AU - Garay-Sevilla, Ma Eugenia
AU - García-Ortiz, Humberto
AU - Gieger, Christian
AU - Glaser, Benjamin
AU - González-Villalpando, Clicerio
AU - Gonzalez, Ma Elena
AU - Grarup, Niels
AU - Groop, Leif
AU - Gross, Myron
AU - Haiman, Christopher
AU - Small, Kerrin S.
AU - Spector, Timothy D.
N1 - Funding Information:
This work was supported by NIH/NIDDK U01 DK105554 to JCF. This research has been conducted using the UK Biobank Resource under application number 27892. MSU is supported by NIH/NIDDK K23 DK114551. AODL was supported by NIH/NICHD K12 HD052896. MB is supported by NIH/NIDDK DK062370. JCF is also supported by NIH/ NIDDK K24 DK110550. JMM is supported by American Diabetes Association Innovative and Clinical Translational Award 1-19-ICTS-068. Please see Supplementary Information for additional Extended Acknowledgements.
Publisher Copyright:
© 2021, The Author(s).
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2021/12
Y1 - 2021/12
N2 - Hundreds of thousands of genetic variants have been reported to cause severe monogenic diseases, but the probability that a variant carrier develops the disease (termed penetrance) is unknown for virtually all of them. Additionally, the clinical utility of common polygenetic variation remains uncertain. Using exome sequencing from 77,184 adult individuals (38,618 multi-ancestral individuals from a type 2 diabetes case-control study and 38,566 participants from the UK Biobank, for whom genotype array data were also available), we apply clinical standard-of-care gene variant curation for eight monogenic metabolic conditions. Rare variants causing monogenic diabetes and dyslipidemias display effect sizes significantly larger than the top 1% of the corresponding polygenic scores. Nevertheless, penetrance estimates for monogenic variant carriers average 60% or lower for most conditions. We assess epidemiologic and genetic factors contributing to risk prediction in monogenic variant carriers, demonstrating that inclusion of polygenic variation significantly improves biomarker estimation for two monogenic dyslipidemias.
AB - Hundreds of thousands of genetic variants have been reported to cause severe monogenic diseases, but the probability that a variant carrier develops the disease (termed penetrance) is unknown for virtually all of them. Additionally, the clinical utility of common polygenetic variation remains uncertain. Using exome sequencing from 77,184 adult individuals (38,618 multi-ancestral individuals from a type 2 diabetes case-control study and 38,566 participants from the UK Biobank, for whom genotype array data were also available), we apply clinical standard-of-care gene variant curation for eight monogenic metabolic conditions. Rare variants causing monogenic diabetes and dyslipidemias display effect sizes significantly larger than the top 1% of the corresponding polygenic scores. Nevertheless, penetrance estimates for monogenic variant carriers average 60% or lower for most conditions. We assess epidemiologic and genetic factors contributing to risk prediction in monogenic variant carriers, demonstrating that inclusion of polygenic variation significantly improves biomarker estimation for two monogenic dyslipidemias.
UR - http://www.scopus.com/inward/record.url?scp=85107774343&partnerID=8YFLogxK
U2 - 10.1038/s41467-021-23556-4
DO - 10.1038/s41467-021-23556-4
M3 - Article
C2 - 34108472
AN - SCOPUS:85107774343
SN - 2041-1723
VL - 12
JO - Nature Communications
JF - Nature Communications
IS - 1
M1 - 3505
ER -