Determinants of penetrance and variable expressivity in monogenic metabolic conditions across 77,184 exomes
Goodrich, J.K. ; Groop, Leif LU ; Nilsson, Peter M LU ; Tuomi, Tiinamaija LU
and Udler, M.S.
(2021)
In Nature Communications
12(1).
- Abstract
- 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%... (More)
- 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. © 2021, The Author(s). (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/ce8387eb-c0b0-4853-8cd6-751ad3d2f760
- author
- Goodrich, J.K.
; Groop, Leif
LU
; Nilsson, Peter M
LU
; Tuomi, Tiinamaija
LU
and Udler, M.S.
- author collaboration
- organization
- publishing date
- 2021
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- database, detection method, disease severity, epidemiology, gene expression, genetic variation, genotype, adult, Article, case control study, cohort analysis, controlled study, dyslipidemia, effect size, exome, genetic risk score, genetic variability, heredity, human, major clinical study, monogenic disorder, non insulin dependent diabetes mellitus, penetrance, phenotype, whole exome sequencing, biological variation, genetic predisposition, genetics, metabolism, multifactorial inheritance, risk assessment, biological marker, Adult, Biological Variation, Population, Biomarkers, Diabetes Mellitus, Type 2, Dyslipidemias, Exome, Genetic Predisposition to Disease, Genotype, Humans, Multifactorial Inheritance, Penetrance, Risk Assessment
- in
- Nature Communications
- volume
- 12
- issue
- 1
- publisher
- Nature Publishing Group
- external identifiers
-
- scopus:85107774343
- pmid:34108472
- ISSN
- 2041-1723
- DOI
- 10.1038/s41467-021-23556-4
- language
- English
- LU publication?
- yes
- id
- ce8387eb-c0b0-4853-8cd6-751ad3d2f760
- date added to LUP
- 2021-12-28 09:59:21
- date last changed
- 2024-05-04 19:30:25
@article{ce8387eb-c0b0-4853-8cd6-751ad3d2f760,
abstract = {{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. © 2021, The Author(s).}},
author = {{Goodrich, J.K. and Groop, Leif and Nilsson, Peter M and Tuomi, Tiinamaija and Udler, M.S.}},
issn = {{2041-1723}},
keywords = {{database; detection method; disease severity; epidemiology; gene expression; genetic variation; genotype; adult; Article; case control study; cohort analysis; controlled study; dyslipidemia; effect size; exome; genetic risk score; genetic variability; heredity; human; major clinical study; monogenic disorder; non insulin dependent diabetes mellitus; penetrance; phenotype; whole exome sequencing; biological variation; genetic predisposition; genetics; metabolism; multifactorial inheritance; risk assessment; biological marker; Adult; Biological Variation, Population; Biomarkers; Diabetes Mellitus, Type 2; Dyslipidemias; Exome; Genetic Predisposition to Disease; Genotype; Humans; Multifactorial Inheritance; Penetrance; Risk Assessment}},
language = {{eng}},
number = {{1}},
publisher = {{Nature Publishing Group}},
series = {{Nature Communications}},
title = {{Determinants of penetrance and variable expressivity in monogenic metabolic conditions across 77,184 exomes}},
url = {{http://dx.doi.org/10.1038/s41467-021-23556-4}},
doi = {{10.1038/s41467-021-23556-4}},
volume = {{12}},
year = {{2021}},
}