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A method to decipher pleiotropy by detecting underlying heterogeneity driven by hidden subgroups applied to autoimmune and neuropsychiatric diseases
by
Pouget, Jennie G
, Klareskog, Lars
, Rich, Stephen S
, Park, Yu Rang
, Chen, Wei-Min
, Gregersen, Peter K
, Worthington, Jane
, Hu, Xinli
, Wray, Naomi R
, Eyre, Steve
, Martin, Javier
, Huizinga, Tom
, Slowikowski, Kamil
, Dahlqvist, Solbritt Rantapää
, Han, Buhm
, Raychaudhuri, Soumya
, Stahl, Eli
, Lee, Cue Hyunkyu
, Diogo, Dorothee
, Kim, Eunji
, Onengut-Gumuscu, Suna
in
45
/ 631/114/2164
/ 631/208/205/2138
/ 631/378
/ 631/553/1833
/ Agriculture
/ Animal Genetics and Genomics
/ Arthritis, Rheumatoid - genetics
/ Autoimmune diseases
/ Autoimmune Diseases - genetics
/ Biomedicine
/ Cancer Research
/ Charitable foundations
/ Computational Biology
/ Databases, Genetic
/ Depressive Disorder, Major - genetics
/ Diabetes
/ Diabetes Mellitus, Type 1 - genetics
/ Disease
/ Gene expression
/ Gene Expression Regulation
/ Gene Function
/ Genetic aspects
/ Genetic Markers - genetics
/ Genetic Pleiotropy - genetics
/ Genetic Predisposition to Disease
/ Genomes
/ Genotype
/ Health aspects
/ Health risk assessment
/ Heterogeneity
/ Human Genetics
/ Humans
/ Identification and classification
/ Mental depression
/ Mental disorders
/ Mental illness
/ Methods
/ Models, Statistical
/ Pleiotropy
/ Polymorphism, Single Nucleotide - genetics
/ Rheumatoid arthritis
/ Risk factors
/ Risk sharing
/ Studies
/ technical-report
2016
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A method to decipher pleiotropy by detecting underlying heterogeneity driven by hidden subgroups applied to autoimmune and neuropsychiatric diseases
by
Pouget, Jennie G
, Klareskog, Lars
, Rich, Stephen S
, Park, Yu Rang
, Chen, Wei-Min
, Gregersen, Peter K
, Worthington, Jane
, Hu, Xinli
, Wray, Naomi R
, Eyre, Steve
, Martin, Javier
, Huizinga, Tom
, Slowikowski, Kamil
, Dahlqvist, Solbritt Rantapää
, Han, Buhm
, Raychaudhuri, Soumya
, Stahl, Eli
, Lee, Cue Hyunkyu
, Diogo, Dorothee
, Kim, Eunji
, Onengut-Gumuscu, Suna
in
45
/ 631/114/2164
/ 631/208/205/2138
/ 631/378
/ 631/553/1833
/ Agriculture
/ Animal Genetics and Genomics
/ Arthritis, Rheumatoid - genetics
/ Autoimmune diseases
/ Autoimmune Diseases - genetics
/ Biomedicine
/ Cancer Research
/ Charitable foundations
/ Computational Biology
/ Databases, Genetic
/ Depressive Disorder, Major - genetics
/ Diabetes
/ Diabetes Mellitus, Type 1 - genetics
/ Disease
/ Gene expression
/ Gene Expression Regulation
/ Gene Function
/ Genetic aspects
/ Genetic Markers - genetics
/ Genetic Pleiotropy - genetics
/ Genetic Predisposition to Disease
/ Genomes
/ Genotype
/ Health aspects
/ Health risk assessment
/ Heterogeneity
/ Human Genetics
/ Humans
/ Identification and classification
/ Mental depression
/ Mental disorders
/ Mental illness
/ Methods
/ Models, Statistical
/ Pleiotropy
/ Polymorphism, Single Nucleotide - genetics
/ Rheumatoid arthritis
/ Risk factors
/ Risk sharing
/ Studies
/ technical-report
2016
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A method to decipher pleiotropy by detecting underlying heterogeneity driven by hidden subgroups applied to autoimmune and neuropsychiatric diseases
by
Pouget, Jennie G
, Klareskog, Lars
, Rich, Stephen S
, Park, Yu Rang
, Chen, Wei-Min
, Gregersen, Peter K
, Worthington, Jane
, Hu, Xinli
, Wray, Naomi R
, Eyre, Steve
, Martin, Javier
, Huizinga, Tom
, Slowikowski, Kamil
, Dahlqvist, Solbritt Rantapää
, Han, Buhm
, Raychaudhuri, Soumya
, Stahl, Eli
, Lee, Cue Hyunkyu
, Diogo, Dorothee
, Kim, Eunji
, Onengut-Gumuscu, Suna
in
45
/ 631/114/2164
/ 631/208/205/2138
/ 631/378
/ 631/553/1833
/ Agriculture
/ Animal Genetics and Genomics
/ Arthritis, Rheumatoid - genetics
/ Autoimmune diseases
/ Autoimmune Diseases - genetics
/ Biomedicine
/ Cancer Research
/ Charitable foundations
/ Computational Biology
/ Databases, Genetic
/ Depressive Disorder, Major - genetics
/ Diabetes
/ Diabetes Mellitus, Type 1 - genetics
/ Disease
/ Gene expression
/ Gene Expression Regulation
/ Gene Function
/ Genetic aspects
/ Genetic Markers - genetics
/ Genetic Pleiotropy - genetics
/ Genetic Predisposition to Disease
/ Genomes
/ Genotype
/ Health aspects
/ Health risk assessment
/ Heterogeneity
/ Human Genetics
/ Humans
/ Identification and classification
/ Mental depression
/ Mental disorders
/ Mental illness
/ Methods
/ Models, Statistical
/ Pleiotropy
/ Polymorphism, Single Nucleotide - genetics
/ Rheumatoid arthritis
/ Risk factors
/ Risk sharing
/ Studies
/ technical-report
2016
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A method to decipher pleiotropy by detecting underlying heterogeneity driven by hidden subgroups applied to autoimmune and neuropsychiatric diseases
Journal Article
A method to decipher pleiotropy by detecting underlying heterogeneity driven by hidden subgroups applied to autoimmune and neuropsychiatric diseases
2016
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Overview
Soumya Raychaudhuri, Buhm Han and colleagues present a statistical method to distinguish whether shared genetic risk variants among complex traits are driven by whole-group pleiotropy or a subset of individuals who constitute a genetically heterogeneous subgroup. They use the method to examine genetic sharing among autoimmune diseases and between major depressive disorder and schizophrenia and find that most genetic sharing cannot be explained by subgroup heterogeneity but that, in contrast, seronegative rheumatoid arthritis is a heterogeneous condition.
There is growing evidence of shared risk alleles for complex traits (pleiotropy), including autoimmune and neuropsychiatric diseases. This might be due to sharing among all individuals (whole-group pleiotropy) or a subset of individuals in a genetically heterogeneous cohort (subgroup heterogeneity). Here we describe the use of a well-powered statistic, BUHMBOX, to distinguish between those two situations using genotype data. We observed a shared genetic basis for 11 autoimmune diseases and type 1 diabetes (T1D;
P
< 1 × 10
−4
) and for 11 autoimmune diseases and rheumatoid arthritis (RA;
P
< 1 × 10
−3
). This sharing was not explained by subgroup heterogeneity (corrected
P
BUHMBOX
> 0.2; 6,670 T1D cases and 7,279 RA cases). Genetic sharing between seronegative and seropostive RA (
P
< 1 × 10
−9
) had significant evidence of subgroup heterogeneity, suggesting a subgroup of seropositive-like cases within seronegative cases (
P
BUHMBOX
= 0.008; 2,406 seronegative RA cases). We also observed a shared genetic basis for major depressive disorder (MDD) and schizophrenia (
P
< 1 × 10
−4
) that was not explained by subgroup heterogeneity (
P
BUHMBOX
= 0.28; 9,238 MDD cases).
Publisher
Nature Publishing Group US,Nature Publishing Group
Subject
/ 631/378
/ Animal Genetics and Genomics
/ Arthritis, Rheumatoid - genetics
/ Autoimmune Diseases - genetics
/ Depressive Disorder, Major - genetics
/ Diabetes
/ Diabetes Mellitus, Type 1 - genetics
/ Disease
/ Genetic Pleiotropy - genetics
/ Genetic Predisposition to Disease
/ Genomes
/ Genotype
/ Humans
/ Identification and classification
/ Methods
/ Polymorphism, Single Nucleotide - genetics
/ Studies
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