A method to decipher pleiotropy by detecting underlying heterogeneity driven by hidden subgroups applied to autoimmune and neuropsychiatric diseases

Han, Buhm; Pouget, J; Slowikowski, Kamil; Stahl, Eli; Lee, Cue Hyunkyu; Diogo, Dorothée; Hu, Xinli; Park, Yu Rang; Kim, Eunji; Gregersen, Peter K.; Rantapää-Dahlqvist, Solbritt; Worthington, Jane; Martín, Javier; Eyre, Steve; Klareskog, Lars; Huizinga, Tom W J; Chen, Wei Min; Önengüt-Gümüşcü, Suna; Rich, Stephen S.; Wray, Naomi R.; Raychaudhuri, Soumya

doi:10.1038/ng.3572

Cited by 66 publications

(113 citation statements)

References 46 publications

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“…Using BUHMBOX21, a tool that distinguishes true genetic relationships between diseases (pleiotropy) from spurious relationships resulting from heterogeneous mixing of disease cohorts, we determined that misdiagnosed cases in the schizophrenia cohort (for example, young-onset FTD–ALS) did not drive the genetic correlation estimate between ALS and schizophrenia ( P =0.94). Assuming a true genetic correlation of 0%, we estimated the required rate of misdiagnosis of ALS as schizophrenia to be 4.86% (2.47–7.13) to obtain the genetic correlation estimate of 14.3% (7.05–21.6; Supplementary Table 7), which we consider to be too high to be likely.…”

Section: Resultsmentioning

confidence: 99%

“…To distinguish the contribution of misdiagnosis from true genetic pleiotropy we used BUHMBOX21 with 417 independent ALS risk alleles in a sample of 27,647 schizophrenia patients for which individual-level genotype data were available. We also estimated the required misdiagnosis rate M of FTD–ALS as schizophrenia that would lead to the observed genetic correlation estimate as C /( C +1), where C = ρ g N SCZ / N ALS and N SCZ and N ALS are the number of cases in the schizophrenia and ALS datasets, respectively37 (derived in Supplementary Methods 1).…”

Section: Methodsmentioning

confidence: 99%

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Genetic correlation between amyotrophic lateral sclerosis and schizophrenia

McLaughlin¹,

Schijven²,

Rheenen³

et al. 2017

Nat Commun

132

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We have previously shown higher-than-expected rates of schizophrenia in relatives of patients with amyotrophic lateral sclerosis (ALS), suggesting an aetiological relationship between the diseases. Here, we investigate the genetic relationship between ALS and schizophrenia using genome-wide association study data from over 100,000 unique individuals. Using linkage disequilibrium score regression, we estimate the genetic correlation between ALS and schizophrenia to be 14.3% (7.05–21.6; P=1 × 10−4) with schizophrenia polygenic risk scores explaining up to 0.12% of the variance in ALS (P=8.4 × 10−7). A modest increase in comorbidity of ALS and schizophrenia is expected given these findings (odds ratio 1.08–1.26) but this would require very large studies to observe epidemiologically. We identify five potential novel ALS-associated loci using conditional false discovery rate analysis. It is likely that shared neurobiological mechanisms between these two disorders will engender novel hypotheses in future preclinical and clinical studies.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Genetic correlation between amyotrophic lateral sclerosis and schizophrenia

McLaughlin¹,

Schijven²,

Rheenen³

et al. 2017

Nat Commun

132

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“…The Breaking Up Heterogeneous Mixture Based On cross(X)-locus correlations (BUHMBOX) analysis 71 was used to test whether the genetic correlation between persistent ADHD and ADHD in childhood was driven by subgroup heterogeneity, found when there is a subset of children enriched for persistent ADHD-associated alleles. Subgroup heterogeneity was tested in each childhood dataset considering two different SNP sets from the GWAS-MA of persistent ADHD, with P-value thresholds of P<5.00E-05 (62 LD-independent SNPs) and P<1.00E-03 (710 LDindependent SNPs).…”

Section: Buhmbox Analysismentioning

confidence: 99%

Shared genetic background between children and adults with attention deficit/hyperactivity disorder

Rovira¹,

Demontis²,

Sánchez-Mora³

et al. 2019

Preprint

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AbstractAttention deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder characterized by age-inappropriate symptoms of inattention, impulsivity and hyperactivity that persist into adulthood in the majority of the diagnosed children. Despite several risk factors during childhood predicting the persistence of ADHD symptoms into adulthood, the genetic architecture underlying the trajectory of ADHD over time is still unclear. We set out to study the contribution of common genetic variants to the risk for ADHD across the lifespan by conducting meta-analyses of genome-wide association studies on persistent ADHD in adults and ADHD in childhood separately and comparing the genetic background between them in a total sample of 17,149 cases and 32,411 controls. Our results show nine new independent loci and support a shared contribution of common genetic variants to ADHD in children and adults. No subgroup heterogeneity was observed among children, while this group consists of future remitting and persistent individuals. We report similar patterns of genetic correlation of ADHD with other ADHD-related datasets and different traits and disorders among adults, children and when combining both groups. These findings confirm that persistent ADHD in adults is a neurodevelopmental disorder and extend the existing hypothesis of a shared genetic architecture underlying ADHD and different traits to a lifespan perspective.

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“…For example, the simpler problem of detecting the presence of genetic heterogeneity seems to be more tractable [112], as is the task of detecting sub-groups by combining both genetic and non-genetic data. These nongenetic data could include traditional phenotypes, for example environmental covariates, or molecular phenotypes such as gene expression, DNA methylation, or other epigenetic modifications.…”

Section: Genetic Heterogeneitymentioning

confidence: 99%

“…The large number of combinations of risk loci, their small effect sizes, the uncertainty about the size or even about the presence of genetically heterogeneous groups, and the challenging disentanglement from population stratification all contribute to the difficulty of this problem. [112].…”

Section: Detection Of Genetic Heterogeneitymentioning

confidence: 99%

The genetic architecture of psychiatric disorders

Maier¹

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The genetic nature of psychiatric disorders was observed by clinicians long before DNA had been identified as the molecule of inheritance. The greatest identified risk factor of many psychiatric disorders still is a positive family history. Until recently this knowledge has not contributed substantially to treatment efforts or to a better understanding of the disease processes because we lacked the necessary genetic data. Advances in genotyping technologies have brought an end to this data shortage which is leading to a better understanding of the genetic architecture of psychiatric disorders. Two patterns started to emerge which were uncommon in earlier studied Mendelian disorders. (i) most of the genetic part of disease risk is conferred by a large number of genetic loci of small effect, and (ii) genetic loci often influence a large number of traits at the same time. While this is true of many traits ("complex" traits), these two phenomena (polygenicity and pleiotropy) are particularly pronounced in psychiatric disorders. This has wide-reaching consequences for the analysis and interpretation of genetic data and provides challenges as well as opportunities. This thesis focuses on two areas in particular: genetic heterogeneity and genetic risk prediction.Genetic heterogeneity in a phenotypically homogenous group describes a situation where different and distinct genetic risk profiles are causing similar symptoms in different people.This can be easily identified under a Mendelian inheritance pattern, but proves to be challenging under polygenicity. The presence of genetic heterogeneity can limit the accuracy of genetic risk prediction.The aim of genetic risk prediction is to use the information that has been gathered on the effects of genetic loci to estimate the genetic liability of an individual to develop a disease.Here, pleiotropy offers an opportunity to increase the accuracy of genetic prediction by leveraging information from multiple diseases at the same time.The aim in this thesis is to describe several projects which center around the two concepts of genetic risk prediction based on multiple traits and of genetic heterogeneity. Chapter 1 sets the scene with an overview of recently developed polygenic methods. Chapter 2 deals with the effects of genetic heterogeneity on heritability estimates and demonstrates how genetic heterogeneity might contribute to the phenomenon of missing heritability, which is 3 the discrepancy between twin study heritability estimates and the variance explained by the sum of individual genetic loci. Chapter 3 addresses the question of whether genotype clustering can detect groups with different genetic risk profiles. Chapter 4 describes the implementation of a multivariate extension to the univariate Best Linear Unbiased Prediction (BLUP) method and its application to five psychiatric traits. Chapters 4 and 5 investigate whether this multivariate BLUP model can be approximated when only summary statistics, not individual level genotype data, are available for the predi...

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A method to decipher pleiotropy by detecting underlying heterogeneity driven by hidden subgroups applied to autoimmune and neuropsychiatric diseases

Cited by 66 publications

References 46 publications

Genetic correlation between amyotrophic lateral sclerosis and schizophrenia

Genetic correlation between amyotrophic lateral sclerosis and schizophrenia

Shared genetic background between children and adults with attention deficit/hyperactivity disorder

The genetic architecture of psychiatric disorders

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