Using genotype data to distinguish pleiotropy from heterogeneity: deciphering coheritability in autoimmune and neuropsychiatric diseases

Han, Baohui; Jg, Pouget; Slowikowski, Kamil; Stahl, Eli A.; Ch, Lee; Diogo, Dorothée; Hu, Xin; Yr, Park; Kim, Eun Jin; Gregersen, Peter; Dahqvist,; Worthington, Jane; Eyre, Stephen; Klareskog, Lars; Huizinga, Tom W J; Chen, W; Önengüt-Gümüşcü, Suna; Rich, Stephen S.; Wray, Naomi R.; Raychaudhuri, Soumya

doi:10.1101/030783

Cited by 6 publications

(10 citation statements)

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“…Heterogeneity can occur as the result of many different scenarios including diagnostic misclassifications, molecular subtypes, and excessive comorbidity. We evaluated whether pleiotropy or heterogeneity best explained the high comorbidity rates amongst the five diseases studied using BUHMBOX 20 (see Methods ). BUHMBOX detects heterogeneity by calculating the cross-locus correlation of disease B-associated loci among disease A cases; a non-zero correlation is indicative of heterogeneity 20 .…”

Section: Resultsmentioning

confidence: 99%

Analysis of five chronic inflammatory diseases identifies 27 new associations and highlights disease-specific patterns at shared loci

et al. 2016

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We simultaneously investigated the genetic landscape of ankylosing spondylitis, Crohn's disease, psoriasis, primary sclerosing cholangitis and ulcerative colitis to investigate pleiotropy and the relationship between these clinically related diseases. Using high-density genotype data from more than 86,000 individuals of European-ancestry we identified 244 independent multi-disease signals including 27 novel genome-wide significant susceptibility loci and 3 unreported shared risk loci. Complex pleiotropy was supported when contrasting multi-disease signals with expression data sets from human, rat and mouse, and epigenetic and expressed enhancer profiles. The comorbidities among the five immune diseases were best explained by biological pleiotropy rather than heterogeneity (a subgroup of cases that is genetically identical to another disease, possibly due to diagnostic misclassification, molecular subtypes, or excessive comorbidity). In particular, the strong comorbidity between primary sclerosing cholangitis and inflammatory bowel disease is likely the result of a unique disease, which is genetically distinct from classical inflammatory bowel disease phenotypes.

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Section: Resultsmentioning

confidence: 99%

Analysis of five chronic inflammatory diseases identifies 27 new associations and highlights disease-specific patterns at shared loci

et al. 2016

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“…Next, those phenotypes with significant genetic correlation with HIV acquisition were tested to see if they were driven by genome-wide pleiotropy or by overlap with a subset of HIV cases. Here, BUHMBOX was used to perform an analysis of heterogeneity within the cases 25 , making use of their known genome-wide significant SNPs. These SNPs came from the largest and most recent GWAS of these phenotypes, an analysis of 34,241 cases of schizophrenia 35 and of 86,640 cases of inflammatory bowel disease (which also included ulcerative colitis) 36 .…”

Section: Resultsmentioning

confidence: 99%

“…To better understand the cause of any genetic overlaps between HIV acquisition and genetically overlapping phenotypes, we used BUHMBOX to test if genetic correlations were driven by pleiotropy or heterogeneity 25 . BUHMBOX compares LD between known associated SNPs for trait-1 in both cases and controls for trait-2.…”

Section: Methodsmentioning

confidence: 99%

A genome-wide polygenic approach to HIV acquisition uncovers link to inflammatory bowel disease and identifies potential novel genetic variants

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et al. 2017

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Polygenic approaches using genome-wide data have been hugely successful in confirming and quantifying the heritability of complex human traits. Here, we highlight their ability to identify potential novel risk variants by looking for variants with pleiotropic effect in genetically overlapping phenotypes.We used LD Score Regression in a sample of 6,315 HIV+ European individuals and 7,247 controls to test for phenotypes genetically overlapping with susceptibility to HIV-1 infection. Using LD Hub, a web tool that performs LD Score Regression, identified two phenotypes with significant genetic overlap: schizophrenia (rG =0.19, p=0.0007 and ulcerative colitis (rG=0.22, p= 0.0061). We further showed that the genetic overlap between HIV acquisition and schizophrenia is likely driven in part by their shared overlap with cannabis use and sexual behavior. BUMHBOX analyses suggested that these genetic overlaps were driven by genome-wide pleiotropy with HIV acquisition rather than heterogeneity within the HIV acquisition sample. The two diseases identified as genetically overlapping with HIV-1 acquisition have >100 associated variants, and we tested if any of them significantly associated with HIV acquisition. We observed three variants that exceeded our threshold for statistical significance. Two of these were eQTLs in whole blood for genes coding for proteins suspected to be involved in HIV biology: rs1819333 in CCR6 (p=0.0002) and rs4932178 in FURIN (p=0.00033). However, no signal was found for these variants in two smaller African samples totaling 1015 cases and 963 controls, though the mode of acquisition and genetic architecture of these populations differed.These results highlight the ability to use polygenic methods to gain new insights into complex diseases and identify potential associations with individual variants. Crucially, the leveraging of existing, publically available data makes these methods a cost-effective approach. In this case, our results add to the evidence for the role of risk taking behavior and inflammation of the bowel in HIV acquisition.Author SummaryThe biology of what puts certain individuals at greater risk of HIV acquisition is poorly understood. Using several novel polygenic methods, we identify supporting evidence for two important factors leading to acquisition. First, the role of an individual’s genetic predisposition to risk taking behaviours such as number of sexual partners, age at first sexual intercourse drug use, and mental health problems. Second, the role of gut inflammation, in particular a genetic overlap between HIV acquisition with inflammatory bowel disease and the potential role of CCR6 during infection.

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“…Subsequent to our investigations [158] have developed another promising approach to investigate genetic heterogeneity. Their approach differs from the one presented here.…”

Section: Discussionmentioning

confidence: 99%

“…Some merely aimed at identifying the presence of genetic heterogeneity in a population [158], while others had the more ambitious goal of identifying genetic subtypes and grouping individuals accordingly [159]. However, while Arnedo et al [159] reported to find evidence for distinct schizophrenia subtypes, this claim has been heavily disputed on a number of grounds (see PubMed discussion at http://www.ncbi.nlm.nih.gov/pubmed/25219520).…”

Section: Introductionmentioning

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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Using genotype data to distinguish pleiotropy from heterogeneity: deciphering coheritability in autoimmune and neuropsychiatric diseases

Cited by 6 publications

References 42 publications

Analysis of five chronic inflammatory diseases identifies 27 new associations and highlights disease-specific patterns at shared loci

Analysis of five chronic inflammatory diseases identifies 27 new associations and highlights disease-specific patterns at shared loci

A genome-wide polygenic approach to HIV acquisition uncovers link to inflammatory bowel disease and identifies potential novel genetic variants

The genetic architecture of psychiatric disorders

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