scholarly journals The Emerging Genetic Landscape of Hirschsprung Disease and Its Potential Clinical Applications

2021 ◽  
Vol 9 ◽  
Author(s):  
Anwarul Karim ◽  
Clara Sze-Man Tang ◽  
Paul Kwong-Hang Tam
Keyword(s):  
Complex Disease ◽  
Rare Variants ◽  
Hirschsprung Disease ◽  
Distal Colon ◽  
Population Based ◽  
Linkage Analyses ◽  
Sequencing Technologies ◽  
Enteric Ganglia ◽  
Genome Wide ◽  
Family Based

Hirschsprung disease (HSCR) is the leading cause of neonatal functional intestinal obstruction. It is a rare congenital disease with an incidence of one in 3,500–5,000 live births. HSCR is characterized by the absence of enteric ganglia in the distal colon, plausibly due to genetic defects perturbing the normal migration, proliferation, differentiation, and/or survival of the enteric neural crest cells as well as impaired interaction with the enteric progenitor cell niche. Early linkage analyses in Mendelian and syndromic forms of HSCR uncovered variants with large effects in major HSCR genes including RET, EDNRB, and their interacting partners in the same biological pathways. With the advances in genome-wide genotyping and next-generation sequencing technologies, there has been a remarkable progress in understanding of the genetic basis of HSCR in the past few years, with common and rare variants with small to moderate effects being uncovered. The discovery of new HSCR genes such as neuregulin and BACE2 as well as the deeper understanding of the roles and mechanisms of known HSCR genes provided solid evidence that many HSCR cases are in the form of complex polygenic/oligogenic disorder where rare variants act in the sensitized background of HSCR-associated common variants. This review summarizes the roadmap of genetic discoveries of HSCR from the earlier family-based linkage analyses to the recent population-based genome-wide analyses coupled with functional genomics, and how these discoveries facilitated our understanding of the genetic architecture of this complex disease and provide the foundation of clinical translation for precision and stratified medicine.

scholarly journals Deep genotype imputation captures virtually all heritability of autoimmune vitiligo

2020 ◽  
Vol 29 (5) ◽  
pp. 859-863 ◽  
Author(s):  
Genevieve H L Roberts ◽  
Stephanie A Santorico ◽  
Richard A Spritz
Keyword(s):  
Complex Disease ◽  
Rare Variants ◽  
Association Studies ◽  
Genotype Imputation ◽  
Genome Wide Association Studies ◽  
Common Variants ◽  
Genome Wide ◽  
Autoimmune Vitiligo ◽  
Family Based ◽  
Project Data

Abstract Autoimmune vitiligo is a complex disease involving polygenic risk from at least 50 loci previously identified by genome-wide association studies. The objectives of this study were to estimate and compare vitiligo heritability in European-derived patients using both family-based and ‘deep imputation’ genotype-based approaches. We estimated family-based heritability (h2FAM) by vitiligo recurrence among a total 8034 first-degree relatives (3776 siblings, 4258 parents or offspring) of 2122 unrelated vitiligo probands. We estimated genotype-based heritability (h2SNP) by deep imputation to Haplotype Reference Consortium and the 1000 Genomes Project data in unrelated 2812 vitiligo cases and 37 079 controls genotyped genome wide, achieving high-quality imputation from markers with minor allele frequency (MAF) as low as 0.0001. Heritability estimated by both approaches was exceedingly high; h2FAM = 0.75–0.83 and h2SNP = 0.78. These estimates are statistically identical, indicating there is essentially no remaining ‘missing heritability’ for vitiligo. Overall, ~70% of h2SNP is represented by common variants (MAF > 0.01) and 30% by rare variants. These results demonstrate that essentially all vitiligo heritable risk is captured by array-based genotyping and deep imputation. These findings suggest that vitiligo may provide a particularly tractable model for investigation of complex disease genetic architecture and predictive aspects of personalized medicine.

scholarly journals Identifying the phenotypic effect of rare variants by including between-pedigree coancestry in variance components linkage analysis

2017 ◽  
Author(s):  
J.E. Hicks ◽  
M. A. Province
Keyword(s):  
Linkage Analysis ◽  
Variance Components ◽  
Rare Variants ◽  
Simulated Data ◽  
Population Based ◽  
Pedigree Information ◽  
Phenotypic Effect ◽  
Sequencing Technologies ◽  
Variance Components Analysis ◽  
Family Based

AbstractThe contribution of rare variants to disease burden has become an important focus in genetic epidemiology. These effects are difficult to detect in population-based datasets, and as a result, interest in family-based study designs has resurfaced. Linkage analysis tools will need to be updated to accommodate the scale of data generated by modern genotyping and sequencing technologies.In conventional linkage analysis individuals in different pedigrees are assumed to be independent of each other. However, cryptic relatedness is often present in populations and haplotypes that harbor rare variants may be shared between pedigrees as well as within them.With millions of polymorphisms, Identity-by-descent (IBD) states across the genome can now be inferred without use of pedigree information. This is done by identifying long runs of identical-by-state genotypes which are unlikely to arise without IBD. Previously, IBD had to be estimated in pedigrees from recombination events in a sparse set of markers.We present a method for variance-components linkage that can incorporate large number of markers and allows for between-pedigree relatedness. We replace the IBD matrix generated from pedigree-based analysis with one generated from a genotype-based method. All pedigrees in a dataset are considered jointly, allowing between-pedigree IBD to be included in the model.In simulated data, we show that power is increased in the scenario when there is a haplotype shared IBD between members of different pedigrees. If there is no between-pedigree IBD, the analysis reduces to conventional variance-components analysis. By determining IBD states by long runs of dense IBS genotypes, linkage signals can be determined from their physical position, allowing more precise localization.

Abstract 12: Heritability of Ischemic Stroke and its Subtypes

Stroke ◽  
2012 ◽  
Vol 43 (suppl_1) ◽  
Author(s):  
Andrew E Bluher ◽  
Michael A Nalls ◽  
John W Cole ◽  
Pankaj Sharma ◽  
James F Meschia ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Fixed Effects ◽  
Rare Variants ◽  
Phenotypic Variability ◽  
Fixed Effects Model ◽  
Stroke Subtype ◽  
Genome Wide ◽  
Weighted Means ◽  
Family Based ◽  
And Gender

Background and Purpose: Family-based methods for estimating heritability cannot discriminate between shared genetic and shared environmental exposures. Recently, methods have been developed for estimating heritability in population samples using genome-wide SNPs. We used the approach developed by Visscher and colleagues to estimate the heritability of ischemic stroke in Caucasian subjects. In addition to evaluating the overall heritability of ischemic stroke, we assessed whether stroke heritability varies by age, gender, and stroke subtype. Methods: Using publicly available software (GCTA and PLINK), we estimated ischemic stroke heritability stratified by age and gender using genome-wide association (GWA) data from three Caucasian ischemic stroke studies: Ischemic Stroke Genetics Study (ISGS), Bio-Repository of DNA in Stroke (BRAINS), and Genetics of Early-Onset Stroke (GEOS). Weighted means of site-specific heritability point estimates were combined according to a standard fixed effects model. Results: Conclusions: A SNP-based approach may be useful in discerning differences in ischemic stroke heritability between different cohorts and subtypes. Overall, our analysis estimated ischemic stroke heritability to be 31% (SE = 7%), with a suggestion of higher heritability for younger cases. Small vessel stroke showed the highest heritability (58 ± 19%), with cardioembolic showing the lowest heritability (16 ± 14%). It should be emphasized that heritability estimates are population-specific and that the method used only reflects the heritability captured by common SNP variants measured in GWA studies, and not phenotypic variability explained by rare variants.

scholarly journals A novel variant in GLIS3 is associated with osteoarthritis

2018 ◽  
Vol 77 (4) ◽  
pp. 620-623 ◽  
Author(s):  
Elisabetta Casalone ◽  
Ioanna Tachmazidou ◽  
Eleni Zengini ◽  
Konstantinos Hatzikotoulas ◽  
Sophie Hackinger ◽  
...  
Keyword(s):  
Complex Disease ◽  
Genome Wide Association Study ◽  
Total Joint Replacement ◽  
Population Based ◽  
Uk Biobank ◽  
Proteomics Data ◽  
Glucose Levels ◽  
Genome Wide ◽  
A Genome ◽  
The Uk

ObjectivesOsteoarthritis (OA) is a complex disease, but its genetic aetiology remains poorly characterised. To identify novel susceptibility loci for OA, we carried out a genome-wide association study (GWAS) in individuals from the largest UK-based OA collections to date.MethodsWe carried out a discovery GWAS in 5414 OA individuals with knee and/or hip total joint replacement (TJR) and 9939 population-based controls. We followed-up prioritised variants in OA subjects from the interim release of the UK Biobank resource (up to 12 658 cases and 50 898 controls) and our lead finding in operated OA subjects from the full release of UK Biobank (17 894 cases and 89 470 controls). We investigated its functional implications in methylation, gene expression and proteomics data in primary chondrocytes from 12 pairs of intact and degraded cartilage samples from patients undergoing TJR.ResultsWe detect a genome-wide significant association at rs10116772 with TJR (P=3.7×10−8; for allele A: OR (95% CI) 0.97 (0.96 to 0.98)), an intronic variant in GLIS3, which is expressed in cartilage. Variants in strong correlation with rs10116772 have been associated with elevated plasma glucose levels and diabetes.ConclusionsWe identify a novel susceptibility locus for OA that has been previously implicated in diabetes and glycaemic traits.

scholarly journals Targeted resequencing identifies genes with recurrent variation in cerebral palsy

2019 ◽  
Vol 4 (1) ◽  
Author(s):  
C. L. van Eyk ◽  
M. A. Corbett ◽  
M. S. B. Frank ◽  
D. L. Webber ◽  
M. Newman ◽  
...  
Keyword(s):  
Cerebral Palsy ◽  
Rare Variants ◽  
Neurodevelopmental Disorder ◽  
Genetic Determinants ◽  
Zebrafish Model ◽  
Sequencing Technologies ◽  
Genome Wide ◽  
A Genome ◽  
Significant Burden ◽  
Generation Sequencing

Abstract A growing body of evidence points to a considerable and heterogeneous genetic aetiology of cerebral palsy (CP). To identify recurrently variant CP genes, we designed a custom gene panel of 112 candidate genes. We tested 366 clinically unselected singleton cases with CP, including 271 cases not previously examined using next-generation sequencing technologies. Overall, 5.2% of the naïve cases (14/271) harboured a genetic variant of clinical significance in a known disease gene, with a further 4.8% of individuals (13/271) having a variant in a candidate gene classified as intolerant to variation. In the aggregate cohort of individuals from this study and our previous genomic investigations, six recurrently hit genes contributed at least 4% of disease burden to CP: COL4A1, TUBA1A, AGAP1, L1CAM, MAOB and KIF1A. Significance of Rare VAriants (SORVA) burden analysis identified four genes with a genome-wide significant burden of variants, AGAP1, ERLIN1, ZDHHC9 and PROC, of which we functionally assessed AGAP1 using a zebrafish model. Our investigations reinforce that CP is a heterogeneous neurodevelopmental disorder with known as well as novel genetic determinants.

scholarly journals Mitochondrial genome-wide association study of migraine – the HUNT Study

Cephalalgia ◽  
2020 ◽  
Vol 40 (6) ◽  
pp. 625-634 ◽  
Author(s):  
Sigrid Børte ◽  
John-Anker Zwart ◽  
Anne Heidi Skogholt ◽  
Maiken Elvestad Gabrielsen ◽  
Laurent F Thomas ◽  
...  
Keyword(s):  
Mitochondrial Dna ◽  
Mitochondrial Genome ◽  
Association Study ◽  
Genome Wide Association Study ◽  
Rare Variants ◽  
Population Based ◽  
Genome Wide Association ◽  
Health Study ◽  
Genome Wide ◽  
Number Variation

Background Variation in mitochondrial DNA (mtDNA) has been indicated in migraine pathogenesis, but genetic studies to date have focused on candidate variants, with sparse findings. We aimed to perform the first mitochondrial genome-wide association study of migraine, examining both single variants and mitochondrial haplogroups. Methods In total, 71,860 participants from the population-based Nord-Trøndelag Health Study were genotyped. We excluded samples not passing quality control for nuclear genotypes, in addition to samples with low call rate and closely maternally related. We analysed 775 mitochondrial DNA variants in 4021 migraine cases and 14,288 headache-free controls, using logistic regression. In addition, we analysed 3831 cases and 13,584 controls who could be reliably assigned to a mitochondrial haplogroup. Lastly, we attempted to replicate previously reported mitochondrial DNA candidate variants. Results Neither of the mitochondrial variants or haplogroups were associated with migraine. In addition, none of the previously reported mtDNA candidate variants replicated in our data. Conclusions Our findings do not support a major role of mitochondrial genetic variation in migraine pathophysiology, but a larger sample is needed to detect rare variants and future studies should also examine heteroplasmic variation, epigenetic changes and copy-number variation.

scholarly journals Subtle stratification confounds estimates of heritability from rare variants

2016 ◽  
Author(s):  
Gaurav Bhatia ◽  
Alexander Gusev ◽  
Po-Ru Loh ◽  
Hilary Finucane ◽  
Bjarni J. Vilhjálmsson ◽  
...  
Keyword(s):  
Small Proportion ◽  
Population Stratification ◽  
Complex Disease ◽  
Rare Variants ◽  
Case Control ◽  
Narrow Sense ◽  
Narrow Sense Heritability ◽  
Severe Problem ◽  
Potential Source ◽  
Genome Wide

AbstractGenome-wide significant associations generally explain only a small proportion of the narrow-sense heritability of complex disease (h2). While considerably more heritability is explained by all genotyped SNPs (hg2), for most traits, much heritability remains missing (hg2 < h2). Rare variants, poorly tagged by genotyped SNPs, are a major potential source of the gap between hg2 and h2. Recent efforts to assess the contribution of both sequenced and imputed rare variants to phenotypes suggest that substantial heritability may lie in these variants. Here we analyze sequenced SNPs, imputed SNPs and haploSNPs— haplotype variants constructed from within a sample, without using a reference panel— and show that studies of heritability from these variants may be strongly confounded by subtle population stratification. For example, when meta-analyzing heritability estimates from 22 randomly ascertained case-control traits from the GERA cohort, we observe a statistically significant increase in heritability explained by imputed SNPs even after correcting for principal components (PCs) from genotyped (or imputed) SNPs. However, this increase is eliminated when correcting for stratification using PCs from a larger number of haploSNPs. We note that subtle stratification may also impact estimates of heritability from array SNPs, although we find that this is generally a less severe problem. Overall, our results suggest that estimating the heritability explained by rare variants for case-control traits requires exquisite control for population stratification, but current methods may not provide this level of control.

Sign in / Sign up

Export Citation Format

Share Document