Family-based exome-sequencing approach identifies rare susceptibility variants for lithium-responsive bipolar disorder

Genome ◽  
2013 ◽  
Vol 56 (10) ◽  
pp. 634-640 ◽  
Author(s):  
Cristiana Cruceanu ◽  
Amirthagowri Ambalavanan ◽  
Dan Spiegelman ◽  
Julie Gauthier ◽  
Ronald G. Lafrenière ◽  
...  

Bipolar disorder (BD) is a psychiatric condition characterized by the occurrence of at least two episodes of clinically disturbed mood including mania and depression. A vast literature describing BD studies suggests that a strong genetic contribution likely underlies this condition; heritability is estimated to be as high as 80%. Many studies have identified BD susceptibility loci, but because of the genetic and phenotypic heterogeneity observed across individuals, very few loci were subsequently replicated. Research in BD genetics to date has consisted of classical linkage or genome-wide association studies, which have identified candidate genes hypothesized to present common susceptibility variants. Although the observation of such common variants is informative, they can only explain a small fraction of the predicted BD heritability, suggesting a considerable contribution would come from rare and highly penetrant variants. We are seeking to identify such rare variants, and to increase the likelihood of being successful, we aimed to reduce the phenotypic heterogeneity factor by focusing on a well-defined subphenotype of BD: excellent response to lithium monotherapy. Our group has previously shown positive response to lithium therapy clusters in families and has a consistent clinical presentation with minimal comorbidity. To identify such rare variants, we are using a targeted exome capture and high-throughput DNA sequencing approach, and analyzing the entire coding sequences of BD affected individuals from multigenerational families. We are prioritizing rare variants with a frequency of less than 1% in the population that segregate with affected status within each family, as well as being potentially highly penetrant (e.g., protein truncating, missense, or frameshift) or functionally relevant (e.g., 3′UTR, 5′UTR, or splicing). By focusing on rare variants in a familial cohort, we hope to explain a significant portion of the missing heritability in BD, as well as to narrow our current insight on the key biochemical pathways implicated in this complex disorder.

2020 ◽  
Vol 29 (5) ◽  
pp. 859-863 ◽  
Author(s):  
Genevieve H L Roberts ◽  
Stephanie A Santorico ◽  
Richard A Spritz

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.


2018 ◽  
Author(s):  
Suhas Ganesh ◽  
Ahmed P Husayn ◽  
Ravi Kumar Nadella ◽  
Ravi Prabhakar More ◽  
Manasa Sheshadri ◽  
...  

AbstractIntroductionSevere Mental Illnesses (SMI), such as bipolar disorder and schizophrenia, are highly heritable, and have a complex pattern of inheritance. Genome wide association studies detect a part of the heritability, which can be attributed to common genetic variation. Examination of rare variants with Next Generation Sequencing (NGS) may add to the understanding of genetic architecture of SMIs.MethodsWe analyzed 32 ill subjects (with diagnosis of Bipolar Disorder, n=26; schizophrenia, n=4; schizoaffective disorder, n=1 schizophrenia like psychosis, n=1) from 8 multiplex families; and 33 healthy individuals by whole exome sequencing. Prioritized variants were selected by a 4-step filtering process, which included deleteriousness by 5 in silico algorithms; sharing within families, absence in the controls and rarity in South Asian sample of Exome Aggregation Consortium.ResultsWe identified a total of 42 unique rare, non-synonymous deleterious variants in this study with an average of 5 variants per family. None of the variants were shared across families, indicating a ‘private’ mutational profile. Twenty (47.6%) of the variant harboring genes identified in this sample have been previously reported to contribute to the risk of neuropsychiatric syndromes. These include genes which are related to neurodevelopmental processes, or have been implicated in different monogenic syndromes with a severe neurodevelopmental phenotype.ConclusionNGS approaches in family based studies are useful to identify novel and rare variants in genes for complex disorders like SMI. The study further validates the phenotypic burden of rare variants in Mendelian disease genes, indicating pleiotropic effects in the etiology of severe mental illnesses.


2019 ◽  
Author(s):  
Ehsan Ullah ◽  
Khalid Kunji ◽  
Ellen M. Wijsman ◽  
Mohamad Saad

AbstractMotivationImputation of untyped SNPs has become important in Genome-wide Association Studies (GWAS). There has also been a trend towards analyzing rare variants, driven by the decrease of genome sequencing costs. Rare variants are enriched in pedigrees that have many cases or extreme phenotypes. This is especially the case for large pedigrees, which makes family-based designs ideal to detect rare variants associated with complex traits. The costs of performing relatively large family-based GWAS can be significantly reduced by fully sequencing only a fraction of the pedigree and performing imputation on the remaining subjects. The program GIGI can efficiently perform imputation in large pedigrees but can be time consuming. Here, we implement GIGI’s imputation approach in a new program, GIGI2, which performs imputation with computational time reduced by at least 25x on one thread and 120x on eight threads. The memory usage of GIGI2 is reduced by at least 30x. This reduction is achieved by implementing better memory layout and a better algorithm for solving the Identity by Descent graphs, as well as with additional features, including multithreading. We also make GIGI2 available as a webserver based on the same framework as the Michigan Imputation Server.AvailabilityGIGI2 is freely available online at https://cse-git.qcri.org/eullah/GIGI2 and the websever is at https://imputation.qcri.org/[email protected]


Nature ◽  
2021 ◽  
Vol 590 (7845) ◽  
pp. 290-299 ◽  
Author(s):  
Daniel Taliun ◽  
◽  
Daniel N. Harris ◽  
Michael D. Kessler ◽  
Jedidiah Carlson ◽  
...  

AbstractThe Trans-Omics for Precision Medicine (TOPMed) programme seeks to elucidate the genetic architecture and biology of heart, lung, blood and sleep disorders, with the ultimate goal of improving diagnosis, treatment and prevention of these diseases. The initial phases of the programme focused on whole-genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here we describe the TOPMed goals and design as well as the available resources and early insights obtained from the sequence data. The resources include a variant browser, a genotype imputation server, and genomic and phenotypic data that are available through dbGaP (Database of Genotypes and Phenotypes)1. In the first 53,831 TOPMed samples, we detected more than 400 million single-nucleotide and insertion or deletion variants after alignment with the reference genome. Additional previously undescribed variants were detected through assembly of unmapped reads and customized analysis in highly variable loci. Among the more than 400 million detected variants, 97% have frequencies of less than 1% and 46% are singletons that are present in only one individual (53% among unrelated individuals). These rare variants provide insights into mutational processes and recent human evolutionary history. The extensive catalogue of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and noncoding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and reach of genome-wide association studies to include variants down to a frequency of approximately 0.01%.


2021 ◽  
Vol 14 (4) ◽  
pp. 287
Author(s):  
Courtney M. Vecera ◽  
Gabriel R. Fries ◽  
Lokesh R. Shahani ◽  
Jair C. Soares ◽  
Rodrigo Machado-Vieira

Despite being the most widely studied mood stabilizer, researchers have not confirmed a mechanism for lithium’s therapeutic efficacy in Bipolar Disorder (BD). Pharmacogenomic applications may be clinically useful in the future for identifying lithium-responsive patients and facilitating personalized treatment. Six genome-wide association studies (GWAS) reviewed here present evidence of genetic variations related to lithium responsivity and side effect expression. Variants were found on genes regulating the glutamate system, including GAD-like gene 1 (GADL1) and GRIA2 gene, a mutually-regulated target of lithium. In addition, single nucleotide polymorphisms (SNPs) discovered on SESTD1 may account for lithium’s exceptional ability to permeate cell membranes and mediate autoimmune and renal effects. Studies also corroborated the importance of epigenetics and stress regulation on lithium response, finding variants on long, non-coding RNA genes and associations between response and genetic loading for psychiatric comorbidities. Overall, the precision medicine model of stratifying patients based on phenotype seems to derive genotypic support of a separate clinical subtype of lithium-responsive BD. Results have yet to be expounded upon and should therefore be interpreted with caution.


Author(s):  
Navnit S. Makaram ◽  
Stuart H. Ralston

Abstract Purpose of Review To provide an overview of the role of genes and loci that predispose to Paget’s disease of bone and related disorders. Recent Findings Studies over the past ten years have seen major advances in knowledge on the role of genetic factors in Paget’s disease of bone (PDB). Genome wide association studies have identified six loci that predispose to the disease whereas family based studies have identified a further eight genes that cause PDB. This brings the total number of genes and loci implicated in PDB to fourteen. Emerging evidence has shown that a number of these genes also predispose to multisystem proteinopathy syndromes where PDB is accompanied by neurodegeneration and myopathy due to the accumulation of abnormal protein aggregates, emphasising the importance of defects in autophagy in the pathogenesis of PDB. Summary Genetic factors play a key role in the pathogenesis of PDB and the studies in this area have identified several genes previously not suspected to play a role in bone metabolism. Genetic testing coupled to targeted therapeutic intervention is being explored as a way of halting disease progression and improving outcome before irreversible skeletal damage has occurred.


2020 ◽  
Author(s):  
Celine Charon ◽  
Rodrigue Allodji ◽  
Vincent Meyer ◽  
Jean-François Deleuze

Abstract Quality control methods for genome-wide association studies and fine mapping are commonly used for imputation, however, they result in loss of many single nucleotide polymorphisms (SNPs). To investigate the consequences of filtration on imputation, we studied the direct effects on the number of markers, their allele frequencies, imputation quality scores and post-filtration events. We pre-phrased 1,031 genotyped individuals from diverse ethnicities and compared the imputed variants to 1,089 NCBI recorded individuals for additional validation.Without variant pre-filtration based on quality control (QC), we observed no impairment in the imputation of SNPs that failed QC whereas with pre-filtration there was an overall loss of information. Significant differences between frequencies with and without pre-filtration were found only in the range of very rare (5E-04-1E-03) and rare variants (1E-03-5E-03) (p < 1E-04). Increasing the post-filtration imputation quality score from 0.3 to 0.8 reduced the number of single nucleotide variants (SNVs) <0.001 2.5 fold with or without QC pre-filtration and halved the number of very rare variants (5E-04). As a result, to maintain confidence and enough SNVs, we propose here a 2-step post-filtration approach to increase the number of very rare and rare variants compared to conservative post-filtration methods.


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