Rare-variant collapsing analyses of arterial hypertension in the UK biobank.
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ABSTRACT:
SUBMITTER: Zoller B
PROVIDER: S-EPMC10632123 | biostudies-literature | 2023 Nov
REPOSITORIES: biostudies-literature
Publications
Rare-variant collapsing analyses of arterial hypertension in the UK biobank.
Zöller Bengt B Manderstedt Eric E Lind-Halldén Christina C Halldén Christer C
Journal of human hypertension 20230414 11
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Project description:Exome association studies to date have generally been underpowered to systematically evaluate the phenotypic impact of very rare coding variants. We leveraged extensive haplotype sharing between 49,960 exome-sequenced UK Biobank participants and the remainder of the cohort (total n ≈ 500,000) to impute exome-wide variants with accuracy R2 > 0.5 down to minor allele frequency (MAF) ~0.00005. Association and fine-mapping analyses of 54 quantitative traits identified 1,189 significant associations (P < 5 × 10-8) involving 675 distinct rare protein-altering variants (MAF < 0.01) that passed stringent filters for likely causality. Across all traits, 49% of associations (578/1,189) occurred in genes with two or more hits; follow-up analyses of these genes identified allelic series containing up to 45 distinct 'likely-causal' variants. Our results demonstrate the utility of within-cohort imputation in population-scale genome-wide association studies, provide a catalog of likely-causal, large-effect coding variant associations and foreshadow the insights that will be revealed as genetic biobank studies continue to grow.
| S-EPMC8349845 | biostudies-literature
Project description:BackgroundAcute respiratory distress syndrome (ARDS) could account for a considerable proportion of neonatal death, while the genetic etiology and pathophysiology of neonatal ARDS remain elusive. In this case-control study, 515 neonates were enrolled in the China Neonatal Genomes Project (CNGP, NCT03931707) from August 2016 to June 2021, including 196 ARDS and 319 non-ARDS matched by sex, gestational age, birth weight, perinatal asphyxia, pneumonia, sepsis, and necrotizing enterocolitis. Clinical exome sequencing was used to detect genetic variants. Collapsing analyses together with permutation tests were used to identify ARDS risk genes enriched for rare variants in ARDS samples. In silico functional interaction analysis and expression pattern studies at different stages of lung development were used to investigate the biological functions of the risk genes.ResultsCollapsing analyses identified that rare variants were significantly abundant in the genes associated with the precursor of the lamellar body and there were eight predicted risk genes with strong confidence (P < 0.01). Among them, the expression of EDNRB increased significantly in lung development and was up-regulated in ARDS (P < 0.05). In addition, 151 predicted transcriptional target proteins of EDNRB were highly enriched in the lamellar body responsible for pulmonary surfactant storage and secretion.ConclusionsIn our study, the genes associated with pulmonary surfactant storage and release were highly enriched with rare variants. A novel neonatal ARDS risk gene EDNRB may be a key gene for neonatal lung development and pulmonary surfactant homeostasis. Additional validation in independent patient populations and further exploration of underlying molecular mechanisms are warranted.
| S-EPMC9486038 | biostudies-literature
Project description:Integrating human genomics and proteomics can help elucidate disease mechanisms, identify clinical biomarkers and discover drug targets1-4. Because previous proteogenomic studies have focused on common variation via genome-wide association studies, the contribution of rare variants to the plasma proteome remains largely unknown. Here we identify associations between rare protein-coding variants and 2,923 plasma protein abundances measured in 49,736 UK Biobank individuals. Our variant-level exome-wide association study identified 5,433 rare genotype-protein associations, of which 81% were undetected in a previous genome-wide association study of the same cohort5. We then looked at aggregate signals using gene-level collapsing analysis, which revealed 1,962 gene-protein associations. Of the 691 gene-level signals from protein-truncating variants, 99.4% were associated with decreased protein levels. STAB1 and STAB2, encoding scavenger receptors involved in plasma protein clearance, emerged as pleiotropic loci, with 77 and 41 protein associations, respectively. We demonstrate the utility of our publicly accessible resource through several applications. These include detailing an allelic series in NLRC4, identifying potential biomarkers for a fatty liver disease-associated variant in HSD17B13 and bolstering phenome-wide association studies by integrating protein quantitative trait loci with protein-truncating variants in collapsing analyses. Finally, we uncover distinct proteomic consequences of clonal haematopoiesis (CH), including an association between TET2-CH and increased FLT3 levels. Our results highlight a considerable role for rare variation in plasma protein abundance and the value of proteogenomics in therapeutic discovery.
| S-EPMC10567546 | biostudies-literature
Project description:Genome-wide association studies have uncovered thousands of common variants associated with human disease, but the contribution of rare variants to common disease remains relatively unexplored. The UK Biobank contains detailed phenotypic data linked to medical records for approximately 500,000 participants, offering an unprecedented opportunity to evaluate the effect of rare variation on a broad collection of traits1,2. Here we study the relationships between rare protein-coding variants and 17,361 binary and 1,419 quantitative phenotypes using exome sequencing data from 269,171 UK Biobank participants of European ancestry. Gene-based collapsing analyses revealed 1,703 statistically significant gene-phenotype associations for binary traits, with a median odds ratio of 12.4. Furthermore, 83% of these associations were undetectable via single-variant association tests, emphasizing the power of gene-based collapsing analysis in the setting of high allelic heterogeneity. Gene-phenotype associations were also significantly enriched for loss-of-function-mediated traits and approved drug targets. Finally, we performed ancestry-specific and pan-ancestry collapsing analyses using exome sequencing data from 11,933 UK Biobank participants of African, East Asian or South Asian ancestry. Our results highlight a significant contribution of rare variants to common disease. Summary statistics are publicly available through an interactive portal ( http://azphewas.com/ ).
| S-EPMC8458098 | biostudies-literature
Project description:In this study, we analyze the Genetic Analysis Workshop 18 data to identify the genes and underlying single-nucleotide polymorphisms on 11 chromosomes that exhibit significant association with systolic blood pressure. We propose a novel family-based method for rare-variant association detection based on the hierarchical Bayesian framework. The method controls spurious associations caused by population stratification, and improves the statistical power to detect not only individual rare variants, but also genes with either continuous or binary outcomes. Our method utilizes nuclear family information, and takes into account the effects of all single-nucleotide polymorphisms in a gene, using a hierarchical model. When we apply this method to the genome-wide Genetic Analysis Workshop 18 data, several genes and single-nucleotide polymorphisms are identified as potentially related to systolic blood pressure.
| S-EPMC4143697 | biostudies-literature
Project description:In biobank data analysis, most binary phenotypes have unbalanced case-control ratios, and this can cause inflation of type I error rates. Recently, a saddle point approximation (SPA) based single-variant test has been developed to provide an accurate and scalable method to test for associations of such phenotypes. For gene- or region-based multiple-variant tests, a few methods exist that can adjust for unbalanced case-control ratios; however, these methods are either less accurate when case-control ratios are extremely unbalanced or not scalable for large data analyses. To address these problems, we propose SKAT- and SKAT-O- type region-based tests; in these tests, the single-variant score statistic is calibrated based on SPA and efficient resampling (ER). Through simulation studies, we show that the proposed method provides well-calibrated p values. In contrast, when the case-control ratio is 1:99, the unadjusted approach has greatly inflated type I error rates (90 times that of exome-wide sequencing α = 2.5 × 10-6). Additionally, the proposed method has similar computation time to the unadjusted approaches and is scalable for large sample data. In our application, the UK Biobank whole-exome sequence data analysis of 45,596 unrelated European samples and 791 PheCode phenotypes identified 10 rare-variant associations with p value < 10-7, including the associations between JAK2 and myeloproliferative disease, HOXB13 and cancer of prostate, and F11 and congenital coagulation defects. All analysis summary results are publicly available through a web-based visual server, and this availability can help facilitate the identification of the genetic basis of complex diseases.
| S-EPMC7042481 | biostudies-literature
Project description:Phasing involves distinguishing the two parentally inherited copies of each chromosome into haplotypes. Here, we introduce SHAPEIT5, a new phasing method that quickly and accurately processes large sequencing datasets and applied it to UK Biobank (UKB) whole-genome and whole-exome sequencing data. We demonstrate that SHAPEIT5 phases rare variants with low switch error rates of below 5% for variants present in just 1 sample out of 100,000. Furthermore, we outline a method for phasing singletons, which, although less precise, constitutes an important step towards future developments. We then demonstrate that the use of UKB as a reference panel improves the accuracy of genotype imputation, which is even more pronounced when phased with SHAPEIT5 compared with other methods. Finally, we screen the UKB data for loss-of-function compound heterozygous events and identify 549 genes where both gene copies are knocked out. These genes complement current knowledge of gene essentiality in the human genome.
| S-EPMC10335929 | biostudies-literature
Project description:Small patella syndrome presents with small or absent patellae and may result in pulmonary arterial hypertension, typically in children. A pathogenic canonical splice site variant, c.1021+1G>A in the T-box transcription factor 4 (TBX4) gene, currently not included in commercial gene panel, was detected in an adult with pulmonary arterial hypertension and absent patellae. (Level of Difficulty: Advanced.).
| S-EPMC8446047 | biostudies-literature
Project description:IntroductionA previous study of 200,000 exome-sequenced UK Biobank participants to test for association of rare coding variants with hypertension implicated two genes at exome-wide significance, DNMT3A and FES. A total of 42 genes had an uncorrected p value <0.001. These results were followed up in a larger sample of 470,000 exome-sequenced participants.MethodsWeighted burden analysis of rare coding variants in a new sample of 97,050 cases and 172,263 controls was carried out for these 42 genes. Those showing evidence for association were then analysed in the combined sample of 167,127 cases and 302,691 controls.ResultsThe association of DNMT3A and FES with hypertension was replicated in the new sample and they and the previously implicated gene NPR1, which codes for a membrane-bound guanylate cyclase, were all exome-wide significant in the combined sample. Also exome-wide significant as risk genes for hypertension were GUCY1A1, ASXL1, and SMAD6, while GUCY1B1 had a nominal p value of <0.0001. GUCY1A1 and GUCY1B1 code for subunits of a soluble guanylate cyclase. For two genes, DBH, which codes for dopamine beta hydroxylase, and INPPL1, rare coding variants predicted to impair gene function were protective against hypertension, again with exome-wide significance.ConclusionThe findings offer new insights into biological risk factors for hypertension which could be the subject of further investigation. In particular, genetic variants predicted to impair the function of either membrane-bound guanylate cyclase, activated by natriuretic peptides, or soluble guanylate cyclase, activated by nitric oxide, increase risk of hypertension. Conversely, variants impairing the function of dopamine beta hydroxylase, responsible for the synthesis of norepinephrine, reduce hypertension risk.
| S-EPMC10712968 | biostudies-literature
Project description:BackgroundBoth common and rare genetic variants have been shown to contribute to the etiology of complex diseases. Recent genome-wide association studies (GWAS) have successfully investigated how common variants contribute to the genetic factors associated with common human diseases. However, understanding the impact of rare variants, which are abundant in the human population (one in every 17 bases), remains challenging. A number of statistical tests have been developed to analyze collapsed rare variants identified by association tests. Here, we propose a haplotype-based approach. This work inspired by an existing statistical framework of the pedigree disequilibrium test (PDT), which uses genetic data to assess the effects of variants in general pedigrees. We aim to compare the performance between the haplotype-based approach and the rare variant-based approach for detecting rare causal variants in pedigrees.ResultsExtensive simulations in the sequencing setting were carried out to evaluate and compare the haplotype-based approach with the rare variant methods that drew on a more conventional collapsing strategy. As assessed through a variety of scenarios, the haplotype-based pedigree tests had enhanced statistical power compared with the rare variants based pedigree tests when the disease of interest was mainly caused by rare haplotypes (with multiple rare alleles), and vice versa when disease was caused by rare variants acting independently. For most of other situations when disease was caused both by haplotypes with multiple rare alleles and by rare variants with similar effects, these two approaches provided similar power in testing for association.ConclusionsThe haplotype-based approach was designed to assess the role of rare and potentially causal haplotypes. The proposed rare variants-based pedigree tests were designed to assess the role of rare and potentially causal variants. This study clearly documented the situations under which either method performs better than the other. All tests have been implemented in a software, which was submitted to the Comprehensive R Archive Network (CRAN) for general use as a computer program named rvHPDT.
| S-EPMC4131059 | biostudies-literature