Rare Neurovascular Diseases in Korea: Classification and Related Genetic Variants.
Ontology highlight
ABSTRACT:
SUBMITTER: Song Y
PROVIDER: S-EPMC8316781 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Technology advances have promoted gene-based sequencing studies with the aim of identifying rare mutations responsible for complex diseases. A complication in these types of association studies is that the vast majority of non-synonymous mutations are believed to be neutral to phenotypes. It is thus critical to distinguish potential causative variants from neutral variation before performing association tests. In this study, we used existing predicting algorithms to predict functional amino acid substitutions, and incorporated that information into association tests. Using simulations, we comprehensively studied the effects of several influential factors, including the sensitivity and specificity of functional variant predictions, number of variants, and proportion of causative variants, on the performance of association tests. Our results showed that incorporating information regarding functional variants obtained from existing prediction algorithms improves statistical power under certain conditions, particularly when the proportion of causative variants is moderate. The application of the proposed tests to a real sequencing study confirms our conclusions. Our work may help investigators who are planning to pursue gene-based sequencing studies.
| S-EPMC2975623 | biostudies-literature
Project description:Pathogenic variants underlying Mendelian diseases often disrupt the normal physiology of a few tissues and organs. However, variant effect prediction tools that aim to identify pathogenic variants are typically oblivious to tissue contexts. Here we report a machine-learning framework, denoted 'Tissue Risk Assessment of Causality by Expression for variants' (TRACEvar, https://netbio.bgu.ac.il/TRACEvar/), that offers two advancements. First, TRACEvar predicts pathogenic variants that disrupt the normal physiology of specific tissues. This was achieved by creating 14 tissue-specific models that were trained on over 14,000 variants and combined 84 attributes of genetic variants with 495 attributes derived from tissue omics. TRACEvar outperformed 10 well-established and tissue-oblivious variant effect prediction tools. Second, the resulting models are interpretable, thereby illuminating variants' mode-of-action. Application of TRACEvar to variants of 52 rare-disease patients highlighted pathogenicity mechanisms and relevant disease processes. Lastly, interpretation of large-scale models revealed that top-ranking determinants of pathogenicity included attributes of disease-affected tissues, particularly cellular process activities. Hence, tissue contexts and interpretable machine-learning models can greatly enhance the etiology of rare diseases.
| S-SCDT-10_1038-S44320-024-00061-6 | biostudies-other
Project description:Rare DNA alterations that cause heritable diseases are only partially resolvable by clinical next-generation sequencing due to the difficulty of detecting structural variation (SV) in all genomic contexts. Long-read, high fidelity genome sequencing (HiFi-GS) detects SVs with increased sensitivity and enables assembling personal and graph genomes. We leverage standard reference genomes, public assemblies (n = 94) and a large collection of HiFi-GS data from a rare disease program (Genomic Answers for Kids, GA4K, n = 574 assemblies) to build a graph genome representing a unified SV callset in GA4K, identify common variation and prioritize SVs that are more likely to cause genetic disease (MAF < 0.01). Using graphs, we obtain a higher level of reproducibility than the standard reference approach. We observe over 200,000 SV alleles unique to GA4K, including nearly 1000 rare variants that impact coding sequence. With improved specificity for rare SVs, we isolate 30 candidate SVs in phenotypically prioritized genes, including known disease SVs. We isolate a novel diagnostic SV in KMT2E, demonstrating use of personal assemblies coupled with pangenome graphs for rare disease genomics. The community may interrogate our pangenome with additional assemblies to discover new SVs within the allele frequency spectrum relevant to genetic diseases.
| S-EPMC10803329 | biostudies-literature
Project description:To identify rare genetic variants in early age-related macular degeneration (AMD) utilizing whole-exome sequencing (WES). Eight non-related early-AMD families of different Jewish ethnicities were ascertained. Initial mutation screening (phase-1) included common complement factor-H (CFH) p.Y402H; and age relatedmaculopathy susceptibility 2 (ARMS2) p.A69S; and rare variants complement factor-I (CFI) p.V412M; and hemicentin1 (HMCN1) c.4163delC identified previously in our population. Four families, whose initial screening for the aforementioned variants was negative, underwent WES (phase-2). Bioinformatics filtering was based on functionality (from a panel of 234 genes with proven or presumed association to AMD); predicted severity; and frequency (rare variants with minor allele frequency <1%). When applicable, further screening for specific rare variants was carried out on additional cases of similar ethnicities and phenotypes (phase-3). Phase-1 identified three families carrying CFI p.V412M mutation. WES analysis detected probable disease-related variants in three out of the remaining families. These included: a family with a variant in PLEKHA1 gene p.S177N; a family with previously reported variant p.R1210C in CFH gene; and two families with the C3 p.R735W variant. Rare, high-penetrance variants have a profound contribution to early-AMD pathogenesis. Utilization of WES in genetic research of multifactorial diseases as AMD, allows a thorough comprehensive analysis with the identification of previously unreported rare variants.
| S-EPMC6826738 | biostudies-literature
Project description:The purpose of this article is to stimulate discussion about whether a phenome-wide association study is a suitable tool for uncovering late-onset risks in patients with monogenic disorders that are not yet fully recognized because the life expectancy of people with such conditions has only recently extended, and they now reach older ages when they may develop additional complications.
| S-EPMC7818908 | biostudies-literature
Project description:Identifying drivers of complex traits from the noisy signals of genetic variation obtained from high-throughput genome sequencing technologies is a central challenge faced by human geneticists today. We hypothesize that the variants involved in complex diseases are likely to exhibit non-neutral evolutionary signatures. Uncovering the evolutionary history of all variants is therefore of intrinsic interest for complex disease research. However, doing so necessitates the simultaneous elucidation of the targets of natural selection and population-specific demographic history.Here we characterize the action of natural selection operating across complex disease categories, and use population genetic simulations to evaluate the expected patterns of genetic variation in large samples. We focus on populations that have experienced historical bottlenecks followed by explosive growth (consistent with many human populations), and describe the differences between evolutionarily deleterious mutations and those that are neutral.Genes associated with several complex disease categories exhibit stronger signatures of purifying selection than non-disease genes. In addition, loci identified through genome-wide association studies of complex traits also exhibit signatures consistent with being in regions recurrently targeted by purifying selection. Through simulations, we show that population bottlenecks and rapid growth enable deleterious rare variants to persist at low frequencies just as long as neutral variants, but low-frequency and common variants tend to be much younger than neutral variants. This has resulted in a large proportion of modern-day rare alleles that have a deleterious effect on function and that potentially contribute to disease susceptibility.The key question for sequencing-based association studies of complex traits is how to distinguish between deleterious and benign genetic variation. We used population genetic simulations to uncover patterns of genetic variation that distinguish these two categories, especially derived allele age, thereby providing inroads into novel methods for characterizing rare genetic variation driving complex diseases.
| S-EPMC3698246 | biostudies-literature
Project description:Recent studies suggest that rare variants play an important role in the etiology of many traits. Although a number of methods have been developed for genetic association analysis of rare variants, they all assume a relatively homogeneous population under study. Such an assumption may not be valid for samples collected from admixed populations such as African Americans and Hispanic Americans as there is a great extent of local variation in ancestry in these populations. To ensure valid and more powerful rare variant association tests performed in admixed populations, we have developed a local ancestry-based weighted dosage test, which is able to take into account local ancestry of rare alleles, uncertainties in rare variant imputation when imputed data are included, and the direction of effect that rare variants exert on phenotypic outcome. We used simulated sequence data to show that our proposed test has controlled type I error rates, whereas naïve application of existing rare variants tests and tests that adjust for global ancestry lead to inflated type I error rates. We showed that our test has higher power than tests without proper adjustment of ancestry. We also applied the proposed method to a candidate gene study on low-density lipoprotein cholesterol. Our results suggest that it is important to appropriately control for potential population stratification induced by local ancestry difference in the analysis of rare variants in admixed populations.
| S-EPMC3524352 | biostudies-other
Project description:Rare diseases pose a global challenge, in that their collective impact on health systems is considerable, whereas their individually rare occurrence impedes research and development of efficient therapies. In consequence, patients and their families are often unable to find an expert for their affliction, let alone a cure. The tide is turning as pharmaceutical companies embrace gene therapy development and as serviceable tools for the repair of primary mutations separate the ability to create cures from underlying disease expertise. Whereas gene therapy by gene addition took decades to reach the clinic by incremental disease-specific refinements of vectors and methods, gene therapy by genome editing in its basic form merely requires certainty about the causative mutation. Suddenly we move from concept to trial in 3 years instead of 30: therapy development in the fast lane, with all the positive and negative implications of the phrase. Since their first application to eukaryotic cells in 2013, the proliferation and refinement in particular of tools based on clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein (Cas) prokaryotic RNA-guided nucleases has prompted a landslide of therapy-development studies for rare diseases. An estimated thousands of orphan diseases are up for adoption, and legislative, entrepreneurial, and research initiatives may finally conspire to find many of them a good home. Here we summarize the most significant recent achievements and remaining hurdles in the application of CRISPR/Cas technology to rare diseases and take a glimpse at the exciting road ahead.
| S-EPMC6469594 | biostudies-literature
Project description:Background: Calcium ions (Ca2+) play an essential role in excitation-contraction coupling in the heart. The association between cardiovascular diseases (CVDs) and genetic polymorphisms in key regulators of Ca2+ homeostasis is well established but still inadequately understood. Methods: The associations of 11,274 genetic variants located in nine calcium signaling-related genes with 118 diseases of the circulatory system were explored using a large sample from the United Kingdom Biobank (N = 308,366). The clinical outcomes in electronic health records were mapped to the phecode system. Survival analyses were employed to study the role of variants in CVDs incidence and mortality. Phenome-wide association studies (PheWAS) were performed to investigate the effect of variants on cardiovascular risk factors. Results: The reported association between rs1801253 in β1-adrenergic receptor (ADRB1) and hypertension was successfully replicated, and we additionally found the blood pressure-lowering G allele of this variant was associated with a delayed onset of hypertension and a decreased level of apolipoprotein A. The association of rs4484922 in calsequestrin 2 (CASQ2) with atrial fibrillation/flutter was identified, and this variant also displayed nominal evidence of association with QRS duration and carotid intima-medial thickness. Moreover, our results indicated suggestive associations of rs79613429 in ryanodine receptor 2 (RYR2) with precordial pain. Conclusion: Multiple novel associations established in our study highlight genetic testing as a useful method for CVDs diagnosis and prevention.
| S-EPMC8666440 | biostudies-literature
Project description:A case of a patient with an early and severe visual impairment is described. Due to the occurrence of skin papules a suspect of pseudoxanthoma elasticum (PXE) was posed. PXE is a rare autosomal recessive disease clinically characterized by skin, cardiovascular and ocular manifestations, these last being those that most severely affect patients' quality of life. A whole exome sequencing approach focusing on 340 genes related to the calcification process and/or to inherited retinal diseases (IRDs) was performed. Rare monoallelic sequence variants in ABCA4, ABCC6, IMPG1, POC1B and RAX2 were found. The presence of calcified elastic fibers was assessed by ultrastructural analysis on a skin biopsy. Diagnosis of PXE was based on clinical, biomolecular and morphological results, although the additional involvement of several IRD genes is important to explain the unexpectedly severe ophthalmological phenotype of the patient also in prognostic and therapeutic perspectives. Data indicate that genetic screening using a wide-spectrum analysis approach is essential to assist ophthalmologists in improving patient counseling.
| S-EPMC8534466 | biostudies-literature