scholarly journals A General Statistic to Test an Optimally Weighted Combination of Common and/or Rare Variants

2019 ◽  
Author(s):  
Jianjun Zhang ◽  
Baolin Wu ◽  
Qiuying Sha ◽  
Shuanglin Zhang ◽  
Xuexia Wang
Keyword(s):  
Rare Variants ◽  
Association Studies ◽  
Genome Wide Association ◽  
P Value ◽  
Type I ◽  
Genome Wide Association Studies ◽  
Simulation Studies ◽  
Genome Wide ◽  
Combination Scheme ◽  
Weighted Combination

AbstractBoth genome-wide association study and next generation sequencing data analyses are widely employed in order to identify disease susceptible common and/or rare genetic variants in many large scale genetic studies. Rare variants generally have large effects though they are hard to detect due to their low frequency. Currently, many existing statistical methods for rare variants association studies employ a weighted combination scheme, which usually puts subjective weights or suboptimal weights based on some ad hoc assumptions (e.g. ignoring dependence between rare variants). In this study, we analytically derive optimal weights for both common and rare variants and propose a General and novel approach to Test association between an Optimally Weighted combination of variants (G-TOW) in a gene or pathway for a continuous or dichotomous trait while easily adjusting for covariates. We conduct extensive simulation studies to evaluate the performance of G-TOW. Results of the simulation studies show that G-TOW has properly controlled type I error rates and it is the most powerful test among the methods we compared, when testing effects of either both rare and common variants or rare variants only. We also illustrate the effectiveness of G-TOW using the Genetic Analysis Workshop 17 (GAW17) data. In addition, we applied G-TOW and other competitive methods to test association for schizophrenia. The G-TOW have successfully verified genes FYN and VPS39 which are associated with schizophrenia reported in existing publications. Both of these genes are missed by the weighted sum statistic (WSS) and the sequence kernel association test (SKAT). G-TOW also showed much stronger significance (p-value=0.0037) than our previously developed method named Testing the effect of an Optimally Weighted combination of variants (TOW) (p-value=0.0143) on gene FYN. FYN is a member of the protein-tyrosine kinase oncogene family that phosphorylates glutamate metabotropic receptors and ionotropic N-methyl-d-aspartate (NMDA) receptors. NMDA modulates trafficking, subcellular distribution and function. It is involved in neuronal apoptosis, brain development and synaptic transmission and lower expression, which has been observed in the platelets of schizophrenic patients compared with controls. The application for schizophrenia indicates that G-TOW is a powerful tool in genome-wide association studies.

scholarly journals Reproducibility in the UK Biobank of Genome-Wide Significant Signals Discovered in Earlier Genome-wide Association Studies

2020 ◽  
Author(s):  
Jack W. O’Sullivan ◽  
John P. A. Ioannidis
Keyword(s):  
Effect Size ◽  
Association Studies ◽  
Genome Wide Association ◽  
P Value ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Single Nucleotide ◽  
Genome Wide ◽  
The Uk ◽  
Open Question

AbstractWith the establishment of large biobanks, discovery of single nucleotide polymorphism (SNPs) that are associated with various phenotypes has been accelerated. An open question is whether SNPs identified with genome-wide significance in earlier genome-wide association studies (GWAS) are replicated also in later GWAS conducted in biobanks. To address this question, the authors examined a publicly available GWAS database and identified two, independent GWAS on the same phenotype (an earlier, “discovery” GWAS and a later, replication GWAS done in the UK biobank). The analysis evaluated 136,318,924 SNPs (of which 6,289 had reached p<5e-8 in the discovery GWAS) from 4,397,962 participants across nine phenotypes. The overall replication rate was 85.0% and it was lower for binary than for quantitative phenotypes (58.1% versus 94.8% respectively). There was a18.0% decrease in SNP effect size for binary phenotypes, but a 12.0% increase for quantitative phenotypes. Using the discovery SNP effect size, phenotype trait (binary or quantitative), and discovery p-value, we built and validated a model that predicted SNP replication with area under the Receiver Operator Curve = 0.90. While non-replication may often reflect lack of power rather than genuine false-positive findings, these results provide insights about which discovered associations are likely to be seen again across subsequent GWAS.

scholarly journals Genome-Wide Association Study Identifies Loci Associated with Sensitive Skin

Cosmetics ◽  
2020 ◽  
Vol 7 (2) ◽  
pp. 49
Author(s):  
Miranda A. Farage ◽  
Yunxuan Jiang ◽  
Jay P. Tiesman ◽  
Pierre Fontanillas ◽  
Rosemarie Osborne
Keyword(s):  
Genome Wide Association Study ◽  
Association Studies ◽  
Genome Wide Association ◽  
European Ancestry ◽  
P Value ◽  
Genome Wide Association Studies ◽  
Online Questionnaire ◽  
Sensitive Skin ◽  
Genome Wide ◽  
Skin Conditions

Individuals suffering from sensitive skin often have other skin conditions and/or diseases, such as fair skin, freckles, rosacea, or atopic dermatitis. Genome-wide association studies (GWAS) have been performed for some of these conditions, but not for sensitive skin. In this study, a total of 23,426 unrelated participants of European ancestry from the 23andMe database were evaluated for self-declared sensitive skin, other skin conditions, and diseases using an online questionnaire format. Responders were separated into two groups: those who declared they had sensitive skin (n = 8971) and those who declared their skin was not sensitive (controls, n = 14,455). A GWAS of sensitive skin individuals identified three genome-wide significance loci (p-value < 5 × 10−8) and seven suggestive loci (p-value < 1 × 10−6). Of the three most significant loci, all have been associated with pigmentation and two have been associated with acne.

scholarly journals Haplotype-based genome wide association study using a novel SNP-set method : RAINBOW

2019 ◽  
Author(s):  
Kosuke Hamazaki ◽  
Hiroyoshi Iwata
Keyword(s):  
Haplotype Block ◽  
Rare Variants ◽  
Association Studies ◽  
False Positives ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Multiple Alleles ◽  
Genome Wide ◽  
Causal Variants ◽  
Novel Snp

AbstractBackgroundDiffculty in detecting rare variants is one of the problems in conventional genome wide association studies (GWAS). The problem is closely related to the complex gene compositions comprising multiple alleles, such as haplotypes. Several single nucleotide polymorphism (SNP) set approaches have been proposed to solve this problem. These methods, however, have been rarely discussed in connection with haplotypes. In this study, we developed a novel SNP-set GWAS method named “RAINBOW” and applied the method to haplotype-based GWAS by regarding a haplotype block as a SNP-set. Combining haplotype block estimation and SNP-set GWAS, haplotype-based GWAS can be conducted without prior information of haplotypes.ResultsWe prepared 100 datasets of simulated phenotypic data and real marker genotype data of Oryza sativa subsp. indica, and performed GWAS of the datasets. We compared the power of our method, the conventional single-SNP GWAS, the conventional haplotype-based GWAS, and the conventional SNP-set GWAS. The results of the comparison indicated that the proposed method was able to better control false positives than the others. The proposed method was also excellent at detecting causal variants without relying on the linkage disequilibrium if causal variants were genotyped in the dataset. Moreover, the proposed method showed greater power than the other methods, i.e., it was able to detect causal variants that were not detected by the others, especially when the causal variants were located very close to each other and the directions of their effects were opposite.ConclusionThe proposed method, RAINBOW, is especially superior in controlling false positives, detecting causal variants, and detecting nearby causal variants with opposite effects. By using the SNP-set approach as the proposed method, we expect that detecting not only rare variants but also genes with complex mechanisms, such as genes with multiple causal variants, can be realized. RAINBOW was implemented as the R package and is available at https://github.com/KosukeHamazaki/RAINBOW.

scholarly journals Genome Wide Prediction, Mapping and Development of Genomic Resources of Mastitis Associated Genes in Water Buffalo

2021 ◽  
Vol 8 ◽  
Author(s):  
Sarika Jaiswal ◽  
Jaisri Jagannadham ◽  
Juli Kumari ◽  
Mir Asif Iquebal ◽  
Anoop Kishor Singh Gurjar ◽  
...  
Keyword(s):  
Water Buffalo ◽  
Rare Variants ◽  
Association Studies ◽  
Resistance Breeding ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genomic Resources ◽  
Limited Success ◽  
Genome Wide ◽  
Gene Panels

Water buffalo (Bubalus bubalis) are an important animal resource that contributes milk, meat, leather, dairy products, and power for plowing and transport. However, mastitis, a bacterial disease affecting milk production and reproduction efficiency, is most prevalent in populations having intensive selection for higher milk yield, especially where the inbreeding level is also high. Climate change and poor hygiene management practices further complicate the issue. The management of this disease faces major challenges, like antibiotic resistance, maximum residue level, horizontal gene transfer, and limited success in resistance breeding. Bovine mastitis genome wide association studies have had limited success due to breed differences, sample sizes, and minor allele frequency, lowering the power to detect the diseases associated with SNPs. In this work, we focused on the application of targeted gene panels (TGPs) in screening for candidate gene association analysis, and how this approach overcomes the limitation of genome wide association studies. This work will facilitate the targeted sequencing of buffalo genomic regions with high depth coverage required to mine the extremely rare variants potentially associated with buffalo mastitis. Although the whole genome assembly of water buffalo is available, neither mastitis genes are predicted nor TGP in the form of web-genomic resources are available for future variant mining and association studies. Out of the 129 mastitis associated genes of cattle, 101 were completely mapped on the buffalo genome to make TGP. This further helped in identifying rare variants in water buffalo. Eighty-five genes were validated in the buffalo gene expression atlas, with the RNA-Seq data of 50 tissues. The functions of 97 genes were predicted, revealing 225 pathways. The mastitis proteins were used for protein-protein interaction network analysis to obtain additional cross-talking proteins. A total of 1,306 SNPs and 152 indels were identified from 101 genes. Water Buffalo-MSTdb was developed with 3-tier architecture to retrieve mastitis associated genes having genomic coordinates with chromosomal details for TGP sequencing for mining of minor alleles for further association studies. Lastly, a web-genomic resource was made available to mine variants of targeted gene panels in buffalo for mastitis resistance breeding in an endeavor to ensure improved productivity and the reproductive efficiency of water buffalo.

scholarly journals A meta-analysis of the genome-wide association studies on two genetically correlated phenotypes (self-reported headache and self-reported migraine) identifies four new risk loci for headaches (N=397,385)

2021 ◽  
Author(s):  
Weihua Meng ◽  
Parminder Reel ◽  
Charvi Nangia ◽  
Aravind Rajendrakumar ◽  
Harry Hebert ◽  
...  
Keyword(s):  
Association Studies ◽  
Meta Analysis ◽  
The Self ◽  
Genome Wide Association ◽  
P Value ◽  
Clinical Settings ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Genetic Mechanisms ◽  
The Uk

Headache is one of the commonest complaints that doctors need to address in clinical settings. The genetic mechanisms of different types of headache are not well understood. In this study, we performed a meta-analysis of genome-wide association studies (GWAS) on the self-reported headache phenotype from the UK Biobank cohort and the self-reported migraine phenotype from the 23andMe resource using the metaUSAT for genetically correlated phenotypes (N=397,385). We identified 38 loci for headaches, of which 34 loci have been reported before and 4 loci were newly identified. The LRP1-STAT6-SDR9C7 region in chromosome 12 was the most significantly associated locus with a leading P value of 1.24 x 10-62 of rs11172113. The ONECUT2 gene locus in chromosome 18 was the strongest signal among the 4 new loci with a P value of 1.29 x 10-9 of rs673939. Our study demonstrated that the genetically correlated phenotypes of self-reported headache and self-reported migraine can be meta-analysed together in theory and in practice to boost study power to identify more new variants for headaches. This study has paved way for a large GWAS meta-analysis study involving cohorts of different, though genetically correlated headache phenotypes.

scholarly journals FORGE: multivariate calculation of gene-wide p-values from Genome-Wide Association Studies Authors and Affiliations

2015 ◽  
Author(s):  
Inti Inal Pedroso ◽  
Michael R Barnes ◽  
Anbarasu Lourdusamy ◽  
Ammar Al-Chalabi ◽  
Gerome Breen
Keyword(s):  
Statistical Power ◽  
Association Studies ◽  
Single Point ◽  
Genome Wide Association ◽  
P Value ◽  
Disease Genes ◽  
Snp Analysis ◽  
Genome Wide Association Studies ◽  
P Values ◽  
Genome Wide

Genome-wide association studies (GWAS) have proven a valuable tool to explore the genetic basis of many traits. However, many GWAS lack statistical power and the commonly used single-point analysis method needs to be complemented to enhance power and interpretation. Multivariate region or gene-wide association are an alternative, allowing for identification of disease genes in a manner more robust to allelic heterogeneity. Gene-based association also facilitates systems biology analyses by generating a single p-value per gene. We have designed and implemented FORGE, a software suite which implements a range of methods for the combination of p-values for the individual genetic variants within a gene or genomic region. The software can be used with summary statistics (marker ids and p-values) and accepts as input the result file formats of commonly used genetic association software. When applied to a study of Crohn's disease susceptibility, it identified all genes found by single SNP analysis and additional genes identified by large independent meta-analysis. FORGE p-values on gene-set analyses highlighted association with the Jak-STAT and cytokine signalling pathways, both previously associated with CD. We highlight the software's main features, its future development directions and provide a comparison with alternative available software tools. FORGE can be freely accessed at https://github.com/inti/FORGE.

scholarly journals Αποτίμηση γενετικών παραγόντων κινδύνου για διαταραχές των οστών

2020 ◽  
Author(s):  
Μαρία Χρήστου
Keyword(s):  
Bone Mineral Density ◽  
Bone Mineral ◽  
Association Studies ◽  
Genome Wide Association ◽  
P Value ◽  
Genome Wide Association Studies ◽  
Mineral Density ◽  
Genome Wide

Σκοπός της διδακτορικής διατριβής ήταν η αποσαφήνιση της αιτιολογίας της οστεοπόρωσης, της συχνότερης διαταραχής των οστών, μέσω μελέτης της γενετικής πλειοτροπίας της νόσου.Στην προσπάθεια αποτίμησης των πλειοτροπικών γενετικών πολυμορφισμών που σχετίζονται με ελαττωμένη οστική πυκνότητα (Bone Mineral Density, BMD) και διάφορους φαινοτύπους πραγματοποιήθηκε ανασκόπηση της βιβλιογραφίας. Περιγράφηκαν τα πρόσφατα δεδομένα γενετικής πλειοτροπίας μεταξύ της BMD και της οστεοπόρωσης και 5 φαινοτύπων εντός του μυοσκελετικού συστήματος (κάταγμα, οστεοαρθρίτιδα, ρευματοειδής αρθρίτιδα, άλιπη σωματική μάζα, εκφύλιση μεσοσπονδύλιου δίσκου στην οσφυϊκή μοίρα της σπονδυλικής στήλης), καθώς επίσης των ακόλουθων 15 φαινοτύπων εκτός του μυοσκελετικού συστήματος: δείκτης μάζας σώματος, περιφέρεια μέσης, λόγος περιφέρειας μέσης-ισχίου, λιπώδης μάζα, %λίπος, στεφανιαία νόσος, σακχαρώδης διαβήτης τύπου 2, λιπίδια πλάσματος, ύψος, ηλικία εμμηναρχής, ηλικία κατά την εφηβεία γενικότερα, κατανάλωση αλκοόλ, ανδρογενής αλωπεκία, καρκίνος μαστού και εκφύλιση ωχράς κηλίδας σχετιζόμενη με την ηλικία.Στην προσπάθεια περαιτέρω διερεύνησης των ανωτέρω ενδείξεων παρουσίας πλειοτροπίας μεταξύ μυοσκελετικών και μη φαινοτύπων και της ελαττωμένης BMD, καθώς επίσης περαιτέρω κατανόησης της γενετικής αρχιτεκτονικής της BMD, αναζητήθηκαν πλειοτροπικές συσχετίσεις με φαινομενικά μη σχετιζόμενους, μη οστικούς φαινοτύπους. Ειδικότερα, στη φάση ανακάλυψης της οστικής πλειοτροπίας, πραγματοποιώντας ευρεία σάρωση του γονιδιώματος (genome-wide pleiotropy scan), ελέγχθηκαν πολυμορφισμοί του NHGRI-EBI Καταλόγου που σχετίζονται με διάφορους μη οστικούς φαινοτύπους σε προηγούμενες μελέτες ευρείας σάρωσης του γονιδιώματος (Genome Wide Association Studies, GWAS) για συσχέτιση με την BMD (αυχένα κεφαλής μηριαίου οστού, οσφυϊκή μοίρα σπονδυλικής στήλης) σε περισσότερα από 80.000 άτομα του μεγάλου διεθνούς συνασπισμού GEFOS. Στη συνέχεια, στη φάση επικύρωσης της οστικής πλειοτροπίας, οι 72 ισχυρότεροι πολυμορφισμοί από τη φάση ανακάλυψης ελέγχθηκαν για επικύρωση σε περισσότερα από 400.000 άτομα από τη μεγάλη μελέτη UK Biobank.Με αυτόν τον τρόπο εντοπίστηκαν 12 πλειοτροπικοί πολυμορφισμοί που σχετίζονται με την BMD (πτέρνας) και τους ακόλουθους 14 μη οστικούς φαινοτύπους σε επίπεδο p-value<5x10-8: ύψος, περιφέρεια μέσης, νόσος Parkinson, καρκίνος στομάχου μη καρδιακού τύπου, ανδρογενής αλωπεκία, αλλεργικές ασθένειες (άσθμα, πυρετός εκ χόρτου, έκζεμα), ατοπική δερματίτιδα, ατοπία γενικότερα, μαγνήσιο ορού, ηλεκτρολύτες ούρων, πρωτεΐνες ορού, δικτυοερυθροκύτταρα, κατανάλωση καφέ και εκπαιδευτικό επίπεδο. Οι 12 πλειοτροπικοί πολυμορφισμοί βρίσκονταν σε 11 γενετικούς τόπους, σε 8 χρωμοσώματα. Εννέα πολυμορφισμοί περιλαμβάνονταν στον NHGRI-EBI Κατάλογο, ενώ 3 πολυμορφισμοί ήταν γειτονικοί. Συμπερασματικά, η διδακτορική διατριβή ανέδειξε την παρουσία διάφορων φαινοτυπικών συσχετίσεων για την οστεοπόρωση μέσω μελέτης της γενετικής πλειοτροπίας. Αξιοσημείωτα οφέλη από τη διερεύνηση της γενετικής πλειοτροπίας της οστεοπόρωσης αποτελούν οι κλινικές συνέπειες ενσωμάτωσης των μοριακών ανακαλύψεων (υπεύθυνα γονίδια και μονοπάτια) στην αιτιολογία της νόσου. Στόχος είναι οι μελλοντικές προσπάθειες να επικεντρωθούν στην ανάπτυξη νέων φαρμάκων με πλειοτροπικές δράσεις, στην επαναστόχευση των ήδη υπάρχοντων φαρμάκων, καθώς επίσης στην εκτίμηση του κινδύνου ανάπτυξης της νόσου σε άτομα υψηλού κινδύνου.

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