scholarly journals Metagenome-genome-wide association studies reveal human genetic impact on the oral microbiome

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Xiaomin Liu ◽  
Xin Tong ◽  
Jie Zhu ◽  
Liu Tian ◽  
Zhuye Jie ◽  
...  
Keyword(s):  
Human Genetics ◽  
Association Studies ◽  
Daily Basis ◽  
Oral Bacteria ◽  
Oral Microbiome ◽  
Risk Scores ◽  
Oral Microbiota ◽  
Genome Wide Association Studies ◽  
Mirna Genes ◽  
Genome Wide

AbstractThe oral microbiota contains billions of microbial cells, which could contribute to diseases in many body sites. Challenged by eating, drinking, and dental hygiene on a daily basis, the oral microbiota is regarded as highly dynamic. Here, we report significant human genomic associations with the oral metagenome from more than 1915 individuals, for both the tongue dorsum (n = 2017) and saliva (n = 1915). We identified five genetic loci associated with oral microbiota at study-wide significance (p < 3.16 × 10−11). Four of the five associations were well replicated in an independent cohort of 1439 individuals: rs1196764 at APPL2 with Prevotella jejuni, Oribacterium uSGB 3339 and Solobacterium uSGB 315; rs3775944 at the serum uric acid transporter SLC2A9 with Oribacterium uSGB 1215, Oribacterium uSGB 489 and Lachnoanaerobaculum umeaense; rs4911713 near OR11H1 with species F0422 uSGB 392; and rs36186689 at LOC105371703 with Eggerthia. Further analyses confirmed 84% (386/455 for tongue dorsum) and 85% (391/466 for saliva) of host genome-microbiome associations including six genome-wide significant associations mutually validated between the two niches. As many of the oral microbiome-associated genetic variants lie near miRNA genes, we tentatively validated the potential of host miRNAs to modulate the growth of specific oral bacteria. Human genetics accounted for at least 10% of oral microbiome compositions between individuals. Machine learning models showed that polygenetic risk scores dominated over oral microbiome in predicting risk of dental diseases such as dental calculus and gingival bleeding. These findings indicate that human genetic differences are one explanation for a stable or recurrent oral microbiome in each individual.

scholarly journals Metagenome-genome-wide association studies reveal human genetic impact on the oral microbiome

2021 ◽  
Author(s):  
Xiaomin Liu ◽  
Xin Tong ◽  
Jie Zhu ◽  
Liu Tian ◽  
Zhuye Jie ◽  
...  
Keyword(s):  
Human Genetics ◽  
Association Studies ◽  
Daily Basis ◽  
Oral Microbiome ◽  
Oral Microbiota ◽  
Genome Wide Association Studies ◽  
Prevotella Melaninogenica ◽  
Genome Wide ◽  
Genetic Impact ◽  
Dental Diseases

The oral microbiota contains billions of microbial cells, which could contribute to diseases in a number of body sites. Challenged by eating, drinking and dental hygiene on a daily basis, the oral microbiota is regarded as highly dynamic. Here, we report significant human genomic associations with the oral metagenome from more than 1,915 individuals, for both the tongue dorsum and saliva. Five genetic loci, APPL2, SLC2A9 and MGST1 associated with tongue dorsum, LOC102723769-OR11H1-POTEH and MTRNR2L1-LOC105371703-MIR4522 associated with salivary microbial features, reached study-wide significance (p < 3.16 * 10-11). Further analyses confirmed 6 genome-wide significant loci shared between tongue dorsum and saliva. For example, the dental caries pathogen Prevotella melaninogenica associated with MARK2-RCOR2; the periodontitis bacteria Treponema associated with CCL26-CCL24 and Porphyromonas associated with CSMD1 at both niches. Human genetics account for at least 10% of oral microbiome differences between individuals. Machine learning models showed that polygenetic risk score dominated over oral microbiome in predicting predisposing risk of dental diseases such as dental calculus and gingival bleeding. These findings indicate that human genetic differences are one explanation for a stable or recurrent oral microbiome in each individual.

scholarly journals Challenges of Adjusting Single-Nucleotide Polymorphism Effect Sizes for Linkage Disequilibrium

2021 ◽  
pp. 1-11
Author(s):  
Valentina Escott-Price ◽  
Karl Michael Schmidt
Keyword(s):  
Linkage Disequilibrium ◽  
Association Studies ◽  
Statistical Significance ◽  
Ordinary Least Squares ◽  
Effect Sizes ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Single Nucleotide ◽  
Genome Wide ◽  
Tikhonov Regularisation

<b><i>Background:</i></b> Genome-wide association studies (GWAS) were successful in identifying SNPs showing association with disease, but their individual effect sizes are small and require large sample sizes to achieve statistical significance. Methods of post-GWAS analysis, including gene-based, gene-set and polygenic risk scores, combine the SNP effect sizes in an attempt to boost the power of the analyses. To avoid giving undue weight to SNPs in linkage disequilibrium (LD), the LD needs to be taken into account in these analyses. <b><i>Objectives:</i></b> We review methods that attempt to adjust the effect sizes (β<i>-</i>coefficients) of summary statistics, instead of simple LD pruning. <b><i>Methods:</i></b> We subject LD adjustment approaches to a mathematical analysis, recognising Tikhonov regularisation as a framework for comparison. <b><i>Results:</i></b> Observing the similarity of the processes involved with the more straightforward Tikhonov-regularised ordinary least squares estimate for multivariate regression coefficients, we note that current methods based on a Bayesian model for the effect sizes effectively provide an implicit choice of the regularisation parameter, which is convenient, but at the price of reduced transparency and, especially in smaller LD blocks, a risk of incomplete LD correction. <b><i>Conclusions:</i></b> There is no simple answer to the question which method is best, but where interpretability of the LD adjustment is essential, as in research aiming at identifying the genomic aetiology of disorders, our study suggests that a more direct choice of mild regularisation in the correction of effect sizes may be preferable.

Stroke Genetics: Turning Discoveries into Clinical Applications

Stroke ◽  
2021 ◽  
Author(s):  
Martin Dichgans ◽  
Nathalie Beaufort ◽  
Stephanie Debette ◽  
Christopher D. Anderson
Keyword(s):  
Mendelian Randomization ◽  
Association Studies ◽  
Clinical Applications ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Neuroprotective Agents ◽  
Experimental Systems ◽  
Genome Wide ◽  
Rapid Pace

The field of medical and population genetics in stroke is moving at a rapid pace and has led to unanticipated opportunities for discovery and clinical applications. Genome-wide association studies have highlighted the role of specific pathways relevant to etiologically defined subtypes of stroke and to stroke as a whole. They have further offered starting points for the exploration of novel pathways and pharmacological strategies in experimental systems. Mendelian randomization studies continue to provide insights in the causal relationships between exposures and outcomes and have become a useful tool for predicting the efficacy and side effects of drugs. Additional applications that have emerged from recent discoveries include risk prediction based on polygenic risk scores and pharmacogenomics. Among the topics currently moving into focus is the genetics of stroke outcome. While still at its infancy, this field is expected to boost the development of neuroprotective agents. We provide a brief overview on recent progress in these areas.

scholarly journals Age-related late-onset disease heritability patterns and implications for genome-wide association studies

2018 ◽  
Author(s):  
Roman Teo Oliynyk
Keyword(s):  
Old Age ◽  
Cumulative Incidence ◽  
Late Onset ◽  
Association Studies ◽  
Genome Wide Association ◽  
Risk Scores ◽  
Cerebral Stroke ◽  
Genome Wide Association Studies ◽  
Polygenic Risk ◽  
Genome Wide

AbstractBackgroundGenome-wide association studies and other computational biology techniques are gradually discovering the causal gene variants that contribute to late-onset human diseases. After more than a decade of genome-wide association study efforts, these can account for only a fraction of the heritability implied by familial studies, the so-called “missing heritability” problem.MethodsComputer simulations of polygenic late-onset diseases in an aging population have quantified the risk allele frequency decrease at older ages caused by individuals with higher polygenic risk scores becoming ill proportionately earlier. This effect is most prominent for diseases characterized by high cumulative incidence and high heritability, examples of which include Alzheimer’s disease, coronary artery disease, cerebral stroke, and type 2 diabetes.ResultsThe incidence rate for late-onset diseases grows exponentially for decades after early onset ages, guaranteeing that the cohorts used for genome-wide association studies overrepresent older individuals with lower polygenic risk scores, whose disease cases are disproportionately due to environmental causes such as old age itself. This mechanism explains the decline in clinical predictive power with age and the lower discovery power of familial studies of heritability and genome-wide association studies. It also explains the relatively constant-with-age heritability found for late-onset diseases of lower prevalence, exemplified by cancers.ConclusionsFor late-onset polygenic diseases showing high cumulative incidence together with high initial heritability, rather than using relatively old age-matched cohorts, study cohorts combining the youngest possible cases with the oldest possible controls may significantly improve the discovery power of genome-wide association studies.

scholarly journals Increasing Sample Diversity in Psychiatric Genetics – Introducing a new Cohort of Patients with Schizophrenia and Controls from Vietnam – Results from a Pilot Study

2021 ◽  
Author(s):  
VT Nguyen ◽  
A Braun ◽  
J Kraft ◽  
TMT Ta ◽  
GM Panagiotaropoulou ◽  
...  
Keyword(s):  
Pilot Study ◽  
Data Collection ◽  
Predictive Power ◽  
Association Studies ◽  
East Asian ◽  
Genetic Research ◽  
European Ancestry ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Genome Wide

AbstractObjectivesGenome-Wide Association Studies (GWAS) of Schizophrenia (SCZ) have provided new biological insights; however, most cohorts are of European ancestry. As a result, derived polygenic risk scores (PRS) show decreased predictive power when applied to populations of different ancestries. We aimed to assess the feasibility of a large-scale data collection in Hanoi, Vietnam, contribute to international efforts to diversify ancestry in SCZ genetic research and examine the transferability of SCZ-PRS to individuals of Vietnamese Kinh ancestry.MethodsIn a pilot study, 368 individuals (including 190 SCZ cases) were recruited at the Hanoi Medical University’s associated psychiatric hospitals and outpatient facilities. Data collection included sociodemographic data, baseline clinical data, clinical interviews assessing symptom severity and genome-wide SNP genotyping. SCZ-PRS were generated using different training data sets: i) European, ii) East-Asian and iii) trans-ancestry GWAS summary statistics from the latest SCZ GWAS meta-analysis.ResultsSCZ-PRS significantly predicted case status in Vietnamese individuals using mixed-ancestry (R2 liability=4.9%, p=6.83*10−8), East-Asian (R2 liability=4.5%, p=2.73*10−7) and European (R2 liability=3.8%, p = 1.79*10−6) discovery samples.DiscussionOur results corroborate previous findings of reduced PRS predictive power across populations, highlighting the importance of ancestral diversity in GWA studies.

GWAS contribution to atrial fibrillation and atrial fibrillation-related stroke: pathophysiological implications

2019 ◽  
Vol 20 (10) ◽  
pp. 765-780 ◽  
Author(s):  
Diana Cruz ◽  
Ricardo Pinto ◽  
Margarida Freitas-Silva ◽  
José Pedro Nunes ◽  
Rui Medeiros
Keyword(s):  
Atrial Fibrillation ◽  
Genetic Variants ◽  
Complex Traits ◽  
Association Studies ◽  
Cardioembolic Stroke ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Genetic Determinants ◽  
Genome Wide ◽  
Genome Wide Significance

Atrial fibrillation (AF) and stroke are included in a group of complex traits that have been approached regarding of their study by susceptibility genetic determinants. Since 2007, several genome-wide association studies (GWAS) aiming to identify genetic variants modulating AF risk have been conducted. Thus, 11 GWAS have identified 26 SNPs (p < 5 × 10-2), of which 19 reached genome-wide significance (p < 5 × 10-8). From those variants, seven were also associated with cardioembolic stroke and three reached genome-wide significance in stroke GWAS. These associations may shed a light on putative shared etiologic mechanisms between AF and cardioembolic stroke. Additionally, some of these identified variants have been incorporated in genetic risk scores in order to elucidate new approaches of stroke prediction, prevention and treatment.

scholarly journals Critical Analysis of Genome-Wide Association Studies: Triple Negative Breast Cancer Quae Exempli Causa

2020 ◽  
Vol 21 (16) ◽  
pp. 5835
Author(s):  
Maria-Ancuta Jurj ◽  
Mihail Buse ◽  
Alina-Andreea Zimta ◽  
Angelo Paradiso ◽  
Schuyler S. Korban ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
Genetic Risk ◽  
Triple Negative ◽  
Cancer Susceptibility ◽  
Association Studies ◽  
Breast Cancer Susceptibility ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Genome Wide

Genome-wide association studies (GWAS) are useful in assessing and analyzing either differences or variations in DNA sequences across the human genome to detect genetic risk factors of diseases prevalent within a target population under study. The ultimate goal of GWAS is to predict either disease risk or disease progression by identifying genetic risk factors. These risk factors will define the biological basis of disease susceptibility for the purposes of developing innovative, preventative, and therapeutic strategies. As single nucleotide polymorphisms (SNPs) are often used in GWAS, their relevance for triple negative breast cancer (TNBC) will be assessed in this review. Furthermore, as there are different levels and patterns of linkage disequilibrium (LD) present within different human subpopulations, a plausible strategy to evaluate known SNPs associated with incidence of breast cancer in ethnically different patient cohorts will be presented and discussed. Additionally, a description of GWAS for TNBC will be presented, involving various identified SNPs correlated with miRNA sites to determine their efficacies on either prognosis or progression of TNBC in patients. Although GWAS have identified multiple common breast cancer susceptibility variants that individually would result in minor risks, it is their combined effects that would likely result in major risks. Thus, one approach to quantify synergistic effects of such common variants is to utilize polygenic risk scores. Therefore, studies utilizing predictive risk scores (PRSs) based on known breast cancer susceptibility SNPs will be evaluated. Such PRSs are potentially useful in improving stratification for screening, particularly when combining family history, other risk factors, and risk prediction models. In conclusion, although interpretation of the results from GWAS remains a challenge, the use of SNPs associated with TNBC may elucidate and better contextualize these studies.

scholarly journals Genome-Wide Association Studies of Schizophrenia and Bipolar Disorder in a Diverse Cohort of US Veterans

2020 ◽  
Author(s):  
Tim B Bigdeli ◽  
Ayman H Fanous ◽  
Yuli Li ◽  
Nallakkandi Rajeevan ◽  
Frederick Sayward ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Association Studies ◽  
Genome Wide Association ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Susceptibility Loci ◽  
New Associations ◽  
Genome Wide ◽  
Us Veterans

Abstract Background Schizophrenia (SCZ) and bipolar disorder (BIP) are debilitating neuropsychiatric disorders, collectively affecting 2% of the world’s population. Recognizing the major impact of these psychiatric disorders on the psychosocial function of more than 200 000 US Veterans, the Department of Veterans Affairs (VA) recently completed genotyping of more than 8000 veterans with SCZ and BIP in the Cooperative Studies Program (CSP) #572. Methods We performed genome-wide association studies (GWAS) in CSP #572 and benchmarked the predictive value of polygenic risk scores (PRS) constructed from published findings. We combined our results with available summary statistics from several recent GWAS, realizing the largest and most diverse studies of these disorders to date. Results Our primary GWAS uncovered new associations between CHD7 variants and SCZ, and novel BIP associations with variants in Sortilin Related VPS10 Domain Containing Receptor 3 (SORCS3) and downstream of PCDH11X. Combining our results with published summary statistics for SCZ yielded 39 novel susceptibility loci including CRHR1, and we identified 10 additional findings for BIP (28 326 cases and 90 570 controls). PRS trained on published GWAS were significantly associated with case-control status among European American (P &lt; 10–30) and African American (P &lt; .0005) participants in CSP #572. Conclusions We have demonstrated that published findings for SCZ and BIP are robustly generalizable to a diverse cohort of US veterans. Leveraging available summary statistics from GWAS of global populations, we report 52 new susceptibility loci and improved fine-mapping resolution for dozens of previously reported associations.

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