scholarly journals Genome-Wide Association and Mendelian Randomization Analysis Reveal the Causal Relationship Between White Blood Cell Subtypes and Asthma in Africans

2021 ◽  
Vol 12 ◽  
Author(s):  
Opeyemi Soremekun ◽  
Chisom Soremekun ◽  
Tafadzwa Machipisa ◽  
Mahmoud Soliman ◽  
Oyekanmi Nashiru ◽  
...  
Keyword(s):  
Blood Cell ◽  
Causal Relationship ◽  
White Blood Cell ◽  
Fine Mapping ◽  
Mendelian Randomization ◽  
African Ancestry ◽  
Genome Wide Association ◽  
Monocyte Count ◽  
Summary Statistics ◽  
Genome Wide

Background: White blood cell (WBC) traits and their subtypes such as basophil count (Bas), eosinophil count (Eos), lymphocyte count (Lym), monocyte count (Mon), and neutrophil counts (Neu) are known to be associated with diseases such as stroke, peripheral arterial disease, and coronary heart disease.Methods: We meta-analyze summary statistics from genome-wide association studies in 17,802 participants from the African Partnership for Chronic Disease Research (APCDR) and African ancestry individuals from the Blood Cell Consortium (BCX2) using GWAMA. We further carried out a Bayesian fine mapping to identify causal variants driving the association with WBC subtypes. To access the causal relationship between WBC subtypes and asthma, we conducted a two-sample Mendelian randomization (MR) analysis using summary statistics of the Consortium on Asthma among African Ancestry Populations (CAAPA: ncases = 7,009, ncontrol = 7,645) as our outcome phenotype.Results: Our metanalysis identified 269 loci at a genome-wide significant value of (p = 5 × 10−9) in a composite of the WBC subtypes while the Bayesian fine-mapping analysis identified genetic variants that are more causal than the sentinel single-nucleotide polymorphism (SNP). We found for the first time five novel genes (LOC126987/MTCO3P14, LINC01525, GAPDHP32/HSD3BP3, FLG-AS1/HMGN3P1, and TRK-CTT13-1/MGST3) not previously reported to be associated with any WBC subtype. Our MR analysis showed that Mon (IVW estimate = 0.38, CI: 0.221, 0.539, p < 0.001), Neu (IVW estimate = 0.189, CI: 0.133, 0.245, p < 0.001), and WBCc (IVW estimate = 0.185, CI: 0.108, 0.262, p < 0.001) are associated with increased risk of asthma. However, there was no evidence of causal relationship between Lym and asthma risk.Conclusion: This study provides insight into the relationship between some WBC subtypes and asthma and potential route in the treatment of asthma and may further inform a new therapeutic approach.

scholarly journals CAUSALdb: a database for disease/trait causal variants identified using summary statistics of genome-wide association studies

2019 ◽  
Author(s):  
Jianhua Wang ◽  
Dandan Huang ◽  
Yao Zhou ◽  
Hongcheng Yao ◽  
Huanhuan Liu ◽  
...  
Keyword(s):  
Fine Mapping ◽  
Genetic Variants ◽  
Association Studies ◽  
Complex Trait ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Genome Wide ◽  
Credible Sets ◽  
Causal Variants

Abstract Genome-wide association studies (GWASs) have revolutionized the field of complex trait genetics over the past decade, yet for most of the significant genotype-phenotype associations the true causal variants remain unknown. Identifying and interpreting how causal genetic variants confer disease susceptibility is still a big challenge. Herein we introduce a new database, CAUSALdb, to integrate the most comprehensive GWAS summary statistics to date and identify credible sets of potential causal variants using uniformly processed fine-mapping. The database has six major features: it (i) curates 3052 high-quality, fine-mappable GWAS summary statistics across five human super-populations and 2629 unique traits; (ii) estimates causal probabilities of all genetic variants in GWAS significant loci using three state-of-the-art fine-mapping tools; (iii) maps the reported traits to a powerful ontology MeSH, making it simple for users to browse studies on the trait tree; (iv) incorporates highly interactive Manhattan and LocusZoom-like plots to allow visualization of credible sets in a single web page more efficiently; (v) enables online comparison of causal relations on variant-, gene- and trait-levels among studies with different sample sizes or populations and (vi) offers comprehensive variant annotations by integrating massive base-wise and allele-specific functional annotations. CAUSALdb is freely available at http://mulinlab.org/causaldb.

scholarly journals Fine mapping of breast cancer genome-wide association studies loci in women of African ancestry identifies novel susceptibility markers

2013 ◽  
Vol 34 (7) ◽  
pp. 1520-1528 ◽  
Author(s):  
Y. Zheng ◽  
T. O. Ogundiran ◽  
A. G. Falusi ◽  
K. L. Nathanson ◽  
E. M. John ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Fine Mapping ◽  
Association Studies ◽  
African Ancestry ◽  
Cancer Genome ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide

scholarly journals Correction to: Multi-ethnic genome-wide association analyses of white blood cell and platelet traits in the Population Architecture using Genomics and Epidemiology (PAGE) Study

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Yao Hu ◽  
Stephanie A. Bien ◽  
Katherine K. Nishimura ◽  
Jeffrey Haessler ◽  
Chani J. Hodonsky ◽  
...  
Keyword(s):  
Blood Cell ◽  
White Blood Cell ◽  
Genome Wide Association ◽  
Association Analyses ◽  
Genome Wide

scholarly journals Genome-Wide Association Study of White Blood Cell Counts in Patients With Ischemic Stroke

Stroke ◽  
2019 ◽  
Vol 50 (12) ◽  
pp. 3618-3621 ◽  
Author(s):  
Nuria P. Torres-Aguila ◽  
Caty Carrera ◽  
Anne-Katrine Giese ◽  
Natalia Cullell ◽  
Elena Muiño ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Blood Cell ◽  
Association Study ◽  
White Blood Cell ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Cell Counts ◽  
Blood Cell Counts ◽  
Genome Wide ◽  
White Blood Cell Counts

scholarly journals Prospects of Fine-Mapping Trait-Associated Genomic Regions by Using Summary Statistics from Genome-wide Association Studies

2017 ◽  
Vol 101 (4) ◽  
pp. 539-551 ◽  
Author(s):  
Christian Benner ◽  
Aki S. Havulinna ◽  
Marjo-Riitta Järvelin ◽  
Veikko Salomaa ◽  
Samuli Ripatti ◽  
...  
Keyword(s):  
Fine Mapping ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Genome Wide ◽  
Genomic Regions

scholarly journals Identification of nine novel loci related to hematological traits in a Japanese population

2018 ◽  
Vol 50 (9) ◽  
pp. 758-769 ◽  
Author(s):  
Yoshiki Yasukochi ◽  
Jun Sakuma ◽  
Ichiro Takeuchi ◽  
Kimihiko Kato ◽  
Mitsutoshi Oguri ◽  
...  
Keyword(s):  
Blood Cell ◽  
Cell Count ◽  
Genetic Variants ◽  
Association Studies ◽  
Single Point ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Monocyte Count ◽  
Blood Cell Count ◽  
Genome Wide

Recent genome-wide association studies have identified various genetic variants associated with hematological traits. Although it is possible that quantitative data of hematological traits are varied among the years examined, conventional genome-wide association studies have been conducted in a cross-sectional manner that measures traits at a single point in time. To address this issue, we have traced blood profiles in 4,884 Japanese individuals who underwent annual health check-ups for several years. In the present study, longitudinal exome-wide association studies were conducted to identify genetic variants related to 13 hematological phenotypes. The generalized estimating equation model showed that a total of 67 single nucleotide polymorphisms (SNPs) were significantly [false discovery rate (FDR) of <0.01] associated with hematological phenotypes. Of the 67 SNPs, nine SNPs were identified as novel hematological markers: rs4686683 of SENP2 for red blood cell count (FDR = 0.008, P = 5.5 × 10−6); rs3917688 of SELP for mean corpuscular volume (FDR = 0.005, P = 2.4 × 10−6); rs3133745 of C8orf37-AS1 for white blood cell count (FDR = 0.003, P = 1.3 × 10−6); rs13121954 at 4q31.2 for basophil count (FDR = 0.007, P = 3.1 × 10−5); rs7584099 at 2q22.3 (FDR = 2.6 × 10−5, P = 8.8 × 10−8), rs1579219 of HCG17 (FDR = 0.003, P = 2.0 × 10−5), and rs10757049 of DENND4C (FDR = 0.008, P = 5.6 × 10−5) for eosinophil count; rs12338 of CTSB for neutrophil count (FDR = 0.007, P = 2.9 × 10−5); and rs395967 of OSMR-AS1 for monocyte count (FDR = 0.008, P = 3.2 × 10−5).

scholarly journals A causal relationship between cigarette smoking and type 2 diabetes mellitus: A Mendelian randomization study

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Shuai Yuan ◽  
Susanna C. Larsson
Keyword(s):  
Type 2 Diabetes ◽  
Cigarette Smoking ◽  
Causal Relationship ◽  
Mendelian Randomization ◽  
Meta Analysis ◽  
Smoking Initiation ◽  
Genome Wide Association ◽  
European Ancestry ◽  
Genome Wide

AbstractThe causality between smoking and type 2 diabetes is unclear. We conducted a two-sample Mendelian randomization study to explore the causal relationship between smoking initiation and type 2 diabetes. Summary-level data for type 2 diabetes were obtained from a meta-analysis of 32 genome-wide association studies (DIAbetes Genetics Replication And Meta-analysis consortium), which included 898 130 individuals of European ancestry. Totally, 377 single-nucleotide polymorphisms associated with smoking initiation at genome wide significance threshold (p < 5 × 10−8) were identified from the hitherto largest genome-wide association study on smoking. The inverse-variance weighted, weighted median, MR-Egger regression, and MR-PRESSO approaches were used to analyze the data. Genetically predicted smoking initiation was associated with type 2 diabetes with an odds ratio of 1.28 (95% confidence interval, 1.20, 1.37; p = 2.35 × 10−12). Results were consistent across sensitivity analyses and there was no evidence of horizontal pleiotropy. This study provides genetic evidence supporting a causal association between the smoking initiation and type 2 diabetes. Reducing cigarette smoking initiation can now be even more strongly recommended for type 2 diabetes prevention.

scholarly journals Multi-ethnic genome-wide association analyses of white blood cell and platelet traits in the Population Architecture using Genomics and Epidemiology (PAGE) study

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Yao Hu ◽  
Stephanie A. Bien ◽  
Katherine K. Nishimura ◽  
Jeffrey Haessler ◽  
Chani J. Hodonsky ◽  
...  
Keyword(s):  
Blood Cell ◽  
White Blood Cell ◽  
Complex Traits ◽  
Association Studies ◽  
Genetic Association Studies ◽  
Genome Wide Association ◽  
European Ancestry ◽  
Genome Wide Association Studies ◽  
Association Analyses ◽  
Genome Wide

Abstract Background Circulating white blood cell and platelet traits are clinically linked to various disease outcomes and differ across individuals and ancestry groups. Genetic factors play an important role in determining these traits and many loci have been identified. However, most of these findings were identified in populations of European ancestry (EA), with African Americans (AA), Hispanics/Latinos (HL), and other races/ethnicities being severely underrepresented. Results We performed ancestry-combined and ancestry-specific genome-wide association studies (GWAS) for white blood cell and platelet traits in the ancestrally diverse Population Architecture using Genomics and Epidemiology (PAGE) Study, including 16,201 AA, 21,347 HL, and 27,236 EA participants. We identified six novel findings at suggestive significance (P < 5E-8), which need confirmation, and independent signals at six previously established regions at genome-wide significance (P < 2E-9). We confirmed multiple previously reported genome-wide significant variants in the single variant association analysis and multiple genes using PrediXcan. Evaluation of loci reported from a Euro-centric GWAS indicated attenuation of effect estimates in AA and HL compared to EA populations. Conclusions Our results highlighted the potential to identify ancestry-specific and ancestry-agnostic variants in participants with diverse backgrounds and advocate for continued efforts in improving inclusion of racially/ethnically diverse populations in genetic association studies for complex traits.

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