scholarly journals Identification of seven genes essential for male fertility through a genome-wide association study of non-obstructive azoospermia and RNA interference-mediated large-scale functional screening in Drosophila

2014 ◽  
Vol 24 (5) ◽  
pp. 1493-1503 ◽  
Author(s):  
J. Yu ◽  
H. Wu ◽  
Y. Wen ◽  
Y. Liu ◽  
T. Zhou ◽  
...  
2011 ◽  
Vol 44 (2) ◽  
pp. 183-186 ◽  
Author(s):  
Zhibin Hu ◽  
Yankai Xia ◽  
Xuejiang Guo ◽  
Juncheng Dai ◽  
HongGang Li ◽  
...  

Author(s):  
Daigo Okada ◽  
Naotoshi Nakamura ◽  
Kazuya Setoh ◽  
Takahisa Kawaguchi ◽  
Koichiro Higasa ◽  
...  

AbstractHuman immune systems are very complex, and the basis for individual differences in immune phenotypes is largely unclear. One reason is that the phenotype of the immune system is so complex that it is very difficult to describe its features and quantify differences between samples. To identify the genetic factors that cause individual differences in whole lymphocyte profiles and their changes after vaccination without having to rely on biological assumptions, we performed a genome-wide association study (GWAS), using cytometry data. Here, we applied computational analysis to the cytometry data of 301 people before receiving an influenza vaccine, and 1, 7, and 90 days after the vaccination to extract the feature statistics of the lymphocyte profiles in a nonparametric and data-driven manner. We analyzed two types of cytometry data: measurements of six markers for B cell classification and seven markers for T cell classification. The coordinate values calculated by this method can be treated as feature statistics of the lymphocyte profile. Next, we examined the genetic basis of individual differences in human immune phenotypes with a GWAS for the feature statistics, and we newly identified seven significant and 36 suggestive single-nucleotide polymorphisms associated with the individual differences in lymphocyte profiles and their change after vaccination. This study provides a new workflow for performing combined analyses of cytometry data and other types of genomics data.


Author(s):  
Mary Hoekstra ◽  
Hao Yu Chen ◽  
Jian Rong ◽  
Line Dufresne ◽  
Jie Yao ◽  
...  

Objective: Lp(a) (lipoprotein[a]) is an independent risk factor for cardiovascular diseases and plasma levels are primarily determined by variation at the LPA locus. We performed a genome-wide association study in the UK Biobank to determine whether additional loci influence Lp(a) levels. Approach and Results: We included 293 274 White British individuals in the discovery analysis. Approximately 93 095 623 variants were tested for association with natural log-transformed Lp(a) levels using linear regression models adjusted for age, sex, genotype batch, and 20 principal components of genetic ancestry. After quality control, 131 independent variants were associated at genome-wide significance (P ≤5×10 -8 ). In addition to validating previous associations at LPA , APOE , and CETP , we identified a novel variant at the APOH locus, encoding β2GPI (beta2-glycoprotein I). The APOH variant rs8178824 was associated with increased Lp(a) levels (β [95% CI] [ln nmol/L], 0.064 [0.047–0.081]; P =2.8×10 -13 ) and demonstrated a stronger effect after adjustment for variation at the LPA locus (β [95% CI] [ln nmol/L], 0.089 [0.076–0.10]; P =3.8×10 -42 ). This association was replicated in a meta-analysis of 5465 European-ancestry individuals from the Framingham Offspring Study and Multi-Ethnic Study of Atherosclerosis (β [95% CI] [ln mg/dL], 0.16 [0.044–0.28]; P =0.0071). Conclusions: In a large-scale genome-wide association study of Lp(a) levels, we identified APOH as a novel locus for Lp(a) in individuals of European ancestry. Additional studies are needed to determine the precise role of β2GPI in influencing Lp(a) levels as well as its potential as a therapeutic target.


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