scholarly journals Association study of childhood food allergy with genome-wide association studies–discovered loci of atopic dermatitis and eosinophilic esophagitis

2017 ◽  
Vol 140 (6) ◽  
pp. 1713-1716 ◽  
Author(s):  
Tomomitsu Hirota ◽  
Tsuguhisa Nakayama ◽  
Sakura Sato ◽  
Noriyuki Yanagida ◽  
Teruaki Matsui ◽  
...  
2021 ◽  
Author(s):  
Gui-Juan Feng ◽  
Qian Xu ◽  
Jing-Jing Ni ◽  
Shan-Shan Yang ◽  
Bai-Xue Han ◽  
...  

Abstract Age at menarche (AAM) is a sign of puberty of females. It is a heritable trait associated with various adult diseases. However, the genetic mechanism that determines AAM and links it to disease risk is poorly understood. Aiming to uncover the genetic basis for AAM, we conducted a joint association study in up to 438,089 participants from 3 genome-wide association studies of European and East Asian ancestries. Twenty-one novel genomic loci were identified at the genome-wide significance level. Besides, we observed significant genetic correlations between AAM and 67 complex traits, and the highest genetic correlation was observed between AAM and body mass index (rg=-0.19, P=6.11×10−31). Latent causal variable analyses demonstrate that there is a genetically causal effect of AAM on high blood pressure (GCP=0.47, P=0.02), forced vital capacity (GCP=0.63, P=0.02), age at first live birth (GCP=0.51, P=0.03), impedance of right arm (GCP=0.41, P<1×10-7) and right leg fat percentage (GCP=-0.10, P=0.02), etc. Enrichment analysis identified 5 enriched tissues and 51 enriched gene sets. Four of the five enriched tissues were related to the nervous system, including the hypothalamus middle, hypothalamo hypophyseal system, neurosecretory systems and hypothalamus. The fifth tissue was the retina in the sensory organ. The most significant gene set was the ‘decreased circulating luteinizing hormone level’ (P=2.45×10-6). Our findings may provide useful insights that elucidate the mechanisms determining AAM and the genetic interplay between AAM and some traits of women.


Cephalalgia ◽  
2014 ◽  
Vol 35 (9) ◽  
pp. 776-782 ◽  
Author(s):  
Cèlia Sintas ◽  
Jèssica Fernández-Morales ◽  
Marta Vila-Pueyo ◽  
Bernat Narberhaus ◽  
Concepció Arenas ◽  
...  

Background Migraine is a common disabling condition that affects approximately 15% of the population. Several genome-wide association studies have attempted to identify susceptibility variants involved in migraine, reporting several candidate loci for the disorder. Methods In order to replicate findings from previous genome-wide association studies, a case–control association study was performed. Twelve single nucleotide polymorphisms were genotyped in a Spanish sample of 512 migraine with aura patients and 535 migraine-free controls. Results Nominal associations were found for single nucleotide polymorphisms rs2651899 (within the PRDM16 gene), rs10166942 (near TRPM8), rs12134493 (close to TSPAN2) and rs10504861 (near MMP16) in our migraine with aura sample. Conclusions Our study provides suggestive replication, in a Spanish migraine with aura sample, of four genome-wide association study findings previously reported in common migraine. However, larger sample sets should be explored to confirm our results.


Author(s):  
Braden T Tierney ◽  
Yixuan He ◽  
George M Church ◽  
Eran Segal ◽  
Aleksandar D Kostic ◽  
...  

AbstractOver the past decade, studies of the human genome and microbiome have deepened our understanding of the connections between human genes, environments, microbes, and disease. For example, the sheer number of indicators of the microbiome and human genetic common variants associated with disease has been immense, but clinical utility has been elusive. Here, we compared the predictive capabilities of the human microbiome versus human genomic common variants across 13 common diseases. We concluded that microbiomic indicators outperform human genetics in predicting host phenotype (overall Microbiome-Association-Study [MAS] area under the curve [AUC] = 0.79 [SE = 0.03], overall Genome-Wide-Association-Study [GWAS] AUC = 0.67 [SE = 0.02]). Our results, while preliminary and focused on a subset of the totality of disease, demonstrate the relative predictive ability of the microbiome, indicating that it may outperform human genetics in discriminating human disease cases and controls. They additionally motivate the need for population-level microbiome sequencing resources, akin to the UK Biobank, to further improve and reproduce metagenomic models of disease.


2020 ◽  
Vol 112 (10) ◽  
pp. 1003-1012 ◽  
Author(s):  
Jun Zhong ◽  
Ashley Jermusyk ◽  
Lang Wu ◽  
Jason W Hoskins ◽  
Irene Collins ◽  
...  

Abstract Background Although 20 pancreatic cancer susceptibility loci have been identified through genome-wide association studies in individuals of European ancestry, much of its heritability remains unexplained and the genes responsible largely unknown. Methods To discover novel pancreatic cancer risk loci and possible causal genes, we performed a pancreatic cancer transcriptome-wide association study in Europeans using three approaches: FUSION, MetaXcan, and Summary-MulTiXcan. We integrated genome-wide association studies summary statistics from 9040 pancreatic cancer cases and 12 496 controls, with gene expression prediction models built using transcriptome data from histologically normal pancreatic tissue samples (NCI Laboratory of Translational Genomics [n = 95] and Genotype-Tissue Expression v7 [n = 174] datasets) and data from 48 different tissues (Genotype-Tissue Expression v7, n = 74–421 samples). Results We identified 25 genes whose genetically predicted expression was statistically significantly associated with pancreatic cancer risk (false discovery rate &lt; .05), including 14 candidate genes at 11 novel loci (1p36.12: CELA3B; 9q31.1: SMC2, SMC2-AS1; 10q23.31: RP11-80H5.9; 12q13.13: SMUG1; 14q32.33: BTBD6; 15q23: HEXA; 15q26.1: RCCD1; 17q12: PNMT, CDK12, PGAP3; 17q22: SUPT4H1; 18q11.22: RP11-888D10.3; and 19p13.11: PGPEP1) and 11 at six known risk loci (5p15.33: TERT, CLPTM1L, ZDHHC11B; 7p14.1: INHBA; 9q34.2: ABO; 13q12.2: PDX1; 13q22.1: KLF5; and 16q23.1: WDR59, CFDP1, BCAR1, TMEM170A). The association for 12 of these genes (CELA3B, SMC2, and PNMT at novel risk loci and TERT, CLPTM1L, INHBA, ABO, PDX1, KLF5, WDR59, CFDP1, and BCAR1 at known loci) remained statistically significant after Bonferroni correction. Conclusions By integrating gene expression and genotype data, we identified novel pancreatic cancer risk loci and candidate functional genes that warrant further investigation.


2018 ◽  
Author(s):  
Lynsey S Hall ◽  
Christopher W Medway ◽  
Antonio F Pardinas ◽  
Elliott G Rees ◽  
Valentina Escott-Price ◽  
...  

AbstractSchizophrenia is a complex highly heritable disorder. Genome-wide association studies have identified multiple loci that influence the risk of developing schizophrenia, although the causal variants driving these associations and their impacts on specific genes are largely unknown. Here we link genetic findings to gene expression in the human brain by performing a transcriptome-wide association study (TWAS) in which we integrate the largest published genome-wide association dataset of schizophrenia, with publically available post mortem expression data from the dorsolateral prefrontal cortex (DLPFC). We identify a significant correlation between schizophrenia risk and expression at eighty-nine genes in DLPFC, including forty-two genes not identified in earlier TWAS of this transcriptomic resource. Genes whose expression correlate with schizophrenia were enriched for those involved in nervous system development, abnormal synaptic transmission, reduced long term potentiation, and calcium-dependent cell-cell adhesion. Previous genetic studies have implicated post-synaptic glutamatergic and gabaergic processes in schizophrenia; here we extend this to include molecules that regulate presynaptic transmitter release. We identify specific candidate genes to which we assign predicted directions of effect in terms of expression level, facilitating downstream experimental studies geared towards a better mechanistic understanding of schizophrenia pathogenesis.


2014 ◽  
Vol 76 (3) ◽  
pp. 310-315 ◽  
Author(s):  
Xiang-Rui Meng ◽  
Jie-Yun Song ◽  
Jun Ma ◽  
Fang-Hong Liu ◽  
Xiao-Rui Shang ◽  
...  

2011 ◽  
Vol 44 (2) ◽  
pp. 187-192 ◽  
Author(s):  
Lavinia Paternoster ◽  
◽  
Marie Standl ◽  
Chih-Mei Chen ◽  
Adaikalavan Ramasamy ◽  
...  

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