scholarly journals Functionally distinct ERAP1 and ERAP2 are a hallmark of HLA-A29-(Birdshot) Uveitis

2018 ◽  
Author(s):  
Jonas J.W. Kuiper ◽  
Jessica van Setten ◽  
Matthew Devall ◽  
Mircea Cretu-Stancu ◽  
Sanne Hiddingh ◽  
...  
Keyword(s):  
Protein Expression ◽  
Meta Analysis ◽  
Genetic Studies ◽  
Mhc I ◽  
Altered Expression ◽  
Transcriptomic Data ◽  
Root Cause ◽  
Protective Haplotype ◽  
Consistent Direction ◽  
Spanish Cohort

AbstractBirdshot Uveitis (Birdshot) is a rare eye condition that affects HLA-A29-positive individuals and could be considered a prototypic member of the recently proposed “MHC-I-opathy” family. Genetic studies have pinpointed the ERAP1 and ERAP2 genes as shared associations across MHC-I-opathies, which suggests ERAP dysfunction may be a root cause for MHC-I-opathies. We mapped the ERAP1 and ERAP2 haplotypes in 84 Dutch cases and 890 controls. We identified association at variant rs10044354, which mediated a marked increase in ERAP2 expression. We also identified and cloned an independently associated ERAP1 haplotype (tagged by rs2287987) present in more than half of the cases; this ERAP1 haplotype is also the primary risk and protective haplotype for other MHC-I-opathies. We show that the risk ERAP1 haplotype conferred significantly altered expression of ERAP1 isoforms in transcriptomic data (n=360), resulting in lowered protein expression and distinct enzymatic activity. Both the association for rs10044354 (meta-analysis: OR[95% CI]=2.07[1.58-2.71], p=1.24 × 10(−7)) and rs2287987 (OR[95% CI]: =2.01 [1.51-2.67], p=1.41 × 10(−6)) replicated and showed consistent direction of effect in an independent Spanish cohort of 46 cases and 2,103 controls. In both cohorts, the combined rs2287987-rs10044354 haplotype associated with Birdshot more strongly than either SNP alone (meta-analysis: p=3.9 × 10(−9)). Finally, we observed that ERAP2 protein expression is dependent on the ERAP1 background across three European populations (n=3,353). In conclusion, a functionally distinct combination of ERAP1 and ERAP2 are a hallmark of Birdshot and provide rationale for strategies designed to correct ERAP function for treatment of Birdshot and MHC-I-opathies more broadly.

Changes in myosin heavy chain mRNA and protein expression in human skeletal muscle with age and endurance exercise training

2005 ◽  
Vol 99 (1) ◽  
pp. 95-102 ◽  
Author(s):  
Kevin R. Short ◽  
Janet L. Vittone ◽  
Maureen L. Bigelow ◽  
David N. Proctor ◽  
Jill M. Coenen-Schimke ◽  
...  
Keyword(s):  
Exercise Training ◽  
Protein Expression ◽  
Myosin Heavy Chain ◽  
Endurance Exercise ◽  
Heavy Chain ◽  
Contractile Function ◽  
Mhc I ◽  
Altered Expression ◽  
Endurance Exercise Training ◽  
Mhc Iia

Aging is associated with reduced muscle strength and atrophy of type II muscle fibers. Muscle fiber type and contractile function are primarily determined by myosin heavy chain (MHC) isoforms. There are few data available on the effects of aging on MHC isoform expression in humans. In the present study, we tested the hypothesis that MHC isoform protein composition and mRNA abundance would favor a fast-to-slow isoform shift with aging and in response to endurance exercise training. Muscle biopsies were obtained from previously sedentary, healthy men and women, aged 21–87 yr before ( n = 77) and after ( n = 65) 16 wk of bicycle training (up to 45 min at 80% peak heart rate, 3–4 days/wk). At baseline, MHC I mRNA was unchanged with age, whereas IIa and IIx declined by 14 and 10% per decade, respectively ( P < 0.001). MHC IIa and IIx protein declined by 3 and 1% per decade with a reciprocal increase in MHC I ( P < 0.05). After training, MHC I and IIa mRNA increased by 61 and 99%, respectively, and IIx decreased by 50% (all P < 0.001). The increase in MHC I mRNA was positively associated with age, whereas the changes in MHC IIa and IIx mRNA were similar across age. MHC I protein increased by 6% and was positively related to age, whereas IIx decreased by 5% and was inversely related to age. These results suggest that the altered expression of MHC isoforms with aging is transcriptionally regulated. In response to endurance exercise, regulation of MHC isoform transcripts remains robust in older muscle, but this did not result in corresponding changes in MHC protein expression.

scholarly journals Meta-analysis of transcriptomic data reveals clusters of consistently deregulated gene and disease ontologies in Down syndrome

2021 ◽  
Vol 17 (9) ◽  
pp. e1009317
Author(s):  
Ilario De Toma ◽  
Cesar Sierra ◽  
Mara Dierssen
Keyword(s):  
Down Syndrome ◽  
Differential Expression ◽  
Web Application ◽  
Meta Analysis ◽  
Chromosome 21 ◽  
Complex Disorders ◽  
Transcriptomic Data ◽  
Genome Wide ◽  
A Genome ◽  
The Impact

Trisomy of human chromosome 21 (HSA21) causes Down syndrome (DS). The trisomy does not simply result in the upregulation of HSA21--encoded genes but also leads to a genome-wide transcriptomic deregulation, which affect differently each tissue and cell type as a result of epigenetic mechanisms and protein-protein interactions. We performed a meta-analysis integrating the differential expression (DE) analyses of all publicly available transcriptomic datasets, both in human and mouse, comparing trisomic and euploid transcriptomes from different sources. We integrated all these data in a “DS network”. We found that genome wide deregulation as a consequence of trisomy 21 is not arbitrary, but involves deregulation of specific molecular cascades in which both HSA21 genes and HSA21 interactors are more consistently deregulated compared to other genes. In fact, gene deregulation happens in “clusters”, so that groups from 2 to 13 genes are found consistently deregulated. Most of these events of “co-deregulation” involve genes belonging to the same GO category, and genes associated with the same disease class. The most consistent changes are enriched in interferon related categories and neutrophil activation, reinforcing the concept that DS is an inflammatory disease. Our results also suggest that the impact of the trisomy might diverge in each tissue due to the different gene set deregulation, even though the triplicated genes are the same. Our original method to integrate transcriptomic data confirmed not only the importance of known genes, such as SOD1, but also detected new ones that could be extremely useful for generating or confirming hypotheses and supporting new putative therapeutic candidates. We created “metaDEA” an R package that uses our method to integrate every kind of transcriptomic data and therefore could be used with other complex disorders, such as cancer. We also created a user-friendly web application to query Ensembl gene IDs and retrieve all the information of their differential expression across the datasets.

Genetics of Depression

2013 ◽  
pp. 396-410
Author(s):  
Douglas F. Levinson
Keyword(s):  
Association Studies ◽  
Meta Analysis ◽  
Lifetime Risk ◽  
Depression And Anxiety ◽  
Genetic Studies ◽  
Candidate Gene Studies ◽  
Methodological Problems ◽  
Continuous Measures ◽  
Depressive Episodes ◽  
Significant Linkage

Categorical major depressive disorder has been the focus of most genetic studies, although some studies use continuous measures or consider both depression and anxiety. Lifetime risk of major depression is high (12-20%), heritability is below 40%, and the relative risk to first-degree relatives is approximately 3. These characteristics are challenging for current genetic methods. There have been several significant linkage findings which do not consistently replicate. Genomewide association studies have not produced significant findings, but analyses that cut across diagnostic boundaries seem promising. Candidate gene studies have been fraught with methodological problems, although the largest meta-analysis to date supported the hypothesis that 5-HTTLPR genotype and specific stressors interact to predict depressive episodes (but not lifetime risk of depression). Future steps include application of sequencing and stem cell technologies. Methods are need to build larger samples with more detailed clinical assessment. Outstanding genetic epidemiological issues should be addressed by new studies.

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