Global transcriptional changes caused by an EDMD mutation correlate to tissue specific disease phenotypes inC. elegans

Parkinson disease (PD) is a complex neurodegenerative disease with a range of causes and clinical presentations. Over 76 genetic loci (comprising 90 SNPs) have been associated with PD by the most recent GWAS meta-analysis. Most of these PD-associated variants are located in non-coding regions of the genome and it is difficult to understand what they are doing and how they contribute to the aetiology of PD. We hypothesised that PD-associated genetic variants modulate disease risk through tissue-specific expression quantitative trait loci (eQTL) effects. We developed and validated a machine learning approach that integrated tissue-specific eQTL data on known PD-associated genetic variants with PD case and control genotypes from the Wellcome Trust Case Control Consortium, the UK Biobank, and NeuroX. In so doing, our analysis ranked the tissue-specific transcription effects for PD-associated genetic variants and estimated their relative contributions to PD risk. We identified roles for SNPs that are connected with INPP5P, CNTN1, GBA and SNCA in PD. Ranking the variants and tissue-specific eQTL effects contributing most to the machine learning model suggested a key role in the risk of developing PD for two variants (rs7617877 and rs6808178) and eQTL associated transcriptional changes of EAF1-AS1 within the heart atrial appendage. Similarly, effects associated with eQTLs located within the brain cerebellum were also recognized to confer major PD risk. These findings warrant further mechanistic investigations to determine if these transcriptional changes could act as early contributors to PD risk and disease development.

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Combination of acid β-glucosidase mutation and Saposin C deficiency in mice reveals Gba1 mutation dependent and tissue-specific disease phenotype

Scientific Reports ◽

10.1038/s41598-019-41914-7 ◽

2019 ◽

Vol 9 (1) ◽

Author(s):

Benjamin Liou ◽

Wujuan Zhang ◽

Venette Fannin ◽

Brian Quinn ◽

Huimin Ran ◽

...

Keyword(s):

Disease Phenotype ◽

Tissue Specific ◽

Specific Disease ◽

Saposin C

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VGF: An inducible gene product, precursor of a diverse array of neuro-endocrine peptides and tissue-specific disease biomarkers

Journal of Chemical Neuroanatomy ◽

10.1016/j.jchemneu.2011.05.007 ◽

2011 ◽

Vol 42 (4) ◽

pp. 249-261 ◽

Cited By ~ 36

Author(s):

Gian-Luca Ferri ◽

Barbara Noli ◽

Carla Brancia ◽

Filomena D’Amato ◽

Cristina Cocco

Keyword(s):

Gene Product ◽

Tissue Specific ◽

Disease Biomarkers ◽

Specific Disease ◽

Inducible Gene

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Insights into genetic factors contributing to variability in SARS-CoV-2 susceptibility and COVID-19 disease severity

10.1101/2021.05.10.21256423 ◽

2021 ◽

Author(s):

Matteo D'Antonio ◽

Timothy D. Arthur ◽

Jennifer P. Nguyen ◽

Hiroko Matsui ◽

Agnieszka D'Antonio-Chronowska ◽

...

Keyword(s):

Disease Severity ◽

Molecular Mechanisms ◽

Genetic Factors ◽

Summary Statistics ◽

Altered Expression ◽

Tissue Specific ◽

Host Genetics ◽

Disease Phenotypes ◽

Specific Signal ◽

Similarities And Differences

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we applied colocalization to compare summary statistics for 16 GWASs from the COVID-19 Host Genetics Initiative to investigate similarities and differences in their genetic signals. We identified 9 loci associated with susceptibility (one with two independent GWAS signals; one with an ethnicity-specific signal), 14 associated with severity (one with two independent GWAS signals; two with ethnicity-specific signals) and one harboring two discrepant GWAS signals (one for susceptibility; one for severity). Utilizing colocalization we also identified 45 GTEx tissues that had eQTL(s) for 18 genes strongly associated with GWAS signals in eleven loci (1-4 genes per locus). Some of these genes showed tissue-specific altered expression and others showed altered expression in up to 41 different tissue types. Our study provides insights into the complex molecular mechanisms underlying inherited predispositions to COVID-19-disease phenotypes.

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Machine Learning Identifies Six Genetic Variants and Alterations in the Heart Atrial Appendage as Key Contributors to PD Risk Predictivity

Frontiers in Genetics ◽

10.3389/fgene.2021.785436 ◽

2022 ◽

Vol 12 ◽

Author(s):

Daniel Ho ◽

William Schierding ◽

Sophie L. Farrow ◽

Antony A. Cooper ◽

Andreas W. Kempa-Liehr ◽

...

Keyword(s):

Machine Learning ◽

Genetic Variants ◽

Disease Risk ◽

Meta Analysis ◽

Atrial Appendage ◽

Specific Expression ◽

Tissue Specific ◽

Transcriptional Changes ◽

The Uk ◽

Eqtl Data

Parkinson’s disease (PD) is a complex neurodegenerative disease with a range of causes and clinical presentations. Over 76 genetic loci (comprising 90 SNPs) have been associated with PD by the most recent GWAS meta-analysis. Most of these PD-associated variants are located in non-coding regions of the genome and it is difficult to understand what they are doing and how they contribute to the aetiology of PD. We hypothesised that PD-associated genetic variants modulate disease risk through tissue-specific expression quantitative trait loci (eQTL) effects. We developed and validated a machine learning approach that integrated tissue-specific eQTL data on known PD-associated genetic variants with PD case and control genotypes from the Wellcome Trust Case Control Consortium. In so doing, our analysis ranked the tissue-specific transcription effects for PD-associated genetic variants and estimated their relative contributions to PD risk. We identified roles for SNPs that are connected with INPP5P, CNTN1, GBA and SNCA in PD. Ranking the variants and tissue-specific eQTL effects contributing most to the machine learning model suggested a key role in the risk of developing PD for two variants (rs7617877 and rs6808178) and eQTL associated transcriptional changes of EAF1-AS1 within the heart atrial appendage. Similarly, effects associated with eQTLs located within the Brain Cerebellum were also recognized to confer major PD risk. These findings were replicated in two additional, independent cohorts (the UK Biobank, and NeuroX) and thus warrant further mechanistic investigations to determine if these transcriptional changes could act as early contributors to PD risk and disease development.

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Disease tolerance alters host competence in a wild songbird

Biology Letters ◽

10.1098/rsbl.2021.0362 ◽

2021 ◽

Vol 17 (10) ◽

Author(s):

Rachel M. Ruden ◽

James S. Adelman

Keyword(s):

Clinical Signs ◽

Fitness Costs ◽

Tissue Specific ◽

House Finches ◽

Disease Phenotypes ◽

Bird Feeders ◽

Host Competence ◽

Behavioural Tolerance ◽

Pathogen Fitness ◽

Specific Tolerance

Individuals can express a range of disease phenotypes during infection, with important implications for epidemics. Tolerance, in particular, is a host response that minimizes the per-pathogen fitness costs of infection. Because tolerant hosts show milder clinical signs and higher survival, despite similar pathogen burdens, their potential for prolonged pathogen shedding may facilitate the spread of pathogens. To test this, we simulated outbreaks of mycoplasmal conjunctivitis in house finches, asking how the speed of transmission varied with tissue-specific and behavioural components of tolerance, milder conjunctivitis and anorexia for a given pathogen load, respectively. Because tissue-specific tolerance hinders pathogen deposition onto bird feeders, important transmission hubs, we predicted it would slow transmission. Because behavioural tolerance should increase interactions with bird feeders, we predicted it would speed transmission. Our findings supported these predictions, suggesting that variation in tolerance could help identify individuals most likely to transmit pathogens.

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