Elder, J. T. | bioRxiv Science

bioRxiv2024

Loopsim: Enrichment Analysis of ChromosomeConformation Capture with Fast EmpiricalDistribution Simulation

SummaryGene regulation is intricately influenced by the three-dimensional organization of the genome. In particular, chromatin can exist in loop structures that enable long-range regulatory interactions. By utilizing chromosome conformation capture techniques such as Hi-C, valuable information regarding the organization of these loop structures in 3D space can be obtained. While functional/feature enrichment has become a standard downstream analysis for different genomic data to provide biological context, tools that developed specifically for high throughput assays capturing chromosome conformation are relatively limited. Here, we present Loopsim, a command-line application that performs enrichment analysis on Hi-C loop profiles against user-defined regions. Loopsim efficiently simulates a background distribution using a distinctive sampling approach that considers loop size, intervals, loop-loop distances, and structure; it then computes loop-level statistics based on the empirical null distribution. AvailabilityLoopsim is a Python package available via PyPI (https://pypi.org/project/loopsim) and the source code is available on GitHub (https://github.com/CutaneousBioinf/Loopsim) under the MIT license.

bioinformatics↗

bioRxiv2018

Evidence of a common causal relationship between body mass index and inflammatory skin disease: a Mendelian Randomization study

ObjectivePsoriasis and eczema are common inflammatory skin diseases that have been reported to be associated with obesity. However, causality has not yet been established. We aimed to investigate the possible causal relationship between body mass index (BMI) and psoriasis or eczema.\n\nMethodsFollowing a review of published epidemiological evidence of the association between obesity and either psoriasis or eczema, Mendelian Randomization (MR) was used to test for a causal relationship between BMI and these inflammatory skin conditions. We used a genetic instrument comprising 97 single nucleotide polymorphisms (SNPs) associated with BMI. One-sample MR was conducted using individual-level data (401,508 individuals) from the UK Biobank and the Nord-Trondelag Health Study (HUNT), Norway. Two-sample MR was performed with summary-level data (731,021 individuals) from published BMI, psoriasis and eczema GWAS. The one-sample and two-sample MR estimates were meta-analysed using a fixed effect model. To explore the reverse causal direction, MR analysis with genetic instruments comprising variants from recent genome-wide analyses for psoriasis and eczema were used to test if inflammatory skin disease has a causal effect on BMI.\n\nResultsPublished observational data show an association of greater BMI with both psoriasis and eczema case status. The observational associations were confirmed in UK Biobank and HUNT datasets. MR analyses provide evidence that higher BMI causally increases the odds of psoriasis (by 53% per 5 units higher BMI; OR= 1.09 (1.06 to 1.12) per 1 kg/m2; P=4.67x10-9) and eczema (by 8% per 5 units higher BMI; OR=1.02 (1.00 to 1.03) per 1 kg/m2; P=0.09). When investigating causality in the opposite direction, MR estimates provide little evidence for an effect of either psoriasis or eczema influencing BMI.\n\nConclusionOur study, using genetic variants as instrumental variables for BMI, shows that higher BMI leads to a higher risk of inflammatory skin disease. The causal relationship was stronger for psoriasis than eczema. Therapies and life-style interventions aimed at controlling BMI or targeting the mechanisms linking obesity with skin inflammation may offer an opportunity for the prevention or treatment of these common skin diseases.

genetics↗