Evidence map›Paper›PMID 41256748›Full record

ArticleJournal of clinical practice and research2023

Estimation of Genetic Correlation Between Rheumatoid Arthritis and Multiple Sclerosis Using Summary Statistics from Genome-Wide Association Studies.

Ragıp Onur Öztornacı

Abstract read
In one paragraph

Article in Journal of clinical practice and research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

1 author.

Ragıp Onur ÖztornacıKoç University Translational Research Center, Koç University, İstanbul, Türkiye.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Genome-wide association studies (GWAS) have revolutionized our understanding of the genetic basis of diseases by examining millions of genetic variants across the genome. Rheumatoid arthritis (RA) and multiple sclerosis (MS) are chronic autoimmune diseases characterized by immune system dysregulation and inflammation. Investigating the genetic correlation between RA and MS can provide insights into shared genetic factors, potential mechanisms, and pathways underlying these complex disorders. The objective of this study was to compare different statistical methods to estimate the genetic correlation between RA and MS using GWAS summary statistics. Materials and Methods: To estimate single nucleotide polymorphism (SNP) heritability and genetic correlation, we utilized two popular methods: Linkage Disequilibrium Score Regression (LDSC) and Linkage Disequilibrium Adjusted Kinship (LDAK) models. Results: Our analysis revealed a significant, moderate, positive correlation between RA and MS using both LDSC and LDAK (LSDC Conclusion: There is a significant positive genetic correlation between RA and MS, indicating a shared genetic component. Differential heritability estimates from LDAK and LDSC highlight the importance of the method. Genetic overlap informs common pathways and potential therapeutic targets. These findings contribute to the evidence of a moderately positive genetic correlation, emphasizing the need for further research and personalized approaches to managing autoimmune diseases.

Indexed as

Genetic correlationgenome-wide association studies summary statisticslinkage disequilibrium adjusted kinship (LDAK)linkage disequilibrium score regression (LDSC)snp heritability

Identifiers

PMID41256748
PMCPMC12478714

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.