Genetic analyses identify pleiotropy and causality for blood proteins and highlight Wnt/β-catenin signalling in migraine

Tanha, Hamzeh Mesrian; Nyholt, Dale R.

doi:10.1038/s41467-022-30184-z

Cited by 10 publications

(10 citation statements)

References 65 publications

(104 reference statements)

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“…Follow-up studies have also shown that FARS2 de ciency leads to reduced mitochondrial tRNA(Phe) aminylation, abnormal mitochondrial tRNA metabolism, reduced mitochondrial complex levels, reduced respiratory chain complex enzyme activity, and mitochondrial dysfunction, which in turn affects cell growth and development 74 . Furthermore, it has also been shown that pQTL loci on FARS2 share genetic structure with migraine 75 .…”

Section: Discussionmentioning

confidence: 99%

Assessing the causal relationship between mitochondria-associated proteins and chronic liver diseases：a comprehensive Mendelian randomisation study

guo,

Ye,

Wang

et al. 2023

Preprint

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Mitochondria-related proteins (MRPs) and chronic liver diseases have been linked in various studies, although their causal relationship has not been elucidated. In this study, we investigated the causal associations between MRPs and non-alcoholic fatty liver disease (NALFD), liver cirrhosis and hepatocellular carcinoma (HCC) by two-sample bidirectional Mendelian randomisation(MR) analysis.The random-effect Inverse variance weighted (IVW) is the primary analysis for causality analysis while MR-Egger and Weighted Median (WM) as complementary analyses. Cochran Q test, MR-Egger intercept test, MR-PRESSO and leave-one-out analysis were used for sensitivity analyses. In addition, we performed bonferroni correction,multivariable MR analysis(MVMR),reverse causality detection and protein–protein interaction(PPI) network to enrich the results of this study.After rigorous genetic variant selection, IVW, sensitivity analysis, 3 genetically determined MRPs were significantly associated with NAFLD [MRPL33 (OR: 1.06, 95% CI: 1.00-1.11, p = 0.0284), MRPL34 (OR: 0.88, 95% CI: 0.78–0.98, p = 0.0294) and FARS2 (OR : 0.90, 95% CI: 0.84–0.97, p = 0.0120)], 2 MRPs were significantly associated with liver cirrhosis[MICU1 (OR: 1.11, 95% CI: 1.00-1.22, p = 0.0337) and NUDT8 (OR: 1.16, 95% CI: 1.03–1.30, p = 0.0096)], and 4 MRPs were significantly correlated with HCC [MRPL32 (OR: 0.62, 95% CI: 0.39–0.99, p = 0. 0492), MRPL33 (OR:1.29, 95% CI: 1.07–1.55, p = 0.0063), SCO1 (OR:0.56, 95% CI. 0.38–0.83, p = 0.0036) and SIRT5 (OR:0.71, 95% CI: 0.53–0.96, p = 0.0283)].Our findings provide a new perspective on the exploration of the underlying mechanisms of chronic liver diseases. However, further studies are still needed to explore the mechanisms of possible potential causal associations between MRPs and chronic liver diseases.

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Section: Discussionmentioning

confidence: 99%

Assessing the causal relationship between mitochondria-associated proteins and chronic liver diseases：a comprehensive Mendelian randomisation study

guo,

Ye,

Wang

et al. 2023

Preprint

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“…To date, many scholars have applied the LCV approach to integrate multi-omics data and identified causal associations between the proteome and some phenotypes, such as migraine, blood biomarkers, and psychiatric disorders. [ 72 , 73 ] We believe that the LCV method can also be applied to the proteome and genome integration analysis of obesity.…”

Section: Discussionmentioning

confidence: 99%

Proteome and genome integration analysis of obesity

Zhao

Han

et al. 2023

Chinese Medical Journal

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The prevalence of obesity has increased worldwide in recent decades. Genetic factors are now known to play a substantial role in the predisposition to obesity and may contribute up to 70% of the risk for obesity. Technological advancements during the last decades have allowed the identification of many hundreds of genetic markers associated with obesity. However, the transformation of current genetic variant-obesity associations into biological knowledge has been proven challenging. Genomics and proteomics are complementary fields, as proteomics extends functional analyses. Integrating genomic and proteomic data can help to bridge a gap in knowledge regarding genetic variantobesity associations and to identify new drug targets for the treatment of obesity. We provide an overview of the published papers on the integrated analysis of proteomic and genomic data in obesity and summarize four mainstream strategies: overlap, colocalization, Mendelian randomization, and proteome-wide association studies. The integrated analyses identified many obesity-associated proteins, such as leptin, follistatin, and adenylate cyclase 3. Despite great progress, integrative studies focusing on obesity are still limited. There is an increased demand for large prospective cohort studies to identify and validate findings, and further apply these findings to the prevention, intervention, and treatment of obesity. In addition, we also discuss several other potential integration methods.

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“…stressful life events, vasoconstriction, platelet clumping, and occupational exposure to paints, glues or thinner, and diesel exhaust (103). Studies are also starting to emerge that examine other health-related markers such as brain volume (104), blood metabolites (90), and blood proteins (105). In addition to the caution that replication of positive MR findings is urgently needed, it is also important to note, that the power of a MR study is dependent on the size of the original GWAS.…”

Section: Causality In Migrainementioning

confidence: 99%

Migraine genetics: Status and road forward

et al. 2023

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Background Migraine is considered a multifactorial genetic disorder. Different platforms and methods are used to unravel the genetic basis of migraine. Initially, linkage analysis in multigenerational families followed by Sanger sequencing of protein-coding parts (exons) of genes in the genomic region shared by affected family members identified high-effect risk DNA mutations for rare Mendelian forms of migraine, foremost hemiplegic migraine. More recently, genome-wide association studies testing millions of DNA variants in large groups of patients and controls have proven successful in identifying many dozens of low-effect risk DNA variants for the more common forms of migraine with the number of associated DNA variants increasing steadily with larger sample sizes. Currently, next-generation sequencing, utilising whole exome and whole genome sequence data, and other omics data are being used to facilitate their functional interpretation and the discovery of additional risk factors. Various methods and analysis tools, such as genetic correlation and causality analysis, are used to further characterise genetic risk factors. Findings We describe recent findings in genome-wide association studies and next-generation sequencing analysis in migraine. We show that the combined results of the two most recent and most powerful migraine genome-wide association studies have identified a total of 178 LD-independent ( r2 < 0.1) genome-wide significant single nucleotide polymorphisms (SNPs), of which 99 were unique to Hautakangas et al., 11 were unique to Choquet et al., and 68 were identified by both studies. When considering that Choquet et al. also identified three SNPs in a female-specific genome-wide association studies then these two recent studies identified 181 independent SNPs robustly associated with migraine. Cross-trait and causal analyses are beginning to identify and characterise specific biological factors that contribute to migraine risk and its comorbid conditions. Conclusion This review provides a timely update and overview of recent genetic findings in migraine.

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Genetic analyses identify pleiotropy and causality for blood proteins and highlight Wnt/β-catenin signalling in migraine

Abstract: Migraine is a common complex disorder with a significant polygenic SNP heritability ($${h}_{{SNP}}^{2}$$ h S N P 2 ). Here we utilise genome-wide association study (GWAS) summary statistics to study pleiotropy between blood p… Show more

Cited by 10 publications

References 65 publications

Assessing the causal relationship between mitochondria-associated proteins and chronic liver diseases：a comprehensive Mendelian randomisation study

Assessing the causal relationship between mitochondria-associated proteins and chronic liver diseases：a comprehensive Mendelian randomisation study

Proteome and genome integration analysis of obesity

Migraine genetics: Status and road forward

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