Serum Uric Acid Level and Multiple Sclerosis: A Mendelian Randomization Study

Assessing the causal effect of genetically predicted metabolites and metabolic pathways on vitiligo: Evidence from Mendelian randomization and animal experiments

Vitiligo is a common chronic skin depigmentation disorder that seriously decreases the patients' overall quality of life. Human blood metabolites could contribute to unraveling the underlying biological mechanisms of vitiligo. We used GWAS summary statistics to assess the causal association between genetically predicted 1400 serum metabolites and vitiligo risk by Mendelian randomization (MR). Then, after constructing the mouse model of vitiligo, we did non-targeted metabolomics analysis on the mouse serum and validated MR's pathway enrichment results ulteriorly. In the initial phase, MR analysis revealed causative associations between 36 metabolites and vitiligo risk, including 8 metabolite ratios and 28 individual metabolites (19 known and 9 unknown metabolites). In the validation stage, 7 metabolites were successfully validated. Of the 28 individual metabolites, most are related to lipid metabolism. Genetically predicted higher 4-oxo-retinoic acid showed the strongest protective effect on vitiligo, while the most potent risk effect was the increase in quinate. The metabolites associated with vitiligo risk are mainly enriched in alpha-linolenic acid metabolism, linoleic acid metabolism, arginine biosynthesis and metabolism pathways, validated through the serum metabolomics of vitiligo mouse. By integrating genomics and metabolomics, this study provides new insights into the association between metabolites and vitiligo, highlighting the potential roles of specific metabolites in the pathogenesis of vitiligo. These metabolites associated with vitiligo could serve as new biomarkers, further research could help to reveal how these metabolites influence specific pathways in the development of vitiligo.

Allopurinol use and risk of multiple sclerosis

BACKGROUND

Low uric acid levels have been observed in patients with multiple sclerosis (MS). As allopurinol is commonly used to lower uric acid in gout patients, this study examined allopurinol use in individuals with MS during the five years before diagnosis, compared to a matched control group.

METHODS

This nationwide case-control study used Danish health registry data. 9,063 individuals diagnosed with MS between 2008 and 2023 were included on the day of MS diagnosis, while 90,630 controls, were matched from the general population. Controls were matched on age, gender, place of residence, and inclusion date. Allopurinol prescriptions were tracked annually for five years prior to the inclusion date. The primary outcome was the odds ratio of allopurinol use in MS patients compared to controls, analyzed using conditional logistic regression.

RESULTS

In the five years prior to the MS diagnosis or matching date for controls, allopurinol use was consistently lower in MS cases. In total, 0.30% (n = 27) of MS cases had at least one allopurinol prescription, compared to 0.62% (n = 558) of controls, corresponding to an odds ratio of 0.48 (95% CI: 0.33-0.71).

CONCLUSIONS

Individuals diagnosed with MS had significantly lower allopurinol use in the five years preceding their diagnosis, suggesting an inverse relationship between uric acid levels and MS risk. Reduced uric acid levels may be associated with early MS development, possibly due to its antioxidant properties or metabolic changes. Alternatively, these findings suggest a possible protective effect of allopurinol against MS, warranting further investigation.

Extracellular Purine Metabolism-Potential Target in Multiple Sclerosis

The purinergic signaling system comprises a complex network of extracellular purines and purine-metabolizing ectoenzymes, nucleotide and nucleoside receptors, ATP release channels, and nucleoside transporters. Because of its immunomodulatory function, this system is critically involved in the pathogenesis of multiple sclerosis (MS) and its best-characterized animal model, experimental autoimmune encephalomyelitis (EAE). MS is a chronic neuroinflammatory demyelinating and neurodegenerative disease with autoimmune etiology and great heterogeneity, mostly affecting young adults and leading to permanent disability. In MS/EAE, alterations were detected in almost all components of the purinergic signaling system in both peripheral immune cells and central nervous system (CNS) glial cells, which play an important role in the pathogenesis of the disease. A decrease in extracellular ATP levels and an increase in its downstream metabolites, particularly adenosine and inosine, were frequently observed at MS, indicating a shift in metabolism toward an anti-inflammatory environment. Accordingly, upregulation of the major ectonucleotidase tandem CD39/CD73 was detected in the blood cells and CNS of relapsing-remitting MS patients. Based on the postulated role of A2A receptors in the transition from acute to chronic neuroinflammation, the association of variants of the adenosine deaminase gene with the severity of MS, and the beneficial effects of inosine treatment in EAE, the adenosinergic system emerged as a promising target in neuroinflammation. More recently, several publications have identified ADP-dependent P2Y12 receptors and the major extracellular ADP producing enzyme nucleoside triphosphate diphosphohydrolase 2 (NTPDase2) as novel potential targets in MS.

Lipid metabolites and sarcopenia-related traits: a Mendelian randomization study

OBJECTIVE

To explore the influence of lipid metabolism on the risk of sarcopenia.

METHODS

Two-sample Mendelian randomization (MR) analysis was used to determine causality. A total of 179 lipid metabolism data points were used for exposure, and the data were obtained from a plasma lipid metabolite study of 7174 participants. The total muscle mass and total muscle strength, as well as the muscle strength and muscle mass of different sex groups, were selected as the relevant traits of sarcopenia. Data for outcomes were obtained from the UK Biobank, and sample sizes ranged from 135 468 to 450 243. Inverse-variance weighted (IVW), as the main method for evaluating the causal relationship between lipid metabolites and sarcopenia, uses the false discovery rate (FDR) for multiple comparisons and conducts heterogeneity, pleiotropy, and reverse causality tests.

RESULTS

Twenty-seven lipid metabolites, mainly phosphatidylcholine, phosphatidylethanolamine, ceramide, triacylglycerol, sphingomyelin, and sterol ester, were found to be associated with the risk of sarcopenia. Ceramide (d40:1), ceramide (d40:2), and sterol ester are risk factors for decreased muscle mass and strength. There is a positive causal relationship between various phosphatidylcholine lipids and muscle mass and strength. Sphingomyelin (d42:2) is a protective factor for total muscle strength and female muscle strength. There are inconsistent effects between different lipid metabolites, triacylglycerol, and muscle strength and muscle mass.

CONCLUSIONS

There was a causal relationship between 27 lipid metabolites and sarcopenia traits, and targeting specific lipid metabolites may benefit sarcopenia diagnosis, disease assessment, and treatment.

Discovering Potential Mechanisms of Intervertebral Disc Disease Using Systematic Mendelian Randomization of Human Circulating Immunocytomics

BACKGROUND

Although intervertebral disc degeneration (IVDD) is a critical factor in many spine-related diseases and has an extremely high prevalence in the aging population, the potential pathogenesis remains to be clarified entirely. Immune cells have been found to perform an essential function during the onset and progression of IVDD in recent years. Therefore, we explored the association between immune cell characteristics and IVDD through Mendelian randomization (MR) analysis and further delved into the mediating role of potential metabolites.

METHODS

Based on the MR analysis, the association of 731 immune cell phenotypes and 1400 metabolites on IVDD were assessed. Single nucleotide polymorphisms were closely associated the expression levels of immune cell characteristics and the concentrations of metabolites and have been used as instrumental variables for deducing them as risk factors or protective factors for IVDD. In addition, mediation analyses have been performed to identify potential metabolite mediators between immune cell characteristics and IVDD.

RESULTS

MR analysis identified 27 immune cell phenotypes and 79 metabolites significantly associated with IVDD. In addition, mediation analysis was performed by selecting the immune cell phenotype that most significantly increased the risk of IVDD - CD86 on monocytes. A total of 4 metabolite-mediated mediation relationships were revealed (3 b-hydroxy-5-cholenoic acid, X-22509, N-acetyl-L-glutamine, and N2-acetyl, N6, N6-dimethyllysine).

CONCLUSIONS

The findings of this analysis identified underlying association between immune cell phenotypes, metabolite, and IVDD that may serve as predictive and prognostic clinical biomarkers and benefit IVDD pathogenesis research.

Nucleotide polymorphism-based study utilizes human plasma liposomes to discover potential therapeutic targets for intervertebral disc disease

Background

While intervertebral disc degeneration (IVDD) is crucial in numerous spinally related illnesses and is common among the elderly, the complete understanding of its pathogenic mechanisms is still an area of ongoing study. In recent years, it has revealed that liposomes are crucial in the initiation and progression of IVDD. However, their intrinsic mediators and related mechanisms remain unclear. With the development of genomics, an increasing amount of data points to the contribution of genetics in the etiology of disease. Accordingly, this study explored the causality between liposomes and IVDD by Mendelian randomization (MR) analysis and deeply investigated the intermediary roles of undetected metabolites.

Methods

According to MR analysis, 179 liposomes and 1400 metabolites were evaluated for their causal association with IVDD. Single nucleotide polymorphisms (SNPs) are strongly associated with the concentrations of liposomes and metabolites. Consequently, they were employed as instrumental variables (IVs) to deduce if they constituted risk elements or protective elements for IVDD. Furthermore, mediation analysis was conducted to pinpoint possible metabolic mediators that link liposomes to IVDD. The inverse variance weighting (IVW) was the main analytical technique. Various confidence tests in the causality estimates were performed, including consistency, heterogeneity, pleiotropy, and sensitivity analyses. Inverse MR analysis was also utilized to estimate potential reverse causality.

Results

MR analysis identified 13 liposomes and 79 metabolites markedly relevant to IVDD. Moreover, the mediation analysis was carried out by choosing the liposome, specifically the triacylglycerol (48:2) levels, which were found to be most notably associated with an increased risk of IVDD. In all, three metabolite-associated mediators were identified (3-methylcytidine levels, inosine 5'-monophosphate (IMP) to phosphate ratio, and adenosine 5'-diphosphate (ADP) to glycine ratio).

Conclusion

The analysis's findings suggested possible causal connections between liposomes, metabolites, and IVDD, which could act as both forecast and prognosis clinical indicators, thereby aiding in the exploration of the pathogenesis behind IVDD.

Therapeutic potential of single-nucleotide polymorphism-mediated IL6R inhibitors in ankylosing spondylitis treatment

Objective

Interleukin-6 (IL-6) is a multiple-effect cell factor implicated in the etiopathogenesis of several rheumatologic disorders. The blockade of the IL-6 pathway via IL6R inhibitors effectively treats these disorders. However, the clinical significance of the IL6R blockade for ankylosing spondylitis (AS) therapy remains controversial. With advances in genomics, increasing evidence has revealed the role of heritability in the etiology of disease, and Mendelian randomization (MR) analyses are being used more broadly to infer causation. Therefore, this MR study aims to evaluate the potential therapeutic utility of IL6R-targeted approaches in AS.

Methods

The C-reactive protein (CRP) level was used as an exposure factor, and rheumatoid arthritis (RA) was used as a positive control. As-related genome-wide association study (GWAS) data were used as the primary outcome of drug-targeted MR analyses to test the relation between IL6R blockers and AS. Inverse variance weighting (IVW) is the primary analytical approach. Various sensitivity tests were performed to check the robustness and trustworthiness of the causality estimation, including consistency, heterogeneity, and pleiotropy analyses. In addition, repeated analysis was conducted using different GWAS data related to exposures and outcomes to examine the results for stability.

Results

According to the IVW results, IL6R inhibitors significantly reduced the risk of AS in ukb-b-18194 (OR: 0.995, 95% CI 0.993-0.996, P = 5.12 × 10-08) and ukb-a-88 (OR: 0.994, 95% CI 0.993-0.996, P = 6.25 × 10-15). Moreover, repeated analyses were performed using different exposure-related GWAS data, yielding similar results, ukb-b-18194 (OR: 0.995, 95% CI 0.993-0.997, P = 1.25 × 10-06) and ukb-a-88 (OR: 0.995, 95% CI 0.994-0.997, P = 7.81 × 10-09). Heterogeneity analyses and pleiotropy analyses indicated no significant heterogeneity or pleiotropy.

Conclusion

This MR analysis result further validates that the IL-6 pathway may contribute to the pathogenesis of AS and that the inhibition of IL6R reduces the risk of AS. These findings may guide future studies and provide more favorable drug treatment options for people at high risk of AS.

The causal relationship between serum metabolites and the risk of psoriasis: a Mendelian randomization and meta-analysis study

Objective

To explore the influence of serum metabolites on the risk of psoriasis.

Methods

In the initial stage, we applied Mendelian randomization to evaluate the association between 1,400 serum metabolites and the risk of psoriasis. Causal effects were primarily assessed through the Inverse-Variance Weighted method and Wald Ratio's odds ratios, and 95% confidence intervals. False Discovery Rate was used for multiple comparison corrections. Sensitivity analyses were conducted using Cochran's Q Test, MR-PRESSO. MR-Steiger Test was employed to check for reverse causality. In the validation stage, we sought other sources of psoriasis GWAS data to verify the initial results and used meta-analysis to combine the effect sizes to obtain robust causal relationships. In addition, we also conducted metabolic pathway enrichment analysis on known metabolites that have a causal relationship with the risk of psoriasis in both stages.

Results

In the initial stage, we identified 112 metabolites causally associated with psoriasis, including 32 metabolite ratios and 80 metabolites (69 known and 11 unknown). In the validation stage, 24 metabolites (16 known, 1 unknown, and 7 metabolite ratios) were confirmed to have a causal relationship with psoriasis onset. Meta-analysis results showed that the overall effect of combined metabolites was consistent with the main analysis in direction and robust in the causal relationship with psoriasis onset. Of the 16 known metabolites, most were attributed to lipid metabolism, with 5 as risk factors and 8 as protective factors for psoriasis. Peptidic metabolite Gamma-glutamylvaline levels had a negative causal relationship with psoriasis, while exogenous metabolite Catechol sulfate levels and amino acid 3-methylglutaconate levels had a positive causal relationship with the disease onset. The metabolites associated with psoriasis risk in the two stages are mainly enriched in the following metabolic pathways: Glutathione metabolism, Alpha Linolenic Acid and Linoleic Acid Metabolism, Biosynthesis of unsaturated fatty acids, Arachidonic acid metabolism, Glycerophospholipid metabolism.

Conclusion

Circulating metabolites may have a potential causal relationship with psoriasis risk, and targeting specific metabolites may benefit psoriasis diagnosis, disease assessment, and treatment.

A systematic review of Mendelian randomization studies on multiple sclerosis

Mendelian randomization (MR) is a powerful approach for assessing the causal effect of putative risk factors on an outcome, using genetic variants as instrumental variables. The methodology and application developed in the framework of MR have been dramatically improved, taking advantage of the many public genome-wide association study (GWAS) data. The availability of summary-level data allowed to perform numerous MR studies especially for complex diseases, pinpointing modifiable exposures causally related to increased or decreased disease risk. Multiple sclerosis (MS) is a complex multifactorial disease whose aetiology involves both genetic and non-genetic risk factors and their interplay. Previous observational studies have revealed associations between candidate modifiable exposures and MS risk; although being prone to confounding, and reverse causation, these studies were unable to draw causal conclusions. MR analysis addresses the limitations of observational studies and allows to establish reliable and accurate causal conclusions. Here, we systematically reviewed the studies evaluating the causal effect, through MR, of genetic and non-genetic exposures on MS risk. Among 107 papers found, only 42 were eligible for final evaluation and qualitative synthesis. We found that, above all, low vitamin D levels and high adult body mass index (BMI) appear to be uncontested risk factors for increased MS risk.

A metabolome-wide Mendelian randomization study prioritizes potential causal circulating metabolites for multiple sclerosis

To prioritize circulating metabolites that likely play causal roles in the pathogenesis of multiple sclerosis (MS). Two-sample Mendelian randomization analysis was performed to estimate the causal effects of 571 circulating metabolites on the risk of MS. Genetic instruments for circulating metabolites were obtained from three previous genome-wide association studies (GWAS) of the blood metabolome (N = 7824; 24,925; and 115,078; respectively), while genetic associations with MS were from a large GWAS by the International Multiple Sclerosis Genetics Consortium (14,802 cases and 26,703 control). The primary analysis was performed with the multiplicative random-effect inverse variance-weighted method, while multiple sensitivity analyses were conducted with the weighted median, weighted mode, MR-Egger, and MR-PRESSO. A total of 29 metabolites had suggestive evidence of causal associations with MS. Genetically instrumented levels of serine (OR = 1.56, 95% CI = 1.25-1.95), lysine (OR = 1.18, 95% CI = 1.01-1.38), acetone (OR = 2.45, 95% CI = 1.02-5.90), and acetoacetate (OR = 2.47, 95% CI = 1.14-5.34) were associated with a higher MS risk. Total cholesterol and phospholipids in large very-low-density lipoprotein were associated with a lower MS risk (OR = 0.83, 95% CI = 0.69-1.00; OR = 0.80, 95% CI = 0.68-0.95), but risk-increasing associations (OR = 1.20, 95% CI = 1.04-1.40; OR = 1.13, 95% CI = 1.00-1.28) were observed for the same two lipids in very large high-density lipoprotein. Our metabolome-wide Mendelian randomization study prioritized a list of circulating metabolites, such as serine, lysine, acetone, acetoacetate, and lipids, that likely have causal associations with MS.

Uric acid and neurological disease: a narrative review

Hyperuricemia often accompanies hypertension, diabetes, dyslipidemia, metabolic syndrome, and chronic renal disease; it is also closely related to cardiovascular disease. Moreover, several epidemiological studies have linked hyperuricemia and ischemic stroke. However, uric acid may also have neuroprotective effects because of its antioxidant properties. An association between low uric acid levels and neurodegenerative diseases has been suggested, which may be attributed to diminished neuroprotective effects as a result of reduced uric acid. This review will focus on the relationship between uric acid and various neurological diseases including stroke, neuroimmune diseases, and neurodegenerative diseases. When considering both the risk and pathogenesis of neurological diseases, it is important to consider the conflicting dual nature of uric acid as both a vascular risk factor and a neuroprotective factor. This dual nature of uric acid is important because it may help to elucidate the biological role of uric acid in various neurological diseases and provide new insights into the etiology and treatment of these diseases.

Association Between Sleep Traits and Rheumatoid Arthritis: A Mendelian Randomization Study

Currently, the causal association between sleep disorders and rheumatoid arthritis (RA) has been poorly understood. In this two-sample Mendelian randomization (TSMR) study, we tried to explore whether sleep disorders are causally associated with RA. Seven sleep-related traits were chosen from the published Genome-Wide Association Study (GWAS): short sleep duration, frequent insomnia, any insomnia, sleep duration, getting up, morningness (early-to-bed/up habit), and snoring, 27, 53, 57, 57, 70, 274, and 42 individual single-nucleotide polymorphisms (SNPs) (P < 5 × 10-8) were obtained as instrumental variables (IVs) for these sleep-related traits. Outcome variables were obtained from a public GWAS study that included 14,361 cases and 43,923 European Ancestry controls. The causal relationship between sleep disturbances and RA risk were evaluated by a two-sample Mendelian randomization (MR) analysis using inverse variance weighted (IVW), MR-Egger regression, weighted median, and weight mode methods. MR-Egger Regression and Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) were used to test for horizontal pleomorphism and outliers. There was no evidence of a link between RA and frequent insomnia (IVW, odds ratio (OR): 0.99; 95% interval (CI): 0.84-1.16; P = 0.858), any insomnia (IVW, OR: 1.09; 95% CI: 0.85-1.42; P = 0.489), sleep duration (IVW, OR: 0.65, 95% CI: 0.38-1.10, P = 0.269), getting up (IVW, OR: 0.56, 95% CI: 0.13-2.46, P = 0.442), morningness (IVW, OR: 2.59; 95% CI: 0.73-9.16; P = 0.142), or snoring (IVW, OR: 0.95; 95% CI: 0.68-1.33; P = 0.757). Short sleep duration (6h) had a causal effect on RA, as supported by IVW and weighted median (OR: 1.47, 95% CI: 1.12-1.94, P = 0.006; OR: 1.43, 95%CI:1.01-2.05, P = 0.047). Sensitivity analysis showed that the results were stable. Our findings imply that short sleep duration is causally linked to an increased risk of RA. Therefore, sleep length should be considered in disease models, and physicians should advise people to avoid short sleep duration practices to lower the risk of RA.

Clinical and Radiological Characteristics of Children and Adults With First-Attack Myelin Oligodendrocyte Glycoprotein Antibody Disease and Analysis of Risk Factors for Predicting the Severity at Disease Onset in Central China

Objective

To analyze and compare different clinical, laboratory, and magnetic resonance imaging characteristics between pediatric and adult patients with first-attack myelin oligodendrocyte glycoprotein antibody disease (MOGAD) and to explore predictive factors for severity at disease onset.

Methods

Patients diagnosed with MOGAD at the First Affiliated Hospital of Zhengzhou University from January 2013 to August 2021 were enrolled in this retrospective study. Age at disease onset, sex, comorbidities, laboratory tests, magnetic resonance imaging (MRI) characteristics, and Expanded Disability Status Scale (EDSS) scores were collected and analyzed. The association between risk factors and initial EDSS scores at disease onset was analyzed using logistic regression models and Spearman correlation analyses. A receiver-operating characteristic (ROC) curve analysis was used to evaluate the predictive ability of the uric acid and homocysteine (Hcy) levels for the severity of neurological dysfunction at the onset of MOGAD.

Results

Sixty-seven patients (female, n=34; male, n=33) with first-attack MOGAD were included in this study. The mean age at onset was 26.43 ± 18.22 years (range: 3–79 years). Among patients &lt;18 years of age, the most common presenting symptoms were loss of vision (36.0%), and nausea and vomiting (24.0%), and the most common disease spectrum was acute disseminated encephalomyelitis (ADEM) (40.0%). Among patients aged ≥18 years, the most common presenting symptoms were loss of vision (35.7%), paresthesia (33.3%), and paralysis (26.2%), and the most common disease spectrum was optic neuritis (35.7%). The most common lesions were cortical gray matter/paracortical white matter lesions in both pediatric and adult patients. Uric acid [odds ratio (OR)=1.014; 95% confidence interval (CI)=1.006–1.022; P=0.000] and serum Hcy (OR=1.125; 95% CI=1.017–1.246; P=0.023) levels were significantly associated with the severity of neurological dysfunction at disease onset. Uric acid levels (r=0.2583; P=0.035) and Hcy levels (r=0.3971; P=0.0009) were positively correlated with initial EDSS scores. The areas under the ROC curve were 0.7775 (95% CI= 0.6617‒0.8933; P&lt;0.001) and 0.6767 (95% CI=0.5433‒0.8102, P=0.014) for uric acid and Hcy levels, respectively.

Conclusion

The clinical phenotype of MOGAD varies in patients of different ages. The most common disease spectrum was ADEM in patients aged&lt;18 years, while optic neuritis was commonly found in patients aged ≥18 years. The uric acid and Hcy levels are risk factors for the severity of neurological dysfunction at disease onset in patients with first-attack MOGAD.