Investigating the relationships between unfavourable habitual sleep and metabolomic traits: evidence from multi-cohort multivariable regression and Mendelian randomization analyses

Abstract Background Sleep traits are associated with cardiometabolic disease risk, with evidence from Mendelian randomization (MR) suggesting that insomnia symptoms and shorter sleep duration increase coronary artery disease risk. We combined adjusted multivariable regression (AMV) and MR analyses of phenotypes of unfavourable sleep on 113 metabolomic traits to investigate possible biochemical mechanisms linking sleep to cardiovascular disease. Methods We used AMV (N = 17,368) combined with two-sample MR (N = 38,618) to examine effects of self-reported insomnia symptoms, total habitual sleep duration, and chronotype on 113 metabolomic traits. The AMV analyses were conducted on data from 10 cohorts of mostly Europeans, adjusted for age, sex, and body mass index. For the MR analyses, we used summary results from published European-ancestry genome-wide association studies of self-reported sleep traits and of nuclear magnetic resonance (NMR) serum metabolites. We used the inverse-variance weighted (IVW) method and complemented this with sensitivity analyses to assess MR assumptions. Results We found consistent evidence from AMV and MR analyses for associations of usual vs. sometimes/rare/never insomnia symptoms with lower citrate (− 0.08 standard deviation (SD)[95% confidence interval (CI) − 0.12, − 0.03] in AMV and − 0.03SD [− 0.07, − 0.003] in MR), higher glycoprotein acetyls (0.08SD [95% CI 0.03, 0.12] in AMV and 0.06SD [0.03, 0.10) in MR]), lower total very large HDL particles (− 0.04SD [− 0.08, 0.00] in AMV and − 0.05SD [− 0.09, − 0.02] in MR), and lower phospholipids in very large HDL particles (− 0.04SD [− 0.08, 0.002] in AMV and − 0.05SD [− 0.08, − 0.02] in MR). Longer total sleep duration associated with higher creatinine concentrations using both methods (0.02SD per 1 h [0.01, 0.03] in AMV and 0.15SD [0.02, 0.29] in MR) and with isoleucine in MR analyses (0.22SD [0.08, 0.35]). No consistent evidence was observed for effects of chronotype on metabolomic measures. Conclusions Whilst our results suggested that unfavourable sleep traits may not cause widespread metabolic disruption, some notable effects were observed. The evidence for possible effects of insomnia symptoms on glycoprotein acetyls and citrate and longer total sleep duration on creatinine and isoleucine might explain some of the effects, found in MR analyses of these sleep traits on coronary heart disease, which warrant further investigation.

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Investigating the relationships between unfavorable sleep and metabolomic traits: evidence from multi-cohort multivariable regression and Mendelian randomization analyses

10.1101/2020.08.27.20173518 ◽

2020 ◽

Author(s):

Maxime M Bos ◽

Neil J Goulding ◽

Matthew A Lee ◽

Amy Hofman ◽

Mariska Bot ◽

...

Keyword(s):

Sleep Duration ◽

Mendelian Randomization ◽

Disease Risk ◽

Association Studies ◽

Sensitivity Analyses ◽

European Ancestry ◽

Genome Wide Association Studies ◽

Multivariable Regression ◽

Artery Disease ◽

Insomnia Symptoms

Background: Sleep traits are associated with cardiometabolic disease risk, with evidence from Mendelian randomization (MR) suggesting that insomnia symptoms and shorter sleep duration increase coronary artery disease risk. We combined adjusted multivariable regression (AMV) and MR analyses of phenotypes of unfavourable sleep on 113 metabolomic traits to investigate possible biochemical mechanisms linking sleep to cardiovascular disease. Methods: We used AMV (N=17,370) combined with two-sample MR (N=38,618) to examine effects of self-reported insomnia symptoms, total habitual sleep duration, and chronotype on 113 metabolomic traits. The AMV analyses were conducted on data from 10 cohorts of mostly Europeans, adjusted for age, sex and body mass index. For the MR analyses, we used summary results from published European-ancestry genome-wide association studies of self-reported sleep traits and of nuclear magnetic resonance (NMR) serum metabolites. We used the inverse-variance weighted (IVW) method and complemented this with sensitivity analyses to assess MR assumptions. Results: We found consistent evidence from AMV and MR analyses for associations of usual vs. sometimes/rare/never insomnia symptoms with lower citrate (-0.08 standard deviation (SD)[95% confidence interval (CI): -0.12, -0.03] in AMV and -0.03SD [-0.07, -0.003] in MR), higher glycoprotein acetyls (0.08SD [95%CI: 0.03, 0.12] in AMV and 0.06SD [0.03, 0.10) in MR]), lower total very large HDL particles (-0.04SD [-0.08, 0.00] in AMV and -0.05SD [-0.09, -0.02] in MR) and lower phospholipids in very large HDL particles (-0.04SD [-0.08, 0.002] in AMV and -0.05SD [-0.08, -0.02] in MR). Longer total sleep duration associated with higher creatinine concentrations using both methods (0.02SD per 1-hour [0.01, 0.03] in AMV and 0.15SD [0.02, 0.29] in MR) and with isoleucine in MR analyses (0.22SD [0.08, 0.35]). No consistent evidence was observed for effects of chronotype on metabolomic measures. Conclusions: Whilst our results suggested that unfavourable sleep traits may not cause widespread metabolic disruption, some notable effects were observed. The evidence for possible effects of insomnia symptoms on glycoprotein acetyls and citrate and longer total sleep duration on creatinine and isoleucine might explain some of the effects, found in MR analyses of these sleep traits on coronary heart disease, which warrant further investigation.

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454Relationships between sleep traits and metabolic profiles: evidence from multivariable regression and Mendelian randomization analyses

International Journal of Epidemiology ◽

10.1093/ije/dyab168.236 ◽

2021 ◽

Vol 50 (Supplement_1) ◽

Author(s):

Neil Goulding ◽

Maxime Bos ◽

Diana van Heemst ◽

Raymond Noordam ◽

Deborah Lawlor

Keyword(s):

Sleep Duration ◽

Mendelian Randomization ◽

Causal Effect ◽

Association Studies ◽

Inflammatory Marker ◽

Genome Wide Association Studies ◽

Inverse Variance ◽

Multivariable Regression ◽

Multivariable Analyses ◽

Insomnia Symptoms

Abstract Background Sleep traits are associated with cardiometabolic disease. The aim of this study was to explore the causal effect of sleep traits (duration and insomnia) on multiple metabolic traits. Methods We used age, sex and BMI adjusted multivariable regression (N = 17,370) and two-sample summary statistic Mendelian randomization (MR) to examine effects of sleep duration and insomnia symptoms on ∼150 NMR metabolites. Multivariable analyses were conducted on data from nine European cohorts and meta-analysed. MR analyses utilised summary statistics from published genome-wide association studies (GWAS) of self-reported sleep traits (sample 1; N = 446,118 to 1,331,010) and from GWAS on NMR serum metabolites (sample 2; N = 38,618). We used inverse-variance weighted (IVW) for the main MR analyses and weighed median (WM) and MR-Egger to explore bias due to pleiotropy. Results MR IVW and multivariable analyses both suggest a positive effect of insomnia symptoms on glycoprotein acetyls (MR: 0.06 s.d. increase in mean concentration comparing any symptoms to none; p = 5.9e-4) and between total sleep duration and creatinine (MR: 0.16 s.d. increase per additional hour; p = 0.03). WM and MR-Egger analyses show consistent results. There was evidence for thirteen and eight effects of insomnia and duration in multivariable only and three and one, respectively, in MR only. Conclusions Insomnia symptoms lead to higher levels of an inflammatory marker (glycoprotein acetyls) and longer sleep duration leads to higher creatinine levels. Key messages We found no evidence of widespread metabolic disruption by sleep traits.

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Growth Differentiation Factor 15 Is Associated With Alzheimer’s Disease Risk

Frontiers in Genetics ◽

10.3389/fgene.2021.700371 ◽

2021 ◽

Vol 12 ◽

Author(s):

Peng-Fei Wu ◽

Xing-Hao Zhang ◽

Ping Zhou ◽

Rui Yin ◽

Xiao-Ting Zhou ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Mendelian Randomization ◽

Association Studies ◽

Sensitivity Analyses ◽

European Ancestry ◽

Reverse Direction ◽

Genome Wide Association Studies ◽

Growth Differentiation Factor 15 ◽

Differentiation Factor

BackgroundPrevious observational studies have suggested that associations exist between growth differentiation factor 15 (GDF-15) and neurodegenerative diseases. We aimed to investigate the causal relationships between GDF-15 and Alzheimer’s disease (AD), Parkinson’s disease (PD), and amyotrophic lateral sclerosis (ALS).MethodsUsing summary-level datasets from genome-wide association studies of European ancestry, we performed a two-sample Mendelian randomization (MR) study. Genetic variants significantly associated (p < 5 × 10–8) with GDF-15 were selected as instrumental variables (n = 5). An inverse-variance weighted method was implemented as the primary MR approach, while weighted median, MR–Egger, leave-one-out analysis, and Cochran’s Q-test were conducted as sensitivity analyses. All analyses were performed using R 3.6.1 with relevant packages.ResultsMR provided evidence for the association of elevated GDF-15 levels with a higher risk of AD (odds ratio = 1.14; 95% confidence interval, 1.04–1.24; p = 0.004). In the reverse direction, Mendelian randomization suggested no causal effect of genetically proxied risk of AD on circulating GDF-15 (p = 0.450). The causal effects of GDF-15 on PD (p = 0.597) or ALS (p = 0.120) were not identified, and the MR results likewise did not support the association of genetic liability to PD or ALS with genetically predicted levels of GDF-15. No evident heterogeneity or horizontal pleiotropy was revealed by multiple sensitivity analyses.ConclusionWe highlighted the role of GDF-15 in AD as altogether a promising diagnostic marker and a therapeutic target.

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Causal association of adipokines with osteoarthritis: a Mendelian randomization study

Rheumatology ◽

10.1093/rheumatology/keaa719 ◽

2020 ◽

Author(s):

Jiayao Fan ◽

Jiahao Zhu ◽

Lingling Sun ◽

Yasong Li ◽

Tianle Wang ◽

...

Keyword(s):

Mendelian Randomization ◽

Association Studies ◽

Genome Wide Association ◽

Sensitivity Analyses ◽

European Ancestry ◽

Genome Wide Association Studies ◽

Knee Oa ◽

Genome Wide ◽

A Genome ◽

Weighted Median

Abstract Objective This two-sample Mendelian randomization study aimed to delve into the effects of genetically predicted adipokine levels on OA. Methods Summary statistic data for OA originated from a meta-analysis of a genome-wide association study with an overall 50 508 subjects of European ancestry. Publicly available summary data from four genome-wide association studies were exploited to respectively identify instrumental variables of adiponectin, leptin, resistin, chemerin and retinol-blinding protein 4. Subsequently, Mendelian randomization analyses were conducted with inverse variance weighted (IVW), weighted median and Mendelian randomization-Egger regression. Furthermore, sensitivity analyses were then conducted to assess the robustness of our results. Results The positive causality between genetically predicted leptin level and risk of total OA was indicated by IVW [odds ratio (OR): 2.40, 95% CI: 1.13–5.09] and weighted median (OR: 2.94, 95% CI: 1.23–6.99). In subgroup analyses, evidence of potential harmful effects of higher level of adiponectin (OR: 1.28, 95% CI: 1.01–1.61 using IVW), leptin (OR: 3.44, 95% CI: 1.18–10.03 using IVW) and resistin (OR: 1.18, 95% CI: 1.03–1.36 using IVW) on risk of knee OA were acquired. However, the mentioned effects on risk of hip OA were not statistically significant. Slight evidence was identified supporting causality of chemerin and retinol-blinding protein 4 for OA. The findings of this study were verified by the results from sensitivity analysis. Conclusions An association between genetically predicted leptin level and risk of total OA was identified. Furthermore, association of genetically predicted levels of adiponectin, leptin and resistin with risk of knee OA were reported.

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Genetically Determined Inflammatory Biomarkers and the Risk of Heart Failure: A Mendelian Randomization Study

Frontiers in Cardiovascular Medicine ◽

10.3389/fcvm.2021.734400 ◽

2021 ◽

Vol 8 ◽

Author(s):

Xintao Li ◽

Shi Peng ◽

Bo Guan ◽

Songwen Chen ◽

Genqing Zhou ◽

...

Keyword(s):

Heart Failure ◽

Signaling Pathway ◽

Mendelian Randomization ◽

Association Studies ◽

Interleukin 1 ◽

Inflammatory Biomarkers ◽

Sensitivity Analyses ◽

European Ancestry ◽

Genome Wide Association Studies ◽

Genetically Determined

Background: Positive associations between inflammatory biomarkers and the risk of heart failure (HF) have been reported in conventional observational studies. However, the causal effects of inflammatory biomarkers on HF have not been fully elucidated. We conducted a Mendelian randomization (MR) study to examine the possible etiological roles of inflammatory biomarkers in HF.Methods: Summary statistical data for the associations between single nucleotide polymorphisms (SNPs) and C-reactive protein (CRP), fibrinogen, and components of the interleukin-1 (IL-1)-interleukin-6 (IL-6) inflammatory signaling pathway, namely, interleukin-1β (IL-1β), IL-1 receptor antagonist (IL-1ra), IL-6, and soluble IL-6 receptor (sIL-6r), were obtained from genome-wide association studies (GWASs) for individuals of European descent. The GWAS dataset of 977,323 participants of European ancestry, which included 47,309 HF cases and 930,014 controls, was collected to identify genetic variants underlying HF. A two-sample Mendelian randomization framework was implemented to examine the causality of the association between these inflammatory biomarkers and HF.Results: Our MR analyses found that genetically determined CRP and fibrinogen were not causally associated with HF risk (odds ratio [OR] = 0.93, 95% confidence interval [CI] = 0.84–1.02, p = 0.15; OR = 0.94, 95% CI = 0.55–1.58, p = 0.80, respectively). These findings remained consistent using different Mendelian randomization methods and in sensitivity analyses. For the IL-1-IL-6 pathway, causal estimates for IL-6 (OR = 0.86, 95% CI 0.81–0.91, p < 0.001), but not for IL-1β, IL-1ra, or sIL-6r, were significant. However, the association between genetically determined IL-6 and HF risk became non-significant after excluding SNPs with potential pleiotropy (OR = 0.89, 95% CI = 0.77–1.03, p = 0.12).Conclusion: Our study did not identify convincing evidence to support that CRP and fibrinogen, together with their upstream IL-1-IL-6 signaling pathway, were causally associated with HF risk.

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Genetic Evidence That Carbohydrate-Stimulated Insulin Secretion Leads to Obesity

Clinical Chemistry ◽

10.1373/clinchem.2017.280727 ◽

2018 ◽

Vol 64 (1) ◽

pp. 192-200 ◽

Cited By ~ 31

Author(s):

Christina M Astley ◽

Jennifer N Todd ◽

Rany M Salem ◽

Sailaja Vedantam ◽

Cara B Ebbeling ◽

...

Keyword(s):

Body Weight ◽

Insulin Secretion ◽

Causal Relationship ◽

Mendelian Randomization ◽

Association Studies ◽

Sensitivity Analyses ◽

European Ancestry ◽

Oral Glucose ◽

Genome Wide Association Studies ◽

Genetically Determined

Abstract BACKGROUND A fundamental precept of the carbohydrate–insulin model of obesity is that insulin secretion drives weight gain. However, fasting hyperinsulinemia can also be driven by obesity-induced insulin resistance. We used genetic variation to isolate and estimate the potentially causal effect of insulin secretion on body weight. METHODS Genetic instruments of variation of insulin secretion [assessed as insulin concentration 30 min after oral glucose (insulin-30)] were used to estimate the causal relationship between increased insulin secretion and body mass index (BMI), using bidirectional Mendelian randomization analysis of genome-wide association studies. Data sources included summary results from the largest published metaanalyses of predominantly European ancestry for insulin secretion (n = 26037) and BMI (n = 322154), as well as individual-level data from the UK Biobank (n = 138541). Data from the Cardiology and Metabolic Patient Cohort study at Massachusetts General Hospital (n = 1675) were used to validate genetic associations with insulin secretion and to test the observational association of insulin secretion and BMI. RESULTS Higher genetically determined insulin-30 was strongly associated with higher BMI (β = 0.098, P = 2.2 × 10−21), consistent with a causal role in obesity. Similar positive associations were noted in sensitivity analyses using other genetic variants as instrumental variables. By contrast, higher genetically determined BMI was not associated with insulin-30. CONCLUSIONS Mendelian randomization analyses provide evidence for a causal relationship of glucose-stimulated insulin secretion on body weight, consistent with the carbohydrate–insulin model of obesity.

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The contribution of tissue-grouped BMI-associated gene sets to cardiometabolic-disease risk: a Mendelian randomization study

International Journal of Epidemiology ◽

10.1093/ije/dyaa070 ◽

2020 ◽

Vol 49 (4) ◽

pp. 1246-1256

Author(s):

Inge Verkouter ◽

Renée de Mutsert ◽

Roelof A J Smit ◽

Stella Trompet ◽

Frits R Rosendaal ◽

...

Keyword(s):

Genetic Variants ◽

Mendelian Randomization ◽

Disease Risk ◽

Expression Profiles ◽

Association Studies ◽

Tissue Expression ◽

Cardiometabolic Disease ◽

Genome Wide Association Studies ◽

Gene Sets ◽

Artery Disease

Abstract Background Body mass index (BMI)-associated loci are used to explore the effects of obesity using Mendelian randomization (MR), but the contribution of individual tissues to risks remains unknown. We aimed to identify tissue-grouped pathways of BMI-associated loci and relate these to cardiometabolic disease using MR analyses. Methods Using Genotype-Tissue Expression (GTEx) data, we performed overrepresentation tests to identify tissue-grouped gene sets based on mRNA-expression profiles from 634 previously published BMI-associated loci. We conducted two-sample MR with inverse-variance-weighted methods, to examine associations between tissue-grouped BMI-associated genetic instruments and type 2 diabetes mellitus (T2DM) and coronary artery disease (CAD), with use of summary-level data from published genome-wide association studies (T2DM: 74 124 cases, 824 006 controls; CAD: 60 801 cases, 123 504 controls). Additionally, we performed MR analyses on T2DM and CAD using randomly sampled sets of 100 or 200 BMI-associated genetic variants. Results We identified 17 partly overlapping tissue-grouped gene sets, of which 12 were brain areas, where BMI-associated genes were differentially expressed. In tissue-grouped MR analyses, all gene sets were similarly associated with increased risks of T2DM and CAD. MR analyses with randomly sampled genetic variants on T2DM and CAD resulted in a distribution of effect estimates similar to tissue-grouped gene sets. Conclusions Overrepresentation tests revealed differential expression of BMI-associated genes in 17 different tissues. However, with our biology-based approach using tissue-grouped MR analyses, we did not identify different risks of T2DM or CAD for the BMI-associated gene sets, which was reflected by similar effect estimates obtained by randomly sampled gene sets.

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Mendelian randomization highlights insomnia as a risk factor for pain diagnoses

SLEEP ◽

10.1093/sleep/zsab025 ◽

2021 ◽

Author(s):

Martin Broberg ◽

Juha Karjalainen ◽

Hanna M Ollila ◽

Keyword(s):

Mendelian Randomization ◽

Clinical Investigation ◽

Association Studies ◽

Sensitivity Analyses ◽

Genome Wide Association Studies ◽

Study Objective ◽

Increased Risk ◽

Icd 10 ◽

Chronic Pain Conditions ◽

Insomnia Symptoms

Abstract Study objective Insomnia has been linked to acute and chronic pain conditions; however, it is unclear whether such relationships are causal. Recently, a large number of genetic variants have been discovered for both insomnia and pain through genome-wide association studies (GWAS) providing a unique opportunity to examine evidence for causal relationships through the use of the Mendelian randomization paradigm. Methods To elucidate the causality between insomnia and pain we performed bidirectional Mendelian randomization analysis in FinnGen, where clinically diagnosed ICD-10 categories of pain had been evaluated. In addition, we used measures of self-reported insomnia symptoms. We used endpoints for pain in the FinnGen Release 5 (R5) (N=218,379), and a non-overlapping sample for insomnia (UK Biobank (UKBB) and 23andMe, N=1,331,010 or UKBB alone N=453,379). We assessed robustness of results through conventional MR sensitivity analyses. Results Genetic liability to insomnia symptoms increased the odds of reporting pain (odds ratio (OR) [95% confidence interval (CI)] = 1.47 [1.38–1.58], P = 4.12x10 -28). Manifested pain had a small effect on increased risk for insomnia (OR [95% CI] = 1.04 [1.01–1.07], P < 0.05). Results were consistent in sensitivity analyses. Conclusions Our findings support a bidirectional causal relationship between insomnia and pain. These data support further clinical investigation into the utility of insomnia treatment as a strategy for pain management and vice versa.

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Depression and Osteoporosis: A Mendelian Randomization Study

Calcified Tissue International ◽

10.1007/s00223-021-00886-5 ◽

2021 ◽

Author(s):

Bin He ◽

Qiong Lyu ◽

Lifeng Yin ◽

Muzi Zhang ◽

Zhengxue Quan ◽

...

Keyword(s):

Observational Studies ◽

Mendelian Randomization ◽

Causal Effect ◽

Association Studies ◽

Meta Analysis ◽

Sensitivity Analyses ◽

European Ancestry ◽

Genome Wide Association Studies ◽

Reverse Causality ◽

Mineral Density

AbstractObservational studies suggest a link between depression and osteoporosis, but these may be subject to confounding and reverse causality. In this two-sample Mendelian randomization analysis, we included the large meta-analysis of genome-wide association studies for depression among 807,553 individuals (246,363 cases and 561,190 controls) of European descent, the large meta-analysis to identify genetic variants associated with femoral neck bone mineral density (FN-BMD), forearm BMD (FA-BMD) and lumbar spine BMD (LS-BMD) among 53,236 individuals of European ancestry, and the GWAS summary data of heel BMD (HE-BMD) and fracture among 426,824 individuals of European ancestry. The results revealed that genetic predisposition towards depression showed no causal effect on FA-BMD (beta-estimate: 0.091, 95% confidence interval [CI] − 0.088 to 0.269, SE:0.091, P value = 0.320), FN-BMD (beta-estimate: 0.066, 95% CI − 0.016 to 0.148, SE:0.042, P value = 0.113), LS-BMD (beta-estimate: 0.074, 95% CI − 0.029 to 0.177, SE:0.052, P value = 0.159), HE-BMD (beta-estimate: 0.009, 95% CI − 0.043 to 0.061, SE:0.027, P value = 0.727), or fracture (beta-estimate: 0.008, 95% CI − 0.071 to 0.087, SE:0.041, P value = 0.844). These results were also confirmed by multiple sensitivity analyses. Contrary to the findings of observational studies, our results do not reveal a causal role of depression in osteoporosis or fracture.

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Adipokines and risk of rheumatoid arthritis: a Mendelian randomization study

10.21203/rs.3.rs-36474/v1 ◽

2020 ◽

Author(s):

Jiahao Zhu ◽

Haiyan Zheng ◽

Yasong Li ◽

Tianle Wang ◽

Yaohong Zhong ◽

...

Keyword(s):

Rheumatoid Arthritis ◽

Large Scale ◽

Mendelian Randomization ◽

Association Studies ◽

Statistical Significance ◽

Sensitivity Analyses ◽

European Ancestry ◽

Genome Wide Association Studies ◽

Primary Analysis ◽

Genome Wide

Abstract Background: Circulating adipokines levels have been reported to be associated with the risk of rheumatoid arthritis (RA). However, it is still unclear whether these associations are causal or biased by reverse causation or residual confounding. This study aimed to assess potential causal roles of five adipokines (namely, adiponectin, leptin, resistin, chemerin, and retinol-blinding protein 4 [RBP4]) in the occurrence of RA.Methods: We conducted a two-sample Mendelian randomization analysis to investigate these associations. We used summary-level data from genome-wide association studies (GWASs) for adipokines in individuals of European ancestry as the exposure, and a separate large-scale meta-analysis of a GWAS which included 14,361 RA cases and 43,923 controls of European ancestry as the outcome. Genetic variants were selected as instrumental variables if robustly genome-wide significant in their associations with adipokines. The causal effects were estimated using the inverse-variance weighted method in the primary analysis. Sensitivity analyses were performed to warrant that bias due to genetic pleiotropy was unlikely.Results: The circulating resistin was found to be the only adipokinetic factor having statistical significance, with higher levels causally associated with the risk of RA (odds ratio: 1.28; 95% confidence interval: [1.07, 1.53] per unit increase in the natural log-transformed resistin). In contrast, associations of adiponectin, leptin, chemerin, and RBP4 with risk of RA were not statistically significant. The MR assumptions did not seem to be violated. Sensitivity analyses yielded consistent findings.Conclusions: Genetically predicted circulating resistin levels were positively associated with RA risk. Our analysis suggested that resistin may play a notable causal role in RA pathogenesis. It would be beneficial for the development of clinical as well as public health strategies that target appropriate levels of resistin for future RA intervention.

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