Genetically predicted iron status and life expectancy.

BACKGROUND & AIMS: Systemic iron status affects multiple health outcomes, however its net effect on life expectancy is not known. We conducted a two-sample Mendelian randomization (MR) study to investigate the association of genetically proxied iron status with life expectancy. METHODS: Using genetic data from 48,972 individuals, we identified three genetic variants as instrumental variables for systemic iron status. We obtained genetic associations of these variants with parental lifespan (n = 1,012,240) and individual survival to the 90th vs. 60th percentile age (11,262 cases and 25,483 controls). We used the inverse-variance weighted method to estimate the effect of a 1-standard deviation (SD) increase in genetically predicted serum iron on each of the life expectancy outcomes. RESULTS: We found a detrimental effect of genetically proxied higher iron status on life expectancy. A 1-SD increase in genetically predicted serum iron corresponded to 0.70 (95% confidence interval [CI] -1.17, -0.24; P = 3.00 × 10-3) fewer years of parental lifespan and had odds ratio 0.81 (95% CI 0.70, 0.93; P = 4.44 × 10-3) for survival to the 90th vs. 60th percentile age. We did not find evidence to suggest that these results were biased by pleiotropic effects of the genetic variants. CONCLUSIONS: Higher systemic iron status may reduce life expectancy. The clinical implications of this finding warrant further investigation, particularly in the context of iron supplementation in individuals with normal iron status

Habitual sleep disturbances and migraine: a Mendelian randomization study

Objective: Sleep disturbances are associated with increased risk of migraine, however the extent of shared underlying biology and the direction of causal relationships between these traits is unclear. Delineating causality between sleep patterns and migraine may offer new pathophysiologic insights and inform subsequent intervention studies. Here, we used genetic approaches to test for shared genetic influences between sleep patterns and migraine, and to test whether habitual sleep patterns may be causal risk factors for migraine and vice versa.Methods: To quantify genetic overlap, we performed genome-wide genetic correlation analyses using genome-wide association studies of nine sleep traits in the UK Biobank (n ≥ 237,627), and migraine from the International Headache Genetics Consortium (59,674 cases and 316,078 controls). We then tested for potential causal effects between sleep traits and migraine using bidirectional, two-sample Mendelian randomization.Results: Seven sleep traits demonstrated genetic overlap with migraine, including insomnia symptoms (rg = 0.29, P Interpretation: These data support a shared genetic basis between several sleep traits and migraine, and support potential causal effects of difficulty awakening and insomnia symptoms on migraine risk. Treatment of sleep disturbances may therefore be a promising clinical intervention in the management of migraine.</p

A genome-wide cross-phenotype meta-analysis of the association of blood pressure with migraine

Blood pressure (BP) was inconsistently associated with migraine and the mechanisms of BP-lowering medications in migraine prophylaxis are unknown. Leveraging large-scale summary statistics for migraine (Ncases/Ncontrols = 59,674/316,078) and BP (N = 757,601), we find positive genetic correlations of migraine with diastolic BP (DBP, rg = 0.11, P = 3.56 × 10-06) and systolic BP (SBP, rg = 0.06, P = 0.01), but not pulse pressure (PP, rg = -0.01, P = 0.75). Cross-trait meta-analysis reveals 14 shared loci (P ≤ 5 × 10-08), nine of which replicate (P < 0.05) in the UK Biobank. Five shared loci (ITGB5, SMG6, ADRA2B, ANKDD1B, and KIAA0040) are reinforced in gene-level analysis and highlight potential mechanisms involving vascular development, endothelial function and calcium homeostasis. Mendelian randomization reveals stronger instrumental estimates of DBP (OR [95% CI] = 1.20 [1.15-1.25]/10 mmHg; P = 5.57 × 10-25) on migraine than SBP (1.05 [1.03-1.07]/10 mmHg; P = 2.60 × 10-07) and a corresponding opposite effect for PP (0.92 [0.88-0.95]/10 mmHg; P = 3.65 × 10-07). These findings support a critical role of DBP in migraine susceptibility and shared biology underlying BP and migraine

A genome-wide cross-phenotype meta-analysis of the association of blood pressure with migraine

Blood pressure (BP) was inconsistently associated with migraine and the mechanisms of BP-lowering medications in migraine prophylaxis are unknown. Leveraging large-scale summary statistics for migraine (N-cases/N-controls = 59,674/316,078) and BP (N = 757,601), we find positive genetic correlations of migraine with diastolic BP (DBP, r(g) = 0.11, P = 3.56 x 10(-06)) and systolic BP (SBP, r(g) = 0.06, P = 0.01), but not pulse pressure (PP, r(g) = -0.01, P = 0.75). Cross-trait meta-analysis reveals 14 shared loci (P <= 5 x 10(-08)), nine of which replicate (P < 0.05) in the UK Biobank. Five shared loci (ITGB5, SMG6, ADRA2B, ANKDD1B, and KIAA0040) are reinforced in gene-level analysis and highlight potential mechanisms involving vascular development, endothelial function and calcium homeostasis. Mendelian randomization reveals stronger instrumental estimates of DBP (OR [95% CI] = 1.20 [1.15-1.25]/10 mmHg; P = 5.57 x 10(-25)) on migraine than SBP (1.05 [1.03-1.07]/10 mmHg; P = 2.60 x 10(-07)) and a corresponding opposite effect for PP (0.92 [0.88-0.95]/10 mmHg; P = 3.65 x 10(-07)). These findings support a critical role of DBP in migraine susceptibility and shared biology underlying BP and migraine

Leveraging human genetic data to investigate the cardiometabolic effects of glucose-dependent insulinotropic polypeptide signalling.

AIMS/HYPOTHESIS: The aim of this study was to leverage human genetic data to investigate the cardiometabolic effects of glucose-dependent insulinotropic polypeptide (GIP) signalling. METHODS: Data were obtained from summary statistics of large-scale genome-wide association studies. We examined whether genetic associations for type 2 diabetes liability in the GIP and GIPR genes co-localised with genetic associations for 11 cardiometabolic outcomes. For those outcomes that showed evidence of co-localisation (posterior probability >0.8), we performed Mendelian randomisation analyses to estimate the association of genetically proxied GIP signalling with risk of cardiometabolic outcomes, and to test whether this exceeded the estimate observed when considering type 2 diabetes liability variants from other regions of the genome. RESULTS: Evidence of co-localisation with genetic associations of type 2 diabetes liability at both the GIP and GIPR genes was observed for five outcomes. Mendelian randomisation analyses provided evidence for associations of lower genetically proxied type 2 diabetes liability at the GIP and GIPR genes with lower BMI (estimate in SD units -0.16, 95% CI -0.30, -0.02), C-reactive protein (-0.13, 95% CI -0.19, -0.08) and triacylglycerol levels (-0.17, 95% CI -0.22, -0.12), and higher HDL-cholesterol levels (0.19, 95% CI 0.14, 0.25). For all of these outcomes, the estimates were greater in magnitude than those observed when considering type 2 diabetes liability variants from other regions of the genome. CONCLUSIONS/INTERPRETATION: This study provides genetic evidence to support a beneficial role of sustained GIP signalling on cardiometabolic health greater than that expected from improved glycaemic control alone. Further clinical investigation is warranted. DATA AVAILABILITY: All data used in this study are publicly available. The scripts for the analysis are available at: https://github.com/vkarhune/GeneticallyProxiedGIP

A genome-wide cross-phenotype meta-analysis of the association of blood pressure with migraine.

Blood pressure (BP) was inconsistently associated with migraine and the mechanisms of BP-lowering medications in migraine prophylaxis are unknown. Leveraging large-scale summary statistics for migraine (Ncases/Ncontrols = 59,674/316,078) and BP (N = 757,601), we find positive genetic correlations of migraine with diastolic BP (DBP, rg = 0.11, P = 3.56 × 10-06) and systolic BP (SBP, rg = 0.06, P = 0.01), but not pulse pressure (PP, rg = -0.01, P = 0.75). Cross-trait meta-analysis reveals 14 shared loci (P ≤ 5 × 10-08), nine of which replicate (P < 0.05) in the UK Biobank. Five shared loci (ITGB5, SMG6, ADRA2B, ANKDD1B, and KIAA0040) are reinforced in gene-level analysis and highlight potential mechanisms involving vascular development, endothelial function and calcium homeostasis. Mendelian randomization reveals stronger instrumental estimates of DBP (OR [95% CI] = 1.20 [1.15-1.25]/10 mmHg; P = 5.57 × 10-25) on migraine than SBP (1.05 [1.03-1.07]/10 mmHg; P = 2.60 × 10-07) and a corresponding opposite effect for PP (0.92 [0.88-0.95]/10 mmHg; P = 3.65 × 10-07). These findings support a critical role of DBP in migraine susceptibility and shared biology underlying BP and migraine

Genetic Evidence for Repurposing of GLP1R (Glucagon-Like Peptide-1 Receptor) Agonists to Prevent Heart Failure.

Background This study was designed to investigate the genetic evidence for repurposing of GLP1R (glucagon-like peptide-1 receptor) agonists to prevent heart failure (HF) and whether the potential benefit exceeds the benefit conferred by more general glycemic control. Methods and Results We applied 2-sample Mendelian randomization of genetically proxied GLP1R agonism on HF as the main outcome and left ventricular ejection fraction as the secondary outcome. The associations were compared with those of general glycemic control on the same outcomes. Genetic associations were obtained from genome-wide association study summary statistics of type 2 diabetes mellitus (228 499 cases and 1 178 783 controls), glycated hemoglobin (n=344 182), HF (47,309 cases and 930 014 controls), and left ventricular ejection fraction (n=16 923). Genetic proxies for GLP1R agonism associated with reduced risk of HF (odds ratio per 1 mmol/mol decrease in glycated hemoglobin 0.75; 95% CI, 0.64-0.87; P=1.69×10-4), and higher left ventricular ejection fraction (SD change in left ventricular ejection fraction per 1 mmol/mol decrease in glycated hemoglobin 0.22%; 95% CI, 0.03-0.42; P=0.03). The magnitude of these benefits exceeded those expected from improved glycemic control more generally. The results were similar in sensitivity analyses, and we did not find evidence to suggest that these associations were mediated by reduced coronary artery disease risk. Conclusions This genetic evidence supports the repurposing of GLP1R agonists for preventing HF

Obesity Partially Mediates the Diabetogenic Effect of Lowering LDL Cholesterol

OBJECTIVE LDL cholesterol (LDLc)-lowering drugs modestly increase body weight and type 2 diabetes risk, but the extent to which the diabetogenic effect of lowering LDLc is mediated through increased BMI is unknown. RESEARCH DESIGN AND METHODS We conducted summary-level univariable and multivariable Mendelian randomization (MR) analyses in 921,908 participants to investigate the effect of lowering LDLc on type 2 diabetes risk and the proportion of this effect mediated through BMI. We used data from 92,532 participants from 14 observational studies to replicate findings in individual-level MR analyses. RESULTS A 1-SD decrease in genetically predicted LDLc was associated with increased type 2 diabetes odds (odds ratio [OR] 1.12 [95% CI 1.01, 1.24]) and BMI (b 5 0.07 SD units [95% CI 0.02, 0.12]) in univariable MR analyses. The multivariable MR analysis showed evidence of an indirect effect of lowering LDLc on type 2 diabetes through BMI (OR 1.04 [95% CI 1.01, 1.08]) with a proportion mediated of 38% of the total effect (P 5 0.03). Total and indirect effect estimates were similar across a number of sensitivity analyses. Individual-level MR analyses confirmed the indirect effect of lowering LDLc on type 2 diabetes through BMI with an estimated proportion mediated of 8% (P 5 0.04). CONCLUSIONS These findings suggest that the diabetogenic effect attributed to lowering LDLc is partially mediated through increased BMI. Our results could help advance understanding of adipose tissue and lipids in type 2 diabetes pathophysiology and inform strategies to reduce diabetes risk among individuals taking LDLc-lowering medications

Genetic determinants of daytime napping and effects on cardiometabolic health

This is the final version. Available from Nature Research via the DOI in this record. Summary GWAS statistics are publicly available at The Sleep Disorder Knowledge Portal webpage: http://sleepdisordergenetics.org/.Daytime napping is a common, heritable behavior, but its genetic basis and causal relationship with cardiometabolic health remain unclear. Here, we perform a genome-wide association study of self-reported daytime napping in the UK Biobank (n = 452,633) and identify 123 loci of which 61 replicate in the 23andMe research cohort (n = 541,333). Findings include missense variants in established drug targets for sleep disorders (HCRTR1, HCRTR2), genes with roles in arousal (TRPC6, PNOC), and genes suggesting an obesity-hypersomnolence pathway (PNOC, PATJ). Association signals are concordant with accelerometer-measured daytime inactivity duration and 33 loci colocalize with loci for other sleep phenotypes. Cluster analysis identifies three distinct clusters of nap-promoting mechanisms with heterogeneous associations with cardiometabolic outcomes. Mendelian randomization shows potential causal links between more frequent daytime napping and higher blood pressure and waist circumference.National Institute of HealthNational Institute of HealthNational Institute of HealthNational Institute of HealthNational Institute of HealthMGH Research Scholar Fund, Academy of FinlandMedical Research CouncilSpanish Government of Investigation, Development and InnovationSeneca FoundationNIDDKInstrumentarium Science FoundationYrjö Jahnsson Foundatio

Leveraging genetic predictors of factor XI levels to anticipate results from clinical trials

BACKGROUND: Factor XI (FXI) is a promising therapeutic target for the prevention of thrombotic disease without increasing bleeding risk. METHODS: We performed Mendelian randomization (MR) analyses to investigate the association of genetically predicted reductions in FXI levels with risk of venous thromboembolism, ischemic stroke, bleeding outcomes, and lifespan. RESULTS: Genetically predicted reductions in FXI levels were associated with lower risk of ischemic stroke (odds ratio per 1 standard deviation (SD) lower serum FXI 0.90, 95% confidence interval 0.87-0.93, p = 1.59 × 10-11 ), and venous thromboembolism (0.54, 0.49-0.59, p = 2.13 × 10-39 ) but did not associate with increased bleeding risk (p > 0.16). Genetically predicted reductions in serum FXI levels associated with longer lifespan (0.37 years per 1 SD lower serum FXI, 0.13-0.61, p = 0.003). CONCLUSIONS: These genetic data support FXI as a potentially efficacious and safe therapeutic target and anticipate positive results from ongoing phase 3 clinical trials