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OBJECTIVE: To investigate the causal effect of protein intake on hypertension and the related mediating pathways. PATIENTS AND METHODS: Using genome-wide association study summary statistics of European ancestry, we applied univariable and multivariable Mendelian randomization to estimate the bidirectional associations of relative protein intake and related metabolomic signatures with hypertension (FinnGen: Ncase=42,857/Ncontrol=162,837; UK Biobank: Ncase=77,723/Ncontrol=330,366) and blood pressure (International Consortium of Blood Pressure: N=757,601) and two-step Mendelian randomization to assess the mediating roles of 40 cardiometabolic factors therein. Mendelian randomization estimates of hypertension from FinnGen and UK Biobank were meta-analyzed without heterogeneity. We performed the study from May 15, 2023, to September 15, 2023. RESULTS: Each 1-SD higher relative protein intake was causally associated with 69% (odds ratio, 0.31; 95% CI, 0.11 to 0.89) lower hypertension risk independent of the effects of other macronutrients, and was the only macronutrient associated with 2.21 (95% CI, 0.52 to 3.91) mm Hg lower pulse pressure, in a unidirectional manner. Higher plant protein-related metabolomic signature (glycine) was associated with lower hypertension risk and pulse pressure, whereas higher animal protein-related metabolomic signatures (leucine, isoleucine, valine, and isovalerylcarnitine [only systolic blood pressure]) were associated with higher hypertension risk, pulse pressure, and systolic blood pressure. The effect of relative protein intake on hypertension was causally mediated by frailty index (mediation proportion, 40.28%), monounsaturated fatty acids (13.81%), saturated fatty acids (11.39%), grip strength (5.34%), standing height (3.99%), and sitting height (3.61%). CONCLUSION: Higher relative protein intake causally reduces the risk of hypertension, partly mediated by physical fitness and circulating fatty acids.
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Mental well-being relates to multitudinous lifestyle behaviours and morbidities and underpins healthy aging. Thus far, causal evidence on whether and in what pattern mental well-being impacts healthy aging and the underlying mediating pathways is unknown. Applying genetic instruments of the well-being spectrum and its four dimensions including life satisfaction, positive affect, neuroticism and depressive symptoms (n = 80,852 to 2,370,390), we performed two-sample Mendelian randomization analyses to estimate the causal effect of mental well-being on the genetically independent phenotype of aging (aging-GIP), a robust and representative aging phenotype, and its components including resilience, self-rated health, healthspan, parental lifespan and longevity (n = 36,745 to 1,012,240). Analyses were adjusted for income, education and occupation. All the data were from the largest available genome-wide association studies in populations of European descent. Better mental well-being spectrum (each one Z-score higher) was causally associated with a higher aging-GIP (ß [95% confidence interval (CI)] in different models ranging from 1.00 [0.82-1.18] to 1.07 [0.91-1.24] standard deviations (s.d.)) independent of socioeconomic indicators. Similar association patterns were seen for resilience (ß [95% CI] ranging from 0.97 [0.82-1.12] to 1.04 [0.91-1.17] s.d.), self-rated health (0.61 [0.43-0.79] to 0.76 [0.59-0.93] points), healthspan (odds ratio [95% CI] ranging from 1.23 [1.02-1.48] to 1.35 [1.11-1.65]) and parental lifespan (1.77 [0.010-3.54] to 2.95 [1.13-4.76] years). Two-step Mendelian randomization mediation analyses identified 33 out of 106 candidates as mediators between the well-being spectrum and the aging-GIP: mainly lifestyles (for example, TV watching and smoking), behaviours (for example, medication use) and diseases (for example, heart failure, attention-deficit hyperactivity disorder, stroke, coronary atherosclerosis and ischaemic heart disease), each exhibiting a mediation proportion of >5%. These findings underscore the importance of mental well-being in promoting healthy aging and inform preventive targets for bridging aging disparities attributable to suboptimal mental health.
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Insight into associations between the gut microbiome with metabolism and aging is crucial for tailoring interventions to promote healthy longevity. In a discovery cohort of 10,207 individuals aged 40-93 years, we used 21 metabolic parameters to classify individuals into five clusters, termed metabolic multimorbidity clusters (MCs), that represent different metabolic subphenotypes. Compared to the cluster classified as metabolically healthy (MC1), clusters classified as 'obesity-related mixed' (MC4) and 'hyperglycemia' (MC5) exhibited an increased 11.1-year cardiovascular disease (CVD) risk by 75% (multivariable-adjusted hazard ratio (HR): 1.75, 95% confidence interval (CI): 1.43-2.14) and by 117% (2.17, 1.72-2.74), respectively. These associations were replicated in a second cohort of 9,061 individuals with a 10.0-year follow-up. Based on analysis of 4,491 shotgun fecal metagenomes from the discovery cohort, we found that gut microbial composition was associated with both MCs and age. Next, using 55 age-specific microbial species to capture biological age, we developed a gut microbial age (MA) metric, which was validated in four external cohorts comprising 4,425 metagenomic samples. Among individuals aged 60 years or older, the increased CVD risk associated with MC4 or MC5, as compared to MC1, MC2 or MC3, was exacerbated in individuals with high MA but diminished in individuals with low MA, independent of age, sex and other lifestyle and dietary factors. This pattern, in which younger MA appears to counteract the CVD risk attributable to metabolic dysfunction, implies a modulating role of MA in cardiovascular health for metabolically unhealthy older people.