Clustered Mendelian randomization analyses identify distinct and opposing pathways in the association between genetically influenced insulin-like growth factor-1 and type 2 diabetes mellitus

Genetic Evidence for Distinct Biological Mechanisms That Link Adiposity to Type 2 Diabetes: Toward Precision Medicine

We aimed to unravel the mechanisms connecting adiposity to type 2 diabetes. We used MR-Clust to cluster independent genetic variants associated with body fat percentage (388 variants) and BMI (540 variants) based on their impact on type 2 diabetes. We identified five clusters of adiposity-increasing alleles associated with higher type 2 diabetes risk (unfavorable adiposity) and three clusters associated with lower risk (favorable adiposity). We then characterized each cluster based on various biomarkers, metabolites, and MRI-based measures of fat distribution and muscle quality. Analyzing the metabolic signatures of these clusters revealed two primary mechanisms connecting higher adiposity to reduced type 2 diabetes risk. The first involves higher adiposity in subcutaneous tissues (abdomen and thigh), lower liver fat, improved insulin sensitivity, and decreased risk of cardiometabolic diseases and diabetes complications. The second mechanism is characterized by increased body size and enhanced muscle quality, with no impact on cardiometabolic outcomes. Furthermore, our findings unveil diverse mechanisms linking higher adiposity to higher disease risk, such as cholesterol pathways or inflammation. These results reinforce the existence of adiposity-related mechanisms that may act as protective factors against type 2 diabetes and its complications, especially when accompanied by reduced ectopic liver fat.

ARTICLE HIGHLIGHTS

Mammographic density mediates the protective effect of early-life body size on breast cancer risk

The unexplained protective effect of childhood adiposity on breast cancer risk may be mediated via mammographic density (MD). Here, we investigate a complex relationship between adiposity in childhood and adulthood, puberty onset, MD phenotypes (dense area (DA), non-dense area (NDA), percent density (PD)), and their effects on breast cancer. We use Mendelian randomization (MR) and multivariable MR to estimate the total and direct effects of adiposity and age at menarche on MD phenotypes. Childhood adiposity has a decreasing effect on DA, while adulthood adiposity increases NDA. Later menarche increases DA/PD, but when accounting for childhood adiposity, this effect is attenuated. Next, we examine the effect of MD on breast cancer risk. DA/PD have a risk-increasing effect on breast cancer across all subtypes. The MD SNPs estimates are heterogeneous, and additional analyses suggest that different mechanisms may be linking MD and breast cancer. Finally, we evaluate the role of MD in the protective effect of childhood adiposity on breast cancer. Mediation MR analysis shows that 56% (95% CIs [32%-79%]) of this effect is mediated via DA. Our finding suggests that higher childhood adiposity decreases mammographic DA, subsequently reducing breast cancer risk. Understanding this mechanism is important for identifying potential intervention targets.

Mendelian randomization analysis demonstrates the causal effects of IGF family members in diabetes

Background

Observational studies have consistently shown significant associations between the IGF family and metabolic diseases, including diabetes. However, these associations can be influenced by confounding factors and reverse causation. This study aimed to assess the causal relationship between the IGF family and diabetes using Mendelian randomization (MR).

Methods

We conducted a two-sample MR analysis to investigate the causal effects of the IGF family on diabetes. Instrumental variables for the IGF family and diabetes were derived from summary-level statistics obtained from genome-wide association studies. Horizontal pleiotropy was assessed using MR-Egger regression and the weighted median method. We applied the inverse-variance weighted method as part of the conventional MR analysis to evaluate the causal impact of the IGF family on diabetes risk. To test the robustness of the results, we also employed MR-Egger regression, the weighted median method, and a leave-one-out analysis.

Results

Our study revealed that IGF-1 causally increases the risk of Type 2 Diabetes (T2D), while IGFBP-6, adiponectin and INSR decreases the risk (IGF-1, OR 1.02 [95% CI 1-1.03], p = 0.01; IGFBP-6, OR 0.92 [95% CI 0.87-0.98], p = 0.01; Adiponectin, OR 0.837 [95% CI 0.721-0.970], p = 0.018; INSR, OR 0.910 [95% CI 0.872-0.950], p = 1.52 × 10-5). Additionally, genetically lower levels of IGF-1 and IGFBP-5, along with higher levels of IGFBP-7, were associated with an increased risk of Type 1 Diabetes (T1D) (IGF-1, OR 0.981 [95% CI 0.963-0.999], p = 0.037; IGFBP-5, OR 0.882 [95% CI 0.778-0.999], p = 0.049; IGFBP-7, OR 1.103 [95% CI 1.008-1.206], p = 0.033).

Conclusion

In summary, our investigation has unveiled causal relationships between specific IGF family members and T1D and T2D through MR analysis. Generally, the IGF family appears to reduce the risk of T1D, but it presents a more complex and controversial role in the context of T2D. These findings provide compelling evidence that T2D is intricately linked with developmental impairment. Our study results offer fresh insights into the pathogenesis and the significance of serum IGF family member concentrations in assessing diabetes risk.

Metabolic diseases and healthy aging: identifying environmental and behavioral risk factors and promoting public health

Aging is a progressive and irreversible pathophysiological process that manifests as the decline in tissue and cellular functions, along with a significant increase in the risk of various aging-related diseases, including metabolic diseases. While advances in modern medicine have significantly promoted human health and extended human lifespan, metabolic diseases such as obesity and type 2 diabetes among the older adults pose a major challenge to global public health as societies age. Therefore, understanding the complex interaction between risk factors and metabolic diseases is crucial for promoting well-being and healthy aging. This review article explores the environmental and behavioral risk factors associated with metabolic diseases and their impact on healthy aging. The environment, including an obesogenic environment and exposure to environmental toxins, is strongly correlated with the rising prevalence of obesity and its comorbidities. Behavioral factors, such as diet, physical activity, smoking, alcohol consumption, and sleep patterns, significantly influence the risk of metabolic diseases throughout aging. Public health interventions targeting modifiable risk factors can effectively promote healthier lifestyles and prevent metabolic diseases. Collaboration between government agencies, healthcare providers and community organizations is essential for implementing these interventions and creating supportive environments that foster healthy aging.

The mediating role of mammographic density in the protective effect of early-life adiposity on breast cancer risk: a multivariable Mendelian randomization study

Observational studies suggest that mammographic density (MD) may have a role in the unexplained protective effect of childhood adiposity on breast cancer risk. Here, we investigated a complex and interlinked relationship between puberty onset, adiposity, MD, and their effects on breast cancer using Mendelian randomization (MR). We estimated the effects of childhood and adulthood adiposity, and age at menarche on MD phenotypes (dense area (DA), non-dense area (NDA), percent density (PD)) using MR and multivariable MR (MVMR), allowing us to disentangle their total and direct effects. Next, we examined the effect of MD on breast cancer risk, including risk of molecular subtypes, and accounting for genetic pleiotropy. Finally, we used MVMR to evaluate whether the protective effect of childhood adiposity on breast cancer was mediated by MD. Childhood adiposity had a strong inverse effect on mammographic DA, while adulthood adiposity increased NDA. Later menarche had an effect of increasing DA and PD, but when accounting for childhood adiposity, this effect attenuated to the null. DA and PD had a risk-increasing effect on breast cancer across all subtypes. The MD single-nucleotide polymorphism (SNP) estimates were extremely heterogeneous, and examination of the SNPs suggested different mechanisms may be linking MD and breast cancer. Finally, MR mediation analysis estimated that 56% (95% CIs [32% - 79%]) of the childhood adiposity effect on breast cancer risk was mediated via DA. In this work, we sought to disentangle the relationship between factors affecting MD and breast cancer. We showed that higher childhood adiposity decreases mammographic DA, which subsequently leads to reduced breast cancer risk. Understanding this mechanism is of great importance for identifying potential targets of intervention, since advocating weight gain in childhood would not be recommended.

Causal factors underlying diabetes risk informed by Mendelian randomisation analysis: evidence, opportunities and challenges

Diabetes and its complications cause a heavy disease burden globally. Identifying exposures, risk factors and molecular processes causally associated with the development of diabetes can provide important evidence bases for disease prevention and spur novel therapeutic strategies. Mendelian randomisation (MR), an epidemiological approach that uses genetic instruments to infer causal associations between an exposure and an outcome, can be leveraged to complement evidence from observational and clinical studies. This narrative review aims to summarise the evidence on potential causal risk factors for diabetes by integrating published MR studies on type 1 and 2 diabetes, and to reflect on future perspectives of MR studies on diabetes. Despite the genetic influence on type 1 diabetes, few MR studies have been conducted to identify causal exposures or molecular processes leading to increased disease risk. In type 2 diabetes, MR analyses support causal associations of somatic, mental and lifestyle factors with development of the disease. These studies have also identified biomarkers, some of them derived from the gut microbiota, and molecular processes leading to increased disease risk. These studies provide valuable data to better understand disease pathophysiology and explore potential therapeutic targets. Because genetic association studies have mostly been restricted to participants of European descent, multi-ancestry cohorts are needed to examine the role of different types of physical activity, dietary components, metabolites, protein biomarkers and gut microbiome in diabetes development.

Investigating sex-specific associations of lipid traits with type 2 diabetes, glycemic traits and sex hormones using Mendelian randomization

BACKGROUND

Low-density lipoprotein (LDL)-cholesterol is positively associated with cardiovascular disease (CVD) and inversely associated with type 2 diabetes, which could detract from lipid modification. Here, we examined whether lipid traits potentially relevant to CVD aetiology, i.e. apolipoprotein B (apoB), triglycerides (TG) and lipoprotein(a) [Lp(a)] exhibited the same associations. We investigated sex-specifically, including the role of sex hormones, because sex disparities exist in lipid profile and type 2 diabetes. We also replicated where possible.

METHODS

We used Mendelian randomization (MR) to examine sex-specific associations of apoB, TG and Lp(a) with type 2 diabetes, HbA1c, fasting insulin, fasting glucose, testosterone and estradiol in the largest relevant sex-specific genome-wide association studies (GWAS) in people of European ancestry and replicated where possible. We also assessed sex-specific associations of liability to type 2 diabetes with apoB, TG and Lp(a).

RESULTS

Genetically predicted apoB and Lp(a) had little association with type 2 diabetes or glycemic traits in women or men. Genetically predicted higher TG was associated with higher type 2 diabetes risk [odds ratio (OR) 1.44 per standard deviation (SD), 95% confidence interval (CI) 1.26 to 1.65], HbA1c and fasting insulin specifically in women. Higher TG was associated with lower testosterone in women and higher testosterone in men, but with lower estradiol in men and women. Genetic liability to type 2 diabetes was associated with higher TG in women, and possibly with lower apoB in men.

CONCLUSIONS

Lipid traits potentially relevant to CVD aetiology do not exhibit contrasting associations with CVD and type 2 diabetes. However, higher TG is associated with higher type 2 diabetes risk and glycemic traits, which in turn further increases TG specifically in women, possibly driven by sex hormones.

Obesity, Fat Distribution and Risk of Cancer in Women and Men: A Mendelian Randomisation Study

Obesity and upper-body fat distribution are independent, cardiometabolic risk factors but whether they also display comparable associations with cancer risk is unknown. We investigated the causal relationships between body mass index (BMI) and BMI-adjusted waist-to-hip ratio (WHRadjBMI) and cancer risk and searched for potential drivers linking these traits to carcinogenesis using two-sample and multivariable Mendelian randomisation. In women, genetically instrumented higher BMI was associated with lower breast (OR = 0.87, 95% CI 0.81-0.93) and higher endometrial (OR = 1.75, 95% CI 1.55-1.96) cancer risk whilst WHRadjBMI was associated with higher colon cancer risk (OR = 1.22, 95% CI 1.07-1.42). In men, elevated BMI was associated with lower prostate cancer risk (OR = 0.91, 95% CI 0.85-0.98). Mechanistically, testosterone and insulin mediated 21% and 35%, respectively of the total, genetically determined association of BMI with endometrial cancer risk whilst HDL cholesterol and IGF-1 mediated 40% and 22%, respectively of the association between BMI and breast cancer risk. In men, testosterone mediated 21% of the association between BMI and prostate cancer risk. Colon cancer aside, the total amount of body fat might be more important than its location in modulating cancer susceptibility due to differential effects of obesity and fat distribution on adiposity-associated cancer drivers.