Stratification of Type 2 Diabetes by Age of Diagnosis in the UK Biobank Reveals Subgroup-Specific Genetic Associations and Causal Risk Profiles

Association of a composite trait for anthropometrics, adiposity and energy expenditure with cardiometabolic diseases: An age-stratified cohort and genetic risk score analysis

AIM

Various anthropometric measures capture distinct as well as overlapping characteristics of an individual's body composition. To characterize independent body composition measures, we aimed to reduce easily-obtainable individual measures reflecting adiposity, anthropometrics and energy expenditure into fewer independent constructs, and to assess their potential sex- and age-specific relation with cardiometabolic diseases.

METHODS

Analyses were performed within European ancestry participants from UK Biobank (N = 418,963, mean age 58.0 years, 56% women). Principal components (PC) analyses were used for the dimension reduction of 11 measures of adiposity, anthropometrics and energy expenditure. PCs were studied in relation to incident type 2 diabetes mellitus (T2D) and coronary artery disease (CAD). Multivariable-adjusted Cox regression analyses, adjusted for confounding factors, were performed in all and stratified by age. Genome-wide association studies were performed in half of the cohort (N = 156,295) to identify genetic variants as instrumental variables. Genetic risk score analyses were performed in the other half of the cohort stratified by age of disease onset (N = 156,295).

RESULTS

We identified two PCs, of which PC1 reflected lower overall adiposity (negatively correlated with all adiposity aspects) and PC2 reflected more central adiposity (mainly correlated with higher waist-hip ratio, but with lower total body fat) and increased height, collectively capturing 87.8% of the total variance. Similar to that observed in the multivariable-adjusted regression analyses, we found associations between the PC1 genetic risk score and lower risks of CAD and T2D [CAD cases <50 years, odds ratio: 0.91 (95% confidence interval 0.87, 0.94) per SD; T2D cases <50 years, odds ratio: 0.76 (0.72, 0.81)], which attenuated with higher age (p-values 8.13E-4 and 2.41E-6, respectively). No associations were found for PC2.

CONCLUSIONS

The consistently observed weaker associations of the composite traits with cardiometabolic disease suggests the need for age-specific cardiometabolic disease prevention strategies.

A polygenic risk score derived from common variants of monogenic diabetes genes is associated with young-onset type 2 diabetes and cardiovascular-kidney complications

AIMS/HYPOTHESIS

Monogenic diabetes is caused by rare mutations in genes usually implicated in beta cell biology. Common variants of monogenic diabetes genes (MDG) may jointly influence the risk of young-onset type 2 diabetes (YOD, diagnosed before the age of 40 years) and cardiovascular and kidney events.

METHODS

Using whole-exome sequencing data, we constructed a weighted polygenic risk score (wPRS) consisting of 135 common variants (minor allele frequency >0.01) of 34 MDG based on r2>0.2 for linkage disequilibrium in a discovery case-control cohort of 453 adults with YOD (median [IQR] age 39.7 [34.9-46.9] years) and 405 without YOD (median [IQR] age 56.7 [50.3-61.0] years), followed by validation in an independent cross-sectional cohort with array-based genotyping for YOD and a prospective cohort of individuals with type 2 diabetes for cardiovascular and kidney events.

RESULTS

In the discovery cohort, the OR of the 135 common variants for YOD ranged from 1.00 to 2.61. In the validation cohort (920 YOD and 4910 non-YOD), top-10%-wPRS was associated with an OR of 1.42 (95% CI 1.03, 1.95, p=0.033) for YOD compared with bottom-10%-wPRS. In 2313 individuals with type 2 diabetes (median [IQR]: age 53.4 [45.4-61.7] years; disease duration 4.0 [1.0-9.0] years) observed for a median (IQR) of 17.5 (14.4-21.8) years, standardised wPRS was associated with increased HR for incident cardiovascular events (1.16 [95% CI 1.06, 1.27], p=0.001), kidney events (1.09 [95% CI 1.02, 1.16], p=0.013) and cardiovascular-kidney events (1.10 [95% CI 1.03, 1.16], p=0.003). Using the 'bottom-20%-wPRS plus baseline disease duration <5 years' group as referent, the 'top-20%-wPRS plus baseline disease duration 5 to <10 years' group had unadjusted and adjusted HR of 1.60 (95% CI 1.17, 2.19, p=0.003) and 1.62 (95% CI 1.16, 2.26, p=0.005), respectively, for cardiovascular-kidney events compared with 1.38 (95% CI 0.97, 1.98, p=0.075) and 1.06 (95% CI 0.72, 1.57, p=0.752) in the 'bottom-20%-wPRS plus baseline disease duration ≥10 years' group.

CONCLUSIONS/INTERPRETATION

Common variants of MDG increased risk for YOD and cardiovascular-kidney events.

Genetic association analyses highlight apolipoprotein B as a determinant of chronic kidney disease in patients with type 2 diabetes

BACKGROUND

Blood lipid levels were associated with chronic kidney disease (CKD) in patients with type 2 diabetes (T2D), but the genetic basis and causal nature remain unclear.

OBJECTIVE

This study aimed to investigate the relationships of lipids and their fractions with CKD in patients with T2D.

METHODS

Our prospective analysis involved 8,607 White participants with T2D but no CKD at baseline from the UK Biobank. Five common lipid traits were included as exposures. Weighted genetic risk scores (GRSs) for these lipid traits were developed. The causal associations between lipid traits, as well as lipid fractions, and CKD were explored using linear or nonlinear Mendelian randomization (MR). The 10-year predicted probabilities of CKD were evaluated via integrating MR and Cox models.

RESULTS

Higher GRS of apolipoprotein B (ApoB) was associated with an increased CKD risk (hazard ratio (HR) [95% confidence interval (CI)]:1.07[1.02,1.13] per SD; P = 0.008) after adjusting for potential confounders. Linear MR indicated a positive association between genetically predicted ApoB levels and CKD (HR [95% CI]:1.53 [1.12,2.09]; P = 0.008), but no evidence of associations was found between other lipid traits and CKD in T2D. Regarding 12 ApoB- containing lipid fractions, a significant causal association was found between medium very-low-density lipoprotein particles and CKD (HR[95% CI]:1.16[1.02,1.32];P = 0.020). Nonlinear MR did not support nonlinearity in these causal associations. The 10-year probability curve showed that ApoB level was positively associated with the risk of CKD in patients with T2D.

CONCLUSION

Lower ApoB levels were causally associated with a reduced risk of CKD in patients with T2D, positioning ApoB as a potential therapeutic target for CKD prevention in this population.

Association Between Accelerometer-Measured Irregular Sleep Duration and Type 2 Diabetes Risk: A Prospective Cohort Study in the UK Biobank

OBJECTIVE

To evaluate the association between irregular sleep duration and incident diabetes in a U.K. population over 7 years of follow-up.

RESEARCH DESIGN AND METHODS

Among 84,421 UK Biobank participants (mean age 62 years) who were free of diabetes at the time of providing accelerometer data in 2013-2015 and prospectively followed until May 2022, sleep duration variability was quantified by the within-person SD of 7-night accelerometer-measured sleep duration. We used Cox proportional hazard models to estimate hazard ratios (HRs) for incident diabetes (identified from medical records, death register, and/or self-reported diagnosis) according to categories of sleep duration SD.

RESULTS

There were 2,058 incident diabetes cases over 622,080 person-years of follow-up. Compared with sleep duration SD ≤ 30 min, the HR (95% CI) was 1.15 (0.99, 1.33) for 31-45 min, 1.28 (1.10, 1.48) for 46-60 min, 1.54 (1.32, 1.80) for 61-90 min, and 1.59 (1.33, 1.90) for ≥91 min, after adjusting for age, sex, and race. We found a nonlinear relationship (P nonlinearity 0.0002), with individuals with a sleep duration SD of >60 vs. ≤60 min having 34% higher diabetes risk (95% CI 1.22, 1.47). Further adjustment for lifestyle, comorbidities, environmental factors, and adiposity attenuated the association (HR comparing sleep duration SD of >60 vs. ≤60 min: 1.11; 95% CI 1.01, 1.22). The association was stronger among individuals with lower diabetes polygenic risk score (PRS; P interaction ≤ 0.0264) and longer sleep duration (P interaction ≤ 0.0009).

CONCLUSIONS

Irregular sleep duration was associated with higher diabetes risk, particularly in individuals with a lower diabetes PRS and longer sleep duration.

Young-Onset Diabetes in East Asians: From Epidemiology to Precision Medicine

Precision diagnosis is the keystone of clinical medicine. In East Asians, classical type 1 diabetes is uncommon in patients with youngonset diabetes diagnosed before age of 40, in whom a family history, obesity, and beta-cell and kidney dysfunction are key features. Young-onset diabetes affects one in five Asian adults with diabetes in clinic settings; however, it is often misclassified, resulting in delayed or non-targeted treatment. Complex aetiologies, long disease duration, aggressive clinical course, and a lack of evidence-based guidelines have contributed to variable care standards and premature death in these young patients. The high burden of comorbidities, notably mental illness, highlights the numerous knowledge gaps related to this silent killer. The majority of adult patients with youngonset diabetes are managed as part of a heterogeneous population of patients with various ages of diagnosis. A multidisciplinary care team led by physicians with special interest in young-onset diabetes will help improve the precision of diagnosis and address their physical, mental, and behavioral health. To this end, payors, planners, and providers need to align and re-design the practice environment to gather data systematically during routine practice to elucidate the multicausality of young-onset diabetes, treat to multiple targets, and improve outcomes in these vulnerable individuals.

BMI and Cardiometabolic Traits in Japanese: A Mendelian Randomization Study

BACKGROUND

Although many observational studies have demonstrated significant relationships between obesity and cardiometabolic traits, the causality of these relationships in East Asians remains to be elucidated.

METHODS

We conducted individual-level Mendelian randomization (MR) analyses targeting 14,083 participants in the Japan Multi-Institutional Collaborative Cohort Study and two-sample MR analyses using summary statistics based on genome-wide association study data from 173,430 Japanese. Using 83 body mass index (BMI)-related loci, genetic risk scores (GRS) for BMI were calculated, and the effects of BMI on cardiometabolic traits were examined for individual-level MR analyses using the two-stage least squares estimator method. The β-coefficients and standard errors for the per-allele association of each single-nucleotide polymorphism as well as all outcomes, or odds ratios with 95% confidence intervals were calculated in the two-sample MR analyses.

RESULTS

In individual-level MR analyses, the GRS of BMI was not significantly associated with any cardiometabolic traits. In two-sample MR analyses, higher BMI was associated with increased risks of higher blood pressure, triglycerides, and uric acid, as well as lower high-density-lipoprotein cholesterol and eGFR. The associations of BMI with type 2 diabetes in two-sample MR analyses were inconsistent using different methods, including the directions.

CONCLUSION

The results of this study suggest that, even among the Japanese, an East Asian population with low levels of obesity, higher BMI could be causally associated with the development of a variety of cardiometabolic traits. Causality in those associations should be clarified in future studies with larger populations, especially those of BMI with type 2 diabetes.

Factors associated with adherence or nonadherence to insulin therapy among adults with type 2 diabetes mellitus: A scoping review

BACKGROUND AND AIM

One of the greatest barriers to the treatment of T2DM is nonadherence which particularly applies to insulin therapy. There is a need for a comprehensive overview of all factors associated with nonadherence to insulin therapy. The aim of this study was to identify factors associated with adherence or nonadherence to insulin therapy among adults with T2DM.

METHODS

A scoping review was conducted in accordance with the PRISMA 2020 statement. A systematic search was performed in PubMed, Cinahl, and Web of Science (January 2013 to March 2023).

RESULTS

A final sample of 48 studies was included in the scoping review. The synthesis revealed 30 factors associated with adherence or nonadherence. The factors were grouped into 6 themes: demographics, attitude and perceptions, management of diabetes, impact on daily living, disease and medication, and healthcare system.

CONCLUSION

The most prominent factors identified were age, cost of healthcare, personal beliefs towards insulin therapy, social stigma, patient education, complexity of diabetes treatment, impact of insulin therapy on daily life, and fear of side effects. The results indicate a need for further research to determine threshold values for the factors associated with adherence or nonadherence.

The impact of sociodemographic status on the association of classical cardiovascular risk factors with coronary artery disease: a stratified Mendelian randomization study

OBJECTIVES

Low socioeconomic status (SES) is associated with cardiovascular risk factors and increased coronary artery disease (CAD) risk. We tested whether SES is an effect modifier of the association between classical cardiovascular risk factors and CAD using SES-stratified Mendelian Randomization in European-ancestry participants from UK Biobank.

STUDY DESIGN AND SETTING

We calculated weighted genetic risk scores (GRS) for the risk factors body mass index (BMI), systolic blood pressure, low-density lipoprotein cholesterol, and triglycerides. Participants were stratified by Townsend deprivation index score. Logistic regression models were used to investigate associations between GRSs and CAD occurrence. Additionally, stratification based on GRS-adjusted Townsend deprivation index residuals was conducted to correct for possible collider-stratification bias.

RESULTS

In a total sample size of N = 446,485, with 52,946 cases, the risk for CAD per standard deviation increase in genetically influenced BMI was highest in the group with the lowest 25% SES (odds ratio: 1.126, 95% confidence interval: 1.106-1.145; odds ratio: 1.081, 95% confidence interval: 1.059-1.103 in high SES), remaining similar after controlling for possible collider-stratification bias. The effects of genetically influenced systolic blood pressure, low-density lipoprotein cholesterol, and triglyceride on CAD were similar between SES groups.

CONCLUSION

CAD risk attributable to increased BMI is not homogenous and could be modified by SES. This emphasizes the need of tailor-made approaches for BMI-associated CAD risk reduction.

Stratified genome-wide association analysis of type 2 diabetes reveals subgroups with genetic and environmental heterogeneity

Type 2 diabetes (T2D) is a heterogeneous illness caused by genetic and environmental factors. Previous genome-wide association studies (GWAS) have identified many genetic variants associated with T2D and found evidence of differing genetic profiles by age-at-onset. This study seeks to explore further the genetic and environmental drivers of T2D by analyzing subgroups on the basis of age-at-onset of diabetes and body mass index (BMI). In the UK Biobank, 36 494 T2D cases were stratified into three subgroups, and GWAS was performed for all T2D cases and for each subgroup relative to 421 021 controls. Altogether, 18 single nucleotide polymorphisms were significantly associated with T2D genome-wide in one or more subgroups and also showed evidence of heterogeneity between the subgroups (Cochrane's Q P < 0.01), with two SNPs remaining significant after multiple testing (in CDKN2B and CYTIP). Combined risk scores, on the basis of genetic profile, BMI and age, resulted in excellent diabetes prediction [area under the ROC curve (AUC) = 0.92]. A modest improvement in prediction (AUC = 0.93) was seen when the contribution of genetic and environmental factors was evaluated separately for each subgroup. Increasing sample sizes of genetic studies enables us to stratify disease cases into subgroups, which have sufficient power to highlight areas of genetic heterogeneity. Despite some evidence that optimizing combined risk scores by subgroup improves prediction, larger sample sizes are likely needed for prediction when using a stratification approach.

Earlier Age at Type 2 Diabetes Diagnosis Is Associated With Increased Genetic Risk of Cardiovascular Disease

OBJECTIVE

We investigated genetic risk of cardiovascular disease (CVD) by age at type 2 diabetes (T2D) diagnosis.

RESEARCH DESIGN AND METHODS

We compared incident CVD events by age at T2D diagnosis using UK Biobank (N = 12,321) and the Seoul National University Hospital (SNUH) cohort (N = 1,165). Genetic risk was quantified using polygenic risk score (PRS).

RESULTS

Individuals with earlier T2D diagnosis had higher CVD risk. In UK Biobank, the effect size of coronary artery disease (CAD) PRS on incident CAD was largest in individuals diagnosed with T2D at ages 30-39 years (hazard ratio 2.25; 95% CI 1.56-3.26) and decreased as age at diagnosis increased: ages 40-49 (1.51; 1.30-1.75), 50-59 (1.36; 1.24-1.50), and 60-69 years (1.30; 1.14-1.48) (Pinteraction = 0.0031). A similar trend was observed in the SNUH cohort. This increased genetic risk associated with earlier T2D diagnosis was largely mitigated by a healthy lifestyle.

CONCLUSIONS

Individuals with an earlier T2D diagnosis have a higher genetic risk of CAD, and this information could be used to tailor lifestyle interventions.

Four missense genetic variants in CUBN are associated with higher levels of eGFR in non-diabetes but not in diabetes mellitus or its subtypes: A genetic association study in Europeans

AIM

Rare genetic variants in the CUBN gene encoding the main albumin-transporter in the proximal tubule of the kidneys have previously been associated with microalbuminuria and higher urine albumin levels, also in diabetes. Sequencing studies in isolated proteinuria suggest that these variants might not affect kidney function, despite proteinuria. However, the relation of these CUBN missense variants to the estimated glomerular filtration rate (eGFR) is largely unexplored. We hereby broadly examine the associations between four CUBN missense variants and eGFR_creatinine in Europeans with Type 1 (T1D) and Type 2 Diabetes (T2D). Furthermore, we sought to deepen our understanding of these variants in a range of single- and aggregate- variant analyses of other kidney-related traits in individuals with and without diabetes mellitus.

METHODS

We carried out a genetic association-based linear regression analysis between four CUBN missense variants (rs141640975, rs144360241, rs45551835, rs1801239) and eGFR_creatinine (ml/min/1.73 m², CKD-EPI_{creatinine(2012)}, natural log-transformed) in populations with T1D (n ~ 3,588) or T2D (n ~ 31,155) from multiple European studies and in individuals without diabetes from UK Biobank (UKBB, n ~ 370,061) with replication in deCODE (n = 127,090). Summary results of the diabetes-group were meta-analyzed using the fixed-effect inverse-variance method.

RESULTS

Albeit we did not observe associations between eGFR_creatinine and CUBN in the diabetes-group, we found significant positive associations between the minor alleles of all four variants and eGFR_creatinine in the UKBB individuals without diabetes with rs141640975 being the strongest (Effect=0.02, P_{eGFR_creatinine}=2.2 × 10^-9). We replicated the findings for rs141640975 in the Icelandic non-diabetes population (Effect=0.026, P_{eGFR_creatinine}=7.7 × 10^-4). For rs141640975, the eGFR_creatinine-association showed significant interaction with albuminuria levels (normo-, micro-, and macroalbuminuria; p = 0.03). An aggregated genetic risk score (GRS) was associated with higher urine albumin levels and eGFR_creatinine. The rs141640975 variant was also associated with higher levels of eGFR_{creatinine-cystatin C} (ml/min/1.73 m², CKD-EPI₂₀₂₁, natural log-transformed) and lower circulating cystatin C levels.

CONCLUSIONS

The positive associations between the four CUBN missense variants and eGFR in a large population without diabetes suggests a pleiotropic role of CUBN as a novel eGFR-locus in addition to it being a known albuminuria-locus. Additional associations with diverse renal function measures (lower cystatin C and higher eGFR_{creatinine-cystatin C} levels) and a CUBN-focused GRS further suggests an important role of CUBN in the future personalization of chronic kidney disease management in people without diabetes.

Causal associations between age at diagnosis of diabetes and cardiovascular outcomes: a Mendelian randomization study

CONTEXT

Whether diabetes diagnosed at different age groups is causally associated with cardiovascular diseases (CVDs) is unknown.

OBJECTIVE

We conducted two-sample Mendelian randomization analyses to investigate the causal associations of diabetes by age at diagnosis with five type-specific CVDs and 11 cardiometabolic traits.

METHODS

We selected 208 single nucleotide polymorphisms (SNPs) for diabetes and 3, 21, 57, and 14 SNPs for diabetes diagnosed at <50, 50-60, 60-70, and >70 years, respectively, based on the GWAS (24,986 cases/187,130 controls) in the UK Biobank, and extracted genetic associations with stroke, myocardial infarction, heart failure, atrial fibrillation, and CVD mortality, as well as blood pressures, adiposity measurements, and lipids and apolipoproteins from corresponding European-descent GWASs. The inverse-variance weighted method was used as main analysis with several sensitivity analyses.

RESULTS

Diabetes diagnosed at all four age groups was causally associated with increased risks of stroke (5%-8%) and myocardial infarction (8%-10%), higher systolic blood pressure (0.56-0.94 mmHg) and waist-to-hip ratio (0.003-0.004), and lower body mass index (0.31-0.42 kg/m2), waist circumference (0.68-0.99 cm), and hip circumference (0.57-0.80 cm). Diabetes diagnosed at specific age groups was causally associated with increased risks of heart failure (4%) and CVD mortality (8%), higher diastolic blood pressure (0.20 mmHg) and triglycerides (0.06 SD), and lower high-density lipoprotein cholesterol (0.02 mmol/L). The effect sizes of genetically determined diabetes on CVD subtypes and cardiometabolic traits were comparable and the corresponding 95% confidence intervals largely overlapped across the four age groups.

CONCLUSION

Our findings provide novel evidence that genetically determined diabetes subgroups by age at diagnosis have similar causal effects on CVD and cardiometabolic risks.

The association of measures of body shape and adiposity with incidence of cardiometabolic disease from an ageing perspective

While obesity increases the risk of developing cardiometabolic diseases (CMDs), these associations seem to attenuate with increasing age, albeit studied poorly. The present study aimed to investigate the associations between adiposity and CMDs in sex-specific groups of chronological age and leukocyte telomere length (LTL) as a measure of biological age. We investigated the associations between BMI, a body shape index, waist-to-hip ratio (adjusted for BMI) and total body fat, and incident coronary artery disease (CAD), type 2 diabetes (T2D) and ischemic stroke (IS) in 413,017 European-ancestry participants of the UK Biobank without CMD at baseline. We assessed the change in the associations between adiposity and CMD over strata of increasing chronological age or decreasing LTL. Participants (56% women) had a median (IQR) age of 57.0 (50.0-63.0) years. The median follow-up time was 12 years. People with higher BMI had a higher risk of incident CAD (HR 1.14 (95% confidence interval [CI] 1.13, 1.16)), T2D (HR 1.70 (95% CI 1.68, 1.72)) and IS (HR 1.09 (95% CI 1.06, 1.12)). In groups based on chronological age and LTL, adiposity measures were associated with higher risk of CAD and T2D in both men and women, but these associations attenuated with increasing chronological age (P_interactions < 0.001), but not with decreasing LTL (P_interaction men = 0.85; P_interaction women = 0.27). Increased (abdominal) adiposity was associated with higher risk of incident CMDs, which attenuated with increasing chronological age but not with decreasing LTL. Future research may validate these findings using different measures of biological age.

Comprehensive risk profiles of family history and lifestyle and metabolic risk factors in relation to diabetes: A prospective cohort study

BACKGROUND

Family history of diabetes, unhealthy lifestyles, and metabolic disorders are individually associated with higher risk of diabetes, but how different combinations of the three risk categories are associated with incident diabetes remains unclear. We aimed to estimate the associations of comprehensive risk profiles of family history and lifestyle and metabolic risk factors with diabetes risk.

METHODS

This study included 5290 participants without diabetes at baseline with a mean follow-up of 4.4 years. Five unhealthy lifestyles and five metabolic disorders were each allocated a score, resulting in an aggregated lifestyle and metabolic risk score ranging from 0 to 5. Eight risk profiles were constructed from combinations of three risk categories: family history of diabetes (yes, no), lifestyle risk (high, low), and metabolic risk (high, low).

RESULTS

Compared with the profile without any risk category, other profiles exhibited incrementally higher risks of diabetes with increasing numbers of categories: the hazard ratio (HR, 95% confidence interval [CI]) for diabetes ranged from 1.34 (1.01-1.79) to 2.33 (1.60-3.39) for profiles with one risk category, ranged from 2.42 (1.45-4.04) to 4.18 (2.42-7.21) for profiles with two risk categories, and was 4.59 (2.85-7.39) for the profile with three risk categories. The associations between the numbers of risk categories and diabetes risk were more prominent in women (pinteraction  = .025) and slightly more prominent in adults <55 years (pinteraction  = .052).

CONCLUSIONS

This study delineated associations between comprehensive risk profiles with diabetes risk, with stronger associations observed in women and slightly stronger associations in adults younger than 55 years.

Association of mental health with the risk of coronary artery disease in patients with diabetes: A mendelian randomization study

BACKGROUND AND AIMS

Observational studies have shown an association between mental health and coronary artery disease (CAD) in patients with diabetes. Nevertheless, whether these associations are causal is still unknown. In this two-sample Mendelian randomization (MR) study, we aimed to assess the causality between mental health and CAD in patients with diabetes.

METHODS AND RESULTS

Single-nucleotide polymorphisms (SNPs) associated with: depression (807,553 individuals), anxiety (83,556 individuals) and neuroticism (329,821 individuals) were identified from the largest genome-wide association studies (GWAS). Summary-level data for CAD were extracted from the recently published GWAS of 15,666 diabetic patients (3968 CAD cases and 11,696 controls). The inverse-variance weighted (IVW) method was used for the main analysis. Sensitivity analyses included weighted median, maximum likelihood, and the MR-Egger method. Genetic liability to depression was significantly associated with a higher risk of CAD in patients with diabetes (odds ratio [OR], 1.286; 95%CI，1.018-1.621；p = 0.035). For anxiety and neuroticism, no causal association with CAD in patients with diabetes was observed. Consistent results were obtained in most sensitivity analyses.

CONCLUSIONS

This MR study provides genetic evidence that depression is a potential risk factor for CAD in patients with diabetes. However, anxiety and neuroticism were not causally associated with CAD in patients with diabetes. Mental health treatments should be enhanced to prevent CAD in patients with diabetes.

Classical risk factors for primary coronary artery disease from an aging perspective through Mendelian Randomization

The significance of classical risk factors in coronary artery disease (CAD) remains unclear in older age due to possible changes in underlying disease pathologies. Therefore, we conducted Mendelian Randomization approaches to investigate the causal relationship between classical risk factors and primary CAD in different age groups. A Mendelian Randomization study was conducted in European-ethnicity individuals from the UK Biobank population. Analyses were performed using data of 22,313 CAD cases (71.6% men) and 407,920 controls (44.5% men). Using logistic regression analyses, we investigated the associations between standardized genetic risk score and primary CAD stratified by age of diagnosis. In addition, feature importance and model accuracy were assessed in different age groups to evaluate predictive power of the genetic risk scores with increasing age. We found age-dependent associations for all classical CAD risk factors. Notably, body mass index (OR 1.22 diagnosis < 50 years; OR 1.02 diagnosis > 70 years), blood pressure (OR 1.12 < 50 years; OR 1.04 > 70 years), LDL cholesterol (OR 1.16 < 50 years; OR 1.02 > 70 years), and triglyceride levels (OR 1.11 < 50 years; 1.04 > 70 years). In line with the Mendelian Randomization analyses, model accuracy and feature importance of the classical risk factors decreased with increasing age of diagnosis. Causal determinants for primary CAD are age dependent with classical CAD risk factors attenuating in relation with primary CAD with increasing age. These results question the need for (some) currently applied cardiovascular disease risk reducing interventions at older age.