Diabetes genetic predisposition score and cardiovascular complications among patients with type 2 diabetes

Radiomics analysis of pericoronary adipose tissue based on plain CT for preliminary screening of coronary artery disease in patients with type 2 diabetes mellitus

BACKGROUND

Type 2 diabetes mellitus (T2DM) is associated with a markedly increased prevalence of coronary artery disease (CAD). Radiomics features of pericoronary adipose tissue (PCAT) were correlated with inflammation, which may have potential value in the prediction of CAD.

PURPOSE

To determine whether radiomics analysis of PCAT captured by plain computed tomography (CT) could predict obstructive CAD in patients with T2DM.

MATERIAL AND METHODS

The study included 155 patients with T2DM with suspected CAD between January 2020 and December 2021. Volumes of right coronary artery of 10-50 mm were delineated in the plain CT to extract radiomics features and PCAT CT attenuation (PCATa). Least absolute shrinkage and selection operator was used to select the useful radiomics features to calculate the radiomics score (Rad-score). Univariate and multivariable logistic regression were applied to select independent predictors. The predictive performance was evaluated by the area under the receiver operating characteristics curve (AUC).

RESULTS

Rad-score (per 0.1 increments: odds ratio [OR] = 1.297; P < 0.001), coronary artery calcium score (CACS) (OR = 1.003; P = 0.037), and sex (OR = 3.245; P = 0.026) were identified as independent predictors for obstructive CAD. Rad-score (AUC = 0.835) outperformed CACS (AUC = 0.780), sex (AUC = 0.665), and PCATa (AUC = 0.550) in predicting obstructive CAD (P = 0.017 and 0.003 for Rad-score vs. sex and PCATa, respectively); however, the improvement between Rad-score and CACS had no statistical significance (P = 0.490).

CONCLUSION

Plain CT-derived Rad-score may be used as a preliminary screening tool for obstructive CAD in patients with T2DM.

Non-contrast CT-based radiomics nomogram of pericoronary adipose tissue for predicting haemodynamically significant coronary stenosis in patients with type 2 diabetes

BACKGROUND

Type 2 diabetes mellitus (T2DM) patients have a higher incidence of coronary artery disease than the general population. The aim of this study was to develop a radiomics nomogram of pericoronary adipose tissue (PCAT) based on non-contrast CT to predict haemodynamically significant coronary stenosis in T2DM patients.

METHODS

The study enrolled 215 T2DM patients who underwent non-contrast CT and coronary computed tomography angiography (CCTA). CCTA derived fractional flow reserve (FFR_CT) ≤ 0.80 was defined as hemodynamically significant stenosis.1691 radiomics features were extracted from PCAT on non-contrast CT. Minimum redundancy maximum relevance (mRMR) and least absolute shrinkage and selection operator (LASSO) were used to select useful radiomics features to construct Radscore. Logistic regression was applied to select significant factors among Radscore, fat attenuation index (FAI) and coronary artery calcium score (CACS) to construct radiomics nomogram.

RESULTS

Radscore [odds ratio (OR) = 2.84; P < 0.001] and CACS (OR = 1.00; P = 0.023) were identified as independent predictors to construct the radiomics nomogram. The radiomics nomogram showed excellent performance [training cohort: area under the curve (AUC) = 0.81; 95% CI: 0.76-0.86; validation cohort: AUC = 0.83; 95%CI: 0.76-0.90] to predict haemodynamically significant coronary stenosis in patients with T2DM. Decision curve analysis demonstrated high clinical value of the radiomics nomogram.

CONCLUSION

The non-contrast CT-based radiomics nomogram of PCAT could effectively predict haemodynamically significant coronary stenosis in patients with T2DM, which might be a potential noninvasive tool for screening of high-risk patients.

Cardiovascular disease in diabetes, beyond glucose

Despite the decades-old knowledge that diabetes mellitus is a major risk factor for cardiovascular disease, the reasons for this association are only partially understood. While this association is true for both type 1 and type 2 diabetes, different pathophysiological processes may be responsible. Lipids and other risk factors are indeed important, whereas the role of glucose is less clear. This lack of clarity stems from clinical trials that do not unambiguously show that intensive glycemic control reduces cardiovascular events. Animal models have provided mechanisms that link diabetes to increased atherosclerosis, and evidence consistent with the importance of factors beyond hyperglycemia has emerged. We review clinical, pathological, and animal studies exploring the pathogenesis of atherosclerosis in humans living with diabetes and in mouse models of diabetes. An increased effort to identify risk factors beyond glucose is now needed to prevent the increased cardiovascular disease risk associated with diabetes.

A diabetes-associated genetic variant is associated with diastolic dysfunction and cardiovascular disease

Aims

Although the epidemiological association between Type 2 diabetes and congestive heart failure (CHF) as well as cardiovascular disease (CVD) is well established, associations between diabetes‐related single‐nucleotide polymorphisms (SNPs), CHF, and CVD have been surprisingly inconclusive. Our aim is to examine if 43 diabetes‐related SNPs were associated with prevalent diastolic dysfunction assessed by echocardiography and incident CVD and/or CHF.

Methods and results

We genotyped 43 SNPs that previously reported genome‐wide significant associations with Type 2 diabetes, in 1444 subjects from the population‐based Malmö Preventive Project‐Re‐examination Study (MPP‐RES) (mean age 68 years; 29% women, 36% prevalent diabetes) (discovery cohort) and in 996 subjects from the VARA cohort (mean age 51 years, 52% women, 7% prevalent diabetes) (replication cohort). Multivariable logistic regression was assessed. Genetic variants that reached significant association with diastolic dysfunction in both cohorts were then analysed for association with incident CVD/CHF in a larger sample of the MPP‐RES cohort (3,407 cases and 11,776 controls, median follow up >30 years) using Cox regression analysis. A common variant at the HNF1B [major allele (T) coded, also the risk allele for diabetes] was the only SNP associated with increased risk of prevalent diastolic dysfunction in both the discovery [MPP‐RES; odds ratio (OR) 1.21, P = 0.024), and the replication cohort (VARA; OR 1.38, P = 0.042]. Cox regression analysis showed that carriers of the T‐allele of rs757210 had an increased risk of future CVD (HR 1.05, P = 0.042). No significant association was seen for incident CHF.

Conclusions

The diabetes susceptibility locus HNF1B is associated with prevalent diastolic dysfunction in two independent Swedish cohorts as well as incident cardiovascular disease.

Coagulatory Defects in Type-1 and Type-2 Diabetes

Diabetes (both type-1 and type-2) affects millions of individuals worldwide. A major cause of death for individuals with diabetes is cardiovascular diseases, in part since both types of diabetes lead to physiological changes that affect haemostasis. Those changes include altered concentrations of coagulatory proteins, hyper-activation of platelets, changes in metal ion homeostasis, alterations in lipid metabolism (leading to lipotoxicity in the heart and atherosclerosis), the presence of pro-coagulatory microparticles and endothelial dysfunction. In this review, we explore the different mechanisms by which diabetes leads to an increased risk of developing coagulatory disorders and how this differs between type-1 and type-2 diabetes.

Genetic predisposition to type 2 diabetes is associated with severity of coronary artery disease in patients with acute coronary syndromes

Background

Accumulating evidence has shown that type 2 diabetes (T2D) and coronary artery disease (CAD) may stem from a ‘common soil’. The aim of our study was to examine the association between genetic predisposition to T2D and the risk of severe CAD among patients with acute coronary syndromes (ACS) undergoing angiography.

Methods

The current case–control study included 1414 ACS patients with at least one major epicardial vessel stenosis > 50% enrolled in the ACS Genetic Study. The severity of CAD was quantified by the number of coronary arteries involved. Genetic risk score (GRS) was calculated using 41 common variants that robustly associated with increased risk of T2D in East Asians. Logistic regression models were used to estimate the association between GRS and the severity of CAD.

Results

In the age-, sex- and BMI-adjusted model, each additional risk allele was associated with a 6% increased risk of multi-vessel disease (OR = 1.06, 95% CI 1.02–1.09). The OR was 1.43 (95% CI 1.08–1.89) for the risk of severe CAD when comparing the extreme tertiles of T2D-GRS. The association was not reduced after further adjustment for conventional cardiovascular risk factors. Additional adjustment for T2D status in our regression model attenuated the association by approximately one quarter. In subgroup analysis, the strengths of the associations between GRS and the severity of CAD were broadly similar in terms of baseline demographic information and disease characteristics.

Conclusions

Our data indicated that genetic predisposition to T2D is associated with elevated risk of severe CAD. This association revealed a possible causal relationship and is partially mediated through diabetic status.

Type 2 Diabetes Mellitus and Cardiovascular Disease: Genetic and Epigenetic Links

Type 2 diabetes mellitus (DM) is a common metabolic disorder predisposing to diabetic cardiomyopathy and atherosclerotic cardiovascular disease (CVD), which could lead to heart failure through a variety of mechanisms, including myocardial infarction and chronic pressure overload. Pathogenetic mechanisms, mainly linked to hyperglycemia and chronic sustained hyperinsulinemia, include changes in metabolic profiles, intracellular signaling pathways, energy production, redox status, increased susceptibility to ischemia, and extracellular matrix remodeling. The close relationship between type 2 DM and CVD has led to the common soil hypothesis, postulating that both conditions share common genetic and environmental factors influencing this association. However, although the common risk factors of both CVD and type 2 DM, such as obesity, insulin resistance, dyslipidemia, inflammation, and thrombophilia, can be identified in the majority of affected patients, less is known about how these factors influence both conditions, so that efforts are still needed for a more comprehensive understanding of this relationship. The genetic, epigenetic, and environmental backgrounds of both type 2 DM and CVD have been more recently studied and updated. However, the underlying pathogenetic mechanisms have seldom been investigated within the broader shared background, but rather studied in the specific context of type 2 DM or CVD, separately. As the precise pathophysiological links between type 2 DM and CVD are not entirely understood and many aspects still require elucidation, an integrated description of the genetic, epigenetic, and environmental influences involved in the concomitant development of both diseases is of paramount importance to shed new light on the interlinks between type 2 DM and CVD. This review addresses the current knowledge of overlapping genetic and epigenetic aspects in type 2 DM and CVD, including microRNAs and long non-coding RNAs, whose abnormal regulation has been implicated in both disease conditions, either etiologically or as cause for their progression. Understanding the links between these disorders may help to drive future research toward an integrated pathophysiological approach and to provide future directions in the field.

Plasma Taurine, Diabetes Genetic Predisposition, and Changes of Insulin Sensitivity in Response to Weight-Loss Diets

CONTEXT

Taurine metabolism disturbance is closely linked to obesity, insulin resistance, and diabetes. Previous evidence suggested that the preventative effects of taurine on diabetes might be through regulating the expression levels of diabetes-related genes.

OBJECTIVE

We estimated whether blood taurine levels modified the overall genetic susceptibility to diabetes on improvement of insulin sensitivity in a randomized dietary trial.

DESIGN AND SETTING

We genotyped 31 diabetes-associated variants to calculate a genetic risk score (GRS) and measured plasma taurine levels and glycemic traits among participants from the Preventing Overweight Using Novel Dietary Strategies (POUNDS Lost) trial.

PARTICIPANTS

Seven-hundred eleven overweight or obese participants (age 30-70 y; 60% females) had genetic variants genotyped and blood taurine levels measured.

INTERVENTION

Participants went on 2-year weight-loss diets, which were different in macronutrient composition.

MAIN OUTCOME MEASURE

Improvements in glycemic traits were measured.

RESULTS

We found that baseline taurine levels significantly modified the effects of diabetes GRS on changes in fasting glucose, insulin, and homeostatic model assessment of insulin resistance (HOMA-IR) during the 2-year diet intervention (P-interaction = .04, .01, .002, respectively), regardless of weight loss. High baseline taurine levels were associated with a less reduction in both glucose and HOMA-IR among the participants with the lowest tertile of diabetes GRS (both P = .02), and with a greater reduction in both insulin and HOMA-IR among those with the highest tertile of diabetes GRS (both P = .04).

CONCLUSIONS

Our data suggest that blood taurine levels might differentially modulate the effects of diabetes-related genes on improvement of insulin sensitivity among overweight/obese patients on weight-loss diets.

Genetic susceptibility to diabetes and long-term improvement of insulin resistance and β cell function during weight loss: the Preventing Overweight Using Novel Dietary Strategies (POUNDS LOST) trial

BACKGROUND

Diet interventions have shown effectiveness in improving diabetes risk factors; however, little is known about whether the effects of diet intervention are different according to genetic susceptibility.

OBJECTIVE

We examined interactions between weight-loss diets and the genetic risk score (GRS) for diabetes on 2-y changes in markers of insulin resistance and β cell function in a randomized controlled trial.

DESIGN

Data from the Preventing Overweight Using Novel Dietary Strategies (POUNDS LOST) trial were analyzed. A GRS was calculated on the basis of 31 diabetes-associated variants in 744 overweight or obese nondiabetic adults (80% white Americans). We assessed the changes in insulin resistance and β cell function over the 2-y intervention.

RESULTS

Dietary protein significantly interacted with the diabetes GRS on fasting insulin, glycated hemoglobin (HbA1c), the homeostasis model assessment of β cell function (HOMA-B), and the homeostasis model assessment of insulin resistance (HOMA-IR) at 2 y in white Americans (P-interaction = 0.02, 0.04, 0.01, and 0.05, respectively). The lower GRS was associated with a greater decrease in fasting insulin (P = 0.04), HbA1c (P = 0.0001), and HOMA-IR (P = 0.02), and a lesser increase in HOMA-B (P = 0.004) in participants consuming a low-protein diet. Participants with a higher GRS might have a greater reduction in fasting insulin when consuming a high-protein diet (P = 0.03).

CONCLUSIONS

Our data suggest that individuals with a lower genetic risk of diabetes may benefit more from consuming a low-protein weight-loss diet in improving insulin resistance and β cell function, whereas a high-protein diet may be more beneficial for white patients with a higher genetic risk. This trial was registered at clinicaltrials.gov as NCT00072995.

Association of a 62 Variants Type 2 Diabetes Genetic Risk Score With Markers of Subclinical Atherosclerosis: A Transethnic, Multicenter Study

BACKGROUND

Type 2 diabetes mellitus (T2D) and cardiovascular disease share risk factors and subclinical atherosclerosis (SCA) predicts events in those with and without diabetes mellitus. T2D genetic risk may predict both T2D and SCA. We hypothesized that greater T2D genetic risk is associated with higher extent of SCA.

METHODS AND RESULTS

In a cross-sectional analysis, including ≤9210 European Americans, 3773 African Americans, 1446 Hispanic Americans, and 773 Chinese Americans without known cardiovascular disease and enrolled in the Framingham Heart Study, Coronary Artery Risk Development in Young Adults, Multi-Ethnic Study of Atherosclerosis, and Genetic Epidemiology Network of Arteriopathy studies, we tested a 62 T2D-loci genetic risk score for association with measures of SCA, including coronary artery or abdominal aortic calcium score, common and internal carotid artery intima-media thickness, and ankle-brachial index. We used ancestry-stratified linear regression models, with random effects accounting for family relatedness when appropriate, applying a genetic-only (adjusted for sex) and a full SCA risk factors-adjusted model (significance, P<0.01=0.05/5, number of traits analyzed). An inverse association with coronary artery calcium score in Multi-Ethnic Study of Atherosclerosis Europeans (fully-adjusted P=0.004) and with common carotid artery intima-media thickness in the Framingham Heart Study (P=0.009) was not confirmed in other study cohorts, either separately or in meta-analysis. Secondary analyses showed no consistent associations with β-cell and insulin resistance genetic risk sub-scores in the Framingham Heart Study and in the Coronary Artery Risk Development in Young Adults.

CONCLUSIONS

SCA does not have a major genetic component linked to a burden of 62 T2D loci identified by large genome-wide association studies. A shared T2D-SCA genetic basis, if any, might become apparent from better functional information about both T2D and cardiovascular disease risk loci.

Insights into the genetic basis of type 2 diabetes

Type 2 diabetes is one of the most common complex diseases, of which considerable efforts have been made to unravel the pathophysiological mechanisms. Recently, large‐scale genome‐wide association (GWA) studies have successfully identified genetic loci robustly associated with type 2 diabetes by searching susceptibility variants across the entire genome in an unbiased, hypothesis‐free manner. The number of loci has climbed from just three in 2006 to approximately 70 today. For the common type 2 diabetes‐associated variants, three features have been noted. First, genetic impacts of individual variants are generally modest; mostly, allelic odds ratios range between 1.06 and 1.20. Second, most of the loci identified to date are not in or near obvious candidate genes, but some are often located in the intergenic regions. Third, although the number of loci is limited, there might be some population specificity in type 2 diabetes association. Although we can estimate a single or a few target genes for individual loci detected in GWA studies by referring to the data for experiments in vitro, biological function remains largely unknown for a substantial part of such target genes. Nevertheless, new biology is arising from GWA study discoveries; for example, genes implicated in β‐cell dysfunction are over‐represented within type 2 diabetes‐associated regions. Toward translational advances, we have just begun to face new challenges – elucidation of multifaceted (i.e., molecular, cellular and physiological) mechanistic insights into disease biology by considering interaction with the environment. The present review summarizes recent advances in the genetics of type 2 diabetes, together with its realistic potential.

Genetic risk score associations with cardiovascular disease and mortality in the Diabetes Heart Study

OBJECTIVE Given the high rates of cardiovascular disease (CVD) and associated mortality in individuals with type 2 diabetes, identifying and understanding predictors of CVD events and mortality could help inform clinical management in this high-risk group. Recent large-scale genetic studies may provide additional tools in this regard. RESEARCH DESIGN AND METHODS Genetic risk scores (GRSs) were constructed in 1,175 self-identified European American (EA) individuals comprising the family-based Diabetes Heart Study based on 1) 13 single nucleotide polymorphisms (SNPs) and 2) 30 SNPs with previously documented associations with CVD in genome-wide association studies. Associations between each GRS and a self-reported history of CVD, coronary artery calcified plaque (CAC) determined by noncontrast computed tomography scan, all-cause mortality, and CVD mortality were examined using marginal models with generalized estimating equations and Cox proportional hazards models. RESULTS The weighted 13-SNP GRS was associated with prior CVD (odds ratio [OR] 1.51 [95% CI 1.22-1.86]; P = 0.0002), CAC (β-coefficient [β] 0.22 [0.02-0.43]; P = 0.04) and CVD mortality (hazard ratio [HR] 1.35 [1.10-1.81]; P = 0.04) when adjusting for the other known CVD risk factors: age, sex, type 2 diabetes affection status, BMI, current smoking status, hypertension, and dyslipidemia. The weighted 30-SNP GRS was also associated with prior CVD (OR 1.33 [1.08-1.65]; P = 0.008), CAC (β 0.29 [0.08-0.50]; P = 0.006), all-cause mortality (HR 1.28 [1.05-1.56]; P = 0.01), and CVD mortality (HR 1.46 [1.08-1.96]; P = 0.01). CONCLUSIONS These findings support the utility of two simple GRSs in examining genetic associations for adverse outcomes in EAs with type 2 diabetes.

Genetic insights into cardiometabolic risk factors

Many biochemical traits are recognised as risk factors, which contribute to or predict the development of disease. Only a few are in widespread use, usually to assist with treatment decisions and motivate behavioural change. The greatest effort has gone into evaluation of risk factors for cardiovascular disease and/or diabetes, with substantial overlap as 'cardiometabolic' risk. Over the past few years many genome-wide association studies (GWAS) have sought to account for variation in risk factors, with the expectation that identifying relevant polymorphisms would improve our understanding or prediction of disease; others have taken the direct approach of genomic case-control studies for the corresponding diseases. Large GWAS have been published for coronary heart disease and Type 2 diabetes, and also for associated biomarkers or risk factors including body mass index, lipids, C-reactive protein, urate, liver function tests, glucose and insulin. Results are not encouraging for personal risk prediction based on genotyping, mainly because known risk loci only account for a small proportion of risk. Overlap of allelic associations between disease and marker, as found for low density lipoprotein cholesterol and heart disease, supports a causal association, but in other cases genetic studies have cast doubt on accepted risk factors. Some loci show unexpected effects on multiple markers or diseases. An intriguing feature of risk factors is the blurring of categories shown by the correlation between them and the genetic overlap between diseases previously thought of as distinct. GWAS can provide insight into relationships between risk factors, biomarkers and diseases, with potential for new approaches to disease classification.

Current Insights into the Joint Genetic Basis of Type 2 Diabetes and Coronary Heart Disease

The large-scale genome-wide association studies conducted so far identified numerous allelic variants associated with type 2 diabetes (T2D), coronary heart disease (CHD) and related cardiometabolic traits. Many T2D- and some CHD-risk loci are also linked with metabolic traits that are hallmarks of insulin resistance (lipid profile, abdominal adiposity). Chromosome 9p21.3 and 2q36.3 are the most consistently replicated loci appearing to share genetic risk for both T2D and CHD. Although many glucose- or insulin-related trait variants are also linked with T2D risk, none of them is associated with CHD. Hence, while T2D and CHD are strongly clinically linked together, further ongoing analyses are needed to clarify the existence of a shared underlying genetic signature of these complex traits. The present review summarizes an updated picture of T2D-CHD genetics as of 2013, aiming to provide a platform for targeted studies dissecting the contribution of genetics to the phenotypic heterogeneity of T2D and CHD.

Introduction to personalized medicine in diabetes mellitus

The world is facing an epidemic rise in diabetes mellitus (DM) incidence, which is challenging health funders, health systems, clinicians, and patients to understand and respond to a flood of research and knowledge. Evidence-based guidelines provide uniform management recommendations for "average" patients that rarely take into account individual variation in susceptibility to DM, to its complications, and responses to pharmacological and lifestyle interventions. Personalized medicine combines bioinformatics with genomic, proteomic, metabolomic, pharmacogenomic ("omics") and other new technologies to explore pathophysiology and to characterize more precisely an individual's risk for disease, as well as response to interventions. In this review we will introduce readers to personalized medicine as applied to DM, in particular the use of clinical, genetic, metabolic, and other markers of risk for DM and its chronic microvascular and macrovascular complications, as well as insights into variations in response to and tolerance of commonly used medications, dietary changes, and exercise. These advances in "omic" information and techniques also provide clues to potential pathophysiological mechanisms underlying DM and its complications.

Association between a genetic variant related to glutamic acid metabolism and coronary heart disease in individuals with type 2 diabetes

IMPORTANCE

Diabetes is associated with an elevated risk of coronary heart disease (CHD). Previous studies have suggested that the genetic factors predisposing to excess cardiovascular risk may be different in diabetic and nondiabetic individuals.

OBJECTIVE

To identify genetic determinants of CHD that are specific to patients with diabetes.

DESIGN, SETTING, AND PARTICIPANTS

We studied 5 independent sets of CHD cases and CHD-negative controls from the Nurses' Health Study (enrolled in 1976 and followed up through 2008), Health Professionals Follow-up Study (enrolled in 1986 and followed up through 2008), Joslin Heart Study (enrolled in 2001-2008), Gargano Heart Study (enrolled in 2001-2008), and Catanzaro Study (enrolled in 2004-2010). Included were a total of 1517 CHD cases and 2671 CHD-negative controls, all with type 2 diabetes. Results in diabetic patients were compared with those in 737 nondiabetic CHD cases and 1637 nondiabetic CHD-negative controls from the Nurses' Health Study and Health Professionals Follow-up Study cohorts. Exposures included 2,543,016 common genetic variants occurring throughout the genome.

MAIN OUTCOMES AND MEASURES

Coronary heart disease--defined as fatal or nonfatal myocardial infarction, coronary artery bypass grafting, percutaneous transluminal coronary angioplasty, or angiographic evidence of significant stenosis of the coronary arteries.

RESULTS

A variant on chromosome 1q25 (rs10911021) was consistently associated with CHD risk among diabetic participants, with risk allele frequencies of 0.733 in cases vs 0.679 in controls (odds ratio, 1.36 [95% CI, 1.22-1.51]; P = 2 × 10(-8)). No association between this variant and CHD was detected among nondiabetic participants, with risk allele frequencies of 0.697 in cases vs 0.696 in controls (odds ratio, 0.99 [95% CI, 0.87-1.13]; P = .89), consistent with a significant gene × diabetes interaction on CHD risk (P = 2 × 10(-4)). Compared with protective allele homozygotes, rs10911021 risk allele homozygotes were characterized by a 32% decrease in the expression of the neighboring glutamate-ammonia ligase (GLUL) gene in human endothelial cells (P = .0048). A decreased ratio between plasma levels of γ-glutamyl cycle intermediates pyroglutamic and glutamic acid was also shown in risk allele homozygotes (P = .029).

CONCLUSION AND RELEVANCE

A single-nucleotide polymorphism (rs10911021) was identified that was significantly associated with CHD among persons with diabetes but not in those without diabetes and was functionally related to glutamic acid metabolism, suggesting a mechanistic link.