Diabetes has become a major burden of healthcare expenditure. Diabetes management following a uniform treatment algorithm is often associated with progressive treatment failure and development of ...diabetic complications. Recent advances in our understanding of the genomic architecture of diabetes and its complications have provided the framework for development of precision medicine to personalize diabetes prevention and management. In the present review, we summarized recent advances in the understanding of the genetic basis of diabetes and its complications. From a clinician's perspective, we attempted to provide a balanced perspective on the utility of genomic medicine in the field of diabetes. Using genetic information to guide management of monogenic forms of diabetes represents the best‐known examples of genomic medicine for diabetes. Although major strides have been made in genetic research for diabetes, its complications and pharmacogenetics, ongoing efforts are required to translate these findings into practice by incorporating genetic information into a risk prediction model for prioritization of treatment strategies, as well as using multi‐omic analyses to discover novel drug targets with companion diagnostics. Further research is also required to ensure the appropriate use of this information to empower individuals and healthcare professionals to make personalized decisions for achieving the optimal outcome.
Diabetes management following a uniform treatment algorithm is often associated with progressive treatment failure and development of diabetic complications. Recent advances in our understanding in the genomic architecture of diabetes and its complications have provided the framework for development of precision medicine to personalize diabetes prevention and management. In this review, we summarized recent advances in the understanding of the genetic basis of diabetes and its complications and how this can aid clinical management.
Diabetes is a major cause of end stage renal disease (ESRD), yet the natural history of diabetic kidney disease is not well understood. We aimed to identify patterns of estimated GFR (eGFR) ...trajectory and to determine the clinical and genetic factors and their associations of these different patterns with all-cause mortality in patients with type 2 diabetes. Among 6330 patients with baseline eGFR >60 ml/min per 1.73 m2 in the Hong Kong Diabetes Register, a total of 456 patients (7.2%) developed Stage 5 chronic kidney disease or ESRD over a median follow-up of 13 years (incidence rate 5.6 per 1000 person-years). Joint latent class modeling was used to identify different patterns of eGFR trajectory. Four distinct and non-linear trajectories of eGFR were identified: slow decline (84.3% of patients), curvilinear decline (6.5%), progressive decline (6.1%) and accelerated decline (3.1%). Microalbuminuria and retinopathy were associated with accelerated eGFR decline, which was itself associated with all-cause mortality (odds ratio OR 6.9; 95% confidence interval CI: 5.6–8.4 for comparison with slow eGFR decline). Of 68 candidate genetic loci evaluated, the inclusion of five loci (rs11803049, rs911119, rs1933182, rs11123170, and rs889472) improved the prediction of eGFR trajectories (net reclassification improvement 0.232; 95% CI: 0.057-–0.406). Our study highlights substantial heterogeneity in the patterns of eGFR decline among patients with diabetic kidney disease, and identifies associated clinical and genetic factors that may help to identify those who are more likely to experience an accelerated decline in kidney function.
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•53 essential oils (EOs) as larvicides and synergists with deltamethrin were screened.•Main components of 9 active EOs were analyzed by GC–MS.•F. vulgare EO has the highest larvicidal ...activity with LC50 value of 27.5 ppm.•C. sinensis EO shows more synergy with deltamethrin against adults than PBO.•Relationship between chemical components and anti-mosquito activity was discussed.
Although the extensive use of synthetic insecticides to control mosquito vectors have gained significant success, meanwhile resulted in various problems, such as increase in insecticide-resistant mosquitoes, environmental pollution, and health threat to human beings. Hence, there is an urgent need for alternative insecticides and effective synergists to combine with existing insecticides, which are safe to public health and environment. In this work, the larvicidal activity of 53 commercial essential oils (EOs) and their synergistic effect with deltamethrin against Aedes albopictus adults were screened, then the main constituents of active EOs were analyzed by GC–MS. The most potent EOs against the larvae are from Foeniculum vulgare (fennel), Thymus vulgaris (thyme), Citrus medica (lime), and Camellia sinensis (green tea) with LC50 values of 27.5, 31.6, 51.3, 53.5 ppm, respectively. The most efficient EOs enhancing the efficacy of deltamethrin are C. sinensis (green tea), the co-toxic factor is 316.67, which is more than the positive control PBO (co-toxic factor = 283.35). It suggests that there is significant potential of natural EOs in the application of mosquito control as larvicides or synergists for enhancing efficacy of current adulticides.
Nonalbuminuric diabetic kidney disease (DKD) has become the prevailing DKD phenotype. We compared the risks of adverse outcomes among patients with this phenotype compared with other DKD phenotypes.
...Multicenter prospective cohort study.
19,025 Chinese adults with type 2 diabetes enrolled in the Hong Kong Diabetes Biobank.
DKD phenotypes defined by baseline estimated glomerular filtration rate (eGFR) and albuminuria: no DKD (no decreased eGFR or albuminuria), albuminuria without decreased eGFR, decreased eGFR without albuminuria, and albuminuria with decreased eGFR.
All-cause mortality, cardiovascular disease (CVD) events, hospitalization for heart failure (HF), and chronic kidney disease (CKD) progression (incident kidney failure or sustained eGFR reduction ≥40%).
Multivariable Cox proportional or cause-specific hazards models to estimate the relative risks of death, CVD, hospitalization for HF, and CKD progression. Multiple imputation was used for missing covariates.
Mean participant age was 61.1 years, 58.3% were male, and mean diabetes duration was 11.1 years. During 54,260 person-years of follow-up, 438 deaths, 1,076 CVD events, 298 hospitalizations for HF, and 1,161 episodes of CKD progression occurred. Compared with the no-DKD subgroup, the subgroup with decreased eGFR without albuminuria had higher risks of all-cause mortality (hazard ratio HR, 1.59 95% CI, 1.04-2.44), hospitalization for HF (HR, 3.08 95% CI, 1.82-5.21), and CKD progression (HR, 2.37 95% CI, 1.63-3.43), but the risk of CVD was not significantly greater (HR, 1.14 95% CI, 0.88-1.48). The risks of death, CVD, hospitalization for HF, and CKD progression were higher in the setting of albuminuria with or without decreased eGFR. A sensitivity analysis that excluded participants with baseline eGFR <30 mL/min/1.73 m2 yielded similar findings.
Potential misclassification because of drug use.
Nonalbuminuric DKD was associated with higher risks of hospitalization for HF and of CKD progression than no DKD, regardless of baseline eGFR.
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•In a randomized clinical trial, providing personalized risk prediction based on genetic markers of diabetic kidney disease on top of standard integrated care (including risk prediction based on ...clinical risk factors) led to improvement in target attainment, with no difference between the two groups.•Subjects who received genetic counselling had higher diabetes empowerment, with improved positive attitude and reduced diabetes distress.•Subjects with high GRS had the highest increments in attaining multiple treatment targets accompanied by improvement in self-management.•Future studies on the implementation of precision medicine in diabetes need to include assessment of patient reported outcomes, as well as evaluate how best to communicate risk to patients to improve patient empowerment and long-term outcome.
We evaluated the effect of personalized risk counseling incorporating clinical and genetic risk factors on patient empowerment and risk factor control in diabetes.
Patients with type 2 diabetes (T2D) with suboptimal glycaemic control (HbA1c ≥ 7.5%) were randomized to a genetic counselling (GC) or control group. All patients underwent genetic testing for alleles at three loci associated with diabetic complications. The GC group received additional explanation of the joint associations of genetic and modifiable risk factors on risk of complications. All patients were reassessed at 12 months including validated questionnaires for patient reported outcomes. The primary outcome was proportion of patients reaching ≥ 3 of 5 predefined treatment targets (HbA1c < 7%, BP < 130/80 mmHg, LDL-C < 2.6 mmol/L, Triglyceride < 2.0 mmol/L, use of renin-angiotensin system inhibitors). Secondary outcomes included new-onset chronic kidney disease or microalbuminuria and patient reported outcome measures.
A total of 435 patients were randomized and 420 patients were included in the modified intention-to-treat analysis. At 12 months, the proportion of patients who attained ≥ 3 targets increased from 41.6% to 52.3% in the GC group (p = 0.007) versus 49.5% to 62.6% in the control group (p = 0.003), without between-group difference. Both groups had similar reduction in HbA1c, LDL-C and increased use of medications. In per protocol analysis, the GC group had higher diabetes empowerment, with reduced diabetes distress. In the GC group, the greatest improvement in positive attitude and self-care activities was observed in the intermediate to high genetic risk score (GRS) groups.
In patients with T2D receiving integrated care, additional counselling on genetic risk of complications did not further improve risk factor control, although the improvement in self-efficacy warrants long-term evaluation.
In this study we aim to unravel genetic determinants of coronary heart disease (CHD) in type 2 diabetes (T2D) and explore their applications.
We performed a two-stage genome-wide association study ...for CHD in Chinese patients with T2D (3,596 case and 8,898 control subjects), followed by replications in European patients with T2D (764 case and 4,276 control subjects) and general populations (n = 51,442-547,261). Each identified variant was examined for its association with a wide range of phenotypes and its interactions with glycemic, blood pressure (BP), and lipid controls in incident cardiovascular diseases.
We identified a novel variant (rs10171703) for CHD (odds ratio 1.21 95% CI 1.13-1.30; P = 2.4 × 10-8) and BP (β ± SE 0.130 ± 0.017; P = 4.1 × 10-14) at PDE1A in Chinese T2D patients but found only a modest association with CHD in general populations. This variant modulated the effects of BP goal attainment (130/80 mmHg) on CHD (Pinteraction = 0.0155) and myocardial infarction (MI) (Pinteraction = 5.1 × 10-4). Patients with CC genotype of rs10171703 had >40% reduction in either cardiovascular events in response to BP control (2.9 × 10-8 < P < 3.6 × 10-5), those with CT genotype had no difference (0.0726 < P < 0.2614), and those with TT genotype had a threefold increase in MI risk (P = 6.7 × 10-3).
We discovered a novel CHD- and BP-related variant at PDE1A that interacted with BP goal attainment with divergent effects on CHD risk in Chinese patients with T2D. Incorporating this information may facilitate individualized treatment strategies for precision care in diabetes, only when our findings are validated.
Type 1 diabetes, type 2 diabetes, gestational diabetes and diabetic complications are complex diseases that involve interactions between environmental and genetic factors for disease onset and ...progression. With advances in genetic research, there has been a rapid increase in the list of genetic risk variants identified to be associated with diabetes and diabetic complications. These discoveries have provided potential of using genetic information to guide precision medicine in individuals with diabetes. These important findings also provide better understanding for disease etiology and may serve as novel treatment targets. Identification of mutations accountable for Mendelian forms of monogenic diabetes can facilitate precise diagnoses and optimization of treatment of these rare forms of diabetes. Use of genetic testing has been shown to be particularly important for the management of monogenic diabetes. In addition, recent findings in the area of pharmacogenetics have also highlighted how genetic variants can influence an individual's response to medications, including oral glucose-lowering drugs. We review recent related publications and summarize the current state of knowledge regarding the genetics of diabetes and diabetic complications, and provide a perspective on the use of genetic testing to guide precision medicine for the prediction, prevention, pharmacogenetics and management of diabetes and diabetic complications. Complex care protocols hinder patients with diabetes from achieving control of cardio-metabolic risk factors. Despite accumulating knowledge on genetics of diabetes and its complications, it remains unknown whether genetic testing and counselling would affect self-efficacy and cardio-metabolic control in patients with type 2 diabetes (T2D). We conducted a randomized clinical trial to address this knowledge gap. Between 2015 and 2017, we randomized eligible patients with T2D patients with age range of 40-75 years and suboptimal glycemic control (HbA1c>7.5%) and without overt clinical complications into two groups, a genetic counseling group (GC) and a control group. All patients underwent genetic testing for alleles at three risk loci related to diabetic complications (ACE I/D polymorphism, aldose reductase (CA)n polymorphism, PRKCB1 rs3760106 polymorphism), from which an aggregated genetic risk score was calculated. Both groups received standard medical care while the GC group received additional genetic counseling, incorporating education on the management of traditional risk factors. The structured personalized risk counseling was based on an established genetic counseling framework for common polygenic disorders, and was designed to enable the participants to understand the interaction between genetic and modifiable risks. At baseline and study end, all participants underwent comprehensive diabetes-related assessment and questionnaire survey, using scales of EQ-5D, PHQ-9, CCQ-4, DDS-17C, DES-20, SDSCA-15 and PPC-9. We recruited 435 patients with type 2 diabetes mellitus (DM) who received integrated care including comprehensive assessment, issue of a personalized report based on clinical risk profiles and attained treated targets together with group education. The primary composite end-point was the proportion of patients who achieved at least three out of the pre-defined treatment targets: 1) BP<130/80 mmHg; 2) HbA1c <7%; 3) LDLC <2.6 mmol/l; 4) TG <2mmol/l; 5) Usage of ACEI/ARB medicine. The secondary composite outcome included: 1) incident CKD (defined as eGFR<60ml/min/1.73m 2 ); 2) microalbuminuria 3) patients self-empowerment as measured on questionnaire of DES-20; 4) self-management as measured on questionnaire of SDSCA-17. A total of 420 patients were included in the modified intention-to-treat analysis (214 in GC group, mean age 58.5±8.0, mean DM duration 12.7±7.1 years), excluding 15 subsequently due to pre-existing exclusion criteria. Among subjects in the GC arm, a total of 186 completed the study and were eligible for the per-protocol analysis, whereas another 28 defaulted the genetic counseling session and had the genetic testing results sent to them, with last-observation brought forward for laboratory results to define outcome. At baseline, there was no between-group difference in risk factor target attainment and diabetic complications of microalbuminuria or chronic kidney disease (CKD). At 12-months, the proportion of participants who attained ≥3 targets increased from 42% to 53% for the GC group versus 49% to 62% for the control group, without significant between-group difference. The GC group tended to have a lower total diabetes-related distress (DDS) score and a significantly higher total score of diabetes empowerment scale (DES) than the control group at the end of study. There was a tendency for interaction between genetic risk and response to treatment, but this didn't reach statistical significance. In patients with T2D receiving integrated care including a personalized risk report based on clinical profiles, additional individualized counseling on genetic risk of complications did not further improve risk factor control. However, genetic counseling significantly improved efficacy in patients with T2D and its long-term effects warrants further investigation.
BackgroundMultiple barriers and the complex nature of diabetes hinder patients from achieving control of cardio-metabolic risk factors. Empowerment is a key component in improving self-care to attain ...treatment targets. The discovery of diabetes-associated genetic factors underpins the concept of precision medicine although patient empowerment remains a key factor. Despite accumulating knowledge on genetics of diabetes and its complications, it remains unknown whether genetic testing and counselling would affect self-efficacy and cardio-metabolic control in patients with type 2 diabetes (T2D).AimWe conducted this trial to address this knowledge gap.MethodWe conducted a randomized clinical trial whereby T2D patients aged 40-75 with moderate risks of incident endpoints were recruited and randomized into two groups, a genetic counseling group (GC) and a control group. All patients underwent genetic testing for alleles at three risk loci related to diabetic complications, from which an aggregated genetic risk score was calculated. Control group received standardized medical care (including a risk report based on clinical risk factors), whereas GC group received additional genetic counseling, incorporating education on the management of traditional risk factors. The structured personalized risk counseling was based on an established genetic counseling framework for common polygenic genetic disorders, and was designed to convey risk information and helping the individual to understand that risk. Clinical measurements, laboratory tests and questionnaire surveys were collected at baseline and after one-year to assess risk control and disease efficacy using the Diabetes Empowerment Scale (DES-20) and Diabetes Distress Scale (DDS-17). The genetic information was disclosed to the control group at the end of the study period. The primary endpoint was percentage of subjects reaching at least 3 out of 5 of the following treatment targets: i) BP<130/80mmHg, ii) HbA1C<7.0%, iii) LDL-C<2.6mmol/L, iv) TG<2.0mmol/L and v) prescription of ACEI/RAS inhibitors. Secondary outcomes included new-onset CKD or microalbuminuria, patient empowerment, patient behaviour and diabetes-related distress.ResultsWe recruited 435 patients into the trial, though 15 had to be excluded subsequently due to pre-existing exclusion criteria. A total of 420 patients were included in the modified intention-to-treat analysis (214 in GC group, mean age 58.5u00b18.0, mean DM duration 12.7u00b17.1 years). Among subjects in the GC arm, a total of 186 completed the study and were eligible for the per-protocol analysis, whereas another 28 defaulted the genetic counseling session and had the genetic testing results sent to them. For those who defaulted one-year assessment, we use the method of last-observation brought forward for laboratory results to define outcome.At the end of the 12-month study period, there was improvement in the percentage of patients from both arms which reach 3 out of 5 of the treatment targets(on-target rate increase: 11.2% for GC vs.13.6% for control). The proportions of patients who did not attained 3 of 5 treatment targets at baseline but attained post-trial was similar in both groups (20.8% for GC vs. 23.8% for control, P>0.05). There was no significant difference in the secondary outcome of microalbuminuria, or new onset CKD. Compared with the control group, subjects in the GC group had lower total DDS score (36.3u00b112.2 for GC vs. 38.8u00b113.0 for control), but the difference was not statistically significant. A significant increase in total DES score was observed in GC group (57.7u00b111.0 for GC vs. 55.1u00b111.8 for control, P<0.05), especially in scores of three sub-dimensions, achieving diabetes goal (2.98u00b10.68 for GC vs. 2.82u00b10.72for control, P<0.05), overcoming barriers score changes (0.15u00b10.78 for GC vs. (-0.07)u00b10.73 for control, P<0.05) and determining methods (2.88u00b10.65 for GC vs. 2.74u00b10.70 for control, P<0.05). There was some evidence of interaction between underlying genetic risk and response to treatment.DiscussionProviding individualized genetic counseling on genetic risk of future complications did not impact significantly on risk factor control after 12 months. The lack of benefit associated with genetic testing may be due to the complexity of disease management and the relative short follow-up time (only one year). Genetic counseling significantly improved efficacy in patients with T2D. The impact of genetic testing and counseling as a personalized tool to improve patientsu2019 efficacy over a longer-term warrants further investigations in future studies.
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