Diagnosis and treatment of type 1 diabetes at the dawn of the personalized medicine era.

Type 1 diabetes affects millions of people globally and requires careful management to avoid serious long-term complications, including heart and kidney disease, stroke, and loss of sight. The type 1 diabetes patient cohort is highly heterogeneous, with individuals presenting with disease at different stages and severities, arising from distinct etiologies, and overlaying varied genetic backgrounds. At present, the "one-size-fits-all" treatment for type 1 diabetes is exogenic insulin substitution therapy, but this approach fails to achieve optimal blood glucose control in many individuals. With advances in our understanding of early-stage diabetes development, diabetes stratification, and the role of genetics, type 1 diabetes is a promising candidate for a personalized medicine approach, which aims to apply "the right therapy at the right time, to the right patient". In the case of type 1 diabetes, great efforts are now being focused on risk stratification for diabetes development to enable pre-clinical detection, and the application of treatments such as gene therapy, to prevent pancreatic destruction in a sub-set of patients. Alongside this, breakthroughs in stem cell therapies hold great promise for the regeneration of pancreatic tissues in some individuals. Here we review the recent initiatives in the field of personalized medicine for type 1 diabetes, including the latest discoveries in stem cell and gene therapy for the disease, and current obstacles that must be overcome before the dream of personalized medicine for all type 1 diabetes patients can be realized.

Polygenic Risk Scores in Coronary Artery Disease and Atrial Fibrillation.

Coronary artery disease (CAD) and atrial fibrillation (AF) are two highly prevalent cardiovascular disorders that are associated with substantial morbidity and mortality. Conventional clinical risk factors for these disorders may not be identified prior to mid-adult life when pathophysiological processes are already established. A better understanding of the genetic underpinnings of disease should facilitate early detection of individuals at risk and preventative intervention. Single rare variants of large effect size that are causative for CAD, AF, or predisposing factors such as hypertension or hyperlipidaemia, may give rise to familial forms of disease. However, in most individuals, CAD and AF are complex traits in which combinations of genetic and acquired factors play a role. Common genetic variants that affect disease susceptibility have been identified by genome-wide association studies, but the predictive value of any single variant is limited. To address this issue, polygenic risk scores (PRS), comprised of suites of disease-associated common variants have been devised. In CAD and AF, incorporation of PRS into risk stratification algorithms has provided incremental prognostic information to clinical factors alone. The long-term health and economic benefits of PRS-guided clinical management remain to be determined however, and further evidence-based data are required.

Genomic prediction of coronary heart disease.

AIMS: Genetics plays an important role in coronary heart disease (CHD) but the clinical utility of genomic risk scores (GRSs) relative to clinical risk scores, such as the Framingham Risk Score (FRS), is unclear. Our aim was to construct and externally validate a CHD GRS, in terms of lifetime CHD risk and relative to traditional clinical risk scores. METHODS AND RESULTS: We generated a GRS of 49 310 SNPs based on a CARDIoGRAMplusC4D Consortium meta-analysis of CHD, then independently tested it using five prospective population cohorts (three FINRISK cohorts, combined n = 12 676, 757 incident CHD events; two Framingham Heart Study cohorts (FHS), combined n = 3406, 587 incident CHD events). The GRS was associated with incident CHD (FINRISK HR = 1.74, 95% confidence interval (CI) 1.61-1.86 per S.D. of GRS; Framingham HR = 1.28, 95% CI 1.18-1.38), and was largely unchanged by adjustment for known risk factors, including family history. Integration of the GRS with the FRS or ACC/AHA13 scores improved the 10 years risk prediction (meta-analysis C-index: +1.5-1.6%, P < 0.001), particularly for individuals ≥60 years old (meta-analysis C-index: +4.6-5.1%, P < 0.001). Importantly, the GRS captured substantially different trajectories of absolute risk, with men in the top 20% of attaining 10% cumulative CHD risk 12-18 y earlier than those in the bottom 20%. High genomic risk was partially compensated for by low systolic blood pressure, low cholesterol level, and non-smoking. CONCLUSIONS: A GRS based on a large number of SNPs improves CHD risk prediction and encodes different trajectories of lifetime risk not captured by traditional clinical risk scores.

Genetics of Atrial Fibrillation: State of the Art in 2017.

Genetic variation is an important determinant of atrial fibrillation (AF) susceptibility. Numerous rare variants in protein-coding sequences of genes have been associated with AF in families and in early-onset cases, and chromosomal loci harbouring common risk variants have been mapped in AF cohorts. Many of these loci are in non-coding regions of the human genome and are thought to contain regulatory sequences that modulate gene expression. Disease genes implicated to date have predominantly encoded cardiac ion channels, with predicted mutation effects on the atrial action potential duration. More recent studies have expanded the spectrum of disease-associated genes to include myocardial structural components and have highlighted an unsuspected role for cardiac transcription factors. These paradigm-shifting discoveries suggest that abnormalities of atrial specification arising during cardiac development might provide a template for AF in later adult life. With the escalating pace of variant discovery, there is an increasing need for mechanistic studies not only to evaluate single variants, but also to determine the collective effects of each person's burden of rare and common genetic variants, co-morbidities and lifestyle factors on the atrial substrate for arrhythmogenesis. Elucidation of an individual's genetic predisposition and modifiable environmental risk factors will facilitate personalised approaches to AF treatment.

Barriers to gBRCA Testing in High-Risk HER2-Negative Early Breast Cancer.

Despite the OlympiA trial demonstrating that early-stage, high-risk, HER2- germline BRCA1 and BRCA2 mutation (gBRCAm) positive breast cancer patients can benefit from PARPi in the adjuvant setting, the gBRCA testing rate in early-stage HR+/HER2- patients remains suboptimal compared to that in early-stage TNBC patients. To better understand the perceived barriers associated with gBRCA testing in HR+/HER2- disease, a quantitative survey was conducted across stakeholders (n = 430) including medical oncologists, surgeons, nurses, physician assistants, payers, and patients. This study revealed that while payers claim to cover gBRCA testing, poor clinician documentation and overutilization are key challenges. Therefore, payers place utilization management controls on gBRCA testing due to their impression that clinicians overtest. These controls have led to healthcare professionals experiencing payer pushback in the form of reimbursement limitations and denials. The perceived challenges to gBRCA testing stem from the lack of consensus dictating which patients are high risk and should be tested. While payers define high risk based on the CPS + EG score from the OlympiA trial, HCPs adopt a broader definition including genomic risk scores, lymph node involvement, and tumor grade and size. A dialogue to harmonize risk classification and testing eligibility across stakeholders is critical to address this disconnect and increase gBRCA testing in appropriate patients.

Relationship between genomic risk scores (GRS) and coronary artery calcium (CAC) score: A pilot study.

BACKGROUND: Coronary artery disease (CAD) genomic risk scores (GRS), as FDR202, GRS46K, 1.7M, and MetaGRS, help in assessing cardiovascular related morbidity and mortality. Interventions to adhere to a healthy lifestyle as a means of prevention based on the GRS have a potential to greatly reduce incident CAD event rates. We performed a prospective observational study to see the relationship between GRS and coronary artery calcium (CAC) scoring in individuals who are at risk. METHODS: 104 subjects with mean age 55.1 ± 8.8 years were enrolled and consented and all the participants underwent CAC scoring. 55 (53%) were male. CAC score was measured using the Agatston method. Spearman correlation analysis assessed relationships between GRS scores and CAC scores, in the entire sample and in subjects with CAC score greater than zero. Multivariable linear regression analyzed associations while adjusting potential confounding variables. RESULTS: Mean ± SD CAC score of the study population was 49.0 ± 130. A significant negative correlation was noted between FDR202 Prevalence and total CAC Score in 39 subjects with CAC >0, r = -0.35, p = 0.02. Multivariable analysis shows a significant association between FDR202 prevalence and log adjusted CAC score in subjects with CAC >0 while adjusting age, gender, hypertension and hyperlipidemia (ß = -0.2, SE = 0.1, p = 0.04). No significant correlations were found between GRS46K, 1.7M, and MetaGRS with CAC score. CONCLUSION: Additional research is necessary in a larger population to evaluate the potential role of GRS for the detection of CAD. This allows the individuals to adopt a healthy lifestyle modification to minimize the cardiovascular risk and delays the onset of most diseases of old age to prolong the life.

Cardiovascular Precision Medicine in the Genomics Era.

Precision medicine strives to delineate disease using multiple data sources-from genomics to digital health metrics-in order to be more precise and accurate in our diagnoses, definitions, and treatments of disease subtypes. By defining disease at a deeper level, we can treat patients based on an understanding of the molecular underpinnings of their presentations, rather than grouping patients into broad categories with one-size-fits-all treatments. In this review, the authors examine how precision medicine, specifically that surrounding genetic testing and genetic therapeutics, has begun to make strides in both common and rare cardiovascular diseases in the clinic and the laboratory, and how these advances are beginning to enable us to more effectively define risk, diagnose disease, and deliver therapeutics for each individual patient.