448 hot topic(s) found with the query "Diabetes"
Multi-ancestry polygenic mechanisms of type 2 diabetes
K Smith et al, Nature Medicine, March 6, 2024
(Posted: Mar 06, 2024 9AM)
From the abstract: "Type 2 diabetes (T2D) is a multifactorial disease with substantial genetic risk, for which the underlying biological mechanisms are not fully understood. In this study, we identified multi-ancestry T2D genetic clusters by analyzing genetic data from diverse populations in 37 published T2D genome-wide association studies representing more than 1.4 million individuals. We implemented soft clustering with 650 T2D-associated genetic variants and 110 T2D-related traits, capturing known and novel T2D clusters with distinct cardiometabolic trait associations across two independent biobanks. "
Ambitious survey of human diversity yields millions of undiscovered genetic variants Analysis of the ‘All of Us’ genomic data set begins to tackle inequities in genetics research.
M Koslov, Nature, February 19, 2024
(Posted: Feb 20, 2024 7AM)
From the abstract: "A massive US programme that aims to improve health care by focusing on the genomes and health profiles of historically underrepresented groups has begun to yield results. Analyses of up to 245,000 genomes gathered by the All of Us programme, run by the US National Institutes of Health in Bethesda, Maryland, have uncovered more than 275 million new genetic markers, nearly 150 of which might contribute to type 2 diabetes. The work has also identified gaps in genetics research on non-white populations. The findings were published on 19 February in a package of papers "
AI-based diabetes care: risk prediction models and implementation concerns
SCY Wang et al, NPJ Digital Medicine, February 15, 2024
(Posted: Feb 16, 2024 4PM)
From the abstract: " The utilization of artificial intelligence (AI) in diabetes care has focused on early intervention and treatment management. Notably, usage has expanded to predict an individual’s risk for developing type 2 diabetes. A scoping review shows that while most studies used unimodal AI models, multimodal approaches were superior because they integrate multiple types of data. However, creating multimodal models and determining model performance are challenging tasks given the multi-factored nature of diabetes. For both unimodal and multimodal models, there are also concerns of bias with the lack of external validations and representation of race, age, and gender in training data."
Precision prognostics for cardiovascular disease in Type 2 diabetes: a systematic review and meta-analysis
A Ahmad et al, Com Med January 22, 2024
(Posted: Jan 22, 2024 8AM)
From the abstract: " We conducted a systematic review and meta-analysis of longitudinal studies to identify potentially novel prognostic factors that may improve CVD risk prediction in T2D. Out of 9380 studies identified, 416 studies met inclusion criteria. Outcomes were reported for 321 biomarker studies, 48 genetic marker studies, and 47 risk score/model studies."
Mediating Factors in the Association of Maternal Educational Level With Pregnancy Outcomes: A Mendelian Randomization Study.
Tormod Rogne et al. JAMA Netw Open 2024 1 (1) e2351166
(Posted: Jan 12, 2024 6AM)
From the abstract: " Which pathways mediate the inequity in pregnancy health associated with low educational attainment? In this cohort study of more than 3 million individuals, an association between genetically estimated lower educational attainment and increased risk of ectopic pregnancy, hyperemesis gravidarum, gestational diabetes, preeclampsia, preterm birth, and offspring low birth weight was observed. A sizeable portion of these associations were explained by targetable risk factors. These findings suggest that the association of socioeconomic inequalities with adverse pregnancy outcomes may be reduced by intervening for type 2 diabetes, body mass index, smoking, high-density lipoprotein cholesterol level, and systolic blood pressure."
What Is Prediabetes?
J Jin, JAMA Patient Corner, December 1, 2023
(Posted: Dec 02, 2023 9AM)
From the article: " Prediabetes affects approximately 1 in 3 US adults and about 720 million individuals worldwide. People with prediabetes often have no symptoms, so most people with prediabetes do not know they have it. Risk Factors for Prediabetes include: Being older than 45 years; Being overweight or obese; Being physically active less than 3 times a week; Eating an unhealthy diet; Having a parent or sibling with type 2 diabetes; Having a history of diabetes during pregnancy (gestational diabetes) or giving birth to an infant weighing more than 9 pounds; Having polycystic ovary syndrome."
Digital Technology for Diabetes
MS Hughes et al, NEJM, November 29, 2023
(Posted: Nov 30, 2023 9AM)
From the article: "It is not unreasonable to forecast that developments in diabetes technology will continue to improve glycemic control while decreasing the burdens for patients in managing diabetes. If widely adopted, these types of technology have the potential to improve the lives of both patients with type 1, type 2, and other forms of diabetes. The onus lies with the medical profession to help achieve greater and more equitable use of these methods. "
Including diverse populations enhances the discovery of type 2 diabetes loci
S Fatumo, Nat Rev Genetics, November 22, 2023
(Posted: Nov 22, 2023 9AM)
From the paper: "A recent multi-ancestry GWAS meta-analysis greatly advances our understanding of the genetic basis of T2D by encompassing a broad range of populations. The insights gained from this research provide a foundation for future functional investigations, therapeutic development and the translation of GWAS findings to improve global health outcomes for all, regardless of genetic background. "
Association Between a First-Degree Family History and Self-Reported Personal History of Obesity, Diabetes, and Heart and Blood Conditions: Results From the All of Us Research Program.
Danielle Rasooly et al. J Am Heart Assoc 2023 11 e030779
(Posted: Nov 13, 2023 8PM)
From the abstract: "We assessed the association between a self-reported family history of ODHBs and their risk in the adult population (age =20 years) of the AoU (All of Us) Research Program, a longitudinal cohort study of diverse participants across the United States. We conducted a family history-wide association study to systematically assess the association of a first-degree family history of 15 ODHBs in AoU. We use the FamWAS method to estimate 225 familial associations among 15 ODHBs. The results include overlapping associations between family history of different types of cardiometabolic conditions (such as type 2 diabetes and coronary artery disease), and their risk factors (obesity, hypertension), where adults with a family history of 1 ODHB exhibited 1.1 to 5.6 times (1.5, on average) the odds of having a different ODHB. "
Digital lifestyle treatment improves long-term metabolic control in type 2 diabetes with different effects in pathophysiological and genetic subgroups.
Vishal A Salunkhe et al. NPJ Digit Med 2023 10 (1) 199
(Posted: Oct 30, 2023 9AM)
From the abstract: "To address the unmet need for scalable solutions for lifestyle treatment, we developed a new digital method to promote behavioral change. Here we report that patients with type-2 diabetes in Sweden (n?=?331) exposed to the intervention have significantly improved HbA1c during a median follow-up of 1038 days (4?mmol/mol compared with matched controls; P?=?0.009). This is paralleled by reduced body weight, ameliorated insulin secretion, increased physical activity, and cognitive eating restraints. Participants with high BMI and insulin resistance have an even larger response, as have non-risk allele carriers for the FTO gene. "
A scoping review of artificial intelligence-based methods for diabetes risk prediction.
Farida Mohsen et al. NPJ Digit Med 2023 10 (1) 197
(Posted: Oct 30, 2023 9AM)
From the abstract: "The increasing prevalence of type 2 diabetes mellitus (T2DM) and its associated health complications highlight the need to develop predictive models for early diagnosis and intervention. While many artificial intelligence (AI) models for T2DM risk prediction have emerged, a comprehensive review of their advancements and challenges is currently lacking. This scoping review maps out the existing literature on AI-based models for T2DM prediction, adhering to the PRISMA extension for Scoping Reviews guidelines. "
From a Fledgling Genetic Science, A Murky Market for Prediction
A Smart, Undark, October 27, 2023
(Posted: Oct 27, 2023 4PM)
From the article: "Although polygenic scores alone may not be powerful predictors of disease, many researchers are optimistic that they can be combined with other, more conventional methods of risk estimation to improve screening for common conditions like cancer, cardiovascular diseases, and diabetes.
At the same time, however, a chorus of experts say that society should temper any expectations that polygenic scores will revolutionize health care. "
Precision medicine of obesity as an integral part of type 2 diabetes management – past, present, and future
L Szczerbinski et al. The Lancet Diabetes Endocr, October 4, 2023
(Posted: Oct 06, 2023 8AM)
From the abstract: " In this Review, we discuss advances in the genetics of obesity from the past decade—with emphasis on developments from the past 5 years—with a focus on metabolic consequences, and their potential implications for precision management of the disease. We also provide an overview of the potential role of genetics in guiding weight loss strategies. Finally, we propose a vision for the future of precision obesity management."
Precision medicine for cardiometabolic disease: a framework for clinical translation
PW Franks et al, The Lancet Diabetes Endoc, October 4, 2023
(Posted: Oct 06, 2023 8AM)
From the abstract: "To contextualise precision medicine in both research and clinical settings, and to encourage the successful translation of discovery science into clinical practice, in this Series paper we outline a model (the EPPOS model) that builds on contemporary evidence-based approaches; includes precision medicine that improves disease-related predictions by stratifying a cohort into subgroups of similar characteristics, or using participants' characteristics to model treatment outcomes directly; "
Understanding diabetes heterogeneity: key steps towards precision medicine in diabetes
RD Leslie et al, The Lancet Diabetes and Endocrinology, October 4, 2023
(Posted: Oct 06, 2023 7AM)
From the abstract: "Diabetes is a highly heterogeneous condition; yet, it is diagnosed by measuring a single blood-borne metabolite, glucose, irrespective of etiology. Although pragmatically helpful, disease classification can become complex and limit advances in research and medical care. The impact of any given disease risk factor will vary from person-to-person depending on their background, diabetes-related propensity, and environmental exposures. Defining the consequent heterogeneity within diabetes through precision medicine could improve health outcomes today and shine a light on avenues for novel therapy in the future. "
Second international consensus report on gaps and opportunities for the clinical translation of precision diabetes medicine
DK Tobias et al, Nature Medicine, October 5, 2023
(Posted: Oct 05, 2023 9AM)
From the abstract: "This international consensus report on precision diabetes medicine summarizes the findings from a systematic evidence review across the key pillars of precision medicine (prevention, diagnosis, treatment, prognosis) in four recognized forms of diabetes (monogenic, gestational, type 1, type 2). These reviews address key questions about the translation of precision medicine research into practice. Although not complete, owing to the vast literature on this topic, they revealed opportunities for the immediate or near-term clinical implementation of precision diabetes medicine. "
Participant characteristics in the prevention of gestational diabetes as evidence for precision medicine: a systematic review and meta-analysis
S Lim et al, Comm Medicine, October 5, 2023
(Posted: Oct 05, 2023 9AM)
From the abstract: "Precision prevention involves using the unique characteristics of a particular group to determine their responses to preventive interventions. This study aimed to systematically evaluate the participant characteristics associated with responses to interventions in gestational diabetes mellitus (GDM) prevention. GDM prevention through metformin or lifestyle differs according to some individual characteristics. Future research should include trials commencing preconception and provide results disaggregated by a priori defined participant characteristics including social and environmental factors, clinical traits, and other novel risk factors to predict GDM prevention through interventions. "
Genotype-stratified treatment for monogenic insulin resistance: a systematic review
RK Semple et al, Comm Medicine, October 5, 2023
(Posted: Oct 05, 2023 9AM)
From the abstract: " Systematic review using PubMed, MEDLINE and Embase (1 January 1987 to 23 June 2021). Studies reporting individual-level effects of pharmacologic and/or surgical interventions in monogenic IR were eligible. The evidence guiding genotype-specific treatment of monogenic IR is of low to very low quality. Metreleptin and Thiazolidinediones appear to improve metabolic markers in lipodystrophy, and rhIGF-1 appears to lower HbA1c in INSR-related IR. For other interventions, there is insufficient evidence to assess efficacy and risks in aggregated lipodystrophy or genetic subgroups. "
Utility and precision evidence of technology in the treatment of type 1 diabetes: a systematic review
LM Jacobsen et al, Comm Medicine, October 5, 2023
(Posted: Oct 05, 2023 9AM)
From the abstract: "The greatest change in the treatment of people living with type 1 diabetes in the last decade has been the explosion of technology assisting in all aspects of diabetes therapy, from glucose monitoring to insulin delivery and decision making. As such, the aim of our systematic review was to assess the utility of these technologies as well as identify any precision medicine-directed findings to personalize care. "
Cost effectiveness review of text messaging, smartphone application, and website interventions targeting T2DM or hypertension.
Ruben Willems et al. NPJ Digit Med 2023 8 (1) 150
(Posted: Aug 21, 2023 8AM)
Digital health interventions have been shown to be clinically-effective for type 2 diabetes mellitus (T2DM) and hypertension prevention and treatment. This study synthesizes and compares the cost-effectiveness of text-messaging, smartphone application, and websites. We found that digital interventions are cost-effective without substantial differences between the different delivery modes. Future health economic studies should increase transparency, conduct sufficient sensitivity analyses, and appraise the ICUR more critically in light of a reasoned willingness-to-pay threshold.
An AI-Enhanced Electronic Health Record Could Boost Primary Care Productivity.
Jeffrey E Harris et al. JAMA 2023 8
(Posted: Aug 08, 2023 8PM)
More than a few commentators have seriously inquired whether artificial intelligence (AI) could ultimately replace many clinicians. The far likelier prospect, however, is that the newly emerging technology will enhance clinical productivity. To be sure, AI-based pattern recognition software can already scan retinal photos for complications of diabetes, detect tuberculosis on chest x-rays, and evaluate screening mammograms. And some AI applications have been found to be comparable if not superior to human clinical judgment.
Are You Up to Date on Your Preventive Care?
CDC, July 2023
(Posted: Aug 01, 2023 9AM)
Family health history is a record of the diseases and health conditions in your family. You and your family members share genes. You may also have behaviors in common, like what you do for physical activity and what you like to eat. You may live in the same area and come into contact with similar harmful things in the environment. Family history includes all of these factors, any of which can affect your health. If you have a family history of a chronic disease, like cancer, heart disease, diabetes, or osteoporosis, you’re more likely to get that disease yourself.
A genetically supported drug repurposing pipeline for diabetes treatment using electronic health records.
Megan M Shuey et al. EBioMedicine 2023 7 104674
(Posted: Jul 05, 2023 7AM)
We developed and tested a genetically-informed drug-repurposing pipeline for diabetes management. This approach mapped genetically-predicted gene expression signals from the largest genome-wide association study for type 2 diabetes mellitus to drug targets using publicly available databases to identify drug–gene pairs. These drug–gene pairs were then validated using a two-step approach: 1) a self-controlled case-series (SCCS) using electronic health records from a discovery and replication population, and 2) Mendelian randomization (MR).
CKD Risk Factors
CDC, June 2023
(Posted: Jul 01, 2023 4PM)
Diabetes and high blood pressure are the more common causes of CKD in most adults. Other risk factors include heart disease, obesity, a family history of CKD, inherited kidney disorders, past damage to the kidneys, and older age.
Family history can help identify health risks, but many Latino people know little about theirs
L Medrano, American Heart News, June 2023
(Posted: Jun 30, 2023 10AM)
At the doctor's office, questions about a person's family health history often can help health care professionals determine the risk of developing chronic conditions, including heart disease, high blood pressure and diabetes. But among many Latino people, especially immigrants, talking about and recording family health history is rare. The reasons are not well understood, but studies suggest that cultural influences – family dynamics, stigma, fear and secrecy – can create barriers.
Suddenly, It Looks Like We’re in a Golden Age for Medicine We may be on the cusp of an era of astonishing innovation — the limits of which aren’t even clear yet.
DW Wells, New York Times. June 23, 2023
(Posted: Jun 24, 2023 10AM)
And although the very first person to receive Crispr gene therapy in the United States received it just four years ago, for sickle-cell disease, it has since been rolled out for testing on congenital blindness, heart disease, diabetes, cancer and H.I.V. So far only two applications for such treatments have been submitted to the F.D.A., but all told, some 400 million people worldwide are afflicted by one or more diseases arising from single-gene mutations that would be theoretically simple for Crispr to fix.
Biomarkers and personalised medicine in paediatric kidney disease
BL Neuen, The Lancet Ped Adol Med, June 2023
(Posted: May 31, 2023 7AM)
The concept of precision medicine for children and adults with chronic kidney disease has gained considerable attention in the past decade, with improvements in our understanding of the genetic, molecular, and other mechanisms that drive disease predisposition and progression. A notable example is the US National Institute of Diabetes and Digestive and Kidney Diseases' Kidney Precision Medicine Project,
Clinical utility of polygenic risk scores: a critical 2023 appraisal
S Koch et al, J Comm Genetics, May 3, 2023
(Posted: May 03, 2023 7AM)
We surveyed the current state of PRSs for various diseases, including breast cancer, diabetes, prostate cancer, coronary artery disease, and Parkinson disease, with an extra focus upon the potential improvement of clinical scores by their combination with PRSs. We observed that the diagnostic and prognostic performance of PRSs alone is consistently low, as expected. Moreover, combining a PRS with a clinical score at best led to moderate improvement of the power of either risk marker. Despite the large number of PRSs reported in the scientific literature, prospective studies of their clinical utility, particularly of the PRS-associated improvement of standard screening or therapeutic procedures, are still rare.
Early Pregnancy Loss
K Walter, JAMA, April 2023
(Posted: Apr 16, 2023 6AM)
Early pregnancy loss is caused most commonly by fetal chromosomal abnormalities, which account for more than two-thirds of all early pregnancy loss between 6 and 10 weeks of gestation. Risk factors for early pregnancy loss include older age at onset of pregnancy, prior pregnancy loss, some medical conditions (such as diabetes, hyperthyroidism, and lupus), and exposures during pregnancy that may harm a developing fetus (such as alcohol; some viral or bacterial infections; environmental exposure to lead, mercury, or radiation; and certain medications).
Development and Validation of a Prediction Model for Future Estimated Glomerular Filtration Rate in People With Type 2 Diabetes and Chronic Kidney Disease.
Mariella Gregorich et al. JAMA network open 2023 4 (4) e231870
(Posted: Apr 08, 2023 0PM)
Can routinely available data from primary care visits be used to develop and externally validate a prediction model that reliably predicts estimated glomerular filtration rate (eGFR) for upcoming follow-up visits? In this prognostic study involving 4637 adults with type 2 diabetes and chronic kidney disease, a prediction model including 13 routinely collected baseline variables based on data from 3 prospective multinational cohort studies was developed and externally validated. The model was robust, well calibrated, and capable of predicting decreases in eGFR up to 5 years after baseline.
Effectiveness of artificial intelligence screening in preventing vision loss from diabetes: a policy model.
Roomasa Channa et al. NPJ digital medicine 2023 3 (1) 53
(Posted: Mar 28, 2023 6AM)
We designed the Care Process for Preventing Vision Loss from Diabetes (CAREVL), as a Markov model to compare the effectiveness of point-of-care autonomous AI-based screening with in-office clinical exam by an eye care provider (ECP), on preventing vision loss among patients with diabetes. The estimated incidence of vision loss at 5 years was 1535 per 100,000 in the AI-screened group compared to 1625 per 100,000 in the ECP group, leading to a modelled risk difference of 90 per 100,000. The base-case CAREVL model estimated that an autonomous AI-based screening strategy would result in 27,000 fewer Americans with vision loss at 5 years compared with ECP.
Evaluation of polygenic risk scores to differentiate between type 1 and type 2 diabetes.
Muhammad Shoaib et al. Genetic epidemiology 2023 2
(Posted: Mar 04, 2023 9AM)
We evaluated PRS models for T1D and T2D in European genetic ancestry participants from the UK Biobank (UKB) and then in the Michigan Genomics Initiative (MGI). Specifically, we investigated the utility of T1D and T2D PRS to discriminate between T1D, T2D, and controls in unrelated UKB individuals of European ancestry. We derived PRS models using external non-UKB GWAS. The T1D PRS model with the best discrimination between T1D cases and controls (area under the receiver operator curve [AUC]?=?0.805) also yielded the best discrimination of T1D from T2D cases in the UKB (AUC?=?0.792) and separation in MGI (AUC?=?0.686).
Causal factors underlying diabetes risk informed by Mendelian randomisation analysis: evidence, opportunities and challenges.
Shuai Yuan et al. Diabetologia 2023 2
(Posted: Mar 01, 2023 0PM)
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 summarize the evidence on potential causal risk factors for diabetes by integrating published MR studies on type 1 and 2 diabetes.
Beyond genetic screening-functionality-based precision medicine in monogenic obesity.
Antje Körner et al. The lancet. Diabetes & endocrinology 2023 2 (3) 143-144
(Posted: Feb 28, 2023 7AM)
Most genes causing monogenic obesity are implicated in the central energy regulatory circuits of the leptin-melanocortin pathway. Even though monogenic obesity is still a rare disease entity, identifying these patients is important since there are now promising treatment options such as setmelanotide, a melanocortin receptor agonist, which was recently approved by the US Food and Drug Administration and European Medicines Agency
Analysis of Pregnancy Complications and Epigenetic Gestational Age of Newborns
CL Acosta et al, JAMA Network Open, February 24, 2023
(Posted: Feb 24, 2023 11AM)
Is exposure to gestational diabetes, gestational hypertension, or preeclampsia associated with biological gestational age, measured via epigenetic clocks, in newborns? In this national multisite cohort study of 1801 children, preeclampsia and gestational diabetes were significantly associated with decelerated gestational age in exposed offspring at birth vs unexposed offspring (ie, they were estimated to be biologically younger than their chronological gestational age), and these associations were more pronounced in female offspring. No associations were observed for gestational hypertension and accelerated or decelerated biological age.
The necessity of incorporating non-genetic risk factors into polygenic risk score models
S van Dam et al, Sci Reports, February 20, 2023
(Posted: Feb 20, 2023 8AM)
The growing public interest in genetic risk scores for various health conditions can be harnessed to inspire preventive health action. However, current commercially available genetic risk scores can be deceiving as they do not consider other, easily attainable risk factors, such as sex, BMI, age, smoking habits, parental disease status and physical activity. We show improved performance at identifying the 10% most at-risk individuals for type 2 diabetes (T2D) and coronary artery disease (CAD) by including common risk factors.
Association of Hypertensive Disorders of Pregnancy With Future Cardiovascular Disease.
Bilal Rayes et al. JAMA network open 2023 2 (2) e230034
(Posted: Feb 18, 2023 8AM)
Is there evidence for an association between hypertensive disorders of pregnancy (HDPs) and long-term risk of cardiovascular disease? In this large genome-wide genetic association study using mendelian randomization, HDPs were associated with higher risk of coronary artery disease and ischemic stroke but not heart failure or atrial fibrillation. Mediation analysis revealed a partial attenuation of the association between HDPs and coronary artery disease after adjustment for systolic blood pressure and type 2 diabetes. These results support the consideration of HDPs as potential risk factors for cardiovascular disease.
Association of COVID-19 Vaccination With Risk for Incident Diabetes After COVID-19 Infection.
Alan C Kwan et al. JAMA network open 2023 2 (2) e2255965
(Posted: Feb 16, 2023 6AM)
In this cohort study, COVID-19 infection was associated with increased risk of diabetes, consistent findings of a meta-analysis.1 Our results suggest that this risk persisted as the Omicron variant became predominant, and the association remained even after accounting for temporal confounders. Diabetes risk after COVID-19 infection was higher in unvaccinated than vaccinated patients, suggesting a benefit of vaccination.
How a pioneering diabetes drug offers hope for preventing autoimmune disorders
E Dolgin, Nature, February 15, 2023
(Posted: Feb 15, 2023 7AM)
Teplizumab is a type of antibody therapy. It blocks T cells, the ’attack dogs’ of the immune system, stopping them destroying insulin-producing islet cells in the pancreas. Mikayla received a two-week course of treatment in July 2016, as part of a clinical trial to test whether the therapy could help to keep T1D at bay.
The 76-person study found that people who received the treatment developed diabetes symptoms after about five years, on average. That’s three years longer than the average delay for those who received the placebo.
DNA methylation age acceleration is associated with risk of diabetes complications.
Valentin Max Vetter et al. Communications medicine 2023 2 (1) 21
(Posted: Feb 12, 2023 7AM)
We report on a statistically significant association between oral glucose tolerance test results and Hannum and PhenoAge DNAmAA. PhenoAge was also associated with fasting glucose. In contrast, we found no cross-sectional association after covariate adjustment between DNAmAA and a diagnosis of T2D. However, longitudinal analyses showed that every additional year of 7-CpG DNAmAA at baseline increased the odds for developing one or more additional complications or worsening of an already existing complication during the follow-up period.
Large-scale genetic analysis shows microRNAs in human pancreas associated with diabetes
NHGRI, February 2023
(Posted: Feb 11, 2023 8AM)
In a new large-scale genetic analysis, scientists have found a set of small RNA molecules, called microRNAs, in human pancreatic cells that are strongly associated with type 2 diabetes. Researchers discovered the microRNAs in groups of cells called pancreatic islets, which produce hormones, such as insulin, that the body uses to regulate energy levels. In people with diabetes, the islets fail to produce sufficient insulin to control blood sugar, which is why understanding the basic biology of pancreatic islets is important for human health.
How rare mutations contribute to complex traits
LM Evans et al, Nature, February 8, 2023
(Posted: Feb 09, 2023 6AM)
Our understanding of the genetic mutations that affect complex human traits — such as height, smoking-related behaviour or the risk of diabetes — has been vastly broadened by genome-wide association studies (GWASs). But such research has focused largely on associations between traits of interest and variants that are common in the human population. Rare variants pose challenges to GWASs, because they can be studied using only large samples and in-depth genetic information, and can be more strongly confounded by non-genetic factors than can common variants,
Trialing precision medicine for type 2 diabetes
SJ Pilla et al, Nature Medicine, February 6, 2023
(Posted: Feb 07, 2023 6AM)
A study prospectively evaluating a stratified approach to selecting treatment heralds a new era of precision medicine for type 2 diabetes, which should incorporate ongoing discovery, social determinants of health and healthcare transformation.
Loci for insulin processing and secretion provide insight into type 2 diabetes risk.
K Alaine Broadaway et al. American journal of human genetics 2023 1
(Posted: Jan 27, 2023 7AM)
Insulin secretion is critical for glucose homeostasis, and increased levels of the precursor proinsulin relative to insulin indicate pancreatic islet beta-cell stress and insufficient insulin secretory capacity in the setting of insulin resistance. We conducted meta-analyses of genome-wide association results for fasting proinsulin from 16 European-ancestry studies in 45,861 individuals. We found 36 independent signals at 30 loci (p value < 5 × 10-8), which validated 12 previously reported loci for proinsulin and ten additional loci previously identified for another glycemic trait.
How our microbiome is shaped by family, friends and even neighbours.
Callaway Ewen et al. Nature 2023 1
(Posted: Jan 21, 2023 6AM)
People living in the same household share more than just a roof (and pints of milk). Be they family or flatmate, housemates tend to have the same microbes colonizing their bodies, and the longer the cohabitation, the more similar these microbiomes become. The conclusion — based on a new study of the gut and mouth microbiomes of thousands of people from around the world1 — raises the possibility that diseases linked to microbiome dysfunction, including cancer, diabetes and obesity, could be partly transmissible.
Genetic predictors of lifelong medication-use patterns in cardiometabolic diseases.
Kiiskinen Tuomo et al. Nature medicine 2023 1
(Posted: Jan 20, 2023 6AM)
Little is known about the genetic determinants of medication use in preventing cardiometabolic diseases. Using the Finnish nationwide drug purchase registry with follow-up since 1995, we performed genome-wide association analyses of longitudinal patterns of medication use in hyperlipidemia, hypertension and type 2 diabetes in up to 193,933 individuals (55% women) in the FinnGen study. In meta-analyses of up to 567,671 individuals combining FinnGen with the Estonian Biobank and the UK Biobank, we discovered 333 independent loci (P?<?5?×?10–9) associated with medication use.
Identification of serum metabolome signatures associated with retinal and renal complications of type 2 diabetes.
Tomofuji Yoshihiko et al. Communications medicine 2023 1 (1) 5
(Posted: Jan 11, 2023 6AM)
We profiled serum metabolites of persons with type 2 diabetes with both DR and DKD (N?=?141) and without complications (N?=?159) using a comprehensive non-targeted metabolomics approach with mass spectrometry. Based on the serum metabolite profiles, case–control comparisons and metabolite set enrichment analysis (MSEA) were performed. Here we show that five metabolites (cyclohexylamine, P?=?4.5?×?10-6; 1,2-distearoyl-glycero-3-phosphocholine, P?=?7.3?×?10-6; piperidine, P?=?4.8?×?10-4; N-acetylneuraminic acid, P?=?5.1?×?10-4; stearoyl ethanolamide, P?=?6.8?×?10-4) are significantly increased in those with the complications. MSEA identifies fatty acid biosynthesis as the type 2 diabetes complications-associated biological pathway (P?=?0.0020).
Acute respiratory distress syndrome after SARS-CoV-2 infection on young adult population: International observational federated study based on electronic health records through the 4CE consortium
B Moal et al, PLOS ONE, Jan 4, 2023
(Posted: Jan 05, 2023 5AM)
Among the 75,377 hospitalized patients with positive SARS-CoV-2 PCR, 1001 young adults presented with ARDS (7.8% of young hospitalized adults). Their mortality rate at 90 days was 16.2% and they presented with a similar complication rate for infection than older adults with ARDS. Peptic ulcer disease, paralysis, obesity, congestive heart failure, valvular disease, diabetes, chronic pulmonary disease and liver disease were associated with a higher risk of ARDS. We described a high prevalence of obesity (53%), hypertension (38%- although not significantly associated with ARDS), and diabetes (32%).
Pharmacogenomics of GLP-1 receptor agonists: a genome-wide analysis of observational data and large randomised controlled trials.
Dawed Adem Y et al. The lancet. Diabetes & endocrinology 2022 12 (1) 33-41
(Posted: Dec 20, 2022 8AM)
In the treatment of type 2 diabetes, GLP-1 receptor agonists lower blood glucose concentrations, body weight, and have cardiovascular benefits. The efficacy and side effects of GLP-1 receptor agonists vary between people. Human pharmacogenomic studies of this inter-individual variation can provide both biological insight into drug action and provide biomarkers to inform clinical decision making. This genome-wide pharmacogenomic study of GLP-1 receptor agonists provides novel biological and clinical insights. Clinically, when genotype is routinely available at the point of prescribing, individuals with ARRB1 variants might benefit from earlier initiation of GLP-1 receptor agonists.
Aiming for equitable precision medicine in diabetes.
et al. Nature medicine 2022 11 (11) 2223
(Posted: Nov 18, 2022 6AM)
New initiatives aimed at reducing the burden of diabetes are laudable, but they will have to account for the disease’s complexity and heterogeneity to be truly effective and equitable at a global scale. A growing body of evidence supports the idea that variation exists not only in disease presentation and progression but also in individual responses to therapy, which suggests that a ‘one-size-fits-all’ approach to meeting the global coverage targets will be insufficient.
Improving Machine Learning Diabetes Prediction Models for the Utmost Clinical Effectiveness
J Shin et al, J Per Med, November 14, 2022
(Posted: Nov 15, 2022 9AM)
DNA Methylation Implicated in Human Obesity and Diabetes
ME Tucker, Medscape, November 2022
(Posted: Nov 14, 2022 6AM)
Previous attempts to identify causal associations between DNA methylation and both obesity and type 2 diabetes have been hindered by challenges in collecting and isolating cells from human tissue. Recent data suggest that manipulation of DNA methylation enzymes in adipocytes can induce or prevent obesity and type 2 diabetes through cellular effects on energy expenditure and insulin sensitivity.
Broad-capture proteomics and machine learning for early detection of type 2 diabetes risk
Nature Medicine, November 10, 2022
(Posted: Nov 11, 2022 7AM)
Impaired glucose tolerance (IGT) is a common condition that affects glucose control after sugar consumption. Isolated IGT is undetected by screening and diagnostic strategies, leaving affected individuals at high risk of developing diabetes. Here, a machine-learning framework identifies a three-protein signature for detecting isolated IGT from a single blood sample.
Proteomic signatures for identification of impaired glucose tolerance
JC Zanini et al, Nature Medicine, November 10, 2022
(Posted: Nov 11, 2022 7AM)
We applied machine learning to the proteomic profiles of a single fasted sample from 11,546 participants of the Fenland study to test discrimination of iIGT defined using the gold-standard OGTTs. We observed significantly improved discriminative performance by adding only three proteins (RTN4R, CBPM and GHR) to the best clinical model (AUROC = 0.80 (95% confidence interval: 0.79–0.86), P?=?0.004), which we validated in an external cohort. Increased plasma levels of these candidate proteins were associated with an increased risk for future T2D in an independent cohort and were also increased in individuals genetically susceptible to impaired glucose homeostasis and T2D.
Discovering a trans-omics biomarker signature that predisposes high risk diabetic patients to diabetic kidney disease
I W Wu et al, NPJ Digital Medicine, November 2, 2022
(Posted: Nov 03, 2022 8AM)
Diabetic kidney disease is the leading cause of end-stage kidney disease worldwide; however, the integration of high-dimensional trans-omics data to predict this diabetic complication is rare. We develop artificial intelligence (AI)-assisted models using machine learning algorithms to identify a biomarker signature that predisposes high risk patients with diabetes mellitus (DM) to diabetic kidney disease based on clinical information, untargeted metabolomics, targeted lipidomics and genome-wide single nucleotide polymorphism (SNP) datasets. This involves 618 individuals who are split into training and testing cohorts of 557 and 61 subjects, respectively.
NIH-funded study finds personalized kidney screening for people with type 1 diabetes could reduce costs, detect disease earlier
NIH, November 2, 2022
(Posted: Nov 02, 2022 10AM)
Taking a personalized approach to kidney disease screening for people with type 1 diabetes (T1D) may reduce the time that chronic kidney disease (CKD) goes undetected, according to a new analysis. According to the model’s findings: People with AER of 21-30 mg per 24 hours and a HbA1c of at least 9% are at high risk for developing CKD and could be screened for urine albumin every six months. This screening frequency could reduce time with undetected kidney disease so that appropriate interventions can be instituted as early as possible. Those with AER = 10 mg per 24 hours and a HbA1c = 8% are at lower risk for developing CKD and could be screened every two years. This change reduces patient burden and potentially saves millions of dollars compared to annual screening. All others with T1D = 5 years could continue to be screened annually.
Type 2 Diabetes
E Ahmad et al, The Lancet, November 2022
(Posted: Nov 02, 2022 6AM)
Type 2 diabetes accounts for nearly 90% of the approximately 537 million cases of diabetes worldwide. Access to novel therapies improves person-centred outcomes beyond glycaemic control. Precision medicine, including multiomics and pharmacogenomics, hold promise to enhance understanding of disease heterogeneity, leading to targeted therapies. Technology might improve outcomes, but its potential is yet to be realised. Despite advances, substantial barriers to changing the course of the epidemic remain.
Diabetes and Alzheimer's disease: shared genetic susceptibility?
J Hardy et al, The Lancet Neurology, November 1, 2022
(Posted: Nov 02, 2022 6AM)
Maturity-Onset Diabetes of the Young: Mutations, Physiological Consequences, and Treatment Options
H Younis et al, J Per Med, October 25, 2022
(Posted: Oct 25, 2022 10AM)
MODY is often misdiagnosed as type 1 or type 2 diabetes mellitus due to an overlap in clinical features, high cost and limited availability of genetic testing, and unfamiliarity with MODY outside of the medical profession. The primary aim of this review is to investigate the genetic characterization of the MODY subtypes. Additionally, this review will elucidate the link between the genetics, function, and clinical manifestations of MODY in each of the 14 subtypes. In providing this knowledge, we hope to assist in the accurate diagnosis of MODY patients and, subsequently, in ensuring they receive appropriate treatment.
A combined polygenic score of 21,293 rare and 22 common variants improves diabetes diagnosis based on hemoglobin A1C levels
P Dornbos et al, Nature Genetics, October 24, 2022
(Posted: Oct 25, 2022 10AM)
We developed a method for constructing rare variant PGSs and applied it to calculate genetically modified hemoglobin A1C thresholds for type 2 diabetes (T2D) diagnosis7,8,9,10. The resultant rare variant PGS is highly polygenic (21,293 variants across 154 genes), depends on ultra-rare variants (72.7% observed in fewer than three people) and identifies significantly more undiagnosed T2D cases than expected by chance (odds ratio?=?2.71; P?=?1.51?×?10-6). A PGS combining common and rare variants is expected to identify 4.9?million misdiagnosed T2D cases in the United States.
Fitbit step counts clarify the association between activity and chronic disease risk
Nature Medicine, October 11, 2022
(Posted: Oct 12, 2022 8AM)
Using electronic health records data from the All of Us Research Program, we show that higher daily step counts in data collected over several years of Fitbit fitness tracker use were associated with lower risk of common, chronic diseases, including diabetes, hypertension, gastroesophageal reflux disease, depression, obesity and sleep apnea.
Transcriptomics-based network medicine approach identifies metformin as a repurposable drug for atrial fibrillation
JC Lal et al, Cell Reports Med, October 11, 2022
(Posted: Oct 12, 2022 8AM)
Using the active compactor, a new design analysis of large-scale longitudinal electronic health record (EHR) data, we determine that metformin use is significantly associated with a reduced risk of AF (odds ratio = 0.48, 95%, confidence interval [CI] 0.36–0.64, p < 0.001) compared with standard treatments for diabetes.
Multi-omic phenotyping reveals host-microbe responses to bariatric surgery, glycaemic control and obesity
NC Penny et al, Comm Medicine, October 7, 2022
(Posted: Oct 08, 2022 7AM)
Here we show that bariatric surgery reverses several disrupted pathways characteristic of T2D. The differential metabolite set representative of bariatric surgery overlaps with both diabetes (19.3% commonality) and body mass index (18.6% commonality). However, the percentage overlap between diabetes and body mass index is minimal (4.0% commonality), consistent with weight-independent mechanisms of T2D resolution. The gut microbiota is more strongly correlated to body mass index than T2D.
The Joint Public Health Impact of Family History of Diabetes and Cardiovascular Disease among Adults in the United States: A Population-Based Study
D Rasooly et al, Public Health Genomics, October 6, 2022
(Posted: Oct 06, 2022 1PM)
Participants with joint family history exhibit 6.5 greater odds for having both diseases and are diagnosed with diabetes 6.6 years earlier than participants without family history. Healthy participants without prevalent CVD or diabetes but with joint family history exhibit a greater prevalence of diabetes risk factors compared to no family history counterparts. Joint family history is associated with an increase in all-cause mortality. Over 44% of the US adult population has a family history of CVD and/or diabetes. This wide presence of high-risk family history suggests that clinical and public health efforts should collect and act on joint family history of CVD and diabetes to improve population efforts in the prevention and early detection of these common chronic diseases.
Pharmacogenetics of Cardiovascular Prevention in Diabetes: From Precision Medicine to Identification of Novel Targets
ML Morieri et al, J Per Medicine, August 29,2022
(Posted: Aug 29, 2022 1PM)
Precision Medicine in Diabetes, Current Research and Future Perspectives
R Franceschi, J Per Medicine, July 28, 2022
(Posted: Jul 28, 2022 6AM)
Recently the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD) have jointly released an expert opinion-based consensus report on precision medicine. The report defines precision diabetes medicine as “an approach to optimize the diagnosis, prediction, prevention, or treatment of diabetes by integrating multidimensional data, accounting for individual differences”, and it is characterized by six categories; precision diagnosis, precision therapeutics, precision prevention, precision treatment, precision prognosis and precision monitoring. Precision medicine in diabetes utilizes the individual’s unique genetic makeup, environment or context data (that can be collected from clinical records, wearable technology, genomics and other ‘omics data) and allows one to appreciate individual characteristics, differences, circumstances and preferences
Polygenic Risk Scores for Cardiovascular Disease: A Scientific Statement From the American Heart Association
JW O'Sullivan et al, Circulation, July 18, 2022
(Posted: Jul 18, 2022 1PM)
Individuals and their physicians are increasingly presented with polygenic risk scores for cardiovascular conditions in clinical encounters. In this scientific statement, we review the contemporary science, clinical considerations, and future challenges for polygenic risk scores for cardiovascular diseases. We selected 5 cardiometabolic diseases (coronary artery disease, hypercholesterolemia, type 2 diabetes, atrial fibrillation, and venous thromboembolic disease) and response to drug therapy and offer provisional guidance to health care professionals, researchers, policymakers, and patients.
Incorporating family history of disease improves polygenic risk scores in diverse populations
MLA Hujeol et al, Cell Genomics, July 13, 2022
(Posted: Jul 14, 2022 7AM)
Polygenic risk scores (PRSs) derived from genotype data and family history (FH) of disease provide valuable information for predicting disease risk, but PRSs perform poorly when applied to diverse populations. Here, we explore methods for combining both types of information (PRS-FH) in UK Biobank data. We evaluated PRS, FH, and PRS-FH using liability-scale R2, primarily focusing on 3 well-powered diseases (type 2 diabetes, hypertension, and depression). PRS attained average prediction R2s of 5.8%, 4.0%, and 0.53% in non-British Europeans, South Asians, and Africans, confirming poor cross-population transferability. In contrast, PRS-FH attained average prediction R2s of 13%, 12%, and 10%, respectively, representing a large improvement in Europeans and an extremely large improvement in Africans. In conclusion, including family history improves the accuracy of polygenic risk scores, particularly in diverse populations.
International electronic health record-derived post-acute sequelae profiles of COVID-19 patients
HG Zhang et al, NPJ Digital Medicine, June 29, 2022
(Posted: Jun 29, 2022 7PM)
We leveraged electronic health record (EHR) data from 277 international hospitals representing 414,602 patients with COVID-19, 2.3 million control patients without COVID-19 in the inpatient and outpatient settings, and over 221 million diagnosis codes to systematically identify new-onset conditions enriched among patients with COVID-19 during the post-acute period. Compared to inpatient controls, inpatient COVID-19 cases were at significant risk for angina pectoris (RR 1.30, 95% CI 1.09–1.55), heart failure (RR 1.22, 95% CI 1.10–1.35), cognitive dysfunctions (RR 1.18, 95% CI 1.07–1.31), and fatigue (RR 1.18, 95% CI 1.07–1.30). Relative to outpatient controls, outpatient COVID-19 cases were at risk for pulmonary embolism (RR 2.10, 95% CI 1.58–2.76), venous embolism (RR 1.34, 95% CI 1.17–1.54), atrial fibrillation (RR 1.30, 95% CI 1.13–1.50), type 2 diabetes (RR 1.26, 95% CI 1.16–1.36) and vitamin D deficiency (RR 1.19, 95% CI 1.09–1.30).
Development and validation of a trans-ancestry polygenic risk score for type 2 diabetes in diverse populations
T Ge et al, Genome Medicine, June 29, 2022
(Posted: Jun 29, 2022 6PM)
We integrated T2D GWAS in European, African, and East Asian populations to construct a trans-ancestry T2D PRS using a newly developed Bayesian polygenic modeling method, and assessed the prediction accuracy of the PRS in the multi-ethnic Electronic Medical Records and Genomics (eMERGE) study (11,945 cases; 57,694 controls), four Black cohorts (5137 cases; 9657 controls), and the Taiwan Biobank (4570 cases; 84,996 controls). We additionally evaluated a post hoc ancestry adjustment method that can express the polygenic risk on the same scale across ancestrally diverse individuals and facilitate the clinical implementation of the PRS in prospective cohorts.
Enhancing self-management in type 1 diabetes with wearables and deep learning
T Zhu et al, NPJ Digital Medicine, June 27, 2022
(Posted: Jun 27, 2022 10AM)
Continuous glucose monitoring (CGM) is widely used in T1D self-management for real-time glucose measurements, while smartphone apps are adopted as basic electronic diaries, data visualization tools, and simple decision support tools for insulin dosing. Applying a mixed effects logistic regression analysis to the outcomes of a six-week longitudinal study in 12 T1D adults using CGM and a clinically validated wearable sensor wristband, we identified several significant associations between physiological measurements and hypo- and hyperglycemic events measured an hour later.
Extending precision medicine tools to populations at high risk of type 2 diabetes.
Misra Shivani et al. PLoS medicine 2022 5 (5) e1003989
(Posted: May 28, 2022 11AM)
The generation of ethnicity-specific T2D PS for every subethnic group remains aspirational, as the large sample sizes needed to do this robustly are prohibitive (the genetic ancestry of the Indian subcontinent, for example, is more diverse than the whole of Europe. Thus, strategies to utilise existing scores derived from other populations, or leveraging multi-ancestry GWAS, have predominated. Attempts to apply a PS derived in a population of one ancestry to another ethnic group have shown variable performance.
Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation.
Mahajan Anubha et al. Nature genetics 2022 5 (5) 560-572
(Posted: May 18, 2022 11AM)
We assembled an ancestrally diverse collection of genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 180,834 affected individuals and 1,159,055 controls (48.9% non-European descent) through the Diabetes Meta-Analysis of Trans-Ethnic association studies (DIAMANTE) Consortium. Multi-ancestry GWAS meta-analysis identified 237 loci attaining stringent genome-wide significance (P < 5 × 10-9), which were delineated to 338 distinct association signals. Fine-mapping of these signals was enhanced by the increased sample size and expanded population diversity of the multi-ancestry meta-analysis, which localized 54.4% of T2D associations to a single variant with >50% posterior probability
Polygenic scores, diet quality, and type 2 diabetes risk: An observational study among 35,759 adults from 3 US cohorts.
Merino Jordi et al. PLoS medicine 2022 4 (4) e1003972
(Posted: May 03, 2022 11AM)
In 3 cohort studies involving 35,759 men and women in the US, we used novel polygenic scores for type 2 diabetes to systematically evaluate the presence of additive and multiplicative interactions between genetic risk and diet quality on the development of type 2 diabetes.
We found that both low diet quality and increased overall or pathway-specific genetic risk were independently associated with higher risk of type 2 diabetes.
We documented that within any genetic risk category, high diet quality, as compared to low diet quality, was associated with a nearly 30% lower risk of type 2 diabetes. Further, we showed that the risk of type 2 diabetes attributed to the combination of increased genetic risk and low diet quality was similar to the sum of the risks associated with each factor alone.
Hospitalizations of Children Aged 5–11 Years with Laboratory-Confirmed COVID-19 — COVID-NET, 14 States, March 2020–February 2022
DS Shi et al, MMWR, April 19, 2022
(Posted: Apr 20, 2022 9AM)
COVID-19 can cause severe illness in children. Children aged 5–11 years became eligible for COVID-19 vaccination on November 2, 2021. During the period of Omicron predominance (December 19, 2021–February 28, 2022), COVID-19–associated hospitalization rates in children aged 5–11 years were approximately twice as high among unvaccinated as among vaccinated children. Non-Hispanic Black children represented the largest group of unvaccinated children. Thirty percent of hospitalized children had no underlying medical conditions, and 19% were admitted to an intensive care unit. Children with diabetes and obesity were more likely to experience severe COVID-19.
Vaccinating Children with Disabilities Against COVID-19
CDC, April 2022
(Posted: Apr 14, 2022 10AM)
CDC recommends everyone 5 years and older get vaccinated against COVID-19 - including children with disabilities who may be at a higher risk for severe illness from COVID-19. Many children with disabilities have underlying medical conditions - such as lung, heart, or kidney disease, a weakened immune system, cancer, diabetes, some blood diseases, or conditions of the muscular or central nervous system - which put them at increased risk for severe illness from COVID-19.
Donor and recipient polygenic risk scores influence the risk of post-transplant diabetes
A Shaked et al Nature Medicine, April 2022
(Posted: Apr 09, 2022 2PM)
Post-transplant diabetes mellitus (PTDM) reduces allograft and recipient life span. Polygenic risk scores (PRSs) show robust association with greater risk of developing type?2 diabetes (T2D). We examined the association of PTDM with T2D PRS in liver recipients (n?=?1,581) and their donors (n?=?1,555), and kidney recipients (n?=?2,062) and their donors (n?=?533). Recipient T2D PRS was associated with pre-transplant T2D and the development of PTDM. T2D PRS in liver donors, but not in kidney donors, was an independent risk factor for PTDM development.
Diabetes risk rises after COVID, massive study finds- Even mild SARS-CoV-2 infections can amplify a person’s chance of developing diabetes, especially for those already susceptible to the disease.
C Watson, Nature, March 31, 2022
(Posted: Mar 31, 2022 7AM)
Rising diabetes diagnosis in long COVID
KMV Narayan et al, The Lancet, March, 2022
(Posted: Mar 28, 2022 2PM)
Chronic Kidney Disease Basics
CDC, March 2022
(Posted: Mar 15, 2022 7AM)
Kidney diseases are a leading cause of death in the United States. About 37 million US adults are estimated to have CKD, and most are undiagnosed. 40% of people with severely reduced kidney function (not on dialysis) are not aware of having CKD. Talk to your doctor about getting tested if you have any of these risk factors: Diabetes, High blood pressure, Heart disease, Family history of CKD, Obesity.
Applying implementation science to improve care for familial hypercholesterolemia.
Jones Laney K et al. Current opinion in endocrinology, diabetes, and obesity 2021 11 (2) 141-151
(Posted: Mar 14, 2022 7AM)
Improving care of individuals with familial hypercholesteremia (FH) is reliant on the synthesis of evidence-based guidelines and their subsequent implementation into clinical care. This review describes implementation strategies, defined as methods to improve translation of evidence into FH care, that have been mapped to strategies from the Expert Recommendations for Implementing Change (ERIC) compilation. There were only 8 of 37 studies that utilized an implementation science theory, model, or framework and two that explicitly addressed health disparities or equity.
Microbiome and metabolome features of the cardiometabolic disease spectrum
S Fromentin et al, Nature Medicine, February 17, 2022
(Posted: Feb 18, 2022 8AM)
We recruited 1,241 middle-aged Europeans, including healthy individuals, individuals with dysmetabolic morbidities (obesity and type 2 diabetes) but lacking overt IHD diagnosis and individuals with ischemic heart disease at three distinct clinical stages—acute coronary syndrome, chronic IHD and IHD with heart failure—and characterized their phenome, gut metagenome and serum and urine metabolome. We found that about 75% of microbiome and metabolome features that distinguish individuals with IHD from healthy individuals.
Polygenic Prediction of Type 2 Diabetes in Africa.
Chikowore Tinashe et al. Diabetes care 2022 1
(Posted: Jan 18, 2022 7AM)
Polygenic prediction of type 2 diabetes (T2D) in continental Africans is adversely affected by the limited number of genome-wide association studies (GWAS) of T2D from Africa and the poor transferability of European-derived polygenic risk scores (PRSs) in diverse ethnicities. We set out to evaluate if African American–, European-, or multiethnic-derived PRSs would improve polygenic prediction in continental Africans.
Novel insights into the consequences of obesity: a phenotype-wide Mendelian randomization study
C He et al, EJHG January 1, 2022
(Posted: Jan 03, 2022 2PM)
Obesity is thought to significantly impact the quality of life. In this study, we sought to evaluate the health consequences of obesity on the risk of a broad spectrum of human diseases. The causal effects of exposing to obesity on health outcomes were inferred using Mendelian randomization (MR) analyses using a fixed effects inverse-variance weighted model. Our MR results confirmed many putative disease risks due to obesity, such as diabetes, dyslipidemia, sleep disorder, gout, smoking behaviors, arthritis, myocardial infarction, and diabetes-related eye disease. The novel findings indicated that elevated red blood cell count was inferred as a mediator of BMI-induced type 2 diabetes in our bidirectional MR analysis.
Population study of the gut microbiome: associations with diet, lifestyle, and cardiometabolic disease
RL Walker et al, Genome Medicine, December 2021
(Posted: Dec 20, 2021 9AM)
We demonstrate that overall microbial diversity decreases with increasing 10-year CVD risk and body mass index measures. We link lifestyle factors, especially diet and exercise, to microbial diversity. Our association analyses reveal both known and unreported microbial associations with CVD and diabetes, related prescription medications, as well as many anthropometric and blood test measurements.
New CDC Partnerships to Advance the Development and Validation of Next Generation Sequencing Tests: A Publicly Available List of Expert Curated Variants
L Kalman et al, CDC Blog Post, November 16, 2021
(Posted: Nov 17, 2021 5PM)
CDC has partnered with the Clinical Genome Resource (ClinGen) to develop a publicly available list of expert curated variants. As part of this study, the ClinGen Variant Curation Expert Panels nominated 546 variants found in 84 disease associated genes (link to table of genes ), including common pathogenic and difficult to detect variants. Variant types nominated included 346 SNVs, 104 deletions, 37 CNVs, 25 duplications, 18 deletion-insertions, 5 inversions, 4 insertions, 2 complex rearrangements, 3 in difficult to sequence regions, and 2 fusions. The nominated variants are associated with a wide range of diseases that include heritable cancers, inborn errors of metabolism, cardiomyopathy, diabetes, and immune disorders.
Genome-wide association analyses highlight etiological differences underlying newly defined subtypes of diabetes
DM Aly et al, Nature Genetics, November 4, 2021
(Posted: Nov 05, 2021 6PM)
We used genome-wide association and genetic risk score (GRS) analysis to compare the underlying genetic drivers. Individuals from the Swedish ANDIS (All New Diabetics In Scania) study were compared to individuals without diabetes; the Finnish DIREVA (Diabetes register in Vasa) and Botnia studies were used for replication. We show that subtypes differ with regard to family history of diabetes and association with GRS for diabetes-related traits.
Trans-ethnic Mendelian-randomization study reveals causal relationships between cardiometabolic factors and chronic kidney disease.
Zheng Jie et al. International journal of epidemiology 2021 10
(Posted: Oct 24, 2021 6PM)
51, 672 CKD cases and 958 102 controls of European ancestry from CKDGen, UK Biobank and HUNT, and 13 093 CKD cases and 238 118 controls of East Asian ancestry from Biobank Japan, China Kadoorie Biobank and Japan-Kidney-Biobank/ToMMo were included. Eight risk factors showed reliable evidence of causal effects on CKD in Europeans, including genetically predicted body mass index (BMI), hypertension, systolic blood pressure, high-density lipoprotein cholesterol, apolipoprotein A-I, lipoprotein(a), type 2 diabetes (T2D) and nephrolithiasis. In East Asians, BMI, T2D and nephrolithiasis showed evidence of causality on CKD.
Development features and study characteristics of mobile health apps in the management of chronic conditions: a systematic review of randomised trials
M Cucchiniello et al, NPJ Digital Medicine, October 5, 2021
(Posted: Oct 05, 2021 6AM)
We identified 69 studies on diabetes (n?=?29), cardiovascular diseases (n?=?13), chronic respiratory diseases (n?=?13), cancer (n?=?10) or their combinations (n?=?4). The apps rarely adopted developmental factors in the design stage, with only around one-third of studies reporting user or healthcare professional engagement. Findings were not significant for the majority of studies across all CD, with most RCTs revealing a high risk of bias.
The Unequal Burden of the Covid-19 Pandemic: Racial/Ethnic Disparities in US Cause-Specific Mortality
AN Luck et al, MEDRXIV, September 17, 2021
(Posted: Sep 18, 2021 11AM)
Using 2019 and 2020 provisional death counts from the National Center for Health Statistics and population estimates from the US Census Bureau, we estimate age-standardized death rates by race/ethnicity and attribute changes in mortality to various causes of death. We also examine how patterns of change across racial/ethnic groups vary by age and sex. Covid-19 death rates in 2020 were highest in the Hispanic community whereas Black individuals had the largest increase in all-cause mortality between 2019 and 2020. Increases in mortality from heart disease, diabetes, and external causes of death accounted for the adverse trend in all-cause mortality within the Black population.
Digital intervention increases influenza vaccination rates for people with diabetes in a decentralized randomized trial
JL Lee et al, NPJ Digital Medicine, September 17, 2021
(Posted: Sep 17, 2021 6AM)
People with diabetes (PWD) have an increased risk of developing influenza-related complications, including pneumonia, abnormal glycemic events, and hospitalization. Annual influenza vaccination is recommended for PWD, but vaccination rates are suboptimal. The study aimed to increase influenza vaccination rate in people with self-reported diabetes. This study was a prospective, 1:1 randomized controlled trial of a 6-month Digital Diabetes Intervention in U.S. adults with diabetes.
What is pharmacogenomics?
CB de Villiers, PHG Foundation, August 2021
(Posted: Aug 26, 2021 7AM)
Pharmacogenomics, a branch of precision medicine, is the study of genomic characteristics that affect how individuals respond to drugs. It could be useful for improving treatment for a wide variety of conditions such as depression, schizophrenia, heart disease, diabetes, cancer, and infectious diseases.
Innovative new model predicts glucose levels without poking or prodding
L Wedland et al, NPJ Digital Medicine, August 20, 2021
(Posted: Aug 20, 2021 11AM)
Non-invasive glucose monitoring once seemed like an impossible challenge, but today’s technology and the incredible work of Bent et al. promise a future in which daily fingersticks are obsolete. The new challenge will be realizing that promise in an accessible and practical way that benefits all patients.
Positive predictive value highlights four novel candidates for actionable genetic screening from analysis of 220,000 clinicogenomic records
KMS Barrett et al, Genetics in Medicine, August 13, 2021
(Posted: Aug 13, 2021 8AM)
We identify 74 statistically significant gene–disease associations across 27 genes. Seven of these conditions have a positive predictive value (PPV) of at least 30% in both cohorts. Three are already used in population screening programs (BRCA1, BRCA2, LDLR), and we also identify four new candidates for population screening: GCK with diabetes mellitus, HBB with ß-thalassemia minor and intermedia, PKD1 with cystic kidney disease, and MIP with cataracts.
Preventing type 1 diabetes in childhood.
Dayan Colin M et al. Science (New York, N.Y.) 2021 7 (6554) 506-510
(Posted: Jul 31, 2021 9AM)
Type 1 diabetes (T1D) is an autoimmune disease in which the insulin-producing ß cells of the pancreas are destroyed by T lymphocytes. Recent studies have demonstrated that monitoring for pancreatic islet autoantibodies, combined with genetic risk assessment, can identify most children who will develop T1D when they still have sufficient ß cell function to control glucose concentrations without the need for insulin.
Immunotherapy: Building a bridge to a cure for type 1 diabetes.
Bluestone Jeffrey A et al. Science (New York, N.Y.) 2021 7 (6554) 510-516
(Posted: Jul 31, 2021 9AM)
Over the past two decades, research has identified multiple immune cell types and soluble factors that destroy insulin-producing ß cells. These insights into disease pathogenesis have enabled the development of therapies to prevent and modify T1D. In this review, we highlight the key events that initiate and sustain pancreatic islet inflammation in T1D, the current state of the immunological therapies, and their advantages for the treatment of T1D.
Deep transfer learning and data augmentation improve glucose levels prediction in type 2 diabetes patients
Y Deng et al, NPJ Digital Medicine, July 14, 2021
(Posted: Jul 16, 2021 7AM)
We developed deep-learning methods to predict patient-specific blood glucose during various time horizons in the immediate future using patient-specific every 30-min long glucose measurements by the continuous glucose monitoring (CGM) to predict future glucose levels in 5?min to 1?h.
What Causes Type 2 Diabetes
CDC,July 2021
(Posted: Jul 13, 2021 7AM)
There’s more to why people get type 2 diabetes than you may know. Although lifestyle is a big part, so are family history, age, and race. Learn about what causes type 2 diabetes and how you can help lower your risk.
The penetrance of age-related monogenic disease depends on ascertainment context
UL Mirshahi et al, MEDRXIV, July 2, 2021
(Posted: Jul 02, 2021 7AM)
The background rate of diabetes, but not clinical features or variant type, explained the reduced penetrance in the unselected cohorts. In contrast, penetrance of mild hyperglycaemia for pathogenic GCK variants was similarly high across cohorts (ranging from 89 to 97%) despite substantial variation in the background rates of diabetes.
‘Nobody is catching it’: Algorithms used in health care nationwide are rife with bias
C Ross, Stat News, June 21, 2021
(Posted: Jun 21, 2021 8AM)
The algorithms carry out an array of crucial tasks: helping emergency rooms nationwide triage patients, predicting who will develop diabetes, and flagging patients who need more help to manage their medical conditions. But instead of making health care delivery more objective and precise, a new report finds, these algorithms — some of which have been in use for many years — are often making it more biased along racial and economic lines.
