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  • 1
    In: Communications Medicine, Springer Science and Business Media LLC, Vol. 3, No. 1 ( 2023-10-05)
    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. Methods Screening of 835 peer-reviewed articles was followed by systematic review of 70 of them (focusing on randomized trials and extension studies with ≥50 participants from the past 10 years). Results We find that novel technologies, ranging from continuous glucose monitoring systems, insulin pumps and decision support tools to the most advanced hybrid closed loop systems, improve important measures like HbA1c, time in range, and glycemic variability, while reducing hypoglycemia risk. Several studies included person-reported outcomes, allowing assessment of the burden or benefit of the technology in the lives of those with type 1 diabetes, demonstrating positive results or, at a minimum, no increase in self-care burden compared with standard care. Important limitations of the trials to date are their small size, the scarcity of pre-planned or powered analyses in sub-populations such as children, racial/ethnic minorities, people with advanced complications, and variations in baseline glycemic levels. In addition, confounders including education with device initiation, concomitant behavioral modifications, and frequent contact with the healthcare team are rarely described in enough detail to assess their impact. Conclusions Our review highlights the potential of technology in the treatment of people living with type 1 diabetes and provides suggestions for optimization of outcomes and areas of further study for precision medicine-directed technology use in type 1 diabetes.
    Type of Medium: Online Resource
    ISSN: 2730-664X
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
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  • 2
    In: Communications Medicine, Springer Science and Business Media LLC, Vol. 3, No. 1 ( 2023-10-05)
    Abstract: Type 1 diabetes (T1D) results from immune-mediated destruction of insulin-producing beta cells. Prevention efforts have focused on immune modulation and supporting beta cell health before or around diagnosis; however, heterogeneity in disease progression and therapy response has limited translation to clinical practice, highlighting the need for precision medicine approaches to T1D disease modification. Methods To understand the state of knowledge in this area, we performed a systematic review of randomized-controlled trials with $$\ge$$ ≥ 50 participants cataloged in PubMed or Embase from the past 25 years testing T1D disease-modifying therapies and/or identifying features linked to treatment response, analyzing bias using a Cochrane-risk-of-bias instrument. Results We identify and summarize 75 manuscripts, 15 describing 11 prevention trials for individuals with increased risk for T1D, and 60 describing treatments aimed at preventing beta cell loss at disease onset. Seventeen interventions, mostly immunotherapies, show benefit compared to placebo (only two prior to T1D onset). Fifty-seven studies employ precision analyses to assess features linked to treatment response. Age, beta cell function measures, and immune phenotypes are most frequently tested. However, analyses are typically not prespecified, with inconsistent methods of reporting, and tend to report positive findings. Conclusions While the quality of prevention and intervention trials is overall high, the low quality of precision analyses makes it difficult to draw meaningful conclusions that inform clinical practice. To facilitate precision medicine approaches to T1D prevention, considerations for future precision studies include the incorporation of uniform outcome measures, reproducible biomarkers, and prespecified, fully powered precision analyses into future trial design.
    Type of Medium: Online Resource
    ISSN: 2730-664X
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
    detail.hit.zdb_id: 3096949-9
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  • 3
    In: Children, MDPI AG, Vol. 9, No. 12 ( 2022-11-23), p. 1797-
    Abstract: Background: asthma, a chronic respiratory disease caused by inflammation and narrowing of the small airways in the lungs, is the most common chronic childhood disease. Prevalence of childhood asthma in the United States is 5.8%. In boys, prevalence is 5.7% and it is 6% in girls. Asthma is associated with other comorbidities such as major depressive disorder and anxiety disorder. This study explores the association between asthma and depression. Methods: we conducted a retrospective cross-sectional study using NHANES data from 2013 to 2018. Asthma and childhood onset asthma were assessed using questionnaires MCQ010 and MCQ025, respectively. Sociodemographic variables were summarized, and univariate analysis was performed to determine the association between asthma and major depressive disorder and its individual symptoms. Results: there were 402,167 participants from 2013–2018 in our study: no asthma in 84.70%; asthma in 15.30%. Childhood onset asthma (COA) included 10.51% and adult-onset asthma (AOA) included 4.79%. Median age of COA is 5 years and AOA is 41 years. Among the asthma groups, most AOA were females (67.77%, p 〈 0.0001), most COA were males (52.16%, p 〈 0.0001), and ethnicity was predominantly White in AOA (42.39%, p 〈 0001) and in COA (35.24%, p 〈 0.0001). AOA mostly had annual household income from $0–24,999 (35.91%, p 〈 0.0001), while COA mostly had annual household income from $25,000–64,999 (36.66%, p 〈 0.0001). There was a significantly higher prevalence of MDD in COA (38.90%) and AOA (47.30%) compared to NOA (31.91%). Frequency of symptoms related to MDD were found to have a significantly higher prevalence and severity in the asthma groups compared to no asthma, and slightly greater and more severe in AOA than in COA. Symptoms include having little interest in doing things (COA 18.38% vs. AOA 22.50% vs. NOA 15.44%), feeling down, depressed, or hopeless (COA 20.05% vs. AOA 22.77% vs. NOA 15.85%), having trouble sleeping or sleeping too much (COA 27.38% vs. AOA 23.15% vs. NOA 22.24%), feeling tired or having little energy (COA 39.17% vs. AOA 34.24% vs. NOA 33.97%), having poor appetite or overeating (COA 19.88% vs. AOA 20.02% vs. NOA 15.11%), feeling bad about yourself (COA 13.90% vs. AOA 13.79% vs. NOA 10.78%), having trouble concentrating on things (COA 12.34% vs. AOA 14.41% vs. NOA 10.06%), moving or speaking slowly or too fast (COA 8.59% vs. AOA 9.72% vs. NOA 6.09%), thinking you would be better off dead (COA 3.12% vs. AOA 4.38% vs. NOA 1.95%) and having the difficulties these problems have caused (COA 21.66% vs. AOA 26.73% vs. NOA 19.34%, p 〈 0.0001). Conclusion: MDD and related symptoms were significantly higher and more severe in participants with asthma compared to no asthma. Between adult-onset asthma compared to childhood onset asthma, adult-onset asthma had slightly greater and more severe MDD and related symptoms compared to childhood onset asthma.
    Type of Medium: Online Resource
    ISSN: 2227-9067
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2732685-8
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  • 4
    In: Nature Medicine, Springer Science and Business Media LLC
    Type of Medium: Online Resource
    ISSN: 1078-8956 , 1546-170X
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
    detail.hit.zdb_id: 1484517-9
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  • 5
    In: Communications Medicine, Springer Science and Business Media LLC, Vol. 3, No. 1 ( 2023-10-05)
    Abstract: Monogenic diabetes presents opportunities for precision medicine but is underdiagnosed. This review systematically assessed the evidence for (1) clinical criteria and (2) methods for genetic testing for monogenic diabetes, summarized resources for (3) considering a gene or (4) variant as causal for monogenic diabetes, provided expert recommendations for (5) reporting of results; and reviewed (6) next steps after monogenic diabetes diagnosis and (7) challenges in precision medicine field. Methods Pubmed and Embase databases were searched (1990-2022) using inclusion/exclusion criteria for studies that sequenced one or more monogenic diabetes genes in at least 100 probands (Question 1), evaluated a non-obsolete genetic testing method to diagnose monogenic diabetes (Question 2). The risk of bias was assessed using the revised QUADAS-2 tool. Existing guidelines were summarized for questions 3-5, and review of studies for questions 6-7, supplemented by expert recommendations. Results were summarized in tables and informed recommendations for clinical practice. Results There are 100, 32, 36, and 14 studies included for questions 1, 2, 6, and 7 respectively. On this basis, four recommendations for who to test and five on how to test for monogenic diabetes are provided. Existing guidelines for variant curation and gene-disease validity curation are summarized. Reporting by gene names is recommended as an alternative to the term MODY. Key steps after making a genetic diagnosis and major gaps in our current knowledge are highlighted. Conclusions We provide a synthesis of current evidence and expert opinion on how to use precision diagnostics to identify individuals with monogenic diabetes.
    Type of Medium: Online Resource
    ISSN: 2730-664X
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
    detail.hit.zdb_id: 3096949-9
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  • 6
    In: Communications Medicine, Springer Science and Business Media LLC, Vol. 3, No. 1 ( 2023-10-05)
    Abstract: A precision medicine approach in type 2 diabetes requires the identification of clinical and biological features that are reproducibly associated with differences in clinical outcomes with specific anti-hyperglycaemic therapies. Robust evidence of such treatment effect heterogeneity could support more individualized clinical decisions on optimal type 2 diabetes therapy. Methods We performed a pre-registered systematic review of meta-analysis studies, randomized control trials, and observational studies evaluating clinical and biological features associated with heterogenous treatment effects for SGLT2-inhibitor and GLP1-receptor agonist therapies, considering glycaemic, cardiovascular, and renal outcomes. After screening 5,686 studies, we included 101 studies of SGLT2-inhibitors and 75 studies of GLP1-receptor agonists in the final systematic review. Results Here we show that the majority of included papers have methodological limitations precluding robust assessment of treatment effect heterogeneity. For SGLT2-inhibitors, multiple observational studies suggest lower renal function as a predictor of lesser glycaemic response, while markers of reduced insulin secretion predict lesser glycaemic response with GLP1-receptor agonists. For both therapies, multiple post-hoc analyses of randomized control trials (including trial meta-analysis) identify minimal clinically relevant treatment effect heterogeneity for cardiovascular and renal outcomes. Conclusions Current evidence on treatment effect heterogeneity for SGLT2-inhibitor and GLP1-receptor agonist therapies is limited, likely reflecting the methodological limitations of published studies. Robust and appropriately powered studies are required to understand type 2 diabetes treatment effect heterogeneity and evaluate the potential for precision medicine to inform future clinical care.
    Type of Medium: Online Resource
    ISSN: 2730-664X
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
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  • 7
    In: Communications Medicine, Springer Science and Business Media LLC, Vol. 3, No. 1 ( 2023-10-05)
    Abstract: The variability in the effectiveness of type 2 diabetes (T2D) preventive interventions highlights the potential to identify the factors that determine treatment responses and those that would benefit the most from a given intervention. We conducted a systematic review to synthesize the evidence to support whether sociodemographic, clinical, behavioral, and molecular factors modify the efficacy of dietary or lifestyle interventions to prevent T2D. Methods We searched MEDLINE, Embase, and Cochrane databases for studies reporting on the effect of a lifestyle, dietary pattern, or dietary supplement interventions on the incidence of T2D and reporting the results stratified by any effect modifier. We extracted relevant statistical findings and qualitatively synthesized the evidence for each modifier based on the direction of findings reported in available studies. We used the Diabetes Canada Clinical Practice Scale to assess the certainty of the evidence for a given effect modifier. Results The 81 publications that met our criteria for inclusion are from 33 unique trials. The evidence is low to very low to attribute variability in intervention effectiveness to individual characteristics such as age, sex, BMI, race/ethnicity, socioeconomic status, baseline behavioral factors, or genetic predisposition. Conclusions We report evidence, albeit low certainty, that those with poorer health status, particularly those with prediabetes at baseline, tend to benefit more from T2D prevention strategies compared to healthier counterparts. Our synthesis highlights the need for purposefully designed clinical trials to inform whether individual factors influence the success of T2D prevention strategies.
    Type of Medium: Online Resource
    ISSN: 2730-664X
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
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  • 8
    In: Communications Medicine, Springer Science and Business Media LLC, Vol. 3, No. 1 ( 2023-10-05)
    Abstract: Gestational Diabetes Mellitus (GDM) affects approximately 1 in 7 pregnancies globally. It is associated with short- and long-term risks for both mother and baby. Therefore, optimizing treatment to effectively treat the condition has wide-ranging beneficial effects. However, despite the known heterogeneity in GDM, treatment guidelines and approaches are generally standardized. We hypothesized that a precision medicine approach could be a tool for risk-stratification of women to streamline successful GDM management. With the relatively short timeframe available to treat GDM, commencing effective therapy earlier, with more rapid normalization of hyperglycaemia, could have benefits for both mother and fetus. Methods We conducted two systematic reviews, to identify precision markers that may predict effective lifestyle and pharmacological interventions. Results There was a paucity of studies examining precision lifestyle-based interventions for GDM highlighting the pressing need for further research in this area. We found a number of precision markers identified from routine clinical measures that may enable earlier identification of those requiring escalation of pharmacological therapy (to metformin, sulphonylureas or insulin). This included previous history of GDM, Body Mass Index and blood glucose concentrations at diagnosis. Conclusions Clinical measurements at diagnosis could potentially be used as precision markers in the treatment of GDM. Whether there are other sensitive markers that could be identified using more complex individual-level data, such as omics, and if these can feasibly be implemented in clinical practice remains unknown. These will be important to consider in future studies.
    Type of Medium: Online Resource
    ISSN: 2730-664X
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
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  • 9
    In: Communications Medicine, Springer Science and Business Media LLC, Vol. 3, No. 1 ( 2023-10-05)
    Abstract: Heterogeneity in type 2 diabetes presentation and progression suggests that precision medicine interventions could improve clinical outcomes. We undertook a systematic review to determine whether strategies to subclassify type 2 diabetes were associated with high quality evidence, reproducible results and improved outcomes for patients. Methods We searched PubMed and Embase for publications that used ‘simple subclassification’ approaches using simple categorisation of clinical characteristics, or ‘complex subclassification’ approaches which used machine learning or ‘omics approaches in people with established type 2 diabetes. We excluded other diabetes subtypes and those predicting incident type 2 diabetes. We assessed quality, reproducibility and clinical relevance of extracted full-text articles and qualitatively synthesised a summary of subclassification approaches. Results Here we show data from 51 studies that demonstrate many simple stratification approaches, but none have been replicated and many are not associated with meaningful clinical outcomes. Complex stratification was reviewed in 62 studies and produced reproducible subtypes of type 2 diabetes that are associated with outcomes. Both approaches require a higher grade of evidence but support the premise that type 2 diabetes can be subclassified into clinically meaningful subtypes. Conclusion Critical next steps toward clinical implementation are to test whether subtypes exist in more diverse ancestries and whether tailoring interventions to subtypes will improve outcomes.
    Type of Medium: Online Resource
    ISSN: 2730-664X
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
    detail.hit.zdb_id: 3096949-9
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  • 10
    In: Communications Medicine, Springer Science and Business Media LLC, Vol. 3, No. 1 ( 2023-12-18)
    Abstract: Perinatal outcomes vary for women with gestational diabetes mellitus (GDM). The precise factors beyond glycemic status that may refine GDM diagnosis remain unclear. We conducted a systematic review and meta-analysis of potential precision markers for GDM. Methods Systematic literature searches were performed in PubMed and EMBASE from inception to March 2022 for studies comparing perinatal outcomes among women with GDM. We searched for precision markers in the following categories: maternal anthropometrics, clinical/sociocultural factors, non-glycemic biochemical markers, genetics/genomics or other -omics, and fetal biometry. We conducted post-hoc meta-analyses of a subset of studies with data on the association of maternal body mass index (BMI, kg/m 2 ) with offspring macrosomia or large-for-gestational age (LGA). Results A total of 5905 titles/abstracts were screened, 775 full-texts reviewed, and 137 studies synthesized. Maternal anthropometrics were the most frequent risk marker. Meta-analysis demonstrated that women with GDM and overweight/obesity vs. GDM with normal range BMI are at higher risk of offspring macrosomia (13 studies [ n = 28,763]; odds ratio [OR] 2.65; 95% Confidence Interval [CI] 1.91, 3.68), and LGA (10 studies [ n = 20,070]; OR 2.23; 95% CI 2.00, 2.49). Lipids and insulin resistance/secretion indices were the most studied non-glycemic biochemical markers, with increased triglycerides and insulin resistance generally associated with greater risk of offspring macrosomia or LGA. Studies evaluating other markers had inconsistent findings as to whether they could be used as precision markers. Conclusions Maternal overweight/obesity is associated with greater risk of offspring macrosomia or LGA in women with GDM. Pregnancy insulin resistance or hypertriglyceridemia may be useful in GDM risk stratification. Future studies examining non-glycemic biochemical, genetic, other -omic, or sociocultural precision markers among women with GDM are warranted.
    Type of Medium: Online Resource
    ISSN: 2730-664X
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
    detail.hit.zdb_id: 3096949-9
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