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A significant number of studies invoked diabetes as a risk factor for virus infections, but the issue remains controversial. We aimed to examine whether non-autoimmune diabetes mellitus enhances the risk of virus infections compared with the risk in healthy individuals without non-autoimmune diabetes mellitus. In this systematic review and meta-analysis, we assessed case-control and cohort studies on the association between non-autoimmune diabetes and viruses. We searched PubMed, Embase, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, and Web of Science with no language restriction, to identify articles published until February 15, 2021. The main outcome assessment was the risk of virus infection in individuals with non-autoimmune diabetes. We used a random-effects model to pool individual studies and assessed heterogeneity (I2) using the χ2 test on Cochrane’s Q statistic. This study is registered with PROSPERO, number CRD42019134142. Out of 3136 articles identified, we included 68 articles (90 studies, as the number of virus and or diabetes phenotype varied between included articles). The summary OR between non-autoimmune diabetes and virus infections risk were, 10.8(95% CI: 10.3–11.4; 1-study) for SARS-CoV-2; 3.6(95%CI: 2.7–4.9, I2 = 91.7%; 43-studies) for HCV; 2.7(95% CI: 1.3–5.4, I2 = 89.9%, 8-studies;) for HHV8; 2.1(95% CI: 1.7–2.5; 1-study) for H1N1 virus; 1.6(95% CI: 1.2–2.13, I2 = 98.3%, 27-studies) for HBV; 1.5(95% CI: 1.1–2.0; 1-study) for HSV1; 3.5(95% CI: 0.6–18.3 , I2 = 83.9%, 5-studies) for CMV; 2.9(95% CI: 1–8.7, 1-study) for TTV; 2.6(95% CI: 0.7–9.1, 1-study) for Parvovirus B19; 0.7(95% CI: 0.3–1.5 , 1-study) for coxsackie B virus; and 0.2(95% CI: 0–6.2; 1-study) for HGV. Our findings suggest that, non-autoimmune diabetes is associated with increased susceptibility to viruses especially SARS-CoV-2, HCV, HHV8, H1N1 virus, HBV and HSV1. Thus, these viruses deserve more attention from diabetes health-care providers, researchers, policy makers, and stakeholders for improved detection, overall proper management, and efficient control of viruses in people with non-autoimmune diabetes.

Viruses have been considered potential triggers for the development of diabetes. This study assessed insulin secretion and insulin sensitivity in human herpesvirus 8 (HHV8)-infected and uninfected sub-Saharan African people with diabetes.In all, 173 people with non-autoimmune diabetes were enrolled consecutively: 124 with type 2 diabetes mellitus (T2DM) and 49 with ketosis-prone diabetes (KPD) admitted in hyperglycemic crisis. Those with KPD were further subdivided into those with new-onset ketotic-phase KPD (n = 34) or non-ketotic phase KPD (n = 15). All participants were screened for HHV8-specific antibodies and genomic DNA. Blood samples were collected for analysis of fasting glucose, HbA1c, lipid profile, and C-peptide, with insulin resistance and secretion estimated by homeostasis model assessment.Among the 173 diabetic participants, 88 (50.9%) were positive for HHV8 antibodies (Ac-HHV8+), including 15 (8.7%) positive for HHV8 DNA (DNA-HHV8+). The seroprevalence of HHV8 was similar between T2DM (55.6%) and KPD (61.2%) subjects. Of those with and without ketotic-phase KPD, 35.3% and 46.7% were Ac-HHV8+, respectively. Body mass index was significantly in lower DNA-HHV8+ than DNA-HHV8- subjects. Low-density lipoprotein and total cholesterol were significantly higher, but C-peptide and homeostatic model assessment of β-cell function (HOMA-β) were significantly lower in DNA-HHV8+ than DNA-HHV8- participants. After excluding DNA-HHV8+ participants, triglyceride concentrations were significantly higher in Ac-HHV8+ (n = 73) than Ac-HHV8- (n = 85) subjects. In contrast, HOMA-β was significantly higher among Ac-HHV8+ than Ac-HHV8- participants.In the present study, HHV8 DNA positivity was associated with low insulin secretion in this sub-Saharan African diabetes population.

Diabetes mellitus (DM) is associated with several musculoskeletal disorders. The incidence of DM and the life expectancy of the diabetic patient have both increased, resulting in the increased prevalence and clinical importance of musculoskeletal alterations in diabetic subjects. The exact pathophysiology of most of these musculoskeletal disorders remains obscure. Connective tissue disorders, neuropathy, vasculopathy or combinations of these problems, may underlie the increased incidence of musculoskeletal disorders in DM. The development of musculoskeletal disorders is dependent on age and on the duration of DM; however, it has been difficult to show a direct correlation with the metabolic control of DM. Most of these disorders can be diagnosed clinically, but some radiological examination may help, especially in differential diagnosis. No specific treatment is available, and treatments used in the general population are also recommended for diabetic subjects. Infectious complications affecting the musculoskeletal system are common in DM subjects, and these, possibly life-threatening, complications should be systematically discussed.

Despite a well-recognized clinical benefit of the 2nd generation tyrosine kinase inhibitor nilotinib in patients with imatinib-resistant/-intolerant or newly diagnosed chronic myeloid leukemia, recent evidence suggests that nilotinib has a propensity to increase the risk of occlusive arterial events, especially in patients with pre-existing cardiovascular risk factors. Given the key role of lipids in cardiovascular diseases, we studied the plasma lipid profile and global cardiovascular risk prior to and during nilotinib therapy in a series of 27 patients in the setting of an observationalsingle-center study. Data from a minimum 1-year follow-up showed that nilotinib significantly increased total, low and highdensity lipoprotein cholesterol within 3 months. Consequently, the proportion of patients with non-optimal low density lipoprotein cholesterol increased from 48.1% to 88.9% by 12 months, leading to cholesterol-lowering drug intervention in 22.2% of patients. The proportion of patients with low levels of high density lipoprotein cholesterol decreased from 40.7% to 7.4% by 12 months. In contrast, a significant decrease in triglycerides was observed. Global cardiovascular risk worsened in 11.1% of patients due to diabetes or occlusive arterial events. Whether hypercholesterolemia was the main driver of occlusive arterial events was uncertain: a longer follow-up is necessary to ask whether nilotinib-induced hypercholesterolemia increaseslong-term risk of atherosclerotic diseases. Nevertheless, given keyatherogenicproperties of low density lipoprotein cholesterol, we conclude that when prescribing nilotinib, commitment to detect lipid disordersat baseline and during follow-up is mandatory given their frequency, requirement for lifestyle or drug intervention and potential for long-term cardiovascular complications.

Abstract 1686 Background: ENESTnd established the superior efficacy of frontline NIL vs IM in pts with CML-CP. An association between NIL treatment and hyperglycemia has been previously reported. NIL-mediated increases in fasting plasma glucose levels (FGLs) have been shown to be reversible, with levels returning to normal on treatment discontinuation; in contrast, IM has been shown to decrease FGLs in pts with diabetes (Breccia M, Alimena G. Leuk Res. 2009;33:871–875). Here, we report the incidence of hyperglycemia and related glycemic outcomes with NIL and IM by 3 y in ENESTnd. Methods: Pts were randomized to receive NIL 300 mg twice daily (BID; n = 282), NIL 400 mg BID (n = 281), or IM 400 mg once daily (QD; n = 283). This analysis included randomized pts who had ≥1 dose of study drug and no drug treatment for diabetes mellitus /prediabetes at baseline (BL; 264, 262, and 267 pts in the NIL 300 mg BID, NIL 400 mg BID, and IM arms, respectively); pts with treated diabetes at BL (15, 15, and 13 pts, respectively) were excluded. Hyperglycemia was defined as FGL ≥1.1 g/L, prediabetes as FGL ≥1.1 g/L to < 1.26 g/L or glycated hemoglobin (HbA1C) ≥5.7% to < 6.5%, and diabetes as FGL ≥1.26 g/L or HbA1C ≥6.5%. These criteria represent a combination of World Health Organization and American Diabetes Association guidelines. Results: At BL, median age and mean body mass index (BMI) were similar across the 3 arms (Table). In the NIL 300 mg BID, NIL 400 mg BID, and IM arms, respectively, 34.9%, 35.5%, and 37.8% of pts had untreated prediabetes at BL, and 6.1%, 6.1%, and 3.4% of pts had untreated diabetes at BL. Median time on treatment in the 3 arms was similar (≈ 3 y). Cumulative incidence of hyperglycemia by 3 y was higher with NIL vs IM (Table). By 3 y, grade 3/4 hyperglycemia was reported in 6 (2.3%), 7 (2.7%), and 0 pts on NIL 300 mg BID, NIL 400 mg BID, and IM, respectively; no pt discontinued due to hyperglycemia. Median time to hyperglycemia was longer with NIL 300 mg BID than with NIL 400 mg BID. From BL to 3 y, there were minimal changes in mean BMI and mean HbA1C in all 3 arms; greater increases in mean fasting insulin were observed with NIL vs IM. Excluding pts with diabetes at BL, 20.1%, 22.8%, and 8.9% of pts developed diabetes by 3 y, and 48.8%, 51.6%, and 50.0% developed prediabetes by 3 y (NIL 300 mg BID, NIL 400 mg BID, and IM, respectively). Relatively few pts required antidiabetic medication by 3 y. Based on a multivariate analysis, prediabetes at BL was a risk factor for development of hyperglycemia in all 3 treatment arms (P =.0252.0004, and.0296 [NIL 300 mg BID, NIL 400 mg BID, and IM arms, respectively]). Age > 60 y at BL was a risk factor for NIL 300 mg BID (P =.0183) and IM (P =.0010) but was not a risk factor for NIL 400 mg BID (P =.6001). Dyslipidemia (P =.0455) at BL was identified as an additional risk factor for development of hyperglycemia on IM in the multivariate analysis. Conclusions: In ENESTnd, the incidence of hyperglycemia by 3 y was higher with NIL vs IM. However, most events were low grade, HbA1C levels remained stable over time, and few pts required antidiabetic medication. The underlying mechanism of action driving NIL-mediated hyperglycemia is unknown, but the increases in fasting insulin observed suggest NIL therapy is associated with insulin resistance. NIL-treated pts with CML-CP and BL risk factors for diabetes should be monitored closely. Disclosures: Delphine: Novartis: Honoraria; BMS: Honoraria; Teva: Honoraria. Gautier:Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees. Breccia:Novartis: Honoraria; BMS: Honoraria; Celgene: Honoraria. Saglio:Novartis: Consultancy, Speakers Bureau; BMS: Consultancy, Speakers Bureau; Pfizer: Consultancy. Hughes:Novartis: Consultancy, Honoraria, Research Funding; BMS: Consultancy, Honoraria, Research Funding; Ariad: Consultancy, Honoraria; CSL: Research Funding. Kantarjian:Novartis Pharmaceuticals Corp: Consultancy, Research Funding; BMS: Research Funding; Pfizer: Research Funding. Kemp:Novartis Pharmaceuticals Corp: Employment. Gao:Novartis: Employment. Piccolo:Novartis Pharma AG: Employment. Larson:Novartis: Consultancy, Honoraria, Research Funding; BMS: Consultancy, Research Funding; Pfizer: Consultancy; Ariad: Consultancy, Research Funding. Hochhaus:BMS: Consultancy, Honoraria, Research Funding; Pfizer: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria, Research Funding; Ariad: Consultancy, Honoraria, Research Funding.

Introduction The extent to which postprandial glucagon reductions contribute to lowering of postprandial glucose in patients with type 2 diabetes mellitus (T2DM) is currently unknown. The aim of this analysis was to determine whether a reduction in postprandial glucagon following treatment with the glucagon-like peptide-1 receptor agonist lixisenatide correlates with a reduction in postprandial glucose and glycated hemoglobin (HbA1c) in patients with T2DM. Methods A post hoc analysis was performed on pooled data from the modified intent-to-treat populations of two lixisenatide Phase 3 trials: GetGoal-M (lixisenatide versus placebo as add-on to metformin) and GetGoal-S (lixisenatide versus placebo as add-on to sulfonylurea [SU] ± metformin). Glucagon levels were assessed 2 h after a standardized meal test performed at baseline and Week 24 and were examined for correlation with changes in 2-h postprandial glucose and HbA1c. Results Lixisenatide reduced 2-h postprandial glucagon at Week 24 compared with placebo (P