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Metformin is used for the treatment of insulin resistant diabetes. Diabetics are at an increased risk of developing dementia. Recent epidemiological studies suggest that metformin treatment prevents cognitive decline in diabetics. A pilot clinical study found cognitive improvement with metformin in patients with mild cognitive impairment (MCI). Preclinical studies suggest metformin reduces Alzheimer-like pathology in mouse models of Alzheimer's disease (AD). In the current study, we used 11-month-old SAMP8 mice. Mice were given daily injections of metformin at 20 mg/kg/sc or 200 mg/kg/sc for eight weeks. After four weeks, mice were tested in T-maze footshock avoidance, object recognition, and Barnes maze. At the end of the study, brain tissue was collected for analysis of PKC (PKCζ, PKCι, PKCα, PKCγ, PKCɛ), GSK-3β, pGSK-3βser9, pGSK-3βtyr216, pTau404, and APP. Metformin improved both acquisition and retention in SAMP8 mice in T-maze footshock avoidance, retention in novel object recognition, and acquisition in the Barnes maze. Biochemical analysis indicated that metformin increased both atypical and conventional forms of PKC; PKCζ, and PKCα at 20 mg/kg. Metformin significantly increased pGSK-3βser9 at 200 mg/kg, and decreased Aβ at 20 mg/kg and pTau404 and APPc99 at both 20 mg/kg and 200 mg/kg. There were no differences in blood glucose levels between the aged vehicle and metformin treated mice. Metformin improved learning and memory in the SAMP8 mouse model of spontaneous onset AD. Biochemical analysis indicates that metformin improved memory by decreasing APPc99 and pTau. The current study lends support to the therapeutic potential of metformin for AD.

Metformin hydrochloride (Met) is the first-line drug to treat type 2 diabetes and has shown high efficiency in reducing Alzheimer's disease in recent studies. Herein, a borneol W/O/W composite submicron emulsion containing Met (B-Met-W/O/W SE) was prepared, expecting longer in-vivo circulation time, better bioavailability and brain targeting of Met drug. In the optimized formulation, the mean droplets size, polydispersity index and encapsulation efficiency of the composite were 386.5 nm, 0.219 and 87.26%, respectively. FTIR analysis confirmed that Met interacted with carriers in B-Met-W/O/W SE. Compared with Met free drug, in-vitro release of Met in B-Met-W/O/W SE delivery system was much slower. In pharmacokinetic studies in rats, the AUC, MRT and t of the B-Met-W/O/W SE system were respectively 1.27, 2.49 and 4.02-fold higher than Met free drug system. The drug-targeting index of B-Met-W/O/W SE system to the brain tissue was also higher than that of Met free drug system and Met-W/O/W SE system. These results indicated that B-Met-W/O/W SE drug delivery system is a promising candidate in treating clinical Alzheimer's disease.
Copyright © 2019 Elsevier B.V. All rights reserved.

Metformin is a first-line drug for the treatment of individuals with type 2 diabetes, yet its precise mechanism of action remains unclear. Metformin exerts its antihyperglycemic action primarily through lowering hepatic glucose production (HGP). This suppression is thought to be mediated through inhibition of mitochondrial respiratory complex I, and thus elevation of 5'-adenosine monophosphate (AMP) levels and the activation of AMP-activated protein kinase (AMPK), though this proposition has been challenged given results in mice lacking hepatic AMPK. Here we report that the AMP-inhibited enzyme fructose-1,6-bisphosphatase-1 (FBP1), a rate-controlling enzyme in gluconeogenesis, functions as a major contributor to the therapeutic action of metformin. We identified a point mutation in FBP1 that renders it insensitive to AMP while sparing regulation by fructose-2,6-bisphosphate (F-2,6-P), and knock-in (KI) of this mutant in mice significantly reduces their response to metformin treatment. We observe this during a metformin tolerance test and in a metformin-euglycemic clamp that we have developed. The antihyperglycemic effect of metformin in high-fat diet-fed diabetic FBP1-KI mice was also significantly blunted compared to wild-type controls. Collectively, we show a new mechanism of action for metformin and provide further evidence that molecular targeting of FBP1 can have antihyperglycemic effects.

PURPOSE - Several observational studies suggest that metformin reduces incidence cancer risk; however, many of these studies suffer from time-related biases and several cancer outcomes have not been investigated due to small sample sizes.
METHODS - We constructed a propensity score-matched retrospective cohort of 84,434 veterans newly prescribed metformin or a sulfonylurea as monotherapy. We used Cox proportional hazard regression to assess the association between metformin use compared to sulfonylurea use and incidence cancer risk for 10 solid tumors. We adjusted for clinical covariates including hemoglobin A1C, antihypertensive and lipid-lowering medications, and body mass index. Incidence cancers were defined by ICD-9-CM codes.
RESULTS - Among 42,217 new metformin users and 42,217 matched-new sulfonylurea users, we identified 2,575 incidence cancers. Metformin was inversely associated with liver cancer (adjusted hazard ratio [aHR] = 0.44, 95% CI 0.31, 0.64) compared to sulfonylurea. We found no association between metformin use and risk of incidence bladder, breast, colorectal, esophageal, gastric, lung, pancreatic, prostate, or renal cancer when compared to sulfonylurea use.
CONCLUSIONS - In this large cohort study that accounted for time-related biases, we observed no association between the use of metformin and most cancers; however, we found a strong inverse association between metformin and liver cancer. Randomized trials of metformin for prevention of liver cancer would be useful to verify these observations.

BACKGROUND - Medications that impact insulin sensitivity or cause weight gain may increase heart failure risk. Our aim was to compare heart failure and cardiovascular death outcomes among patients initiating sulfonylureas for diabetes mellitus treatment versus metformin.
METHODS AND RESULTS - National Veterans Health Administration databases were linked to Medicare, Medicaid, and National Death Index data. Veterans aged ≥18 years who initiated metformin or sulfonylureas between 2001 and 2011 and whose creatinine was <1.4 (females) or 1.5 mg/dL (males) were included. Each metformin patient was propensity score-matched to a sulfonylurea initiator. The outcome was hospitalization for acute decompensated heart failure as the primary reason for admission or a cardiovascular death. There were 126 867 and 79 192 new users of metformin and sulfonylurea, respectively. Propensity score matching yielded 65 986 per group. Median age was 66 years, and 97% of patients were male; hemoglobin A 6.9% (6.3, 7.7); body mass index 30.7 kg/m (27.4, 34.6); and 6% had heart failure history. There were 1236 events (1184 heart failure hospitalizations and 52 cardiovascular deaths) among sulfonylurea initiators and 1078 events (1043 heart failure hospitalizations and 35 cardiovascular deaths) among metformin initiators. There were 12.4 versus 8.9 events per 1000 person-years of use (adjusted hazard ratio 1.32, 95%CI 1.21, 1.43). The rate difference was 4 heart failure hospitalizations or cardiovascular deaths per 1000 users of sulfonylureas versus metformin annually.
CONCLUSIONS - Predominantly male patients initiating treatment for diabetes mellitus with sulfonylurea had a higher risk of heart failure and cardiovascular death compared to similar patients initiating metformin.
© 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

BACKGROUND AND OBJECTIVES - Diabetes is the leading cause of ESRD. Glucose control improves kidney outcomes. Most patients eventually require treatment intensification with second-line medications; however, the differential effects of those therapies on kidney function are unknown.
DESIGN, SETTING, PARTICIPANTS & MEASUREMENTS - We studied a retrospective cohort of veterans on metformin monotherapy from 2001 to 2008 who added either insulin or sulfonylurea and were followed through September of 2011. We used propensity score matching 1:4 for those who intensified with insulin versus sulfonylurea, respectively. The primary composite outcome was persistent decline in eGFR≥35% from baseline (GFR event) or a diagnosis of ESRD. The secondary outcome was a GFR event, ESRD, or death. Outcome risks were compared using marginal structural models to account for time-varying covariates. The primary analysis required persistence with the intensified regimen. An effect modification of baseline eGFR and the intervention on both outcomes was evaluated.
RESULTS - There were 1989 patients on metformin and insulin and 7956 patients on metformin and sulfonylurea. Median patient age was 60 years old (interquartile range, 54-67), median hemoglobin A1c was 8.1% (interquartile range, 7.1%-9.9%), and median creatinine was 1.0 mg/dl (interquartile range, 0.9-1.1). The rate of GFR event or ESRD (primary outcome) was 31 versus 26 per 1000 person-years for those who added insulin versus sulfonylureas, respectively (adjusted hazard ratio, 1.27; 95% confidence interval, 0.99 to 1.63). The rate of GFR event, ESRD, or death was 64 versus 49 per 1000 person-years, respectively (adjusted hazard ratio, 1.33; 95% confidence interval, 1.11 to 1.59). Tests for a therapy by baseline eGFR interaction for both the primary and secondary outcomes were not significant (P=0.39 and P=0.12, respectively).
CONCLUSIONS - Among patients who intensified metformin monotherapy, the addition of insulin compared with a sulfonylurea was not associated with a higher rate of kidney outcomes but was associated with a higher rate of the composite outcome that included death. These risks were not modified by baseline eGFR.
Copyright © 2016 by the American Society of Nephrology.

One-third of type-2 diabetic patients respond poorly to metformin. Despite extensive research, the impact of genetic and nongenetic factors on long-term outcome is unknown. In this study we combine nonlinear mixed effect modeling with computational genetic methodologies to identify predictors of long-term response. In all, 1,056 patients contributed their genetic, demographic, and long-term HbA1c data. The top nine variants (of 12,000 variants in 267 candidate genes) accounted for approximately one-third of the variability in the disease progression parameter. Average serum creatinine level, age, and weight were determinants of symptomatic response; however, explaining negligible variability. Two single nucleotide polymorphisms (SNPs) in CSMD1 gene (rs2617102, rs2954625) and one SNP in a pharmacologically relevant SLC22A2 gene (rs316009) influenced disease progression, with minor alleles leading to less and more favorable outcomes, respectively. Overall, our study highlights the influence of genetic factors on long-term HbA1c response and provides a computational model, which when validated, may be used to individualize treatment.
© 2016 American Society for Clinical Pharmacology and Therapeutics.

BACKGROUND - To describe common type 2 diabetes treatment intensification regimens, patients' characteristics and changes in glycated hemoglobin (HbA1c) and body mass index (BMI).
METHODS - We constructed a national retrospective cohort of veterans initially treated for diabetes with either metformin or sulfonylurea from 2001 through 2008, using Veterans Health Administration (VHA) and Medicare data. Patients were followed through September, 2011 to identify common diabetes treatment intensification regimens. We evaluated changes in HbA1c and BMI post-intensification for metformin-based regimens.
RESULTS - We identified 323,857 veterans who initiated diabetes treatment. Of these, 55 % initiated metformin, 43 % sulfonylurea and 2 % other regimens. Fifty percent (N = 89,057) of metformin initiators remained on metformin monotherapy over a median follow-up 58 months (interquartile range [IQR] 35, 74). Among 80,725 patients who intensified metformin monotherapy, the four most common regimens were addition of sulfonylurea (79 %), thiazolidinedione [TZD] (6 %), or insulin (8 %), and switch to insulin monotherapy (2 %). Across these regimens, median HbA1c values declined from a range of 7.0-7.8 % (53-62 mmol/mol) at intensification to 6.6-7.0 % (49-53 mmol/mol) at 1 year, and remained stable up to 3 years afterwards. Median BMI ranged between 30.5 and 32 kg/m(2) at intensification and increased very modestly in those who intensified with oral regimens, but 1-2 kg/m(2) over 3 years among those who intensified with insulin-based regimens.
CONCLUSIONS - By 1 year post-intensification of metformin monotherapy, HbA1c declined in all four common intensification regimens, and remained close to 7 % in subsequent follow-up. BMI increased substantially for those on insulin-based regimens.

BACKGROUND - Hypoglycemia remains a common life-threatening event associated with diabetes treatment. We compared the risk of first or recurrent hypoglycemia event among metformin initiators who intensified treatment with insulin versus sulfonylurea.
METHODS - We assembled a retrospective cohort using databases of the Veterans Health Administration, Medicare and the National Death Index. Metformin initiators who intensified treatment with insulin or sulfonylurea were followed to either their first or recurrent hypoglycemia event using Cox proportional hazard models. Hypoglycemia was defined as hospital admission or an emergency department visit for hypoglycemia, or an outpatient blood glucose value of less than 3.3 mmol/L. We conducted additional analyses for risk of first hypoglycemia event, with death as the competing risk.
RESULTS - Among 178,341 metformin initiators, 2948 added insulin and 39,990 added sulfonylurea. Propensity score matching yielded 2436 patients taking metformin plus insulin and 12,180 taking metformin plus sulfonylurea. Patients took metformin for a median of 14 (interquartile range [IQR] 5-30) months, and the median glycated hemoglobin level was 8.1% (IQR 7.2%-9.9%) at intensification. In the group who added insulin, 121 first hypoglycemia events occurred, and 466 first events occurred in the group who added sulfonylurea (30.9 v. 24.6 events per 1000 person-years; adjusted hazard ratio [HR] 1.30, 95% confidence interval [CI] 1.06-1.59). For recurrent hypoglycemia, there were 159 events in the insulin group and 585 events in the sulfonylurea group (39.1 v. 30.0 per 1000 person-years; adjusted HR 1.39, 95% CI 1.12-1.72). In separate competing risk analyses, the adjusted HR for hypoglycemia was 1.28 (95% CI 1.04-1.56).
INTERPRETATION - Among patients using metformin who could use either insulin or sulfonylurea, the addition of insulin was associated with a higher risk of hypoglycemia than the addition of sulfonylurea. This finding should be considered by patients and clinicians when discussing the risks and benefits of adding insulin versus a sulfonylurea.
© 2016 Canadian Medical Association or its licensors.

A drug exerts its effects typically through a signal transduction cascade, which is non-linear and involves intertwined networks of multiple signaling pathways. Construction of such a signaling pathway network (SPNetwork) can enable identification of novel drug targets and deep understanding of drug action. However, it is challenging to synopsize critical components of these interwoven pathways into one network. To tackle this issue, we developed a novel computational framework, the Drug-specific Signaling Pathway Network (DSPathNet). The DSPathNet amalgamates the prior drug knowledge and drug-induced gene expression via random walk algorithms. Using the drug metformin, we illustrated this framework and obtained one metformin-specific SPNetwork containing 477 nodes and 1,366 edges. To evaluate this network, we performed the gene set enrichment analysis using the disease genes of type 2 diabetes (T2D) and cancer, one T2D genome-wide association study (GWAS) dataset, three cancer GWAS datasets, and one GWAS dataset of cancer patients with T2D on metformin. The results showed that the metformin network was significantly enriched with disease genes for both T2D and cancer, and that the network also included genes that may be associated with metformin-associated cancer survival. Furthermore, from the metformin SPNetwork and common genes to T2D and cancer, we generated a subnetwork to highlight the molecule crosstalk between T2D and cancer. The follow-up network analyses and literature mining revealed that seven genes (CDKN1A, ESR1, MAX, MYC, PPARGC1A, SP1, and STK11) and one novel MYC-centered pathway with CDKN1A, SP1, and STK11 might play important roles in metformin's antidiabetic and anticancer effects. Some results are supported by previous studies. In summary, our study 1) develops a novel framework to construct drug-specific signal transduction networks; 2) provides insights into the molecular mode of metformin; 3) serves a model for exploring signaling pathways to facilitate understanding of drug action, disease pathogenesis, and identification of drug targets.