The Importance and Role of Multiple Risk Factor Control in Type 2 Diabetes.

PURPOSE OF REVIEW: The importance of composite risk factor control for reducing CVD risk in type 2 diabetes (T2DM) has gained increased attention and here we review the latest findings in the field. RECENT FINDINGS: The Steno-2 study was the first to show that early intensive risk factor control could improve risk factor status and halve the CVD risk in patients with diabetes with lasting impact. A range of observational studies have added further insight to the importance of multiple risk factor control showing an incremental association between number of risk factors controlled and reduction in CVD risk. Noteworthy, a Swedish population-based study recently showed that optimal risk factor status in patients with T2DM was associated with a CVD risk similar to the general population. Early intensive intervention to achieve optimal risk factor control reduces CVD risk and should be of principal focus in T2DM management.

Microtubule affinity-regulating kinase 2 is associated with DNA damage response and cisplatin resistance in non-small cell lung cancer.

Microtubule affinity-regulating kinases (MARKs) are involved in several cellular functions but few studies have correlated MARK kinase expression with cancer, and none have explored their role in lung cancer. In this study, we identified MARK2 as frequently disrupted by DNA hypomethylation and copy gain, resulting in concordant overexpression in independent lung tumor cohorts and we demonstrate a role for MARK2 in lung tumor biology. Manipulation of MARK2 in lung cell lines revealed its involvement in cell viability and anchorage-independent growth. Analyses of both manipulated cell lines and clinical tumor specimens identified a potential role for MARK2 in cell cycle activation and DNA repair. Associations between MARK2 and the E2F, Myc/Max and NF-κB pathways were identified by luciferase assays and in-depth assessment of the NF-κB pathway suggests a negative association between MARK2 expression and NF-κB due to activation of non-canonical NF-κB signaling. Finally, we show that high MARK2 expression levels correlate with resistance to cisplatin, a standard first line chemotherapy for lung cancer. Collectively, our work supports a role for MARK2 in promoting malignant phenotypes of lung cancer and potentially modulating response to the DNA damaging chemotherapeutic, cisplatin.

A treatment-based algorithm for identification of diabetes type in the National Health and Nutrition Examination Survey.

In epidemiology studies, identification of diabetes type (type 1 vs. type 2) among study participants with diabetes is important; however, conventional diabetes type identification approaches that include age at diabetes diagnosis as an initial criterion introduces biases. Using data from the National Health and Nutrition Examination Survey, we have developed a novel algorithm which does not include age at diagnosis to identify participants with self-reported diagnosed diabetes as having type 1 vs. type 2 diabetes. METHODS: A total of 5457 National Health and Nutrition Examination Survey participants between cycles 1999-2000 and 2015-2016 reported that a health professional had diagnosed them as having diabetes at a time other than during pregnancy and had complete information on diabetes-related questions. After developing an algorithm based on information regarding the treatment(s) they received, we classified these participants as having type 1 or type 2 diabetes. RESULTS: The treatment-based algorithm yielded a 6-94% split for type 1 and type 2 diabetes, which is consistent with reports from the Centers for Disease Control and other resources. Moreover, the demographics and clinical characteristics of the assigned type 1 and type 2 cases were consistent with contemporary epidemiologic findings. CONCLUSION: Applying diabetes treatment information from the National Health and Nutrition Examination Survey, as formulated in our treatment-based algorithm, may better identify type 1 and type 2 diabetes cases and thus prevent the specific biases imposed by conventional approaches which include the age of diabetes diagnosis as an initial criterion for diabetes type classification.