Diagnostic efficacy of cystatin-c in association with different ACE genes predicting renal insufficiency in T2DM.

Diabetic nephropathy (DN) seems to be the major cause of chronic kidney disease that may finally lead to End Stage Renal Disease. So, renal function assessment in type 2 diabetes mellitus (T2DM) individuals is very important. Clearly, DN pathogenesis is multifactorial and different proteins, genes and environmental factors can contribute to the onset of the disease. We assessed sensitive and specific biomarkers (in blood and urine) which can predict kidney disease susceptibility among T2DM patients. Serum cystatin-c (cyst-c) in blood and urinary hemeoxygenase (HO-1) in addition to ACE I/D polymorphism and ACE G2350A genotypes. Hundred and eight T2DM patients and 85 controls were enrolled. Serum cystatin-c and urinary (HO-1) were tested by ELISA. Genetic determination of both ACE I/D polymorphism and ACE G2350A genotypes was performed by PCR for all participants. Significant rise in serum cystatin-c and urinary HO-1 levels were shown in diabetic groups compared with control group. Moreover, GG genotype of ACE G2350A gene in diabetic group was associated with rise in serum cystatin-c and urinary HO-1 compared with control group. Mutant AA genotype demonstrated increase in urinary HO-1. DD polymorphism was associated with rise in serum creatinine and cyst-c in diabetic group. Positive correlation was seen between duration of diabetes and serum cyst-c and between serum glucose and urinary (HO-1) in diabetic group. The results from this study indicated an association of serum cystatin-c with GG genotype of ACE G2350A in conjugation with DD polymorphism of ACE I/D which could be an early predictor of tubular injury in T2DM diabetic patients.

Temporal trend of diarrhea morbidity rate with climate change: Egypt as a case study.

Many studies have detected a relationship between diarrhea morbidity rates with the changes in precipitation, temperature, floods, droughts, water shortage, etc. But, most of the authors were cautious in their studies, because of the lack of empirical climate-health data and there were large uncertainties in the future projections. The study aimed to refine the link between the morbidity rates of diarrhea in some Egyptian governorates representative of the three Egyptian geographical divisions with the meteorological changes that occurred in the 2006-2016 period for which the medical data are available, as a case study. Medical raw data was collected from the Information Centre Department of the Egyptian Ministry of Health and Population. The meteorological data of temperature and precipitation extremes were defined as data outside the 10th-90th percentile range of values of the period of study, and their analysis was done using a methodology similar to the one recommended by the WMO and integrated in the CLIMDEX software. Relationships between the morbidity rates of diarrhea in seven Egyptian governorates and the meteorological changes that occurred in the period 2006 to 2016 were analyzed using multiple linear regression analysis to identify the most effective meteorological factor that affects the trend of morbidity rate of diarrhea in each governorate. Statistical analysis revealed that some meteorological parameters can be used as predictors for morbidity rates of diarrhea in Cairo, Alexandria, and Gharbia, but not in Aswan, Behaira, and Dakahlia where the temporal evolution cannot be related with meteorology. In Red Sea, there was no temporal trend and no significant relationships between the diarrhea morbidity rate and meteorological parameters. The predictor meteorological parameters for morbidity rates of diarrhea were found to be depending on the geographic locations and infrastructures in these governorates. It was concluded that the meteorological data that can be used as predictors for the morbidity rate of diarrhea is depending on the geographical location and infrastructures of the target location. The socioeconomic levels as well as the infrastructures in the governorate must be considered confounders in future studies.