Mohamed Dafaalla

Risk factors of diabetic cardiac autonomic neuropathy in patients with type 1 diabetes mellitus: a meta-analysis

Objectives We aimed to stratify the possible risk factors for diabetic cardiac autonomic neuropathy (CAN). Methods We did a meta-analysis of risk factors of CAN. We did a web-based search for literature in MEDLINE/PubMed, Scopus database and CENTRAL database up to August 2015. We included clinical trials or cohort studies that provide data about relationship between CAN and variables of interest. Our risk factors of interest were age, sex, duration of diabetes, body mass index (BMI), systolic blood pressure (sBP) and diastolic blood pressure (dBP), glycated haemoglobin (HbA1c), high-density lipoprotein and low-density lipoprotein (HDL and LDL), triglycerides, retinopathy and nephropathy. We generated Forest plots, χ2 test and I2 as tests for heterogeneity, risk ratio (RR), mean difference (MD), CIs and p values by ReVMan V.5.3 software. Results We found a total of 882 related items. We excluded 873 studies from the title and abstract and 4 studies after review of full reports. Four studies were included. Our meta-analysis showed significant association between CAN and age (MD=4.94 (3.46 to 6.42)), duration of diabetes (MD=4.51 (2.51 to 6.52)), HbA1c (MD=0.48 (0.28 to 0.67)), BMI (MD=0.55 (0.08 to 1.01)), serum triglycerides (MD=0.09 (0.01 to 0.17)), proliferative retinopathy (RR=3.69 (1.20 to 11.34)), microalbuminuria (RR=2.47 (1.43 to 4.29)), hypertension (RR=4.18 (2.52 to 6.91)) and sBP (MD=4.10 (2.20 to 6.00)). We neither discovered the absence of significant association between the development of CAN and male sex (RR=1.57 (0.45 to 5.39)), dBP (MD=0.89 (−0.36 to 2.14)), cholesterol level (MD=1.19 (−0.99 to 3.36)), LDL (MD=0.12 (−0.15 to 0.39)), nor HDL level (MD=−0.28 (−0.58 to 0.03)). Conclusions Age, duration of diabetes, HbA1c, BMI, serum triglycerides, proliferative retinopathy, microalbuminuria, hypertension and sBP are directly related to the risk of development of diabetic CAN.

In silico analysis of non-synonymous Single nucleotide polymorphisms of BMBR2 (PPH1) gene and demonstration of gene's network interactions

A major challenge for bringing safe and effective new treatment to patients is the deep understanding of a disease. Here, we describe the integration of multi-omics data with systems biology algorithms for tackling three milestones in the drug development process: Construction of pathways and comparison between normal or diseased cells; Identification of drug mode of action (MoA) and Prediction of drug toxicity and efficacy. On the experimental front, we develop custom multiplex proteomic and phosphoproteomic assays based on the Luminex technology. To guarantee the quality of the assays we quantify the cross-reactivity profile of antibodies and we have developed optimization algorithms to select the optimal pairs. Currently, a ~40x phosphoprotein panel and a ~80x cytokine panel have been developed. On the computational front, signaling cascades are modeled with a Boolean or fuzzy logic framework and signaling pathways or optimized in order to fit the phopshoproteomic data at hand. Then, knowing the cells topology, we monitor drug-induced topology alterations in order to reveal drug mode of action. Subsequently, supervised machine learning algorithms was able to select MoAs with reduced toxicity and increased efficacy. So far we have applied our approach in several diseases including liver cancer, osteoarthritis and multiple sclerosis.N syndrome is a nonspecific kidney disorder characterized by a number of signs of disease: Proteinuria, hypoalbuminemia and edema. It is characterized by an increase in permeability of the capillary walls of the glomerulus leading to the presence of high levels of protein in the urine. NPHS2 is encoding Podocin an important protein in renal filtration function. Analysis of the genetic variation that can alter the expression and the function of the NPHS2 gene was done using computational methods. Genomic analysis of NPHS2 was initiated by Sift and Polyphen-2 servers and yielded 18 mutations to be damaging , the mutant amino acids biophysical characteristics and multiple sequence alignment were demonstrated to be affecting the protein function using AlignGVGD and Panther platforms. 11 mutations affected protein function the most. Genetic co-expression profile and interactions were demonstrated by GeneMANIA server, and NPHS2 is found to be co-expressed with a neuronal protein, 3D structure molding was done using Phyre2 and Chimera. Computational methods yield accurate results which can be a basis of diagnosis of steroid resistant nephrotic syndrome.M syndrome is a common autosomal dominant hereditary connective tissue disorder with variable presentations, mutations in FBN1 gene were found to be responsible for Marfan syndrome and other relate connective tissue disorders. SNPs contributes to gene mutations and expression variations justifying phenotypic variations among patients and hence such SNPs would be potential target for identification and analysis which may help in early diagnosis of such life threatening disorder. Computational methods were used on this work focusing on analysis of SNPs in the coding regions of FBN1 gene found as non-synonymous variants (nsSNP) and those in the 3’un-translated regions (3’UTR) affecting miRNA binding using computational methods including SIFT and polyphen for analysis of (nsSNPs) while (3’UTR) SNPs was analyzed using PolymiRTS tool functions and Interactions of FBN1 gene with functional similar genes was predicted using gene MANIA software. Out of 1134 ns-SNPs analyzed, 38 SNPs were found to damaging while analysis of 175 SNP in 3’UTR prove that 24 SNPs are disturbing to their target sites and 46 SNPs are creating to new target sites. Using the damaging ns-SNPs predicted on this work may be helpful in early diagnosis and on screening of FBN1 related disorders.Mutations in BMPR2 gene are seen in about 15% of sporadic cases and about 40% of familial cases of PPH. We have studied non-synonymous SNPs in BMPR2-002 (ENST00000374574). Non-synonymous dsSNPs were identified using NCBI-database. Then advanced bioinformatics analysis was used to determine the functionality of each SNP in the coding region. Out of 323 SNPs which were found in the coding region, only 7 were found to be damaging in both SIFT and polyphen. 53 SNPs in 3UTR region were found to disrupt miRNA binding sites, whereas 55 SNPs were found to create new ones. Certain SNPs affect binding sites of certain MicroRNAs that have been linked to hepatic cancer and prostate cancer. BMPR2 gene interactions with other genes were identified and classified according to multiple parameters (physical interaction, co-localization, co-expression, pathway and prediction). BMPR2 is an important regulator in BMP pathway which affects cellular growth. Certain SNPs were found to affect BMPR2 structure hence function for better correlation with clinical cases.H tear fluid is a complex mixture containing high concentrations of proteins and is increasingly becoming an important source for studying protein composition of eye-related diseases. An important part of proteomic research is accurate quantification of proteins and this has made the incorporation of differentially stable isotopes in samples widely used. Dimethyl labeling at peptide level is a cost-effective, undemanding and fast labeling procedure that is applicable to nearly any biological sample. In addition, this procedure is capable of labeling sub-microgram to milligrams of sample and all reagents are compatible with LC-MS analysis. Therefore, the aim of this study was to look into the suitability of stable isotope dimethyl labeling for quantitative proteomics on tear fluid. The tear proteins were extracted using a single unit filter-aided method for both sample handling and protein extraction from Schirmer strips. The peptides were reversely labeled with a light label and an intermediate label and mixed before LC-MS/ MS analysis. The different stable isotopically labeled peptides showed a known mass difference when looking into the MS specters. Additionally, a clear signal intensity difference between the differentially labeled peptides was observed. These results show that stable isotope dimethyl labeling of tear proteins is both possible and successful and may serve as an important quantification method for tear proteome.

The correlation between the neurological complications of rheumatoid arthritis with the disease activity and functional impairment (Disability)

Objectives: To identify the impact and predictors of the neurological complications of rheumatoid arthritis (RA) among Sudanese patients. Methodology: A case series study of 58 consecutive patients diagnosed as having RA at Omdurman teaching hospital rheumatology clinic was done. Patients have another possible etiology for the neurological manifestations were excluded. The doctors of rheumatology clinic examined the patients and the Clinical Disease Activity Index (CDAI) was calculated. A senior consultant neurologist objectively assessed the neurological complications of RA. The patients were interviewed using the Health Assessment Questionnaire (HAQ) to evaluate the functional impairment. Various statistical tests were used to assess any possible association between various variables obtained. Results: Almost 60% have neurological signs (pyramidal system signs 43.1%, proximal weakness 8.6%, sensorimotor neuropathy 5.2%, pure sensory neuropathy 1.7%, extrapyramidal/cerebellar 0%). The mean HAQ scores for patients who express neurological signs and those who don’t express are 1.34 and 1.40 respectively without significant difference (P = 0.778). The association between the neurological complications and disease activity, ESR value, and rheumatoid factor status is not significant (P = 0.701, 0.515, 0.299 respectively). There is not only a strong association between the disease activity (CDAI) of RA and functional status (HAQ) of the patient (P = 0.0, R = 0.56), but also 30% of variability of the functional impairment can be attributed exclusively to the variability of the disease activity (R2 = 0.3). Conclusion: The RA activity is the major determinant of disease morbidity. The functional impairment caused by the neurological complications is negligible. The disease activity, ESR value, and rheumatoid factor status are poor predictors of the neurologic complications.