Habiba Alsafar

Identifying Common Genetic Risk Factors of Diabetic Neuropathies

Type 2 diabetes mellitus (T2DM) is a global public health problem of epidemic proportions, with 60–70% of affected individuals suffering from associated neurovascular complications that act on multiple organ systems. The most common and clinically significant neuropathies of T2DM include uremic neuropathy, peripheral neuropathy, and cardiac autonomic neuropathy. These conditions seriously impact an individual’s quality of life and significantly increase the risk of morbidity and mortality. Although advances in gene sequencing technologies have identified several genetic variants that may regulate the development and progression of T2DM, little is known about whether or not the variants are involved in disease progression and how these genetic variants are associated with diabetic neuropathy specifically. Significant missing heritability data and complex disease etiologies remain to be explained. This article is the first to provide a review of the genetic risk variants implicated in the diabetic neuropathies and to highlight potential commonalities. We thereby aim to contribute to the creation of a genetic-metabolic model that will help to elucidate the cause of diabetic neuropathies, evaluate a patient’s risk profile, and ultimately facilitate preventative and targeted treatment for the individual.

Population genetics data for 21 autosomal STR loci for United Arab Emirates (UAE) population using next generation multiplex STR kit

DNA samples were analysed from 519 healthy, unrelated and consenting individuals who reside in the United Arab Emirates (UAE) and were randomly chosen for this study. The UAE is one of the middle-eastern countries located on the Arabian Gulf. It shares a border with Iran, Saudi Arabia and Oman. The UAE was founded in 1971, and consists of seven Emirates: Abu Dhabi, Dubai, Sharjah, Ajman, Ra’s Al-Khaymah, Al-Fujairah and Umm Al-Quwain [1]. According to the National Bureau of Statistics (2012), the total UAE population was reported to be around 8.26 million in 2010 [2]. The statistics showed that some 11.5% of the total population comprised of native Arabs, with majority of the population being of Indian and Pakistani ethnicities. In the early part of the twentieth century, the different Arabic tribes migrated in different directions in search of suitable locations to colonize. Some moved into coastal regions, while others inhabited the desert. Despite the modernization throughout the union, the basic family structure and pattern of native UAE Arab population has remained unchanged. Culturally, the preference for consanguineous marriages remains embedded in the society [3]. However, as the awareness of the social and medical impact of consanguinity increases and with diversification, non-consanguineous marriages appear to be on the increase, which has possibly resulted in greater genetic diversity throughout the population [4,5]. The increase in genetic diversity in the population is of interest to assess whether STR markers can be used for forensic and paternity purposes. This study expands on previous publications with regards to the analysis of UAE populations with the amplification of additional STR markers and a larger population sample size [6]. The DNA samples analysed in the current study were obtained from indigenous UAE nationals residing in Abu Dhabi, UAE in accordance with approval from the Ethics committee of the Ministry of Health of the United Arab Emirates (2011). Informed consent was received from every volunteer during this collection process and de-identified data is presented. This study was also approved by the Ethics committee of the University of Central Lancashire (2014) as it was carried out as part of Masters Project in DNA profiling. The DNA samples provided for this study were collected and extracted using the Genotek’s Oragene-DNA kit (Genotek, Ottawa, Canada) in accordance with manufacturers guidelines. The quantities of extracted DNA samples were determined using a NanoDrop spectrophotometer (Thermo Scientific, Wilmington DE, USA).

Autosomal Short Tandem Repeat (STR) Variation Based on 15 Loci in a Population from the Central Region (Riyadh Province) of Saudi Arabia

Introduction: The small size of Short Tandem Repeats (STRs), their ubiquitous genome-wide distribution and polymorphic nature enhances their value in human forensic/population genetics applications. Objectives: This study aims to investigate the short tandem repeat variation based on 15 loci in a population from the central region of Saudi Arabia. Methods: Allele frequency variation for 15 Short Tandem Repeat (STR) loci was examined in 190 unrelated Saudi volunteers. Results: This study summarizes the allele distribution in the Saudi population and compares them to other populations located in Asia, Africa, the Middle East and Europe. The standard forensic parameters of Observed Hetrozygosity (Ho), Expected Heterozygosity (He) and Gene Diversity Index (GD) were determined for the following 15 STR loci: D8S1179, D21S1, D7S820, CSF1PO, D3S1358, TH0, D13S317, D16S539, D2S1338, D19S433, vWA, TPOX, D18S5, D5S818 and FGA. The most frequent alleles in the Saudi population were: 8 repeats (0.558) at TPOX, 12 (0.411) at D13S317, 12 (0.385) at CSF1PO, 11 (0.382) at D16D539 and 10 (0.358) at D7S820. The 15 markers utilized in this study are highly informative as evidenced by their high power of discrimination (PD) values with D2S1338, D19S433 and FGA having the highest PD values. The relationship between the Saudi population and other geographically distributed populations, assessed by a Multidimensional Scaling (MDS) plot, showed that the Saudi population clustered with groups from Yemen, Iraq, Qatar, Oman and Bahrain. Conclusion: TPOX, D13S317, CSF1PO, D16D539 and D7S820 markers were found suitable for forensic analysis, paternity testing and can also be used for chimerism study after allogenic bone marrow transplantation for Saudi population. On the other hand, the population admixture with other ethnic origins might explain the variable degree of genetic distances of this population and other Arab-related groups.

Clinical profiles, comorbidities and complications of type 2 diabetes mellitus in patients from United Arab Emirates

Objective To assess clinical profiles of patients with type 2 diabetes in the United Arab Emirates (UAE), including patterns, frequencies, and risk factors of microvascular and macrovascular complications. Research design and methods Four hundred and ninety patients with type 2 diabetes were enrolled from two major hospitals in Abu Dhabi. The presence of microvascular and macrovascular complications was assessed using logistic regression, and demographic, clinical and laboratory data were collected. Significance was set at p<0.05. Results Hypertension (83.40%), obesity (90.49%) and dyslipidemia (93.43%) were common type 2 diabetes comorbidities. Most of the patients had relatively poor glycemic control and presented with multiple complications (83.47% of patients had one or more complication), with frequent renal involvement. The most frequent complication was retinopathy (13.26%). However, the pattern of complications varied based on age, where in patients <65 years, a single pattern presented, usually retinopathy, while multiple complications was typically seen in patients >65 years old. Low estimated glomerular filtration rate in combination with disease duration was the most significant risk factor in the development of a diabetic-associated complication especially for coronary artery disease, whereas age, lipid values and waist circumference were significantly associated with the development of diabetic retinopathy. Conclusions Patients with type 2 diabetes mellitus in the UAE frequently present with comorbidities and complications. Renal disease was found to be the most common comorbidity, while retinopathy was noted as the most common diabetic complication. This emphasizes the need for screening and prevention program toward early, asymptomatic identification of comorbidities and commence treatment, especially for longer disease duration.

Using facial images for the diagnosis of genetic syndromes: A survey

The analysis of facial appearance is significant to an early diagnosis of medical genetic diseases. The fast development of image processing and machine learning techniques facilitates the detection of facial dysmorphic features. This paper is a survey of the recent studies developed for the screening of genetic abnormalities across the facial features obtained from two dimensional and three dimensional images.

Poincaré plot analysis of heart rate variability in the diabetic patients in the UAE

Major complications such as cardiac death and cardiac autonomic neuropathy are caused by diabetic autonomic neuropathy. Heart Rate Variability (HRV) analysis has shown to detect variations in the autonomic balance of heart rate and is useful for early detection of autonomic dysfunction. This study presents the outcome of HRV analysis of short ECG recordings taken from nondiabetic and type 2 diabetes patients, applying Poincaré plot indices represented by short term variation (SD1), long term variation (SD2) and complex correlation (CCM) measure which measures the temporal dynamics, for early detection of cardiac autonomic neuropathy. SD1 and the ratio SD1/SD2 were found to be significantly lower in type 2 diabetes patients than the control group. The highest discriminatory power was observed with CCM, indicating the advantage of using a dynamic measure for HRV rather than the static Poincaré plot indices. SD1 and CCM could be markers for CVD risk in type 2 diabetic patients.

Association of the Genetic Polymorphisms in Transcription Factor 7-Like 2 and Peroxisome Proliferator-Activated Receptors-γ2 with Type 2 Diabetes Mellitus and Its Interaction with Obesity Status in Emirati Population

Background. Transcription factor 7-like 2 gene (TCF7L2) and peroxisome proliferator-activated receptors-γ2 (PPAR-γ2) have a profound effect on the incidence of type 2 diabetes mellitus (T2DM) and had previously been found to be associated with T2DM risk in various ppopulations. However, studies in the Arab population are inconsistent. We conducted a case control study to confirm the association of variants rs10885409 of TCF7L2 and Pro12Ala (rs1801282) of PPAR-γ2 with risk of T2DM and related complications in Emirati population of Arab origin. We also investigated the interaction of these associations with obesity status. Methods. DNA was extracted from the saliva samples of 272 T2DM patients and 216 nondiabetic Emiratis. Genotyping for rs10885409 (TCF7L2) and rs1801282 (PPAR-γ2 P12A) variants was accomplished with a TaqMan assay. The subgroups were constituted according to obesity status. Results. In the nonobese group, the rs10885409 C allele in the recessive model was significantly associated with the incidence of T2DM (OR 1.975 [95% CI 1.127–3.461], P = 0.017), but this association was not observed in the obese group or when BMI was not considered. PPAR-γ2 risk allele Pro12 frequency (0.96) was similar in the groups tested and more than 90% population was homozygous for this allele. Conclusions. Our case-control study is the first of its kind in Emiratis which establishes TCF7L2 rs10885409 C allele as a T2DM risk factor in Emiratis and this association is modulated by obesity status. We also confirmed that Pro12Ala mutation in PPAR-γ2 is not associated with T2DM risk in this population.

Association of Angiotensin Converting Enzyme Insertion-Deletion Polymorphism with Hypertension in Emiratis with Type 2 Diabetes Mellitus and Its Interaction with Obesity Status

The association of Angiotensin Converting Enzyme (ACE) insertion-deletion (I/D) polymorphism with Type 2 Diabetes Mellitus (T2DM) and hypertension has been extensively studied throughout various ethnic populations but largely with inconsistent findings. We investigated these associations in Emirati population and their interaction with obesity status. Saliva samples were collected from a total of 564 Emiratis (277 T2DM and 297 healthy). DNA was extracted and the samples were genotyped for ACE I/D polymorphism by a PCR based method followed by gel electrophoresis. Upon evaluation of the ACE I/D polymorphism amongst all T2DM, hypertensive patients, and respective controls regardless of obesity status, ACE DD genotype was not found to be associated with either T2DM [odds ratio (OR) = 1.34, p = 0.086] or hypertension [odd ratio (OR) = 1.02, p = 0.93]. When the genetic variants amongst the nonobese and obese population were analyzed separately, the risk genotype ACE DD conferred significantly increased risk of hypertension in nonobese population [odds ratio (OR) = 1.80, p = 0.02] but was found to be protective against the hypertension in the obese group ((OR) = 0.54, p = 0.01). However, there was no effect of obesity status on the association of ACE genotypes with T2DM. The risk of hypertension associated with ACE DD is modulated by obesity status and hence future genetic association studies should take obesity into account for the interpretation of data. We also confirmed that ACE I/D polymorphism is not associated with T2DM risk in Emirati population.

A 1000 Arab genome project to study the Emirati population

Discoveries from the human genome, HapMap, and 1000 genome projects have collectively contributed toward the creation of a catalog of human genetic variations that has improved our understanding of human diversity. Despite the collegial nature of many of these genome study consortiums, which has led to the cataloging of genetic variations of different ethnic groups from around the world, genome data on the Arab population remains overwhelmingly underrepresented. The National Arab Genome project in the United Arab Emirates (UAE) aims to address this deficiency by using Next Generation Sequencing (NGS) technology to provide data to improve our understanding of the Arab genome and catalog variants that are unique to the Arab population of the UAE. The project was conceived to shed light on the similarities and differences between the Arab genome and those of the other ethnic groups.

Landmark detection from 3D mesh facial models for image-based analysis of dysmorphology

Facial landmark detection is a task of interest for facial dysmorphology, an important factor in the diagnosis of genetic conditions. In this paper, we propose a framework for feature points detection from 3D face images. The method is based on 3D Constrained Local Model (CLM) which learns both global variations in the 3D facial scan and local changes around every vertex landmark. Compared to state of the art methods our framework is distinguished by the following novel aspects: 1) It operates on facial surfaces, 2) It allows fusion of shape and color information on the mesh surface, 3) It introduces the use of LBP descriptors on the mesh. We showcase our landmarks detection framework on a set of scans including down syndrome and control cases. We also validate our method through a series of quantitative experiments conducted with the publicly available Bosphorus database.