A Population-Specific Major Allele Reference Genome From The United Arab Emirates Population

Moroccan genome project: genomic insight into a North African population

Africa's 1.5 billion people are underrepresented in genomic databases. The African Genome Variation Project exclusively focuses on Sub-Saharan populations, making Morocco, located in North Africa, a valuable site for studying genetic diversity. Understanding genetic variation and customized therapy requires population-specific reference genomes. This study presents Phase 1 results from the Moroccan Genome Project (MGP), which sequenced 109 Moroccan genomes. We report over 27 million variants, including 1.4 million novel ones, of which 15,378 are highly prevalent in the Moroccan population. Furthermore, we propose a Moroccan Major Allele Reference Genome (MMARG), generated using high-coverage consensus sequences from the 109 whole genomes. This MMARG represents more accurately the Moroccan genetic variation than GRCh38. This baseline study also generates an informative genetic variation database that supports regional population-specific initiatives and precision medicine in Morocco and North Africa. The results stress the necessity of population-relevant data in Human genetic research.

A reference quality, fully annotated diploid genome from a Saudi individual

We have used multiple sequencing approaches to sequence the genome of a volunteer from Saudi Arabia. We use the resulting data to generate a de novo assembly of the genome, and use different computational approaches to refine the assembly. As a consequence, we provide a contiguous assembly of the complete genome of an individual from Saudi Arabia for all chromosomes except chromosome Y, and label this assembly KSA001. We transferred genome annotations from reference genomes to fully annotate KSA001, and we make all primary sequencing data, the assembly, and the genome annotations freely available in public databases using the FAIR data principles. KSA001 is the first telomere-to-telomere-assembled genome from a Saudi individual that is freely available for any purpose.

Investigating the genetic makeup of the major histocompatibility complex (MHC) in the United Arab Emirates population through next-generation sequencing

The Human leukocyte antigen (HLA) molecules are central to immune response and have associations with the phenotypes of various diseases and induced drug toxicity. Further, the role of HLA molecules in presenting antigens significantly affects the transplantation outcome. The objective of this study was to examine the extent of the diversity of HLA alleles in the population of the United Arab Emirates (UAE) using Next-Generation Sequencing methodologies and encompassing a larger cohort of individuals. A cohort of 570 unrelated healthy citizens of the UAE volunteered to provide samples for Whole Genome Sequencing and Whole Exome Sequencing. The definition of the HLA alleles was achieved through the application of the bioinformatics tools, HLA-LA and xHLA. Subsequently, the findings from this study were compared with other local and international datasets. A broad range of HLA alleles in the UAE population, of which some were previously unreported, was identified. A comparison with other populations confirmed the current population's unique intertwined genetic heritage while highlighting similarities with populations from the Middle East region. Some disease-associated HLA alleles were detected at a frequency of > 5%, such as HLA-B*51:01, HLA-DRB1*03:01, HLA-DRB1*15:01, and HLA-DQB1*02:01. The increase in allele homozygosity, especially for HLA class I genes, was identified in samples with a higher level of genome-wide homozygosity. This highlights a possible effect of consanguinity on the HLA homozygosity. The HLA allele distribution in the UAE population showcases a unique profile, underscoring the need for tailored databases for traditional activities such as unrelated transplant matching and for newer initiatives in precision medicine based on specific populations. This research is part of a concerted effort to improve the knowledge base, particularly in the fields of transplant medicine and investigating disease associations as well as in understanding human migration patterns within the Arabian Peninsula and surrounding regions.

Utilizing Pharmacogenomic Data for a Safer Use of Statins among the Emirati Population

BACKGROUND

Statins are the most prescribed lipid-lowering drugs worldwide. The associated adverse events, especially muscle symptoms, have been frequently reported despite their perceived safety. Three pharmacogenes, the solute carrier organic anion transporter family member 1B1 (SLCO1B1), ATP-binding cassette subfamily G member 2 (ABCG2), and cytochrome P450 2C9 (CYP2C9) are suggested as safety biomarkers for statins. The Clinical Pharmacogenomic Implementation Consortium (CPIC) issued clinical guidelines for statin use based on these three genes.

OBJECTIVES

The present study aimed to examine variants in these pharmacogenes to predict the safety of statin use among the Emirati population.

METHODS

Analyzing 242 whole exome sequencing data at the three genes enabled the determination of the frequencies of the single nucleotide polymorphisms (SNPs), annotating the haplotypes and the predicted functions of their proteins.

RESULTS

In our cohort, 29.8% and 5.4% had SLCO1B1 decreased and poor function, respectively. The high frequency warns of the possibility of significant side effects of some statins and the importance of pharmacogenomic testing. We found a low frequency (6%) of the ABCG2:rs2231142 variant, which indicates the low probability of Emirati patients being recommended against higher rosuvastatin doses compared with other populations with higher frequencies of this variant. In contrast, we found high frequencies of the functionally impaired CYP2C9 alleles, which makes fluvastatin a less favorable choice.

CONCLUSION

Among the sparse studies available, the present one demonstrates all SLCO1B1 and CYP2C9 function-impairing alleles among Emiratis. We highlighted how population-specific pharmacogenomic data can predict safer choices of statins, especially in understudied populations.

Critical assessment of on-premise approaches to scalable genome analysis

BACKGROUND

Plummeting DNA sequencing cost in recent years has enabled genome sequencing projects to scale up by several orders of magnitude, which is transforming genomics into a highly data-intensive field of research. This development provides the much needed statistical power required for genotype-phenotype predictions in complex diseases.

METHODS

In order to efficiently leverage the wealth of information, we here assessed several genomic data science tools. The rationale to focus on on-premise installations is to cope with situations where data confidentiality and compliance regulations etc. rule out cloud based solutions. We established a comprehensive qualitative and quantitative comparison between BCFtools, SnpSift, Hail, GEMINI, and OpenCGA. The tools were compared in terms of data storage technology, query speed, scalability, annotation, data manipulation, visualization, data output representation, and availability.

RESULTS

Tools that leverage sophisticated data structures are noted as the most suitable for large-scale projects in varying degrees of scalability in comparison to flat-file manipulation (e.g., BCFtools, and SnpSift). Remarkably, for small to mid-size projects, even lightweight relational database.

CONCLUSION

The assessment criteria provide insights into the typical questions posed in scalable genomics and serve as guidance for the development of scalable computational infrastructure in genomics.

A genome-wide association study identifies a possible role for cannabinoid signalling in the pathogenesis of diabetic kidney disease

Diabetic kidney disease (DKD), also known as diabetic nephropathy, is the leading cause of renal impairment and end-stage renal disease. Patients with diabetes are at risk for DKD because of poor control of their blood glucose, as well as nonmodifiable risk factors including age, ethnicity, and genetics. This genome-wide association study (GWAS) was conducted for the first time in the Emirati population to investigate possible genetic factors associated with the development and progression of DKD. We included data on 7,921,925 single nucleotide polymorphism (SNPs) in 258 cases of type 2 diabetes mellitus (T2DM) who developed DKD and 938 control subjects with T2DM who did not develop DKD. GWAS suggestive results (P < 1 × 10-5) were further replicated using summary statistics from three cohorts with T2DM-induced DKD (Bio Bank Japan data, UK Biobank, and FinnGen Project data) and T1DM-induced DKD (UK-ROI cohort data from Belfast, UK). When conducting a multiple linear regression model for gene-set analyses, the CNR2 gene demonstrated genome-wide significance at 1.46 × 10-6. SNPs in CNR2 gene, encodes cannabinoid receptor 2 or CB2, were replicated in Japanese samples with the leading SNP rs2501391 showing a Pcombined = 9.3 × 10-7, and odds ratio = 0.67 in association with DKD associated with T2DM, but not with T1DM, without any significant association with T2DM itself. The allele frequencies of our cohort and those of the replication cohorts were in most cases markedly different. In addition, we replicated the association between rs1564939 in the GLRA3 gene and DKD in T2DM (P = 0.016, odds ratio = 0.54 per allele C). Our findings suggest evidence that cannabinoid signalling may be involved in the development of DKD through CB2, which is expressed in different kidney regions and known to be involved in insulin resistance, inflammation, and the development of kidney fibrosis.

Whole-Exome Sequencing in Family Trios Reveals De Novo Mutations Associated with Type 1 Diabetes Mellitus

Type 1 diabetes mellitus (T1DM) is a chronic autoimmune disease characterized by insulin deficiency and loss of pancreatic islet β-cells. The objective of this study is to identify de novo mutations in 13 trios from singleton families that contribute to the genetic basis of T1DM through the application of whole-exome sequencing (WES). Of the 13 families sampled for this project, 12 had de novo variants, with Family 7 having the highest number (nine) of variants linked to T1DM/autoimmune pathways, whilst Family 4 did not have any variants past the filtering steps. There were 10 variants of 7 genes reportedly associated with T1DM (MST1; TDG; TYRO3; IFIHI; GLIS3; VEGFA; TYK2). There were 20 variants of 13 genes that were linked to endocrine, metabolic, or autoimmune diseases. Our findings demonstrate that trio-based WES is a powerful approach for identifying new candidate genes for the pathogenesis of T1D. Genotyping and functional annotation of the discovered de novo variants in a large cohort is recommended to ascertain their association with disease pathogenesis.

Whole Exome Sequencing in South Africa: Stakeholder Views on Return of Individual Research Results and Incidental Findings

The use of whole exome sequencing (WES) in medical research is increasing in South Africa (SA), raising important questions about whether and which individual genetic research results, particularly incidental findings, should be returned to patients. Whilst some commentaries and opinions related to the topic have been published in SA, there is no qualitative data on the views of professional stakeholders on this topic. Seventeen participants including clinicians, genomics researchers, and genetic counsellors (GCs) were recruited from the Western Cape in SA. Semi-structured interviews were conducted, and the transcripts analysed using the framework approach for data analysis. Current roadblocks for the clinical adoption of WES in SA include a lack of standardised guidelines; complexities relating to variant interpretation due to lack of functional studies and underrepresentation of people of African ancestry in the reference genome, population and variant databases; lack of resources and skilled personnel for variant confirmation and follow-up. Suggestions to overcome these barriers include obtaining funding and buy-in from the private and public sectors and medical insurance companies; the generation of a locally relevant reference genome; training of health professionals in the field of genomics and bioinformatics; and multidisciplinary collaboration. Participants emphasised the importance of upscaling the accessibility to and training of GCs, as well as upskilling of clinicians and genetic nurses for return of genetic data in collaboration with GCs and medical geneticists. Future research could focus on exploring the development of stakeholder partnerships for increased access to trained specialists as well as community engagement and education, alongside the development of guidelines for result disclosure.

Ethnicity-Specific Features of COVID-19 Among Arabs, Africans, South Asians, East Asians, and Caucasians in the United Arab Emirates

Background

Dubai (United Arab Emirates; UAE) has a multi-national population which makes it exceptionally interesting study sample because of its unique demographic factors.

Objective

To stratify the risk factors for the multinational society of the UAE.

Methods

A retrospective chart review of 560 patients sequentially admitted to inpatient care with laboratory confirmed COVID-19 was conducted. We studied patients’ demographics, clinical features, laboratory results, disease severity, and outcomes. The parameters were compared across different ethnic groups using tree-based estimators to rank the ethnicity-specific disease features. We trained ML classification algorithms to build a model of ethnic specificity of COVID-19 based on clinical presentation and laboratory findings on admission.

Results

Out of 560 patients, 43.6% were South Asians, 26.4% Middle Easterns, 16.8% East Asians, 10.7% Caucasians, and 2.5% are under others. UAE nationals represented half of the Middle Eastern patients, and 13% of the entire cohort. Hypertension was the most common comorbidity in COVID-19 patients. Subjective complaint of fever and cough were the chief presenting symptoms. Two-thirds of the patients had either a mild disease or were asymptomatic. Only 20% of the entire cohort needed oxygen therapy, and 12% needed ICU admission. Forty patients (~7%) needed invasive ventilation and fifteen patients died (2.7%). We observed differences in disease severity among different ethnic groups. Caucasian or East-Asian COVID-19 patients tended to have a more severe disease despite a lower risk profile. In contrast to this, Middle Eastern COVID-19 patients had a higher risk factor profile, but they did not differ markedly in disease severity from the other ethnic groups. There was no noticeable difference between the Middle Eastern subethnicities—Arabs and Africans—in disease severity (p = 0.81). However, there were disparities in the SOFA score, D-dimer (p = 0.015), fibrinogen (p = 0.007), and background diseases (hypertension, p = 0.003; diabetes and smoking, p = 0.045) between the subethnicities.

Conclusion

We observed variations in disease severity among different ethnic groups. The high accuracy (average AUC = 0.9586) of the ethnicity classification model based on the laboratory and clinical findings suggests the presence of ethnic-specific disease features. Larger studies are needed to explore the role of ethnicity in COVID-19 disease features.

Heterogeneity in biomarkers, mitogenome and genetic disorders of the Arab population with special emphasis on large-scale whole-exome sequencing

More than 25 million DNA variations have been discovered as novel including major alleles from the Arab population. Exome studies on the Saudi genome discovered > 3000 novel nucleotide variants associated with > 1200 rare genetic disorders. Reclassification of many pathogenic variants in the Human Gene Mutation Database and ClinVar Database as benign through the Arab database facilitates building a detailed and comprehensive map of the human morbid genome. Intellectual disability comes first with the combined and observed carrier frequency of 0.06779 among Saudi Arabians; retinal dystrophy is the next highest. Genome studies have discovered interesting novel candidate disease marker variations in many genes from consanguineous families. More than 7 pathogenic variants in the C12orf57 gene are prominently associated with the etiology of developmental delay/intellectual impairment in Arab ancestries. Advances in large-scale genome studies open a new outlook on Mendelian genes and disorders. In the past half-dozen years, candidate genes of intellectual disability, neurogenetic disorders, blood and bleeding disorders and rare genetic diseases have been well documented through genomic medicine studies in combination with advanced computational biology applications. The Arab mitogenome exposed hundreds of variations in the mtDNA genome and ancestral sharing with Africa, the Near East and East Asia and its association with obesity. These recent discoveries in disease markers and molecular genetics of the Arab population will have a positive impact towards supporting genetic counsellors on reaching consanguineous families to manage stress linked to genetics and precision medicine. This narrative review summarizes the advances in molecular medical genetics and recent discoveries on pathogenic variants. Despite the fact that these initiatives are targeting the genetics and genomics of disorders prevalent in Arab populations, a lack of complete cooperation across the projects needed to be revisited to uncover the Arab population's prominent disease markers. This shows that further study is needed in genomics to fully comprehend the molecular abnormalities and associated pathogenesis that cause inherited disorders in Arab ancestries.

Discovery of genomic variation across a generation

Over the past 30 years (the timespan of a generation), advances in genomics technologies have revealed tremendous and unexpected variation in the human genome and have provided increasingly accurate answers to long-standing questions of how much genetic variation exists in human populations and to what degree the DNA complement changes between parents and offspring. Tracking the characteristics of these inherited and spontaneous (or de novo) variations has been the basis of the study of human genetic disease. From genome-wide microarray and next-generation sequencing scans, we now know that each human genome contains over 3 million single nucleotide variants when compared with the ~ 3 billion base pairs in the human reference genome, along with roughly an order of magnitude more DNA—approximately 30 megabase pairs (Mb)—being ‘structurally variable’, mostly in the form of indels and copy number changes. Additional large-scale variations include balanced inversions (average of 18 Mb) and complex, difficult-to-resolve alterations. Collectively, ~1% of an individual’s genome will differ from the human reference sequence. When comparing across a generation, fewer than 100 new genetic variants are typically detected in the euchromatic portion of a child’s genome. Driven by increasingly higher-resolution and higher-throughput sequencing technologies, newer and more accurate databases of genetic variation (for instance, more comprehensive structural variation data and phasing of combinations of variants along chromosomes) of worldwide populations will emerge to underpin the next era of discovery in human molecular genetics.