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250105g FIRST SERIES OF STUDENT RESEARCH GROUP MEETINGS: GROUP #7 7.00-7.55pm 07/01/2025

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Agenda of Meeting with PNU Students prepared by  Prof Omar Hasan Kasule MB ChB (MUK), MPH (Harvard), DrPH (Harvard). 

 

Time

Sunday

Jan 5, 2025

Monday

Jan 6, 2025

Tuesday

Jan 7, 2025

Wednesday

Jan 8, 2025

Thursday

Jan 9, 2025

7.00pm –

 7.55pm

 

Group 1

Group 4

Group 7

Group 10

Group 13

8.00pm –

 8.55pm

 

Group 2

Group 5

Group 8

Group 11

 

9.00pm –

 9.55pm

 

Group 3

Group 6

Group 9

Group 12

 

 

AGENDA
  • Know one another: self-introductions – 5 minutes
  • The way forward – 5 minutes
  • Presentation of the proposed research program -5 minutes
  • Q&A and open discussion – 30 minutes

WAY FORWARD
  • Vision: publish at least 2 papers; the first a review within 6 months and the second based on laboratory or data analysis within 1-3 years.
  • First step: We shall start by brain-storming about the assigned topic then the group will review the literature to narrow down the topic and develop key words.
  • Second step: Systematic literature review within the group and 1-hour presentation to Prof Omar once a week or once every two weeks.
  • Third step: familiarization with available laboratory equipment and procedures to prepare one or more research proposal from each group. Faculty will be appointed as supervisors or principal investigators. Students will be co-authors.
  • Some of the research will be new and innovative. Some of it will be attempts at validating research carried outside the Kingdom.

GENE MAPPING OF COMMON CHILDHOOD CONDITIONS IN SAUDI ARABIA: diabetes, asthma - 1
  • Gene variants relate to common disease conditions in Saudi Arabia[1], especially because of consanguineous marriages[2].
  • Gene mapping identifies the location of a gene on the chromosome or the distance between genes.
  • Genome mapping can be optical[3] or electronic[4].
  • Genome mapping can be related to specific disease conditions like diabetes[5],[6], asthma[7],[8],[9],[10],[11], wheezing conditions[12], several recessive conditions[13].

GENE MAPPING OF COMMON CHILDHOOD CONDITIONS IN SAUDI ARABIA: diabetes, asthma – 2
  • What is needed:
    • Identification of some common childhood diseases.
    • Thorough literature review to know what has been studied and discover gaps in knowledge.
    • Identification of specific topics and key words before undertaking a deeper literature review.
    • Eventually develop a proposal and do laboratory work using equipment and procedures available at the Research Center.

REFERENCE:

[1] Mariam Aleissa, Taghrid Aloraini, Lamia Fahad Alsubaie, Madawi Hassoun, Ghada Abdulrahman, Abdulrahman Swaid, Wafa Al Eyaid, Fuad Al Mutairi, Faroug Ababneh, Majid Alfadhel, and Ahmed Alfares. Common disease-associated gene variants in a Saudi Arabian population. Annals of Saudi Medicine. Volume 42, Issue 1 January-February 2022. BACKGROUND:  Screening programs for the most prevalent conditions occurring in a country is an evidence-based prevention strategy. The burden of autosomal recessive disease variations in Saudi Arabia is high because of the highly consanguineous population. The optimal solution for estimating the carrier frequency of the most prevalent diseases is carrier screening. OBJECTIVES: Identify the most influential recessive alleles associated with disease in the Saudi population. DESIGN:  We used clinical whole-exome sequencing data from an in-house familial database to evaluate the most prevalent genetic variations associated with disease in a Saudi population. SETTINGS:  King Abdullah International Medical Research Center (KAIMRC) and King Abdulaziz Medical City. METHODS:  Whole exome sequencing data obtained from clinical studies of family members, a cohort of 1314 affected and unaffected individuals, were filtered using the in-house pipeline to extract the most prevalent variant in the dataset. MAIN OUTCOME MEASURES:  Most prevalent genetic variations associated with disease in the Saudi population. SAMPLE SIZE:  1314 affected and unaffected individuals. RESULTS:  We identified 37 autosomal recessive variants and two heterozygous X-linked variants in 35 genes associated with the most prevalent disorders, which included hematologic (32%), endocrine (21%), metabolic (11%) and immunological (10%) diseases. CONCLUSION:  This study provides an update of the most frequently occurring alleles, which support future carrier screening programs. LIMITATIONS: Single center that might represent the different regions but may be biased. In addition, most of the families included in the database are part of the proband's genetic identification for specific phenotypes. 

[2] Amerh S. Alqahtani, Raniah S. Alotibi, Taghrid Aloraini, Fahad Almsned, Yara Alassali, Ahmed Alfares, Bader Alhaddad,, Mariam M. Al Eissa. Introduction: Rare diseases (RDs) create a massive burden for governments and families because sufferers of these diseases are required to undergo long-term treatment or rehabilitation to maintain a normal life. In Saudi Arabia (SA), the prevalence of RDs is high as a result of cultural and socio-economic factors. This study, however, aims to shed light on the genetic component of the prevalence of RDs in SA. Methodology: A retrospective study was conducted between September 2020 and December 2021 at King Saud Medical City, a tertiary hospital of the Ministry of Health (MOH), SA. A total of 1080 individuals with 544 potentially relevant variants were included. The index was 738, and the samples were tested in a commercialized laboratory using different molecular techniques, including next-generation sequencing. Result: A total of 867 molecular genetics tests were conducted on 738 probands. These tests included 610 exome sequencing (ES) tests, four genome sequencing (GS) tests, 82 molecular panels, 106 single nucleotide polymorphism (SNP) array, four methylation studies, 58 single-gene studies and three mitochondrial genome sequencing tests. The diagnostic yield among molecular genetics studies was 41.8% in ES, 24% in panels, 12% in SNP array and 24% in single gene studies. The majority of the identified potential variants (68%) were single nucleotide variants (SNV). Other ascertained variants included frameshift (11%), deletion (10%), duplication (5%), splicing (9%), in-frame deletion (3%) and indels (1%). The rate of positive consanguinity was 56%, and the autosomal recessive accounted for 54%. We found a significant correlation between the ES detection rate and positive consanguinity. We illustrated the presence of rare treatable conditions in DNAJC12, SLC19A3, and ALDH7A1, and the presence of the founder effect variant in SKIC2. Neurodevelopmental disorders were the main phenotype for which genetics studies were required (35.7%). Conclusion: This is the sixth-largest local study reporting next-generation sequencing. The results indicate the influence of consanguineous marriages on genetic disease and the burden it causes for the Kingdom of SA. This study highlights the need to enrich our society’s knowledge of genetic disorders. We recommend utilising ES as a first-tier test to establish genetic diagnosis in a highly consanguineous population.

[3] Paul Dremsek, Thomas Schwarz, Beatrix Weil, Alina Malashka, Franco Laccone, Jürgen Neesen. Optical Genome Mapping in Routine Human Genetic Diagnostics-Its Advantages and Limitations. Genes (Basel). 2021 Dec 8;12(12):1958. In recent years, optical genome mapping (OGM) has developed into a highly promising method of detecting large-scale structural variants in human genomes. It is capable of detecting structural variants considered difficult to detect by other current methods. Hence, it promises to be feasible as a first-line diagnostic tool, permitting insight into a new realm of previously unknown variants. However, due to its novelty, little experience with OGM is available to infer best practices for its application or to clarify which features cannot be detected. In this study, we used the Saphyr system (Bionano Genomics, San Diego, CA, USA), to explore its capabilities in human genetic diagnostics. To this end, we tested 14 DNA samples to confirm a total of 14 different structural or numerical chromosomal variants originally detected by other means, namely, deletions, duplications, inversions, trisomies, and a translocation. Overall, 12 variants could be confirmed; one deletion and one inversion could not. The prerequisites for detection of similar variants were explored by reviewing the OGM data of 54 samples analyzed in our laboratory. Limitations, some owing to the novelty of the method and some inherent to it, were described. Finally, we tested the successful application of OGM in routine diagnostics and described some of the challenges that merit consideration when utilizing OGM as a diagnostic tool. Keywords: OGM; cytogenetics; cytogenomics; numerical chromosomal aberrations; optical genome mapping; routine genetic testing; structural chromosomal aberrations.

[4] Sarah Moore, Jean McGowan-Jordan, Adam C Smith, Katrina Rack, Udo Koehler, Marian Stevens-Kroef, Hayk Barseghyan, Rashmi Kanagal-Shamanna, Ros Hastings, ISCN Standing Committee. Genome Mapping Nomenclature. Cytogenet Genome Res. 2023;163(5-6):236-246. Background: Genome Mapping Technologies (optical and electronic) use ultra-high molecular weight DNA to detect structural variation and have application in constitutional genetic disorders, hematological neoplasms, and solid tumors. Genome mapping can detect balanced and unbalanced structural variation, copy number changes, and haplotypes. The technique is analogous to chromosomal microarray analysis, although genome mapping has the added benefit of being able to detect and ascertain the nature of more abnormalities in a single assay than array, karyotyping, or FISH alone. Key messages: This paper describes a specific nomenclature for genome mapping that can be used by diagnostic and research centers to report their findings accurately. An international nomenclature is essential for patient results to be understood by different healthcare providers as well as for clear communication in publications and consistency in databases. Summary: Genome mapping can detect aneuploidy, balanced and unbalanced structural variation, as well as copy number changes. The Standing Committee for the International System for Human Cytogenomic Nomenclature (ISCN) recognised there was a need for a specific nomenclature for genome mapping that encompasses the range of abnormalities detected by this technique. This paper explains the general principles of the nomenclature as well as giving specific ISCN examples for the different types of numerical and structural rearrangements.

Keywords: Chromosome abnormalities; Fusion gene; Genome mapping; ISCN; Nomenclature; OGM.

[5] Karmen Stankov, Damir Benc, Dragan Draskovic. Genetic and epigenetic factors in etiology of diabetes mellitus type 1. Pediatrics. 2013 Dec;132(6):1112-22. Diabetes mellitus type 1 (T1D) is a complex disease resulting from the interplay of genetic, epigenetic, and environmental factors. Recent progress in understanding the genetic basis of T1D has resulted in an increased recognition of childhood diabetes heterogeneity. After the initial success of family-based linkage analyses, which uncovered the strong linkage and association between HLA gene variants and T1D, genome-wide association studies performed with high-density single-nucleotide polymorphism genotyping platforms provided evidence for a number of novel loci, although fine mapping and characterization of these new regions remains to be performed. T1D is one of the most heritable common diseases, and among autoimmune diseases it has the largest range of concordance rates in monozygotic twins. This fact, coupled with evidence of various epigenetic modifications of gene expression, provides convincing proof of the complex interplay between genetic and environmental factors. In T1D, epigenetic phenomena, such as DNA methylation, histone modifications, and microRNA dysregulation, have been associated with altered gene expression. Increasing epidemiologic and experimental evidence supports the role of genetic and epigenetic alterations in the etiopathology of diabetes. We discuss recent results related to the role of genetic and epigenetic factors involved in development of T1D. 

[6] Andrea K Steck, Marian J Rewers. Genetics of type 1 diabetes. Clin Chem. 2011 Feb;57(2):176-85. Background: Type 1 diabetes, a multifactorial disease with a strong genetic component, is caused by the autoimmune destruction of pancreatic β cells. The major susceptibility locus maps to the HLA class II genes at 6p21, although more than 40 non-HLA susceptibility gene markers have been confirmed. Content: Although HLA class II alleles account for up to 30%-50% of genetic type 1 diabetes risk, multiple non-MHC loci contribute to disease risk with smaller effects. These include the insulin, PTPN22, CTLA4, IL2RA, IFIH1, and other recently discovered loci. Genomewide association studies performed with high-density single-nucleotide-polymorphism genotyping platforms have provided evidence for a number of novel loci, although fine mapping and characterization of these new regions remain to be performed. Children born with the high-risk genotype HLADR3/4-DQ8 comprise almost 50% of children who develop antiislet autoimmunity by the age of 5 years. Genetic risk for type 1 diabetes can be further stratified by selection of children with susceptible genotypes at other diabetes genes, by selection of children with a multiple family history of diabetes, and/or by selection of relatives that are HLA identical to the proband. Summary: Children with the HLA-risk genotypes DR3/4-DQ8 or DR4/DR4 who have a family history of type 1 diabetes have more than a 1 in 5 risk for developing islet autoantibodies during childhood, and children with the same HLA-risk genotype but no family history have approximately a 1 in 20 risk. Determining extreme genetic risk is a prerequisite for the implementation of primary prevention trials, which are now underway for relatives of individuals with type 1 diabetes.

[7] Carole Ober, Chris G McKennan, Kevin M Magnaye, Matthew C Altman, Charles Washington 3rd, Catherine Stanhope, Katherine A Naughton, Mario G Rosasco, Leonard B Bacharier, Dean Billheimer, Diane R Gold, Lisa Gress, Tina Hartert, Suzanne Havstad, Gurjit K Khurana Hershey, Brian Hallmark, D Kyle Hogarth, Daniel J Jackson, Christine C Johnson, Meyer Kattan, Robert F Lemanske, Susan V Lynch, Eneida A Mendonca, Rachel L Miller, Edward T Naureckas, George T O'Connor, Christine M Seroogy, Ganesa Wegienka, Steven R White, Robert A Wood, Anne L Wright, Edward M Zoratti, Fernando D Martinez, Dennis Ownby, Dan L Nicolae, Albert M Levin, James E Gern; Environmental Influences on Child Health Outcomes-Children's Respiratory Research Workgroup. Expression quantitative trait locus fine mapping of the 17q12-21 asthma locus in African American children: a genetic association and gene expression study.  Lancet Respir Med. 2020 May;8(5):482-492. Background: African ancestry is associated with a higher prevalence and greater severity of asthma than European ancestries, yet genetic studies of the most common locus associated with childhood-onset asthma, 17q12-21, in African Americans have been inconclusive. The aim of this study was to leverage both the phenotyping of the Children's Respiratory and Environmental Workgroup (CREW) birth cohort consortium, and the reduced linkage disequilibrium in African Americans, to fine map the 17q12-21 locus. Methods: We first did a genetic association study and meta-analysis using 17q12-21 tag single-nucleotide polymorphisms (SNPs) for childhood-onset asthma in 1613 European American and 870 African American children from the CREW consortium. Nine tag SNPs were selected based on linkage disequilibrium patterns at 17q12-21 and their association with asthma, considering the effect allele under an additive model (0, 1, or 2 effect alleles). Results were meta-analysed with publicly available summary data from the EVE consortium (on 4303 European American and 3034 African American individuals) for seven of the nine SNPs of interest. Subsequently, we tested for expression quantitative trait loci (eQTLs) among the SNPs associated with childhood-onset asthma and the expression of 17q12-21 genes in resting peripheral blood mononuclear cells (PBMCs) from 85 African American CREW children and in upper airway epithelial cells from 246 African American CREW children; and in lower airway epithelial cells from 44 European American and 72 African American adults from a case-control study of asthma genetic risk in Chicago (IL, USA). Findings: 17q12-21 SNPs were broadly associated with asthma in European Americans. Only two SNPs (rs2305480 in gasdermin-B [GSDMB] and rs8076131 in ORMDL sphingolipid biosynthesis regulator 3 [ORMDL3]) were associated with asthma in African Americans, at a Bonferroni-corrected threshold of p<0·0055 (for rs2305480_G, odds ratio [OR] 1·36 [95% CI 1·12-1·65], p=0·0014; and for rs8076131_A, OR 1·37 [1·13-1·67], p=0·0010). In upper airway epithelial cells from African American children, genotype at rs2305480 was the most significant eQTL for GSDMB (eQTL effect size [β] 1·35 [95% CI 1·25-1·46], p<0·0001), and to a lesser extent showed an eQTL effect for post-GPI attachment to proteins phospholipase 3 (β 1·15 [1·08-1·22], p<0·0001). No SNPs were eQTLs for ORMDL3. By contrast, in PBMCs, the five core SNPs were associated only with expression of GSDMB and ORMDL3. Genotype at rs12936231 (in zona pellucida binding protein 2) showed the strongest associations across both genes (for GSDMB, eQTLβ 1·24 [1·15-1·32], p<0·0001; and for ORMDL3 (β 1·19 [1·12-1·24], p<0·0001). The eQTL effects of rs2305480 on GSDMB expression were replicated in lower airway cells from African American adults (β 1·29 [1·15-1·44], p<0·0001). Interpretation: Our study suggests that SNPs regulating GSDMB expression in airway epithelial cells have a major role in childhood-onset asthma, whereas SNPs regulating the expression levels of 17q12-21 genes in resting blood cells are not central to asthma risk. Our genetic and gene expression data in African Americans and European Americans indicated GSDMB to be the leading candidate gene at this important asthma locus.

[8] Ming-Liang Gu, Jing Zhao. Mapping and localization of susceptible genes in asthma. Chin Med J (Engl). 2011 Jan;124(1):132-43. Objective: To elucidate the development of mapping and localization of susceptible genes on chromosomes to asthma related phenotypes. Data sources: Published articles about susceptibility genes for asthma related phenotypes were selected using PubMed. Study selection: Using methods of candidate gene positional clone and genome-wide scan with linkage and association analysis to determine the location in the genome of susceptibility genes to asthma and asthma related phenotypes. Results: There are multiple regions in the genome harboring susceptibility genes to asthma and asthma related phenotypes, including chromosomes 5, 11, 12, 6, 2, 3, 13, 7, 14, 9, 19 and 17. Many of these regions contain candidate genes involved in asthma development and progression. Some susceptible genes may affect the phenotype expression or response to therapy. In addition, the interaction of multiple genes with the environment may contribute to the susceptibility to asthma. Conclusions: As an essential step toward cloning the susceptible genes to asthma, fine mapping and localization on chromosomes are definitely needed. Novel powerful tools for gene discovery and the integration of genetics, biology and bioinformatics should be pursued.

[9] Ming-Liang Gu, Xiao-Qun Dong, Jing Zhao. New insight into the genes susceptible to asthma. J Asthma. 2010 Mar;47(2):113-6. There is considerable worldwide interest in identifying genes related to susceptibility to asthma. Progress has been slow in part because of the complexity and heterogeneity of the disease. Although at least 170 genes located on 10 chromosomes have been associated with or in linkage with asthma and asthma-related phenotypes, the majority of the reports have either been preliminary or the results have been controversial. In order to overcome the problems with the inherent complexity of asthma and methodological issues, the authors propose a strategy for identification of asthma susceptibility genes based on theories of systems biology and bioinformatics and candidate gene approach.

[10] Hongsheng Gui, Albert M Levin, Donglei Hu, Patrick Sleiman, Shujie Xiao, Angel C Y Mak, Mao Yang, Andrea J Barczak, Scott Huntsman, Celeste Eng, Samantha Hochstadt, Ellen Zhang, Kyle Whitehouse, Samantha Simons, Whitney Cabral, Sami Takriti, Gonçalo Abecasis, Thomas W Blackwell, Hyun Min Kang, Deborah A Nickerson, Soren Germer, David E Lanfear, Frank Gilliland, W James Gauderman, Rajesh Kumar, David J Erle, Fernando D Martinez, Hakon Hakonarson, Esteban G Burchard, L Keoki Williams. Mapping the 17q12-21.1 Locus for Variants Associated with Early-Onset Asthma in African Americans. Am J Respir Crit Care Med. 2021 Feb 15;203(4):424-436. Rationale: The 17q12-21.1 locus is one of the most highly replicated genetic associations with asthma. Individuals of African descent have lower linkage disequilibrium in this region, which could facilitate identifying causal variants.Objectives: To identify functional variants at 17q12-21.1 associated with early-onset asthma among African American individuals.Methods: We evaluated African American participants from SAPPHIRE (Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-Ethnicity) (n = 1,940), SAGE II (Study of African Americans, Asthma, Genes and Environment) (n = 885), and GCPD-A (Study of the Genetic Causes of Complex Pediatric Disorders-Asthma) (n = 2,805). Associations with asthma onset at ages under 5 years were meta-analyzed across cohorts. The lead signal was reevaluated considering haplotypes informed by genetic ancestry (i.e., African vs. European). Both an expression-quantitative trait locus analysis and a phenome-wide association study were performed on the lead variant.Measurements and Main Results: The meta-analyzed results from SAPPHIRE, SAGE II, and the GCPD-A identified rs11078928 as the top association for early-onset asthma. A haplotype analysis suggested that the asthma association partitioned most closely with the rs11078928 genotype. Genetic ancestry did not appear to influence the effect of this variant. In the expression-quantitative trait locus analysis, rs11078928 was related to alternative splicing of GSDMB(gasdermin-B) transcripts. The phenome-wide association study of rs11078928 suggested that this variant was predominantly associated with asthma and asthma-associated symptoms. Conclusions: A splice-acceptor polymorphism appears to be a causal variant for asthma at the 17q12-21.1 locus. This variant appears to have the same magnitude of effect in individuals of African and European descent.

[11] Michelle M Stein, Emma E , Nathan Schoettler, Britney A Helling, Kevin M Magnaye, Catherine Stanhope, Catherine Igartua, Andréanne Morin, Charles Washington 3rd, Dan Nicolae, Klaus Bønnelykke, Carole Ober. A decade of research on the 17q12-21 asthma locus: Piecing together the puzzle. J Allergy Clin Immunol. 2018 Sep;142(3):749-764.e3. Chromosome 17q12-21 remains the most highly replicated and significant asthma locus. Genotypes in the core region defined by the first genome-wide association study correlate with expression of 2 genes, ORM1-like 3 (ORMDL3) and gasdermin B (GSDMB), making these prime candidate asthma genes, although recent studies have implicated gasdermin A (GSDMA) distal to and post-GPI attachment to proteins 3 (PGAP3) proximal to the core region as independent loci. We review 10 years of studies on the 17q12-21 locus and suggest that genotype-specific risks for asthma at the proximal and distal loci are not specific to early-onset asthma and mediated by PGAP3, ORMDL3, and/or GSDMA expression. We propose that the weak and inconsistent associations of 17q single nucleotide polymorphisms with asthma in African Americans is due to the high frequency of some 17q alleles, the breakdown of linkage disequilibrium on African-derived chromosomes, and possibly different early-life asthma endotypes in these children. Finally, the inconsistent association between asthma and gene expression levels in blood or lung cells from older children and adults suggests that genotype effects may mediate asthma risk or protection during critical developmental windows and/or in response to relevant exposures in early life. Thus studies of young children and ethnically diverse populations are required to fully understand the relationship between genotype and asthma phenotype and the gene regulatory architecture at this locus.

Keywords: GSDMA; GSDMB; ORMDL3; PGAP3; Wheezing; gene expression; genome-wide association study; immune cells; lung cells.

[12] Brian Hallmark, Ganesa Wegienka, Suzanne Havstad, Dean Billheimer, Dennis Ownby, Eneida A Mendonca, Lisa Gress, Debra A Stern, Jocelyn Biagini Myers, Gurjit K Khurana Hershey, Lori Hoepner, Rachel L Miller, Robert F Lemanske, Daniel J Jackson, Diane R Gold, George T O'Connor, Dan L Nicolae, James E Gern, Carole Ober, Anne L Wright, Fernando D Martinez. Chromosome 17q12-21 Variants Are Associated with Multiple Wheezing Phenotypes in Childhood. Am J Respir Crit Care Med. 2021 Apr 1;203(7):864-870. Rationale: Birth cohort studies have identified several temporal patterns of wheezing, only some of which are associated with asthma. Whether 17q12-21 genetic variants, which are closely associated with asthma, are also associated with childhood wheezing phenotypes remains poorly explored.Objectives: To determine whether wheezing phenotypes, defined by latent class analysis (LCA), are associated with nine 17q12-21 SNPs and if so, whether these relationships differ by race/ancestry.Methods: Data from seven U.S. birth cohorts (n = 3,786) from the CREW (Children's Respiratory Research and Environment Workgroup) were harmonized to represent whether subjects wheezed in each year of life from birth until age 11 years. LCA was then performed to identify wheeze phenotypes. Genetic associations between SNPs and wheeze phenotypes were assessed separately in European American (EA) (n = 1,308) and, for the first time, in African American (AA) (n = 620) children.Measurements and Main Results: The LCA best supported four latent classes of wheeze: infrequent, transient, late-onset, and persistent. Odds of belonging to any of the three wheezing classes (vs. infrequent) increased with the risk alleles for multiple SNPs in EA children. Only one SNP, rs2305480, showed increased odds of belonging to any wheezing class in both AA and EA children.Conclusions: These results indicate that 17q12-21 is a "wheezing locus," and this association may reflect an early life susceptibility to respiratory viruses common to all wheezing children. Which children will have their symptoms remit or reoccur during childhood may be independent of the influence of rs2305480.

[13]  Al-Owain M, Al-Zaidan H, Al-Hassnan Z. 2012. Map of autosomal recessive genetic disorders in Saudi Arabia: Concepts and future directions. Am J Med Genet Part A 158A: 2629–2640. Saudi Arabia has a population of 27.1 million. Prevalence of many autosomal recessive disorders is higher than in other known populations. This is attributable to the high rate of consanguineous marriages (56%), the tribal structure, and large family size. Founder mutations have been recognized in many autosomal recessive disorders, many of which are overrepresented within certain tribes. On the other hand, allelic heterogeneity is also observed among common and rare autosomal recessive conditions. With the adoption of more advanced molecular techniques in the country in recent years in conjunction with international collaboration, the mapping of various autosomal recessive disorders has increased dramatically. Different genetic concepts pertinent to this highly inbred population are discussed here. Addressing such genetic disorders at the national level will become a cornerstone of strategic health care initiatives in the 21st century. Current efforts are hampered by many socio-cultural and health care related factors. Education about genetic diseases, establishment of a “national registry” and mutational database, and enhanced healthcare access are crucial for success of any preventative campaign. © 2012 Wiley Periodicals, Inc.