Qatar genome: Insights on genomics from the Middle East.

Despite recent biomedical breakthroughs and large genomic studies growing momentum, the Middle Eastern population, home to over 400 million people, is underrepresented in the human genome variation databases. Here we describe insights from Phase 1 of the Qatar Genome Program with whole genome sequenced 6047 individuals from Qatar. We identified more than 88 million variants of which 24 million are novel and 23 million are singletons. Consistent with the high consanguinity and founder effects in the region, we found that several rare deleterious variants were more common in the Qatari population while others seem to provide protection against diseases and have shaped the genetic architecture of adaptive phenotypes. These results highlight the value of our data as a resource to advance genetic studies in the Arab and neighboring Middle Eastern populations and will significantly boost the current efforts to improve our understanding of global patterns of human variations, human history, and genetic contributions to health and diseases in diverse populations.

Willingness to participate in genome testing: a survey of public attitudes from Qatar.

Genomics has the potential to revolutionize medical approaches to disease prevention, diagnosis, and treatment, but it does not come without challenges. The success of a national population-based genome program, like the Qatar Genome Program (QGP), depends on the willingness of citizens to donate samples and take up genomic testing services. This study explores public attitudes of the Qatari population toward genetic testing and toward participating in the QGP. A representative sample of 837 adult Qataris was surveyed in May 2016. Approximately 71% of respondents surveyed reported that they were willing to participate in the activities of the QGP. Willingness to participate was significantly associated with basic literacy in genetics, a family history of genetic diseases, and previous experience with genetic testing through premarital screening. Respondents cited the desire to know more about their health status as the principle motivation for participating, while lack of time and information were reported as the most important barriers. With QGP plans to ramp up the scale of its national operation toward more integration into clinical care settings, it is critical to understand public attitudes and their determinants. The results demonstrate public support but also identify the need for more education and individual counseling that not only provide information on the process, challenges, and benefits of genomic testing, but that also address concerns about information security.

PopPAnTe: population and pedigree association testing for quantitative data.

BACKGROUND: Family-based designs, from twin studies to isolated populations with their complex genealogical data, are a valuable resource for genetic studies of heritable molecular biomarkers. Existing software for family-based studies have mainly focused on facilitating association between response phenotypes and genetic markers, and no user-friendly tools are at present available to straightforwardly extend association studies in related samples to large datasets of generic quantitative data, as those generated by current -omics technologies. RESULTS: We developed PopPAnTe, a user-friendly Java program, which evaluates the association of quantitative data in related samples. Additionally, PopPAnTe implements data pre and post processing, region based testing, and empirical assessment of associations. CONCLUSIONS: PopPAnTe is an integrated and flexible framework for pairwise association testing in related samples with a large number of predictors and response variables. It works either with family data of any size and complexity, or, when the genealogical information is unknown, it uses genetic similarity information between individuals as those inferred from genome-wide genetic data. It can therefore be particularly useful in facilitating usage of biobank data collections from population isolates when extensive genealogical information is missing.

A systems view of type 2 diabetes-associated metabolic perturbations in saliva, blood and urine at different timescales of glycaemic control.

AIMS/HYPOTHESIS: Metabolomics has opened new avenues for studying metabolic alterations in type 2 diabetes. While many urine and blood metabolites have been associated individually with diabetes, a complete systems view analysis of metabolic dysregulations across multiple biofluids and over varying timescales of glycaemic control is still lacking. METHODS: Here we report a broad metabolomics study in a clinical setting, covering 2,178 metabolite measures in saliva, blood plasma and urine from 188 individuals with diabetes and 181 controls of Arab and Asian descent. Using multivariate linear regression we identified metabolites associated with diabetes and markers of acute, short-term and long-term glycaemic control. RESULTS: Ninety-four metabolite associations with diabetes were identified at a Bonferroni level of significance (p < 2.3 × 10(-5)), 16 of which have never been reported. Sixty-five of these diabetes-associated metabolites were associated with at least one marker of glycaemic control in the diabetes group. Using Gaussian graphical modelling, we constructed a metabolic network that links diabetes-associated metabolites from three biofluids across three different timescales of glycaemic control. CONCLUSIONS/INTERPRETATION: Our study reveals a complex network of biochemical dysregulation involving metabolites from different pathways of diabetes pathology, and provides a reference framework for future diabetes studies with metabolic endpoints.

Elevated HbA1c levels in individuals not diagnosed with type 2 diabetes in Qatar: a pilot study.

BACKGROUND: The prevalence of type 2 diabetes (T2D) in Qatar and the Middle East is one of the highest in the world. It is estimated that about one quarter of the individuals with tbl2D are undiagnosed. Elevated HbA1c levels are an indicator of tbl2D or a pre-diabetic state. In this study we set out to examine which factors, such as anthropometric and socio-demographic risk factors, are associated with elevated HbA1c levels in a population without tbl2D. METHODS: We examined 191 subjects with no record of tbl2D. Anthropometrics and HbA1c were measured. Socio-demographic (age, gender, ethnicity and educational level) and health information were assessed through questionnaires. Elevated HbA1c levels were defined as >6.0% (>42 mmol/mol). Individual risk factors were examined in relationship to having elevated HbA1c levels using logistic regression. RESULTS: Thirty-eight (20%) study participants had elevated HbA1c levels. Participants from South Asian and Filipino descent were more likely to present with elevated HbA1c levels than Arab participants (adjusted odds ratios (OR): 13.30 (95% confidence interval (CI): 4.24, 41.79), p < 0.001 for South Asian and 4.54 (95% CI: 1.04, 19.83), p = 0.04 for Filipinos). A body mass index of above 30 kg/m(2) was associated with elevated HbA1c levels (adjusted OR: 2.90 (95% CI: 1.29, 6.51), p = 0.01). Neither gender nor educational level was associated with elevated HbA1c levels. CONCLUSIONS: Elevated HbA1c levels in individuals not diagnosed with diabetes were most frequently found in the South Asian and Filipino immigrant population. Special attention should therefore be given to the early identification of tbl2D in these subjects.

Cost-effectiveness analysis of genotype-guided optimization of major depression treatment in Qatar.

Background: Pharmacogenetic testing improves the efficacy and safety of antidepressant pharmacotherapy for moderate-severe major depressive disorder by identifying genetic variations that influence medication metabolism, and adjusting treatment regimens accordingly. This study aims to assess the cost-effectiveness of implementing a pharmacogenetic testing approach to guide the prescription of antidepressants. Methods: From the public hospital perspective, we developed a two-stage decision tree diagram of a short-term 6-week follow up, and a lifetime Markov model with 3-month cycles. The analysis compared the current standard of care with the alternative strategy of Pharmacogenetic-guided (multi-gene panel) testing in adult patients with moderate-severe major depressive disorder. Clinical outcomes and utilities were obtained from published studies, while healthcare costs were locally available. The short-term incremental cost-effectiveness ratio was against treatment response without side effects and without relapse, and against treatment response with/without side effects and without relapse. The long-term incremental cost-effectiveness ratio was against the quality-adjusted life year gained and years of life saved. Results: Adopting the pharmacogenetic-guided therapy for adult patients with moderate-severe major depressive disorder in Qatar resulted in cost savings of Qatari Riyal 2,289 (95% confidence interval, -22,654-26,340) for the health system. In the short term, the pharmacogenetic-guided testing was associated with higher response rates without side effects and without relapse (mean difference 0.10, 95% confidence interval 0.09-0.15) and higher response rates with or without side effects and without relapse (mean difference 0.05, 95% confidence interval 0.04-0.06). For long term, the pharmacogenetic-guided testing resulted in 0.13 years of life saved and 0.06 quality-adjusted life year gained, per person, along with cost savings of Qatari Riyal 46,215 (95% confidence interval-15,744-101,758). The sensitivity analyses confirmed the robustness of the model results. Conclusion: Implementing pharmacogenetic testing to guide antidepressant use was found to improve population health outcomes, while also significantly reducing health system costs.

QPGx-CARES: Qatar pharmacogenetics clinical applications and research enhancement strategies.

Pharmacogenetic (PGx)-informed medication prescription is a cutting-edge genomic application in contemporary medicine, offering the potential to overcome the conventional "trial-and-error" approach in drug prescription. The ability to use an individual's genetic profile to predict drug responses allows for personalized drug and dosage selection, thereby enhancing the safety and efficacy of treatments. However, despite significant scientific and clinical advancements in PGx, its integration into routine healthcare practices remains limited. To address this gap, the Qatar Genome Program (QGP) has embarked on an ambitious initiative known as QPGx-CARES (Qatar Pharmacogenetics Clinical Applications and Research Enhancement Strategies), which aims to set a roadmap for optimizing PGx research and clinical implementation on a national scale. The goal of QPGx-CARES initiative is to integrate PGx testing into clinical settings with the aim of improving patient health outcomes. In 2022, QGP initiated several implementation projects in various clinical settings. These projects aimed to evaluate the clinical utility of PGx testing, gather valuable insights into the effective dissemination of PGx data to healthcare professionals and patients, and identify the gaps and the challenges for wider adoption. QPGx-CARES strategy aimed to integrate evidence-based PGx findings into clinical practice, focusing on implementing PGx testing for cardiovascular medications, supported by robust scientific evidence. The current initiative sets a precedent for the nationwide implementation of precision medicine across diverse clinical domains.

A roadmap to the molecular human linking multiomics with population traits and diabetes subtypes.

In-depth multiomic phenotyping provides molecular insights into complex physiological processes and their pathologies. Here, we report on integrating 18 diverse deep molecular phenotyping (omics-) technologies applied to urine, blood, and saliva samples from 391 participants of the multiethnic diabetes Qatar Metabolomics Study of Diabetes (QMDiab). Using 6,304 quantitative molecular traits with 1,221,345 genetic variants, methylation at 470,837 DNA CpG sites, and gene expression of 57,000 transcripts, we determine (1) within-platform partial correlations, (2) between-platform mutual best correlations, and (3) genome-, epigenome-, transcriptome-, and phenome-wide associations. Combined into a molecular network of > 34,000 statistically significant trait-trait links in biofluids, our study portrays "The Molecular Human". We describe the variances explained by each omics in the phenotypes (age, sex, BMI, and diabetes state), platform complementarity, and the inherent correlation structures of multiomics data. Further, we construct multi-molecular network of diabetes subtypes. Finally, we generated an open-access web interface to "The Molecular Human" ( http://comics.metabolomix.com ), providing interactive data exploration and hypotheses generation possibilities.

The QChip1 knowledgebase and microarray for precision medicine in Qatar.

Risk genes for Mendelian (single-gene) disorders (SGDs) are consistent across populations, but pathogenic risk variants that cause SGDs are typically population-private. The goal was to develop "QChip1," an inexpensive genotyping microarray to comprehensively screen newborns, couples, and patients for SGD risk variants in Qatar, a small nation on the Arabian Peninsula with a high degree of consanguinity. Over 108 variants in 8445 Qatari were identified for inclusion in a genotyping array containing 165,695 probes for 83,542 known and potentially pathogenic variants in 3438 SGDs. QChip1 had a concordance with whole-genome sequencing of 99.1%. Testing of QChip1 with 2707 Qatari genomes identified 32,674 risk variants, an average of 134 pathogenic alleles per Qatari genome. The most common pathogenic variants were those causing homocystinuria (1.12% risk allele frequency), and Stargardt disease (2.07%). The majority (85%) of Qatari SGD pathogenic variants were not present in Western populations such as European American, South Asian American, and African American in New York City and European and Afro-Caribbean in Puerto Rico; and only 50% were observed in a broad collection of data across the Greater Middle East including Kuwait, Iran, and United Arab Emirates. This study demonstrates the feasibility of developing accurate screening tools to identify SGD risk variants in understudied populations, and the need for ancestry-specific SGD screening tools.

Rare loss-of-function variants in type I IFN immunity genes are not associated with severe COVID-19.

A recent report found that rare predicted loss-of-function (pLOF) variants across 13 candidate genes in TLR3- and IRF7-dependent type I IFN pathways explain up to 3.5% of severe COVID-19 cases. We performed whole-exome or whole-genome sequencing of 1,864 COVID-19 cases (713 with severe and 1,151 with mild disease) and 15,033 ancestry-matched population controls across 4 independent COVID-19 biobanks. We tested whether rare pLOF variants in these 13 genes were associated with severe COVID-19. We identified only 1 rare pLOF mutation across these genes among 713 cases with severe COVID-19 and observed no enrichment of pLOFs in severe cases compared to population controls or mild COVID-19 cases. We found no evidence of association of rare LOF variants in the 13 candidate genes with severe COVID-19 outcomes.

Failure to replicate the association of rare loss-of-function variants in type I IFN immunity genes with severe COVID-19.

A recent report found that rare predicted loss-of-function (pLOF) variants across 13 candidate genes in TLR3- and IRF7-dependent type I IFN pathways explain up to 3.5% of severe COVID-19 cases. We performed whole-exome or whole-genome sequencing of 1,934 COVID-19 cases (713 with severe and 1,221 with mild disease) and 15,251 ancestry-matched population controls across four independent COVID-19 biobanks. We then tested if rare pLOF variants in these 13 genes were associated with severe COVID-19. We identified only one rare pLOF mutation across these genes amongst 713 cases with severe COVID-19 and observed no enrichment of pLOFs in severe cases compared to population controls or mild COVID-19 cases. We find no evidence of association of rare loss-of-function variants in the proposed 13 candidate genes with severe COVID-19 outcomes.

Epigenetic associations of type 2 diabetes and BMI in an Arab population.

BACKGROUND: The prevalence of type 2 diabetes (T2D) and obesity has dramatically increased within a few generations, reaching epidemic levels. In addition to genetic risk factors, epigenetic mechanisms triggered by changing environment are investigated for their role in the pathogenesis of these complex diseases. Epigenome-wide association studies (EWASs) have revealed significant associations of T2D, obesity, and BMI with DNA methylation. However, populations from the Middle East, where T2D and obesity rates are highest worldwide, have not been investigated so far. METHODS: We performed the first EWAS in an Arab population with T2D and BMI and attempted to replicate 47 EWAS associations previously reported in Caucasians. We used the Illumina Infinium HumanMethylation450 BeadChip to quantify DNA methylation in whole blood DNA from 123 subjects of 15 multigenerational families from Qatar. To investigate the effect of differing genetic background and environment on the epigenetic associations, we further assessed the effect of replicated loci in 810 twins from UK. RESULTS: Our EWAS suggested a novel association between T2D and cg06721411 (DQX1; p value = 1.18 × 10(-9)). We replicated in the Qatari population seven CpG associations with BMI (SOCS3, p value = 3.99 × 10(-6); SREBF1, p value = 4.33 × 10(-5); SBNO2, p value = 5.87 × 10(-5); CPT1A, p value = 7.99 × 10(-5); PRR5L, p value = 1.85 × 10(-4); cg03078551, intergenic region on chromosome 17; p value = 1.00 × 10(-3); LY6G6E, p value = 1.10 × 10(-3)) and one with T2D (TXNIP, p value = 2.46 × 10(-5)). All the associations were further confirmed in the UK cohort for both BMI and T2D. Meta-analysis increased the significance of the observed associations and revealed strong heterogeneity of the effect sizes (apart from CPT1A), although associations at these loci showed concordant direction in the two populations. CONCLUSIONS: Our study replicated eight known CpG associations with T2D or BMI in an Arab population. Heterogeneity of the effects at all loci except CPT1A between the Qatari and UK studies suggests that the underlying mechanisms might depend on genetic background and environmental pressure. Our EWAS results provide a basis for comparison with other ethnicities.

Mendelian inheritance of trimodal CpG methylation sites suggests distal cis-acting genetic effects.

BACKGROUND: Environmentally influenced phenotypes, such as obesity and insulin resistance, can be transmitted over multiple generations. Epigenetic modifications, such as methylation of DNA cytosine-guanine (CpG) pairs, may be carriers of inherited information. At the population level, the methylation state of such "heritable" CpG sites is expected to follow a trimodal distribution, and their mode of inheritance should be Mendelian. METHODS: Using the Illumina Infinium 450 K DNA methylation array, we determined DNA CpG-methylation in blood cells from a family cohort 123 individuals of Arab ethnicity, including 18 elementary father-mother-child trios, we asked whether Mendelian inheritance of CpG methylation is observed, and most importantly, whether it is independent of any genetic signals. Using 40× whole genome sequencing, we therefore excluded all CpG sites with possibly confounding genetic variants (SNP) within the binding regions of the Illumina probes. RESULTS: We identified a total of 955 CpG sites that displayed a trimodal distribution and confirmed trimodality in a study of 1805 unrelated Caucasians. Of 955 CpG sites, 99.9% observed a strict Mendelian pattern of inheritance and had no SNP within +/-110 nucleotides of the CpG site by design. However, in 97% of these cases a distal cis-acting SNP within a +/-1 Mbp window was found that explained the observed CpG distribution, excluding the hypothesis of epigenetic inheritance for these clear-cut trimodal sites. Using power analysis, we showed that in 46% of all cases, the closest CpG-associated SNP was located more than 1000 bp from the CpG site. CONCLUSIONS: Our findings suggest that CpG methylation is maintained over larger genomic distances. Furthermore, nearly half of the SNPs associated with these trimodal sites were also associated with the expression of nearby genes (P = 4.08 × 10-6), implying a regulatory effect of these trimodal CpG sites.

Association of DNA methylation with age, gender, and smoking in an Arab population.

BACKGROUND: Modification of DNA by methylation of cytosines at CpG dinucleotides is a widespread phenomenon that leads to changes in gene expression, thereby influencing and regulating many biological processes. Recent technical advances in the genome-wide determination of single-base DNA-methylation enabled epigenome-wide association studies (EWASs). Early EWASs established robust associations between age and gender with the degree of CpG methylation at specific sites. Other studies uncovered associations with cigarette smoking. However, so far these studies were mainly conducted in Caucasians, raising the question of whether these findings can also be extrapolated to other populations. RESULTS: Here, we present an EWAS with age, gender, and smoking status in a family study of 123 individuals of Arab descent. We determined DNA methylation at over 450,000 CpG sites using the Illumina Infinium HumanMethylation450 BeadChip, applied state-of-the-art data processing protocols, including correction for blood cell type heterogeneity and hidden confounders, and eliminated probes containing SNPs at the targeted CpG site using 40× whole-genome sequencing data. Using this approach, we could replicate the leading published EWAS associations with age, gender and smoking, and recovered hallmarks of gender-specific epigenetic changes. Interestingly, we could even replicate the recently reported precise prediction of chronological age based on the methylation of only a few selected CpG sites. CONCLUSION: Our study supports the view that when applied with state-of-the art protocols to account for all potential confounders, DNA methylation arrays represent powerful tools for EWAS with more complex phenotypes that can also be successfully applied to non-Caucasian populations.

Evaluation of SNP calling using single and multiple-sample calling algorithms by validation against array base genotyping and Mendelian inheritance.

BACKGROUND: With diminishing costs of next generation sequencing (NGS), whole genome analysis becomes a standard tool for identifying genetic causes of inherited diseases. Commercial NGS service providers in general not only provide raw genomic reads, but further deliver SNP calls to their clients. However, the question for the user arises whether to use the SNP data as is, or process the raw sequencing data further through more sophisticated SNP calling pipelines with more advanced algorithms. RESULTS: Here we report a detailed comparison of SNPs called using the popular GATK multiple-sample calling protocol to SNPs delivered as part of a 40x whole genome sequencing project by Illumina Inc of 171 human genomes of Arab descent (108 unrelated Qatari genomes, 19 trios, and 2 families with rare diseases) and compare them to variants provided by the Illumina CASAVA pipeline. GATK multi-sample calling identifies more variants than the CASAVA pipeline. The additional variants from GATK are robust for Mendelian consistencies but weak in terms of statistical parameters such as TsTv ratio. However, these additional variants do not make a difference in detecting the causative variants in the studied phenotype. CONCLUSION: Both pipelines, GATK multi-sample calling and Illumina CASAVA single sample calling, have highly similar performance in SNP calling at the level of putatively causative variants.

1,5-Anhydroglucitol in saliva is a noninvasive marker of short-term glycemic control.

CONTEXT: In most ethnicities at least a quarter of all cases with diabetes is assumed to be undiagnosed. Screening for diabetes using saliva has been suggested as an effective approach to identify affected individuals. OBJECTIVE: The objective of the study was to identify a noninvasive metabolic marker of type 2 diabetes in saliva. DESIGN AND SETTING: In a case-control study of type 2 diabetes, we used a clinical metabolomics discovery study to screen for diabetes-relevant metabolic readouts in saliva, using blood and urine as a reference. With a combination of three metabolomics platforms based on nontargeted mass spectrometry, we examined 2178 metabolites in saliva, blood plasma, and urine samples from 188 subjects with type 2 diabetes and 181 controls of Arab and Asian ethnicities. RESULTS: We found a strong association of type 2 diabetes with 1,5-anhydroglucitol (1,5-AG) in saliva (P = 3.6 × 10(-13)). Levels of 1,5-AG in saliva highly correlated with 1,5-AG levels in blood and inversely correlated with blood glucose and glycosylated hemoglobin levels. These findings were robust across three different non-Caucasian ethnicities (Arabs, South Asians, and Filipinos), irrespective of body mass index, age, and gender. CONCLUSIONS: Clinical studies have already established 1,5-AG in blood as a reliable marker of short-term glycemic control. Our study suggests that 1,5-AG in saliva can be used in national screening programs for undiagnosed diabetes, which are of particular interest for Middle Eastern countries with young populations and exceptionally high diabetes rates.

Ethnic and gender differences in advanced glycation end products measured by skin auto-fluorescence.

Background Advanced glycation end products (AGEs) have been shown to be a predictor of cardiovascular risk in Caucasian subjects. In this study we examine whether the existing reference values are useable for non-Caucasian ethnicities. Furthermore, we assessed whether gender and smoking affect AGEs. Methods AGEs were determined by a non-invasive method of skin auto-fluorescence (AF). AF was measured in 200 Arabs, 99 South Asians, 35 Filipinos and 14 subjects of other/mixed ethnicity in the Qatar Metabolomics Study on Diabetes (QMDiab). Using multivariate linear regression analysis and adjusting for age and type 2 diabetes, we assessed whether ethnicity, gender and smoking were associated with AF. Results The mean AF was 2.27 arbitrary units (AU) (SD: 0.63). Arabs and Filipinos had a significant higher AF than the South Asian population (0.25 arbitrary units (AU) (95% CI: 0.11‒0.39), p = 0.001 and 0.34 (95% CI: 0.13‒0.55), p = 0.001 respectively). Also, AF was significantly higher in females (0.41 AU (95% CI: 0.29‒0.53), p < 0.001). AF associated with smoking (0.21 AU (95% CI: 0.01‒0.41), p = 0.04) and increased with the number of pack-years smoked (p = 0.02). Conclusions This study suggests that the existing reference values should take ethnicity, gender and smoking into account. Larger studies in specific ethnicities are necessary to create ethnic- and gender-specific reference values.