Myeloproliferative neoplasms are clonal disorders characterized by the presence of several gene mutations associated with particular hematologic parameters, clinical evolution, and prognosis. Few therapeutic options are available, among which interferon α (IFNα) presents interesting properties like the ability to induce hematologic responses (HRs) and molecular responses (MRs) in patients with JAK2 mutation. We report on the response to IFNα therapy in a cohort of 31 essential thrombocythemia (ET) patients with CALR mutations (mean follow-up of 11.8 years). HR was achieved in all patients. Median CALR mutant allelic burden (%CALR) significantly decreased from 41% at baseline to 26% after treatment, and 2 patients even achieved complete MR. In contrast, %CALR was not significantly modified in ET patients treated with hydroxyurea or aspirin only. Next-generation sequencing identified additional mutations in 6 patients (affecting TET2, ASXL1, IDH2, and TP53 genes). The presence of additional mutations was associated with poorer MR on CALR mutant clones, with only minor or no MRs in this subset of patients. Analysis of the evolution of the different variant allele frequencies showed that the mutated clones had a differential sensitivity to IFNα in a given patient, but no new mutation emerged during treatment. In all, this study shows that IFNα induces high rates of HRs and MRs in CALR-mutated ET, and that the presence of additional nondriver mutations may influence the MR to therapy.

Background: Consanguineous marriages are common in the Middle East including the Gulf countries. The rate of consanguinity in Qatar is approximately 54%, which are mainly first cousins’ marriages. Previous studies showed that consanguinity increases the prevalence of birth defects and other genetic disorders. Thus, we studied the effects of consanguinity in a cohort of subjects with certain genetic disorders in Qatar.Methods: This cross‐sectional study was conducted at two centers in Qatar (Hamad Medical Corporation “HMC” and Shafallah “SC”) including 599 Qatari families with certain types of genetic and nongenetic anomalies.Results: Consanguineous marriages were seen in 397 of 599 (66.2%) Qatari families and first cousin group counts for 65% in Qatari population. In the total cohort and at HMC, all consanguineous marriages had a significantly higher risk of Autosomal Recessive disorders than nonconsanguineous marriages (total cohort: odds ratio (OR) = 1.72; 95% CI: 1.10, 2.71; p = .02; HMC: OR = 2.98; 95% CI: 1.37, 6.09; p = .005). On the other hand, at HMC, nonconsanguinity was significantly related to chromosomal abnormality (OR = 6.36; 95% CI: 1.13, 35.85; p = .036).Conclusion: Our data suggest a significant role of parental consanguinity in increasing the prevalence of genetic disorders; mainly Autosomal Recessive disorders. Chromosomal abnormality disorders were significantly higher among nonconsanguineous marriages. These results help better inform policy makers on social, educational, and public health initiatives that might mitigate the impact of genetic disease in the Qatari society.

The prevalence rate of Autism Spectrum Disorder (ASD) has reached over 1% world-wide prompting governments, health providers and schools to develop programs and policies to address this challenging disorder. Here, we review the cause(s), as well as environmental factors, genetic mutations, and neural pathways that are implicated in ASD. We also discuss the criteria that are commonly used for the diagnosis of ASD and future clinical genetic testing that can aid in the diagnosis of this disorder. Finally, we provide practical steps that can be used to reduce the incidence and severity of ASD, as well as prognosis and treatment of autism.

Precision medicine—of which precision prescribing is a core component—is becoming a new frontier in today’s healthcare. Both artificial intelligence (AI) and machine learning (ML) have the potential to enhance our understanding of data and therefore our ability to accurately diagnose and treat patients. By leveraging these technologies and processes, we can uncover associations between a person’s genomic makeup and their health, identify biomarkers associated with diseases, fine-tune patient selection for clinical trials, reduce costs, and accelerate drug discovery and vaccine development. Although real-world data pose challenges in terms of collection, representation, and missing or inaccurate data sets, the integration of precision medicine into healthcare is critical. Clearly, precision medicine can benefit from health information innovations that empower decision-making at the patient level. Healthcare fusion is an example of an innovative framework and process [K Zhai et al. ECKM 2022, 20(3), pp. 179–192]. Data science and process improvement are also expected to play a role in resource planning and operational efficiency for optimal patient-centered care. Driving this transformation are advances in ‘omics’ technologies, digital devices, and imaging capabilities, along with an arsenal of powerful analytics tools working across a multitude of institutions and stakeholders. Encompassing this entire ecosystem, medicine will be evidence-based and driven by three key components: (1) Data curation through clinical diagnostics and behavioral apps that capture health and disease states; (2) Individualized solutions driven by advanced data analytics and personalized therapies; and (3) Business models that deliver value and incentivize growth. The aim of this paper is to present a novel conceptual framework to leverage AI and enhance information flow to serve the patient as per components one and two.

Congenital anomalies (CAs) are a leading cause of morbidity and mortality in early life. We aimed to assess the incidence, risk factors, and outcomes of major CAs in the State of Qatar. A population-based retrospective data analysis of registry data retrieved from the Perinatal Neonatal Outcomes Research Study in the Arabian Gulf (PEARL-Peristat Study) between April 2017 and March 2018. The sample included 25,204 newborn records, which were audited between April 2017 and March 2018, of which 25,073 live births were identified and included in the study. Maternal risk factors and neonatal outcomes were assessed for association with specific CAs, including chromosomal/genetic, central nervous system (CNS), cardiovascular system (CVS), facial, renal, multiple congenital anomalies (MCAs) using univariate and multivariate analyses. The incidence of any CA among live births was 1.3% (n = 332). The most common CAs were CVS (n = 117; 35%), MCAs (n = 69, 21%), chromosomal/genetic (51; 15%), renal (n = 39; 12%), CNS (n = 20; 6%), facial (14, 4%), and other (GIT, Resp, Urogenital, Skeletal) (n = 22, 7%) anomalies. Multivariable regression analysis showed that multiple pregnancies, parity ≥ 1, maternal BMI, and demographic factors (mother’s age and ethnicity, and infant’s gender) were associated with various specific CAs. In-hospital mortality rate due to CAs was estimated to be 15.4%. CAs were significantly associated with high rates of caesarean deliveries (aOR 1.51; 95% CI 1.04–2.19), Apgar < 7 at 1 min (aOR 5.44; 95% CI 3.10–9.55), Apgar < 7 at 5 min (aOR 17.26; 95% CI 6.31–47.18), in-hospital mortality (aOR 76.16; 37.96–152.8), admission to neonatal intensive care unit (NICU) or perinatal death of neonate in labor room (LR)/operation theatre (OT) (aOR 34.03; 95% CI 20.51–56.46), prematurity (aOR 4.17; 95% CI 2.75–6.32), and low birth weight (aOR 5.88; 95% CI 3.92–8.82) before and after adjustment for the significant risk factors. This is the first study to assess the incidence, maternal risk factors, and neonatal outcomes associated with CAs in the state of Qatar. Therefore, a specialized congenital anomaly data registry is needed to identify risk factors and outcomes. In addition, counselling of mothers and their families may help to identify specific needs for pregnant women and their babies.