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  1. AU="Umlai, Umm-Kulthum Ismail"
  2. AU="Reddi, Jyoti M"
  3. AU=Zeissig Sebastian
  4. AU="Valentini, Mariaconsuelo"

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  1. Artikel: Case Report: Phenotype-Gene Correlation in a Case of Novel Tandem 4q Microduplication With Short Stature, Speech Delay and Microcephaly.

    Umlai, Umm-Kulthum Ismail / Haris, Basma / Hussain, Khalid / Jithesh, Puthen Veettil

    Frontiers in endocrinology

    2022  Band 12, Seite(n) 783235

    Abstract: We describe a sporadic case of a pure, tandem, interstitial chromosome 4q duplication, arr[hg19] 4q28.1q32.3 (127,008,069-165,250,477) x3 in a boy born at 36 weeks of gestation. He presented with microcephaly (head circumference < ... ...

    Abstract We describe a sporadic case of a pure, tandem, interstitial chromosome 4q duplication, arr[hg19] 4q28.1q32.3 (127,008,069-165,250,477) x3 in a boy born at 36 weeks of gestation. He presented with microcephaly (head circumference <1
    Mesh-Begriff(e) Chromosome Duplication/genetics ; Humans ; Language Development Disorders/genetics ; Male ; Microcephaly/genetics ; Phenotype ; Protein Serine-Threonine Kinases ; Retrospective Studies
    Chemische Substanzen PLK4 protein, human (EC 2.7.1.-) ; Protein Serine-Threonine Kinases (EC 2.7.11.1)
    Sprache Englisch
    Erscheinungsdatum 2022-02-03
    Erscheinungsland Switzerland
    Dokumenttyp Case Reports ; Research Support, Non-U.S. Gov't
    ZDB-ID 2592084-4
    ISSN 1664-2392
    ISSN 1664-2392
    DOI 10.3389/fendo.2021.783235
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  2. Artikel ; Online: Genome sequencing data analysis for rare disease gene discovery.

    Umlai, Umm-Kulthum Ismail / Bangarusamy, Dhinoth Kumar / Estivill, Xavier / Jithesh, Puthen Veettil

    Briefings in bioinformatics

    2021  Band 23, Heft 1

    Abstract: Rare diseases occur in a smaller proportion of the general population, which is variedly defined as less than 200 000 individuals (US) or in less than 1 in 2000 individuals (Europe). Although rare, they collectively make up to approximately 7000 ... ...

    Abstract Rare diseases occur in a smaller proportion of the general population, which is variedly defined as less than 200 000 individuals (US) or in less than 1 in 2000 individuals (Europe). Although rare, they collectively make up to approximately 7000 different disorders, with majority having a genetic origin, and affect roughly 300 million people globally. Most of the patients and their families undergo a long and frustrating diagnostic odyssey. However, advances in the field of genomics have started to facilitate the process of diagnosis, though it is hindered by the difficulty in genome data analysis and interpretation. A major impediment in diagnosis is in the understanding of the diverse approaches, tools and datasets available for variant prioritization, the most important step in the analysis of millions of variants to select a few potential variants. Here we present a review of the latest methodological developments and spectrum of tools available for rare disease genetic variant discovery and recommend appropriate data interpretation methods for variant prioritization. We have categorized the resources based on various steps of the variant interpretation workflow, starting from data processing, variant calling, annotation, filtration and finally prioritization, with a special emphasis on the last two steps. The methods discussed here pertain to elucidating the genetic basis of disease in individual patient cases via trio- or family-based analysis of the genome data. We advocate the use of a combination of tools and datasets and to follow multiple iterative approaches to elucidate the potential causative variant.
    Mesh-Begriff(e) Data Analysis ; Genetic Association Studies ; Genome ; High-Throughput Nucleotide Sequencing ; Humans ; Rare Diseases/diagnosis ; Rare Diseases/genetics ; Software
    Sprache Englisch
    Erscheinungsdatum 2021-09-09
    Erscheinungsland England
    Dokumenttyp Journal Article ; Research Support, Non-U.S. Gov't ; Review
    ZDB-ID 2068142-2
    ISSN 1477-4054 ; 1467-5463
    ISSN (online) 1477-4054
    ISSN 1467-5463
    DOI 10.1093/bib/bbab363
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  3. Artikel ; Online: Genome-wide association study and trans-ethnic meta-analysis identify novel susceptibility loci for type 2 diabetes mellitus.

    Elashi, Asma A / Toor, Salman M / Umlai, Umm-Kulthum Ismail / Al-Sarraj, Yasser A / Taheri, Shahrad / Suhre, Karsten / Abou-Samra, Abdul Badi / Albagha, Omar M E

    BMC medical genomics

    2024  Band 17, Heft 1, Seite(n) 115

    Abstract: Background: The genetic basis of type 2 diabetes (T2D) is under-investigated in the Middle East, despite the rapidly growing disease prevalence. We aimed to define the genetic determinants of T2D in Qatar.: Methods: Using whole genome sequencing of ... ...

    Abstract Background: The genetic basis of type 2 diabetes (T2D) is under-investigated in the Middle East, despite the rapidly growing disease prevalence. We aimed to define the genetic determinants of T2D in Qatar.
    Methods: Using whole genome sequencing of 11,436 participants (2765 T2D cases and 8671 controls) from the population-based Qatar Biobank (QBB), we conducted a genome-wide association study (GWAS) of T2D with and without body mass index (BMI) adjustment.
    Results: We replicated 93 known T2D-associated loci in a BMI-unadjusted model, while 96 known loci were replicated in a BMI-adjusted model. The effect sizes and allele frequencies of replicated SNPs in the Qatari population generally concurred with those from European populations. We identified a locus specific to our cohort located between the APOBEC3H and CBX7 genes in the BMI-unadjusted model. Also, we performed a transethnic meta-analysis of our cohort with a previous GWAS on T2D in multi-ancestry individuals (180,834 T2D cases and 1,159,055 controls). One locus in DYNC2H1 gene reached genome-wide significance in the meta-analysis. Assessing polygenic risk scores derived from European- and multi-ancestries in the Qatari population showed higher predictive performance of the multi-ancestry panel compared to the European panel.
    Conclusion: Our study provides new insights into the genetic architecture of T2D in a Middle Eastern population and identifies genes that may be explored further for their involvement in T2D pathogenesis.
    Mesh-Begriff(e) Humans ; Diabetes Mellitus, Type 2/genetics ; Genome-Wide Association Study ; Genetic Predisposition to Disease ; Polymorphism, Single Nucleotide ; Qatar/epidemiology ; Male ; Female ; Middle Aged ; Genetic Loci ; Case-Control Studies ; Body Mass Index ; Ethnicity/genetics
    Sprache Englisch
    Erscheinungsdatum 2024-04-29
    Erscheinungsland England
    Dokumenttyp Journal Article ; Research Support, Non-U.S. Gov't ; Meta-Analysis
    ZDB-ID 2411865-5
    ISSN 1755-8794 ; 1755-8794
    ISSN (online) 1755-8794
    ISSN 1755-8794
    DOI 10.1186/s12920-024-01855-1
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  4. Artikel ; Online: Correction: Genome-wide association study and trans-ethnic meta-analysis identify novel susceptibility loci for type 2 diabetes mellitus.

    Elashi, Asma A / Toor, Salman M / Umlai, Umm-Kulthum Ismail / Al-Sarraj, Yasser A / Taheri, Shahrad / Suhre, Karsten / Abou-Samra, Abdul Badi / Albagha, Omar M E

    BMC medical genomics

    2024  Band 17, Heft 1, Seite(n) 131

    Sprache Englisch
    Erscheinungsdatum 2024-05-16
    Erscheinungsland England
    Dokumenttyp Published Erratum
    ZDB-ID 2411865-5
    ISSN 1755-8794 ; 1755-8794
    ISSN (online) 1755-8794
    ISSN 1755-8794
    DOI 10.1186/s12920-024-01903-w
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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