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Pajusalu S, Vals MA, Mihkla L, Šamarina U, Kahre T, Õunap K. The Estimated Prevalence of N-Linked Congenital Disorders of Glycosylation Across Various Populations Based on Allele Frequencies in General Population Databases. Front Genet 2021; 12:719437. [PMID: 34447415 PMCID: PMC8383291 DOI: 10.3389/fgene.2021.719437] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Accepted: 07/21/2021] [Indexed: 01/16/2023] Open
Abstract
Congenital disorders of glycosylation (CDG) are a widely acknowledged group of metabolic diseases. PMM2-CDG is the most frequently diagnosed CDG with a prevalence as high as one in 20,000. In contrast, the prevalence of other CDG types remains unknown. This study aimed to analyze the estimated prevalence of different N-linked protein glycosylation disorders. We extracted allele frequencies for diverse populations from The Genome Aggregation Database (gnomAD), encompassing variant frequency information from 141,456 individuals. To identify pathogenic variants, we used the ClinVar database as a primary source. High confidence loss-of-function variants as defined by the LOFTEE algorithm were also classified as pathogenic. After summing up population frequencies for pathogenic alleles, estimated disease birth prevalence values with confidence intervals were calculated using the Bayesian method. We first validated our approach using two more common recessive disorders (cystic fibrosis and phenylketonuria) by showing that the estimated prevalences calculated from population allele frequencies were in accordance with previously published epidemiological studies. Among assessed 27 autosomal recessive N-glycosylation disorders, the only disease with estimated birth prevalence higher than one in 100,000 was PMM2-CDG (in both, all gnomAD individuals and those with European ancestry). The combined prevalence of 27 different N-glycosylation disorders was around one in 22,000 Europeans but varied considerably across populations. We will show estimated prevalence data from diverse populations and explain the possible pitfalls of this analysis. Still, we are confident that these data will guide CDG research and clinical care to identify CDG across populations.
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Affiliation(s)
- Sander Pajusalu
- Department of Clinical Genetics, Institute of Clinical Medicine, University of Tartu, Tartu, Estonia.,Department of Clinical Genetics, United Laboratories, Tartu University Hospital, Tartu, Estonia
| | - Mari-Anne Vals
- Department of Clinical Genetics, Institute of Clinical Medicine, University of Tartu, Tartu, Estonia.,Children's Clinic, Tartu University Hospital, Tartu, Estonia
| | - Laura Mihkla
- Department of Clinical Genetics, Institute of Clinical Medicine, University of Tartu, Tartu, Estonia.,Department of Clinical Genetics, United Laboratories, Tartu University Hospital, Tartu, Estonia
| | - Ustina Šamarina
- Department of Clinical Genetics, United Laboratories, Tartu University Hospital, Tartu, Estonia
| | - Tiina Kahre
- Department of Clinical Genetics, Institute of Clinical Medicine, University of Tartu, Tartu, Estonia.,Department of Clinical Genetics, United Laboratories, Tartu University Hospital, Tartu, Estonia
| | - Katrin Õunap
- Department of Clinical Genetics, Institute of Clinical Medicine, University of Tartu, Tartu, Estonia.,Department of Clinical Genetics, United Laboratories, Tartu University Hospital, Tartu, Estonia
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Hillert A, Anikster Y, Belanger-Quintana A, Burlina A, Burton BK, Carducci C, Chiesa AE, Christodoulou J, Đorđević M, Desviat LR, Eliyahu A, Evers RAF, Fajkusova L, Feillet F, Bonfim-Freitas PE, Giżewska M, Gundorova P, Karall D, Kneller K, Kutsev SI, Leuzzi V, Levy HL, Lichter-Konecki U, Muntau AC, Namour F, Oltarzewski M, Paras A, Perez B, Polak E, Polyakov AV, Porta F, Rohrbach M, Scholl-Bürgi S, Spécola N, Stojiljković M, Shen N, Santana-da Silva LC, Skouma A, van Spronsen F, Stoppioni V, Thöny B, Trefz FK, Vockley J, Yu Y, Zschocke J, Hoffmann GF, Garbade SF, Blau N. The Genetic Landscape and Epidemiology of Phenylketonuria. Am J Hum Genet 2020; 107:234-250. [PMID: 32668217 PMCID: PMC7413859 DOI: 10.1016/j.ajhg.2020.06.006] [Citation(s) in RCA: 121] [Impact Index Per Article: 30.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2020] [Accepted: 06/05/2020] [Indexed: 11/22/2022] Open
Abstract
Phenylketonuria (PKU), caused by variants in the phenylalanine hydroxylase (PAH) gene, is the most common autosomal-recessive Mendelian phenotype of amino acid metabolism. We estimated that globally 0.45 million individuals have PKU, with global prevalence 1:23,930 live births (range 1:4,500 [Italy]-1:125,000 [Japan]). Comparing genotypes and metabolic phenotypes from 16,092 affected subjects revealed differences in disease severity in 51 countries from 17 world regions, with the global phenotype distribution of 62% classic PKU, 22% mild PKU, and 16% mild hyperphenylalaninemia. A gradient in genotype and phenotype distribution exists across Europe, from classic PKU in the east to mild PKU in the southwest and mild hyperphenylalaninemia in the south. The c.1241A>G (p.Tyr414Cys)-associated genotype can be traced from Northern to Western Europe, from Sweden via Norway, to Denmark, to the Netherlands. The frequency of classic PKU increases from Europe (56%) via Middle East (71%) to Australia (80%). Of 758 PAH variants, c.1222C>T (p.Arg408Trp) (22.2%), c.1066-11G>A (IVS10-11G>A) (6.4%), and c.782G>A (p.Arg261Gln) (5.5%) were most common and responsible for two prevalent genotypes: p.[Arg408Trp];[Arg408Trp] (11.4%) and c.[1066-11G>A];[1066-11G>A] (2.6%). Most genotypes (73%) were compound heterozygous, 27% were homozygous, and 55% of 3,659 different genotypes occurred in only a single individual. PAH variants were scored using an allelic phenotype value and correlated with pre-treatment blood phenylalanine concentrations (n = 6,115) and tetrahydrobiopterin loading test results (n = 4,381), enabling prediction of both a genotype-based phenotype (88%) and tetrahydrobiopterin responsiveness (83%). This study shows that large genotype databases enable accurate phenotype prediction, allowing appropriate targeting of therapies to optimize clinical outcome.
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Affiliation(s)
- Alicia Hillert
- Division of Child Neurology and Metabolic Medicine, Centre for Child and Adolescent Medicine, Clinic I, University Hospital Heidelberg, 69120 Heidelberg, Germany
| | - Yair Anikster
- Metabolic Disease Unit, Edmond and Lily Safra Children's Hospital, Sheba Medical Center, Tel-Aviv University, 52621 Tel-Aviv, Israel
| | - Amaya Belanger-Quintana
- Unidad de Enfermedades Metabolicas, Servicio de Pediatria, Hospital Ramon y Cajal, 28034 Madrid, Spain
| | - Alberto Burlina
- Division of Inherited Metabolic Diseases, Department of Woman's and Child's Health, University Hospital, 35129 Padua, Italy
| | - Barbara K Burton
- Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, IL 60611, USA
| | - Carla Carducci
- Department of Experimental Medicine, Sapienza University of Rome, 00185 Rome, Italy
| | - Ana E Chiesa
- Fundación de Endocrinología Infantil (FEI), C1425 Buenos Aires, Argentina
| | - John Christodoulou
- Murdoch Children's Research Institute and Department of Pediatrics, University of Melbourne, Melbourne, VIC 3052, Australia
| | - Maja Đorđević
- Institute of Mother and Child Healthcare "Dr. Vukan Čupić," 11000 Belgrade, Serbia
| | - Lourdes R Desviat
- Centro de Diagnóstico de Enfermedades Moleculares, Centro de Biología Molecular CSIC-UAM, Universidad Autónoma de Madrid. CIBERER, IdiPAz, 28049 Madrid, Spain
| | - Aviva Eliyahu
- Metabolic Disease Unit, Edmond and Lily Safra Children's Hospital, Sheba Medical Center, Tel-Aviv University, 52621 Tel-Aviv, Israel
| | - Roeland A F Evers
- University of Groningen, University Medical Center Groningen, Beatrix Children's Hospital, Section of Metabolic Diseases, 9712 CP Groningen, the Netherlands
| | - Lena Fajkusova
- Centre of Molecular Biology and Gene Therapy, University Hospital Brno, 62500 Brno, Czech Republic
| | - François Feillet
- Reference Center for Inherited Metabolic Diseases, University Hospital of Nancy, 54511 Vandoeuvre-lès-Nancy, France
| | - Pedro E Bonfim-Freitas
- Laboratory of Inborn Errors of Metabolism, Institute of Biological Sciences, Federal University of Pará, Belém 66075-110, Brazil
| | - Maria Giżewska
- Department of Pediatrics, Endocrinology, Diabetology, Metabolic Diseases and Cardiology, Pomeranian Medical University, 71-252 Szczecin, Poland
| | | | - Daniela Karall
- Clinic of Pediatrics, Division of Inherited Metabolic Disorders, Medical University of Innsbruck, 6020 Innsbruck, Austria
| | - Katya Kneller
- Metabolic Disease Unit, Edmond and Lily Safra Children's Hospital, Sheba Medical Center, Tel-Aviv University, 52621 Tel-Aviv, Israel
| | | | - Vincenzo Leuzzi
- Department of Human Neuroscience, Sapienza University of Rome, 00185 Rome, Italy
| | - Harvey L Levy
- Division of Genetics and Genomics, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | | | - Ania C Muntau
- University Children's Hospital, University Medical Center Hamburg Eppendorf, 20246 Hamburg, Germany
| | - Fares Namour
- Reference Center for Inherited Metabolic Diseases, University Hospital of Nancy, 54511 Vandoeuvre-lès-Nancy, France
| | - Mariusz Oltarzewski
- Department of Screening and Metabolic Diagnostics, Institute of Mother and Child, 01-211 Warsaw, Poland
| | - Andrea Paras
- Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, IL 60611, USA
| | - Belen Perez
- Centro de Diagnóstico de Enfermedades Moleculares, Centro de Biología Molecular CSIC-UAM, Universidad Autónoma de Madrid. CIBERER, IdiPAz, 28049 Madrid, Spain
| | - Emil Polak
- Comenius University, Faculty of Natural Sciences, Department of Molecular Biology, 84215 Bratislava 4, Slovak Republic
| | | | - Francesco Porta
- Department of Pediatrics, AOU Citta' della Salute e della Scienza di Torino, 10126 Torino, Italy
| | - Marianne Rohrbach
- Division of Metabolism, University Children's Hospital, 8032 Zürich, Switzerland
| | - Sabine Scholl-Bürgi
- Clinic of Pediatrics, Division of Inherited Metabolic Disorders, Medical University of Innsbruck, 6020 Innsbruck, Austria
| | - Norma Spécola
- Unidad de Metabolismo. Hospital de Niños "Sor Ludovica" de La Plata, 1904 Buenos Aires, Argentina
| | - Maja Stojiljković
- Institute of Molecular Genetics and Genetic Engineering, University of Belgrade, 11000 Belgrade, Serbia
| | - Nan Shen
- Department of Infectious Diseases, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, 2000025 Shanghai, China
| | - Luiz C Santana-da Silva
- Laboratory of Inborn Errors of Metabolism, Institute of Biological Sciences, Federal University of Pará, Belém 66075-110, Brazil
| | | | - Francjan van Spronsen
- University of Groningen, University Medical Center Groningen, Beatrix Children's Hospital, Section of Metabolic Diseases, 9712 CP Groningen, the Netherlands
| | - Vera Stoppioni
- Centro Screening Neonatale Regione Marche, Azienda Ospedaliera Ospedali Riuniti Marche Nord, 61032 Fano, Italy
| | - Beat Thöny
- Division of Metabolism, University Children's Hospital, 8032 Zürich, Switzerland
| | - Friedrich K Trefz
- Division of Child Neurology and Metabolic Medicine, Centre for Child and Adolescent Medicine, Clinic I, University Hospital Heidelberg, 69120 Heidelberg, Germany
| | - Jerry Vockley
- UPMC, Children's Hospital of Pittsburgh, Pittsburgh, PA 15224, USA
| | - Youngguo Yu
- Department of Pediatric Endocrinology/Genetics, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Institute for Pediatric Research, 2000025 Shanghai, China
| | - Johannes Zschocke
- Institute of Human Genetics, Medical University Innsbruck, 6020 Innsbruck, Austria
| | - Georg F Hoffmann
- Division of Child Neurology and Metabolic Medicine, Centre for Child and Adolescent Medicine, Clinic I, University Hospital Heidelberg, 69120 Heidelberg, Germany
| | - Sven F Garbade
- Division of Child Neurology and Metabolic Medicine, Centre for Child and Adolescent Medicine, Clinic I, University Hospital Heidelberg, 69120 Heidelberg, Germany.
| | - Nenad Blau
- Division of Child Neurology and Metabolic Medicine, Centre for Child and Adolescent Medicine, Clinic I, University Hospital Heidelberg, 69120 Heidelberg, Germany; Division of Metabolism, University Children's Hospital, 8032 Zürich, Switzerland.
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4
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Lilleväli H, Reinson K, Muru K, Saarsalu S, Künnapas K, Kahre T, Murumets Ü, Õunap K. The evaluation of phenylalanine levels in Estonian phenylketonuria patients during eight years by electronic laboratory records. Mol Genet Metab Rep 2019; 19:100467. [PMID: 30963030 PMCID: PMC6434493 DOI: 10.1016/j.ymgmr.2019.100467] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2019] [Revised: 03/16/2019] [Accepted: 03/16/2019] [Indexed: 01/01/2023] Open
Abstract
Blood phenylalanine (Phe) values from the dried blood spots of all Estonian phenylketonuria (PKU) patients have been deposited into a unified electronic laboratory database for eight years, providing an opportunity to assess the adherence of the patients to dietary recommendations over time and to observe patient practices both individually and collectively. Our results demonstrate generally good adherence to clinical and dietary recommendations during the first six years of life, as the percentage of patients with median Phe values fitting under the national recommendation levels were 95%, 84% and 70% in age groups 0-1, 1-2 and 2-6 years, respectively. Conversely, significant deviations occur in the group of 6 to 12 year-olds, mildly decreasing in adolescence and increasing in adulthood (43%, 53% and 57%, respectively). Wide individual differences occurred in all groups, especially in patients with a classical PKU phenotype caused by PAH variants that fully abolish phenylalanine hydroxylase activity. Surprisingly, some of the best dietary adherence was seen in the late-diagnosed PKU patients with poor cognitive functioning. As a rule, the median of Phe values crosses the recommended thresholds in approximately one third to one half of the patients of each age group after the first two years of life.
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Affiliation(s)
- Hardo Lilleväli
- Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia.,Department of Clinical Genetics, United Laboratories, Tartu University Hospital, Tartu, Estonia
| | - Karit Reinson
- Department of Clinical Genetics, United Laboratories, Tartu University Hospital, Tartu, Estonia.,Department of Clinical Genetics, Institute of Clinical Medicine, University of Tartu, Tartu, Estonia
| | - Kai Muru
- Department of Clinical Genetics, United Laboratories, Tartu University Hospital, Tartu, Estonia.,Department of Clinical Genetics, Institute of Clinical Medicine, University of Tartu, Tartu, Estonia
| | - Siret Saarsalu
- Department of Clinical Genetics, United Laboratories, Tartu University Hospital, Tartu, Estonia
| | - Kadi Künnapas
- Department of Clinical Genetics, United Laboratories, Tartu University Hospital, Tartu, Estonia
| | - Tiina Kahre
- Department of Clinical Genetics, United Laboratories, Tartu University Hospital, Tartu, Estonia.,Department of Clinical Genetics, Institute of Clinical Medicine, University of Tartu, Tartu, Estonia
| | - Ülle Murumets
- Department of Clinical Genetics, United Laboratories, Tartu University Hospital, Tartu, Estonia
| | - Katrin Õunap
- Department of Clinical Genetics, United Laboratories, Tartu University Hospital, Tartu, Estonia.,Department of Clinical Genetics, Institute of Clinical Medicine, University of Tartu, Tartu, Estonia
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