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Elfatih A, Saad C, Mifsud B, Mbarek H. Analysis of 14,392 whole genomes reveals 3.5% of Qataris carry medically actionable variants. Eur J Hum Genet 2024:10.1038/s41431-024-01656-1. [PMID: 39020067 DOI: 10.1038/s41431-024-01656-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 06/05/2024] [Accepted: 06/19/2024] [Indexed: 07/19/2024] Open
Abstract
Arabic populations are underrepresented in large genome projects; therefore, the frequency of clinically actionable variants among Arabs is largely unknown. Here, we investigated genetic variation in 14,392 whole genomes from the Qatar Genome Program (QGP) across the list of 78 actionable genes (v3.1) determined by the American College of Medical Genetics and Genomics (ACMG). Variants were categorized into one of the following groups: (1) Pathogenic (P), (2) Likely pathogenic (LP), and (3) Rare variants of uncertain significance with evidence of pathogenicity. For the classification, we used variant databases, effect predictors, and the disease-relevant phenotypes available for the cohort. Data on cardiovascular disease, cancer, and hypercholesterolemia allowed us to assess the disease-relevant phenotype association of rare missense variants. We identified 248 distinct variants in 50 ACMG genes that fulfilled our criteria to be included in one of the three groups affecting 1036 genotype-positive participants of the QGP cohort. The most frequent variants were in TTN, followed by RYR1 and ATP7B. The prevalence of reportable secondary findings was 3.5%. A further 46 heterozygous variants in six genes with an autosomal recessive mode of inheritance were detected in 200 individuals, accounting for an additional 1.4%. Altogether, they affect 5% of the population. Due to the high consanguinity rate in the QGP cohort (28% in spouses and 60% in parents), P and LP variants both in genes with dominant and recessive inheritance are important for developing better treatment options and preventive strategies in Qatar and the Arabic population of the Middle East.
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Affiliation(s)
- Amal Elfatih
- Hamad Bin Khalifa University, College of Health and Life Science, Genomics and Precision Medicine, Doha, Qatar
| | - Chadi Saad
- Qatar Genome Program, Qatar Foundation, Qatar Science and Technology Park, Innovation Center, Doha, Qatar
| | - Borbala Mifsud
- Hamad Bin Khalifa University, College of Health and Life Science, Genomics and Precision Medicine, Doha, Qatar.
- William Harvey Research Institute, Queen Mary University London, London, UK.
| | - Hamdi Mbarek
- Qatar Genome Program, Qatar Foundation, Qatar Science and Technology Park, Innovation Center, Doha, Qatar.
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2
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Caeser R, Chiang J, Tan ES, Tai ES, Ngeow J. Cascade testing for hereditary cancer in Singapore: how population genomics help guide clinical policy. Fam Cancer 2024; 23:133-140. [PMID: 38662262 DOI: 10.1007/s10689-024-00376-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2024] [Accepted: 03/14/2024] [Indexed: 04/26/2024]
Abstract
Hereditary Cancer makes up around 5-10% of all cancers. It is important to diagnose hereditary cancer in a timely fashion, as not only do patients require long-term care from a young age, but their relatives also require management. The main approach to capture at-risk relatives is cascade testing. It involves genetic testing of relatives of the first detected carrier of a pathogenic variant in a family i.e. the proband. The current standard of care for cascade testing is a patient-mediated approach. Probands are then advised to inform and encourage family members to undergo genetic testing. In Singapore, cascade testing is inefficient, around 10-15%, lower than the 30% global average. Here, we describe the cascade testing process and its effort to increase testing in Singapore. Precision Health Research, Singapore (PRECISE), was set up to coordinate Singapore's National Precision Medicine strategy and has awarded five clinical implementation pilots, with one of them seeking to identify strategies for how cascade testing for hereditary cancer can be increased in a safe and cost-efficient manner. Achieving this will be done through addressing barriers such as cost, manpower shortages, exploring a digital channel for contacting at-risk relatives, and getting a deeper insight into why genetic testing gets declined. If successful, it will likely result in care pathways that are a cost-effective public health intervention for identifying individuals at risk. Surveillance and management of those unaffected at-risk individuals, if caught early, will result in improved patient outcomes, and further reduce the healthcare burden for the economy.
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Affiliation(s)
- Rebecca Caeser
- Cancer Genetics Service, Division of Medical Oncology, National Cancer Centre Singapore, Singapore, 169610, Singapore
- Oncology Academic Clinical Program, Duke-NUS Medical School, Singapore, Singapore
| | - Jianbang Chiang
- Cancer Genetics Service, Division of Medical Oncology, National Cancer Centre Singapore, Singapore, 169610, Singapore
- Oncology Academic Clinical Program, Duke-NUS Medical School, Singapore, Singapore
| | - Ee Shien Tan
- Duke-National University of Singapore (NUS) Medical School, National University of Singapore, Singapore, Singapore
- Genetics Service, Department of Pediatrics, Kadang Kerbau (KK) Women's and Children's Hospital, Singapore, Singapore
| | - E Shyong Tai
- Duke-National University of Singapore (NUS) Medical School, National University of Singapore, Singapore, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Precision Health Research, Singapore, Singapore
| | - Joanne Ngeow
- Cancer Genetics Service, Division of Medical Oncology, National Cancer Centre Singapore, Singapore, 169610, Singapore.
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 308232, Singapore.
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3
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Hillary RF, Ng HK, McCartney DL, Elliott HR, Walker RM, Campbell A, Huang F, Direk K, Welsh P, Sattar N, Corley J, Hayward C, McIntosh AM, Sudlow C, Evans KL, Cox SR, Chambers JC, Loh M, Relton CL, Marioni RE, Yousefi PD, Suderman M. Blood-based epigenome-wide analyses of chronic low-grade inflammation across diverse population cohorts. CELL GENOMICS 2024; 4:100544. [PMID: 38692281 PMCID: PMC11099341 DOI: 10.1016/j.xgen.2024.100544] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 02/09/2024] [Accepted: 04/03/2024] [Indexed: 05/03/2024]
Abstract
Chronic inflammation is a hallmark of age-related disease states. The effectiveness of inflammatory proteins including C-reactive protein (CRP) in assessing long-term inflammation is hindered by their phasic nature. DNA methylation (DNAm) signatures of CRP may act as more reliable markers of chronic inflammation. We show that inter-individual differences in DNAm capture 50% of the variance in circulating CRP (N = 17,936, Generation Scotland). We develop a series of DNAm predictors of CRP using state-of-the-art algorithms. An elastic-net-regression-based predictor outperformed competing methods and explained 18% of phenotypic variance in the Lothian Birth Cohort of 1936 (LBC1936) cohort, doubling that of existing DNAm predictors. DNAm predictors performed comparably in four additional test cohorts (Avon Longitudinal Study of Parents and Children, Health for Life in Singapore, Southall and Brent Revisited, and LBC1921), including for individuals of diverse genetic ancestry and different age groups. The best-performing predictor surpassed assay-measured CRP and a genetic score in its associations with 26 health outcomes. Our findings forge new avenues for assessing chronic low-grade inflammation in diverse populations.
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Affiliation(s)
- Robert F Hillary
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Hong Kiat Ng
- Lee Kong Chian School of Medicine, Nanyang Technological University, Clinical Sciences Building, Singapore 308232, Singapore
| | - Daniel L McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Hannah R Elliott
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol BS8 2BN, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 1UD, UK
| | - Rosie M Walker
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH4 2XU, UK; School of Psychology, University of Exeter, Exeter EX4 4QG, UK
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Felicia Huang
- MRC Unit for Lifelong Health and Ageing, University College London, London WC1E 7HB, UK
| | - Kenan Direk
- Imperial Clinical Trials Unit, School of Public Health, Imperial College London, London SW7 2AZ, UK
| | - Paul Welsh
- School of Cardiovascular and Metabolic Health, BHF Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow G12 8TA, UK
| | - Naveed Sattar
- School of Cardiovascular and Metabolic Health, BHF Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow G12 8TA, UK
| | - Janie Corley
- Lothian Birth Cohort Studies, Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, UK
| | - Caroline Hayward
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH4 2XU, UK; Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Andrew M McIntosh
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH4 2XU, UK; Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh EH10 5HF, UK
| | - Cathie Sudlow
- Centre for Clinical Brain Sciences, Edinburgh Imaging and UK Dementia Research Institute, University of Edinburgh, Edinburgh EH16 4SB, UK; British Heart Foundation Data Science Centre, Health Data Research UK, London NW1 2BE, UK; Health Data Research UK, London NW1 2BE, UK
| | - Kathryn L Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Simon R Cox
- Lothian Birth Cohort Studies, Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, UK
| | - John C Chambers
- Lee Kong Chian School of Medicine, Nanyang Technological University, Clinical Sciences Building, Singapore 308232, Singapore; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, St Mary's Campus, London W2 1PG, UK
| | - Marie Loh
- Lee Kong Chian School of Medicine, Nanyang Technological University, Clinical Sciences Building, Singapore 308232, Singapore; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, St Mary's Campus, London W2 1PG, UK; National Skin Centre, Singapore 308205, Singapore; Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore 138672, Singapore
| | - Caroline L Relton
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol BS8 2BN, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 1UD, UK
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH4 2XU, UK.
| | - Paul D Yousefi
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol BS8 2BN, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 1UD, UK.
| | - Matthew Suderman
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol BS8 2BN, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 1UD, UK.
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Yeo NKW, Lim CK, Yaung KN, Khoo NKH, Arkachaisri T, Albani S, Yeo JG. Genetic interrogation for sequence and copy number variants in systemic lupus erythematosus. Front Genet 2024; 15:1341272. [PMID: 38501057 PMCID: PMC10944961 DOI: 10.3389/fgene.2024.1341272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Accepted: 02/20/2024] [Indexed: 03/20/2024] Open
Abstract
Early-onset systemic lupus erythematosus presents with a more severe disease and is associated with a greater genetic burden, especially in patients from Black, Asian or Hispanic ancestries. Next-generation sequencing techniques, notably whole exome sequencing, have been extensively used in genomic interrogation studies to identify causal disease variants that are increasingly implicated in the development of autoimmunity. This Review discusses the known casual variants of polygenic and monogenic systemic lupus erythematosus and its implications under certain genetic disparities while suggesting an age-based sequencing strategy to aid in clinical diagnostics and patient management for improved patient care.
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Affiliation(s)
- Nicholas Kim-Wah Yeo
- Translational Immunology Institute, SingHealth Duke-NUS Academic Medical Centre, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - Che Kang Lim
- Duke-NUS Medical School, Singapore, Singapore
- Department of Clinical Translation Research, Singapore General Hospital, Singapore, Singapore
| | - Katherine Nay Yaung
- Translational Immunology Institute, SingHealth Duke-NUS Academic Medical Centre, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - Nicholas Kim Huat Khoo
- Translational Immunology Institute, SingHealth Duke-NUS Academic Medical Centre, Singapore, Singapore
| | - Thaschawee Arkachaisri
- Translational Immunology Institute, SingHealth Duke-NUS Academic Medical Centre, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
- Rheumatology and Immunology Service, KK Women's and Children's Hospital, Singapore, Singapore
| | - Salvatore Albani
- Translational Immunology Institute, SingHealth Duke-NUS Academic Medical Centre, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
- Rheumatology and Immunology Service, KK Women's and Children's Hospital, Singapore, Singapore
| | - Joo Guan Yeo
- Translational Immunology Institute, SingHealth Duke-NUS Academic Medical Centre, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
- Rheumatology and Immunology Service, KK Women's and Children's Hospital, Singapore, Singapore
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5
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Moynihan D, Monaco S, Ting TW, Narasimhalu K, Hsieh J, Kam S, Lim JY, Lim WK, Davila S, Bylstra Y, Balakrishnan ID, Heng M, Chia E, Yeo KK, Goh BK, Gupta R, Tan T, Baynam G, Jamuar SS. Cluster analysis and visualisation of electronic health records data to identify undiagnosed patients with rare genetic diseases. Sci Rep 2024; 14:5056. [PMID: 38424111 PMCID: PMC10904843 DOI: 10.1038/s41598-024-55424-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Accepted: 02/23/2024] [Indexed: 03/02/2024] Open
Abstract
Rare genetic diseases affect 5-8% of the population but are often undiagnosed or misdiagnosed. Electronic health records (EHR) contain large amounts of data, which provide opportunities for analysing and mining. Data mining, in the form of cluster analysis and visualisation, was performed on a database containing deidentified health records of 1.28 million patients across 3 major hospitals in Singapore, in a bid to improve the diagnostic process for patients who are living with an undiagnosed rare disease, specifically focusing on Fabry Disease and Familial Hypercholesterolaemia (FH). On a baseline of 4 patients, we identified 2 additional patients with potential diagnosis of Fabry disease, suggesting a potential 50% increase in diagnosis. Similarly, we identified > 12,000 individuals who fulfil the clinical and laboratory criteria for FH but had not been diagnosed previously. This proof-of-concept study showed that it is possible to perform mining on EHR data albeit with some challenges and limitations.
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Affiliation(s)
| | | | - Teck Wah Ting
- Genetics Service, Department of Paediatrics, KK Women's and Children's Hospital, 100 Bukit Timah Road, Singapore, 229899, Singapore
- SingHealth Duke-NUS Genomic Medicine Centre, Singapore, Singapore
| | - Kaavya Narasimhalu
- SingHealth Duke-NUS Genomic Medicine Centre, Singapore, Singapore
- Department of Neurology, National Neuroscience Institute (Singapore General Hospital), Singapore, Singapore
| | - Jenny Hsieh
- SingHealth Duke-NUS Genomic Medicine Centre, Singapore, Singapore
- Department of Internal Medicine, Singapore General Hospital, Singapore, Singapore
| | - Sylvia Kam
- Genetics Service, Department of Paediatrics, KK Women's and Children's Hospital, 100 Bukit Timah Road, Singapore, 229899, Singapore
- SingHealth Duke-NUS Genomic Medicine Centre, Singapore, Singapore
| | - Jiin Ying Lim
- Genetics Service, Department of Paediatrics, KK Women's and Children's Hospital, 100 Bukit Timah Road, Singapore, 229899, Singapore
- SingHealth Duke-NUS Genomic Medicine Centre, Singapore, Singapore
| | - Weng Khong Lim
- SingHealth Duke-NUS Genomic Medicine Centre, Singapore, Singapore
- SingHealth Duke-NUS Institute of Precision Medicine, Singapore, Singapore
- Cancer & Stem Cell Biology Program, Duke-NUS Medical School, Singapore, Singapore
- Laboratory of Genome Variation Analytics, Genome Institute of Singapore, Singapore, Singapore
| | - Sonia Davila
- SingHealth Duke-NUS Genomic Medicine Centre, Singapore, Singapore
- SingHealth Duke-NUS Institute of Precision Medicine, Singapore, Singapore
| | - Yasmin Bylstra
- SingHealth Duke-NUS Genomic Medicine Centre, Singapore, Singapore
- SingHealth Duke-NUS Institute of Precision Medicine, Singapore, Singapore
| | - Iswaree Devi Balakrishnan
- SingHealth Duke-NUS Genomic Medicine Centre, Singapore, Singapore
- National Heart Centre Singapore, Singapore, Singapore
| | - Mark Heng
- SingHealth Office of Insights and Analytics, Singapore, Singapore
| | - Elian Chia
- SingHealth Office of Insights and Analytics, Singapore, Singapore
| | | | - Bee Keow Goh
- Data Analytics Office, KK Women's and Children's Hospital, Singapore, Singapore
| | | | - Tele Tan
- Curtin University, Perth, Australia
| | - Gareth Baynam
- Rare Care Centre, Perth Children's Hospital, Perth, WA, Australia
- Western Australian Register of Developmental Anomalies, Perth, WA, Australia
| | - Saumya Shekhar Jamuar
- Genetics Service, Department of Paediatrics, KK Women's and Children's Hospital, 100 Bukit Timah Road, Singapore, 229899, Singapore.
- SingHealth Duke-NUS Genomic Medicine Centre, Singapore, Singapore.
- SingHealth Duke-NUS Institute of Precision Medicine, Singapore, Singapore.
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Latif M, Hashmi JA, Alayoubi AM, Ayub A, Basit S. Identification of Novel and Recurrent Variants in BTD, GBE1, AGL and ASL Genes in Families with Metabolic Disorders in Saudi Arabia. J Clin Med 2024; 13:1193. [PMID: 38592052 PMCID: PMC10932034 DOI: 10.3390/jcm13051193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2023] [Revised: 11/07/2023] [Accepted: 11/14/2023] [Indexed: 04/10/2024] Open
Abstract
Background and Objectives: Inherited metabolic disorders (IMDs) are a group of genetic disorders characterized by defects in enzymes or transport proteins involved in metabolic processes. These defects result in an abnormal accumulation of metabolites and thus interfere with the body's metabolism. A variety of IMDs exist and differential diagnosis is often challenging. Our objective was to gain insight into the genetic basis of IMDs and the correlations between specific genetic mutations and clinical presentations in patients admitted at various hospitals in the Madinah region of the Kingdom of Saudi Arabia. Material and Methods: Whole exome sequencing (WES) has emerged as a powerful tool for diagnosing IMDs and allows for the identification of disease-causing genetic mutations in individuals suspected of IMDs. This ensures accurate diagnosis and appropriate management. WES was performed in four families with multiple individuals showing clinical presentation of IMDs. Validation of the variants identified through WES was conducted using Sanger sequencing. Furthermore, various computational analyses were employed to uncover the disease gene co-expression and metabolic pathways. Results: Exome variant data analysis revealed missense variants in the BTD (c.1270G > C), ASL (c.1300G > T), GBE1 (c.985T > G) and AGL (c.113C > G) genes. Mutations in these genes are known to cause IMDs. Conclusions: Thus, our data showed that exome sequencing, in conjunction with clinical and biochemical characteristics and pathological hallmarks, could deliver an accurate and high-throughput outcome for the diagnosis and sub-typing of IMDs. Overall, our findings emphasize that the integration of WES with clinical and pathological information has the potential to improve the diagnosis and understanding of IMDs and related disorders, ultimately benefiting patients and the medical community.
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Affiliation(s)
- Muhammad Latif
- Department of Basic Medical Sciences, College of Medicine, Taibah University, Madinah 42353, Saudi Arabia; (J.A.H.); (A.M.A.)
- Center for Genetics and Inherited Diseases, Taibah University, Madinah 42353, Saudi Arabia
| | - Jamil Amjad Hashmi
- Department of Basic Medical Sciences, College of Medicine, Taibah University, Madinah 42353, Saudi Arabia; (J.A.H.); (A.M.A.)
- Center for Genetics and Inherited Diseases, Taibah University, Madinah 42353, Saudi Arabia
| | - Abdulfatah M. Alayoubi
- Department of Basic Medical Sciences, College of Medicine, Taibah University, Madinah 42353, Saudi Arabia; (J.A.H.); (A.M.A.)
| | - Arusha Ayub
- Department of Medicine, School of Health Sciences, University of Georgia, Tbilisi, P. O. Box-0171, Georgia;
| | - Sulman Basit
- Department of Basic Medical Sciences, College of Medicine, Taibah University, Madinah 42353, Saudi Arabia; (J.A.H.); (A.M.A.)
- Center for Genetics and Inherited Diseases, Taibah University, Madinah 42353, Saudi Arabia
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Choi WJ, Kim SH, Lee SR, Oh SH, Kim SW, Shin HY, Park HJ. Global carrier frequency and predicted genetic prevalence of patients with pathogenic sequence variants in autosomal recessive genetic neuromuscular diseases. Sci Rep 2024; 14:3806. [PMID: 38361118 PMCID: PMC10869705 DOI: 10.1038/s41598-024-54413-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Accepted: 02/13/2024] [Indexed: 02/17/2024] Open
Abstract
Genetic neuromuscular diseases are clinically and genetically heterogeneous genetic disorders that primarily affect the peripheral nerves, muscles, and neuromuscular junctions. This study aimed to identify pathogenic variants, calculate carrier frequency, and predict the genetic prevalence of autosomal recessive neuromuscular diseases (AR-NMDs). We selected 268 AR-NMD genes and analyzed their genetic variants sourced from the gnomAD database. After identifying the pathogenic variants using an algorithm, we calculated the carrier frequency and predicted the genetic prevalence of AR-NMDs. In total, 10,887 pathogenic variants were identified, including 3848 literature verified and 7039 manually verified variants. In the global population, the carrier frequency of AR-NMDs is 32.9%, with variations across subpopulations ranging from 22.4% in the Finnish population to 36.2% in the non-Finnish European population. The predicted genetic prevalence of AR-NMDs was estimated to be 24.3 cases per 100,000 individuals worldwide, with variations across subpopulations ranging from 26.5 to 41.4 cases per 100,000 individuals in the Latino/Admixed American and the Ashkenazi Jewish populations, respectively. The AR-NMD gene with the highest carrier frequency was GAA (1.3%) and the variant with the highest allele frequency was c.-32-13 T>G in GAA with 0.0033 in the global population. Our study revealed a higher-than-expected frequency of AR-NMD carriers, constituting approximately one-third of the global population, highlighting ethnic heterogeneity in genetic susceptibility.
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Affiliation(s)
- Won-Jun Choi
- CHA University School of Medicine, Seongnam, Republic of Korea
| | - Soo-Hyun Kim
- Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, 211 Eonju-Ro, Gangnam-Gu, Seoul, 06273, Republic of Korea
| | - Sung Rok Lee
- Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, 211 Eonju-Ro, Gangnam-Gu, Seoul, 06273, Republic of Korea
| | - Seung-Hun Oh
- Department of Neurology, CHA Bundang Medical Center, CHA University, Seongnam, Republic of Korea
| | - Seung Woo Kim
- Department of Neurology, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Ha Young Shin
- Department of Neurology, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Hyung Jun Park
- Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, 211 Eonju-Ro, Gangnam-Gu, Seoul, 06273, Republic of Korea.
- Rehabilitation Institute of Neuromuscular Disease, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea.
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8
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Dokuru DR, Horwitz TB, Freis SM, Stallings MC, Ehringer MA. South Asia: The Missing Diverse in Diversity. Behav Genet 2024; 54:51-62. [PMID: 37917228 PMCID: PMC11129896 DOI: 10.1007/s10519-023-10161-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2023] [Accepted: 09/26/2023] [Indexed: 11/04/2023]
Abstract
South Asia, making up around 25% of the world's population, encompasses a wide range of individuals with tremendous genetic and environmental diversity. This region, which spans eight countries, is home to over 4500 anthropologically defined groups that speak numerous languages and have an array of religious beliefs and cultures, making it one of the most diverse places in the world. Much of the region's rich genetic diversity and structure is the result of a complex combination of population history, migration patterns, and endogamous practices. Despite the overwhelming size and diversity, South Asians have often been underrepresented in genetic research, making up less than 2% of the participants in genetic studies. This has led to a lack of population specific understanding of genetic disease risks. We aim to raise awareness about underlying genetic diversity in this ancestry group, call attention to the lack of representation of the group, and to highlight strategies for future studies in South Asians.
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Affiliation(s)
- Deepika R Dokuru
- Institute for Behavioral Genetics, University of Colorado Boulder, 1480 30 St, Boulder, CO, 80303, USA.
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA.
| | - Tanya B Horwitz
- Institute for Behavioral Genetics, University of Colorado Boulder, 1480 30 St, Boulder, CO, 80303, USA
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA
| | - Samantha M Freis
- Institute for Behavioral Genetics, University of Colorado Boulder, 1480 30 St, Boulder, CO, 80303, USA
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA
| | - Michael C Stallings
- Institute for Behavioral Genetics, University of Colorado Boulder, 1480 30 St, Boulder, CO, 80303, USA
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA
| | - Marissa A Ehringer
- Institute for Behavioral Genetics, University of Colorado Boulder, 1480 30 St, Boulder, CO, 80303, USA
- Department of Integrative Physiology, University of Colorado Boulder, Boulder, CO, USA
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9
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Khoo T, Lilleker JB, Thong BYH, Leclair V, Lamb JA, Chinoy H. Epidemiology of the idiopathic inflammatory myopathies. Nat Rev Rheumatol 2023; 19:695-712. [PMID: 37803078 DOI: 10.1038/s41584-023-01033-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/05/2023] [Indexed: 10/08/2023]
Abstract
The idiopathic inflammatory myopathies (IIMs) are a heterogeneous group of systemic autoimmune diseases that affect the skeletal muscles and can also involve the skin, joints, lungs and heart. The epidemiology of IIM is obscured by changing classification criteria and the inherent shortcomings of case identification using healthcare record diagnostic coding. The incidence of IIM is estimated to range from 0.2 to 2 per 100,000 person-years, with prevalence from 2 to 25 per 100,000 people. Although the effects of age and gender on incidence are known, there is only sparse understanding of ethnic differences, particularly in indigenous populations. The incidence of IIM has reportedly increased in the twenty-first century, but whether this is a genuine increase is not yet known. Understanding of the genetic risk factors for different IIM subtypes has advanced considerably. Infections, medications, malignancy and geography are also commonly identified risk factors. Potentially, the COVID-19 pandemic has altered IIM incidence, although evidence of this occurrence is limited to case reports and small case series. Consideration of the current understanding of the epidemiology of IIM can highlight important areas of interest for future research into these rare diseases.
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Affiliation(s)
- Thomas Khoo
- Division of Musculoskeletal and Dermatological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
- School of Medicine, Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide, South Australia, Australia
- Department of Rheumatology, Salford Royal Hospital, Northern Care Alliance NHS Foundation Trust, Manchester Academic Health Science Centre, Salford, UK
| | - James B Lilleker
- Division of Musculoskeletal and Dermatological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
- Manchester Centre for Clinical Neuroscience, Manchester Academic Health Science Centre, Salford Royal Hospital, Northern Care Alliance NHS Foundation Trust, Salford, UK
| | - Bernard Yu-Hor Thong
- Department of Rheumatology, Allergy and Immunology, Tan Tock Seng Hospital, Singapore, Singapore
| | - Valérie Leclair
- Department of Medicine, Division of Rheumatology, McGill University, Montreal, Canada
| | - Janine A Lamb
- Epidemiology and Public Health Group, School of Health Sciences, The University of Manchester, Manchester, UK
| | - Hector Chinoy
- Division of Musculoskeletal and Dermatological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.
- Department of Rheumatology, Salford Royal Hospital, Northern Care Alliance NHS Foundation Trust, Manchester Academic Health Science Centre, Salford, UK.
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10
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Kim Y, Kim JM, Cho HW, Park HY, Park MH. Frequency of actionable secondary findings in 7472 Korean genomes derived from the National Project of Bio Big Data pilot study. Hum Genet 2023; 142:1561-1569. [PMID: 37728764 PMCID: PMC10602966 DOI: 10.1007/s00439-023-02592-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Accepted: 08/14/2023] [Indexed: 09/21/2023]
Abstract
Exome and genome sequencing (ES/GS) in genetic medicine and research leads to discovering genomic secondary findings (SFs) unrelated to the purpose of the primary test. There is a lack of agreement to return the SF results for individuals undergoing the test. The aim of this study is to investigate the frequency of actionable secondary findings using GS data obtained from the rare disease study and the Korean Genome and Epidemiology Study (KoGES) in the National Project of Bio Big Data pilot study. Pathogenic (P) or likely pathogenic (LP) variants of 78 SF genes recommended by the American College of Medical Genetics and Genomics (ACMG) were screened in the rare disease study and KoGES. The pathogenicity of SF gene variants was determined according to the ACMG interpretation. The overall SF rate was 3.75% for 280 individuals with 298 P/LP variants of 41 ACMG SF genes which were identified among 7472 study participants. The frequencies of genes associated with cardiovascular, cancer, and miscellaneous phenotypes were 2.17%, 1.22%, and 0.58%, respectively. The most frequent SF gene was TTN followed by BRCA2. The frequency of actionable SFs among participants with rare disease and general population participants in the Korean population presented here will assist in reporting results of medically actionable SFs in genomic medicine.
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Affiliation(s)
- Youngjun Kim
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju, Republic of Korea
| | - Jeong-Min Kim
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju, Republic of Korea
| | - Hye-Won Cho
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju, Republic of Korea
| | - Hyun-Young Park
- Department of Precision Medicine, National Institute of Health, Cheongju, Republic of Korea.
| | - Mi-Hyun Park
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju, Republic of Korea.
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11
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Forbes M, Hopwood M, Bousman CA. CYP2D6 and CYP2C19 Variant Coverage of Commercial Antidepressant Pharmacogenomic Testing Panels Available in Victoria, Australia. Genes (Basel) 2023; 14:1945. [PMID: 37895294 PMCID: PMC10606650 DOI: 10.3390/genes14101945] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Revised: 10/08/2023] [Accepted: 10/12/2023] [Indexed: 10/29/2023] Open
Abstract
Pharmacogenomic (PGx) testing to inform antidepressant medication selection and dosing is gaining attention from healthcare professionals, patients, and payors in Australia. However, there is often uncertainty regarding which test is most suitable for a particular patient. Here, we identified and evaluated the coverage of CYP2D6 and CYP2C19 variants in commercial antidepressant PGx testing panels in Victoria, a large and ethnically diverse state of Australia. Test characteristics and star alleles tested for both genes were obtained directly from pathology laboratories offering PGx testing and compared against the Association of Molecular Pathology's recommended minimum (Tier 1) and extended (Tier 2) allele sets. Although all tests covered the minimum recommended alleles for CYP2C19, this was not the case for CYP2D6. This study emphasizes that PGx tests might not be suitable for all individuals in Australia due to the limited range of star alleles assessed. Inadequate haplotype coverage may risk misclassification of an individual's predicted metabolizer phenotype, which has ramifications for depression medication selection and dosage. This study underscores the urgent need for greater standardization in PGx testing and emphasizes the importance of considering genetic ancestry when choosing a PGx testing panel to ensure optimal clinical applicability.
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Affiliation(s)
- Malcolm Forbes
- The Institute for Mental and Physical Health and Clinical Translation (IMPACT), School of Medicine, Barwon Health, Deakin University, Geelong, VIC 3220, Australia
- Department of Psychiatry, University of Melbourne, Parkville, VIC 3050, Australia; (M.H.); (C.A.B.)
| | - Mal Hopwood
- Department of Psychiatry, University of Melbourne, Parkville, VIC 3050, Australia; (M.H.); (C.A.B.)
| | - Chad A. Bousman
- Department of Psychiatry, University of Melbourne, Parkville, VIC 3050, Australia; (M.H.); (C.A.B.)
- Department of Medical Genetics, University of Calgary, Calgary, AB T2N 4N2, Canada
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12
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Chan CM, Tan TE, Jain K, Bylstra Y, Mathur RS, Tang RWC, Lee BJH, Jamuar SS, Kam S, Vithana EN, Lim WK, Fenner BJ. RETINITIS PIGMENTOSA ASSOCIATED WITH THE EYS C2139Y VARIANT : An Important Cause of Blindness in East Asian Populations. Retina 2023; 43:1788-1796. [PMID: 37418643 DOI: 10.1097/iae.0000000000003874] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/09/2023]
Abstract
PURPOSE The study aimed to describe the phenotypic features of retinitis pigmentosa (RP) associated with the previously described EYS C2139Y variant in Singaporeans and establish the importance of this variant as a prevalent cause of RP among East Asians. METHODS A clinical phenotyping and exome-sequencing study was conducted on consecutive patients with nonsyndromic RP. Epidemiological analysis was performed using Singaporean and global population-based genetic data. RESULTS A study of 150 consecutive unrelated individuals with nonsyndromic RP found that 87 (58%) of cases had plausible genotypes. A previously described missense variant in the EYS gene, 6416G>A (C2139Y), occurred heterozygously or homozygously in 17 of 150 families (11.3%), all with autosomal recessive RP. Symptom onset in EYS C2139Y-related RP ranged from 6 to 45 years, with visual acuity ranging from 20/20 at 21 years to no light perception by 48 years. C2139Y-related RP had typical findings, including sectoral RP in cases with EYS E2703X in trans . The median age at presentation was 45 years and visual fields declined to less than 20° (Goldmann V4e isopter) by age 65 years. Intereye correlation for visual acuity, fields, and ellipsoid band width was high (r 2 = 0.77-0.95). Carrier prevalence was 0.66% (allele frequency of 0.33%) in Singaporean Chinese and 0.34% in East Asians, suggesting a global disease burden exceeding 10,000 individuals. CONCLUSION The EYS C2139Y variant is common in Singaporean RP patients and other ethnic Chinese populations. Targeted molecular therapy for this single variant could potentially treat a significant proportion of RP cases worldwide.
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Affiliation(s)
- Choi Mun Chan
- Singapore National Eye Centre, Singapore Eye Research Institute, and the Ophthalmology and Visual Sciences Academic Clinical Program (EYE ACP), Duke-NUS Graduate Medical School, Singapore
| | - Tien-En Tan
- Singapore National Eye Centre, Singapore Eye Research Institute, and the Ophthalmology and Visual Sciences Academic Clinical Program (EYE ACP), Duke-NUS Graduate Medical School, Singapore
| | - Kanika Jain
- Genome Institute of Singapore, Agency for Science, Technology and Research (A*STAR), Singapore
| | - Yasmin Bylstra
- SingHealth Duke-NUS Institute of Precision Medicine (PRISM), Singapore
| | - Ranjana S Mathur
- Singapore National Eye Centre, Singapore Eye Research Institute, and the Ophthalmology and Visual Sciences Academic Clinical Program (EYE ACP), Duke-NUS Graduate Medical School, Singapore
| | - Rachael W C Tang
- Singapore National Eye Centre, Singapore Eye Research Institute, and the Ophthalmology and Visual Sciences Academic Clinical Program (EYE ACP), Duke-NUS Graduate Medical School, Singapore
| | - Brian J H Lee
- Lee Kong Chian Medical School, Nanyang Technological University, Singapore; and
| | - Saumya S Jamuar
- Department of Paediatrics, KK Women's and Children's Hospital and the SingHealth Duke-NUS Genomic Medicine Center, Singapore
| | - Sylvia Kam
- Department of Paediatrics, KK Women's and Children's Hospital and the SingHealth Duke-NUS Genomic Medicine Center, Singapore
| | - Eranga N Vithana
- Singapore National Eye Centre, Singapore Eye Research Institute, and the Ophthalmology and Visual Sciences Academic Clinical Program (EYE ACP), Duke-NUS Graduate Medical School, Singapore
| | - Weng Khong Lim
- SingHealth Duke-NUS Institute of Precision Medicine (PRISM), Singapore
| | - Beau J Fenner
- Singapore National Eye Centre, Singapore Eye Research Institute, and the Ophthalmology and Visual Sciences Academic Clinical Program (EYE ACP), Duke-NUS Graduate Medical School, Singapore
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13
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Mina T, Yew YW, Ng HK, Sadhu N, Wansaicheong G, Dalan R, Low DYW, Lam BCC, Riboli E, Lee ES, Ngeow J, Elliott P, Griva K, Loh M, Lee J, Chambers J. Adiposity impacts cognitive function in Asian populations: an epidemiological and Mendelian Randomization study. THE LANCET REGIONAL HEALTH. WESTERN PACIFIC 2023; 33:100710. [PMID: 36851942 PMCID: PMC9957736 DOI: 10.1016/j.lanwpc.2023.100710] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 01/19/2023] [Accepted: 01/26/2023] [Indexed: 02/15/2023]
Abstract
Background Obesity and related metabolic disturbances including diabetes, hypertension and hyperlipidemia predict future cognitive decline. Asia has a high prevalence of both obesity and metabolic disease, potentially amplifying the future burden of dementia in the region. We aimed to investigate the impact of adiposity and metabolic risk on cognitive function in Asian populations, using an epidemiological analysis and a two-sample Mendelian Randomization (MR) study. Methods The Health for Life in Singapore (HELIOS) Study is a population-based cohort of South-East-Asian men and women in Singapore, aged 30-84 years. We analyzed 8769 participants with metabolic and cognitive data collected between 2018 and 2021. Whole-body fat mass was quantified with Dual X-Ray Absorptiometry (DEXA). Cognition was assessed using a computerized cognitive battery. An index of general cognition ' g ' was derived through factor analysis. We tested the relationship of fat mass indices and metabolic measures with ' g ' using regression approaches. We then performed inverse-variance-weighted MR of adiposity and metabolic risk factors on ' g ', using summary statistics for genome-wide association studies of BMI, visceral adipose tissue (VAT), waist-hip-ratio (WHR), blood pressure, HDL cholesterol, triglycerides, fasting glucose, HbA1c, and general cognition. Findings Participants were 58.9% female, and aged 51.4 (11.3) years. In univariate analysis, all 29 adiposity and metabolic measures assessed were associated with ' g ' at P < 0.05. In multivariable analyses, reduced ' g ' was consistently associated with increased visceral fat mass index and lower HDL cholesterol (P < 0.001), but not with blood pressure, triglycerides, or glycemic indices. The reduction in ' g ' associated with 1SD higher visceral fat, or 1SD lower HDL cholesterol, was equivalent to a 0.7 and 0.9-year increase in chronological age respectively (P < 0.001). Inverse variance MR analyses showed that reduced ' g ' is associated with genetically determined elevation of VAT, BMI and WHR (all P < 0.001). In contrast, MR did not support a causal role for blood pressure, lipid, or glycemic indices on cognition. Interpretation We show an independent relationship between adiposity and cognition in a multi-ethnic Asian population. MR analyses suggest that both visceral adiposity and raised BMI are likely to be causally linked to cognition. Our findings have important implications for preservation of cognitive health, including further motivation for action to reverse the rising burden of obesity in the Asia-Pacific region. Funding The Nanyang Technological University-the Lee Kong Chian School of Medicine, National Healthcare Group, National Medical Research Council, Ministry of Education, Singapore.
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Affiliation(s)
- Theresia Mina
- Nanyang Technological University Lee Kong Chian School of Medicine, Level 18 Clinical Sciences Building, 11 Mandalay Road, 308232, Singapore
| | - Yik Weng Yew
- Nanyang Technological University Lee Kong Chian School of Medicine, Level 18 Clinical Sciences Building, 11 Mandalay Road, 308232, Singapore.,National Skin Centre, Research Division, 1 Mandalay Rd, 308205, Singapore
| | - Hong Kiat Ng
- Nanyang Technological University Lee Kong Chian School of Medicine, Level 18 Clinical Sciences Building, 11 Mandalay Road, 308232, Singapore
| | - Nilanjana Sadhu
- Nanyang Technological University Lee Kong Chian School of Medicine, Level 18 Clinical Sciences Building, 11 Mandalay Road, 308232, Singapore
| | - Gervais Wansaicheong
- Nanyang Technological University Lee Kong Chian School of Medicine, Level 18 Clinical Sciences Building, 11 Mandalay Road, 308232, Singapore.,Department of Diagnostic Radiology, Tan Tock Seng Hospital (TTSH), 11 Jalan Tan Tock Seng, 308433, Singapore
| | - Rinkoo Dalan
- Nanyang Technological University Lee Kong Chian School of Medicine, Level 18 Clinical Sciences Building, 11 Mandalay Road, 308232, Singapore.,Department of Endocrinology, TTSH, Singapore
| | - Dorrain Yan Wen Low
- Nanyang Technological University Lee Kong Chian School of Medicine, Level 18 Clinical Sciences Building, 11 Mandalay Road, 308232, Singapore
| | - Benjamin Chih Chiang Lam
- Nanyang Technological University Lee Kong Chian School of Medicine, Level 18 Clinical Sciences Building, 11 Mandalay Road, 308232, Singapore.,Khoo Teck Puat Hospital, Integrated Care for Obesity & Diabetes, 90 Yishun Central, 768828, Singapore
| | - Elio Riboli
- Nanyang Technological University Lee Kong Chian School of Medicine, Level 18 Clinical Sciences Building, 11 Mandalay Road, 308232, Singapore.,Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, 152 Medical School, St Mary's Campus, London, W2 1NY, United Kingdom
| | - Eng Sing Lee
- Nanyang Technological University Lee Kong Chian School of Medicine, Level 18 Clinical Sciences Building, 11 Mandalay Road, 308232, Singapore.,Clinical Research Unit, National Healthcare Group Polyclinic, 3 Fusionopolis Link, Nexus@one-north, #05-10, 138543, Singapore
| | - Joanne Ngeow
- Nanyang Technological University Lee Kong Chian School of Medicine, Level 18 Clinical Sciences Building, 11 Mandalay Road, 308232, Singapore.,Division of Medical Oncology, National Cancer Centre, 11 Hospital Drive, 169610, Singapore
| | - Paul Elliott
- Nanyang Technological University Lee Kong Chian School of Medicine, Level 18 Clinical Sciences Building, 11 Mandalay Road, 308232, Singapore.,Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, 152 Medical School, St Mary's Campus, London, W2 1NY, United Kingdom
| | - Konstadina Griva
- Nanyang Technological University Lee Kong Chian School of Medicine, Level 18 Clinical Sciences Building, 11 Mandalay Road, 308232, Singapore
| | - Marie Loh
- Nanyang Technological University Lee Kong Chian School of Medicine, Level 18 Clinical Sciences Building, 11 Mandalay Road, 308232, Singapore.,National Skin Centre, Research Division, 1 Mandalay Rd, 308205, Singapore
| | - Jimmy Lee
- Nanyang Technological University Lee Kong Chian School of Medicine, Level 18 Clinical Sciences Building, 11 Mandalay Road, 308232, Singapore.,Research Division, Institute of Mental Health, 539747, Singapore
| | - John Chambers
- Nanyang Technological University Lee Kong Chian School of Medicine, Level 18 Clinical Sciences Building, 11 Mandalay Road, 308232, Singapore.,Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, 152 Medical School, St Mary's Campus, London, W2 1NY, United Kingdom
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14
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Sypniewski M, Kresa D, Dobosz P, Topolski P, Kotuła L, Sztromwasser P, Mroczek M. Population WGS-based spinal muscular atrophy carrier screening in a cohort of 1076 healthy Polish individuals. J Appl Genet 2023; 64:135-139. [PMID: 36417168 DOI: 10.1007/s13353-022-00737-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Revised: 11/11/2022] [Accepted: 11/16/2022] [Indexed: 11/24/2022]
Abstract
Spinal muscular atrophy is a severe neuromuscular disorder with an autosomal recessive inheritance pattern. The disease-causing gene is SMN1, and its paralogue, SMN2, is a disease course modifier. Both genes SMN1 and SMN2 show over 99.9% sequence identity and a high rate of crossing over in the genomic region. Due to this reason, SMN1/SMN2 is usually excluded from the whole-genome sequencing (WGS) analysis and investigated with traditional methods, such as MLPA and qPCR. Recently, novel bioinformatic algorithms dedicated to analyzing this particular genomic region have been developed. Here, we analyze the SMN1/SMN2 genomic region with a dedicated program, SMNCopyNumberCaller. We report a similar prevalence of SMN1 gene deletion carrier status (1 per 41 people) to published data from the Polish population (1 per 35 people). Additionally, SMNCopyNumberCaller can identify SMN2 CNVs and SMN2Δ7-8 present in 153 healthy Polish individuals. Two other programs for the CNV analysis in standard genomic regions were not able to provide reliable results. Using WGS-based tools for SMN1/2 genomic region analysis is not only an efficient method in terms of time but will also enable more complex analysis such screening for markers related with a silent carrier status and identification of further genetic modifiers. Although still an experimental method, soon WGS-based SMN1/SMN2 carrier identification may become a standard method for patients screened with WGS for other purposes.
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Affiliation(s)
- Mateusz Sypniewski
- Central Clinical Hospital of Ministry of the Interior and Administration in Warsaw, 02-507, Warsaw, Poland
| | - Dominika Kresa
- Faculty of Bioscience Engineering, KU Leuven, Louvain, Belgium
| | - Paula Dobosz
- Central Clinical Hospital of Ministry of the Interior and Administration in Warsaw, 02-507, Warsaw, Poland
| | - Piotr Topolski
- Central Clinical Hospital of Ministry of the Interior and Administration in Warsaw, 02-507, Warsaw, Poland
| | - Lidia Kotuła
- Zakład Genetyki Klinicznej, Uniwersytet Medyczny w Lublinie, Lublin, Poland
| | | | - Magdalena Mroczek
- Center for Cardiovascular Genetics & Gene Diagnostics, Foundation for People With Rare Diseases, 8952, Schlieren-Zurich, Switzerland.
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