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Malomane D, Williams MP, Huber C, Mangul S, Abedalthagafi M, Chiang CWK. Patterns of population structure and genetic variation within the Saudi Arabian population. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2025.01.10.632500. [PMID: 39868174 PMCID: PMC11761371 DOI: 10.1101/2025.01.10.632500] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 01/28/2025]
Abstract
The Arabian Peninsula is considered the initial site of historic human migration out of Africa. The modern-day indigenous Arabians are believed to be the descendants who remained from the ancient split of the migrants into Eurasia. Here, we investigated how the population history and cultural practices such as endogamy have shaped the genetic variation of the Saudi Arabians. We genotyped 3,352 individuals and identified twelve genetic sub-clusters that corresponded to the geographical distribution of different tribal regions, differentiated by distinct components of ancestry based on comparisons to modern and ancient DNA references. These sub-clusters also showed variation across ranges of the genome covered in runs of homozygosity, as well as differences in population size changes over time. Using 25,488,981 variants found in whole genome sequencing data (WGS) from 302 individuals, we found that the Saudi tend to show proportionally more deleterious alleles than neutral alleles when compared to Africans/African Americans from gnomAD (e.g. a 13% increase of deleterious alleles annotated by AlphaMissense between 0.5 - 5% frequency in Saudi, compared to 7% decrease of the benign alleles; P < 0.001). Saudi sub-clusters with greater inbreeding and lower effective population sizes showed greater enrichment of deleterious alleles as well. Additionally, we found that approximately 10% of the variants discovered in our WGS data are not observed in gnomAD; these variants are also enriched with deleterious annotations. To accelerate studying the population-enriched deleterious alleles and their health consequences in this population, we made available the allele frequency estimates of 25,488,981 variants discovered in our samples. Taken together, our results suggest that Saudi's population history impacts its pattern of genetic variation with potential consequences to the population health. It further highlights the need to sequence diverse and unique populations so to provide a foundation on which to interpret medical- and pharmaco- genomic findings from these populations.
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Affiliation(s)
- D.K. Malomane
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA
| | - M. P. Williams
- Department of Biology, Pennsylvania State University, University Park, PA
| | - C.D. Huber
- Department of Biology, Pennsylvania State University, University Park, PA
| | - S. Mangul
- Titus Department of Clinical Pharmacy, Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, Los Angeles, CA
| | - M. Abedalthagafi
- Department of Pathology and Laboratory Medicine, Emory University Hospital, Atlanta, GA
- Genomics Research Department, King Fahad Medical City, Riyadh, Saudi Arabia
| | - C. W. K. Chiang
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA
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Khan SA, Anwar M, Gohar A, Roosan MR, Hoessli DC, Khatoon A, Shakeel M. Predisposing deleterious variants in the cancer-associated human kinases in the global populations. PLoS One 2024; 19:e0298747. [PMID: 38635549 PMCID: PMC11025791 DOI: 10.1371/journal.pone.0298747] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Accepted: 01/29/2024] [Indexed: 04/20/2024] Open
Abstract
Human kinases play essential and diverse roles in the cellular activities of maintaining homeostasis and growth. Genetic mutations in the genes encoding the kinases (or phosphotransferases) have been linked with various types of cancers. In this study, we cataloged mutations in 500 kinases genes in >65,000 individuals of global populations from the Human Genetic Diversity Project (HGDP) and ExAC databases, and assessed their potentially deleterious impact by using the in silico tools SIFT, Polyphen2, and CADD. The analysis highlighted 35 deleterious non-synonymous SNVs in the ExAC and 5 SNVs in the HGDP project. Notably, a higher number of deleterious mutations was observed in the Non-Finnish Europeans (26 SNVs), followed by the Africans (14 SNVs), East Asians (13 SNVs), and South Asians (12 SNVs). The gene set enrichment analysis highlighted NTRK1 and FGFR3 being most significantly enriched among the kinases. The gene expression analysis revealed over-expression of NTRK1 in liver cancer, whereas, FGFR3 was found over-expressed in lung, breast, and liver cancers compared to their expression in the respective normal tissues. Also, 13 potential drugs were identified that target the NTRK1 protein, whereas 6 potential drugs for the FGFR3 target were identified. Taken together, the study provides a framework for exploring the predisposing germline mutations in kinases to suggest the underlying pathogenic mechanisms in cancers. The potential drugs are also suggested for personalized cancer management.
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Affiliation(s)
- Salman Ahmed Khan
- Department of Molecular Medicine (DMM), Dow College of Biotechnology (DCoB), Dow University of Health Sciences (DUHS), Karachi, Pakistan
- DOW-DOGANA Advanced Molecular Genetics and Genomics Disease Research and Treatment Center (AMGGDRTC), Dow University of Health Sciences (DUHS), Karachi, Pakistan
| | - Misbah Anwar
- Jamil-ur-Rahman Center for Genome Research, Dr. Panjwani Center for Molecular Medicine and Drug Research, International Center for Chemical and Biological Sciences (ICCBS), University of Karachi, Karachi, Pakistan
| | - Atia Gohar
- H.E.J. Research Institute of Chemistry, International Center for Chemical and Biological Sciences (ICCBS), University of Karachi, Karachi, Pakistan
| | - Moom R. Roosan
- Department of Pharmacy Practice, Chapman University School of Pharmacy Harry and Diane Rinker Health Science Campus, Irvine, CA, United States of America
| | - Daniel C. Hoessli
- Jamil-ur-Rahman Center for Genome Research, Dr. Panjwani Center for Molecular Medicine and Drug Research, International Center for Chemical and Biological Sciences (ICCBS), University of Karachi, Karachi, Pakistan
| | - Ambrina Khatoon
- Department of Molecular Medicine, Ziauddin University, Karachi, Pakistan
| | - Muhammad Shakeel
- Jamil-ur-Rahman Center for Genome Research, Dr. Panjwani Center for Molecular Medicine and Drug Research, International Center for Chemical and Biological Sciences (ICCBS), University of Karachi, Karachi, Pakistan
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Ramasamy U, Elizur A, Subramanian S. Deleterious mutation load in the admixed mice population. Front Ecol Evol 2023. [DOI: 10.3389/fevo.2023.1084502] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/18/2023] Open
Abstract
Deleterious mutation loads are known to correlate negatively with effective population size (Ne). Due to this reason, previous studies observed a higher proportion of harmful mutations in small populations than that in large populations. However, the mutational load in an admixed population that derived from introgression between individuals from two populations with vastly different Ne is not known. We investigated this using the whole genome data from two subspecies of the mouse (Mus musculus castaneus and Mus musculus musculus) with significantly different Ne. We used the ratio of diversities at nonsynonymous and synonymous sites (dN/dS) to measure the harmful mutation load. Our results showed that this ratio observed for the admixed population was intermediate between those of the parental populations. The dN/dS ratio of the hybrid population was significantly higher than that of M. m. castaneus but lower than that of M. m. musculus. Our analysis revealed a significant positive correlation between the proportion of M. m. musculus ancestry in admixed individuals and their dN/dS ratio. This suggests that the admixed individuals with high proportions of M. m. musculus ancestry have large dN/dS ratios. We also used the proportion of deleterious nonsynonymous SNVs as a proxy for deleterious mutation load, which also produced similar results. The observed results were in concordance with those expected by theory. We also show a shift in the distribution of fitness effects of nonsynonymous SNVs in the admixed genomes compared to the parental populations. These findings suggest that the deleterious mutation load of the admixed population is determined by the proportion of the ancestries of the subspecies. Therefore, it is important to consider the status and the level of genetic admixture of the populations whilst estimating the mutation loads.
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Deleterious protein-coding variants in diverse cattle breeds of the world. Genet Sel Evol 2021; 53:80. [PMID: 34654372 PMCID: PMC8518297 DOI: 10.1186/s12711-021-00674-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2021] [Accepted: 09/22/2021] [Indexed: 11/16/2022] Open
Abstract
The domestication of wild animals has resulted in a reduction in effective population sizes, which can affect the deleterious mutation load of domesticated breeds. In addition, artificial selection contributes to the accumulation of deleterious mutations because of an increased rate of inbreeding among domesticated animals. Since founder population sizes and artificial selection differ between cattle breeds, their deleterious mutation load can vary. We investigated this question by using whole-genome data from 432 animals belonging to 54 worldwide cattle breeds. Our analysis revealed a negative correlation between genomic heterozygosity and nonsynonymous-to-silent diversity ratio, which suggests a higher proportion of single nucleotide variants (SNVs) affecting proteins in low-diversity breeds. Our results also showed that low-diversity breeds had a larger number of high-frequency (derived allele frequency (DAF) > 0.51) deleterious SNVs than high-diversity breeds. An opposite trend was observed for the low-frequency (DAF ≤ 0.51) deleterious SNVs. Overall, the number of high-frequency deleterious SNVs was larger in the genomes of taurine cattle breeds than of indicine breeds, whereas the number of low-frequency deleterious SNVs was larger in the genomes of indicine cattle than in those of taurine cattle. Furthermore, we observed significant variation in the counts of deleterious SNVs within taurine breeds. The variations in deleterious mutation load between taurine and indicine breeds could be attributed to the population sizes of the wild progenitors before domestication, whereas the variations observed within taurine breeds could be due to differences in inbreeding level, strength of artificial selection, and/or founding population size. Our findings imply that the incidence of genetic diseases can vary between cattle breeds.
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Subramanian S. Harmful mutation load in the mitochondrial genomes of cattle breeds. BMC Res Notes 2021; 14:241. [PMID: 34176488 PMCID: PMC8237412 DOI: 10.1186/s13104-021-05664-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Accepted: 06/18/2021] [Indexed: 12/03/2022] Open
Abstract
Objective Domestication of wild animals results in a reduction in the effective population size, and this could affect the deleterious mutation load of domesticated breeds. Furthermore, artificial selection will also contribute to the accumulation of deleterious mutations due to the increased rate of inbreeding among these animals. The process of domestication, founder population size, and artificial selection differ between cattle breeds, which could lead to a variation in their deleterious mutation loads. We investigated this using mitochondrial genome data from 364 animals belonging to 18 cattle breeds of the world. Results Our analysis revealed more than a fivefold difference in the deleterious mutation load among cattle breeds. We also observed a negative correlation between the breed age and the proportion of deleterious amino acid-changing polymorphisms. This suggests a proportionally higher deleterious SNPs in young breeds compared to older breeds. Our results highlight the magnitude of difference in the deleterious mutations present in the mitochondrial genomes of various breeds. The results of this study could be useful in predicting the rate of incidence of genetic diseases in different breeds. Supplementary Information The online version contains supplementary material available at 10.1186/s13104-021-05664-y.
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Affiliation(s)
- Sankar Subramanian
- GeneCology Research Centre, School of Science, Technology and Engineering, The University of the Sunshine Coast, 1 Moreton Parade, Petrie, Moreton Bay, QLD, 4502, Australia.
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Subramanian S. Population size influences the type of nucleotide variations in humans. BMC Genet 2019; 20:93. [PMID: 31805852 PMCID: PMC6894472 DOI: 10.1186/s12863-019-0798-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2019] [Accepted: 12/01/2019] [Indexed: 11/24/2022] Open
Abstract
Background It is well known that the effective size of a population (Ne) is one of the major determinants of the amount of genetic variation within the population. However, it is unclear whether the types of genetic variations are also dictated by the effective population size. To examine this, we obtained whole genome data from over 100 populations of the world and investigated the patterns of mutational changes. Results Our results revealed that for low frequency variants, the ratio of AT→GC to GC→AT variants (β) was similar across populations, suggesting the similarity of the pattern of mutation in various populations. However, for high frequency variants, β showed a positive correlation with the effective population size of the populations. This suggests a much higher proportion of high frequency AT→GC variants in large populations (e.g. Africans) compared to those with small population sizes (e.g. Asians). These results imply that the substitution patterns vary significantly between populations. These findings could be explained by the effect of GC-biased gene conversion (gBGC), which favors the fixation of G/C over A/T variants in populations. In large population, gBGC causes high β. However, in small populations, genetic drift reduces the effect of gBGC resulting in reduced β. This was further confirmed by a positive relationship between Ne and β for homozygous variants. Conclusions Our results highlight the huge variation in the types of homozygous and high frequency polymorphisms between world populations. We observed the same pattern for deleterious variants, implying that the homozygous polymorphisms associated with recessive genetic diseases will be more enriched with G or C in populations with large Ne (e.g. Africans) than in populations with small Ne (e.g. Europeans).
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Affiliation(s)
- Sankar Subramanian
- GeneCology Research Centre, University of the Sunshine Coast, 90 Sippy Downs Drive, Sippy Downs, QLD 4556, Australia.
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7
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Kremer LS, Bader DM, Mertes C, Kopajtich R, Pichler G, Iuso A, Haack TB, Graf E, Schwarzmayr T, Terrile C, Koňaříková E, Repp B, Kastenmüller G, Adamski J, Lichtner P, Leonhardt C, Funalot B, Donati A, Tiranti V, Lombes A, Jardel C, Gläser D, Taylor RW, Ghezzi D, Mayr JA, Rötig A, Freisinger P, Distelmaier F, Strom TM, Meitinger T, Gagneur J, Prokisch H. Genetic diagnosis of Mendelian disorders via RNA sequencing. Nat Commun 2017; 8:15824. [PMID: 28604674 PMCID: PMC5499207 DOI: 10.1038/ncomms15824] [Citation(s) in RCA: 393] [Impact Index Per Article: 49.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2016] [Accepted: 04/28/2017] [Indexed: 12/23/2022] Open
Abstract
Across a variety of Mendelian disorders, ∼50-75% of patients do not receive a genetic diagnosis by exome sequencing indicating disease-causing variants in non-coding regions. Although genome sequencing in principle reveals all genetic variants, their sizeable number and poorer annotation make prioritization challenging. Here, we demonstrate the power of transcriptome sequencing to molecularly diagnose 10% (5 of 48) of mitochondriopathy patients and identify candidate genes for the remainder. We find a median of one aberrantly expressed gene, five aberrant splicing events and six mono-allelically expressed rare variants in patient-derived fibroblasts and establish disease-causing roles for each kind. Private exons often arise from cryptic splice sites providing an important clue for variant prioritization. One such event is found in the complex I assembly factor TIMMDC1 establishing a novel disease-associated gene. In conclusion, our study expands the diagnostic tools for detecting non-exonic variants and provides examples of intronic loss-of-function variants with pathological relevance.
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Affiliation(s)
- Laura S. Kremer
- Institute of Human Genetics, Helmholtz Zentrum München, 85764 Neuherberg, Germany
- Institute of Human Genetics, Klinikum rechts der Isar, Technische Universität München, 81675 München, Germany
| | - Daniel M. Bader
- Department of Informatics, Technische Universität München, 85748 Garching, Germany
- Quantitative Biosciences Munich, Gene Center, Department of Biochemistry, Ludwig Maximilian Universität München, 81377 München, Germany
| | - Christian Mertes
- Department of Informatics, Technische Universität München, 85748 Garching, Germany
| | - Robert Kopajtich
- Institute of Human Genetics, Helmholtz Zentrum München, 85764 Neuherberg, Germany
- Institute of Human Genetics, Klinikum rechts der Isar, Technische Universität München, 81675 München, Germany
| | - Garwin Pichler
- Department of Proteomics and Signal Transduction, Max-Planck Institute of Biochemistry, 82152 Martinsried, Germany
| | - Arcangela Iuso
- Institute of Human Genetics, Helmholtz Zentrum München, 85764 Neuherberg, Germany
- Institute of Human Genetics, Klinikum rechts der Isar, Technische Universität München, 81675 München, Germany
| | - Tobias B. Haack
- Institute of Human Genetics, Helmholtz Zentrum München, 85764 Neuherberg, Germany
- Institute of Human Genetics, Klinikum rechts der Isar, Technische Universität München, 81675 München, Germany
| | - Elisabeth Graf
- Institute of Human Genetics, Helmholtz Zentrum München, 85764 Neuherberg, Germany
- Institute of Human Genetics, Klinikum rechts der Isar, Technische Universität München, 81675 München, Germany
| | - Thomas Schwarzmayr
- Institute of Human Genetics, Helmholtz Zentrum München, 85764 Neuherberg, Germany
- Institute of Human Genetics, Klinikum rechts der Isar, Technische Universität München, 81675 München, Germany
| | - Caterina Terrile
- Institute of Human Genetics, Helmholtz Zentrum München, 85764 Neuherberg, Germany
| | - Eliška Koňaříková
- Institute of Human Genetics, Helmholtz Zentrum München, 85764 Neuherberg, Germany
- Institute of Human Genetics, Klinikum rechts der Isar, Technische Universität München, 81675 München, Germany
| | - Birgit Repp
- Institute of Human Genetics, Helmholtz Zentrum München, 85764 Neuherberg, Germany
- Institute of Human Genetics, Klinikum rechts der Isar, Technische Universität München, 81675 München, Germany
| | - Gabi Kastenmüller
- Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, 85764 Neuherberg, Germany
| | - Jerzy Adamski
- Institute of Experimental Genetics, Genome Analysis Center, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany
| | - Peter Lichtner
- Institute of Human Genetics, Helmholtz Zentrum München, 85764 Neuherberg, Germany
| | | | - Benoit Funalot
- INSERM U1163, Université Paris Descartes—Sorbonne Paris Cité, Institut Imagine, 75015 Paris, France
| | - Alice Donati
- Metabolic Unit, A. Meyer Children’s Hospital, 50139 Florence, Italy
| | - Valeria Tiranti
- Unit of Molecular Neurogenetics, Foundation IRCCS (Istituto di Ricovero e Cura a Carettere Scientifico) Neurological Institute ‘Carlo Besta’, 20126 Milan, Italy
| | - Anne Lombes
- Inserm UMR 1016, Institut Cochin, 75014 Paris, France
- CNRS UMR 8104, Institut Cochin, 75014 Paris, France
- Université Paris V René Descartes, Institut Cochin, 75014 Paris, France
| | - Claude Jardel
- Inserm UMR 1016, Institut Cochin, 75014 Paris, France
- AP/HP, GHU Pitié-Salpêtrière, Service de Biochimie Métabolique, 75013 Paris, France
| | - Dieter Gläser
- Genetikum, Genetic Counseling and Diagnostics, 89231 Neu-Ulm, Germany
| | - Robert W. Taylor
- Wellcome Centre for Mitochondrial Research, Institute of Neuroscience, Newcastle University, Newcastle upon Tyne NE2 4HH, UK
| | - Daniele Ghezzi
- Unit of Molecular Neurogenetics, Foundation IRCCS (Istituto di Ricovero e Cura a Carettere Scientifico) Neurological Institute ‘Carlo Besta’, 20126 Milan, Italy
| | - Johannes A. Mayr
- Department of Pediatrics, Paracelsus Medical University, A-5020 Salzburg, Austria
| | - Agnes Rötig
- INSERM U1163, Université Paris Descartes—Sorbonne Paris Cité, Institut Imagine, 75015 Paris, France
| | - Peter Freisinger
- Department of Pediatrics, Klinikum Reutlingen, 72764 Reutlingen, Germany
| | - Felix Distelmaier
- Department of General Pediatrics, Neonatology and Pediatric Cardiology, University Children’s Hospital, Heinrich-Heine-University Düsseldorf, 40225 Düsseldorf, Germany
| | - Tim M. Strom
- Institute of Human Genetics, Helmholtz Zentrum München, 85764 Neuherberg, Germany
- Institute of Human Genetics, Klinikum rechts der Isar, Technische Universität München, 81675 München, Germany
| | - Thomas Meitinger
- Institute of Human Genetics, Helmholtz Zentrum München, 85764 Neuherberg, Germany
- Institute of Human Genetics, Klinikum rechts der Isar, Technische Universität München, 81675 München, Germany
| | - Julien Gagneur
- Department of Informatics, Technische Universität München, 85748 Garching, Germany
- Quantitative Biosciences Munich, Gene Center, Department of Biochemistry, Ludwig Maximilian Universität München, 81377 München, Germany
| | - Holger Prokisch
- Institute of Human Genetics, Helmholtz Zentrum München, 85764 Neuherberg, Germany
- Institute of Human Genetics, Klinikum rechts der Isar, Technische Universität München, 81675 München, Germany
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Anazi S, Maddirevula S, Faqeih E, Alsedairy H, Alzahrani F, Shamseldin HE, Patel N, Hashem M, Ibrahim N, Abdulwahab F, Ewida N, Alsaif HS, Al Sharif H, Alamoudi W, Kentab A, Bashiri FA, Alnaser M, AlWadei AH, Alfadhel M, Eyaid W, Hashem A, Al Asmari A, Saleh MM, AlSaman A, Alhasan KA, Alsughayir M, Al Shammari M, Mahmoud A, Al-Hassnan ZN, Al-Husain M, Osama Khalil R, Abd El Meguid N, Masri A, Ali R, Ben-Omran T, El Fishway P, Hashish A, Ercan Sencicek A, State M, Alazami AM, Salih MA, Altassan N, Arold ST, Abouelhoda M, Wakil SM, Monies D, Shaheen R, Alkuraya FS. Clinical genomics expands the morbid genome of intellectual disability and offers a high diagnostic yield. Mol Psychiatry 2017; 22:615-624. [PMID: 27431290 DOI: 10.1038/mp.2016.113] [Citation(s) in RCA: 176] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/04/2016] [Revised: 06/02/2016] [Accepted: 06/06/2016] [Indexed: 12/13/2022]
Abstract
Intellectual disability (ID) is a measurable phenotypic consequence of genetic and environmental factors. In this study, we prospectively assessed the diagnostic yield of genomic tools (molecular karyotyping, multi-gene panel and exome sequencing) in a cohort of 337 ID subjects as a first-tier test and compared it with a standard clinical evaluation performed in parallel. Standard clinical evaluation suggested a diagnosis in 16% of cases (54/337) but only 70% of these (38/54) were subsequently confirmed. On the other hand, the genomic approach revealed a likely diagnosis in 58% (n=196). These included copy number variants in 14% (n=54, 15% are novel), and point mutations revealed by multi-gene panel and exome sequencing in the remaining 43% (1% were found to have Fragile-X). The identified point mutations were mostly recessive (n=117, 81%), consistent with the high consanguinity of the study cohort, but also X-linked (n=8, 6%) and de novo dominant (n=19, 13%). When applied directly on all cases with negative molecular karyotyping, the diagnostic yield of exome sequencing was 60% (77/129). Exome sequencing also identified likely pathogenic variants in three novel candidate genes (DENND5A, NEMF and DNHD1) each of which harbored independent homozygous mutations in patients with overlapping phenotypes. In addition, exome sequencing revealed de novo and recessive variants in 32 genes (MAMDC2, TUBAL3, CPNE6, KLHL24, USP2, PIP5K1A, UBE4A, TP53TG5, ATOH1, C16ORF90, SLC39A14, TRERF1, RGL1, CDH11, SYDE2, HIRA, FEZF2, PROCA1, PIANP, PLK2, QRFPR, AP3B2, NUDT2, UFC1, BTN3A2, TADA1, ARFGEF3, FAM160B1, ZMYM5, SLC45A1, ARHGAP33 and CAPS2), which we highlight as potential candidates on the basis of several lines of evidence, and one of these genes (SLC39A14) was biallelically inactivated in a potentially treatable form of hypermanganesemia and neurodegeneration. Finally, likely causal variants in previously published candidate genes were identified (ASTN1, HELZ, THOC6, WDR45B, ADRA2B and CLIP1), thus supporting their involvement in ID pathogenesis. Our results expand the morbid genome of ID and support the adoption of genomics as a first-tier test for individuals with ID.
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Affiliation(s)
- S Anazi
- Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - S Maddirevula
- Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - E Faqeih
- Department of Pediatric Subspecialties, Children's Hospital, King Fahad Medical City, Riyadh, Saudi Arabia
| | - H Alsedairy
- Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - F Alzahrani
- Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - H E Shamseldin
- Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - N Patel
- Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - M Hashem
- Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - N Ibrahim
- Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - F Abdulwahab
- Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - N Ewida
- Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - H S Alsaif
- Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - H Al Sharif
- Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - W Alamoudi
- Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - A Kentab
- Department of Pediatrics, College of Medicine & King Khalid University Hospital, King Saud University, Riyadh, Saudi Arabia
| | - F A Bashiri
- Department of Pediatrics, College of Medicine & King Khalid University Hospital, King Saud University, Riyadh, Saudi Arabia
| | - M Alnaser
- Department of Pediatrics, College of Medicine & King Khalid University Hospital, King Saud University, Riyadh, Saudi Arabia
| | - A H AlWadei
- Pediatric Neurology Department, National Neuroscience Institute, King Fahad Medical City, Riyadh, Saudi Arabia
| | - M Alfadhel
- Department of Pediatrics, King Saud bin Abdulaziz University for Health Science, King Abdulaziz Medical City, Riyadh, Saudi Arabia
| | - W Eyaid
- Department of Pediatrics, King Saud bin Abdulaziz University for Health Science, King Abdulaziz Medical City, Riyadh, Saudi Arabia
| | - A Hashem
- Department of Pediatrics, Prince Sultan Military Medical City, Riyadh, Saudi Arabia
| | - A Al Asmari
- Department of Pediatric Subspecialties, Children's Hospital, King Fahad Medical City, Riyadh, Saudi Arabia
| | - M M Saleh
- Department of Pediatric Subspecialties, Children's Hospital, King Fahad Medical City, Riyadh, Saudi Arabia
| | - A AlSaman
- Pediatric Neurology Department, National Neuroscience Institute, King Fahad Medical City, Riyadh, Saudi Arabia
| | - K A Alhasan
- Department of Pediatrics, College of Medicine & King Khalid University Hospital, King Saud University, Riyadh, Saudi Arabia
| | - M Alsughayir
- Department of Psychiatry, College of Medicine, King Saud University, Riyadh, Saudi Arabia
| | - M Al Shammari
- Department of Pediatrics, College of Medicine & King Khalid University Hospital, King Saud University, Riyadh, Saudi Arabia
| | - A Mahmoud
- Pediatric Neurology Department, National Neuroscience Institute, King Fahad Medical City, Riyadh, Saudi Arabia
| | - Z N Al-Hassnan
- Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - M Al-Husain
- Department of Pediatrics, College of Medicine & King Khalid University Hospital, King Saud University, Riyadh, Saudi Arabia
| | - R Osama Khalil
- Department of Psychiatry, University of California, San Francisco, San Francisco, CA, USA.,National Research Center, Cairo, Egypt
| | | | - A Masri
- Department of Pediatrics, Faculty of Medicine, The University of Jordan, Amman, Jordan
| | - R Ali
- Clinical & Metabolic Genetics, Pediatrics, Hamad Medical Corporation, Doha, Qatar
| | - T Ben-Omran
- Clinical & Metabolic Genetics, Pediatrics, Hamad Medical Corporation, Doha, Qatar
| | - P El Fishway
- Department of Neurosurgery, Program on Neurogenetics, Yale University School of Medicine, New Haven, CT, USA
| | - A Hashish
- National Research Center, Cairo, Egypt
| | - A Ercan Sencicek
- Department of Neurosurgery, Program on Neurogenetics, Yale University School of Medicine, New Haven, CT, USA
| | - M State
- Department of Psychiatry, University of California, San Francisco, San Francisco, CA, USA
| | - A M Alazami
- Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - M A Salih
- Department of Pediatrics, College of Medicine & King Khalid University Hospital, King Saud University, Riyadh, Saudi Arabia
| | - N Altassan
- Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - S T Arold
- King Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Center (CBRC), Division of Biological and Environmental Sciences and Engineering (BESE), Thuwal, Saudi Arabia
| | - M Abouelhoda
- Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - S M Wakil
- Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - D Monies
- Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - R Shaheen
- Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - F S Alkuraya
- Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia.,Department of Anatomy and Cell Biology, College of Medicine, Alfaisal University, Riyadh, Saudi Arabia
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9
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Simons YB, Sella G. The impact of recent population history on the deleterious mutation load in humans and close evolutionary relatives. Curr Opin Genet Dev 2016; 41:150-158. [PMID: 27744216 DOI: 10.1016/j.gde.2016.09.006] [Citation(s) in RCA: 69] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2016] [Revised: 09/13/2016] [Accepted: 09/18/2016] [Indexed: 01/22/2023]
Abstract
Over the past decade, there has been both great interest and confusion about whether recent demographic events-notably the Out-of-Africa-bottleneck and recent population growth-have led to differences in mutation load among human populations. The confusion can be traced to the use of different summary statistics to measure load, which lead to apparently conflicting results. We argue, however, that when statistics more directly related to load are used, the results of different studies and data sets consistently reveal little or no difference in the load of non-synonymous mutations among human populations. Theory helps to understand why no such differences are seen, as well as to predict in what settings they are to be expected. In particular, as predicted by modeling, there is evidence for changes in the load of recessive loss of function mutations in founder and inbred human populations. Also as predicted, eastern subspecies of gorilla, Neanderthals and Denisovans, who are thought to have undergone reductions in population sizes that exceed the human Out-of-Africa bottleneck in duration and severity, show evidence for increased load of non-synonymous mutations (relative to western subspecies of gorillas and modern humans, respectively). A coherent picture is thus starting to emerge about the effects of demographic history on the mutation load in populations of humans and close evolutionary relatives.
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Affiliation(s)
- Yuval B Simons
- Department of Biological Sciences, Columbia University, New York, NY 10027, USA
| | - Guy Sella
- Department of Biological Sciences, Columbia University, New York, NY 10027, USA.
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