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Asiimwe IG, Blockman M, Cavallari LH, Cohen K, Cupido C, Dandara C, Davis BH, Jacobson B, Johnson JA, Lamorde M, Limdi NA, Morgan J, Mouton JP, Muyambo S, Nakagaayi D, Ndadza A, Okello E, Perera MA, Schapkaitz E, Sekaggya-Wiltshire C, Semakula JR, Tatz G, Waitt C, Yang G, Zhang EJ, Jorgensen AL, Pirmohamed M. Meta-analysis of genome-wide association studies of stable warfarin dose in patients of African ancestry. Blood Adv 2024; 8:5248-5261. [PMID: 39163621 DOI: 10.1182/bloodadvances.2024014227] [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: 07/15/2024] [Revised: 07/31/2024] [Accepted: 07/31/2024] [Indexed: 08/22/2024] Open
Abstract
ABSTRACT Warfarin dose requirements are highly variable because of clinical and genetic factors. Although genetic variants influencing warfarin dose have been identified in European and East Asian populations, more work is needed to identify African-specific genetic variants to help optimize warfarin dosing. We performed genome-wide association studies (GWASs) in 4 African cohorts from Uganda, South Africa, and Zimbabwe, totaling 989 warfarin-treated participants who reached stable dose and had international normalized ratios within therapeutic ranges. We also included 2 African American cohorts recruited by the International Warfarin Pharmacogenetics Consortium (n = 316) and the University of Alabama at Birmingham (n = 199). After the GWAS, we performed standard error-weighted meta-analyses and then conducted stepwise conditional analyses to account for known loci in chromosomes 10 and 16. The genome-wide significance threshold was set at P < 5 × 10-8. The meta-analysis, comprising 1504 participants, identified 242 significant SNPs across 3 genomic loci, with 99.6% of these located within known loci on chromosomes 10 (top SNP: rs58800757, P = 4.27 × 10-13) and 16 (top SNP: rs9925964, P = 9.97 × 10-16). Adjustment for the VKORC1 SNP -1639G>A revealed an additional locus on chromosome 2 (top SNPs rs116057875/rs115254730/rs115240773, P = 3.64 × 10-8), implicating the MALL gene, that could indirectly influence warfarin response through interactions with caveolin-1. In conclusion, we reaffirmed the importance of CYP2C9 and VKORC1 in influencing warfarin dose requirements, and identified a new locus (MALL), that still requires direct evidence of biological plausibility.
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Affiliation(s)
- Innocent G Asiimwe
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, United Kingdom
| | - Marc Blockman
- Division of Clinical Pharmacology, Department of Medicine, University of Cape Town, Cape Town, South Africa
| | - Larisa H Cavallari
- Department of Pharmacotherapy and Translational Research, Center for Pharmacogenomics, University of Florida College of Pharmacy, Gainesville, FL
| | - Karen Cohen
- Division of Clinical Pharmacology, Department of Medicine, University of Cape Town, Cape Town, South Africa
| | - Clint Cupido
- Division of Clinical Pharmacology, Department of Medicine, University of Cape Town, Cape Town, South Africa
- Victoria Hospital Internal Medicine Research Initiative, Victoria Hospital Wynberg, Cape Town, South Africa
| | - Collet Dandara
- Division of Human Genetics, Department of Pathology, Pharmacogenomics and Drug Metabolism Research Group, Institute of Infectious Disease and Molecular Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
| | - Brittney H Davis
- Department of Neurology, The University of Alabama at Birmingham, Birmingham, AL
| | - Barry Jacobson
- Department of Molecular Medicine and Haematology, University of the Witwatersrand, Johannesburg, South Africa
| | - Julie A Johnson
- Division of Pharmaceutics and Pharmacology, Center for Clinical and Translational Science, College of Medicine, The Ohio State University, Columbus, OH
| | - Mohammed Lamorde
- Infectious Diseases Institute, College of Health Sciences, Makerere University, Kampala, Uganda
| | - Nita A Limdi
- Department of Neurology, The University of Alabama at Birmingham, Birmingham, AL
| | - Jennie Morgan
- Metro Health Services, Western Cape Department of Health and Wellness, Cape Town, South Africa
- Division of Family Medicine, Department of Family, Community and Emergency Care, University of Cape Town, Cape Town, South Africa
| | - Johannes P Mouton
- Division of Clinical Pharmacology, Department of Medicine, University of Cape Town, Cape Town, South Africa
| | - Sarudzai Muyambo
- Department of Biological Sciences and Ecology, Faculty of Science, University of Zimbabwe, Harare, Zimbabwe
| | - Doreen Nakagaayi
- Department of Adult Cardiology, Uganda Heart Institute, Kampala, Uganda
| | - Arinao Ndadza
- Division of Human Genetics, Department of Pathology, Pharmacogenomics and Drug Metabolism Research Group, Institute of Infectious Disease and Molecular Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
| | - Emmy Okello
- Department of Adult Cardiology, Uganda Heart Institute, Kampala, Uganda
| | - Minoli A Perera
- Department of Pharmacology, Center for Pharmacogenomics, Northwestern University, Chicago, IL
| | - Elise Schapkaitz
- Department of Molecular Medicine and Hematology, Charlotte Maxeke Johannesburg Academic Hospital National Health Laboratory System Complex and University of Witwatersrand, Johannesburg, South Africa
| | | | - Jerome R Semakula
- Infectious Diseases Institute, College of Health Sciences, Makerere University, Kampala, Uganda
| | - Gayle Tatz
- Division of Clinical Pharmacology, Department of Medicine, University of Cape Town, Cape Town, South Africa
| | - Catriona Waitt
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, United Kingdom
- Infectious Diseases Institute, College of Health Sciences, Makerere University, Kampala, Uganda
| | - Guang Yang
- Department of Pharmacology, Center for Pharmacogenomics, Northwestern University, Chicago, IL
- Genetics Group, Center for Applied Bioinfomatics, St. Jude Children's Research Hospital, Memphis, TN
| | - Eunice J Zhang
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, United Kingdom
| | - Andrea L Jorgensen
- Department of Health Data Science, Institute of Population Health Sciences, University of Liverpool, Liverpool, United Kingdom
| | - Munir Pirmohamed
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, United Kingdom
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Gautam Y, Satish L, Ramirez S, Grashel B, Biagini JM, Martin LJ, Rothenberg ME, Khurana Hershey GK, Mersha TB. Joint genotype and ancestry analysis identify novel loci associated with atopic dermatitis in African American population. HGG ADVANCES 2024; 5:100350. [PMID: 39245941 PMCID: PMC11470243 DOI: 10.1016/j.xhgg.2024.100350] [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: 10/17/2023] [Revised: 09/02/2024] [Accepted: 09/03/2024] [Indexed: 09/10/2024] Open
Abstract
Atopic dermatitis (AD) is a chronic itchy inflammatory disease of the skin. Genetic studies have identified multiple risk factors linked to the disease; however, most of the studies have been derived from European and East Asian populations. The admixed African American (AA) genome may provide an opportunity to discovery ancestry-specific loci involved in AD susceptibility. Herein, we present joint analysis of ancestry and genotype effects followed by validation using differential gene expression analysis on AD using 726 AD-affected individuals and 999 non-AD control individuals from the AA population, genotyped using Multi-Ethnic Global Array (MEGA) followed by imputation using the Consortium on Asthma among African Ancestry Populations in the Americas (CAAPA) reference panel. The joint analysis identified two novel AD-susceptibility loci, rs2195989 in gene ANGPT1 (8q23.1) and rs62538818 in the intergenic region between genes LURAP1L and MPDZ (9p23). Admixture mapping (AM) results showed potential genomic inflation, and we implemented genomic control and identified five ancestry-of-origin loci with European ancestry effects. The multi-omics functional prioritization of variants in AM signals prioritized the loci SLAIN2, RNF39, and FOXA2. Genome-wide association study (GWAS) identified variants significantly associated with AD in the AA population, including SGK1 (rs113357522, odds ratio [OR] = 2.81), EFR3A (rs16904552, OR = 1.725), and MMP14 (rs911912, OR = 1.791). GWAS variants were common in the AA but rare in the European population, which suggests an African-ancestry-specific risk of AD. Four genes (ANGPT1, LURAP1L, EFR3A, and SGK1) were further validated using qPCR from AD and healthy skin. This study highlighted the importance of genetic studies on admixed populations, as well as local ancestry and genotype-ancestry joint effects to identify risk loci for AD.
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Affiliation(s)
- Yadu Gautam
- Division of Asthma Research, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati, Cincinnati, OH, USA
| | - Latha Satish
- Division of Asthma Research, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati, Cincinnati, OH, USA
| | - Stephen Ramirez
- Division of Asthma Research, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati, Cincinnati, OH, USA
| | - Brittany Grashel
- Division of Asthma Research, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati, Cincinnati, OH, USA
| | - Jocelyn M Biagini
- Division of Asthma Research, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati, Cincinnati, OH, USA
| | - Lisa J Martin
- Division of Human Genetics, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati, Cincinnati, OH, USA
| | - Marc E Rothenberg
- Division of Allergy and Immunology, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati, Cincinnati, OH, USA
| | - Gurjit K Khurana Hershey
- Division of Asthma Research, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati, Cincinnati, OH, USA
| | - Tesfaye B Mersha
- Division of Asthma Research, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati, Cincinnati, OH, USA.
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3
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Liang M, Shishkin M, Shchur V, Nielsen R. Understanding admixture fractions: theory and estimation of gene-flow. J Math Biol 2024; 89:47. [PMID: 39363040 DOI: 10.1007/s00285-024-02146-0] [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: 12/09/2023] [Revised: 08/21/2024] [Accepted: 09/17/2024] [Indexed: 10/05/2024]
Abstract
Estimation of admixture proportions has become one of the most commonly used computational tools in population genomics. However, there is remarkably little population genetic theory on statistical properties of these variables. We develop theoretical results that can accurately predict means and variances of admixture proportions within a population using models with recombination and genetic drift. Based on established theory on measures of multilocus disequilibrium, we show that there is a set of recurrence relations that can be used to derive expectations for higher moments of the admixture proportions distribution. We obtain closed form solutions for some special cases. Using these results, we develop a method for estimating admixture parameters from estimated admixture proportions obtained from programs such as Structure or Admixture. We apply this method to HapMap 3 data and find that the population history of African Americans, as expected, is not best explained by a single admixture event between people of European and African ancestry. The model of constant gene flow starting at 8 generations and ending at 2 generations before present gives the best fit.
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Affiliation(s)
- Mason Liang
- Department of Integrative Biology, University of California, Valley Life Sciences Building, Berkeley, CA, 94720, USA
- Department of Statistics, University of California, Evans Hall, Berkeley, CA, 94720, USA
| | - Mikhail Shishkin
- International laboratory of statistical and computational genomics, Faculty of computer science, HSE University, Pokrovskiy Boulevard, 11, Moscow, Russian Federation, 109028
| | - Vladimir Shchur
- International laboratory of statistical and computational genomics, Faculty of computer science, HSE University, Pokrovskiy Boulevard, 11, Moscow, Russian Federation, 109028.
| | - Rasmus Nielsen
- Department of Integrative Biology, University of California, Valley Life Sciences Building, Berkeley, CA, 94720, USA.
- Department of Statistics, University of California, Evans Hall, Berkeley, CA, 94720, USA.
- Globe Institute, University of Copenhagen, Oester Voldgade 5-7, 1350, Copenhagen K, Denmark.
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4
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Ibañez K, Jadhav B, Zanovello M, Gagliardi D, Clarkson C, Facchini S, Garg P, Martin-Trujillo A, Gies SJ, Galassi Deforie V, Dalmia A, Hensman Moss DJ, Vandrovcova J, Rocca C, Moutsianas L, Marini-Bettolo C, Walker H, Turner C, Shoai M, Long JD, Fratta P, Langbehn DR, Tabrizi SJ, Caulfield MJ, Cortese A, Escott-Price V, Hardy J, Houlden H, Sharp AJ, Tucci A. Increased frequency of repeat expansion mutations across different populations. Nat Med 2024:10.1038/s41591-024-03190-5. [PMID: 39354197 DOI: 10.1038/s41591-024-03190-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Accepted: 07/11/2024] [Indexed: 10/03/2024]
Abstract
Repeat expansion disorders (REDs) are a devastating group of predominantly neurological diseases. Together they are common, affecting 1 in 3,000 people worldwide with population-specific differences. However, prevalence estimates of REDs are hampered by heterogeneous clinical presentation, variable geographic distributions and technological limitations leading to underascertainment. Here, leveraging whole-genome sequencing data from 82,176 individuals from different populations, we found an overall disease allele frequency of REDs of 1 in 283 individuals. Modeling disease prevalence using genetic data, age at onset and survival, we show that the expected number of people with REDs would be two to three times higher than currently reported figures, indicating underdiagnosis and/or incomplete penetrance. While some REDs are population specific, for example, Huntington disease-like 2 in Africans, most REDs are represented in all broad genetic ancestries (that is, Europeans, Africans, Americans, East Asians and South Asians), challenging the notion that some REDs are found only in specific populations. These results have worldwide implications for local and global health communities in the diagnosis and counseling of REDs.
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Affiliation(s)
- Kristina Ibañez
- William Harvey Research Institute, Queen Mary University of London, London, UK
| | - Bharati Jadhav
- Department of Genetics and Genomic Sciences and Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Matteo Zanovello
- Department of Neuromuscular Diseases, Institute of Neurology, UCL, London, UK
| | - Delia Gagliardi
- William Harvey Research Institute, Queen Mary University of London, London, UK
- Department of Neuromuscular Diseases, Institute of Neurology, UCL, London, UK
| | | | - Stefano Facchini
- Department of Neuromuscular Diseases, Institute of Neurology, UCL, London, UK
- IRCCS Mondino Foundation, Pavia, Italy
| | - Paras Garg
- Department of Genetics and Genomic Sciences and Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Alejandro Martin-Trujillo
- Department of Genetics and Genomic Sciences and Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Scott J Gies
- Department of Genetics and Genomic Sciences and Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | | | - Davina J Hensman Moss
- St George's, University of London, London, UK
- Department of Neurodegenerative Disorders, Queen Square Institute of Neurology, UCL, London, UK
| | - Jana Vandrovcova
- Department of Neuromuscular Diseases, Institute of Neurology, UCL, London, UK
| | - Clarissa Rocca
- Department of Neuromuscular Diseases, Institute of Neurology, UCL, London, UK
| | | | - Chiara Marini-Bettolo
- The John Walton Muscular Dystrophy Research Centre, Translational and Clinical Research Institute, Newcastle University and Newcastle Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
| | - Helen Walker
- The John Walton Muscular Dystrophy Research Centre, Translational and Clinical Research Institute, Newcastle University and Newcastle Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
| | - Chris Turner
- Centre for Neuromuscular Disease, Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology and National Hospital for Neurology and Neurosurgery, London, UK
| | - Maryam Shoai
- Department of Neurodegenerative Disorders, Queen Square Institute of Neurology, UCL, London, UK
| | - Jeffrey D Long
- Departments of Psychiatry and Biostatistics, The University of Iowa, Iowa City, IA, USA
| | - Pietro Fratta
- Department of Neuromuscular Diseases, Institute of Neurology, UCL, London, UK
| | - Douglas R Langbehn
- Departments of Psychiatry and Biostatistics, The University of Iowa, Iowa City, IA, USA
| | - Sarah J Tabrizi
- UK Dementia Research Institute, UCL, London, UK
- Department of Neurodegenerative Disorders, Queen Square Institute of Neurology, UCL, London, UK
- Huntington's Disease Centre, UCL, London, UK
| | - Mark J Caulfield
- William Harvey Research Institute, Queen Mary University of London, London, UK
| | - Andrea Cortese
- Department of Neuromuscular Diseases, Institute of Neurology, UCL, London, UK
- IRCCS Mondino Foundation, Pavia, Italy
| | - Valentina Escott-Price
- Department of Psychological Medicine and Clinical Neuroscience, School of Medicine, Cardiff University, Cardiff, UK
- Dementia Research Institute, Cardiff University, Cardiff, UK
| | - John Hardy
- Department of Neurodegenerative Disorders, Queen Square Institute of Neurology, UCL, London, UK
| | - Henry Houlden
- Department of Neurodegenerative Disorders, Queen Square Institute of Neurology, UCL, London, UK
- Neurogenetics Unit, National Hospital for Neurology and Neurosurgery, London, UK
| | - Andrew J Sharp
- Department of Genetics and Genomic Sciences and Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Arianna Tucci
- William Harvey Research Institute, Queen Mary University of London, London, UK.
- Department of Neuromuscular Diseases, Institute of Neurology, UCL, London, UK.
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Isshiki M, Griffen A, Meissner P, Spencer P, Cabana MD, Klugman SD, Colón M, Maksumova Z, Suglia S, Isasi C, Greally JM, Raj SM. Genetic disease risks of under-represented founder populations in New York City. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.09.27.24314513. [PMID: 39399040 PMCID: PMC11469344 DOI: 10.1101/2024.09.27.24314513] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 10/15/2024]
Abstract
The detection of founder pathogenic variants, those observed in high frequency only in a group of individuals with increased inter-relatedness, can help improve delivery of health care for that community. We identified 16 groups with shared ancestry, based on genomic segments that are shared through identity by descent (IBD), in New York City using the genomic data of 25,366 residents from the All Of Us Research Program and the Mount Sinai Bio Me biobank. From these groups we defined 8 as founder populations, mostly communities currently under-represented in medical genomics research, such as Puerto Rican, Garifuna and Filipino/Pacific Islanders. The enrichment analysis of ClinVar pathogenic or likely pathogenic (P/LP) variants in each group identified 202 of these damaging variants across the 8 founder populations. We confirmed disease-causing variants previously reported to occur at increased frequencies in Ashkenazi Jewish and Puerto Rican genetic ancestry groups, but most of the damaging variants identified have not been previously associated with any such founder populations, and most of these founder populations have not been described to have increased prevalence of the associated rare disease. Twenty-five of 51 variants meeting Tier 2 clinical screening criteria (1/100 carrier frequency within these founder groups) have never previously been reported. We show how population structure studies can provide insights into rare diseases disproportionately affecting under-represented founder populations, delivering a health care benefit but also a potential source of stigmatization of these communities, who should be part of the decision-making about implementation into health care delivery. Author Summary It is well recognized that genomic studies have been biased towards individuals of European ancestry, and that obtaining medical insights for populations under-represented in medical genomics is crucial to achieve health equity. Here, we use genomic information to identify networks of individuals in New York City who are distinctively related to each other, allowing us to define populations with common genetic ancestry based on genetic similarities rather than by self-reported race or ethnicity. In our study of >25,000 New Yorkers, we identified eight highly-interrelated founder populations, with 202 likely disease-causing variants with increased frequencies in specific founder populations. Many of these population-specific variants are new discoveries, despite their high frequency in founder populations. Studying recent genetic ancestry can help reveal population-specific disease insights that can help with early diagnosis, carrier screening, and opportunities for targeted therapies that all help to reduce health disparities in genomic medicine.
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Wei Y, Zhi D, Zhang S. Fast and accurate local ancestry inference with Recomb-Mix. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.11.17.567650. [PMID: 38014185 PMCID: PMC10680832 DOI: 10.1101/2023.11.17.567650] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
The availability of large genotyped cohorts brings new opportunities for revealing the high-resolution genetic structure of admixed populations via local ancestry inference (LAI), the process of identifying the ancestry of each segment of an individual haplotype. Though current methods achieve high accuracy in standard cases, LAI is still challenging when reference populations are more similar (e.g., intra-continental), when the number of reference populations is too numerous, or when the admixture events are deep in time, all of which are increasingly unavoidable in large biobanks. Here, we present a new LAI method, Recomb-Mix. Recomb-Mix integrates the elements of existing methods of the site-based Li and Stephens model and introduces a new graph collapsing trick to simplify counting paths with the same ancestry label readout. Through comprehensive benchmarking on various simulated datasets, we show that Recomb-Mix is more accurate than existing methods in diverse sets of scenarios while being competitive in terms of resource efficiency. We expect that Recomb-Mix will be a useful method for advancing genetics studies of admixed populations.
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Affiliation(s)
- Yuan Wei
- Department of Computer Science, University of Central Florida, Orlando, FL, USA
| | - Degui Zhi
- McWilliams School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Shaojie Zhang
- Department of Computer Science, University of Central Florida, Orlando, FL, USA
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7
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Vicuña L, Barrientos E, Leiva-Yamaguchi V, Alvares D, Mericq V, Pereira A, Eyheramendy S. Joint models reveal genetic architecture of pubertal stage transitions and their association with BMI in admixed Chilean population. Hum Mol Genet 2024; 33:1660-1670. [PMID: 38981621 DOI: 10.1093/hmg/ddae098] [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: 11/28/2023] [Revised: 05/01/2024] [Accepted: 06/04/2024] [Indexed: 07/11/2024] Open
Abstract
Early or late pubertal onset can lead to disease in adulthood, including cancer, obesity, type 2 diabetes, metabolic disorders, bone fractures, and psychopathologies. Thus, knowing the age at which puberty is attained is crucial as it can serve as a risk factor for future diseases. Pubertal development is divided into five stages of sexual maturation in boys and girls according to the standardized Tanner scale. We performed genome-wide association studies (GWAS) on the "Growth and Obesity Chilean Cohort Study" cohort composed of admixed children with mainly European and Native American ancestry. Using joint models that integrate time-to-event data with longitudinal trajectories of body mass index (BMI), we identified genetic variants associated with phenotypic transitions between pairs of Tanner stages. We identified $42$ novel significant associations, most of them in boys. The GWAS on Tanner $3\rightarrow 4$ transition in boys captured an association peak around the growth-related genes LARS2 and LIMD1 genes, the former of which causes ovarian dysfunction when mutated. The associated variants are expression and splicing Quantitative Trait Loci regulating gene expression and alternative splicing in multiple tissues. Further, higher individual Native American genetic ancestry proportions predicted a significantly earlier puberty onset in boys but not in girls. Finally, the joint models identified a longitudinal BMI parameter significantly associated with several Tanner stages' transitions, confirming the association of BMI with pubertal timing.
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Affiliation(s)
- Lucas Vicuña
- Department of Medicine, Genetics Section, University of Chicago, Chicago, IL 60637, United States
| | - Esteban Barrientos
- Faculty of Engineering and Sciences, Universidad Adolfo Ibáñez, Santiago, Chile
| | | | - Danilo Alvares
- MRC Biostatistics Unit, University of Cambridge, Cambridge CB2 0SR, UK
| | - Veronica Mericq
- Institute of Maternal and Child Research, Faculty of Medicine, University of Chile, Santiago, Chile
| | - Anita Pereira
- Institute of Nutrition and Food Technology, University of Chile, Santiago, Chile
| | - Susana Eyheramendy
- Faculty of Engineering and Sciences, Universidad Adolfo Ibáñez, Santiago, Chile
- Data Observatory Foundation, ANID Technology Center No. DO210001, Chile
- Instituto Milenio Fundamentos de los Datos, Chile
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8
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Boltz TA, Chu BB, Liao C, Sealock JM, Ye R, Majara L, Fu JM, Service S, Zhan L, Medland SE, Chapman SB, Rubinacci S, DeFelice M, Grimsby JL, Abebe T, Alemayehu M, Ashaba FK, Atkinson EG, Bigdeli T, Bradway AB, Brand H, Chibnik LB, Fekadu A, Gatzen M, Gelaye B, Gichuru S, Gildea ML, Hill TC, Huang H, Hubbard KM, Injera WE, James R, Joloba M, Kachulis C, Kalmbach PR, Kamulegeya R, Kigen G, Kim S, Koen N, Kwobah EK, Kyebuzibwa J, Lee S, Lennon NJ, Lind PA, Lopera-Maya EA, Makale J, Mangul S, McMahon J, Mowlem P, Musinguzi H, Mwema RM, Nakasujja N, Newman CP, Nkambule LL, O'Neil CR, Olivares AM, Olsen CM, Ongeri L, Parsa SJ, Pretorius A, Ramesar R, Reagan FL, Sabatti C, Schneider JA, Shiferaw W, Stevenson A, Stricker E, Stroud RE, Tang J, Whiteman D, Yohannes MT, Yu M, Yuan K, Akena D, Atwoli L, Kariuki SM, Koenen KC, Newton CRJC, Stein DJ, Teferra S, Zingela Z, Pato CN, Pato MT, Lopez-Jaramillo C, Freimer N, Ophoff RA, Olde Loohuis LM, Talkowski ME, Neale BM, Howrigan DP, Martin AR. A blended genome and exome sequencing method captures genetic variation in an unbiased, high-quality, and cost-effective manner. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.09.06.611689. [PMID: 39282356 PMCID: PMC11398523 DOI: 10.1101/2024.09.06.611689] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 09/21/2024]
Abstract
We deployed the Blended Genome Exome (BGE), a DNA library blending approach that generates low pass whole genome (1-4× mean depth) and deep whole exome (30-40× mean depth) data in a single sequencing run. This technology is cost-effective, empowers most genomic discoveries possible with deep whole genome sequencing, and provides an unbiased method to capture the diversity of common SNP variation across the globe. To evaluate this new technology at scale, we applied BGE to sequence >53,000 samples from the Populations Underrepresented in Mental Illness Associations Studies (PUMAS) Project, which included participants across African, African American, and Latin American populations. We evaluated the accuracy of BGE imputed genotypes against raw genotype calls from the Illumina Global Screening Array. All PUMAS cohorts hadR 2 concordance ≥95% among SNPs with MAF≥1%, and never fell below ≥90%R 2 for SNPs with MAF<1%. Furthermore, concordance rates among local ancestries within two recently admixed cohorts were consistent among SNPs with MAF≥1%, with only minor deviations in SNPs with MAF<1%. We also benchmarked the discovery capacity of BGE to access protein-coding copy number variants (CNVs) against deep whole genome data, finding that deletions and duplications spanning at least 3 exons had a positive predicted value of ~90%. Our results demonstrate BGE scalability and efficacy in capturing SNPs, indels, and CNVs in the human genome at 28% of the cost of deep whole-genome sequencing. BGE is poised to enhance access to genomic testing and empower genomic discoveries, particularly in underrepresented populations.
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Affiliation(s)
- Toni A Boltz
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Benjamin B Chu
- Department of Psychiatry, School of Medicine, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia
| | - Calwing Liao
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Julia M Sealock
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Robert Ye
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Lerato Majara
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Psychiatry and Mental Health and South African Medical Council Research Unit on Risk and Resilience in Mental Disorders, Neuroscience Institute, University of Cape Town and Groote Schuur Hospital, Cape Town, South Africa
| | - Jack M Fu
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Susan Service
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA, USA
| | - Lingyu Zhan
- Department of Psychiatry, Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA, USA
- The Collaboratory, Institute for Quantitative and Computational Biosciences, University of California Los Angeles, Los Angeles, CA, USA
| | - Sarah E Medland
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Sinéad B Chapman
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- BD2: Breakthrough Discoveries for thriving with Bipolar Disorder, Santa Monica, CA, USA
| | - Simone Rubinacci
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School,, Boston, MA, USA
- Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School,, Boston, MA, USA
| | - Matthew DeFelice
- Broad Clinical Labs (BCL), Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jonna L Grimsby
- Broad Clinical Labs (BCL), Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Tamrat Abebe
- Department of Microbiology, Immunology, and Parasitology, School of Medicine, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia
| | - Melkam Alemayehu
- Department of Psychiatry, School of Medicine, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia
| | - Fred K Ashaba
- Department of Immunology & Molecular Biology, College of Health Sciences, Makerere University, Kampala, Uganda
| | - Elizabeth G Atkinson
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
- Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, TX, USA
| | - Tim Bigdeli
- Institute for Genomics in Health, The State University of New York, Brooklyn, NY, USA
| | - Amanda B Bradway
- Broad Clinical Labs (BCL), Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Harrison Brand
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Lori B Chibnik
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Abebaw Fekadu
- Department of Psychiatry, School of Medicine, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia
- Centre for Innovative Drug Development & Therapeutic Trials for Africa, Addis Ababa University, Addis Ababa, Ethiopia
| | - Michael Gatzen
- Broad Clinical Labs (BCL), Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Bizu Gelaye
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School and The Chester M. Pierce MD, Division of Global Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Stella Gichuru
- Department of Mental Health, Moi Teaching and Referral Hospital, Eldoret, Kenya
| | - Marissa L Gildea
- Broad Clinical Labs (BCL), Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Toni C Hill
- Broad Clinical Labs (BCL), Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Hailiang Huang
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- BD2: Breakthrough Discoveries for thriving with Bipolar Disorder, Santa Monica, CA, USA
| | - Kalyn M Hubbard
- Broad Clinical Labs (BCL), Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Wilfred E Injera
- Department of Medical Laboratory Sciences, School of Health Sciences, Alupe University, Busia, Kenya
| | - Roxanne James
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - Moses Joloba
- School of Biomedical Sciences, School of Medicine, College of Health Sciences, Makerere University, Kampala, Uganda
| | - Christopher Kachulis
- Broad Clinical Labs (BCL), Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Phillip R Kalmbach
- Broad Clinical Labs (BCL), Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Rogers Kamulegeya
- School of Biomedical Sciences, School of Medicine, College of Health Sciences, Makerere University, Kampala, Uganda
| | - Gabriel Kigen
- Department of Pharmacology and Toxicology, Moi University School of Medicine, Eldoret, Kenya
| | - Soyeon Kim
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Nastassja Koen
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
- SA MRC Unit on Risk & Resilience in Mental Disorders, University of Cape Town and Neuroscience Institute, Cape Town, South Africa
| | - Edith K Kwobah
- Department of Mental Health, Moi Teaching and Referral Hospital, Eldoret, Kenya
| | - Joseph Kyebuzibwa
- Department of Psychiatry, School of Medicine, College of Health Sciences, Makerere University, Kampala, Uganda
| | - Seungmo Lee
- Department of Computer Science, University of California Los Angeles, Los Angeles, CA, USA
| | - Niall J Lennon
- Broad Clinical Labs (BCL), Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Penelope A Lind
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Esteban A Lopera-Maya
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Johnstone Makale
- Epidemiology and Demography Department, KEMRI-Wellcome Trust Research Programme-Coast, Kilifi, Kenya
| | - Serghei Mangul
- Department of Quantitative and Computational Biology, Dana and David Dornsife College of Letters, Arts and Sciences, University of Southern California, Los Angeles, CA, USA
- Department of Clinical Pharmacy, Alfred E. Mann School of Pharmacy, University of Southern California, Los Angeles, CA, USA
| | - Justin McMahon
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Pierre Mowlem
- Ampath Laboratories, Moi University School of Medicine, Eldoret, Kenya
| | - Henry Musinguzi
- Department of Immunology & Molecular Biology, College of Health Sciences, Makerere University, Kampala, Uganda
| | - Rehema M Mwema
- Neurosciences Unit, Clinical Department, KEMRI-Wellcome Trust Research Programme-Coast,, Kilifi, Kenya
| | - Noeline Nakasujja
- Department of Psychiatry, School of Medicine, College of Health Sciences, Makerere University, Kampala, Uganda
| | - Carter P Newman
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Lethukuthula L Nkambule
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Conor R O'Neil
- Broad Clinical Labs (BCL), Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Ana Maria Olivares
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | - Linnet Ongeri
- Centre for Clinical Research, Kenya Medical Research Institute, Nairobi, Kenya
| | - Sophie J Parsa
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Adele Pretorius
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - Raj Ramesar
- SA MRC Unit on Risk & Resilience in Mental Disorders, University of Cape Town and Neuroscience Institute, Cape Town, South Africa
| | - Faye L Reagan
- Broad Clinical Labs (BCL), Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Chiara Sabatti
- Department of Biomedical Data Sciences, Stanford University, Stanford, CA, USA
| | | | - Welelta Shiferaw
- Department of Psychiatry, School of Medicine, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia
| | - Anne Stevenson
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Erik Stricker
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Rocky E Stroud
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Jessie Tang
- Broad Clinical Labs (BCL), Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - David Whiteman
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Mary T Yohannes
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Mingrui Yu
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Kai Yuan
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Dickens Akena
- Department of Psychiatry, School of Medicine, College of Health Sciences, Makerere University, Kampala, Uganda
| | - Lukoye Atwoli
- Department of Mental Health and Behavioural Sciences, School of Medicine, Moi University College of Health Sciences, Eldoret, Kenya
- Brain and Mind Institute, The Aga Khan University, Nairobi, Kenya
- Department of Medicine, Medical College East Africa, The Aga Khan University, Nairobi, Kenya
| | - Symon M Kariuki
- Neurosciences Unit, Clinical Department, KEMRI-Wellcome Trust Research Programme-Coast, Kilifi, Kenya
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Karestan C Koenen
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
- Department of Social and Behavioral Sciences, Harvard T. H. Chan School of Public Health, Boston, MA, USA
- Psychiatric & Neurodevelopmental Genetics Unit, Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Charles R J C Newton
- Neurosciences Unit, Clinical Department, KEMRI-Wellcome Trust Research Programme-Coast,, Kilifi, Kenya
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Dan J Stein
- SA MRC Unit on Risk & Resilience in Mental Disorders, University of Cape Town and Neuroscience Institute, Cape Town, South Africa
| | - Solomon Teferra
- Department of Psychiatry, School of Medicine, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia
| | - Zukiswa Zingela
- Executive Dean's Office, Faculty of Health Sciences, Nelson Mandela University, Gqebera, South Africa
| | - Carlos N Pato
- Rutgers University, New Brunswick, NJ, USA
- BD2: Breakthrough Discoveries for thriving with Bipolar Disorder, Santa Monica, CA, USA
| | - Michele T Pato
- Rutgers University, New Brunswick, NJ, USA
- BD2: Breakthrough Discoveries for thriving with Bipolar Disorder, Santa Monica, CA, USA
| | - Carlos Lopez-Jaramillo
- Department of Psychiatry, University of Antioquia, University of Antioquia, Medellín, Antioquia, Colombia
| | - Nelson Freimer
- BD2: Breakthrough Discoveries for thriving with Bipolar Disorder, Santa Monica, CA, USA
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Roel A Ophoff
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Loes M Olde Loohuis
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Department of Computational Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Michael E Talkowski
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Benjamin M Neale
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- BD2: Breakthrough Discoveries for thriving with Bipolar Disorder, Santa Monica, CA, USA
| | - Daniel P Howrigan
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Alicia R Martin
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- BD2: Breakthrough Discoveries for thriving with Bipolar Disorder, Santa Monica, CA, USA
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9
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Wen J, Sun Q, Huang L, Zhou L, Doyle MF, Ekunwe L, Durda P, Olson NC, Reiner AP, Li Y, Raffield LM. Gene expression and splicing QTL analysis of blood cells in African American participants from the Jackson Heart Study. Genetics 2024; 228:iyae098. [PMID: 39056362 PMCID: PMC11373511 DOI: 10.1093/genetics/iyae098] [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: 05/07/2024] [Accepted: 06/05/2024] [Indexed: 07/28/2024] Open
Abstract
Most gene expression and alternative splicing quantitative trait loci (eQTL/sQTL) studies have been biased toward European ancestry individuals. Here, we performed eQTL and sQTL analyses using TOPMed whole-genome sequencing-derived genotype data and RNA-sequencing data from stored peripheral blood mononuclear cells in 1,012 African American participants from the Jackson Heart Study (JHS). At a false discovery rate of 5%, we identified 17,630 unique eQTL credible sets covering 16,538 unique genes; and 24,525 unique sQTL credible sets covering 9,605 unique genes, with lead QTL at P < 5e-8. About 24% of independent eQTLs and independent sQTLs with a minor allele frequency > 1% in JHS were rare (minor allele frequency < 0.1%), and therefore unlikely to be detected, in European ancestry individuals. Finally, we created an open database, which is freely available online, allowing fast query and bulk download of our QTL results.
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Affiliation(s)
- Jia Wen
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA
| | - Quan Sun
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Le Huang
- Curriculum in Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Lingbo Zhou
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Margaret F Doyle
- Department of Pathology and Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington, VT 05405, USA
| | - Lynette Ekunwe
- Department of Medicine, University of MS Medical Center (UMMC), Jackson, MS 39213, USA
| | - Peter Durda
- Department of Pathology and Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington, VT 05405, USA
| | - Nels C Olson
- Department of Pathology and Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington, VT 05405, USA
| | - Alexander P Reiner
- Department of Epidemiology, University of Washington, Seattle, WA 98195, USA
- Division of Public Health Sciences, Fred Hutchinson Cancer Research, Seattle, WA 98109, USA
| | - Yun Li
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Laura M Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA
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10
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Borges VM, Horimoto ARVR, Wijsman EM, Kimura L, Nunes K, Nato AQ, Mingroni-Netto RC. Genomic Exploration of Essential Hypertension in African-Brazilian Quilombo Populations: A Comprehensive Approach with Pedigree Analysis and Family-Based Association Studies. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.06.26.24309531. [PMID: 38978678 PMCID: PMC11230341 DOI: 10.1101/2024.06.26.24309531] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/10/2024]
Abstract
Background Essential Hypertension (EH) is a global health issue, responsible for approximately 9.4 million deaths annually. Its prevalence varies by region, with genetic factors contributing 30-60% to blood pressure variation. Despite extensive research, the genetic complexity of EH remains largely unexplained. This study aimed to investigate the genetic basis of EH in African-derived individuals from partially isolated quilombo remnant populations in Vale do Ribeira (SP-Brazil). Methods Samples from 431 individuals (167 affected, 261 unaffected, 3 with unknown phenotype) were genotyped using a 650k SNP array. Global ancestry proportions were estimated at 47% African, 36% European, and 16% Native American. Additional data from 673 individuals were used to construct six pedigrees. Pedigrees were pruned, and three non-overlapping marker subpanels were created. We phased haplotypes and performed local ancestry analysis to account for admixture. We then conducted genome-wide linkage analysis (GWLA) and performed fine-mapping through family-based association studies (FBAS) on imputed data and through EH-related genes investigation. Results Linkage analysis identified 22 ROIs with LOD scores ranging from 1.45 to 3.03, encompassing 2363 genes. Fine-mapping identified 60 EH-related candidate genes and 118 suggestive or significant variants (FBAS). Among these, 14 genes, including PHGDH, S100A10, MFN2, and RYR2, were strongly associated with hypertension and harbors 29 SNPs. Conclusions Through a complementary approach - combining admixture-adjusted genome-wide linkage analysis based on Markov chain Monte Carlo (MCMC) methods, association studies on imputed data, and in silico investigations - genetic regions, variants, and candidate genes were identified, offering insights into the genetic etiology of EH in quilombo remnant populations.
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Affiliation(s)
- Vinícius Magalhães Borges
- Centro de Estudos sobre o Genoma Humano e Células Tronco, Departamento de Genética e Biologia Evolutiva, Instituto de Biociências, Universidade de São Paulo, São Paulo 05508-090, Brazil
- Department of Biomedical Sciences, Joan C. Edwards School of Medicine, Marshall University, Huntington, WV 25755, USA
| | - Andrea R V R Horimoto
- Division of Medical Genetics, Department of Medicine, University of Washington, Seattle, WA, 98105 USA
| | - Ellen Marie Wijsman
- Division of Medical Genetics, Department of Medicine, University of Washington, Seattle, WA, 98105 USA
| | - Lilian Kimura
- Centro de Estudos sobre o Genoma Humano e Células Tronco, Departamento de Genética e Biologia Evolutiva, Instituto de Biociências, Universidade de São Paulo, São Paulo 05508-090, Brazil
| | - Kelly Nunes
- Centro de Estudos sobre o Genoma Humano e Células Tronco, Departamento de Genética e Biologia Evolutiva, Instituto de Biociências, Universidade de São Paulo, São Paulo 05508-090, Brazil
| | - Alejandro Q Nato
- Department of Biomedical Sciences, Joan C. Edwards School of Medicine, Marshall University, Huntington, WV 25755, USA
| | - Regina Célia Mingroni-Netto
- Centro de Estudos sobre o Genoma Humano e Células Tronco, Departamento de Genética e Biologia Evolutiva, Instituto de Biociências, Universidade de São Paulo, São Paulo 05508-090, Brazil
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11
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Akgun B, Feliciano-Astacio BE, Hamilton-Nelson KL, Scott K, Rivero J, Adams LD, Sanchez JJ, Valladares GS, Tejada S, Bussies PL, Silva-Vergara C, Rodriguez VC, Mena PR, Celis K, Whitehead PG, Prough M, Kosanovic C, Van Booven DJ, Schmidt MA, Acosta H, Griswold AJ, Dalgard CL, McInerney KF, Beecham GW, Cuccaro ML, Vance JM, Pericak-Vance MA, Rajabli F. Genome-wide association analysis and admixture mapping in a Puerto Rican cohort supports an Alzheimer disease risk locus on chromosome 12. Front Aging Neurosci 2024; 16:1459796. [PMID: 39295643 PMCID: PMC11408238 DOI: 10.3389/fnagi.2024.1459796] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2024] [Accepted: 08/26/2024] [Indexed: 09/21/2024] Open
Abstract
Introduction Hispanic/Latino populations are underrepresented in Alzheimer Disease (AD) genetic studies. Puerto Ricans (PR), a three-way admixed (European, African, and Amerindian) population is the second-largest Hispanic group in the continental US. We aimed to conduct a genome-wide association study (GWAS) and comprehensive analyses to identify novel AD susceptibility loci and characterize known AD genetic risk loci in the PR population. Materials and methods Our study included Whole Genome Sequencing (WGS) and phenotype data from 648 PR individuals (345 AD, 303 cognitively unimpaired). We used a generalized linear-mixed model adjusting for sex, age, population substructure, and genetic relationship matrix. To infer local ancestry, we merged the dataset with the HGDP/1000G reference panel. Subsequently, we conducted univariate admixture mapping (AM) analysis. Results We identified suggestive signals within the SLC38A1 and SCN8A genes on chromosome 12q13. This region overlaps with an area of linkage of AD in previous studies (12q13) in independent data sets further supporting. Univariate African AM analysis identified one suggestive ancestral block (p = 7.2×10-6) located in the same region. The ancestry-aware approach showed that this region has both European and African ancestral backgrounds and both contributing to the risk in this region. We also replicated 11 different known AD loci -including APOE- identified in mostly European studies, which is likely due to the high European background of the PR population. Conclusion PR GWAS and AM analysis identified a suggestive AD risk locus on chromosome 12, which includes the SLC38A1 and SCN8A genes. Our findings demonstrate the importance of designing GWAS and ancestry-aware approaches and including underrepresented populations in genetic studies of AD.
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Affiliation(s)
- Bilcag Akgun
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, United States
| | | | - Kara L Hamilton-Nelson
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, United States
| | - Kyle Scott
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, United States
| | - Joe Rivero
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, United States
| | - Larry D Adams
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, United States
| | - Jose J Sanchez
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, United States
| | - Glenies S Valladares
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, United States
| | - Sergio Tejada
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, United States
| | - Parker L Bussies
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, United States
| | - Concepcion Silva-Vergara
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, United States
| | - Vanessa C Rodriguez
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, United States
| | - Pedro R Mena
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, United States
| | - Katrina Celis
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, United States
| | - Patrice G Whitehead
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, United States
| | - Michael Prough
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, United States
| | - Christina Kosanovic
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, United States
| | - Derek J Van Booven
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, United States
| | - Michael A Schmidt
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, United States
| | | | - Anthony J Griswold
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, United States
- Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, United States
| | - Clifton L Dalgard
- Department of Anatomy, Physiology, and Genetics, Uniformed Services University of the Health Sciences, Bethesda, MD, United States
| | - Katalina F McInerney
- Department of Neurology, University of Miami Miller School of Medicine, Miami, FL, United States
| | - Gary W Beecham
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, United States
- Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, United States
| | - Michael L Cuccaro
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, United States
- Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, United States
| | - Jeffery M Vance
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, United States
- Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, United States
- Department of Neurology, University of Miami Miller School of Medicine, Miami, FL, United States
| | - Margaret A Pericak-Vance
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, United States
- Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, United States
- Department of Neurology, University of Miami Miller School of Medicine, Miami, FL, United States
| | - Farid Rajabli
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, United States
- Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, United States
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12
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de la Fuente Castro C, Cortés C, Raghavan M, Castillo D, Castro M, Verdugo RA, Moraga M. The Genomic and Cultural Diversity of the Inka Qhapaq Hucha Ceremony in Chile and Argentina. Genome Biol Evol 2024; 16:evae196. [PMID: 39235046 PMCID: PMC11411372 DOI: 10.1093/gbe/evae196] [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: 03/14/2024] [Revised: 08/26/2024] [Accepted: 09/03/2024] [Indexed: 09/06/2024] Open
Abstract
The South American archaeological record has ample evidence of the socio-cultural dynamism of human populations in the past. This has also been supported through the analysis of ancient genomes, by showing evidence of gene flow across the region. While the extent of these signals is yet to be tested, the growing number of ancient genomes allows for more fine-scaled hypotheses to be evaluated. In this study, we assessed the genetic diversity of individuals associated with the Inka ritual, Qhapaq hucha. As part of this ceremony, one or more individuals were buried with Inka and local-style offerings on mountain summits along the Andes, leaving a very distinctive record. Using paleogenomic tools, we analyzed three individuals: two newly generated genomes from El Plomo Mountain (Chile) and El Toro Mountain (Argentina), and a previously published genome from Argentina (Aconcagua Mountain). Our results reveal a complex demographic scenario with each of the individuals showing different genetic affinities. Furthermore, while two individuals showed genetic similarities with present-day and ancient populations from the southern region of the Inka empire, the third individual may have undertaken long-distance movement. The genetic diversity we observed between individuals from similar cultural contexts supports the highly diverse strategies Inka implemented while incorporating new territories. More broadly, this research contributes to our growing understanding of the population dynamics in the Andes by discussing the implications and temporality of population movements in the region.
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Affiliation(s)
- Constanza de la Fuente Castro
- Programa de Genética Humana, ICBM, Universidad de Chile, Santiago, 8380453, Región Metropolitana, Chile
- Department of Human Genetics, University of Chicago, Chicago, 60637, IL, USA
| | - Constanza Cortés
- Escuela de Arqueología, Universidad Austral, Puerto Montt, 5504327, Región de Los Lagos, Chile
| | - Maanasa Raghavan
- Department of Human Genetics, University of Chicago, Chicago, 60637, IL, USA
| | - Daniela Castillo
- Programa de Genética Humana, ICBM, Universidad de Chile, Santiago, 8380453, Región Metropolitana, Chile
| | - Mario Castro
- Museo Nacional de Historia Natural, Parque Quinta Normal, Santiago, 8500000, Región Metropolitana, Chile
- Departamento de Morfología, Facultad de Medicina, Clínica Alemana-Universidad del Desarrollo, Santiago, 7610615, Región Metropolitana, Chile
| | - Ricardo A Verdugo
- Programa de Genética Humana, ICBM, Universidad de Chile, Santiago, 8380453, Región Metropolitana, Chile
- Departamento de Oncología Básico-Clínica, Universidad de Chile, Santiago, 8380453, Región Metropolitana, Chile
- Instituto de Investigación Interdisciplinaria, Universidad de Talca, Talca 3465548, Región del Maule, Chile
| | - Mauricio Moraga
- Programa de Genética Humana, ICBM, Universidad de Chile, Santiago, 8380453, Región Metropolitana, Chile
- Departamento de Antropología, Facultad de Ciencias Sociales, Universidad de Chile, Santiago, 7800284, Región Metropolitana, Chile
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13
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Moreno-Mayar JV, Sousa da Mota B, Higham T, Klemm S, Gorman Edmunds M, Stenderup J, Iraeta-Orbegozo M, Laborde V, Heyer E, Torres Hochstetter F, Friess M, Allentoft ME, Schroeder H, Delaneau O, Malaspinas AS. Ancient Rapanui genomes reveal resilience and pre-European contact with the Americas. Nature 2024; 633:389-397. [PMID: 39261618 PMCID: PMC11390480 DOI: 10.1038/s41586-024-07881-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Accepted: 07/26/2024] [Indexed: 09/13/2024]
Abstract
Rapa Nui (also known as Easter Island) is one of the most isolated inhabited places in the world. It has captured the imagination of many owing to its archaeological record, which includes iconic megalithic statues called moai1. Two prominent contentions have arisen from the extensive study of Rapa Nui. First, the history of the Rapanui has been presented as a warning tale of resource overexploitation that would have culminated in a major population collapse-the 'ecocide' theory2-4. Second, the possibility of trans-Pacific voyages to the Americas pre-dating European contact is still debated5-7. Here, to address these questions, we reconstructed the genomic history of the Rapanui on the basis of 15 ancient Rapanui individuals that we radiocarbon dated (1670-1950 CE) and whole-genome sequenced (0.4-25.6×). We find that these individuals are Polynesian in origin and most closely related to present-day Rapanui, a finding that will contribute to repatriation efforts. Through effective population size reconstructions and extensive population genetics simulations, we reject a scenario involving a severe population bottleneck during the 1600s, as proposed by the ecocide theory. Furthermore, the ancient and present-day Rapanui carry similar proportions of Native American admixture (about 10%). Using a Bayesian approach integrating genetic and radiocarbon dates, we estimate that this admixture event occurred about 1250-1430 CE.
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Affiliation(s)
- J Víctor Moreno-Mayar
- Globe Institute, Faculty of Health and Medical Science, University of Copenhagen, Copenhagen, Denmark.
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark.
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.
| | - Bárbara Sousa da Mota
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Tom Higham
- Department of Evolutionary Anthropology, University of Vienna, Vienna, Austria
- Human Evolution and Archaeological Science (HEAS) Network, University of Vienna, Vienna, Austria
| | - Signe Klemm
- Globe Institute, Faculty of Health and Medical Science, University of Copenhagen, Copenhagen, Denmark
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | | | - Jesper Stenderup
- Globe Institute, Faculty of Health and Medical Science, University of Copenhagen, Copenhagen, Denmark
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Miren Iraeta-Orbegozo
- Globe Institute, Faculty of Health and Medical Science, University of Copenhagen, Copenhagen, Denmark
- School of Archaeology, University College Dublin, Dublin, Ireland
| | - Véronique Laborde
- Direction Générale Déléguée aux Collections, Muséum national d'Histoire naturelle, Paris, France
| | - Evelyne Heyer
- Eco-anthropologie (EA), Muséum national d'Histoire naturelle, CNRS, Université Paris Cité, Musée de l'Homme, Paris, France
| | | | - Martin Friess
- Eco-anthropologie (EA), Muséum national d'Histoire naturelle, CNRS, Université Paris Cité, Musée de l'Homme, Paris, France
| | - Morten E Allentoft
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
- Trace and Environmental DNA (TrEnD) Laboratory, School of Molecular and Life Sciences, Curtin University, Perth, Western Australia, Australia
| | - Hannes Schroeder
- Globe Institute, Faculty of Health and Medical Science, University of Copenhagen, Copenhagen, Denmark
| | | | - Anna-Sapfo Malaspinas
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.
- Swiss Institute of Bioinformatics, Lausanne, Switzerland.
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14
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Chen Q, Aguirre L, Liang G, Zhao H, Dong T, Borrego F, de Rojas I, Hu Q, Reyes C, Su LY, Zhang B, Lechleiter JD, Göring HHH, De Jager PL, Kleinman JE, Hyde TM, Li PP, Ruiz A, Weinberger DR, Seshadri S, Ma L. Identification of a specific APOE transcript and functional elements associated with Alzheimer's disease. Mol Neurodegener 2024; 19:63. [PMID: 39210471 PMCID: PMC11361112 DOI: 10.1186/s13024-024-00751-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2024] [Accepted: 08/16/2024] [Indexed: 09/04/2024] Open
Abstract
BACKGROUND The APOE gene is the strongest genetic risk factor for late-onset Alzheimer's Disease (LOAD). However, the gene regulatory mechanisms at this locus remain incompletely characterized. METHODS To identify novel AD-linked functional elements within the APOE locus, we integrated SNP variants with multi-omics data from human postmortem brains including 2,179 RNA-seq samples from 3 brain regions and two ancestries (European and African), 667 DNA methylation samples, and ChIP-seq samples. Additionally, we plotted the expression trajectory of APOE transcripts in human brains during development. RESULTS We identified an AD-linked APOE transcript (jxn1.2.2) particularly observed in the dorsolateral prefrontal cortex (DLPFC). The APOE jxn1.2.2 transcript is associated with brain neuropathological features, cognitive impairment, and the presence of the APOE4 allele in DLPFC. We prioritized two independent functional SNPs (rs157580 and rs439401) significantly associated with jxn1.2.2 transcript abundance and DNA methylation levels. These SNPs are located within active chromatin regions and affect brain-related transcription factor-binding affinities. The two SNPs shared effects on the jxn1.2.2 transcript between European and African ethnic groups. CONCLUSION The novel APOE functional elements provide potential therapeutic targets with mechanistic insight into the disease etiology.
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Affiliation(s)
- Qiang Chen
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Dr, San Antonio, TX, 78229, USA
| | - Luis Aguirre
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Dr, San Antonio, TX, 78229, USA
| | - Guoming Liang
- College of Animal Science, Shanxi Agricultural University, Taigu, Shanxi, China
| | - Huanhuan Zhao
- Bioinformatics Program, University of Texas at El Paso, El Paso, TX, USA
| | - Tao Dong
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Felix Borrego
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Dr, San Antonio, TX, 78229, USA
| | - Itziar de Rojas
- Research Center and Memory Clinic, Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Barcelona, Spain
- Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Qichan Hu
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Dr, San Antonio, TX, 78229, USA
| | - Christopher Reyes
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Dr, San Antonio, TX, 78229, USA
| | - Ling-Yan Su
- College of Food Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Bao Zhang
- College of Forensic Medicine, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China
| | - James D Lechleiter
- Department of Cell Systems and Anatomy, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Harald H H Göring
- South Texas Diabetes and Obesity Institute and Division of Human Genetics, University of Texas Rio Grande Valley School of Medicine, San Antonio, TX, USA
| | - Philip L De Jager
- Center for Translational and Computational Neuroimmunology, Department of Neurology and Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Medical Center, New York, NY, USA
| | - Joel E Kleinman
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Thomas M Hyde
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Pan P Li
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Agustín Ruiz
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Dr, San Antonio, TX, 78229, USA
- Research Center and Memory Clinic, Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Barcelona, Spain
- Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Daniel R Weinberger
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Departments of Neurology, Neuroscience, and Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Dr, San Antonio, TX, 78229, USA.
- Department of Neurology, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA.
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA.
| | - Liang Ma
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Dr, San Antonio, TX, 78229, USA.
- Department of Pharmacology, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA.
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15
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Bigdeli TB, Chatzinakos C, Bendl J, Barr PB, Venkatesh S, Gorman BR, Clarence T, Genovese G, Iyegbe CO, Peterson RE, Kolokotronis SO, Burstein D, Meyers JL, Li Y, Rajeevan N, Sayward F, Cheung KH, DeLisi LE, Kosten TR, Zhao H, Achtyes E, Buckley P, Malaspina D, Lehrer D, Rapaport MH, Braff DL, Pato MT, Fanous AH, Pato CN, Huang GD, Muralidhar S, Michael Gaziano J, Pyarajan S, Girdhar K, Lee D, Hoffman GE, Aslan M, Fullard JF, Voloudakis G, Harvey PD, Roussos P. Biological Insights from Schizophrenia-associated Loci in Ancestral Populations. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.08.27.24312631. [PMID: 39252912 PMCID: PMC11383513 DOI: 10.1101/2024.08.27.24312631] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 09/11/2024]
Abstract
Large-scale genome-wide association studies of schizophrenia have uncovered hundreds of associated loci but with extremely limited representation of African diaspora populations. We surveyed electronic health records of 200,000 individuals of African ancestry in the Million Veteran and All of Us Research Programs, and, coupled with genotype-level data from four case-control studies, realized a combined sample size of 13,012 affected and 54,266 unaffected persons. Three genome-wide significant signals - near PLXNA4, PMAIP1, and TRPA1 - are the first to be independently identified in populations of predominantly African ancestry. Joint analyses of African, European, and East Asian ancestries across 86,981 cases and 303,771 controls, yielded 376 distinct autosomal loci, which were refined to 708 putatively causal variants via multi-ancestry fine-mapping. Utilizing single-cell functional genomic data from human brain tissue and two complementary approaches, transcriptome-wide association studies and enhancer-promoter contact mapping, we identified a consensus set of 94 genes across ancestries and pinpointed the specific cell types in which they act. We identified reproducible associations of schizophrenia polygenic risk scores with schizophrenia diagnoses and a range of other mental and physical health problems. Our study addresses a longstanding gap in the generalizability of research findings for schizophrenia across ancestral populations, underlining shared biological underpinnings of schizophrenia across global populations in the presence of broadly divergent risk allele frequencies.
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Affiliation(s)
- Tim B Bigdeli
- VA New York Harbor Healthcare System, Brooklyn, NY
- Department of Psychiatry and Behavioral Sciences and SUNY Downstate Health Sciences University, Brooklyn, NY
- Institute for Genomics in Health (IGH), SUNY Downstate Health Sciences University, Brooklyn, NY
- Department of Epidemiology and Biostatistics, School of Public Health, SUNY Downstate Health Sciences University, Brooklyn, NY
| | - Chris Chatzinakos
- Department of Psychiatry and Behavioral Sciences and SUNY Downstate Health Sciences University, Brooklyn, NY
- Institute for Genomics in Health (IGH), SUNY Downstate Health Sciences University, Brooklyn, NY
| | - Jaroslav Bendl
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, NY
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, NY
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, NY
| | - Peter B Barr
- VA New York Harbor Healthcare System, Brooklyn, NY
- Department of Psychiatry and Behavioral Sciences and SUNY Downstate Health Sciences University, Brooklyn, NY
- Institute for Genomics in Health (IGH), SUNY Downstate Health Sciences University, Brooklyn, NY
- Department of Epidemiology and Biostatistics, School of Public Health, SUNY Downstate Health Sciences University, Brooklyn, NY
| | - Sanan Venkatesh
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, NY
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, NY
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, NY
- Center for Precision Medicine and Translational Therapeutics, James J. Peters VA Medical Center, Bronx, NY, USA
| | - Bryan R Gorman
- Massachusetts Area Veterans Epidemiology, Research, and Information Center (MAVERIC), Jamaica Plain, MA
| | - Tereza Clarence
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, NY
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, NY
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, NY
| | - Giulio Genovese
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA
- Harvard Medical School, Boston, MA
| | - Conrad O Iyegbe
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY
| | - Roseann E Peterson
- VA New York Harbor Healthcare System, Brooklyn, NY
- Department of Psychiatry and Behavioral Sciences and SUNY Downstate Health Sciences University, Brooklyn, NY
- Institute for Genomics in Health (IGH), SUNY Downstate Health Sciences University, Brooklyn, NY
| | - Sergios-Orestis Kolokotronis
- Institute for Genomics in Health (IGH), SUNY Downstate Health Sciences University, Brooklyn, NY
- Department of Epidemiology and Biostatistics, School of Public Health, SUNY Downstate Health Sciences University, Brooklyn, NY
- Division of Infectious Diseases, Department of Medicine, College of Medicine, SUNY Downstate Health Sciences University, Brooklyn, NY
- Department of Cell Biology, College of Medicine, SUNY Downstate Health Sciences University, Brooklyn, NY
| | - David Burstein
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, NY
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, NY
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, NY
- Center for Precision Medicine and Translational Therapeutics, James J. Peters VA Medical Center, Bronx, NY, USA
- Mental Illness Research, Education and Clinical Center VISN2, James J. Peters VA Medical Center, Bronx, NY, USA
| | - Jacquelyn L Meyers
- Department of Psychiatry and Behavioral Sciences and SUNY Downstate Health Sciences University, Brooklyn, NY
- Institute for Genomics in Health (IGH), SUNY Downstate Health Sciences University, Brooklyn, NY
- Department of Epidemiology and Biostatistics, School of Public Health, SUNY Downstate Health Sciences University, Brooklyn, NY
| | - Yuli Li
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT
- Yale University School of Medicine, New Haven, CT
| | - Nallakkandi Rajeevan
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT
- Yale University School of Medicine, New Haven, CT
| | - Frederick Sayward
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT
- Yale University School of Medicine, New Haven, CT
| | - Kei-Hoi Cheung
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT
- Yale University School of Medicine, New Haven, CT
| | - Lynn E DeLisi
- Department of Psychiatry, Cambridge Health Alliance, Cambridge, MA
| | - Thomas R Kosten
- Michael E. DeBakey VA Medical Center, Houston, TX
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX
| | - Hongyu Zhao
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT
- Yale University School of Medicine, New Haven, CT
| | - Eric Achtyes
- Western Michigan University Homer Stryker M.D. School of Medicine, Kalamazoo, MI
| | - Peter Buckley
- University of Tennessee Health Science Center in Memphis, TN
| | - Dolores Malaspina
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, NY
| | - Douglas Lehrer
- Department of Psychiatry, Wright State University, Dayton, OH
| | - Mark H Rapaport
- Huntsman Mental Health Institute, Department of Psychiatry, University of Utah, Salt Lake City, UT
| | - David L Braff
- Department of Psychiatry, University of California, San Diego, CA
- VA San Diego Healthcare System, San Diego, CA
| | - Michele T Pato
- Department of Psychiatry, Robert Wood Johnson Medical School, New Brunswick, NJ
| | - Ayman H Fanous
- Department of Psychiatry, University of Arizona College of Medicine-Phoenix, Phoenix, AZ
- Department of Psychiatry, VA Phoenix Healthcare System, Phoenix, AZ
| | - Carlos N Pato
- Department of Psychiatry, Robert Wood Johnson Medical School, New Brunswick, NJ
| | - Grant D Huang
- Office of Research and Development, Veterans Health Administration, Washington, DC
| | - Sumitra Muralidhar
- Office of Research and Development, Veterans Health Administration, Washington, DC
| | - J Michael Gaziano
- Massachusetts Area Veterans Epidemiology, Research, and Information Center (MAVERIC), Jamaica Plain, MA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA
| | - Saiju Pyarajan
- Massachusetts Area Veterans Epidemiology, Research, and Information Center (MAVERIC), Jamaica Plain, MA
| | - Kiran Girdhar
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, NY
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, NY
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, NY
| | - Donghoon Lee
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, NY
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, NY
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, NY
| | - Gabriel E Hoffman
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, NY
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, NY
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, NY
- Center for Precision Medicine and Translational Therapeutics, James J. Peters VA Medical Center, Bronx, NY, USA
- Mental Illness Research, Education and Clinical Center VISN2, James J. Peters VA Medical Center, Bronx, NY, USA
| | - Mihaela Aslan
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT
- Yale University School of Medicine, New Haven, CT
| | - John F Fullard
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, NY
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, NY
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, NY
| | - Georgios Voloudakis
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, NY
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, NY
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, NY
- Center for Precision Medicine and Translational Therapeutics, James J. Peters VA Medical Center, Bronx, NY, USA
- Mental Illness Research, Education and Clinical Center VISN2, James J. Peters VA Medical Center, Bronx, NY, USA
| | - Philip D Harvey
- Bruce W. Carter Miami Veterans Affairs (VA) Medical Center, Miami, FL
- University of Miami School of Medicine, Miami, FL
| | - Panos Roussos
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, NY
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, NY
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, NY
- Center for Precision Medicine and Translational Therapeutics, James J. Peters VA Medical Center, Bronx, NY, USA
- Mental Illness Research, Education and Clinical Center VISN2, James J. Peters VA Medical Center, Bronx, NY, USA
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16
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Honorato-Mauer J, Shah NN, Maihofer AX, Zai CC, Belangero S, Nievergelt CM, Santoro M, Atkinson E. Characterizing features affecting local ancestry inference performance in admixed populations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.26.609770. [PMID: 39253486 PMCID: PMC11383044 DOI: 10.1101/2024.08.26.609770] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 09/11/2024]
Abstract
In recent years, significant efforts have been made to improve methods for genomic studies of admixed populations using Local Ancestry Inference (LAI). Accurate LAI is crucial to ensure downstream analyses reflect the genetic ancestry of research participants accurately. Here, we test analytic strategies for LAI to provide guidelines for optimal accuracy, focusing on admixed populations reflective of Latin America's primary continental ancestries - African (AFR), Amerindigenous (AMR), and European (EUR). Simulating LD-informed admixed haplotypes under a variety of 2 and 3-way admixture models, we implemented a standard LAI pipeline, testing three reference panel compositions to quantify their overall and ancestry-specific accuracy. We examined LAI miscall frequencies and true positive rates (TPR) across simulation models and continental ancestries. AMR tracts have notably reduced LAI accuracy as compared to EUR and AFR tracts in all comparisons, with TPR means for AMR ranging from 88-94%, EUR from 96-99% and AFR 98-99%. When LAI miscalls occurred, they most frequently erroneously called European ancestry in true Amerindigenous sites. Using a reference panel well-matched to the target population, even with a lower sample size, LAI produced true-positive estimates that were not statistically different from a high sample size but mismatched reference, while being more computationally efficient. While directly responsive to admixed Latin American cohort compositions, these trends are broadly useful for informing best practices for LAI across other admixed populations. Our findings reinforce the need for inclusion of more underrepresented populations in sequencing efforts to improve reference panels.
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Affiliation(s)
- Jessica Honorato-Mauer
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Nirav N Shah
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Adam X Maihofer
- Department of Psychiatry, School of Medicine, University of California at San Diego, La Jolla, CA 92093, USA
| | - Clement C Zai
- Department of Psychiatry, Institute of Medical Science, Laboratory Medicine and Pathobiology, University of Toronto
| | - Sintia Belangero
- Department of Morphology and Genetics, Universidade Federal de São Paulo, São Paulo, 04023-062, Brazil
| | - Caroline M Nievergelt
- Department of Psychiatry, School of Medicine, University of California at San Diego, La Jolla, CA 92093, USA
| | - Marcos Santoro
- Department of Biochemistry, Molecular Biology Division, Universidade Federal de São Paulo, São Paulo, 04023-062, Brazil
| | - Elizabeth Atkinson
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA
- The Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, TX 77030, USA
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17
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Ioannou S, Beecham A, Gomez L, Dauer R, Khakoo N, Pascual L, Quintero M, Lopez J, Leavitt JS, Solis N, Ortega M, Deshpande AR, Kerman DH, Proksell S, Torres EA, Haritunians T, Li D, Abreu MT, McGovern DPB, McCauley JL, Damas OM. Ancestral Diversity in Pharmacogenomics Affects Treatment for Hispanic/Latine Populations With Inflammatory Bowel Disease. Clin Gastroenterol Hepatol 2024:S1542-3565(24)00766-3. [PMID: 39181428 DOI: 10.1016/j.cgh.2024.07.032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/27/2024] [Revised: 07/10/2024] [Accepted: 07/11/2024] [Indexed: 08/27/2024]
Abstract
BACKGROUND AND AIMS The prevalence of inflammatory bowel disease among Hispanic/Latine communities is increasing. Pharmacogenomic studies reveal genetic markers that influence treatment decisions. The aim of our study was to examine the frequency and impact of genetic polymorphisms on thiopurine-associated leukopenia (NUDT15, TPMT) and anti-tumor necrosis factor (TNF) immunogenicity (HLA-DQA1∗05) in a cohort of Hispanic patients of diverse ancestral backgrounds. METHODS We performed a multicenter, retrospective cohort study comprising 2225 Hispanic participants. We measured the frequency of variation affecting drug response in NUDT15, TPMT, and HLA-DQA1∗05; their ancestral origin (European, African, or Amerindian); and the rate of development of myelosuppression and immunogenicity to thiopurines and anti-TNFs, in exposed patients. RESULTS NUDT15 and TPMT variants were rare, except for rs116855232 in NUDT15, which was common only in alleles of Amerindian origin. All NUDT15 variant alleles were inherited on an Amerindian haplotype, and among the Amerindian allele subset, the variant frequency of NUDT15∗4 (rs147390019) was a remarkable 23% in patients with leukopenia but only 3% in patients without leukopenia. HLA-DQA1∗05 and its European tagging variant rs2097432 were common in alleles from all ancestral origins and demonstrated association with immunogenicity to anti-TNFs. However, rs2097432 was only correlated with HLA-DQA1∗05 in the European allele subset. CONCLUSIONS These findings indicate that NUDT15 testing should become standard clinical practice before prescribing thiopurines in individuals with Amerindian/Alaska Native ancestry, including Hispanic individuals. Additionally, rs2097432 should not be used as a surrogate for HLA-DQA1∗05 testing for diverse populations. Ultimately, incorporating ancestry in personalized therapeutic approaches is important for treatment of Hispanic patients with inflammatory bowel disease.
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Affiliation(s)
- Stephanie Ioannou
- Division of Digestive Health and Liver Diseases, University of Miami Miller School of Medicine, Miami, Florida
| | - Ashley Beecham
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, Florida
| | - Lissette Gomez
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, Florida
| | - Ryan Dauer
- Division of Digestive Health and Liver Diseases, University of Miami Miller School of Medicine, Miami, Florida
| | - Nidah Khakoo
- Division of Digestive Health and Liver Diseases, University of Miami Miller School of Medicine, Miami, Florida
| | - Lauren Pascual
- Division of Digestive Health and Liver Diseases, University of Miami Miller School of Medicine, Miami, Florida
| | - Maria Quintero
- Division of Digestive Health and Liver Diseases, University of Miami Miller School of Medicine, Miami, Florida
| | - Joanna Lopez
- Department of Gastroenterology, Gastro Health, Miami, Florida
| | - James S Leavitt
- Department of Gastroenterology, Gastro Health, Miami, Florida
| | - Norma Solis
- Division of Digestive Health and Liver Diseases, University of Miami Miller School of Medicine, Miami, Florida
| | - Mailenys Ortega
- Division of Digestive Health and Liver Diseases, University of Miami Miller School of Medicine, Miami, Florida
| | - Amar R Deshpande
- Division of Digestive Health and Liver Diseases, University of Miami Miller School of Medicine, Miami, Florida
| | - David H Kerman
- Division of Digestive Health and Liver Diseases, University of Miami Miller School of Medicine, Miami, Florida
| | - Siobhan Proksell
- Division of Digestive Health and Liver Diseases, University of Miami Miller School of Medicine, Miami, Florida
| | - Esther A Torres
- Department of Gastroenterology, University of Puerto Rico School of Medicine, San Juan, Puerto Rico
| | - Talin Haritunians
- F. Widjaja Foundation Inflammatory Bowel Disease Institute, Cedars-Sinai Medical Center, Los Angeles, California
| | - Dalin Li
- F. Widjaja Foundation Inflammatory Bowel Disease Institute, Cedars-Sinai Medical Center, Los Angeles, California
| | - Maria T Abreu
- Division of Digestive Health and Liver Diseases, University of Miami Miller School of Medicine, Miami, Florida
| | - Dermott P B McGovern
- F. Widjaja Foundation Inflammatory Bowel Disease Institute, Cedars-Sinai Medical Center, Los Angeles, California
| | - Jacob L McCauley
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, Florida
| | - Oriana M Damas
- Division of Digestive Health and Liver Diseases, University of Miami Miller School of Medicine, Miami, Florida.
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18
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Fu H, Shi G. Local Ancestry Inference Based on Population-Specific Single-Nucleotide Polymorphisms-A Study of Admixed Populations in the 1000 Genomes Project. Genes (Basel) 2024; 15:1099. [PMID: 39202458 PMCID: PMC11353365 DOI: 10.3390/genes15081099] [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: 06/29/2024] [Revised: 08/09/2024] [Accepted: 08/19/2024] [Indexed: 09/03/2024] Open
Abstract
Human populations have interacted throughout history, and a considerable portion of modern human populations show evidence of admixture. Local ancestry inference (LAI) is focused on detecting the genetic ancestry of chromosomal segments in admixed individuals and has wide applications. In this work, we proposed a new LAI method based on population-specific single-nucleotide polymorphisms (SNPs) and applied it in the analysis of admixed populations in the 1000 Genomes Project (1KGP). Based on population-specific SNPs in a sliding window, we computed local ancestry information vectors, which are moment estimators of local ancestral proportions, for two haplotypes of an admixed individual and inferred the local ancestral origins. Then we used African (AFR), East Asian (EAS), European (EUR) and South Asian (SAS) populations from the 1KGP and indigenous American (AMR) populations from the Human Genome Diversity Project (HGDP) as reference populations and conducted the proposed LAI analysis on African American populations and American populations in the 1KGP. The results were compared with those obtained by RFMix, G-Nomix and FLARE. We demonstrated that the existence of alleles in a chromosomal region that are specific to a particular reference population and the absence of alleles specific to the other reference populations provide reasonable evidence for determining the ancestral origin of the region. Contemporary AFR, AMR and EUR populations approximate ancestral populations of the admixed populations well, and the results from RFMix, G-Nomix and FLARE largely agree with those from the Ancestral Spectrum Analyzer (ASA), in which the proposed method was implemented. When admixtures are ancient and contemporary reference populations do not satisfactorily approximate ancestral populations, the performances of RFMix, G-Nomix and FLARE deteriorate with increased error rates and fragmented chromosomal segments. In contrast, our method provides fair results.
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Affiliation(s)
| | - Gang Shi
- School of Telecommunications Engineering, Xidian University, 2 South Taibai Road, Xi’an 710071, China;
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19
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Del Valle-Peréz M, Mejía-García A, Echeverri-López D, Gallo-Bonilla K, Tejada-Moreno JA, Villegas-Lanau A, Chvatal-Medina M, Restrepo JE, Cuartas-Montoya G, Zapata-Builes W. Urofacial (Ochoa) syndrome with a founder pathogenic variant in the HPSE2 gene: a case report and mutation origin. J Appl Genet 2024:10.1007/s13353-024-00896-7. [PMID: 39150614 DOI: 10.1007/s13353-024-00896-7] [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: 05/08/2024] [Revised: 07/16/2024] [Accepted: 07/18/2024] [Indexed: 08/17/2024]
Abstract
Urofacial syndrome or Ochoa syndrome (UFS or UFOS) is a rare disease characterized by inverted facial expression and bladder dysfunction that was described for the first time in Colombia. It is an autosomal recessive pathology with mutations in the HPSE2 and LRIG2 genes. However, 16% of patients do not have any mutations associated with the syndrome. Despite the importance of neurobiology in its pathophysiology, there are no neurological, neuropsychological, or psychological studies in these patients. A 30-year-old male from Medellín, Colombia, with a significant perinatal history, was diagnosed with grade 4 hydronephrosis on his first ultrasound test. At 4 months of age, symptoms such as hypomimia, lagophthalmos, and recurrent urinary tract infections started to manifest. Imaging studies revealed urinary tract dilatation, vesicoureteral reflux, and a double collector system on his left side, which led to the diagnosis of UFS. Multiple procedures, including vesicostomy, ureterostomy, and enterocystoplasty, were performed. At 20 years of age, he achieved urinary sphincter control. Genetic analysis revealed a founder pathogenic variant, c.1516C > T (p.Arg506Ter), in the HPSE2 gene, which produces a truncated protein that lacks 86 amino acids. This variant is classified as pathogenic according to the ClinVar database for UFS. The mutation age is approximately 260-360 years, and the two alleles share a 7.2-7.4 Mb IBD segment. Moreover, we detected European local ancestry in the IBD segment, which is consistent with a Spanish introduction. Neurological examination, neuropsychological assessment, and psychological testing revealed no abnormalities, except for high stress levels. Clinical analysis of this patient revealed distorted facial expression and detrusor-sphincter dyssynergia, which are typical of patients with UFS. Genetic analysis revealed a pathogenic variant in the HPSE2 gene of European origin and a mutation age of 260-360 years. From a neurological, neuropsychological, and psychological (emotional and personality) perspective, the patient showed no signs or symptoms of clinical interest.
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Affiliation(s)
- Manuela Del Valle-Peréz
- Grupo Infettare, Facultad de Medicina, Universidad Cooperativa de Colombia, Medellín, Colombia
| | - Alejandro Mejía-García
- Grupo de Genética Molecular (GENMOL), Facultad de Ciencias Exactas y Naturales (FCEN), Universidad de Antioquia, Medellín, Colombia
| | - Dayana Echeverri-López
- Grupo Infettare, Facultad de Medicina, Universidad Cooperativa de Colombia, Medellín, Colombia
| | - Katherine Gallo-Bonilla
- Grupo Infettare, Facultad de Medicina, Universidad Cooperativa de Colombia, Medellín, Colombia
| | - Johanna A Tejada-Moreno
- Grupo de Genética Molecular (GENMOL), Facultad de Ciencias Exactas y Naturales (FCEN), Universidad de Antioquia, Medellín, Colombia
| | - Andrés Villegas-Lanau
- Grupo de Genética Molecular (GENMOL), Facultad de Ciencias Exactas y Naturales (FCEN), Universidad de Antioquia, Medellín, Colombia
| | - Mateo Chvatal-Medina
- Grupo Inmunovirología, Facultad de Medicina, Universidad de Antioquia, Medellín, Colombia
| | - Jorge E Restrepo
- Grupo OBSERVATOS, Facultad de Educación Y Ciencias Sociales, Tecnológico de Antioquia - Institución Universitaria, Medellín, Colombia
| | - Gina Cuartas-Montoya
- Facultad de Psicología, Grupo Neurociencia Y Cognición, Universidad Cooperativa de Colombia, Medellín, Colombia
| | - Wildeman Zapata-Builes
- Grupo Infettare, Facultad de Medicina, Universidad Cooperativa de Colombia, Medellín, Colombia.
- Grupo Inmunovirología, Facultad de Medicina, Universidad de Antioquia, Medellín, Colombia.
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20
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Rhead B, Hein DM, Pouliot Y, Guinney J, De La Vega FM, Sanford NN. Association of genetic ancestry with molecular tumor profiles in colorectal cancer. Genome Med 2024; 16:99. [PMID: 39138508 PMCID: PMC11321170 DOI: 10.1186/s13073-024-01373-w] [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: 08/14/2023] [Accepted: 08/05/2024] [Indexed: 08/15/2024] Open
Abstract
BACKGROUND There are known disparities in incidence and outcomes of colorectal cancer (CRC) by race and ethnicity. Some of these disparities may be mediated by molecular changes in tumors that occur at different rates across populations. Genetic ancestry is a measure complementary to race and ethnicity that can overcome missing data issues and better capture genetic similarity in admixed populations. We aimed to identify somatic mutations and tumor gene expression differences associated with both genetic ancestry and imputed race and ethnicity. METHODS Sequencing was performed with the Tempus xT NGS 648-gene panel and whole exome capture RNA-Seq for 8454 primarily late-stage CRC patients. Genetic ancestry proportions for five continental groups-Africa (AFR), American indigenous (AMR), East Asia (EAS), Europe (EUR), and South Asia (SAS)-were estimated using ancestry informative markers. To address data gaps, race and ethnicity categories were imputed, resulting in assignments for 952 Hispanic/Latino, 420 non-Hispanic (NH) Asian, 1061 NH Black, and 5763 NH White individuals. We assessed association of genetic ancestry proportions and imputed race and ethnicity categories with somatic mutations in relevant CRC genes and in 2608 expression profiles, as well as 1957 consensus molecular subtypes (CMS). RESULTS Increased AFR ancestry was associated with higher odds of somatic mutations in APC, KRAS, and PIK3CA and lower odds of BRAF mutations. Additionally, increased EAS ancestry was associated with lower odds of mutations in KRAS, EUR with higher odds in BRAF, and the Hispanic/Latino category with lower odds in BRAF. Greater AFR ancestry and the NH Black category were associated with higher rates of CMS3, while a higher proportion of Hispanic/Latino patients exhibited indeterminate CMS classifications. CONCLUSIONS Molecular differences in CRC tumor mutation frequencies and gene expression that may underlie observed differences by race and ethnicity were identified. The association of AFR ancestry with increased KRAS mutations aligns with higher CMS3 subtype rates in NH Black patients. The increase of indeterminate CMS in Hispanic/Latino patients suggests that subtype classification methods could benefit from enhanced patient diversity.
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Affiliation(s)
- Brooke Rhead
- Tempus AI, 600 West Chicago Avenue, Suite 510, Chicago, IL, 60654, USA
| | - David M Hein
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX, 75390, USA
| | - Yannick Pouliot
- Tempus AI, 600 West Chicago Avenue, Suite 510, Chicago, IL, 60654, USA
| | - Justin Guinney
- Tempus AI, 600 West Chicago Avenue, Suite 510, Chicago, IL, 60654, USA
| | - Francisco M De La Vega
- Tempus AI, 600 West Chicago Avenue, Suite 510, Chicago, IL, 60654, USA.
- Department of Biomedical Data Science, Stanford University School of Medicine, 1265 Welch Road, Stanford, CA, 94305, USA.
| | - Nina N Sanford
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX, 75390, USA.
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21
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Platt RN, Enabulele EE, Adeyemi E, Agbugui MO, Ajakaye OG, Amaechi EC, Ejikeugwu CE, Igbeneghu C, Njom VS, Dlamini P, Arya GA, Diaz R, Rabone M, Allan F, Webster B, Emery A, Rollinson D, Anderson TJC. Genomic data reveal a north-south split and introgression history of blood fluke ( Schistosoma haematobium) populations from across Africa. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.06.606828. [PMID: 39149400 PMCID: PMC11326172 DOI: 10.1101/2024.08.06.606828] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/17/2024]
Abstract
The human parasitic fluke, Schistosoma haematobium hybridizes with the livestock parasite S. bovis in the laboratory, but the extent of hybridization in nature is unclear. We analyzed 34.6 million single nucleotide variants in 162 samples from 18 African countries, revealing a sharp genetic discontinuity between northern and southern S. haematobium. We found no evidence for recent hybridization. Instead the data reveal admixture events that occurred 257-879 generations ago in northern S. haematobium populations. Fifteen introgressed S. bovis genes are approaching fixation in northern S. haematobium with four genes potentially driving adaptation. We identified 19 regions that were resistant to introgression; these were enriched on the sex chromosomes. These results (i) demonstrate strong barriers to gene flow between these species, (ii) indicate that hybridization may be less common than currently envisaged, but (iii) reveal profound genomic consequences of interspecific hybridization between schistosomes of medical and veterinary importance.
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Affiliation(s)
- Roy N Platt
- Texas Biomedical Research Institute, San Antonio TX, United States
| | - Egie E Enabulele
- Texas Biomedical Research Institute, San Antonio TX, United States
| | - Ehizogie Adeyemi
- Department of Pathology, University of Benin Teaching Hospital, Edo State, Nigeria
| | - Marian O Agbugui
- Department of Biological Sciences, Edo State University, Uzairue, Nigeria
| | | | - Ebube C Amaechi
- Department of Zoology, University of Ilorin, Kwara State, Nigeria
| | | | - Christopher Igbeneghu
- Department of Medical Laboratory Science, Ladoke Akintola University of Technology, Nigeria
| | - Victor S Njom
- Department of Applied Biology and Biotechnology, Enugu State University of Science and Technology, Nigeria
| | | | - Grace A Arya
- Texas Biomedical Research Institute, San Antonio TX, United States
| | - Robbie Diaz
- Texas Biomedical Research Institute, San Antonio TX, United States
| | - Muriel Rabone
- Science Department, Natural History Museum, London, United Kingdom
| | - Fiona Allan
- Science Department, Natural History Museum, London, United Kingdom
| | - Bonnie Webster
- Science Department, Natural History Museum, London, United Kingdom
| | - Aidan Emery
- Science Department, Natural History Museum, London, United Kingdom
| | - David Rollinson
- Science Department, Natural History Museum, London, United Kingdom
- Global Schistosomiasis Alliance, London, United Kingdom
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22
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Poisner H, Faucon A, Cox N, Bick AG. Genetic determinants and phenotypic consequences of blood T-cell proportions in 207,000 diverse individuals. Nat Commun 2024; 15:6732. [PMID: 39112476 PMCID: PMC11306580 DOI: 10.1038/s41467-024-51095-1] [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: 09/01/2023] [Accepted: 07/29/2024] [Indexed: 08/10/2024] Open
Abstract
T-cells play a critical role in multiple aspects of human health and disease. However, to date the genetic determinants of human T-cell abundance have not been studied at scale because assays quantifying T-cell abundance are not widely used in clinical or research settings. The complete blood count clinical assay quantifies lymphocyte abundance which includes T-cells, B-cells, and NK-cells. To address this gap, we directly estimate T-cell fractions from whole genome sequencing data in over 200,000 individuals from the multi-ethnic TOPMed and All of Us studies. We identified 27 loci associated with T-cell fraction. Interrogating electronic health records identified clinical phenotypes associated with T-cell fraction, including notable changes in T-cell proportions that were highly dynamic over the course of pregnancy. In summary, by estimating T-cell fraction, we obtained new insights into the genetic regulation of T-cells and identified disease consequences of T-cell fractions across the human phenome.
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Affiliation(s)
- Hannah Poisner
- Vanderbilt Genetics Institute, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Annika Faucon
- Vanderbilt Genetics Institute, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Nancy Cox
- Vanderbilt Genetics Institute, Vanderbilt University School of Medicine, Nashville, TN, USA
- Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Alexander G Bick
- Vanderbilt Genetics Institute, Vanderbilt University School of Medicine, Nashville, TN, USA.
- Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
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23
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Oliveira S, Marchi N, Excoffier L. Assessing the limits of local ancestry inference from small reference panels. Mol Ecol Resour 2024; 24:e13981. [PMID: 38775247 DOI: 10.1111/1755-0998.13981] [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: 07/23/2023] [Revised: 04/23/2024] [Accepted: 05/08/2024] [Indexed: 07/31/2024]
Abstract
Admixture is a common biological phenomenon among populations of the same or different species. Identifying admixed tracts within individual genomes can provide valuable information to date admixture events, reconstruct ancestry-specific demographic histories, or detect adaptive introgression, genetic incompatibilities, as well as regions of the genomes affected by (associative-) overdominance. Although many local ancestry inference (LAI) methods have been developed in the last decade, their performance was accessed using large reference panels, which are rarely available for non-model organisms or ancient samples. Moreover, the demographic conditions for which LAI becomes unreliable have not been explicitly outlined. Here, we identify the demographic conditions for which local ancestries can be best estimated using very small reference panels. Furthermore, we compare the performance of two LAI methods (RFMix and MOSAIC) with the performance of a newly developed approach (simpLAI) that can be used even when reference populations consist of single individuals. Based on simulations of various demographic models, we also determine the limits of these LAI tools and propose post-painting filtering steps to reduce false-positive rates and improve the precision and accuracy of the inferred admixed tracts. Besides providing a guide for using LAI, our work shows that reasonable inferences can be obtained from a single diploid genome per reference under demographic conditions that are not uncommon among past human groups and non-model organisms.
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Affiliation(s)
- Sandra Oliveira
- CMPG, Institute for Ecology and Evolution, University of Bern, Berne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Nina Marchi
- CMPG, Institute for Ecology and Evolution, University of Bern, Berne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- UMR7206 Eco-Anthropologie, CNRS-MNHN-Université Paris Cité, Paris, France
| | - Laurent Excoffier
- CMPG, Institute for Ecology and Evolution, University of Bern, Berne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
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24
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Ray NR, Kunkle BW, Hamilton‐Nelson K, Kurup JT, Rajabli F, Qiao M, Vardarajan BN, Cosacak MI, Kizil C, Jean‐Francois M, Cuccaro M, Reyes‐Dumeyer D, Cantwell L, Kuzma A, Vance JM, Gao S, Hendrie HC, Baiyewu O, Ogunniyi A, Akinyemi RO, Lee W, Martin ER, Wang L, Beecham GW, Bush WS, Xu W, Jin F, Wang L, Farrer LA, Haines JL, Byrd GS, Schellenberg GD, Mayeux R, Pericak‐Vance MA, Reitz C. Extended genome-wide association study employing the African genome resources panel identifies novel susceptibility loci for Alzheimer's disease in individuals of African ancestry. Alzheimers Dement 2024; 20:5247-5261. [PMID: 38958117 PMCID: PMC11350055 DOI: 10.1002/alz.13880] [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: 09/20/2023] [Revised: 04/03/2024] [Accepted: 04/12/2024] [Indexed: 07/04/2024]
Abstract
INTRODUCTION Despite a two-fold risk, individuals of African ancestry have been underrepresented in Alzheimer's disease (AD) genomics efforts. METHODS Genome-wide association studies (GWAS) of 2,903 AD cases and 6,265 controls of African ancestry. Within-dataset results were meta-analyzed, followed by functional genomics analyses. RESULTS A novel AD-risk locus was identified in MPDZ on chromosome (chr) 9p23 (rs141610415, MAF = 0.002, p = 3.68×10-9). Two additional novel common and nine rare loci were identified with suggestive associations (P < 9×10-7). Comparison of association and linkage disequilibrium (LD) patterns between datasets with higher and lower degrees of African ancestry showed differential association patterns at chr12q23.2 (ASCL1), suggesting that this association is modulated by regional origin of local African ancestry. DISCUSSION These analyses identified novel AD-associated loci in individuals of African ancestry and suggest that degree of African ancestry modulates some associations. Increased sample sets covering as much African genetic diversity as possible will be critical to identify additional loci and deconvolute local genetic ancestry effects. HIGHLIGHTS Genetic ancestry significantly impacts risk of Alzheimer's Disease (AD). Although individuals of African ancestry are twice as likely to develop AD, they are vastly underrepresented in AD genomics studies. The Alzheimer's Disease Genetics Consortium has previously identified 16 common and rare genetic loci associated with AD in African American individuals. The current analyses significantly expand this effort by increasing the sample size and extending ancestral diversity by including populations from continental Africa. Single variant meta-analysis identified a novel genome-wide significant AD-risk locus in individuals of African ancestry at the MPDZ gene, and 11 additional novel loci with suggestive genome-wide significance at p < 9×10-7. Comparison of African American datasets with samples of higher degree of African ancestry demonstrated differing patterns of association and linkage disequilibrium at one of these loci, suggesting that degree and/or geographic origin of African ancestry modulates the effect at this locus. These findings illustrate the importance of increasing number and ancestral diversity of African ancestry samples in AD genomics studies to fully disentangle the genetic architecture underlying AD, and yield more effective ancestry-informed genetic screening tools and therapeutic interventions.
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Grants
- P30 AG013854 NIA NIH HHS
- International Parkinson Fonds
- P50 MH060451 NIMH NIH HHS
- P30 AG066444 NIA NIH HHS
- R01 AG28786-01A1 North Carolina A&T University
- U01AG46161 NIA NIH HHS
- AG05128 Duke University
- Medical Research Council
- U01AG057659 NIH HHS
- R01 AG022374 NIA NIH HHS
- U19 AG074865 NIA NIH HHS
- P50 AG023501 NIA NIH HHS
- U01 AG046152 NIA NIH HHS
- P30 AG010124 NIA NIH HHS
- U01 HG006375 NHGRI NIH HHS
- Biogen
- U01 AG058654 NIA NIH HHS
- NIMH MH60451 NINDS NIH HHS
- U54 AG052427 NIA NIH HHS
- UO1 HG004610 Group Health Research Institute
- RC2 AG036528 NIA NIH HHS
- P30 AG028377 NIA NIH HHS
- R01AG048927 NIH HHS
- UO1 HG006375 Group Health Research Institute
- R01 AG22018 Rush University
- U01AG46152 NIA NIH HHS
- P50 AG008671 NIA NIH HHS
- P30 AG10133 Indiana University
- P50 AG005142 NIA NIH HHS
- U01 AG10483 Boston University
- Higher Education Funding Council for England
- R01 AG035137 NIA NIH HHS
- R01 AG009029 NIA NIH HHS
- P50 AG005131 NIA NIH HHS
- P50 AG005128 NIA NIH HHS
- P30 AG010133 NIA NIH HHS
- U24 AG021886 NIA NIH HHS
- R01 AG031581 NIA NIH HHS
- 5R01AG012101 New York University
- R01 AG009956 NIA NIH HHS
- P50 AG016574 NIA NIH HHS
- P50 AG005146 NIA NIH HHS
- U01AG058654 NIH HHS
- AG025688 Emory University
- P30AG10161 NIA NIH HHS
- Alzheimer's Drug Discovery Foundation
- U01 AG061356 NIA NIH HHS
- RC2 AG036650 NIA NIH HHS
- Servier
- Janssen Alzheimer Immunotherapy Research & Development, LLC.
- U01 AG032984 NIA NIH HHS
- U01 HG008657 NHGRI NIH HHS
- Brain Net Europe
- R01 AG019085 NIA NIH HHS
- Lumosity
- R01 AG013616 NIA NIH HHS
- U01 AG024904 NIA NIH HHS
- Translational Genomics Research Institute
- P50 AG008702 NIA NIH HHS
- Bristol-Myers Squibb Company
- R01 AG030146 NIA NIH HHS
- R01AG041797 NIA FBS (Columbia University)
- U01 AG072579 NIA NIH HHS
- Piramal Imaging
- DeNDRoN
- UL1 RR029893 NCRR NIH HHS
- Takeda Pharmaceutical Company
- 1R01AG035137 New York University
- R01 AG15819 Rush University
- R01AG30146 NIA NIH HHS
- R01AG15819 NIA NIH HHS
- P50 NS039764 NINDS NIH HHS
- P01 AG003991 NIA NIH HHS
- Office of Research and Development
- Genentech, Inc.
- U01 AG016976 NIA NIH HHS
- US Department of Veterans Affairs Administration
- P30 AG008051 NIA NIH HHS
- P50 AG005681 NIA NIH HHS
- P30 AG013846 NIA NIH HHS
- U24 AG056270 NIA NIH HHS
- RC2 AG036502 NIA NIH HHS
- P01 AG026276 NIA NIH HHS
- R01 AG017917 NIA NIH HHS
- Araclon Biotech
- U01 AG057659 NIA NIH HHS
- R01 MH080295 NIMH NIH HHS
- Hersenstichting Nederland Breinbrekend Werk
- R01 AG026390 NIA NIH HHS
- R01 AG028786 NIA NIH HHS
- KL2 RR024151 NCRR NIH HHS
- Internationale Stiching Alzheimer Onderzoek
- P30AG066462 NIH HHS
- U24 AG026390 NIA FBS (Columbia University)
- Novartis Pharmaceuticals Corporation
- P50 AG005136 NIA NIH HHS
- Meso Scale Diagnostics, LLC.
- CereSpir, Inc.
- P30 AG012300 NIA NIH HHS
- P01 AG03991 University of Washington
- RF1AG059018 NIH HHS
- Canadian Institute of Health Research
- RF1 AG059018 NIA NIH HHS
- BioClinica, Inc.
- U01 AG062943 NIA NIH HHS
- R01 AG012101 NIA NIH HHS
- GE Healthcare
- P50 AG016573 NIA NIH HHS
- U24 AG21886 National Cell Repository for Alzheimer's Disease (NCRAD)
- P50 AG016570 NIA NIH HHS
- P50 AG005134 NIA NIH HHS
- P30 AG066462 NIA NIH HHS
- Stichting MS Research
- P30 AG008017 NIA NIH HHS
- R01AG33193 Boston University
- Howard Hughes Medical Institute
- R01 AG042437 NIA NIH HHS
- U24 AG041689 NIA NIH HHS
- P01 AG019724 NIA NIH HHS
- R01AG36042 NIA NIH HHS
- RC2AG036547 NIA NIH HHS
- R01 AG036042 NIA NIH HHS
- P30 AG010161 NIA NIH HHS
- AG019757 University of Miami
- Kronos Science
- P30 AG08051 New York University
- IIRG-05-14147 Alzheimer's Association
- AG010491 University of Miami
- R01 AG033193 NIA NIH HHS
- P50 AG025688 NIA NIH HHS
- IIRG-08-89720 Alzheimer's Association
- AbbVie
- R37 AG015473 NIA NIH HHS
- U24 AG026395 NIA NIH HHS
- R01 AG032990 NIA NIH HHS
- North Bristol NHS Trust Research and Innovation Department
- AG021547 University of Miami
- R01 AG01101 Rush University
- Transition Therapeutics
- R01 AG072547 NIA NIH HHS
- AG027944 University of Miami
- AG041232 NIA NIH HHS
- A2111048 BrightFocus Foundation
- U01 AG052410 NIA NIH HHS
- Johnson & Johnson Pharmaceutical Research & Development LLC.
- R01 CA129769 NCI NIH HHS
- P50 AG005133 NIA NIH HHS
- U01 AG010483 NIA NIH HHS
- UO1 AG006781 Group Health Research Institute
- Merck & Co., Inc.
- U01AG32984 NIA NIH HHS
- U01 AG024904 NIH HHS
- RC2 AG036547 NIA NIH HHS
- P01 AG002219 NIA NIH HHS
- R01 AG17917 Rush University
- U01 AG006781 NIA NIH HHS
- R01 AG041797 NIA NIH HHS
- NIBIB NIH HHS
- P01 AG010491 NIA NIH HHS
- P50 AG005144 NIA NIH HHS
- U01AG062943 NIH HHS
- R01 AG064614 NIA NIH HHS
- Glaxo Smith Kline
- U01AG072579 NIH HHS
- Biomedical Laboratory Research Program
- U19AG074865 NIH HHS
- R01 AG048927 NIA NIH HHS
- RF1 AG057473 NIA NIH HHS
- R01 AG037212 NIA NIH HHS
- R01 AG022018 NIA NIH HHS
- U24AG056270 NIH HHS
- R01 AG021547 NIA NIH HHS
- R01 AG041232 NIA NIH HHS
- P50 AG005138 NIA NIH HHS
- RF1AG57473 NIA NIH HHS
- R01 AG019757 NIA NIH HHS
- R01 AG020688 NIA NIH HHS
- AG07562 University of Pittsburgh
- R01AG072547 NIH HHS
- Alzheimer's Research Trust
- Pfizer Inc.
- Illinois Department of Public Health
- Elan Pharmaceuticals, Inc.
- NHS trusts
- R01 AG030653 NIA NIH HHS
- AG052410 NIA NIH HHS
- P20 MD000546 NIMHD NIH HHS
- R01 AG027944 NIA NIH HHS
- Eli Lilly and Company
- R01 AG017173 NIA NIH HHS
- R01 AG025259 NIA NIH HHS
- U01 HG004610 NHGRI NIH HHS
- U24-AG041689 University of Pennsylvania
- P30 AG010129 NIA NIH HHS
- U01 AG046161 NIA NIH HHS
- Wellcome Trust
- P30 AG019610 NIA NIH HHS
- IXICO Ltd.
- P50 AG016582 NIA NIH HHS
- R01 AG048015 NIA NIH HHS
- NeuroRx Research
- R01AG17917 NIA NIH HHS
- U01AG61356 NIA NIH HHS
- R01AG36836 NIA NIH HHS
- 5R01AG022374 New York University
- EuroImmun; F. Hoffmann-La Roche Ltd
- R01 AG041718 NIA NIH HHS
- 1RC2AG036502 New York University
- Newcastle University
- AG041718 University of Pittsburgh
- P30 AG028383 NIA NIH HHS
- AG05144 University of Kentucky
- AG030653 University of Pittsburgh
- R01AG48015 NIA NIH HHS
- R01 AG026916 NIA NIH HHS
- P50 AG033514 NIA NIH HHS
- R01 NS059873 NINDS NIH HHS
- # NS39764 NINDS NIH HHS
- ADGC National Institutes of Health, National Institute on Aging (NIH-NIA)
- Neurotrack Technologies
- Fujirebio
- Lundbeck
- MP-V BrightFocus Foundation
- BRACE
- R01 AG015819 NIA NIH HHS
- R01 AG036836 NIA NIH HHS
- Eisai Inc.
- 5R01AG013616 New York University
- W81XWH-12-2-0012 Department of Defense
- R01AG064614 NIH HHS
- AG02365 University of Pittsburgh
- NIH
- University of Pennsylvania
- NACC
- Boston University
- Columbia University
- Duke University
- Emory University
- Indiana University
- Johns Hopkins University
- Massachusetts General Hospital
- Mayo Clinic
- New York University
- Northwestern University
- Oregon Health & Science University
- Rush University
- NIA
- University of Alabama at Birmingham
- University of Arizona
- University of California, Davis
- University of California, Irvine
- University of California, Los Angeles
- University of California, San Diego
- University of California, San Francisco
- University of Kentucky
- University of Michigan
- University of Pittsburgh
- University of Southern California
- University of Miami
- University of Washington
- Vanderbilt University
- NINDS
- Alzheimer's Association
- Office of Research and Development
- BrightFocus Foundation
- Wellcome Trust
- Howard Hughes Medical Institute
- Medical Research Council
- Newcastle University
- Higher Education Funding Council for England
- Alzheimer's Research Trust
- BRACE
- Stichting MS Research
- Department of Defense
- National Institute of Biomedical Imaging and Bioengineering
- AbbVie
- Alzheimer's Drug Discovery Foundation
- BioClinica, Inc.
- Biogen
- Bristol‐Myers Squibb Company
- Eli Lilly and Company
- Genentech, Inc.
- Fujirebio
- GE Healthcare
- Lundbeck
- Merck & Co., Inc.
- Novartis Pharmaceuticals Corporation
- Pfizer Inc.
- Servier
- Takeda Pharmaceutical Company
- Illinois Department of Public Health
- Translational Genomics Research Institute
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25
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Garzón Rodríguez N, Briceño-Balcázar I, Nicolini H, Martínez-Magaña JJ, Genis-Mendoza AD, Flores-Lázaro JC, Villatoro Velázquez JA, Bustos Gamiño M, Medina-Mora ME, Quiroz-Padilla MF. Exploring the relationship between admixture and genetic susceptibility to attention deficit hyperactivity disorder in two Latin American cohorts. J Hum Genet 2024; 69:373-380. [PMID: 38714835 PMCID: PMC11269173 DOI: 10.1038/s10038-024-01246-5] [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: 09/30/2023] [Revised: 03/11/2024] [Accepted: 03/18/2024] [Indexed: 07/13/2024]
Abstract
Contemporary research on the genomics of Attention Deficit Hyperactivity Disorder (ADHD) often underrepresents admixed populations of diverse genomic ancestries, such as Latin Americans. This study explores the relationship between admixture and genetic associations for ADHD in Colombian and Mexican cohorts. Some 546 participants in two groups, ADHD and Control, were genotyped with Infinium PsychArray®. Global ancestry levels were estimated using overall admixture proportions and principal component analysis, while local ancestry was determined using a method to estimate ancestral components along the genome. Genome-wide association analysis (GWAS) was conducted to identify significant associations. Differences between Colombia and Mexico were evaluated using appropriate statistical tests. 354 Single-nucleotide polymorphisms (SNPs) and Single-nucleotide variants (SNVs) related to some genes and intergenic regions exhibited suggestive significance (p-value < 5*10e-5) in the GWAS. None of the variants revealed genome-wide significance (p-value < 5*10e-8). The study identified a significant relationship between risk SNPs and the European component of admixture, notably observed in the LOC105379109 gene. Despite differences in risk association loci, such as FOXP2, our findings suggest a possible homogeneity in genetic variation's impact on ADHD between Colombian and Mexican populations. Current reference datasets for ADHD predominantly consist of samples with high European ancestry, underscoring the need for further research to enhance the representation of reference populations and improve the identification of ADHD risk traits in Latin Americans.
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Affiliation(s)
- Nicolás Garzón Rodríguez
- Laboratorio de Bases Biológicas del Comportamiento, Facultad de Psicología, Universidad de La Sabana, Chía, Colombia
- Doctorado en Biociencias, Facultad de Ingeniería, Universidad de La Sabana, Chía, Colombia
| | | | - Humberto Nicolini
- Laboratorio de Enfermedades Psiquiátricas, Neurodegenerativas y Adicciones, Instituto Nacional de Medicina Genómica, Secretaría de Salud, Mexico City, México
| | - José Jaime Martínez-Magaña
- Laboratorio de Enfermedades Psiquiátricas, Neurodegenerativas y Adicciones, Instituto Nacional de Medicina Genómica, Secretaría de Salud, Mexico City, México
| | - Alma D Genis-Mendoza
- Laboratorio de Enfermedades Psiquiátricas, Neurodegenerativas y Adicciones, Instituto Nacional de Medicina Genómica, Secretaría de Salud, Mexico City, México
- Hospital Psiquiátrico Infantil Dr Juan N. Navarro, Mexico City, México
| | - Julio C Flores-Lázaro
- Facultad de Psicología, Universidad Nacional Autónoma de México - UNAM, Mexico City, México
| | | | - Marycarmen Bustos Gamiño
- Instituto Nacional de Psiquiatría Ramon de la Fuente Muñiz, Secretaría de Salud, Mexico City, México
| | - Maria Elena Medina-Mora
- Facultad de Psicología, Universidad Nacional Autónoma de México - UNAM, Mexico City, México
- Instituto Nacional de Psiquiatría Ramon de la Fuente Muñiz, Secretaría de Salud, Mexico City, México
| | - Maria Fernanda Quiroz-Padilla
- Laboratorio de Bases Biológicas del Comportamiento, Facultad de Psicología, Universidad de La Sabana, Chía, Colombia.
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26
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Benjamin KJM. RFMix-reader: Accelerated reading and processing for local ancestry studies. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.13.603370. [PMID: 39071265 PMCID: PMC11275870 DOI: 10.1101/2024.07.13.603370] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/30/2024]
Abstract
Motivation Local ancestry inference is a powerful technique in genetics, revealing population history and the genetic basis of diseases. It is particularly valuable for improving eQTL discovery and fine-mapping in admixed populations. Despite the widespread use of the RFMix software for local ancestry inference, large-scale genomic studies face challenges of high memory consumption and processing times when handling RFMix output files. Results Here, I present RFMix-reader , a new Python-based parsing software, designed to streamline the analysis of large-scale local ancestry datasets. This software prioritizes computational eiciency and memory optimization, leveraging GPUs when available for additional speed boosts. By overcoming these data processing hurdles, RFMix-reader empowers researchers to unlock the full potential of local ancestry data for understanding human health and health disparities. Availability RFMix-reader is freely available on PyPI at https://pypi.org/project/rfmix-reader/ , implemented in Python 3, and supported on Linux, Windows, and Mac OS. Contact KynonJade.Benjamin@libd.org. Supplementary information Supplementary data are available at https://rfmix-reader.readthedocs.io/en/latest/ .
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27
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Pereira JL, de Souza CA, Neyra JEM, Leite JMRS, Cerqueira A, Mingroni-Netto RC, Soler JMP, Rogero MM, Sarti FM, Fisberg RM. Genetic Ancestry and Self-Reported "Skin Color/Race" in the Urban Admixed Population of São Paulo City, Brazil. Genes (Basel) 2024; 15:917. [PMID: 39062696 PMCID: PMC11276533 DOI: 10.3390/genes15070917] [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: 06/17/2024] [Revised: 07/08/2024] [Accepted: 07/10/2024] [Indexed: 07/28/2024] Open
Abstract
Epidemiological studies frequently classify groups based on phenotypes like self-reported skin color/race, which inaccurately represent genetic ancestry and may lead to misclassification, particularly among individuals of multiracial backgrounds. This study aimed to characterize both global and local genome-wide genetic ancestries and to assess their relationship with self-reported skin color/race in an admixed population of Sao Paulo city. We analyzed 226,346 single-nucleotide polymorphisms from 841 individuals participating in the population-based ISA-Nutrition study. Our findings confirmed the admixed nature of the population, demonstrating substantial European, significant Sub-Saharan African, and minor Native American ancestries, irrespective of skin color. A correlation was observed between global genetic ancestry and self-reported color-race, which was more evident in the extreme proportions of African and European ancestries. Individuals with higher African ancestry tended to identify as Black, those with higher European ancestry tended to identify as White, and individuals with higher Native American ancestry were more likely to self-identify as Mixed, a group with diverse ancestral compositions. However, at the individual level, this correlation was notably weak, and no deviations were observed for specific regions throughout the individual's genome. Our findings emphasize the significance of accurately defining and thoroughly analyzing race and ancestry, especially within admixed populations.
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Affiliation(s)
- Jaqueline L. Pereira
- Department of Nutrition, School of Public Health, University of São Paulo, São Paulo 01246-904, Brazil; (J.L.P.); (J.M.R.S.L.); (M.M.R.)
| | - Camila A. de Souza
- Department of Statistics, Institute of Mathematics and Statistics, University of São Paulo, São Paulo 05508-090, Brazil; (C.A.d.S.); (J.E.M.N.); (J.M.P.S.)
| | - Jennyfer E. M. Neyra
- Department of Statistics, Institute of Mathematics and Statistics, University of São Paulo, São Paulo 05508-090, Brazil; (C.A.d.S.); (J.E.M.N.); (J.M.P.S.)
| | - Jean M. R. S. Leite
- Department of Nutrition, School of Public Health, University of São Paulo, São Paulo 01246-904, Brazil; (J.L.P.); (J.M.R.S.L.); (M.M.R.)
| | - Andressa Cerqueira
- Department of Statistics, Federal University of Sao Carlos, São Carlos 13565-905, Brazil;
| | - Regina C. Mingroni-Netto
- Human Genome and Stem Cell Research Center, Department of Genetics and Evolutionary Biology, Biosciences Institute, University of São Paulo, São Paulo 05508-090, Brazil;
| | - Julia M. P. Soler
- Department of Statistics, Institute of Mathematics and Statistics, University of São Paulo, São Paulo 05508-090, Brazil; (C.A.d.S.); (J.E.M.N.); (J.M.P.S.)
| | - Marcelo M. Rogero
- Department of Nutrition, School of Public Health, University of São Paulo, São Paulo 01246-904, Brazil; (J.L.P.); (J.M.R.S.L.); (M.M.R.)
| | - Flavia M. Sarti
- School of Arts, Sciences and Humanities, University of Sao Paulo, São Paulo 03828-000, Brazil;
| | - Regina M. Fisberg
- Department of Nutrition, School of Public Health, University of São Paulo, São Paulo 01246-904, Brazil; (J.L.P.); (J.M.R.S.L.); (M.M.R.)
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28
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Zhen X, Betti M, Kars ME, Patterson A, Medina-Torres EA, Scheffler Mendoza SC, Herrera Sánchez DA, Lopez-Herrera G, Svyryd Y, Mutchinick O, Gamazon E, Rathmell J, Itan Y, Markle J, O'Farrill Romanillos P, Lugo-Reyes SO, Martinez-Barricarte R. Molecular and clinical characterization of a founder mutation causing G6PC3 deficiency. RESEARCH SQUARE 2024:rs.3.rs-4595246. [PMID: 39041036 PMCID: PMC11261954 DOI: 10.21203/rs.3.rs-4595246/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/24/2024]
Abstract
G6PC3 deficiency is a monogenic immunometabolic disorder that causes syndromic congenital neutropenia. Patients display heterogeneous extra-hematological manifestations, contributing to delayed diagnosis. Here, we investigated the origin and functional consequence of the G6PC3 c.210delC variant found in patients of Mexican origin. Based on the shared haplotypes amongst carriers of the c.210delC mutation, we estimated that this variant originated from a founder effect in a common ancestor. Furthermore, by ancestry analysis, we concluded that it originated in the indigenous Mexican population. At the protein level, we showed that this frameshift mutation leads to an aberrant protein expression in overexpression and patient-derived cells. G6PC3 pathology is driven by the intracellular accumulation of the metabolite 1,5-anhydroglucitol-6-phosphate (1,5-AG6P) that inhibits glycolysis. We characterized how the variant c.210delC impacts glycolysis by performing extracellular flux assays on patient-derived cells. When treated with 1,5-anhydroglucitol (1,5-AG), the precursor to 1,5-AG6P, patient-derived cells exhibited markedly reduced engagement of glycolysis. Finally, we compared the clinical presentation of patients with the mutation c.210delC and all other G6PC3 deficient patients reported in the literature to date, and we found that c.210delC carriers display all prominent clinical features observed in prior G6PC3 deficient patients. In conclusion, G6PC3 c.210delC is a loss-of-function mutation that arose from a founder effect in the indigenous Mexican population. These findings may facilitate the diagnosis of additional patients in this geographical area. Moreover, the in vitro 1,5-AG-dependent functional assay used in our study could be employed to assess the pathogenicity of additional G6PC3 variants.
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Affiliation(s)
- Xin Zhen
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center
| | - Michael Betti
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center
| | - Meltem Ece Kars
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai
| | - Andrew Patterson
- Division of Molecular Pathogenesis, Department of Medicine, Vanderbilt University Medical Center
| | | | | | | | | | - Yevgeniya Svyryd
- Department of Genetics, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán
| | - Osvaldo Mutchinick
- Department of Genetics, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán
| | - Eric Gamazon
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center
| | - Jeffrey Rathmell
- Division of Molecular Pathogenesis, Department of Medicine, Vanderbilt University Medical Center
| | - Yuval Itan
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai
| | - Janet Markle
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center
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29
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Ibañez K, Jadhav B, Zanovello M, Gagliardi D, Clarkson C, Facchini S, Garg P, Martin-Trujillo A, Gies SJ, Deforie VG, Dalmia A, Hensman Moss DJ, Vandrovcova J, Rocca C, Moutsianas L, Marini-Bettolo C, Walker H, Turner C, Shoai M, Long JD, Fratta P, Langbehn DR, Tabrizi SJ, Caulfield MJ, Cortese A, Escott-Price V, Hardy J, Houlden H, Sharp AJ, Tucci A. Increased frequency of repeat expansion mutations across different populations. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.07.03.23292162. [PMID: 37461547 PMCID: PMC10350132 DOI: 10.1101/2023.07.03.23292162] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 07/25/2023]
Abstract
Repeat expansion disorders (REDs) are a devastating group of predominantly neurological diseases. Together they are common, affecting 1 in 3,000 people worldwide with population-specific differences. However, prevalence estimates of REDs are hampered by heterogeneous clinical presentation, variable geographic distributions, and technological limitations leading to under-ascertainment. Here, leveraging whole genome sequencing data from 82,176 individuals from different populations, we found an overall disease allele frequency of REDs of 1 in 283 individuals. Modelling disease prevalence using genetic data, age at onset and survival, we show that the expected number of people with REDs would be two to three times higher than currently reported figures, indicating under-diagnosis and/or incomplete penetrance. While some REDs are population-specific, e.g. Huntington disease-like 2 in Africans, most REDs are represented in all broad genetic ancestries (i.e. Europeans, Africans, Americans, East Asians, and South Asians), challenging the notion that some REDs are found only in specific populations. These results have worldwide implications for local and global health communities in the diagnosis and counselling of REDs.
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Affiliation(s)
- Kristina Ibañez
- William Harvey Research Institute, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Bharati Jadhav
- Department of Genetics and Genomic Sciences and Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029
| | - Matteo Zanovello
- Department of Neuromuscular Diseases, Institute of Neurology, UCL, London, UK
| | - Delia Gagliardi
- William Harvey Research Institute, Queen Mary University of London, London, EC1M 6BQ, UK
- Department of Neuromuscular Diseases, Institute of Neurology, UCL, London, UK
| | - Christopher Clarkson
- William Harvey Research Institute, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Stefano Facchini
- Department of Neuromuscular Diseases, Institute of Neurology, UCL, London, UK
- IRCCS Mondino Foundation, Pavia, Italy
| | - Paras Garg
- Department of Genetics and Genomic Sciences and Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029
| | - Alejandro Martin-Trujillo
- Department of Genetics and Genomic Sciences and Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029
| | - Scott J Gies
- Department of Genetics and Genomic Sciences and Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029
| | | | | | - Davina J. Hensman Moss
- St George’s, University of London, London, SW17 0RE, UK
- Department of Neurodegenerative Disorders, Queen Square Institute of Neurology, UCL, London, UK
| | - Jana Vandrovcova
- Department of Neuromuscular Diseases, Institute of Neurology, UCL, London, UK
| | - Clarissa Rocca
- Department of Neuromuscular Diseases, Institute of Neurology, UCL, London, UK
| | | | - Chiara Marini-Bettolo
- The John Walton Muscular Dystrophy Research Centre, Translational and Clinical Research Institute, Newcastle University and Newcastle Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
| | - Helen Walker
- The John Walton Muscular Dystrophy Research Centre, Translational and Clinical Research Institute, Newcastle University and Newcastle Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
| | - Chris Turner
- MRC Centre for Neuromuscular Disease, National Hospital for Neurology and Neurosurgery, Queen Square, London, WC1N 3BG
| | - Maryam Shoai
- Department of Neurodegenerative Disorders, Queen Square Institute of Neurology, UCL, London, UK
| | - Jeffrey D Long
- Departments of Psychiatry and Biostatistics, The University of Iowa, Iowa City, IA 52242, USA
| | | | - Pietro Fratta
- Department of Neuromuscular Diseases, Institute of Neurology, UCL, London, UK
| | - Douglas R Langbehn
- Departments of Psychiatry and Biostatistics, The University of Iowa, Iowa City, IA 52242, USA
| | - Sarah J Tabrizi
- UK Dementia Research Institute, UCL, London, UK
- Department of Neurodegenerative Disorders, Queen Square Institute of Neurology, UCL, London, UK
- Huntington’s Disease Centre, UCL, London, UK
| | - Mark J Caulfield
- William Harvey Research Institute, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Andrea Cortese
- Department of Neuromuscular Diseases, Institute of Neurology, UCL, London, UK
| | - Valentina Escott-Price
- Department of Psychological Medicine and Clinical Neuroscience, School of Medicine, Cardiff University, UK
- Dementia Research Institute, Cardiff University, UK
| | - John Hardy
- Department of Neurodegenerative Disorders, Queen Square Institute of Neurology, UCL, London, UK
| | - Henry Houlden
- Department of Neurodegenerative Disorders, Queen Square Institute of Neurology, UCL, London, UK
- Neurogenetics Unit, National Hospital for Neurology and Neurosurgery, London, UK
| | - Andrew J Sharp
- Department of Genetics and Genomic Sciences and Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029
| | - Arianna Tucci
- William Harvey Research Institute, Queen Mary University of London, London, EC1M 6BQ, UK
- Department of Neuromuscular Diseases, Institute of Neurology, UCL, London, UK
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30
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Sun Q, Karafin MS, Garrett ME, Li Y, Ashley-Koch A, Telen MJ. A genome-wide association study of alloimmunization in the TOPMed OMG-SCD cohort identifies a locus on chromosome 12. Transfusion 2024. [PMID: 38966903 DOI: 10.1111/trf.17944] [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: 03/19/2024] [Revised: 06/10/2024] [Accepted: 06/20/2024] [Indexed: 07/06/2024]
Abstract
BACKGROUND Red cell alloimmunization after exposure to donor red cells is a very common complication of transfusion for patients with sickle cell disease (SCD), resulting frequently in accelerated donor red blood cell destruction. Patients show substantial differences in their predisposition to alloimmunization, and genetic variability is one proposed component. Although several genetic association studies have been conducted for alloimmunization, the results have been inconsistent, and the genetic determinants of alloimmunization remain largely unknown. STUDY DESIGN AND METHODS We performed a genome-wide association study (GWAS) in 236 African American (AA) SCD patients from the Outcome Modifying Genes in Sickle Cell Disease (OMG-SCD) cohort, which is part of Trans-Omics for Precision Medicine (TOPMed), with whole-genome sequencing data available. We also performed sensitivity analyses adjusting for different sets of covariates and applied different sample grouping strategies based on the number of alloantibodies patients developed. RESULTS We identified one genome-wide significant locus on chr12 (p = 3.1e-9) with no evidence of genomic inflation (lambda = 1.003). Further leveraging QTL evidence from GTEx whole blood and/or Jackson Heart Study PBMC RNA-Seq data, we identified a number of potential genes, such as ARHGAP9, STAT6, and ATP23, that may be driving the association signal. We also discovered some suggestive loci using different analysis strategies. DISCUSSION We call for the community to collect additional alloantibody information within SCD cohorts to further the understanding of the genetic basis of alloimmunization in order to improve transfusion outcomes.
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Affiliation(s)
- Quan Sun
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Matthew S Karafin
- Department of Pathology and Laboratory Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Melanie E Garrett
- Duke Molecular Physiology Institute, Duke University Medical Center, Durham, North Carolina, USA
| | - Yun Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Allison Ashley-Koch
- Duke Molecular Physiology Institute, Duke University Medical Center, Durham, North Carolina, USA
| | - Marilyn J Telen
- Division of Hematology, Department of Medicine, Duke Comprehensive Sickle Cell Center, Duke University Medical Center, Durham, North Carolina, USA
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Lei C, Liu J, Zhang R, Pan Y, Lu Y, Gao Y, Ma X, Yang Y, Guan Y, Mamatyusupu D, Xu S. Ancestral Origins and Admixture History of Kazakhs. Mol Biol Evol 2024; 41:msae144. [PMID: 38995236 PMCID: PMC11272102 DOI: 10.1093/molbev/msae144] [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: 12/15/2023] [Revised: 04/29/2024] [Accepted: 07/02/2024] [Indexed: 07/13/2024] Open
Abstract
Kazakh people, like many other populations that settled in Central Asia, demonstrate an array of mixed anthropological features of East Eurasian (EEA) and West Eurasian (WEA) populations, indicating a possible scenario of biological admixture between already differentiated EEA and WEA populations. However, their complex biological origin, genomic makeup, and genetic interaction with surrounding populations are not well understood. To decipher their genetic structure and population history, we conducted, to our knowledge, the first whole-genome sequencing study of Kazakhs residing in Xinjiang (KZK). We demonstrated that KZK derived their ancestries from 4 ancestral source populations: East Asian (∼39.7%), West Asian (∼28.6%), Siberian (∼23.6%), and South Asian (∼8.1%). The recognizable interactions of EEA and WEA ancestries in Kazakhs were dated back to the 15th century BCE. Kazakhs were genetically distinctive from the Uyghurs in terms of their overall genomic makeup, although the 2 populations were closely related in genetics, and both showed a substantial admixture of western and eastern peoples. Notably, we identified a considerable sex-biased admixture, with an excess of western males and eastern females contributing to the KZK gene pool. We further identified a set of genes that showed remarkable differentiation in KZK from the surrounding populations, including those associated with skin color (SLC24A5, OCA2), essential hypertension (HLA-DQB1), hypertension (MTHFR, SLC35F3), and neuron development (CNTNAP2). These results advance our understanding of the complex history of contacts between Western and Eastern Eurasians, especially those living or along the old Silk Road.
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Affiliation(s)
- Chang Lei
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Jiaojiao Liu
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Rui Zhang
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yuwen Pan
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yan Lu
- Ministry of Education Key Laboratory of Contemporary Anthropology, Fudan University, Shanghai 201203, China
| | - Yang Gao
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Xixian Ma
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yajun Yang
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Yaqun Guan
- Department of Biochemistry and Molecular Biology, Preclinical Medicine College, Xinjiang Medical University, Urumqi 830011, China
| | - Dolikun Mamatyusupu
- College of the Life Sciences and Technology, Xinjiang University, Urumqi 830046, China
| | - Shuhua Xu
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, Fudan University, Shanghai 201203, China
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Kendall C, Robinson J, Debortoli G, Nooranikhojasteh A, Christian D, Newman D, Sayers K, Cole S, Parra E, Schillaci M, Viola B. Global and local ancestry estimation in a captive baboon colony. PLoS One 2024; 19:e0305157. [PMID: 38959276 PMCID: PMC11221750 DOI: 10.1371/journal.pone.0305157] [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: 01/15/2024] [Accepted: 05/24/2024] [Indexed: 07/05/2024] Open
Abstract
The last couple of decades have highlighted the importance of studying hybridization, particularly among primate species, as it allows us to better understand our own evolutionary trajectory. Here, we report on genetic ancestry estimates using dense, full genome data from 881 olive (Papio anubus), yellow (Papio cynocephalus), or olive-yellow crossed captive baboons from the Southwest National Primate Research Center. We calculated global and local ancestry information, imputed low coverage genomes (n = 830) to improve marker quality, and updated the genetic resources of baboons available to assist future studies. We found evidence of historical admixture in some putatively purebred animals and identified errors within the Southwest National Primate Research Center pedigree. We also compared the outputs between two different phasing and imputation pipelines along with two different global ancestry estimation software. There was good agreement between the global ancestry estimation software, with R2 > 0.88, while evidence of phase switch errors increased depending on what phasing and imputation pipeline was used. We also generated updated genetic maps and created a concise set of ancestry informative markers (n = 1,747) to accurately obtain global ancestry estimates.
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Affiliation(s)
| | - Jacqueline Robinson
- Institute for Human Genetics, University of California, San Francisco, San Francisco, California, United States of America
| | - Guilherme Debortoli
- Department of Anthropology, University of Toronto Mississauga, Mississauga, Ontario, Canada
| | - Amin Nooranikhojasteh
- Epigenomics Lab, Princess Margaret Cancer Center, University Health Network, Toronto, Ontario, Canada
| | - Debbie Christian
- Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, Texas, United States of America
| | - Deborah Newman
- Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, Texas, United States of America
| | - Kenneth Sayers
- Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, Texas, United States of America
| | - Shelley Cole
- Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, Texas, United States of America
| | - Esteban Parra
- Department of Anthropology, University of Toronto Mississauga, Mississauga, Ontario, Canada
| | - Michael Schillaci
- Department of Anthropology, University of Toronto Scarborough, Scarborough, Ontario, Canada
| | - Bence Viola
- Department of Anthropology, University of Toronto, Toronto, Ontario, Canada
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Reyna-Blanco CS, Caduff M, Galimberti M, Leuenberger C, Wegmann D. Inference of Locus-Specific Population Mixtures from Linked Genome-Wide Allele Frequencies. Mol Biol Evol 2024; 41:msae137. [PMID: 38958167 PMCID: PMC11255385 DOI: 10.1093/molbev/msae137] [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: 11/06/2023] [Revised: 06/26/2024] [Accepted: 06/27/2024] [Indexed: 07/04/2024] Open
Abstract
Admixture between populations and species is common in nature. Since the influx of new genetic material might be either facilitated or hindered by selection, variation in mixture proportions along the genome is expected in organisms undergoing recombination. Various graph-based models have been developed to better understand these evolutionary dynamics of population splits and mixtures. However, current models assume a single mixture rate for the entire genome and do not explicitly account for linkage. Here, we introduce TreeSwirl, a novel method for inferring branch lengths and locus-specific mixture proportions by using genome-wide allele frequency data, assuming that the admixture graph is known or has been inferred. TreeSwirl builds upon TreeMix that uses Gaussian processes to estimate the presence of gene flow between diverged populations. However, in contrast to TreeMix, our model infers locus-specific mixture proportions employing a hidden Markov model that accounts for linkage. Through simulated data, we demonstrate that TreeSwirl can accurately estimate locus-specific mixture proportions and handle complex demographic scenarios. It also outperforms related D- and f-statistics in terms of accuracy and sensitivity to detect introgressed loci.
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Affiliation(s)
- Carlos S Reyna-Blanco
- Department of Biology, University of Fribourg, Fribourg 1700, Switzerland
- Swiss Institute of Bioinformatics, Fribourg 1700, Switzerland
| | - Madleina Caduff
- Department of Biology, University of Fribourg, Fribourg 1700, Switzerland
- Swiss Institute of Bioinformatics, Fribourg 1700, Switzerland
| | - Marco Galimberti
- Department of Biology, University of Fribourg, Fribourg 1700, Switzerland
- Swiss Institute of Bioinformatics, Fribourg 1700, Switzerland
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | | | - Daniel Wegmann
- Department of Biology, University of Fribourg, Fribourg 1700, Switzerland
- Swiss Institute of Bioinformatics, Fribourg 1700, Switzerland
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Xia R, Jian X, Rodrigue AL, Bressler J, Boerwinkle E, Cui B, Daviglus ML, DeCarli C, Gallo LC, Glahn DC, Knowles EEM, Moon JY, Mosley TH, Satizabal CL, Sofer T, Tarraf W, Testai F, Blangero J, Seshadri S, González HM, Fornage M. Admixture mapping of cognitive function in diverse Hispanic and Latino adults: Results from the Hispanic Community Health Study/Study of Latinos. Alzheimers Dement 2024. [PMID: 38946675 DOI: 10.1002/alz.14082] [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: 04/11/2024] [Revised: 05/28/2024] [Accepted: 05/29/2024] [Indexed: 07/02/2024]
Abstract
INTRODUCTION We conducted admixture mapping and fine-mapping analyses to identify ancestry-of-origin loci influencing cognitive abilities. METHODS We estimated the association of local ancestry intervals across the genome with five neurocognitive measures in 7140 diverse Hispanic and Latino adults (mean age 55 years). We prioritized genetic variants in associated loci and tested them for replication in four independent cohorts. RESULTS We identified nine local ancestry-associated regions for the five neurocognitive measures. There was strong biological support for the observed associations to cognitive function at all loci and there was statistical evidence of independent replication at 4q12, 9p22.1, and 13q12.13. DISCUSSION Our study identified multiple novel loci harboring genes implicated in cognitive functioning and dementia, and uncovered ancestry-relevant genetic variants. It adds to our understanding of the genetic architecture of cognitive function in Hispanic and Latino adults and demonstrates the power of admixture mapping to discover unique haplotypes influencing cognitive function, complementing genome-wide association studies. HIGHLIGHTS We identified nine ancestry-of-origin chromosomal regions associated with five neurocognitive traits. In each associated region, we identified single nucleotide polymorphisms (SNPs) that explained, at least in part, the admixture signal and were tested for replication in independent samples of Black, non-Hispanic White, and Hispanic/Latino adults with the same or similar neurocognitive tests. Statistical evidence of independent replication of the prioritized SNPs was observed for three of the nine associations, at chr4q12, chr9p22.1, and chr13q12.13. At all loci, there was strong biological support for the observed associations to cognitive function and dementia, prioritizing genes such as KIT, implicated in autophagic clearance of neurotoxic proteins and on mast cell and microglial-mediated inflammation; SLC24A2, implicated in synaptic plasticity associated with learning and memory; and MTMR6, implicated in phosphoinositide lipids metabolism.
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Affiliation(s)
- Rui Xia
- Institute of Molecular Medicine, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Xueqiu Jian
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, The University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
| | - Amanda L Rodrigue
- Department of Psychiatry, Harvard Medical School, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Jan Bressler
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Eric Boerwinkle
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Biqi Cui
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, The University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
- Xiangya School of Medicine, Central South University, Changsha, China
| | - Martha L Daviglus
- Institute for Minority Health Research, University of Illinois Chicago, Chicago, Illinois, USA
| | - Charles DeCarli
- Department of Neurology, University of California Davis, Sacramento, California, USA
| | - Linda C Gallo
- Department of Psychology, San Diego State University, San Diego, California, USA
| | - David C Glahn
- Department of Psychiatry, Harvard Medical School, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Emma E M Knowles
- Department of Psychiatry, Harvard Medical School, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Jee-Young Moon
- Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, New York, USA
| | - Thomas H Mosley
- The MIND Center, University of Mississippi Medical Center, Jackson, Mississippi, USA
| | - Claudia L Satizabal
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, The University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
- Department of Population Health Sciences, The University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
| | - Tamar Sofer
- Department of Medicine, Harvard Medical School, Brigham and Women's Hospital, Boston, Massachusetts, USA
- CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Wassim Tarraf
- Institute of Gerontology & Department of Healthcare Sciences, Wayne State University, Detroit, Michigan, USA
| | - Fernando Testai
- Department of Neurology and Rehabilitation, University of Illinois at Chicago, Chicago, Illinois, USA
| | - John Blangero
- Department of Human Genetics, South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville, Texas, USA
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, The University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
| | - Hector M González
- Department of Neurosciences, University of California San Diego, La Jolla, California, USA
| | - Myriam Fornage
- Institute of Molecular Medicine, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, Texas, USA
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas, USA
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Koenig Z, Yohannes MT, Nkambule LL, Zhao X, Goodrich JK, Kim HA, Wilson MW, Tiao G, Hao SP, Sahakian N, Chao KR, Walker MA, Lyu Y, Rehm HL, Neale BM, Talkowski ME, Daly MJ, Brand H, Karczewski KJ, Atkinson EG, Martin AR. A harmonized public resource of deeply sequenced diverse human genomes. Genome Res 2024; 34:796-809. [PMID: 38749656 PMCID: PMC11216312 DOI: 10.1101/gr.278378.123] [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: 08/10/2023] [Accepted: 05/07/2024] [Indexed: 05/18/2024]
Abstract
Underrepresented populations are often excluded from genomic studies owing in part to a lack of resources supporting their analyses. The 1000 Genomes Project (1kGP) and Human Genome Diversity Project (HGDP), which have recently been sequenced to high coverage, are valuable genomic resources because of the global diversity they capture and their open data sharing policies. Here, we harmonized a high-quality set of 4094 whole genomes from 80 populations in the HGDP and 1kGP with data from the Genome Aggregation Database (gnomAD) and identified over 153 million high-quality SNVs, indels, and SVs. We performed a detailed ancestry analysis of this cohort, characterizing population structure and patterns of admixture across populations, analyzing site frequency spectra, and measuring variant counts at global and subcontinental levels. We also show substantial added value from this data set compared with the prior versions of the component resources, typically combined via liftOver and variant intersection; for example, we catalog millions of new genetic variants, mostly rare, compared with previous releases. In addition to unrestricted individual-level public release, we provide detailed tutorials for conducting many of the most common quality-control steps and analyses with these data in a scalable cloud-computing environment and publicly release this new phased joint callset for use as a haplotype resource in phasing and imputation pipelines. This jointly called reference panel will serve as a key resource to support research of diverse ancestry populations.
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Affiliation(s)
- Zan Koenig
- Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
| | - Mary T Yohannes
- Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
| | - Lethukuthula L Nkambule
- Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
| | - Xuefang Zhao
- Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114, USA
| | - Julia K Goodrich
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
- Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
| | - Heesu Ally Kim
- Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
| | - Michael W Wilson
- Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
| | - Grace Tiao
- Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
| | - Stephanie P Hao
- Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114, USA
| | - Nareh Sahakian
- Broad Genomics, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, 02141, USA
| | - Katherine R Chao
- Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
| | - Mark A Walker
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
- Data Sciences Platform, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
| | - Yunfei Lyu
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts 02115, USA
| | - Heidi L Rehm
- Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
| | - Benjamin M Neale
- Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
- Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
- Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
| | - Michael E Talkowski
- Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
- Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114, USA
| | - Mark J Daly
- Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
- Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
- Department of Medicine, Harvard Medical School, Boston, Massachusetts 02115, USA
- Institute for Molecular Medicine Finland, 00290 Helsinki, Finland
| | - Harrison Brand
- Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114, USA
| | - Konrad J Karczewski
- Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
- Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
- Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
| | - Elizabeth G Atkinson
- Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas 77030, USA
| | - Alicia R Martin
- Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA;
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
- Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
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Misek SA, Fultineer A, Kalfon J, Noorbakhsh J, Boyle I, Roy P, Dempster J, Petronio L, Huang K, Saadat A, Green T, Brown A, Doench JG, Root DE, McFarland JM, Beroukhim R, Boehm JS. Germline variation contributes to false negatives in CRISPR-based experiments with varying burden across ancestries. Nat Commun 2024; 15:4892. [PMID: 38849329 PMCID: PMC11161638 DOI: 10.1038/s41467-024-48957-z] [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: 12/05/2023] [Accepted: 05/20/2024] [Indexed: 06/09/2024] Open
Abstract
Reducing disparities is vital for equitable access to precision treatments in cancer. Socioenvironmental factors are a major driver of disparities, but differences in genetic variation likely also contribute. The impact of genetic ancestry on prioritization of cancer targets in drug discovery pipelines has not been systematically explored due to the absence of pre-clinical data at the appropriate scale. Here, we analyze data from 611 genome-scale CRISPR/Cas9 viability experiments in human cell line models to identify ancestry-associated genetic dependencies essential for cell survival. Surprisingly, we find that most putative associations between ancestry and dependency arise from artifacts related to germline variants. Our analysis suggests that for 1.2-2.5% of guides, germline variants in sgRNA targeting sequences reduce cutting by the CRISPR/Cas9 nuclease, disproportionately affecting cell models derived from individuals of recent African descent. We propose three approaches to mitigate this experimental bias, enabling the scientific community to address these disparities.
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Affiliation(s)
- Sean A Misek
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
- Departments of Cancer Biology and Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
- Koch Institute, Massachusetts Institute of Technology, Cambridge, MA, 02142, USA
| | - Aaron Fultineer
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Jeremie Kalfon
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | | | - Isabella Boyle
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Priyanka Roy
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Joshua Dempster
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Lia Petronio
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Katherine Huang
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Alham Saadat
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Thomas Green
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Adam Brown
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - John G Doench
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - David E Root
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | | | - Rameen Beroukhim
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA.
- Departments of Cancer Biology and Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA.
| | - Jesse S Boehm
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA.
- Koch Institute, Massachusetts Institute of Technology, Cambridge, MA, 02142, USA.
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Crowley JJ, Cappi C, Ochoa-Panaifo ME, Frederick RM, Kook M, Wiese AD, Rancourt D, Atkinson EG, Giusti-Rodriguez P, Anderberg JL, Abramowitz JS, Adorno VR, Aguirre C, Alves GS, Alves GS, Ancalade N, Arellano Espinosa AA, Arnold PD, Ayton DM, Barbosa IG, Castano LMB, Barrera CN, Berardo MC, Berrones D, Best JR, Bigdeli TB, Burton CL, Buxbaum JD, Callahan JL, Carneiro MCB, Cepeda SL, Chazelle E, Chire JM, Munoz MC, Quiroz PC, Cobite J, Comer JS, Costa DL, Crosbie J, Cruz VO, Dager G, Daza LF, de la Rosa-Gómez A, Del Río D, Delage FZ, Dreher CB, Fay L, Fazio T, Ferrão YA, Ferreira GM, Figueroa EG, Fontenelle LF, Forero DA, Fragoso DTH, Gadad BS, Garrison SR, González A, Gonzalez LD, González MA, Gonzalez-Barrios P, Goodman WK, Grice DE, Guintivano J, Guttfreund DG, Guzick AG, Halvorsen MW, Hovey JD, Huang H, Irreño-Sotomonte J, Janssen-Aguilar R, Jensen M, Jimenez Reynolds AZ, Lujambio JAJ, Khalfe N, Knutsen MA, Lack C, Lanzagorta N, Lima MO, Longhurst MO, Lozada Martinez DA, Luna ES, Marques AH, Martinez MS, de Los Angeles Matos M, Maye CE, McGuire JF, Menezes G, Minaya C, Miño T, Mithani SM, de Oca CM, Morales-Rivero A, Moreira-de-Oliveira ME, Morris OJ, Muñoz SI, Naqqash Z, Núñez Bracho AA, Núñez Bracho BE, Rojas MCO, Olavarria Castaman LA, Balmaceda TO, Ortega I, Patel DI, Patrick AK, Paz Y Mino M, Perales Orellana JL, Stumpf BP, Peregrina T, Duarte TP, Piacsek KL, Placencia M, Prieto MB, Quarantini LC, Quarantini-Alvim Y, Ramos RT, Ramos IC, Ramos VR, Ramsey KA, Ray EV, Richter MA, Riemann BC, Rivas JC, Rosario MC, Ruggero CJ, Ruiz-Chow AA, Ruiz-Velasco A, Sagarnaga MN, Sampaio AS, Saraiva LC, Schachar RJ, Schneider SC, Schweissing EJ, Seligman LD, Shavitt RG, Soileau KJ, Stewart SE, Storch SB, Strouphauer ER, Cuevas VT, Timpano KR, la Garza BTD, Vallejo-Silva A, Vargas-Medrano J, Vásquez MI, Martinez GV, Weinzimmer SA, Yanez MA, Zai G, Zapata-Restrepo LM, Zappa LM, Zepeda-Burgos RM, Zoghbi AW, Miguel EC, Rodriguez CI, Martinez Mallen MC, Moya PR, Borda T, Moyano MB, Mattheisen M, Pereira S, Lázaro-Muñoz G, Martinez-Gonzalez KG, Pato MT, Nicolini H, Storch EA. Latin American Trans-ancestry INitiative for OCD genomics (LATINO): Study protocol. Am J Med Genet B Neuropsychiatr Genet 2024; 195:e32962. [PMID: 37946624 PMCID: PMC11076176 DOI: 10.1002/ajmg.b.32962] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 09/26/2023] [Accepted: 10/06/2023] [Indexed: 11/12/2023]
Abstract
Obsessive-compulsive disorder (OCD) is a debilitating psychiatric disorder. Worldwide, its prevalence is ~2% and its etiology is mostly unknown. Identifying biological factors contributing to OCD will elucidate underlying mechanisms and might contribute to improved treatment outcomes. Genomic studies of OCD are beginning to reveal long-sought risk loci, but >95% of the cases currently in analysis are of homogenous European ancestry. If not addressed, this Eurocentric bias will result in OCD genomic findings being more accurate for individuals of European ancestry than other ancestries, thereby contributing to health disparities in potential future applications of genomics. In this study protocol paper, we describe the Latin American Trans-ancestry INitiative for OCD genomics (LATINO, https://www.latinostudy.org). LATINO is a new network of investigators from across Latin America, the United States, and Canada who have begun to collect DNA and clinical data from 5000 richly phenotyped OCD cases of Latin American ancestry in a culturally sensitive and ethical manner. In this project, we will utilize trans-ancestry genomic analyses to accelerate the identification of OCD risk loci, fine-map putative causal variants, and improve the performance of polygenic risk scores in diverse populations. We will also capitalize on rich clinical data to examine the genetics of treatment response, biologically plausible OCD subtypes, and symptom dimensions. Additionally, LATINO will help elucidate the diversity of the clinical presentations of OCD across cultures through various trainings developed and offered in collaboration with Latin American investigators. We believe this study will advance the important goal of global mental health discovery and equity.
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Affiliation(s)
- James J Crowley
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Carolina Cappi
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Departamento de Psiquiatria, Universidade de São Paulo, São Paulo, São Paulo, Brazil
| | | | - Renee M Frederick
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, USA
| | - Minjee Kook
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, USA
| | - Andrew D Wiese
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, USA
| | - Diana Rancourt
- Department of Psychology, University of South Florida, Tampa, Florida, USA
| | - Elizabeth G Atkinson
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA
| | - Paola Giusti-Rodriguez
- Department of Psychiatry, University of Florida College of Medicine, Gainesville, Florida, USA
| | - Jacey L Anderberg
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, USA
| | - Jonathan S Abramowitz
- Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Victor R Adorno
- Hospital Psiquiátrico de Asunción, Direccion General, Asuncion, Central, Paraguay
| | - Cinthia Aguirre
- Departamento de Psiquiatría, Hospital Psiquiátrico de Asunción, Asuncion, Central, Paraguay
| | - Gilberto S Alves
- Hospital Nina Rodrigues/Universidade Federal do Maranhão (UFMA), Sao Luis do Maranhao, Maranhao, Brazil
| | - Gustavo S Alves
- Hospital Universitário Professor Edgard Santos, Serviço de Psiquiatria, Laboratório de Neuropsicofarmacologia-LANP, Universidade Federal da Bahia, Salvador, Bahia, Brazil
- Faculdade de Medicina da Bahia, Universidade Federal da Bahia, Pós-Graduação em Medicina e Saúde, Salvador, Bahia, Brazil
| | - NaEshia Ancalade
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | | | - Paul D Arnold
- The Mathison Centre for Mental Health Research & Education, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Daphne M Ayton
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, USA
| | - Izabela G Barbosa
- Departamento de Saúde Mental da Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | | | | | - María Celeste Berardo
- Centro Interdisciplinario de Tourette, TOC, TDAH y Trastornos Asociados (CITA), Buenos Aires, Buenos Aires, Argentina
| | - Dayan Berrones
- Department of Psychology, Rice University, Houston, Texas, USA
| | - John R Best
- Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada
| | - Tim B Bigdeli
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, New York, USA
- VA New York Harbor Healthcare System, Brooklyn, New York, USA
| | - Christie L Burton
- Department of Neurosciences and Mental Health, Hospital for Sick Children, Toronto, Ontario, Canada
| | - Joseph D Buxbaum
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | | | - Maria Cecília B Carneiro
- Departamento de Psiquiatria e Medicina Legal, Universidade Federal do Paraná, Curitiba, Parana, Brazil
| | - Sandra L Cepeda
- Department of Psychology, University of Miami, Coral Gables, Florida, USA
| | - Evelyn Chazelle
- Centro Interdisciplinario de Tourette, TOC, TDAH y Trastornos Asociados (CITA), Buenos Aires, Buenos Aires, Argentina
| | - Jessica M Chire
- Instituto Nacional de Salud Mental "Honorio Delgado-Hideyo Noguchi", Dirección de Niños y Adolescentes Lima, Lima, Peru
| | | | | | - Journa Cobite
- Department of Counseling Psychology, University of Houston, Houston, Texas, USA
| | - Jonathan S Comer
- Department of Psychology, Florida International University, Miami, Florida, USA
| | - Daniel L Costa
- Departamento de Psiquiatria, Universidade de São Paulo, São Paulo, São Paulo, Brazil
| | - Jennifer Crosbie
- Department of Neurosciences and Mental Health, Hospital for Sick Children, Toronto, Ontario, Canada
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Victor O Cruz
- Instituto Nacional de Salud Mental "Honorio Delgado-Hideyo Noguchi", Oficina Ejecutiva de Investigación, Lima, Lima, Peru
- School of Medicine, Universidad San Martin de Porres, Lima, Lima, Peru
| | - Guillermo Dager
- Corporación Universitaria Rafael Nuñez, Cartagena, Bolivar, Colombia
| | - Luisa F Daza
- Hospital Psiquiátrico Universitario Del Valle, Cali, Valle del Cauca, Colombia
| | - Anabel de la Rosa-Gómez
- Facultad de Estudios Superiores Iztacala, Tlalnepantla de Baz, Universidad Nacional Autónoma de México, Ciudad de Mexico, Mexico
| | | | - Fernanda Z Delage
- Departamento de Medicina Forense e Psiquiatria, Universidade Federal do Paraná, Curitiba, Parana, Brazil
| | - Carolina B Dreher
- Departamento de Psiquiatria, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
- Departamento de Psiquiatria, Clínica Médica, Porto Alegre, Rio Grande do Sul, Brazil
| | - Lucila Fay
- Centro Interdisciplinario de Tourette, TOC, TDAH y Trastornos Asociados (CITA), Buenos Aires, Buenos Aires, Argentina
| | - Tomas Fazio
- Centro Interdisciplinario de Tourette, TOC, TDAH y Trastornos Asociados (CITA), Buenos Aires, Buenos Aires, Argentina
| | - Ygor A Ferrão
- Departamento de Psiquiatria, Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil
| | - Gabriela M Ferreira
- Departamento de Medicina Forense e Psiquiatria, Universidade Federal do Paraná, Curitiba, Parana, Brazil
- Hospital de Clínicas da Universidade Federal do Paraná, Curitiba, Parana, Brazil
| | - Edith G Figueroa
- Departamento de Psiquiatría de Adultos, Instituto Nacional de Salud Mental "Honorio Delgado-Hideyo Noguchi", Lima, Lima, Peru
| | - Leonardo F Fontenelle
- Departamento de Psiquiatria e Medicina Legal, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Rio de Janeiro, Brazil
- Departamento de Psiquiatria, Instituto D'Or de Pesquisa e Ensino, Rio de Janeiro, Rio de Janeiro, Brazil
| | - Diego A Forero
- Fundación Universitaria del Área Andina, Escuela de Salud y Ciencias del Deporte, Bogota, Bogota, Colombia
| | - Daniele T H Fragoso
- Departamento de Medicina Forense e Psiquiatria, Universidade Federal do Paraná, Curitiba, Parana, Brazil
| | - Bharathi S Gadad
- Department of Psychiatry, Texas Tech University Health Sciences Center El Paso, El Paso, Texas, USA
| | | | | | - Laura D Gonzalez
- Centro Interdisciplinario de Tourette, TOC, TDAH y Trastornos Asociados (CITA), Buenos Aires, Buenos Aires, Argentina
| | - Marco A González
- Facultad de Estudios Superiores Iztacala, Tlalnepantla de Baz, Universidad Nacional Autónoma de México, Ciudad de Mexico, Mexico
| | - Polaris Gonzalez-Barrios
- Departamento de Psiquiatría, Universidad de Puerto Rico, San Juan, Puerto Rico, USA
- Universidad de Puerto Rico Campus de Ciências Médicas, San Juan, Puerto Rico, USA
| | - Wayne K Goodman
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, USA
| | - Dorothy E Grice
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Jerry Guintivano
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | | | - Andrew G Guzick
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, USA
| | - Matthew W Halvorsen
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Joseph D Hovey
- Department of Psychological Science, The University of Texas Rio Grande Valley, Edinburg, Texas, USA
| | - Hailiang Huang
- Broad Institute of MIT and Harvard, Stanley Center for Psychiatric Research, Cambridge, Massachusetts, USA
| | - Jonathan Irreño-Sotomonte
- Center for Mental Health-Cersame, School of Medicine and Health Sciences, Universidad del Rosario, Bogota, District of Colombia, Colombia
| | - Reinhard Janssen-Aguilar
- Instituto Nacional de Neurología y Neurocirugía Manuel Velasco Suarez, Subdirección de Psiquiatría, Ciudad de México, Ciudad de Mexico, Mexico
| | - Matias Jensen
- Centro de Neurociencias, Universidad de Valparaíso, Valparaiso, Chile
| | | | | | - Nasim Khalfe
- Baylor College of Medicine, School of Medicine, Houston, Texas, USA
| | - Madison A Knutsen
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, USA
- Department of Psychology, Augustana College, Rock Island, Illinois, USA
| | - Caleb Lack
- Department of Psychology, University of Central Oklahoma, Edmond, Oklahoma, USA
| | - Nuria Lanzagorta
- Departamento de Investigación Clínica, Grupo Médico Carracci, Ciudad de México, Ciudad de Mexico, Mexico
| | - Monicke O Lima
- Departamento de Psiquiatria, Universidade de São Paulo, São Paulo, São Paulo, Brazil
| | - Melanie O Longhurst
- Department of Psychiatry, Texas Tech University Health Sciences Center El Paso, El Paso, Texas, USA
| | | | - Elba S Luna
- Instituto Nacional de Salud Mental "Honorio Delgado-Hideyo Noguchi", Oficina Ejecutiva de Investigación, Lima, Lima, Peru
| | - Andrea H Marques
- National Institute of Mental Heatlh (NIMH), Bethesda, Maryland, USA
| | - Molly S Martinez
- DFW OCD Treatment Specialists, Richardson, Texas, USA
- Specialists in OCD and Anxiety Recovery (SOAR), Richardson, Texas, USA
| | - Maria de Los Angeles Matos
- Centro Interdisciplinario de Tourette, TOC, TDAH y Trastornos Asociados (CITA), Buenos Aires, Buenos Aires, Argentina
| | - Caitlyn E Maye
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, USA
| | - Joseph F McGuire
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Gabriela Menezes
- Programa de Ansiedade, Obsessões e Compulsões, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | - Charlene Minaya
- Department of Psychology, Fordham University, New York, New York, USA
| | - Tomás Miño
- Centro de Neurociencias, Universidad de Valparaíso, Valparaiso, Chile
| | - Sara M Mithani
- School of Nursing, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
| | | | | | - Maria E Moreira-de-Oliveira
- Programa de Ansiedade, Obsessões e Compulsões, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | - Olivia J Morris
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, USA
| | - Sandra I Muñoz
- Facultad de Estudios Superiores Iztacala, Tlalnepantla de Baz, Universidad Nacional Autónoma de México, Ciudad de Mexico, Mexico
| | - Zainab Naqqash
- Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada
| | | | | | | | | | - Trinidad Olivos Balmaceda
- Centro Interdisciplinario de Neurociencia de Valparaíso, Universidad de Valparaíso, Valparaiso, Valparaiso, Chile
| | - Iliana Ortega
- The Mathison Centre for Mental Health Research & Education, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Darpan I Patel
- School of Nursing, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
| | - Ainsley K Patrick
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Mariel Paz Y Mino
- Clínica de Salud Mental USFQ, Universidad San Francisco de Quito, Quito, Pichincha, Ecuador
- Universidad San Francisco de Quito, Quito, Pichincha, Ecuador
| | - Jose L Perales Orellana
- Universidad Tegnológica Privada de Santa Cruz (UTEPSA), Santa Cruz de la Sierra, Andres Ibañez, Bolivia
| | - Bárbara Perdigão Stumpf
- Departamento de Saúde Mental da Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | | | | | | | - Maritza Placencia
- Departamento Académico de Ciencias Dinámicas, Universidad Nacional Mayor de San Marcos, Lima, Lima, Peru
| | - María Belén Prieto
- Centro Interdisciplinario de Tourette, TOC, TDAH y Trastornos Asociados (CITA), Buenos Aires, Buenos Aires, Argentina
| | - Lucas C Quarantini
- Hospital Universitário Professor Edgard Santos, Serviço de Psiquiatria, Laboratório de Neuropsicofarmacologia-LANP, Universidade Federal da Bahia, Salvador, Bahia, Brazil
- Departamento de Neurociências e Saúde Mental, Faculdade de Medicina da Bahia, Universidade Federal da Bahia, Salvador, Bahia, Brazil
| | - Yana Quarantini-Alvim
- Hospital Universitário Professor Edgard Santos, Serviço de Psiquiatria, Laboratório de Neuropsicofarmacologia-LANP, Universidade Federal da Bahia, Salvador, Bahia, Brazil
- Faculdade Santa Casa, Faculdade de Psicologia, Salvador, Bahia, Brazil
| | - Renato T Ramos
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
- Department of Psychiatry, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Iaroslava C Ramos
- Department of Psychiatry, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
- Department of Psychiatry, Frederick Thompson Anxiety Disorders Centre, Toronto, Ontario, Canada
| | - Vanessa R Ramos
- Departamento de Psiquiatria, Universidade de São Paulo, São Paulo, São Paulo, Brazil
| | - Kesley A Ramsey
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Elise V Ray
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Margaret A Richter
- Department of Psychiatry, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | | | - Juan C Rivas
- Hospital Psiquiátrico Universitario Del Valle, Cali, Valle del Cauca, Colombia
- Departamento de Psiquiatría, Universidad del Valle, Cali, Valle del Cauca, Colombia
- Departamento de Psiquiatria, Universidad ICESI, Cali, Valle del Cauca, Colombia
- Departamento de Psiquiatria, Fundación Valle del Lili, Cali, Valle del Cauca, Colombia
| | - Maria C Rosario
- Departamento de Psiquiatria da, Universidade Federal de São Paulo (UNIFESP), Sao Paulo, Sao Paulo, Brazil
| | - Camilo J Ruggero
- Department of Psychology, University of North Texas, Denton, Texas, USA
| | | | - Alejandra Ruiz-Velasco
- Department of Psychiatry, Texas Tech University Health Sciences Center El Paso, El Paso, Texas, USA
| | - Melisa N Sagarnaga
- Facultad de Psicología, Universidad de Buenos Aires, Buenos Aires, Buenos Aires, Argentina
| | - Aline S Sampaio
- Hospital Universitário Professor Edgard Santos, Serviço de Psiquiatria, Laboratório de Neuropsicofarmacologia-LANP, Universidade Federal da Bahia, Salvador, Bahia, Brazil
- Faculdade de Medicina da Bahia, Universidade Federal da Bahia, Pós-Graduação em Medicina e Saúde, Salvador, Bahia, Brazil
- Departamento de Neurociências e Saúde Mental, Faculdade de Medicina da Bahia, Universidade Federal da Bahia, Salvador, Bahia, Brazil
| | - Leonardo C Saraiva
- Departamento de Psiquiatria, Universidade de São Paulo, São Paulo, São Paulo, Brazil
| | - Russell J Schachar
- Department of Neurosciences and Mental Health, Hospital for Sick Children, Toronto, Ontario, Canada
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Sophie C Schneider
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, USA
| | - Ethan J Schweissing
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, USA
| | - Laura D Seligman
- Department of Psychological Science, The University of Texas Rio Grande Valley, Edinburg, Texas, USA
| | - Roseli G Shavitt
- Departamento de Psiquiatria, Universidade de São Paulo, São Paulo, São Paulo, Brazil
| | - Keaton J Soileau
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, USA
| | - S Evelyn Stewart
- Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada
- BC Mental Health and Substance Use Services, Vancouver, British Columbia, Canada
- BC Children's Hospital Research Institute, Vancouver, British Columbia, Canada
| | - Shaina B Storch
- Washington University in St. Louis, St. Louis, Missouri, USA
| | | | - Vissente Tapia Cuevas
- Centro Interdisciplinario de Neurociencia de Valparaíso, Universidad de Valparaíso, Valparaiso, Valparaiso, Chile
| | - Kiara R Timpano
- Department of Psychology, University of Miami, Coral Gables, Florida, USA
| | | | - Alexie Vallejo-Silva
- Center for Mental Health-Cersame, School of Medicine and Health Sciences, Universidad del Rosario, Bogota, District of Colombia, Colombia
| | - Javier Vargas-Medrano
- Department of Psychiatry, Texas Tech University Health Sciences Center El Paso, El Paso, Texas, USA
| | - María I Vásquez
- Hospital Nacional Arzobispo Loayza, Servicio de Salud Mental, Lima, Lima, Peru
| | - Guadalupe Vidal Martinez
- Department of Psychiatry, Texas Tech University Health Sciences Center El Paso, El Paso, Texas, USA
| | - Saira A Weinzimmer
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, USA
| | - Mauricio A Yanez
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, USA
| | - Gwyneth Zai
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Department of Molecular Brain Sciences, Centre for Addiction and Mental Health, Neurogenetics Section, Toronto, Ontario, Canada
| | - Lina M Zapata-Restrepo
- Departamento de Psiquiatria, Fundación Valle del Lili, Cali, Valle del Cauca, Colombia
- Facultad de Ciencias de la Salud, Universidad ICESI, Cali, Valle, Colombia
- Department of Neurology, Global Brain Health Institute-University of California San Francisco, San Francisco, California, USA
| | - Luz M Zappa
- Centro Interdisciplinario de Tourette, TOC, TDAH y Trastornos Asociados (CITA), Buenos Aires, Buenos Aires, Argentina
- Departamento de Salud Mental, Hospital de Niños Ricardo Gutierrez, Buenos Aires, Buenos Aires, Argentina
- Hospital Universitario Austral, Materno Infantil, Buenos Aires, Buenos Aires, Argentina
| | - Raquel M Zepeda-Burgos
- Centro de Investigación en Ciencias y Humanidades, Universidad Dr. José Matías Delgado, Santa Tecla, La Libertad, El Salvador
| | - Anthony W Zoghbi
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, USA
- Department of Psychiatry, New York State Psychiatric Institute, New York, New York, USA
| | - Euripedes C Miguel
- Departamento de Psiquiatria, Universidade de São Paulo, São Paulo, São Paulo, Brazil
| | - Carolyn I Rodriguez
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California, USA
- Department of Psychiatry, Temerty Faculty of Medicine, Veterans Affairs Palo Alto Health Care System, Palo Alto, California, USA
| | | | - Pablo R Moya
- Universidad de Valparaíso, Instituto de Fisiología Valparaiso, Valparaiso, Chile
- Centro Interdisciplinario de Neurociencia de Valparaiso (CINV), Valparaiso, Chile
| | - Tania Borda
- Instituto Realize, Buenos Aires, Buenos Aires, Argentina
- Facultad de Psicología, Universidad Catolica Argentina, Buenos Aires, Buenos Aires, Argentina
| | - María Beatriz Moyano
- Centro Interdisciplinario de Tourette, TOC, TDAH y Trastornos Asociados (CITA), Buenos Aires, Buenos Aires, Argentina
- Asociación de Psiquiatras Argentinos (APSA), Buenos Aires, Buenos Aires, Argentina
- Asociación de Psiquiatras Argentinos (APSA), Presidente del Capítulo de Investigacion en Psiquiatria, Buenos Aires, Buenos Aires, Argentina
| | - Manuel Mattheisen
- Department of Community Health and Epidemiology & Faculty of Computer Science, Dalhousie University, Halifax, Nova Scotia, Canada
- LMU Munich, Institute of Psychiatric Phenomics and Genomics (IPPG), Munich, Germany
| | - Stacey Pereira
- Baylor College of Medicine, Center for Medical Ethics and Health Policy, Houston, Texas, USA
| | - Gabriel Lázaro-Muñoz
- Center for Bioethics, Harvard University School of Medicine, Boston, Massachusetts, USA
- Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts, USA
| | | | - Michele T Pato
- Department of Psychiatry, Rutgers University-Robert Wood Johnson Medical School, Piscataway, New Jersey, USA
| | - Humberto Nicolini
- Departamento de Psiquiatría, Ciudad de México, Grupo Médico Carracci, Ciudad de Mexico, Mexico
- Laboratorio de Genómica de Enfermedades Psiquiátricas y Neurodegenerativas, Ciudad de México, Instituto Nacional de Medicina Genómica, Ciudad de Mexico, Mexico
| | - Eric A Storch
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, USA
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Benjamin KJM, Chen Q, Eagles NJ, Huuki-Myers LA, Collado-Torres L, Stolz JM, Pertea G, Shin JH, Paquola ACM, Hyde TM, Kleinman JE, Jaffe AE, Han S, Weinberger DR. Analysis of gene expression in the postmortem brain of neurotypical Black Americans reveals contributions of genetic ancestry. Nat Neurosci 2024; 27:1064-1074. [PMID: 38769152 PMCID: PMC11156587 DOI: 10.1038/s41593-024-01636-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Accepted: 03/29/2024] [Indexed: 05/22/2024]
Abstract
Ancestral differences in genomic variation affect the regulation of gene expression; however, most gene expression studies have been limited to European ancestry samples or adjusted to identify ancestry-independent associations. Here, we instead examined the impact of genetic ancestry on gene expression and DNA methylation in the postmortem brain tissue of admixed Black American neurotypical individuals to identify ancestry-dependent and ancestry-independent contributions. Ancestry-associated differentially expressed genes (DEGs), transcripts and gene networks, while notably not implicating neurons, are enriched for genes related to the immune response and vascular tissue and explain up to 26% of heritability for ischemic stroke, 27% of heritability for Parkinson disease and 30% of heritability for Alzheimer's disease. Ancestry-associated DEGs also show general enrichment for the heritability of diverse immune-related traits but depletion for psychiatric-related traits. We also compared Black and non-Hispanic white Americans, confirming most ancestry-associated DEGs. Our results delineate the extent to which genetic ancestry affects differences in gene expression in the human brain and the implications for brain illness risk.
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Affiliation(s)
- Kynon J M Benjamin
- Lieber Institute for Brain Development, Baltimore, MD, USA.
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
| | - Qiang Chen
- Lieber Institute for Brain Development, Baltimore, MD, USA
| | | | | | - Leonardo Collado-Torres
- Lieber Institute for Brain Development, Baltimore, MD, USA
- Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA
| | - Joshua M Stolz
- Lieber Institute for Brain Development, Baltimore, MD, USA
| | - Geo Pertea
- Lieber Institute for Brain Development, Baltimore, MD, USA
| | - Joo Heon Shin
- Lieber Institute for Brain Development, Baltimore, MD, USA
| | - Apuã C M Paquola
- Lieber Institute for Brain Development, Baltimore, MD, USA
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Thomas M Hyde
- Lieber Institute for Brain Development, Baltimore, MD, USA
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Joel E Kleinman
- Lieber Institute for Brain Development, Baltimore, MD, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Andrew E Jaffe
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Neumora Therapeutics, Watertown, MA, USA
| | - Shizhong Han
- Lieber Institute for Brain Development, Baltimore, MD, USA.
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
| | - Daniel R Weinberger
- Lieber Institute for Brain Development, Baltimore, MD, USA.
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
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Croock D, Swart Y, Schurz H, Petersen DC, Möller M, Uren C. Data Harmonization Guidelines to Combine Multi-platform Genomic Data from Admixed Populations and Boost Power in Genome-Wide Association Studies. Curr Protoc 2024; 4:e1055. [PMID: 38837690 DOI: 10.1002/cpz1.1055] [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] [Indexed: 06/07/2024]
Abstract
Data harmonization involves combining data from multiple independent sources and processing the data to produce one uniform dataset. Merging separate genotypes or whole-genome sequencing datasets has been proposed as a strategy to increase the statistical power of association tests by increasing the effective sample size. However, data harmonization is not a widely adopted strategy due to the difficulties with merging data (including confounding produced by batch effects and population stratification). Detailed data harmonization protocols are scarce and are often conflicting. Moreover, data harmonization protocols that accommodate samples of admixed ancestry are practically non-existent. Existing data harmonization procedures must be modified to ensure the heterogeneous ancestry of admixed individuals is incorporated into additional downstream analyses without confounding results. Here, we propose a set of guidelines for merging multi-platform genetic data from admixed samples that can be adopted by any investigator with elementary bioinformatics experience. We have applied these guidelines to aggregate 1544 tuberculosis (TB) case-control samples from six separate in-house datasets and conducted a genome-wide association study (GWAS) of TB susceptibility. The GWAS performed on the merged dataset had improved power over analyzing the datasets individually and produced summary statistics free from bias introduced by batch effects and population stratification. © 2024 Wiley Periodicals LLC. Basic Protocol 1: Processing separate datasets comprising array genotype data Alternate Protocol 1: Processing separate datasets comprising array genotype and whole-genome sequencing data Alternate Protocol 2: Performing imputation using a local reference panel Basic Protocol 2: Merging separate datasets Basic Protocol 3: Ancestry inference using ADMIXTURE and RFMix Basic Protocol 4: Batch effect correction using pseudo-case-control comparisons.
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Affiliation(s)
- Dayna Croock
- DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Stellenbosch, South Africa
| | - Yolandi Swart
- DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Stellenbosch, South Africa
| | - Haiko Schurz
- DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Stellenbosch, South Africa
| | - Desiree C Petersen
- DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Stellenbosch, South Africa
| | - Marlo Möller
- DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Stellenbosch, South Africa
- Centre for Bioinformatics and Computational Biology, Stellenbosch University, Stellenbosch, South Africa
| | - Caitlin Uren
- DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Stellenbosch, South Africa
- Centre for Bioinformatics and Computational Biology, Stellenbosch University, Stellenbosch, South Africa
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Lyu Y, Wang F, Cheng H, Han J, Dang R, Xia X, Wang H, Zhong J, Lenstra JA, Zhang H, Han J, MacHugh DE, Medugorac I, Upadhyay M, Leonard AS, Ding H, Yang X, Wang MS, Quji S, Zhuzha B, Quzhen P, Wangmu S, Cangjue N, Wa D, Ma W, Liu J, Zhang J, Huang B, Qi X, Li F, Huang Y, Ma Y, Wang Y, Gao Y, Lu W, Lei C, Chen N. Recent selection and introgression facilitated high-altitude adaptation in cattle. Sci Bull (Beijing) 2024:S2095-9273(24)00380-3. [PMID: 38945748 DOI: 10.1016/j.scib.2024.05.030] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 05/09/2024] [Accepted: 05/13/2024] [Indexed: 07/02/2024]
Abstract
During the past 3000 years, cattle on the Qinghai-Xizang Plateau have developed adaptive phenotypes under the selective pressure of hypoxia, ultraviolet (UV) radiation, and extreme cold. The genetic mechanism underlying this rapid adaptation is not yet well understood. Here, we present whole-genome resequencing data for 258 cattle from 32 cattle breeds/populations, including 89 Tibetan cattle representing eight populations distributed at altitudes ranging from 3400 m to 4300 m. Our genomic analysis revealed that Tibetan cattle exhibited a continuous phylogeographic cline from the East Asian taurine to the South Asian indicine ancestries. We found that recently selected genes in Tibetan cattle were related to body size (HMGA2 and NCAPG) and energy expenditure (DUOXA2). We identified signals of sympatric introgression from yak into Tibetan cattle at different altitudes, covering 0.64%-3.26% of their genomes, which included introgressed genes responsible for hypoxia response (EGLN1), cold adaptation (LRP11), DNA damage repair (LATS1), and UV radiation resistance (GNPAT). We observed that introgressed yak alleles were associated with noncoding variants, including those in present EGLN1. In Tibetan cattle, three yak introgressed SNPs in the EGLN1 promoter region reduced the expression of EGLN1, suggesting that these genomic variants enhance hypoxia tolerance. Taken together, our results indicated complex adaptation processes in Tibetan cattle, where recently selected genes and introgressed yak alleles jointly facilitated rapid adaptation to high-altitude environments.
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Affiliation(s)
- Yang Lyu
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China; Key Laboratory of Animal Production, Product Quality, and Security, Ministry of Education, College of Animal Science and Technology, Jilin Agricultural University, Changchun 130118, China
| | - Fuwen Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Haijian Cheng
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China; Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Shandong Key Lab of Animal Disease Control and Breeding, Jinan 250000, China
| | - Jing Han
- College of Veterinary Medicine, Northwest A&F University, Yangling 712100, China
| | - Ruihua Dang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Xiaoting Xia
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Hui Wang
- Key Laboratory of Qinghai-Tibetan Plateau Animal Genetic Resource Reservation and Utilization, Sichuan Province and Ministry of Education, Southwest Minzu University, Chengdu 610000, China
| | - Jincheng Zhong
- Key Laboratory of Qinghai-Tibetan Plateau Animal Genetic Resource Reservation and Utilization, Sichuan Province and Ministry of Education, Southwest Minzu University, Chengdu 610000, China
| | - Johannes A Lenstra
- Faculty of Veterinary Medicine, Utrecht University, Utrecht 3584 CM, The Netherlands
| | - Hucai Zhang
- Institute for Ecological Research and Pollution Control of Plateau Lakes, School of Ecology and Environmental Science, Yunnan University, Kunming 650500, China; Southwest United Graduate School, Kunming 650500, China
| | - Jianlin Han
- Yazhouwan National Laboratory, Sanya 572024, China; CAAS-ILRI Joint Laboratory on Livestock and Forage Genetic Resources, Institute of Animal Science, Chinese Academy of Agriculture Sciences (CAAS), Beijing 100000, China
| | - David E MacHugh
- Animal Genomics Laboratory, UCD School of Agriculture and Food Science, University College Dublin, Dublin D04 V1W8, Ireland; UCD Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin D04 V1W8, Ireland
| | - Ivica Medugorac
- Population Genomics Group, Department of Veterinary Sciences, LMU Munich, Martinsried 82152, Germany
| | - Maulik Upadhyay
- Population Genomics Group, Department of Veterinary Sciences, LMU Munich, Martinsried 82152, Germany
| | - Alexander S Leonard
- Animal Genomics, ETH Zurich, Universitaetstrasse 2, Zurich 8006, Switzerland
| | - He Ding
- Key Laboratory of Animal Production, Product Quality, and Security, Ministry of Education, College of Animal Science and Technology, Jilin Agricultural University, Changchun 130118, China
| | - Xiaorui Yang
- Key Laboratory of Animal Production, Product Quality, and Security, Ministry of Education, College of Animal Science and Technology, Jilin Agricultural University, Changchun 130118, China
| | - Ming-Shan Wang
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | - Suolang Quji
- Institute of Animal Husbandry and Veterinary Science, Xizang Autonomous Region Academy of Agricultural and Animal Husbandry Sciences, Lhasa 850000, China
| | - Basang Zhuzha
- Institute of Animal Husbandry and Veterinary Science, Xizang Autonomous Region Academy of Agricultural and Animal Husbandry Sciences, Lhasa 850000, China
| | - Pubu Quzhen
- Shigatse City Kangma County Shaogang Township Agriculture and Animal Husbandry Comprehensive Service Center, Shigatse 857000, China
| | - Silang Wangmu
- Institute of Animal Husbandry and Veterinary Science, Xizang Autonomous Region Academy of Agricultural and Animal Husbandry Sciences, Lhasa 850000, China
| | - Nima Cangjue
- Institute of Animal Husbandry and Veterinary Science, Xizang Autonomous Region Academy of Agricultural and Animal Husbandry Sciences, Lhasa 850000, China
| | - Da Wa
- Institute of Animal Husbandry and Veterinary Science, Xizang Autonomous Region Academy of Agricultural and Animal Husbandry Sciences, Lhasa 850000, China
| | - Weidong Ma
- Shaanxi Province Agriculture & Husbandry Breeding Farm, Fufeng 722203, China
| | - Jianyong Liu
- Yunnan Academy of Grassland and Animal Science, Kunming 650500, China
| | - Jicai Zhang
- Yunnan Academy of Grassland and Animal Science, Kunming 650500, China
| | - Bizhi Huang
- Yunnan Academy of Grassland and Animal Science, Kunming 650500, China
| | - Xingshan Qi
- Animal Husbandry Bureau in Biyang County, Biyang 463700, China
| | - Fuqiang Li
- Hunan Tianhua Industrial Corporation Ltd., Lianyuan 417126, China
| | - Yongzhen Huang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Yun Ma
- Key Laboratory of Ruminant Molecular and Cellular Breeding of Ningxia Hui Autonomous Region, School of Agriculture, Ningxia University, Yinchuan 750000, China
| | - Yu Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Yuanpeng Gao
- College of Veterinary Medicine, Northwest A&F University, Yangling 712100, China.
| | - Wenfa Lu
- Key Laboratory of Animal Production, Product Quality, and Security, Ministry of Education, College of Animal Science and Technology, Jilin Agricultural University, Changchun 130118, China; Yazhouwan National Laboratory, Sanya 572024, China.
| | - Chuzhao Lei
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China.
| | - Ningbo Chen
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China.
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Miranda JP, Pereira A, Corvalán C, Miquel JF, Alberti G, Gana JC, Santos JL. Genetic determinants of serum bilirubin using inferred native American gene variants in Chilean adolescents. Front Genet 2024; 15:1382103. [PMID: 38826804 PMCID: PMC11140026 DOI: 10.3389/fgene.2024.1382103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Accepted: 04/18/2024] [Indexed: 06/04/2024] Open
Abstract
Gene variants in the UGT1A1 gene are strongly associated with circulating bilirubin levels in several populations, as well as other variants of modest effect across the genome. However, the effects of such variants are unknown regarding the Native American ancestry of the admixed Latino population. Our objective was to assess the Native American genetic determinants of serum bilirubin in Chilean admixed adolescents using the local ancestry deconvolution approach. We measured total serum bilirubin levels in 707 adolescents of the Chilean Growth and Obesity Cohort Study (GOCS) and performed high-density genotyping using the Illumina-MEGA array (>1.7 million genotypes). We constructed a local ancestry reference panel with participants from the 1000 Genomes Project, the Human Genome Diversity Project, and our GOCS cohort. Then, we inferred and isolated haplotype tracts of Native American, European, or African origin to perform genome-wide association studies. In the whole cohort, the rs887829 variant and others near UGT1A1 were the unique signals achieving genome-wide statistical significance (b = 0.30; p = 3.34 × 10-57). After applying deconvolution methods, we found that significance is also maintained in Native American (b = 0.35; p = 3.29 × 10-17) and European (b = 0.28; p = 1.14 × 10-23) ancestry components. The rs887829 variant explained a higher percentage of the variance of bilirubin in the Native American (37.6%) compared to European ancestry (28.4%). In Native American ancestry, carriers of the TT genotype of this variant averaged 4-fold higher bilirubinemia compared to the CC genotype (p = 2.82 × 10-12). We showed for the first time that UGT1A1 variants are the primary determinant of bilirubin levels in Native American ancestry, confirming its pan-ethnic relevance. Our study illustrates the general value of the local ancestry deconvolution approach to assessing isolated ancestry effects in admixed populations.
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Affiliation(s)
- José P. Miranda
- Department of Nutrition, Diabetes, and Metabolism, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
- School of Medicine, PhD in Epidemiology Program, Pontificia Universidad Católica de Chile, Santiago, Chile
- Advanced Center for Chronic Diseases (ACCDiS), Pontificia Universidad Católica de Chile and Universidad de Chile, Santiago, Chile
| | - Ana Pereira
- Instituto de Nutrición y Tecnología de los Alimentos INTA, Universidad de Chile, Santiago, Chile
| | - Camila Corvalán
- Instituto de Nutrición y Tecnología de los Alimentos INTA, Universidad de Chile, Santiago, Chile
| | - Juan F. Miquel
- Department of Gastroenterology, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Gigliola Alberti
- Pediatrics Division, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
- Department of Gastroenterology and Pediatric Nutrition, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Juan C. Gana
- Pediatrics Division, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
- Department of Gastroenterology and Pediatric Nutrition, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - José L. Santos
- Department of Nutrition, Diabetes, and Metabolism, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
- School of Medicine, PhD in Epidemiology Program, Pontificia Universidad Católica de Chile, Santiago, Chile
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Hong SC, Muyas F, Cortés-Ciriano I, Hormoz S. scAI-SNP: a method for inferring ancestry from single-cell data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.14.594208. [PMID: 38798590 PMCID: PMC11118306 DOI: 10.1101/2024.05.14.594208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
Collaborative efforts, such as the Human Cell Atlas, are rapidly accumulating large amounts of single-cell data. To ensure that single-cell atlases are representative of human genetic diversity, we need to determine the ancestry of the donors from whom single-cell data are generated. Self-reporting of race and ethnicity, although important, can be biased and is not always available for the datasets already collected. Here, we introduce scAI-SNP, a tool to infer ancestry directly from single-cell genomics data. To train scAI-SNP, we identified 4.5 million ancestry-informative single-nucleotide polymorphisms (SNPs) in the 1000 Genomes Project dataset across 3201 individuals from 26 population groups. For a query single-cell data set, scAI-SNP uses these ancestry-informative SNPs to compute the contribution of each of the 26 population groups to the ancestry of the donor from whom the cells were obtained. Using diverse single-cell data sets with matched whole-genome sequencing data, we show that scAI-SNP is robust to the sparsity of single-cell data, can accurately and consistently infer ancestry from samples derived from diverse types of tissues and cancer cells, and can be applied to different modalities of single-cell profiling assays, such as single-cell RNA-seq and single-cell ATAC-seq. Finally, we argue that ensuring that single-cell atlases represent diverse ancestry, ideally alongside race and ethnicity, is ultimately important for improved and equitable health outcomes by accounting for human diversity.
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Affiliation(s)
- Sung Chul Hong
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA 02215, USA
| | - Francesc Muyas
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, Cambridge CB10 1SD, UK
| | - Isidro Cortés-Ciriano
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, Cambridge CB10 1SD, UK
| | - Sahand Hormoz
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA 02215, USA
- Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
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43
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Zhen X, Betti MJ, Kars ME, Patterson A, Medina-Torres EA, Scheffler Mendoza SC, Herrera Sánchez DA, Lopez-Herrera G, Svyryd Y, Mutchinick OM, Gamazon E, Rathmell JC, Itan Y, Markle J, O’Farrill Romanillos P, Lugo-Reyes SO, Martinez-Barricarte R. Molecular and clinical characterization of a founder mutation causing G6PC3 deficiency. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.13.24307299. [PMID: 38798393 PMCID: PMC11118594 DOI: 10.1101/2024.05.13.24307299] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
Background G6PC3 deficiency is a rare genetic disorder that causes syndromic congenital neutropenia. It is driven by the intracellular accumulation of a metabolite named 1,5-anhydroglucitol-6-phosphate (1,5-AG6P) that inhibits glycolysis. Patients display heterogeneous extra-hematological manifestations, contributing to delayed diagnosis. Objective The G6PC3 c.210delC variant has been identified in patients of Mexican origin. We set out to study the origin and functional consequence of this mutation. Furthermore, we sought to characterize the clinical phenotypes caused by it. Methods Using whole-genome sequencing data, we conducted haplotype analysis to estimate the age of this allele and traced its ancestral origin. We examined how this mutation affected G6PC3 protein expression and performed extracellular flux assays on patient-derived cells to characterize how this mutation impacts glycolysis. Finally, we compared the clinical presentations of patients with the c.210delC mutation relative to other G6PC3 deficient patients published to date. Results Based on the length of haplotypes shared amongst ten carriers of the G6PC3 c.210delC mutation, we estimated that this variant originated in a common ancestor of indigenous American origin. The mutation causes a frameshift that introduces a premature stop codon, leading to a complete loss of G6PC3 protein expression. When treated with 1,5-anhydroglucitol (1,5-AG), the precursor to 1,5-AG6P, patient-derived cells exhibited markedly reduced engagement of glycolysis. Clinically, c.210delC carriers display all the clinical features of syndromic severe congenital neutropenia type 4 observed in prior reports of G6PC3 deficiency. Conclusion The G6PC3 c.210delC is a loss-of-function mutation that arose from a founder effect in the indigenous Mexican population. These findings may facilitate the diagnosis of additional patients in this geographical area. Moreover, the in vitro 1,5-AG-dependent functional assay used in our study could be employed to assess the pathogenicity of additional G6PC3 variants.
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Affiliation(s)
- Xin Zhen
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Division of Molecular Pathogenesis, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Michael J Betti
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Meltem Ece Kars
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Andrew Patterson
- Division of Molecular Pathogenesis, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Center for Immunobiology, Nashville, TN, USA
| | | | | | | | - Gabriela Lopez-Herrera
- Immune deficiencies laboratory, National Institute of Pediatrics, Health Secretariat, Mexico City, Mexico
| | - Yevgeniya Svyryd
- Department of Genetics, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Osvaldo M. Mutchinick
- Department of Genetics, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Eric Gamazon
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jeffrey C Rathmell
- Division of Molecular Pathogenesis, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Center for Immunobiology, Nashville, TN, USA
- Vanderbilt Institute for Infection, Immunology and Inflammation, Nashville, TN, USA
| | - Yuval Itan
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Janet Markle
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Division of Molecular Pathogenesis, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Center for Immunobiology, Nashville, TN, USA
- Vanderbilt Institute for Infection, Immunology and Inflammation, Nashville, TN, USA
| | | | - Saul Oswaldo Lugo-Reyes
- Immune deficiencies laboratory, National Institute of Pediatrics, Health Secretariat, Mexico City, Mexico
| | - Ruben Martinez-Barricarte
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Division of Molecular Pathogenesis, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Center for Immunobiology, Nashville, TN, USA
- Vanderbilt Institute for Infection, Immunology and Inflammation, Nashville, TN, USA
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Stoneman HR, Price A, Trout NS, Lamont R, Tifour S, Pozdeyev N, Crooks K, Lin M, Rafaels N, Gignoux CR, Marker KM, Hendricks AE. Characterizing substructure via mixture modeling in large-scale genetic summary statistics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.29.577805. [PMID: 38766180 PMCID: PMC11100604 DOI: 10.1101/2024.01.29.577805] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Genetic summary data are broadly accessible and highly useful including for risk prediction, causal inference, fine mapping, and incorporation of external controls. However, collapsing individual-level data into groups masks intra- and inter-sample heterogeneity, leading to confounding, reduced power, and bias. Ultimately, unaccounted substructure limits summary data usability, especially for understudied or admixed populations. Here, we present Summix2, a comprehensive set of methods and software based on a computationally efficient mixture model to estimate and adjust for substructure in genetic summary data. In extensive simulations and application to public data, Summix2 characterizes finer-scale population structure, identifies ascertainment bias, and identifies potential regions of selection due to local substructure deviation. Summix2 increases the robust use of diverse publicly available summary data resulting in improved and more equitable research.
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Affiliation(s)
- Hayley R Stoneman
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Human Medical Genetics and Genomics Program, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Adelle Price
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO 80204, USA
| | - Nikole Scribner Trout
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO 80204, USA
| | - Riley Lamont
- Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO 80204, USA
| | - Souha Tifour
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO 80204, USA
| | - Nikita Pozdeyev
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Kristy Crooks
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Department of Pathology, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Meng Lin
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Nicholas Rafaels
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Christopher R Gignoux
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Human Medical Genetics and Genomics Program, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Katie M Marker
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Human Medical Genetics and Genomics Program, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Audrey E Hendricks
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Human Medical Genetics and Genomics Program, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO 80204, USA
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45
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Williams CM, O'Connell J, Freyman WA, Gignoux CR, Ramachandran S, Williams AL. Phasing millions of samples achieves near perfect accuracy, enabling parent-of-origin classification of variants. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.06.592816. [PMID: 38766004 PMCID: PMC11100733 DOI: 10.1101/2024.05.06.592816] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Haplotype phasing, the process of determining which genetic variants are physically located on the same chromosome, is crucial for various genetic analyses. In this study, we first benchmark SHAPEIT and Beagle, two state-of-the-art phasing methods, on two large datasets: > 8 million diverse, research-consented 23andMe, Inc. customers and the UK Biobank (UKB). We find that both perform exceptionally well. Beagle's median switch error rate (SER) (after excluding single SNP switches) in white British trios from UKB is 0.026% compared to 0.00% for European ancestry 23andMe research participants; 55.6% of European ancestry 23andMe research participants have zero non-single SNP switches, compared to 42.4% of white British trios. South Asian ancestry 23andMe research participants have the highest median SER amongst the 23andMe populations, but it is still remarkably low at 0.46%. We also investigate the relationship between identity-by-descent (IBD) and SER, finding that switch errors tend to occur in regions of little or no IBD segment coverage. SHAPEIT and Beagle excel at 'intra-chromosomal' phasing, but lack the ability to phase across chromosomes, motivating us to develop an inter-chromosomal phasing method, called HAPTIC ( HAP lotype TI ling and C lustering), that assigns paternal and maternal variants discretely genome-wide. Our approach uses identity-by-descent (IBD) segments to phase blocks of variants on different chromosomes. HAPTIC represents the segments a focal individual shares with their relatives as nodes in a signed graph and performs bipartite clustering on the signed graph using spectral clustering. We test HAPTIC on 1022 UKB trios, yielding a median phase error of 0.08% in regions covered by IBD segments (33.5% of sites). We also ran HAPTIC in the 23andMe database and found a median phase error rate (the rate of mismatching alleles between the inferred and true phase) of 0.92% in Europeans (93.8% of sites) and 0.09% in admixed Africans (92.7% of sites). HAPTIC's precision depends heavily on data from relatives, so will increase as datasets grow larger and more diverse. HAPTIC enables analyses that require the parent-of-origin of variants, such as association studies and ancestry inference of untyped parents.
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46
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Goli RC, Chishi KG, Ganguly I, Singh S, Dixit S, Rathi P, Diwakar V, Sree C C, Limbalkar OM, Sukhija N, Kanaka K. Global and Local Ancestry and its Importance: A Review. Curr Genomics 2024; 25:237-260. [PMID: 39156729 PMCID: PMC11327809 DOI: 10.2174/0113892029298909240426094055] [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: 01/13/2024] [Revised: 03/02/2024] [Accepted: 03/11/2024] [Indexed: 08/20/2024] Open
Abstract
The fastest way to significantly change the composition of a population is through admixture, an evolutionary mechanism. In animal breeding history, genetic admixture has provided both short-term and long-term advantages by utilizing the phenomenon of complementarity and heterosis in several traits and genetic diversity, respectively. The traditional method of admixture analysis by pedigree records has now been replaced greatly by genome-wide marker data that enables more precise estimations. Among these markers, SNPs have been the popular choice since they are cost-effective, not so laborious, and automation of genotyping is easy. Certain markers can suggest the possibility of a population's origin from a sample of DNA where the source individual is unknown or unwilling to disclose their lineage, which are called Ancestry-Informative Markers (AIMs). Revealing admixture level at the locus-specific level is termed as local ancestry and can be exploited to identify signs of recent selective response and can account for genetic drift. Considering the importance of genetic admixture and local ancestry, in this mini-review, both concepts are illustrated, encompassing basics, their estimation/identification methods, tools/software used and their applications.
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Affiliation(s)
| | - Kiyevi G. Chishi
- ICAR-National Dairy Research Institute, Karnal, 132001, Haryana, India
| | - Indrajit Ganguly
- ICAR-National Bureau of Animal Genetic Resources, Karnal, 132001, Haryana, India
| | - Sanjeev Singh
- ICAR-National Bureau of Animal Genetic Resources, Karnal, 132001, Haryana, India
| | - S.P. Dixit
- ICAR-National Bureau of Animal Genetic Resources, Karnal, 132001, Haryana, India
| | - Pallavi Rathi
- ICAR-National Dairy Research Institute, Karnal, 132001, Haryana, India
| | - Vikas Diwakar
- ICAR-National Dairy Research Institute, Karnal, 132001, Haryana, India
| | - Chandana Sree C
- ICAR-National Dairy Research Institute, Karnal, 132001, Haryana, India
| | | | - Nidhi Sukhija
- ICAR-National Dairy Research Institute, Karnal, 132001, Haryana, India
- Central Tasar Research and Training Institute, Ranchi, 835303, Jharkhand, India
| | - K.K Kanaka
- ICAR- Indian Institute of Agricultural Biotechnology, Ranchi, 834010, Jharkhand, India
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47
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Sun Q, Yang Y, Rosen JD, Chen J, Li X, Guan W, Jiang MZ, Wen J, Pace RG, Blackman SM, Bamshad MJ, Gibson RL, Cutting GR, O'Neal WK, Knowles MR, Kooperberg C, Reiner AP, Raffield LM, Carson AP, Rich SS, Rotter JI, Loos RJF, Kenny E, Jaeger BC, Min YI, Fuchsberger C, Li Y. MagicalRsq-X: A cross-cohort transferable genotype imputation quality metric. Am J Hum Genet 2024; 111:990-995. [PMID: 38636510 PMCID: PMC11080605 DOI: 10.1016/j.ajhg.2024.04.001] [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: 01/25/2024] [Revised: 03/29/2024] [Accepted: 04/01/2024] [Indexed: 04/20/2024] Open
Abstract
Since genotype imputation was introduced, researchers have been relying on the estimated imputation quality from imputation software to perform post-imputation quality control (QC). However, this quality estimate (denoted as Rsq) performs less well for lower-frequency variants. We recently published MagicalRsq, a machine-learning-based imputation quality calibration, which leverages additional typed markers from the same cohort and outperforms Rsq as a QC metric. In this work, we extended the original MagicalRsq to allow cross-cohort model training and named the new model MagicalRsq-X. We removed the cohort-specific estimated minor allele frequency and included linkage disequilibrium scores and recombination rates as additional features. Leveraging whole-genome sequencing data from TOPMed, specifically participants in the BioMe, JHS, WHI, and MESA studies, we performed comprehensive cross-cohort evaluations for predominantly European and African ancestral individuals based on their inferred global ancestry with the 1000 Genomes and Human Genome Diversity Project data as reference. Our results suggest MagicalRsq-X outperforms Rsq in almost every setting, with 7.3%-14.4% improvement in squared Pearson correlation with true R2, corresponding to 85-218 K variant gains. We further developed a metric to quantify the genetic distances of a target cohort relative to a reference cohort and showed that such metric largely explained the performance of MagicalRsq-X models. Finally, we found MagicalRsq-X saved up to 53 known genome-wide significant variants in one of the largest blood cell trait GWASs that would be missed using the original Rsq for QC. In conclusion, MagicalRsq-X shows superiority for post-imputation QC and benefits genetic studies by distinguishing well and poorly imputed lower-frequency variants.
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Affiliation(s)
- Quan Sun
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Yingxi Yang
- Department of Statistics and Data Science, Yale University, New Haven, CT 06520, USA
| | - Jonathan D Rosen
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jiawen Chen
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Xihao Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Wyliena Guan
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Min-Zhi Jiang
- Department of Applied Physical Sciences, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jia Wen
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Rhonda G Pace
- Marsico Lung Institute/UNC CF Research Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Scott M Blackman
- Division of Pediatric Endocrinology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Michael J Bamshad
- Department of Pediatrics, University of Washington, Seattle, WA 98105, USA; Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Ronald L Gibson
- Department of Pediatrics, University of Washington, Seattle, WA 98105, USA
| | - Garry R Cutting
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Wanda K O'Neal
- Marsico Lung Institute/UNC CF Research Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Michael R Knowles
- Marsico Lung Institute/UNC CF Research Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - Alexander P Reiner
- Department of Epidemiology, University of Washington, Seattle, WA 98195, USA
| | - Laura M Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - April P Carson
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL 35249, USA
| | - Stephen S Rich
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, VA 22908, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York City, NY 10029, USA; Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Eimear Kenny
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York City, NY 10029, USA
| | - Byron C Jaeger
- Wake Forest School of Medicine, Department of Biostatistics and Data Science, Wake Forest University, Winston-Salem, NC 27109, USA
| | - Yuan-I Min
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - Christian Fuchsberger
- Institute for Biomedicine, Eurac Research (affiliated with the University of Lübeck), Bolzano, Italy.
| | - Yun Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
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48
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Vilà-Valls L, Abdeli A, Lucas-Sánchez M, Bekada A, Calafell F, Benhassine T, Comas D. Understanding the genomic heterogeneity of North African Imazighen: from broad to microgeographical perspectives. Sci Rep 2024; 14:9979. [PMID: 38693301 PMCID: PMC11063056 DOI: 10.1038/s41598-024-60568-8] [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: 02/01/2024] [Accepted: 04/24/2024] [Indexed: 05/03/2024] Open
Abstract
The strategic location of North Africa has led to cultural and demographic shifts, shaping its genetic structure. Historical migrations brought different genetic components that are evident in present-day North African genomes, along with autochthonous components. The Imazighen (plural of Amazigh) are believed to be the descendants of autochthonous North Africans and speak various Amazigh languages, which belong to the Afro-Asiatic language family. However, the arrival of different human groups, especially during the Arab conquest, caused cultural and linguistic changes in local populations, increasing their heterogeneity. We aim to characterize the genetic structure of the region, using the largest Amazigh dataset to date and other reference samples. Our findings indicate microgeographical genetic heterogeneity among Amazigh populations, modeled by various admixture waves and different effective population sizes. A first admixture wave is detected group-wide around the twelfth century, whereas a second wave appears in some Amazigh groups around the nineteenth century. These events involved populations with higher genetic ancestry from south of the Sahara compared to the current North Africans. A plausible explanation would be the historical trans-Saharan slave trade, which lasted from the Roman times to the nineteenth century. Furthermore, our investigation shows that assortative mating in North Africa has been rare.
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Affiliation(s)
- Laura Vilà-Valls
- Departament de Medicina i Ciències de la Vida, Institut de Biologia Evolutiva (CSIC-UPF), Universitat Pompeu Fabra, Barcelona, Spain
| | - Amine Abdeli
- Laboratoire de Biologie Cellulaire et Moléculaire, Faculté Des Sciences Biologiques, Université des Sciences et de la Technologie Houari Boumediene, Alger, Algeria
| | - Marcel Lucas-Sánchez
- Departament de Medicina i Ciències de la Vida, Institut de Biologia Evolutiva (CSIC-UPF), Universitat Pompeu Fabra, Barcelona, Spain
| | - Asmahan Bekada
- Département de Biotechnologie, Faculté des Sciences de la Nature et de la Vie, Université Oran 1 (Ahmad Ben Bella), Oran, Algeria
| | - Francesc Calafell
- Departament de Medicina i Ciències de la Vida, Institut de Biologia Evolutiva (CSIC-UPF), Universitat Pompeu Fabra, Barcelona, Spain
| | - Traki Benhassine
- Laboratoire de Biologie Cellulaire et Moléculaire, Faculté Des Sciences Biologiques, Université des Sciences et de la Technologie Houari Boumediene, Alger, Algeria
| | - David Comas
- Departament de Medicina i Ciències de la Vida, Institut de Biologia Evolutiva (CSIC-UPF), Universitat Pompeu Fabra, Barcelona, Spain.
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49
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Dou J, Tan Y, Kock KH, Wang J, Cheng X, Tan LM, Han KY, Hon CC, Park WY, Shin JW, Jin H, Wang Y, Chen H, Ding L, Prabhakar S, Navin N, Chen R, Chen K. Single-nucleotide variant calling in single-cell sequencing data with Monopogen. Nat Biotechnol 2024; 42:803-812. [PMID: 37592035 PMCID: PMC11098741 DOI: 10.1038/s41587-023-01873-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 06/21/2023] [Indexed: 08/19/2023]
Abstract
Single-cell omics technologies enable molecular characterization of diverse cell types and states, but how the resulting transcriptional and epigenetic profiles depend on the cell's genetic background remains understudied. We describe Monopogen, a computational tool to detect single-nucleotide variants (SNVs) from single-cell sequencing data. Monopogen leverages linkage disequilibrium from external reference panels to identify germline SNVs and detects putative somatic SNVs using allele cosegregating patterns at the cell population level. It can identify 100 K to 3 M germline SNVs achieving a genotyping accuracy of 95%, together with hundreds of putative somatic SNVs. Monopogen-derived genotypes enable global and local ancestry inference and identification of admixed samples. It identifies variants associated with cardiomyocyte metabolic levels and epigenomic programs. It also improves putative somatic SNV detection that enables clonal lineage tracing in primary human clonal hematopoiesis. Monopogen brings together population genetics, cell lineage tracing and single-cell omics to uncover genetic determinants of cellular processes.
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Affiliation(s)
- Jinzhuang Dou
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Yukun Tan
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Kian Hong Kock
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
| | - Jun Wang
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Xuesen Cheng
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Le Min Tan
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
| | - Kyung Yeon Han
- Samsung Genome Institute, Samsung Medical Center, Seoul, South Korea
| | - Chung-Chau Hon
- Laboratory for Genome Information Analysis, RIKEN center for Integrative Medical Sciences, Graduate School of Integrated Sciences for Life, Hiroshima University, Higashi-Hiroshima, Japan
| | - Woong-Yang Park
- Samsung Genome Institute, Samsung Medical Center, Seoul, South Korea
| | - Jay W Shin
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
- Laboratory for Advanced Genomics Circuit, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Haijing Jin
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Yujia Wang
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Han Chen
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center, Houston, TX, USA
- Center for Precision Health, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center, Houston, TX, USA
| | - Li Ding
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
- Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
- Siteman Cancer Institute, Washington University School of Medicine, St. Louis, MO, USA
| | - Shyam Prabhakar
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
| | - Nicholas Navin
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Rui Chen
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Ken Chen
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
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50
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Fan Z, Whitaker VM. Genomic signatures of strawberry domestication and diversification. THE PLANT CELL 2024; 36:1622-1636. [PMID: 38113879 PMCID: PMC11062436 DOI: 10.1093/plcell/koad314] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 11/20/2023] [Accepted: 11/25/2023] [Indexed: 12/21/2023]
Abstract
Cultivated strawberry (Fragaria × ananassa) has a brief history of less than 300 yr, beginning with the hybridization of octoploids Fragaria chiloensis and Fragaria virginiana. Here we explored the genomic signatures of early domestication and subsequent diversification for different climates using whole-genome sequences of 289 wild, heirloom, and modern varieties from two major breeding programs in the United States. Four nonadmixed wild octoploid populations were identified, with recurrent introgression among the sympatric populations. The proportion of F. virginiana ancestry increased by 20% in modern varieties over initial hybrids, and the proportion of F. chiloensis subsp. pacifica rose from 0% to 3.4%. Effective population size rapidly declined during early breeding. Meanwhile, divergent selection for distinct environments reshaped wild allelic origins in 21 out of 28 chromosomes. Overlapping divergent selective sweeps in natural and domesticated populations revealed 16 convergent genomic signatures that may be important for climatic adaptation. Despite 20 breeding cycles since initial hybridization, more than half of loci underlying yield and fruit size are still not under artificial selection. These insights add clarity to the domestication and breeding history of what is now the most widely cultivated fruit in the world.
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Affiliation(s)
- Zhen Fan
- Horticultural Sciences Department, University of Florida, IFAS Gulf Coast Research and Education Center, Wimauma, FL 33597, USA
| | - Vance M Whitaker
- Horticultural Sciences Department, University of Florida, IFAS Gulf Coast Research and Education Center, Wimauma, FL 33597, USA
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