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Chang X, Qu HQ, Liu Y, Glessner JT, Hakonarson H. Mitochondrial DNA Haplogroup K Is Protective Against Autism Spectrum Disorder Risk in Populations of European Ancestry. J Am Acad Child Adolesc Psychiatry 2024; 63:835-844. [PMID: 38072244 PMCID: PMC11186604 DOI: 10.1016/j.jaac.2023.09.550] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 09/23/2023] [Accepted: 12/01/2023] [Indexed: 12/23/2023]
Abstract
OBJECTIVE Accumulative evidence indicates a critical role of mitochondrial function in autism spectrum disorders (ASD), implying that ASD risk may be linked to mitochondrial dysfunction due to DNA (mtDNA) variations. Although a few studies have explored the association between mtDNA variations and ASD, the role of mtDNA in ASD is still unclear. Here, we aimed to investigate whether mitochondrial DNA haplogroups are associated with the risk of ASD. METHOD Two European cohorts and an Ashkenazi Jewish (AJ) cohort were analyzed, including 2,062 ASD patients in comparison with 4,632 healthy controls. DNA samples were genotyped using Illumina HumanHap550/610 and Illumina 1M arrays, inclusive of mitochondrial markers. Mitochondrial DNA (mtDNA) haplogroups were identified from genotyping data using HaploGrep2. A mitochondrial genome imputation pipeline was established to detect mtDNA variants. We conducted a case-control study to investigate potential associations of mtDNA haplogroups and variants with the susceptibility to ASD. RESULTS We observed that the ancient adaptive mtDNA haplogroup K was significantly associated with decreased risk of ASD by the investigation of 2 European cohorts including a total of 2,006 cases and 4,435 controls (odds ratio = 0.64, P=1.79 × 10-5), and we replicated this association in an Ashkenazi Jewish (AJ) cohort including 56 cases and 197 controls (odds ratio = 0.35, P = 9.46 × 10-3). Moreover, we demonstrate that the mtDNA variants rs28358571, rs28358584, and rs28358280 are significantly associated with ASD risk. Further expression quantitative trait loci (eQTLs) analysis indicated that the rs28358584 and rs28358280 genotypes are associated with expression levels of nearby genes in brain tissues, suggesting those mtDNA variants may confer risk for ASD via regulation of expression levels of genes encoded by the mitochondrial genome. CONCLUSION This study helps to shed light on the contribution of mitochondria in ASD and provides new insights into the genetic mechanism underlying ASD, suggesting the potential involvement of mtDNA-encoded proteins in the development of ASD. PLAIN LANGUAGE SUMMARY Increasing evidence indicates that mitochondrial dysfunction may be linked to autism spectrum disorder (ASD). This study investigated potential associations of mitochondrial DNA (mtDNA) variants in 2 European and Ashkenazi Jewish cohorts including 2,062 individuals with ASD and 4,632 healthy controls. Researchers found that the ancient mtDNA haplogroup K was linked to a reduced risk of ASD in both European and Ashkenazi Jewish populations. Additionally, specific mtDNA variants were associated with ASD risk and were shown to influence the expression of nearby genes in the brain. These findings highlight the potential involvement of mtDNA in ASD development, offering new insights into the genetic mechanisms underlying the disorder.
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Affiliation(s)
- Xiao Chang
- Children's Hospital of Philadelphia, Pennsylvania, United States; Shandong First Medical University & Shandong Academy of Medical Sciences, Shandong, China.
| | - Hui-Qi Qu
- Children's Hospital of Philadelphia, Pennsylvania, United States
| | - Yichuan Liu
- Children's Hospital of Philadelphia, Pennsylvania, United States
| | | | - Hakon Hakonarson
- Children's Hospital of Philadelphia, Pennsylvania, United States; The Perelman School of Medicine, University of Pennsylvania, Pennsylvania, United States and Faculty of Medicine, University of Iceland, Reykjavik, Iceland
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Vitale D, Koretsky M, Kuznetsov N, Hong S, Martin J, James M, Makarious MB, Leonard H, Iwaki H, Faghri F, Blauwendraat C, Singleton AB, Song Y, Levine K, Sreelatha AAK, Fang ZH, Nalls M. GenoTools: An Open-Source Python Package for Efficient Genotype Data Quality Control and Analysis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.26.586362. [PMID: 38585876 PMCID: PMC10996710 DOI: 10.1101/2024.03.26.586362] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
GenoTools, a Python package, streamlines population genetics research by integrating ancestry estimation, quality control (QC), and genome-wide association studies (GWAS) capabilities into efficient pipelines. By tracking samples, variants, and quality-specific measures throughout fully customizable pipelines, users can easily manage genetics data for large and small studies. GenoTools' "Ancestry" module renders highly accurate predictions, allowing for high-quality ancestry-specific studies, and enables custom ancestry model training and serialization, specified to the user's genotyping or sequencing platform. As the genotype processing engine that powers several large initiatives, including the NIH's Center for Alzheimer's and Related Dementias (CARD) and the Global Parkinson's Genetics Program (GP2). GenoTools was used to process and analyze the UK Biobank and major Alzheimer's Disease (AD) and Parkinson's Disease (PD) datasets with over 400,000 genotypes from arrays and 5000 sequences and has led to novel discoveries in diverse populations. It has provided replicable ancestry predictions, implemented rigorous QC, and conducted genetic ancestry-specific GWAS to identify systematic errors or biases through a single command. GenoTools is a customizable tool that enables users to efficiently analyze and scale genotype data with reproducible and scalable ancestry, QC, and GWAS pipelines.
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Saffie Awad P, Makarious MB, Elsayed I, Sanyaolu A, Wild Crea P, Schumacher Schuh AF, Levine KS, Vitale D, Korestky MJ, Kim J, Peixoto Leal T, Perinan MT, Dey S, Noyce AJ, Reyes-Palomares A, Rodriguez-Losada N, Foo JN, Mohamed W, Heilbron K, Norcliffe-Kaufmann L, Rizig M, Okubadejo N, Nalls M, Blauwendraat C, Singleton A, Leonard H, Mata IF, Bandres Ciga S. Insights into Ancestral Diversity in Parkinsons Disease Risk: A Comparative Assessment of Polygenic Risk Scores. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.11.28.23299090. [PMID: 38076954 PMCID: PMC10705647 DOI: 10.1101/2023.11.28.23299090] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/21/2023]
Abstract
Objectives To evaluate and compare different polygenic risk score (PRS) models in predicting Parkinsons disease (PD) across diverse ancestries, focusing on identifying the most suitable approach for each population and potentially contributing to equitable advancements in precision medicine. Methods We constructed a total of 105 PRS across individual level data from seven diverse ancestries. First, a cross-ancestry conventional PRS comparison was implemented by utilizing the 90 known European risk loci with weighted effects from four independent summary statistics including European, East Asian, Latino/Admixed American, and African/Admixed. These models were adjusted by sex, age, and principal components (28 PRS) and by sex, age, and percentage of admixture (28 PRS) for comparison. Secondly, a novel and refined multi-ancestry best-fit PRS approach was then applied across the seven ancestries by leveraging multi-ancestry meta-analyzed summary statistics and using a p-value thresholding approach (49 PRS) to enhance prediction applicability in a global setting. Results European-based PRS models predicted disease status across all ancestries to differing degrees of accuracy. Ashkenazi Jewish had the highest Odds Ratio (OR): 1.96 (95% CI: 1.69-2.25, p < 0.0001) with an AUC (Area Under the Curve) of 68%. Conversely, the East Asian population, despite having fewer predictive variants (84 out of 90), had an OR of 1.37 (95% CI: 1.32-1.42) and an AUC of 62%, illustrating the cross-ancestry transferability of this model. Lower OR alongside broader confidence intervals were observed in other populations, including Africans (OR =1.38, 95% CI: 1.12-1.63, p=0.001). Adjustment by percentage of admixture did not outperform principal components. Multi-ancestry best-fit PRS models improved risk prediction in European, Ashkenazi Jewish, and African ancestries, yet didn't surpass conventional PRS in admixed populations such as Latino/American admixed and African admixed populations. Interpretation The present study represents a novel and comprehensive assessment of PRS performance across seven ancestries in PD, highlighting the inadequacy of a 'one size fits all' approach in genetic risk prediction. We demonstrated that European based PD PRS models are partially transferable to other ancestries and could be improved by a novel best-fit multi-ancestry PRS, especially in non-admixed populations.
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Danek BP, Makarious MB, Dadu A, Vitale D, Lee PS, Singleton AB, Nalls MA, Sun J, Faghri F. Federated learning for multi-omics: A performance evaluation in Parkinson's disease. PATTERNS (NEW YORK, N.Y.) 2024; 5:100945. [PMID: 38487808 PMCID: PMC10935499 DOI: 10.1016/j.patter.2024.100945] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 01/29/2024] [Accepted: 02/02/2024] [Indexed: 03/17/2024]
Abstract
While machine learning (ML) research has recently grown more in popularity, its application in the omics domain is constrained by access to sufficiently large, high-quality datasets needed to train ML models. Federated learning (FL) represents an opportunity to enable collaborative curation of such datasets among participating institutions. We compare the simulated performance of several models trained using FL against classically trained ML models on the task of multi-omics Parkinson's disease prediction. We find that FL model performance tracks centrally trained ML models, where the most performant FL model achieves an AUC-PR of 0.876 ± 0.009, 0.014 ± 0.003 less than its centrally trained variation. We also determine that the dispersion of samples within a federation plays a meaningful role in model performance. Our study implements several open-source FL frameworks and aims to highlight some of the challenges and opportunities when applying these collaborative methods in multi-omics studies.
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Affiliation(s)
- Benjamin P. Danek
- Department of Computer Science, University of Illinois at Urbana-Champaign, Champaign, IL 61820, USA
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
- DataTecnica, Washington, DC 20037, USA
| | - Mary B. Makarious
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20892, USA
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, UK
- UCL Movement Disorders Centre, University College London, London, UK
| | - Anant Dadu
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
- DataTecnica, Washington, DC 20037, USA
| | - Dan Vitale
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
- DataTecnica, Washington, DC 20037, USA
| | - Paul Suhwan Lee
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
| | - Andrew B. Singleton
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20892, USA
| | - Mike A. Nalls
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
- DataTecnica, Washington, DC 20037, USA
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20892, USA
| | - Jimeng Sun
- Department of Computer Science, University of Illinois at Urbana-Champaign, Champaign, IL 61820, USA
- Carle Illinois College of Medicine, University of Illinois at Urbana-Champaign, Champaign, IL 61820, USA
| | - Faraz Faghri
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
- DataTecnica, Washington, DC 20037, USA
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20892, USA
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Danek B, Makarious MB, Dadu A, Vitale D, Lee PS, Nalls MA, Sun J, Faghri F. Federated Learning for multi-omics: a performance evaluation in Parkinson's disease. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.10.04.560604. [PMID: 37986893 PMCID: PMC10659429 DOI: 10.1101/2023.10.04.560604] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
While machine learning (ML) research has recently grown more in popularity, its application in the omics domain is constrained by access to sufficiently large, high-quality datasets needed to train ML models. Federated Learning (FL) represents an opportunity to enable collaborative curation of such datasets among participating institutions. We compare the simulated performance of several models trained using FL against classically trained ML models on the task of multi-omics Parkinson's Disease prediction. We find that FL model performance tracks centrally trained ML models, where the most performant FL model achieves an AUC-PR of 0.876 ± 0.009, 0.014 ± 0.003 less than its centrally trained variation. We also determine that the dispersion of samples within a federation plays a meaningful role in model performance. Our study implements several open source FL frameworks and aims to highlight some of the challenges and opportunities when applying these collaborative methods in multi-omics studies.
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Affiliation(s)
- Benjamin Danek
- Department of Computer Science, University of Illinois at Urbana-Champaign, Champaign, IL, 61820, USA
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, 20892, USA
- DataTecnica, Washington, DC, 20037, USA
| | - Mary B. Makarious
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, 20892, USA
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, UK
- UCL Movement Disorders Centre, University College London, London, UK
| | - Anant Dadu
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, 20892, USA
- DataTecnica, Washington, DC, 20037, USA
| | - Dan Vitale
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, 20892, USA
- DataTecnica, Washington, DC, 20037, USA
| | - Paul Suhwan Lee
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Mike A Nalls
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, 20892, USA
- DataTecnica, Washington, DC, 20037, USA
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Jimeng Sun
- Department of Computer Science, University of Illinois at Urbana-Champaign, Champaign, IL, 61820, USA
- Carle Illinois College of Medicine, University of Illinois at Urbana-Champaign, Champaign, IL, 61820, USA
| | - Faraz Faghri
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, 20892, USA
- DataTecnica, Washington, DC, 20037, USA
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, 20892, USA
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Koretsky MJ, Alvarado C, Makarious MB, Vitale D, Levine K, Bandres-Ciga S, Dadu A, Scholz SW, Sargent L, Faghri F, Iwaki H, Blauwendraat C, Singleton A, Nalls M, Leonard H. Genetic risk factor clustering within and across neurodegenerative diseases. Brain 2023; 146:4486-4494. [PMID: 37192343 PMCID: PMC10629980 DOI: 10.1093/brain/awad161] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Revised: 04/11/2023] [Accepted: 04/26/2023] [Indexed: 05/18/2023] Open
Abstract
Overlapping symptoms and co-pathologies are common in closely related neurodegenerative diseases (NDDs). Investigating genetic risk variants across these NDDs can give further insight into disease manifestations. In this study we have leveraged genome-wide single nucleotide polymorphisms and genome-wide association study summary statistics to cluster patients based on their genetic status across identified risk variants for five NDDs (Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, Lewy body dementia and frontotemporal dementia). The multi-disease and disease-specific clustering results presented here provide evidence that NDDs have more overlapping genetic aetiology than previously expected and how neurodegeneration should be viewed as a spectrum of symptomology. These clustering analyses also show potential subsets of patients with these diseases that are significantly depleted for any known common genetic risk factors suggesting environmental or other factors at work. Establishing that NDDs with overlapping pathologies share genetic risk loci, future research into how these variants might have different effects on downstream protein expression, pathology and NDD manifestation in general is important for refining and treating NDDs.
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Affiliation(s)
- Mathew J Koretsky
- Center for Alzheimer’s Disease and Related Dementias, National Institutes of Health, Bethesda, MD 20892, USA
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20892, USA
| | - Chelsea Alvarado
- Center for Alzheimer’s Disease and Related Dementias, National Institutes of Health, Bethesda, MD 20892, USA
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20892, USA
- Data Tecnica International LLC, Washington, DC 20037, USA
| | - Mary B Makarious
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20892, USA
- UCL Movement Disorders Centre, University College London, London, WC1E 6BT, UK
| | - Dan Vitale
- Center for Alzheimer’s Disease and Related Dementias, National Institutes of Health, Bethesda, MD 20892, USA
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20892, USA
- Data Tecnica International LLC, Washington, DC 20037, USA
| | - Kristin Levine
- Center for Alzheimer’s Disease and Related Dementias, National Institutes of Health, Bethesda, MD 20892, USA
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20892, USA
- Data Tecnica International LLC, Washington, DC 20037, USA
| | - Sara Bandres-Ciga
- Center for Alzheimer’s Disease and Related Dementias, National Institutes of Health, Bethesda, MD 20892, USA
| | - Anant Dadu
- Center for Alzheimer’s Disease and Related Dementias, National Institutes of Health, Bethesda, MD 20892, USA
- Data Tecnica International LLC, Washington, DC 20037, USA
- Department of Computer Science, University of Illinois at Urbana-Champaign, Champaign, IL 61820, USA
| | - Sonja W Scholz
- Neurodegenerative Diseases Research Unit, National Institute of Neurological Disorders and Stroke, Bethesda, MD 20892, USA
- Department of Neurology, Johns Hopkins University, Baltimore, MD 21287, USA
| | - Lana Sargent
- Center for Alzheimer’s Disease and Related Dementias, National Institutes of Health, Bethesda, MD 20892, USA
| | - Faraz Faghri
- Center for Alzheimer’s Disease and Related Dementias, National Institutes of Health, Bethesda, MD 20892, USA
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20892, USA
- Data Tecnica International LLC, Washington, DC 20037, USA
| | - Hirotaka Iwaki
- Center for Alzheimer’s Disease and Related Dementias, National Institutes of Health, Bethesda, MD 20892, USA
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20892, USA
- Data Tecnica International LLC, Washington, DC 20037, USA
| | - Cornelis Blauwendraat
- Center for Alzheimer’s Disease and Related Dementias, National Institutes of Health, Bethesda, MD 20892, USA
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20892, USA
| | - Andrew Singleton
- Center for Alzheimer’s Disease and Related Dementias, National Institutes of Health, Bethesda, MD 20892, USA
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20892, USA
| | - Mike Nalls
- Center for Alzheimer’s Disease and Related Dementias, National Institutes of Health, Bethesda, MD 20892, USA
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20892, USA
- Data Tecnica International LLC, Washington, DC 20037, USA
| | - Hampton Leonard
- Center for Alzheimer’s Disease and Related Dementias, National Institutes of Health, Bethesda, MD 20892, USA
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20892, USA
- Data Tecnica International LLC, Washington, DC 20037, USA
- DZNE, Tuebingen 72076, Germany
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Jiang H, Qian Y, Zhang Z, Meng M, Deng Y, Wang G, He S, Yang L. Chromosome-level genome assembly and whole-genome resequencing of topmouth culter (Culter alburnus) provide insights into the intraspecific variation of its semi-buoyant and adhesive eggs. Mol Ecol Resour 2023; 23:1841-1852. [PMID: 37475144 DOI: 10.1111/1755-0998.13845] [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: 09/23/2022] [Revised: 04/24/2023] [Accepted: 07/11/2023] [Indexed: 07/22/2023]
Abstract
Topmouth culter (Culter alburnus) is an ecologically and economically important species belonging to the subfamily Culterinae that is native to and widespread in East Asia. Intraspecific variation of semi-buoyant and adhesive eggs in topmouth culter provides an ideal opportunity to investigate the genetic mechanisms of spawning habits underlying the adaptive radiation of cyprinids in East Asia. In this study, we present a chromosome-level genome assembly of topmouth culter and re-sequenced 158 individuals from six locations in China covering three geographical groups and two egg type variations. The topmouth culter genome size was 1.05 Gb, with a contig N50 length of 17.8 Mb and anchored onto 24 chromosomes. Phylogenetic analysis showed that the divergence time of the Culterinae was coinciding with the time of initiation of the Asian monsoon intensification. Gene family evolutionary analysis indicated that the expanded gene families in topmouth culter were associated with dietary adaptation. Population-level genetic analysis indicated clear differentiation among the six populations, which were clustered into three distinct clusters, consistent with their geographical divergence. The historical effective population size of topmouth culter correlated with the Tibetan Plateau uplifting according to the demographic history reconstruction. A selective sweep analysis between adhesive and semi-buoyant egg populations revealed the genes associated with the hydration and adhesiveness of eggs, indicating divergent selection towards different hydrological environments. This study offers a high-resolution genetic resource for further studies on evolutionary adaptation, genetic breeding and conservation of topmouth culter, providing insights into the molecular mechanisms for egg type variation of East Asian cyprinids.
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Affiliation(s)
- Haifeng Jiang
- College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Yuting Qian
- State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, China
| | - Zhi Zhang
- Fujian Key Laboratory on Conservation and Sustainable Utilization of Marine Biodiversity, Fuzhou Institute of Oceanography, Minjiang University, Fuzhou, China
| | - Minghui Meng
- Key Laboratory of Horticultural Plant Biology (MOE), College of Horticulture and Forestry Sciences, Huazhong Agricultural University, Wuhan, China
| | - Yu Deng
- State Key Laboratory of Developmental Biology of Freshwater Fish, Hunan Normal University, Changsha, China
- Life Science College, Hunan Normal University, Changsha, China
| | - Gaoxue Wang
- College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Shunping He
- State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, China
| | - Liandong Yang
- State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, China
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Rizig M, Bandres-Ciga S, Makarious MB, Ojo O, Crea PW, Abiodun O, Levine KS, Abubakar S, Achoru C, Vitale D, Adeniji O, Agabi O, Koretsky MJ, Agulanna U, Hall DA, Akinyemi R, Xie T, Ali M, Shamim EA, Ani-Osheku I, Padmanaban M, Arigbodi O, Standaert DG, Bello A, Dean M, Erameh C, Elsayed I, Farombi T, Okunoye O, Fawale M, Billingsley KJ, Imarhiagbe F, Jerez PA, Iwuozo E, Baker B, Komolafe M, Malik L, Nwani P, Daida K, Nwazor E, Miano-Burkhardt A, Nyandaiti Y, Fang ZH, Obiabo Y, Kluss JH, Odeniyi O, Hernandez D, Odiase F, Tayebi N, Ojini F, Sidranksy E, Onwuegbuzie G, D’Souza AM, Osaigbovo G, Berhe B, Osemwegie N, Reed X, Oshinaike O, Leonard H, Otubogun F, Alvarado CX, Oyakhire S, Ozomma S, Samuel S, Taiwo F, Wahab K, Zubair Y, Iwaki H, Kim JJ, Morris HR, Hardy J, Nalls M, Heilbron K, Norcliffe-Kaufmann L, Blauwendraat C, Houlden H, Singleton A, Okubadejo N. Genome-wide Association Identifies Novel Etiological Insights Associated with Parkinson's Disease in African and African Admixed Populations. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.05.05.23289529. [PMID: 37398408 PMCID: PMC10312852 DOI: 10.1101/2023.05.05.23289529] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
Background Understanding the genetic mechanisms underlying diseases in ancestrally diverse populations is a critical step towards the realization of the global application of precision medicine. The African and African admixed populations enable mapping of complex traits given their greater levels of genetic diversity, extensive population substructure, and distinct linkage disequilibrium patterns. Methods Here we perform a comprehensive genome-wide assessment of Parkinson's disease (PD) in 197,918 individuals (1,488 cases; 196,430 controls) of African and African admixed ancestry, characterizing population-specific risk, differential haplotype structure and admixture, coding and structural genetic variation and polygenic risk profiling. Findings We identified a novel common risk factor for PD and age at onset at the GBA1 locus (risk, rs3115534-G; OR=1.58, 95% CI = 1.37 - 1.80, P=2.397E-14; age at onset, BETA =-2.004, SE =0.57, P = 0.0005), that was found to be rare in non-African/African admixed populations. Downstream short- and long-read whole genome sequencing analyses did not reveal any coding or structural variant underlying the GWAS signal. However, we identified that this signal mediates PD risk via expression quantitative trait locus (eQTL) mechanisms. While previously identified GBA1 associated disease risk variants are coding mutations, here we suggest a novel functional mechanism consistent with a trend in decreasing glucocerebrosidase activity levels. Given the high population frequency of the underlying signal and the phenotypic characteristics of the homozygous carriers, we hypothesize that this variant may not cause Gaucher disease. Additionally, the prevalence of Gaucher's disease in Africa is low. Interpretation The present study identifies a novel African-ancestry genetic risk factor in GBA1 as a major mechanistic basis of PD in the African and African admixed populations. This striking result contrasts to previous work in Northern European populations, both in terms of mechanism and attributable risk. This finding highlights the importance of understanding population-specific genetic risk in complex diseases, a particularly crucial point as the field moves toward precision medicine in PD clinical trials and while recognizing the need for equitable inclusion of ancestrally diverse groups in such trials. Given the distinctive genetics of these underrepresented populations, their inclusion represents a valuable step towards insights into novel genetic determinants underlying PD etiology. This opens new avenues towards RNA-based and other therapeutic strategies aimed at reducing lifetime risk. Research in Context Evidence Before this Study Our current understanding of Parkinson's disease (PD) is disproportionately based on studying populations of European ancestry, leading to a significant gap in our knowledge about the genetics, clinical characteristics, and pathophysiology in underrepresented populations. This is particularly notable in individuals of African and African admixed ancestries. Over the last two decades, we have witnessed a revolution in the research area of complex genetic diseases. In the PD field, large-scale genome-wide association studies in the European, Asian, and Latin American populations have identified multiple risk loci associated with disease. These include 78 loci and 90 independent signals associated with PD risk in the European population, nine replicated loci and two novel population-specific signals in the Asian population, and a total of 11 novel loci recently nominated through multi-ancestry GWAS efforts.Nevertheless, the African and African admixed populations remain completely unexplored in the context of PD genetics. Added Value of this Study To address the lack of diversity in our research field, this study aimed to conduct the first genome-wide assessment of PD genetics in the African and African admixed populations. Here, we identified a genetic risk factor linked to PD etiology, dissected African-specific differences in risk and age at onset, characterized known genetic risk factors, and highlighted the utility of the African and African admixed risk haplotype substructure for future fine-mapping efforts. We identified a novel disease mechanism via expression changes consistent with decreased GBA1 activity levels. Future large scale single cell expression studies should investigate the neuronal populations in which expression differences are most prominent. This novel mechanism may hold promise for future efficient RNA-based therapeutic strategies such as antisense oligonucleotides or short interfering RNAs aimed at preventing and decreasing disease risk. We envisage that these data generated under the umbrella of the Global Parkinson's Genetics Program (GP2) will shed light on the molecular mechanisms involved in the disease process and might pave the way for future clinical trials and therapeutic interventions. This work represents a valuable resource in an underserved population, supporting pioneering research within GP2 and beyond. Deciphering causal and genetic risk factors in all these ancestries will help determine whether interventions, potential targets for disease modifying treatment, and prevention strategies that are being studied in the European populations are relevant to the African and African admixed populations. Implications of all the Available Evidence We nominate a novel signal impacting GBA1 as the major genetic risk factor for PD in the African and African admixed populations. The present study could inform future GBA1 clinical trials, improving patient stratification. In this regard, genetic testing can help to design trials likely to provide meaningful and actionable answers. It is our hope that these findings may ultimately have clinical utility for this underrepresented population.
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Affiliation(s)
- Mie Rizig
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- UCL Movement Disorders Centre, University College London, London, WC1N 3BG, UK
| | - Sara Bandres-Ciga
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
| | - Mary B Makarious
- UCL Movement Disorders Centre, University College London, London, WC1N 3BG, UK
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Oluwadamilola Ojo
- College of Medicine, University of Lagos, Idi Araba, Lagos State, Nigeria
| | - Peter Wild Crea
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | | | - Kristin S Levine
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
- Data Tecnica International, Washington, DC, USA
| | - Sani Abubakar
- Ahmadu Bello University, Zaria, Kaduna State, Nigeria
| | - Charles Achoru
- Jos University Teaching Hospital, Jos, Plateau State, Nigeria
| | - Dan Vitale
- Data Tecnica International, Washington, DC, USA
| | | | - Osigwe Agabi
- College of Medicine, University of Lagos, Idi Araba, Lagos State, Nigeria
| | - Mathew J Koretsky
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
| | - Uchechi Agulanna
- Lagos University Teaching Hospital, Idi Araba, Lagos State, Nigeria
| | - Deborah A. Hall
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - Rufus Akinyemi
- Neuroscience and Ageing Research Unit, Institute for Advanced Medical Research and Training, College of Medicine, University of Ibadan, Ibadan, Oyo State, Nigeria
| | - Tao Xie
- Department of Neurology, University of Chicago Medicine, Chicago, Illinois, USA
| | - Mohammed Ali
- Federal Teaching Hospital Gombe, Gombe State, Nigeria
| | - Ejaz A. Shamim
- Human Motor Control Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
- Kaiser Permanente Mid-Atlantic States, Largo, Maryland, USA
- MidAtlantic Permanente Research Institute, Rockville, Maryland, USA
| | | | - Mahesh Padmanaban
- Department of Neurology, University of Chicago Medicine, Chicago, Illinois, USA
| | | | - David G Standaert
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Abiodun Bello
- University of Ilorin Teaching Hospital, Ilorin, Kwara State, Nigeria
| | - Marissa Dean
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Cyril Erameh
- Irrua Specialist Teaching Hospital, Irrua, Edo State, Nigeria
| | - Inas Elsayed
- Faculty of Pharmacy, University of Gezira, Wadmadani, 20, Sudan
| | | | - Olaitan Okunoye
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Michael Fawale
- Obafemi Awolowo University, Ile-Ife, Osun State, Nigeria
| | - Kimberley J Billingsley
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | | | - Pilar Alvarez Jerez
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
| | | | - Breeana Baker
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
| | | | - Laksh Malik
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
| | - Paul Nwani
- Nnamdi Azikiwe University Teaching Hospital, Nnewi, Anambra State, Nigeria
| | - Kensuke Daida
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Ernest Nwazor
- Rivers State University Teaching Hospital, Port Harcourt, Rivers State, Nigeria
| | - Abigail Miano-Burkhardt
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Yakub Nyandaiti
- University of Maiduguri Teaching Hospital, Maiduguri, Borno State, Nigeria
| | - Zih-Hua Fang
- German Center for Neurodegenerative Diseases (DZNE), Tuebingen, Germany
| | - Yahaya Obiabo
- Federal University of Health Sciences, Otukpo, Benue State, Nigeria
| | - Jillian H. Kluss
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | | | - Dena Hernandez
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | | | - Nahid Tayebi
- Medical Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Francis Ojini
- College of Medicine, University of Lagos, Idi Araba, Lagos State, Nigeria
| | - Ellen Sidranksy
- Medical Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA
| | | | - Andrea M. D’Souza
- Medical Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA
| | | | - Bahafta Berhe
- Medical Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA
| | | | - Xylena Reed
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
| | | | - Hampton Leonard
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
- Data Tecnica International, Washington, DC, USA
| | | | - Chelsea X Alvarado
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
- Data Tecnica International, Washington, DC, USA
| | | | - Simon Ozomma
- University of Calabar Teaching Hospital, Calabar, Cross River State, Nigeria
| | - Sarah Samuel
- University of Maiduguri Teaching Hospital, Maiduguri, Borno State, Nigeria
| | | | - Kolawole Wahab
- University of Ilorin Teaching Hospital, Ilorin, Kwara State, Nigeria
- University of Ilorin, Ilorin, Kwara State, Nigeria
| | - Yusuf Zubair
- National Hospital, Abuja, Federal Capital Territory, Nigeria
| | - Hirotaka Iwaki
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
- Data Tecnica International, Washington, DC, USA
| | - Jonggeol Jeffrey Kim
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Huw R Morris
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- UCL Movement Disorders Centre, University College London, London, WC1N 3BG, UK
| | - John Hardy
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Mike Nalls
- Data Tecnica International, Washington, DC, USA
| | | | | | | | - Cornelis Blauwendraat
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Henry Houlden
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Andrew Singleton
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Njideka Okubadejo
- College of Medicine, University of Lagos, Idi Araba, Lagos State, Nigeria
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Lin Z, Zhu Z, Zhuang M, Wang Z, Zhang Y, Gao F, Niu Q, Ji T. Effects of local domestication warrant attention in honey bee population genetics. SCIENCE ADVANCES 2023; 9:eade7917. [PMID: 37134176 PMCID: PMC10156114 DOI: 10.1126/sciadv.ade7917] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Honey bees, Apis mellifera, have for millennia been managed and exploited by humans and introduced into most suitable regions worldwide. However, given the lack of records for many introduction events, treating A. mellifera populations as native would predictably bias genetic studies regarding origin and evolution. Here, we used the Dongbei bee, a well-documented population, introduced beyond the natural distribution range approximately 100 years ago, to elucidate the effects of local domestication on animal population genetic analyses. Strong domestication pressure was detected in this population, and the genetic divergence between Dongbei bee and its ancestral subspecies was found to have occurred at the lineage level. Results of phylogenetic and time divergence analyses could consequently be misinterpreted. Proposing new subspecies or lineages and performing analyses of origin should thus strive to eliminate anthropogenic effects. We highlight the need for definitions of landrace and breed in honey bee sciences and make preliminary suggestions.
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Affiliation(s)
- Zheguang Lin
- Apicultural Research Institute, College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
| | - Zhongxu Zhu
- Department of Biomedical Sciences, City University of Hong Kong, Hong Kong SAR, China
| | - Mingliang Zhuang
- Apiculture Science Institute of Jilin Province, Jilin 132108, China
| | - Zhi Wang
- Apiculture Science Institute of Jilin Province, Jilin 132108, China
| | - Yi Zhang
- Apicultural Research Institute, College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
| | - Fuchao Gao
- Mudanjiang Branch of Heilongjiang Academy of Agricultural Sciences, Mudanjiang 157043, China
| | - Qingsheng Niu
- Apiculture Science Institute of Jilin Province, Jilin 132108, China
| | - Ting Ji
- Apicultural Research Institute, College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
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10
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Blauwendraat C, Tayebi N, Woo EG, Lopez G, Fierro L, Toffoli M, Limbachiya N, Hughes D, Pitz V, Patel D, Vitale D, Koretsky MJ, Hernandez D, Real R, Alcalay RN, Nalls MA, Morris HR, Schapira AHV, Balwani M, Sidransky E. Polygenic Parkinson's Disease Genetic Risk Score as Risk Modifier of Parkinsonism in Gaucher Disease. Mov Disord 2023; 38:899-903. [PMID: 36869417 PMCID: PMC10271962 DOI: 10.1002/mds.29342] [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: 09/21/2022] [Revised: 12/05/2022] [Accepted: 01/03/2023] [Indexed: 03/05/2023] Open
Abstract
BACKGROUND Biallelic pathogenic variants in GBA1 are the cause of Gaucher disease (GD) type 1 (GD1), a lysosomal storage disorder resulting from deficient glucocerebrosidase. Heterozygous GBA1 variants are also a common genetic risk factor for Parkinson's disease (PD). GD manifests with considerable clinical heterogeneity and is also associated with an increased risk for PD. OBJECTIVE The objective of this study was to investigate the contribution of PD risk variants to risk for PD in patients with GD1. METHODS We studied 225 patients with GD1, including 199 without PD and 26 with PD. All cases were genotyped, and the genetic data were imputed using common pipelines. RESULTS On average, patients with GD1 with PD have a significantly higher PD genetic risk score than those without PD (P = 0.021). CONCLUSIONS Our results indicate that variants included in the PD genetic risk score were more frequent in patients with GD1 who developed PD, suggesting that common risk variants may affect underlying biological pathways. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.
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Affiliation(s)
- Cornelis Blauwendraat
- Integrative Neurogenomics Unit, Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Nahid Tayebi
- Medical Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Elizabeth Geena Woo
- Medical Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Grisel Lopez
- Medical Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Luca Fierro
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Marco Toffoli
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Naomi Limbachiya
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Derralynn Hughes
- Lysosomal Storage Diseases Unit, Royal Free London Hospital NHS Foundation Trust, and Department of Hematology , UCL, London, UK
| | - Vanessa Pitz
- Integrative Neurogenomics Unit, Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Dhairya Patel
- Integrative Neurogenomics Unit, Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Dan Vitale
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
- Data Tecnica International, Washington, DC, USA
| | - Mathew J. Koretsky
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Dena Hernandez
- Molecular Genetics Section, Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Raquel Real
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Roy N. Alcalay
- Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
- Neurological Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
| | - Mike A Nalls
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
- Data Tecnica International, Washington, DC, USA
- Molecular Genetics Section, Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Huw R Morris
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Anthony H. V. Schapira
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Manisha Balwani
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ellen Sidransky
- Medical Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
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11
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Fan J, Hale VL, Lelieveld LT, Whitworth LJ, Busch-Nentwich EM, Troll M, Edelstein PH, Cox TM, Roca FJ, Aerts JMFG, Ramakrishnan L. Gaucher disease protects against tuberculosis. Proc Natl Acad Sci U S A 2023; 120:e2217673120. [PMID: 36745788 PMCID: PMC7614233 DOI: 10.1073/pnas.2217673120] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Accepted: 12/31/2022] [Indexed: 02/08/2023] Open
Abstract
Biallelic mutations in the glucocerebrosidase (GBA1) gene cause Gaucher disease, characterized by lysosomal accumulation of glucosylceramide and glucosylsphingosine in macrophages. Gaucher and other lysosomal diseases occur with high frequency in Ashkenazi Jews. It has been proposed that the underlying mutations confer a selective advantage, in particular conferring protection against tuberculosis. Here, using a zebrafish Gaucher disease model, we find that the mutation GBA1 N370S, predominant among Ashkenazi Jews, increases resistance to tuberculosis through the microbicidal activity of glucosylsphingosine in macrophage lysosomes. Consistent with lysosomal accumulation occurring only in homozygotes, heterozygotes remain susceptible to tuberculosis. Thus, our findings reveal a mechanistic basis for protection against tuberculosis by GBA1 N370S and provide biological plausibility for its selection if the relatively mild deleterious effects in homozygotes were offset by significant protection against tuberculosis, a rampant killer of the young in Europe through the Middle Ages into the 19th century.
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Affiliation(s)
- Jingwen Fan
- Molecular Immunity Unit, Cambridge Institute of Therapeutic Immunology and Infectious Diseases, Department of Medicine, University of Cambridge, CambridgeCB2 0QH, UK
- MRC Laboratory of Molecular Biology, CambridgeCB2 0QH, UK
| | | | - Lindsey T. Lelieveld
- Department of Medical Biochemistry, Leiden Institute of Chemistry, Leiden University2333 CC, Leiden, The Netherlands
| | - Laura J. Whitworth
- Molecular Immunity Unit, Cambridge Institute of Therapeutic Immunology and Infectious Diseases, Department of Medicine, University of Cambridge, CambridgeCB2 0QH, UK
- MRC Laboratory of Molecular Biology, CambridgeCB2 0QH, UK
| | - Elisabeth M. Busch-Nentwich
- Molecular Immunity Unit, Cambridge Institute of Therapeutic Immunology and Infectious Diseases, Department of Medicine, University of Cambridge, CambridgeCB2 0QH, UK
- School of Biological and Behavioral Sciences, Queen Mary University of London, LondonE1 4NS, UK
| | - Mark Troll
- Molecular Immunity Unit, Cambridge Institute of Therapeutic Immunology and Infectious Diseases, Department of Medicine, University of Cambridge, CambridgeCB2 0QH, UK
- MRC Laboratory of Molecular Biology, CambridgeCB2 0QH, UK
| | - Paul H. Edelstein
- Molecular Immunity Unit, Cambridge Institute of Therapeutic Immunology and Infectious Diseases, Department of Medicine, University of Cambridge, CambridgeCB2 0QH, UK
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, PhiladelphiaPA19104
| | - Timothy M. Cox
- Department of Medicine, University of Cambridge, CambridgeCB2 0QQ, UK
| | - Francisco J. Roca
- Molecular Immunity Unit, Cambridge Institute of Therapeutic Immunology and Infectious Diseases, Department of Medicine, University of Cambridge, CambridgeCB2 0QH, UK
- Department of Biochemistry and Molecular Biology B and Immunology, University of Murcia, Murcia30120, Spain
- Biomedical Research Institute of Murcia Pascual Parrilla (IMIB-Arrixaca), Murcia30120, Spain
| | - Johannes M. F. G. Aerts
- Department of Medical Biochemistry, Leiden Institute of Chemistry, Leiden University2333 CC, Leiden, The Netherlands
| | - Lalita Ramakrishnan
- Molecular Immunity Unit, Cambridge Institute of Therapeutic Immunology and Infectious Diseases, Department of Medicine, University of Cambridge, CambridgeCB2 0QH, UK
- MRC Laboratory of Molecular Biology, CambridgeCB2 0QH, UK
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Kotambail A, Selvam P, Muthusamy K, Thomas M, Sudhakar SV, Ghati C, Danda S, Arunachal G. Clustering of Juvenile Canavan disease in an Indian community due to population bottleneck and isolation: genomic signatures of a founder event. Eur J Hum Genet 2023; 31:73-80. [PMID: 36202930 PMCID: PMC9823096 DOI: 10.1038/s41431-022-01198-4] [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: 06/14/2022] [Revised: 08/10/2022] [Accepted: 09/15/2022] [Indexed: 02/08/2023] Open
Abstract
Mild/juvenile Canavan disease (M/JCD) is less frequently reported in the literature and little is known about its pathogenetic mechanisms. We report a comprehensive investigation into the pathogenetic mechanism of a novel NM_000049.4(ASPA):c.526G>A variant in two families. The families belong to Telugu Devanga Chettiar community (TDC) from southern India. TDC has a complex history of migration from their historical origin centuries ago with high endogamy. TDC probably has the highest clustering M/JCD recorded historically (around 24 cases). The pathogenic variant was shown to cause non-classical splicing defect resulting in two different transcripts. The splicing aberration, a loss of function mechanism coupled with a milder missense effect can explain the milder phenotype compared to the infantile-onset CD. The high clustering of an extremely rare form of neurodegenerative disorder with reduced fitness, led us to speculate the possibility of a founder event. Genotyping array of TDC and multiple distinct populations of Indian origin for several population genetic parameters was performed. It yielded robust signatures of a founder event in TDC, such as a high fixation index, increased runs of homozygosity and identity-by-descent in the absence of consanguinity; a large haplotype with high linkage disequilibrium among markers comprising the pathogenic variant; a robust population structure; mutation dating, estimating the age of the potential founder of TDC at around 375 years; possibly a high carrier rate in TDC. This study has not only focused its attention on natural history and pathogenetics but also paves way for carrier screening programs in TDC and future therapeutic studies.
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Affiliation(s)
- Ananthapadmanabha Kotambail
- Department of Human Genetics, National Institute of Mental Health and Neuro Sciences (NIMHANS), Bengaluru, Karnataka, India
| | - Pavalan Selvam
- Department of Clinical Genetics, Christian Medical College and Hospital, Vellore, Tamil Nadu, India
| | - Karthik Muthusamy
- Paediatric Neurology Unit, Department of Neurological Sciences, Christian Medical College and Hospital, Vellore, Tamil Nadu, India
| | - Maya Thomas
- Paediatric Neurology Unit, Department of Neurological Sciences, Christian Medical College and Hospital, Vellore, Tamil Nadu, India
| | - Sniya Valsa Sudhakar
- Department of Radiodiagnosis, Christian Medical College and Hospital, Vellore, Tamil Nadu, India
| | - Chetan Ghati
- Department of Human Genetics, National Institute of Mental Health and Neuro Sciences (NIMHANS), Bengaluru, Karnataka, India
| | - Sumita Danda
- Department of Clinical Genetics, Christian Medical College and Hospital, Vellore, Tamil Nadu, India
| | - Gautham Arunachal
- Department of Human Genetics, National Institute of Mental Health and Neuro Sciences (NIMHANS), Bengaluru, Karnataka, India.
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13
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Genome-wide data from medieval German Jews show that the Ashkenazi founder event pre-dated the 14 th century. Cell 2022; 185:4703-4716.e16. [PMID: 36455558 PMCID: PMC9793425 DOI: 10.1016/j.cell.2022.11.002] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2022] [Revised: 08/26/2022] [Accepted: 11/01/2022] [Indexed: 12/05/2022]
Abstract
We report genome-wide data from 33 Ashkenazi Jews (AJ), dated to the 14th century, obtained following a salvage excavation at the medieval Jewish cemetery of Erfurt, Germany. The Erfurt individuals are genetically similar to modern AJ, but they show more variability in Eastern European-related ancestry than modern AJ. A third of the Erfurt individuals carried a mitochondrial lineage common in modern AJ and eight carried pathogenic variants known to affect AJ today. These observations, together with high levels of runs of homozygosity, suggest that the Erfurt community had already experienced the major reduction in size that affected modern AJ. The Erfurt bottleneck was more severe, implying substructure in medieval AJ. Overall, our results suggest that the AJ founder event and the acquisition of the main sources of ancestry pre-dated the 14th century and highlight late medieval genetic heterogeneity no longer present in modern AJ.
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Brace S, Diekmann Y, Booth T, Macleod R, Timpson A, Stephen W, Emery G, Cabot S, Thomas MG, Barnes I. Genomes from a medieval mass burial show Ashkenazi-associated hereditary diseases pre-date the 12th century. Curr Biol 2022; 32:4350-4359.e6. [PMID: 36044903 PMCID: PMC10499757 DOI: 10.1016/j.cub.2022.08.036] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 07/26/2022] [Accepted: 08/12/2022] [Indexed: 11/16/2022]
Abstract
We report genome sequence data from six individuals excavated from the base of a medieval well at a site in Norwich, UK. A revised radiocarbon analysis of the assemblage is consistent with these individuals being part of a historically attested episode of antisemitic violence on 6 February 1190 CE. We find that four of these individuals were closely related and all six have strong genetic affinities with modern Ashkenazi Jews. We identify four alleles associated with genetic disease in Ashkenazi Jewish populations and infer variation in pigmentation traits, including the presence of red hair. Simulations indicate that Ashkenazi-associated genetic disease alleles were already at appreciable frequencies, centuries earlier than previously hypothesized. These findings provide new insights into a significant historical crime, into Ashkenazi population history, and into the origins of genetic diseases associated with modern Jewish populations.
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Affiliation(s)
- Selina Brace
- Department of Earth Sciences, The Natural History Museum, Cromwell Road, London SW7 5BD, UK
| | - Yoan Diekmann
- Research Department of Genetics, Evolution and Environment, University College London, Gower Street, London WC1E 6BT, UK; Palaeogenetics Group, Institute of Organismic and Molecular Evolution (iomE), Johannes Gutenberg-University Mainz, 55099 Mainz, Germany
| | - Thomas Booth
- Department of Earth Sciences, The Natural History Museum, Cromwell Road, London SW7 5BD, UK; Francis Crick Institute, London NW1 1AT, UK; UCL Genetics Institute, University College London, London, UK
| | - Ruairidh Macleod
- Department of Earth Sciences, The Natural History Museum, Cromwell Road, London SW7 5BD, UK; Research Department of Genetics, Evolution and Environment, University College London, Gower Street, London WC1E 6BT, UK; Department of Archaeology, University of Cambridge, Downing Street, Cambridge CB2 3DZ, UK
| | - Adrian Timpson
- Research Department of Genetics, Evolution and Environment, University College London, Gower Street, London WC1E 6BT, UK
| | - Will Stephen
- Department of Earth Sciences, The Natural History Museum, Cromwell Road, London SW7 5BD, UK
| | - Giles Emery
- Norvic Archaeology, 7 Foxburrow Road, Norwich NR7 8QU, UK
| | - Sophie Cabot
- Norfolk Record Office, The Archive Centre, Martineau Lane, Norwich, Norfolk NR1 2DQ, UK
| | - Mark G Thomas
- Research Department of Genetics, Evolution and Environment, University College London, Gower Street, London WC1E 6BT, UK.
| | - Ian Barnes
- Department of Earth Sciences, The Natural History Museum, Cromwell Road, London SW7 5BD, UK.
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15
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Elhaik E. Principal Component Analyses (PCA)-based findings in population genetic studies are highly biased and must be reevaluated. Sci Rep 2022; 12:14683. [PMID: 36038559 PMCID: PMC9424212 DOI: 10.1038/s41598-022-14395-4] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Accepted: 06/06/2022] [Indexed: 12/29/2022] Open
Abstract
Principal Component Analysis (PCA) is a multivariate analysis that reduces the complexity of datasets while preserving data covariance. The outcome can be visualized on colorful scatterplots, ideally with only a minimal loss of information. PCA applications, implemented in well-cited packages like EIGENSOFT and PLINK, are extensively used as the foremost analyses in population genetics and related fields (e.g., animal and plant or medical genetics). PCA outcomes are used to shape study design, identify, and characterize individuals and populations, and draw historical and ethnobiological conclusions on origins, evolution, dispersion, and relatedness. The replicability crisis in science has prompted us to evaluate whether PCA results are reliable, robust, and replicable. We analyzed twelve common test cases using an intuitive color-based model alongside human population data. We demonstrate that PCA results can be artifacts of the data and can be easily manipulated to generate desired outcomes. PCA adjustment also yielded unfavorable outcomes in association studies. PCA results may not be reliable, robust, or replicable as the field assumes. Our findings raise concerns about the validity of results reported in the population genetics literature and related fields that place a disproportionate reliance upon PCA outcomes and the insights derived from them. We conclude that PCA may have a biasing role in genetic investigations and that 32,000-216,000 genetic studies should be reevaluated. An alternative mixed-admixture population genetic model is discussed.
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Affiliation(s)
- Eran Elhaik
- Department of Biology, Lund University, 22362, Lund, Sweden.
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16
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Tournebize R, Chu G, Moorjani P. Reconstructing the history of founder events using genome-wide patterns of allele sharing across individuals. PLoS Genet 2022; 18:e1010243. [PMID: 35737729 PMCID: PMC9223333 DOI: 10.1371/journal.pgen.1010243] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2022] [Accepted: 05/08/2022] [Indexed: 11/30/2022] Open
Abstract
Founder events play a critical role in shaping genetic diversity, fitness and disease risk in a population. Yet our understanding of the prevalence and distribution of founder events in humans and other species remains incomplete, as most existing methods require large sample sizes or phased genomes. Thus, we developed ASCEND that measures the correlation in allele sharing between pairs of individuals across the genome to infer the age and strength of founder events. We show that ASCEND can reliably estimate the parameters of founder events under a range of demographic scenarios. We then apply ASCEND to two species with contrasting evolutionary histories: ~460 worldwide human populations and ~40 modern dog breeds. In humans, we find that over half of the analyzed populations have evidence for recent founder events, associated with geographic isolation, modes of sustenance, or cultural practices such as endogamy. Notably, island populations have lower population sizes than continental groups and most hunter-gatherer, nomadic and indigenous groups have evidence of recent founder events. Many present-day groups––including Native Americans, Oceanians and South Asians––have experienced more extreme founder events than Ashkenazi Jews who have high rates of recessive diseases due their known history of founder events. Using ancient genomes, we show that the strength of founder events differs markedly across geographic regions and time––with three major founder events related to the peopling of Americas and a trend in decreasing strength of founder events in Europe following the Neolithic transition and steppe migrations. In dogs, we estimate extreme founder events in most breeds that occurred in the last 25 generations, concordant with the establishment of many dog breeds during the Victorian times. Our analysis highlights a widespread history of founder events in humans and dogs and elucidates some of the demographic and cultural practices related to these events. A founder event occurs when small numbers of ancestral individuals give rise to a large fraction of the population. Founder events reduce genetic variation and increase the risk of recessive diseases. Despite their importance in evolutionary and disease studies, we still only have a limited comprehension of their prevalence and properties in humans and other species, as most existing methods require large sample sizes or phased genomes. Here, we present a flexible method, ASCEND, to infer the timing and the strength of founder events that is suitable for sparse datasets with few samples or limited coverage. ASCEND provides reliable estimates across a wide range of demographic scenarios. By applying it to data from two species (humans and dogs), we document a widespread history of recent founder events in both species and provide insights about the demographic processes related to these events. Our analysis helps to identify groups with strong founder events that should be prioritized for future studies as they offer a unique opportunity for biological discovery and reducing disease burden through mapping of recessive disease-causing genes and pathways, as previously shown in studies of Ashkenazi Jews and Finns.
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Affiliation(s)
- Rémi Tournebize
- Department of Molecular and Cell Biology, University of California, Berkeley, California, United States of America
- Center for Computational Biology, University of California, Berkeley, California, United States of America
- * E-mail: (RT); (PM)
| | - Gillian Chu
- Department of Electrical Engineering and Computer Science, University of California, Berkeley, California, United States of America
| | - Priya Moorjani
- Department of Molecular and Cell Biology, University of California, Berkeley, California, United States of America
- Center for Computational Biology, University of California, Berkeley, California, United States of America
- * E-mail: (RT); (PM)
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17
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Thorstensen MJ, Euclide PT, Jeffrey JD, Shi Y, Treberg JR, Watkinson DA, Enders EC, Larson WA, Kobayashi Y, Jeffries KM. A chromosomal inversion may facilitate adaptation despite periodic gene flow in a freshwater fish. Ecol Evol 2022; 12:e8898. [PMID: 35571758 PMCID: PMC9077824 DOI: 10.1002/ece3.8898] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Revised: 04/18/2022] [Accepted: 04/19/2022] [Indexed: 11/11/2022] Open
Affiliation(s)
- Matt J. Thorstensen
- Department of Biological Sciences University of Manitoba Winnipeg Manitoba Canada
| | - Peter T. Euclide
- Wisconsin Cooperative Fishery Research Unit College of Natural Resources U.S. Geological Survey University of Wisconsin‐Stevens Point Stevens Point Wisconsin USA
| | - Jennifer D. Jeffrey
- Department of Biological Sciences University of Manitoba Winnipeg Manitoba Canada
- Department of Biology Richardson College University of Winnipeg Winnipeg Manitoba Canada
| | - Yue Shi
- Wisconsin Cooperative Fishery Research Unit College of Natural Resources U.S. Geological Survey University of Wisconsin‐Stevens Point Stevens Point Wisconsin USA
- College of Fisheries and Ocean Sciences University of Alaska Fairbanks Juneau Alaska USA
| | - Jason R. Treberg
- Department of Biological Sciences University of Manitoba Winnipeg Manitoba Canada
| | | | - Eva C. Enders
- Freshwater Institute, Fisheries and Oceans Canada Winnipeg Manitoba Canada
| | - Wesley A. Larson
- Wisconsin Cooperative Fishery Research Unit College of Natural Resources U.S. Geological Survey University of Wisconsin‐Stevens Point Stevens Point Wisconsin USA
- National Oceanographic and Atmospheric Administration National Marine Fisheries Service Alaska Fisheries Science Center Auke Bay Laboratories Juneau Alaska USA
| | - Yasuhiro Kobayashi
- Department of Biological Sciences Fort Hays State University Hays Kansas USA
- Department of Biology The College of St. Scholastica Duluth Minnesota USA
| | - Ken M. Jeffries
- Department of Biological Sciences University of Manitoba Winnipeg Manitoba Canada
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18
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Makarious MB, Leonard HL, Vitale D, Iwaki H, Sargent L, Dadu A, Violich I, Hutchins E, Saffo D, Bandres-Ciga S, Kim JJ, Song Y, Maleknia M, Bookman M, Nojopranoto W, Campbell RH, Hashemi SH, Botia JA, Carter JF, Craig DW, Van Keuren-Jensen K, Morris HR, Hardy JA, Blauwendraat C, Singleton AB, Faghri F, Nalls MA. Multi-modality machine learning predicting Parkinson's disease. NPJ Parkinsons Dis 2022; 8:35. [PMID: 35365675 PMCID: PMC8975993 DOI: 10.1038/s41531-022-00288-w] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Accepted: 02/01/2022] [Indexed: 02/06/2023] Open
Abstract
Personalized medicine promises individualized disease prediction and treatment. The convergence of machine learning (ML) and available multimodal data is key moving forward. We build upon previous work to deliver multimodal predictions of Parkinson's disease (PD) risk and systematically develop a model using GenoML, an automated ML package, to make improved multi-omic predictions of PD, validated in an external cohort. We investigated top features, constructed hypothesis-free disease-relevant networks, and investigated drug-gene interactions. We performed automated ML on multimodal data from the Parkinson's progression marker initiative (PPMI). After selecting the best performing algorithm, all PPMI data was used to tune the selected model. The model was validated in the Parkinson's Disease Biomarker Program (PDBP) dataset. Our initial model showed an area under the curve (AUC) of 89.72% for the diagnosis of PD. The tuned model was then tested for validation on external data (PDBP, AUC 85.03%). Optimizing thresholds for classification increased the diagnosis prediction accuracy and other metrics. Finally, networks were built to identify gene communities specific to PD. Combining data modalities outperforms the single biomarker paradigm. UPSIT and PRS contributed most to the predictive power of the model, but the accuracy of these are supplemented by many smaller effect transcripts and risk SNPs. Our model is best suited to identifying large groups of individuals to monitor within a health registry or biobank to prioritize for further testing. This approach allows complex predictive models to be reproducible and accessible to the community, with the package, code, and results publicly available.
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Affiliation(s)
- Mary B Makarious
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, UK
- UCL Movement Disorders Centre, University College London, London, UK
| | - Hampton L Leonard
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
- Center for Alzheimer's and Related Dementias, National Institutes of Health, Bethesda, MD, USA
- Data Tecnica International LLC, Glen Echo, MD, USA
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
| | - Dan Vitale
- Center for Alzheimer's and Related Dementias, National Institutes of Health, Bethesda, MD, USA
- Data Tecnica International LLC, Glen Echo, MD, USA
| | - Hirotaka Iwaki
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
- Center for Alzheimer's and Related Dementias, National Institutes of Health, Bethesda, MD, USA
- Data Tecnica International LLC, Glen Echo, MD, USA
| | - Lana Sargent
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
- Center for Alzheimer's and Related Dementias, National Institutes of Health, Bethesda, MD, USA
- School of Nursing, Virginia Commonwealth University, Richmond, VA, USA
- Geriatric Pharmacotherapy Program, School of Pharmacy, Virginia Commonwealth University, Richmond, VA, USA
| | - Anant Dadu
- Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Ivo Violich
- Institute of Translational Genomics, University of Southern California, Los Angeles, CA, USA
| | - Elizabeth Hutchins
- Neurogenomics Division, Translational Genomics Research Institute (TGen), Phoenix, AZ, USA
| | - David Saffo
- Khoury College of Computer Sciences, Northeastern University, Boston, MA, USA
| | - Sara Bandres-Ciga
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Jonggeol Jeff Kim
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
- Preventive Neurology Unit, Wolfson Institute of Preventive Medicine, Queen Mary University of London, London, UK
| | - Yeajin Song
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
- Data Tecnica International LLC, Glen Echo, MD, USA
| | | | - Matt Bookman
- Verily Life Sciences, South San Francisco, CA, USA
| | | | - Roy H Campbell
- Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Sayed Hadi Hashemi
- Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Juan A Botia
- Department of Molecular Neuroscience, UCL Queen Square Institute of Neurology, London, UK
- Departamento de Ingeniería de la Información y las Comunicaciones, Universidad de Murcia, Murcia, Spain
| | | | - David W Craig
- Institute of Translational Genomics, University of Southern California, Los Angeles, CA, USA
| | | | - Huw R Morris
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, UK
- UCL Movement Disorders Centre, University College London, London, UK
| | - John A Hardy
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, UK
- UCL Movement Disorders Centre, University College London, London, UK
- UK Dementia Research Institute and Department of Neurodegenerative Disease and Reta Lila Weston Institute, London, UK
- Institute for Advanced Study, The Hong Kong University of Science and Technology, Hong Kong, Hong Kong SAR, China
| | - Cornelis Blauwendraat
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Andrew B Singleton
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
- Center for Alzheimer's and Related Dementias, National Institutes of Health, Bethesda, MD, USA
| | - Faraz Faghri
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA.
- Center for Alzheimer's and Related Dementias, National Institutes of Health, Bethesda, MD, USA.
- Data Tecnica International LLC, Glen Echo, MD, USA.
| | - Mike A Nalls
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA.
- Center for Alzheimer's and Related Dementias, National Institutes of Health, Bethesda, MD, USA.
- Data Tecnica International LLC, Glen Echo, MD, USA.
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19
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Li JT, Wang Q, Huang Yang MD, Li QS, Cui MS, Dong ZJ, Wang HW, Yu JH, Zhao YJ, Yang CR, Wang YX, Sun XQ, Zhang Y, Zhao R, Jia ZY, Wang XY. Parallel subgenome structure and divergent expression evolution of allo-tetraploid common carp and goldfish. Nat Genet 2021; 53:1493-1503. [PMID: 34594040 PMCID: PMC8492472 DOI: 10.1038/s41588-021-00933-9] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Accepted: 08/05/2021] [Indexed: 02/08/2023]
Abstract
How two subgenomes in allo-tetraploids adapt to coexistence and coordinate through structure and expression evolution requires extensive studies. In the present study, we report an improved genome assembly of allo-tetraploid common carp, an updated genome annotation of allo-tetraploid goldfish and the chromosome-scale assemblies of a progenitor-like diploid Puntius tetrazona and an outgroup diploid Paracanthobrama guichenoti. Parallel subgenome structure evolution in the allo-tetraploids was featured with equivalent chromosome components, higher protein identities, similar transposon divergence and contents, homoeologous exchanges, better synteny level, strong sequence compensation and symmetric purifying selection. Furthermore, we observed subgenome expression divergence processes in the allo-tetraploids, including inter-/intrasubgenome trans-splicing events, expression dominance, decreased expression levels, dosage compensation, stronger expression correlation, dynamic functionalization and balancing of differential expression. The potential disorders introduced by different progenitors in the allo-tetraploids were hypothesized to be alleviated by increasing structural homogeneity and performing versatile expression processes. Resequencing three common carp strains revealed two major ecotypes and uncovered candidate genes relevant to growth and survival rate.
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Affiliation(s)
- Jiong-Tang Li
- Key Laboratory of Aquatic Genomics, Ministry of Agriculture and Rural Affairs, Beijing Key Laboratory of Fishery Biotechnology, Chinese Academy of Fishery Sciences, Beijing, China.
| | - Qi Wang
- Key Laboratory of Aquatic Genomics, Ministry of Agriculture and Rural Affairs, Beijing Key Laboratory of Fishery Biotechnology, Chinese Academy of Fishery Sciences, Beijing, China
| | - Mei-Di Huang Yang
- Key Laboratory of Aquatic Genomics, Ministry of Agriculture and Rural Affairs, Beijing Key Laboratory of Fishery Biotechnology, Chinese Academy of Fishery Sciences, Beijing, China
- College of Fisheries and Life Science, Shanghai Ocean University, Shanghai, China
| | - Qing-Song Li
- Key Laboratory of Aquatic Genomics, Ministry of Agriculture and Rural Affairs, Beijing Key Laboratory of Fishery Biotechnology, Chinese Academy of Fishery Sciences, Beijing, China
- College of Fisheries and Life Science, Shanghai Ocean University, Shanghai, China
| | - Ming-Shu Cui
- Key Laboratory of Aquatic Genomics, Ministry of Agriculture and Rural Affairs, Beijing Key Laboratory of Fishery Biotechnology, Chinese Academy of Fishery Sciences, Beijing, China
- Chinese Academy of Agricultural Sciences, Beijing, China
| | - Zai-Jie Dong
- Key Laboratory of Freshwater Fisheries and Germplasm Resources Utilization, Freshwater Fisheries Research Center of Chinese Academy of Fishery Sciences, Ministry of Agriculture and Rural Affairs, Wuxi, China
| | - Hong-Wei Wang
- Key Laboratory of Aquatic Genomics, Ministry of Agriculture and Rural Affairs, Beijing Key Laboratory of Fishery Biotechnology, Chinese Academy of Fishery Sciences, Beijing, China
| | - Ju-Hua Yu
- Key Laboratory of Freshwater Fisheries and Germplasm Resources Utilization, Freshwater Fisheries Research Center of Chinese Academy of Fishery Sciences, Ministry of Agriculture and Rural Affairs, Wuxi, China
| | - Yu-Jie Zhao
- Key Laboratory of Aquatic Genomics, Ministry of Agriculture and Rural Affairs, Beijing Key Laboratory of Fishery Biotechnology, Chinese Academy of Fishery Sciences, Beijing, China
- College of Fisheries and Life Science, Shanghai Ocean University, Shanghai, China
| | - Chen-Ru Yang
- Key Laboratory of Aquatic Genomics, Ministry of Agriculture and Rural Affairs, Beijing Key Laboratory of Fishery Biotechnology, Chinese Academy of Fishery Sciences, Beijing, China
| | - Ya-Xin Wang
- Key Laboratory of Aquatic Genomics, Ministry of Agriculture and Rural Affairs, Beijing Key Laboratory of Fishery Biotechnology, Chinese Academy of Fishery Sciences, Beijing, China
| | - Xiao-Qing Sun
- Key Laboratory of Aquatic Genomics, Ministry of Agriculture and Rural Affairs, Beijing Key Laboratory of Fishery Biotechnology, Chinese Academy of Fishery Sciences, Beijing, China
| | - Yan Zhang
- Key Laboratory of Aquatic Genomics, Ministry of Agriculture and Rural Affairs, Beijing Key Laboratory of Fishery Biotechnology, Chinese Academy of Fishery Sciences, Beijing, China
| | - Ran Zhao
- Key Laboratory of Aquatic Genomics, Ministry of Agriculture and Rural Affairs, Beijing Key Laboratory of Fishery Biotechnology, Chinese Academy of Fishery Sciences, Beijing, China
| | - Zhi-Ying Jia
- Heilongjiang River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Harbin, China
| | - Xi-Yin Wang
- North China University of Science and Technology, Tangshan, China
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20
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Iwaki H, Leonard HL, Makarious MB, Bookman M, Landin B, Vismer D, Casey B, Gibbs JR, Hernandez DG, Blauwendraat C, Vitale D, Song Y, Kumar D, Dalgard CL, Sadeghi M, Dong X, Misquitta L, Scholz SW, Scherzer CR, Nalls MA, Biswas S, Singleton AB. Accelerating Medicines Partnership: Parkinson's Disease. Genetic Resource. Mov Disord 2021; 36:1795-1804. [PMID: 33960523 PMCID: PMC8453903 DOI: 10.1002/mds.28549] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Revised: 01/20/2021] [Accepted: 02/11/2021] [Indexed: 02/03/2023] Open
Abstract
BACKGROUND Whole-genome sequencing data are available from several large studies across a variety of diseases and traits. However, massive storage and computation resources are required to use these data, and to achieve sufficient power for discoveries, harmonization of multiple cohorts is critical. OBJECTIVES The Accelerating Medicines Partnership Parkinson's Disease program has developed a research platform for Parkinson's disease (PD) that integrates the storage and analysis of whole-genome sequencing data, RNA expression data, and clinical data, harmonized across multiple cohort studies. METHODS The version 1 release contains whole-genome sequencing data derived from 3941 participants from 4 cohorts. Samples underwent joint genotyping by the TOPMed Freeze 9 Variant Calling Pipeline. We performed descriptive analyses of these whole-genome sequencing data using the Accelerating Medicines Partnership Parkinson's Disease platform. RESULTS The clinical diagnosis of participants in version 1 release includes 2005 idiopathic PD patients, 963 healthy controls, 64 prodromal subjects, 62 clinically diagnosed PD subjects without evidence of dopamine deficit, and 705 participants of genetically enriched cohorts carrying PD risk-associated GBA variants or LRRK2 variants, of whom 304 were affected. We did not observe significant enrichment of pathogenic variants in the idiopathic PD group, but the polygenic risk score was higher in PD both in nongenetically enriched cohorts and genetically enriched cohorts. The population analysis showed a correlation between genetically enriched cohorts and Ashkenazi Jewish ancestry. CONCLUSIONS We describe the genetic component of the Accelerating Medicines Partnership Parkinson's Disease platform, a solution to democratize data access and analysis for the PD research community. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. This article is a U.S. Government work and is in the public domain in the USA.
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Affiliation(s)
- Hirotaka Iwaki
- Data Tecnica InternationalGlen EchoMarylandUSA
- Center for Alzheimer's and Related DementiasNational Institute on AgingBethesdaMarylandUSA
- Laboratory of NeurogeneticsNational Institute on AgingBethesdaMarylandUSA
| | - Hampton L. Leonard
- Data Tecnica InternationalGlen EchoMarylandUSA
- Center for Alzheimer's and Related DementiasNational Institute on AgingBethesdaMarylandUSA
- Laboratory of NeurogeneticsNational Institute on AgingBethesdaMarylandUSA
| | - Mary B. Makarious
- Laboratory of NeurogeneticsNational Institute on AgingBethesdaMarylandUSA
| | | | | | | | - Bradford Casey
- The Michael J. Fox Foundation for Parkinson's ResearchNew YorkNew YorkUSA
| | - J. Raphael Gibbs
- Laboratory of NeurogeneticsNational Institute on AgingBethesdaMarylandUSA
| | - Dena G. Hernandez
- Laboratory of NeurogeneticsNational Institute on AgingBethesdaMarylandUSA
| | | | - Daniel Vitale
- Data Tecnica InternationalGlen EchoMarylandUSA
- Center for Alzheimer's and Related DementiasNational Institute on AgingBethesdaMarylandUSA
- Laboratory of NeurogeneticsNational Institute on AgingBethesdaMarylandUSA
| | - Yeajin Song
- Data Tecnica InternationalGlen EchoMarylandUSA
- Center for Alzheimer's and Related DementiasNational Institute on AgingBethesdaMarylandUSA
- Laboratory of NeurogeneticsNational Institute on AgingBethesdaMarylandUSA
| | | | - Clifton L. Dalgard
- Department of Anatomy, Physiology & GeneticsUniformed Services University of the Health SciencesBethesdaMarylandUSA
- The American Genome CenterUniformed Services University of the Health SciencesBethesdaMarylandUSA
| | - Mahdiar Sadeghi
- SanofiFraminghamMassachusettsUSA
- Northeastern UniversityBostonMassachusettsUSA
| | - Xianjun Dong
- Harvard Medical SchoolBrigham and Women's HospitalBostonMassachusettsUSA
| | | | - Sonja W. Scholz
- National Institute of Neurological Disorders and StrokeBethesdaMarylandUSA
- Department of NeurologyJohns Hopkins UniversityBaltimoreMarylandUSA
| | | | - Mike A. Nalls
- Data Tecnica InternationalGlen EchoMarylandUSA
- Center for Alzheimer's and Related DementiasNational Institute on AgingBethesdaMarylandUSA
- Laboratory of NeurogeneticsNational Institute on AgingBethesdaMarylandUSA
| | | | - Andrew B. Singleton
- Center for Alzheimer's and Related DementiasNational Institute on AgingBethesdaMarylandUSA
- Laboratory of NeurogeneticsNational Institute on AgingBethesdaMarylandUSA
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21
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The Genetic Analyses of French Canadians of Quebec Facilitate the Characterization of New Cancer Predisposing Genes Implicated in Hereditary Breast and/or Ovarian Cancer Syndrome Families. Cancers (Basel) 2021; 13:cancers13143406. [PMID: 34298626 PMCID: PMC8305212 DOI: 10.3390/cancers13143406] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Revised: 06/23/2021] [Accepted: 06/24/2021] [Indexed: 12/19/2022] Open
Abstract
The French Canadian population of the province of Quebec has been recognized for its contribution to research in medical genetics, especially in defining the role of heritable pathogenic variants in cancer predisposing genes. Multiple carriers of a limited number of pathogenic variants in BRCA1 and BRCA2, the major risk genes for hereditary breast and/or ovarian cancer syndrome families, have been identified in French Canadians, which is in stark contrast to the array of over 2000 different pathogenic variants reported in each of these genes in other populations. As not all such cancer syndrome families are explained by BRCA1 and BRCA2, newly proposed gene candidates identified in other populations have been investigated for their role in conferring risk in French Canadian cancer families. For example, multiple carriers of distinct variants were identified in PALB2 and RAD51D. The unique genetic architecture of French Canadians has been attributed to shared ancestry due to common ancestors of early settlers of this population with origins mainly from France. In this review, we discuss the merits of genetically characterizing cancer predisposing genes in French Canadians of Quebec. We focused on genes that have been implicated in hereditary breast and/or ovarian cancer syndrome families as they have been the most thoroughly characterized cancer syndromes in this population. We describe how genetic analyses of French Canadians have facilitated: (i) the classification of variants in BRCA1 and BRCA2; (ii) the identification and classification of variants in newly proposed breast and/or ovarian cancer predisposing genes; and (iii) the identification of a new breast cancer predisposing gene candidate, RECQL. The genetic architecture of French Canadians provides a unique opportunity to evaluate new candidate cancer predisposing genes regardless of the population in which they were identified.
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22
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Eslami Rasekh M, Hernández Y, Drinan SD, Fuxman Bass J, Benson G. Genome-wide characterization of human minisatellite VNTRs: population-specific alleles and gene expression differences. Nucleic Acids Res 2021; 49:4308-4324. [PMID: 33849068 PMCID: PMC8096271 DOI: 10.1093/nar/gkab224] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2020] [Revised: 03/06/2021] [Accepted: 03/18/2021] [Indexed: 11/12/2022] Open
Abstract
Variable Number Tandem Repeats (VNTRs) are tandem repeat (TR) loci that vary in copy number across a population. Using our program, VNTRseek, we analyzed human whole genome sequencing datasets from 2770 individuals in order to detect minisatellite VNTRs, i.e., those with pattern sizes ≥7 bp. We detected 35 638 VNTR loci and classified 5676 as commonly polymorphic (i.e. with non-reference alleles occurring in >5% of the population). Commonly polymorphic VNTR loci were found to be enriched in genomic regions with regulatory function, i.e. transcription start sites and enhancers. Investigation of the commonly polymorphic VNTRs in the context of population ancestry revealed that 1096 loci contained population-specific alleles and that those could be used to classify individuals into super-populations with near-perfect accuracy. Search for quantitative trait loci (eQTLs), among the VNTRs proximal to genes, indicated that in 187 genes expression differences correlated with VNTR genotype. We validated our predictions in several ways, including experimentally, through the identification of predicted alleles in long reads, and by comparisons showing consistency between sequencing platforms. This study is the most comprehensive analysis of minisatellite VNTRs in the human population to date.
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Affiliation(s)
| | - Yözen Hernández
- Graduate Program in Bioinformatics, Boston University, Boston, MA 02215, USA
| | | | - Juan I Fuxman Bass
- Graduate Program in Bioinformatics, Boston University, Boston, MA 02215, USA
- Department of Biology, Boston University, Boston, MA 02215, USA
| | - Gary Benson
- Graduate Program in Bioinformatics, Boston University, Boston, MA 02215, USA
- Department of Biology, Boston University, Boston, MA 02215, USA
- Department of Computer Science, Boston University, Boston, MA 02215, USA
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23
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Lucek K, Willi Y. Drivers of linkage disequilibrium across a species' geographic range. PLoS Genet 2021; 17:e1009477. [PMID: 33770075 PMCID: PMC8026057 DOI: 10.1371/journal.pgen.1009477] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2020] [Revised: 04/07/2021] [Accepted: 03/09/2021] [Indexed: 11/25/2022] Open
Abstract
While linkage disequilibrium (LD) is an important parameter in genetics and evolutionary biology, the drivers of LD remain elusive. Using whole-genome sequences from across a species’ range, we assessed the impact of demographic history and mating system on LD. Both range expansion and a shift from outcrossing to selfing in North American Arabidopsis lyrata were associated with increased average genome-wide LD. Our results indicate that range expansion increases short-distance LD at the farthest range edges by about the same amount as a shift to selfing. However, the extent over which LD in genic regions unfolds was shorter for range expansion compared to selfing. Linkage among putatively neutral variants and between neutral and deleterious variants increased to a similar degree with range expansion, providing support that genome-wide LD was positively associated with mutational load. As a consequence, LD combined with mutational load may decelerate range expansions and set range limits. Finally, a small number of genes were identified as LD outliers, suggesting that they experience selection by either of the two demographic processes. These included genes involved in flowering and photoperiod for range expansion, and the self-incompatibility locus for mating system. Nearby genomic variants are often co-inherited because of limited recombination. The extent of non-random association of alleles at different loci is called linkage disequilibrium (LD) and is commonly used in genomic analyses, for example to detect regions under selection or to determine effective population size. Here we reversed testing and addressed how demographic history may affect LD within a species. Using genomic data from more than a thousand individuals of North American Arabidopsis lyrata from across the entire species’ range, we quantified the effect of postglacial range expansion and a shift in mating system from outcrossing to selfing on LD. We show that both factors lead to increased LD, and that the maximal effect of range expansion is comparable with a shift in mating system to selfing. Heightened LD involves deleterious mutations, and therefore, LD can also serve as an indicator of mutation accumulation. Furthermore, we provide evidence that some genes experienced stronger increases in LD possibly due to selection associated with the two demographic changes. Our results provide a novel and broad view on the evolutionary factors shaping LD that may also apply to the very many species that underwent postglacial range expansion.
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Affiliation(s)
- Kay Lucek
- Department of Environmental Sciences, University of Basel, Basel, Switzerland
- * E-mail:
| | - Yvonne Willi
- Department of Environmental Sciences, University of Basel, Basel, Switzerland
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24
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Lahrouchi N, Postma AV, Salazar CM, De Laughter DM, Tjong F, Piherová L, Bowling FZ, Zimmerman D, Lodder EM, Ta-Shma A, Perles Z, Beekman L, Ilgun A, Gunst Q, Hababa M, Škorić-Milosavljević D, Stránecký V, Tomek V, de Knijff P, de Leeuw R, Robinson JY, Burn SC, Mustafa H, Ambrose M, Moss T, Jacober J, Niyazov DM, Wolf B, Kim KH, Cherny S, Rousounides A, Aristidou-Kallika A, Tanteles G, Ange-Line B, Denommé-Pichon AS, Francannet C, Ortiz D, Haak MC, Ten Harkel AD, Manten GT, Dutman AC, Bouman K, Magliozzi M, Radio FC, Santen GW, Herkert JC, Brown HA, Elpeleg O, van den Hoff MJ, Mulder B, Airola MV, Kmoch S, Barnett JV, Clur SA, Frohman MA, Bezzina CR. Biallelic loss-of-function variants in PLD1 cause congenital right-sided cardiac valve defects and neonatal cardiomyopathy. J Clin Invest 2021; 131:142148. [PMID: 33645542 DOI: 10.1172/jci142148] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Accepted: 12/16/2020] [Indexed: 01/12/2023] Open
Abstract
Congenital heart disease is the most common type of birth defect, accounting for one-third of all congenital anomalies. Using whole-exome sequencing of 2718 patients with congenital heart disease and a search in GeneMatcher, we identified 30 patients from 21 unrelated families of different ancestries with biallelic phospholipase D1 (PLD1) variants who presented predominantly with congenital cardiac valve defects. We also associated recessive PLD1 variants with isolated neonatal cardiomyopathy. Furthermore, we established that p.I668F is a founder variant among Ashkenazi Jews (allele frequency of ~2%) and describe the phenotypic spectrum of PLD1-associated congenital heart defects. PLD1 missense variants were overrepresented in regions of the protein critical for catalytic activity, and, correspondingly, we observed a strong reduction in enzymatic activity for most of the mutant proteins in an enzymatic assay. Finally, we demonstrate that PLD1 inhibition decreased endothelial-mesenchymal transition, an established pivotal early step in valvulogenesis. In conclusion, our study provides a more detailed understanding of disease mechanisms and phenotypic expression associated with PLD1 loss of function.
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Affiliation(s)
- Najim Lahrouchi
- Amsterdam UMC, University of Amsterdam, Heart Center, Department of Clinical and Experimental Cardiology, Amsterdam Cardiovascular Sciences
| | - Alex V Postma
- Department of Clinical Genetics, and.,Department of Medical Biology, Amsterdam UMC, Amsterdam, Netherlands
| | - Christian M Salazar
- Department of Pharmacological Sciences and Graduate Program in Molecular and Cellular Pharmacology, Stony Brook University, Stony Brook, New York, USA
| | - Daniel M De Laughter
- Department of Cell and Developmental Biology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Fleur Tjong
- Amsterdam UMC, University of Amsterdam, Heart Center, Department of Clinical and Experimental Cardiology, Amsterdam Cardiovascular Sciences
| | - Lenka Piherová
- Research Unit for Rare Diseases, Department of Pediatrics and Adolescent Medicine, 1st Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Forrest Z Bowling
- Department of Biochemistry and Cell Biology, Stony Brook University, Stony Brook, New York, USA
| | - Dominic Zimmerman
- Amsterdam UMC, University of Amsterdam, Heart Center, Department of Clinical and Experimental Cardiology, Amsterdam Cardiovascular Sciences
| | - Elisabeth M Lodder
- Amsterdam UMC, University of Amsterdam, Heart Center, Department of Clinical and Experimental Cardiology, Amsterdam Cardiovascular Sciences
| | - Asaf Ta-Shma
- Department of Pediatric Cardiology, Hadassah, Hebrew University Medical Center, Jerusalem, Israel
| | - Zeev Perles
- Department of Pediatric Cardiology, Hadassah, Hebrew University Medical Center, Jerusalem, Israel
| | - Leander Beekman
- Amsterdam UMC, University of Amsterdam, Heart Center, Department of Clinical and Experimental Cardiology, Amsterdam Cardiovascular Sciences
| | - Aho Ilgun
- Department of Medical Biology, Amsterdam UMC, Amsterdam, Netherlands
| | - Quinn Gunst
- Department of Medical Biology, Amsterdam UMC, Amsterdam, Netherlands
| | - Mariam Hababa
- Amsterdam UMC, University of Amsterdam, Heart Center, Department of Clinical and Experimental Cardiology, Amsterdam Cardiovascular Sciences
| | - Doris Škorić-Milosavljević
- Amsterdam UMC, University of Amsterdam, Heart Center, Department of Clinical and Experimental Cardiology, Amsterdam Cardiovascular Sciences
| | - Viktor Stránecký
- Research Unit for Rare Diseases, Department of Pediatrics and Adolescent Medicine, 1st Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Viktor Tomek
- Children's Heart Centre, 2nd Faculty of Medicine, Charles University in Prague, Motol University Hospital, Prague, Czech Republic
| | - Peter de Knijff
- Department of Human Genetics, Leiden University Medical Centre, Leiden, Netherlands
| | - Rick de Leeuw
- Department of Human Genetics, Leiden University Medical Centre, Leiden, Netherlands
| | - Jamille Y Robinson
- Department of Pharmacology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | | | - Hiba Mustafa
- Department of Obstetrics, Gynecology and Women's Health
| | - Matthew Ambrose
- Department of Pediatrics, Division of Pediatric Cardiology, and
| | - Timothy Moss
- Department of Pediatrics, University of Minnesota, Minneapolis, Minnesota, USA
| | - Jennifer Jacober
- Department of Pediatrics, Ochsner Clinic, Tulane University, University of Queensland, New Orleans, Louisiana, USA
| | - Dmitriy M Niyazov
- Department of Pediatrics, Ochsner Clinic, Tulane University, University of Queensland, New Orleans, Louisiana, USA
| | - Barry Wolf
- Division of Genetics, Birth Defects and Metabolic Disorders, Ann and Robert H. Lurie Children's Hospital of Chicago, Chicago, Illinois, USA.,Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Katherine H Kim
- Division of Genetics, Birth Defects and Metabolic Disorders, Ann and Robert H. Lurie Children's Hospital of Chicago, Chicago, Illinois, USA.,Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Sara Cherny
- Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA.,Division of Cardiology, Ann and Robert H. Lurie Children's Hospital of Chicago, Chicago, Illinois, USA
| | | | | | - George Tanteles
- Cyprus School of Molecular Medicine, Nicosia, Cyprus.,Department of Clinical Genetics, The Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus
| | - Bruel Ange-Line
- UMR 1231 INSERM, GAD, Université Bourgogne Franche-Comté, Dijon, France.,Unité Fonctionnelle d'Innovation en Diagnostique Génomique des Maladies Rares, FHU-TRANSLAD, Centre Hospitalier Universitaire Estaing (CHU), Dijon Bourgogne, Dijon, France
| | - Anne-Sophie Denommé-Pichon
- UMR 1231 INSERM, GAD, Université Bourgogne Franche-Comté, Dijon, France.,Unité Fonctionnelle d'Innovation en Diagnostique Génomique des Maladies Rares, FHU-TRANSLAD, Centre Hospitalier Universitaire Estaing (CHU), Dijon Bourgogne, Dijon, France
| | | | - Damara Ortiz
- Medical Genetics Department, UPMC Children's Hospital of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | | | - Arend D.J. Ten Harkel
- Department of Pediatric Cardiology, Leiden University Medical Centre, Leiden, Netherlands
| | | | - Annemiek C Dutman
- Department of Pathology, Isala Women and Children's Hospital, Zwolle, Netherlands
| | - Katelijne Bouman
- University Medical Center Groningen, Department of Genetics, University of Groningen, Groningen, Netherlands
| | - Monia Magliozzi
- Genetic and Rare Disease Research Division, Bambino Gesù Children's Hospital IRCCS, Rome, Italy
| | | | - Gijs We Santen
- Department of Human Genetics, Leiden University Medical Center, Leiden, Netherlands
| | - Johanna C Herkert
- University Medical Center Groningen, Department of Genetics, University of Groningen, Groningen, Netherlands
| | - H Alex Brown
- Department of Pharmacology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Orly Elpeleg
- Department of Genetics, Hadassah, Hebrew University Medical Center, Jerusalem, Israel
| | | | - Barbara Mulder
- Amsterdam UMC, University of Amsterdam, Heart Center, Department of Clinical and Experimental Cardiology, Amsterdam Cardiovascular Sciences
| | - Michael V Airola
- Department of Biochemistry and Cell Biology, Stony Brook University, Stony Brook, New York, USA
| | - Stanislav Kmoch
- Research Unit for Rare Diseases, Department of Pediatrics and Adolescent Medicine, 1st Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Joey V Barnett
- Department of Pharmacology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Sally-Ann Clur
- Department of Pediatric Cardiology, Emma Children's Hospital, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Michael A Frohman
- Department of Pharmacological Sciences and Graduate Program in Molecular and Cellular Pharmacology, Stony Brook University, Stony Brook, New York, USA
| | - Connie R Bezzina
- Amsterdam UMC, University of Amsterdam, Heart Center, Department of Clinical and Experimental Cardiology, Amsterdam Cardiovascular Sciences
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25
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Noë M, Hong SM, Wood LD, Thompson ED, Roberts NJ, Goggins MG, Klein AP, Eshleman JR, Kern SE, Hruban RH. Pancreatic cancer pathology viewed in the light of evolution. Cancer Metastasis Rev 2021; 40:661-674. [PMID: 33555482 PMCID: PMC8556193 DOI: 10.1007/s10555-020-09953-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Accepted: 12/30/2020] [Indexed: 12/14/2022]
Abstract
One way to understand ductal adenocarcinoma of the pancreas (pancreatic cancer) is to view it as unimaginably large numbers of evolving living organisms interacting with their environment. This “evolutionary view” creates both expected and surprising perspectives in all stages of neoplastic progression. Advances in the field will require greater attention to this critical evolutionary prospective.
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Affiliation(s)
- Michaël Noë
- Sol Goldman Pancreatic Cancer Research Center, Department of Pathology, The Johns Hopkins University School of Medicine, Carnegie 415, 600 North Wolfe Street, Baltimore, MD, 21287, USA
- Sol Goldman Pancreatic Cancer Research Center, Department of Oncology, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Seung-Mo Hong
- Department of Pathology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Laura D Wood
- Sol Goldman Pancreatic Cancer Research Center, Department of Pathology, The Johns Hopkins University School of Medicine, Carnegie 415, 600 North Wolfe Street, Baltimore, MD, 21287, USA
- Sol Goldman Pancreatic Cancer Research Center, Department of Oncology, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Elizabeth D Thompson
- Sol Goldman Pancreatic Cancer Research Center, Department of Pathology, The Johns Hopkins University School of Medicine, Carnegie 415, 600 North Wolfe Street, Baltimore, MD, 21287, USA
| | - Nicholas J Roberts
- Sol Goldman Pancreatic Cancer Research Center, Department of Pathology, The Johns Hopkins University School of Medicine, Carnegie 415, 600 North Wolfe Street, Baltimore, MD, 21287, USA
- Sol Goldman Pancreatic Cancer Research Center, Department of Oncology, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Michael G Goggins
- Sol Goldman Pancreatic Cancer Research Center, Department of Pathology, The Johns Hopkins University School of Medicine, Carnegie 415, 600 North Wolfe Street, Baltimore, MD, 21287, USA
- Sol Goldman Pancreatic Cancer Research Center, Department of Oncology, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
- Sol Goldman Pancreatic Cancer Research Center, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Alison P Klein
- Sol Goldman Pancreatic Cancer Research Center, Department of Pathology, The Johns Hopkins University School of Medicine, Carnegie 415, 600 North Wolfe Street, Baltimore, MD, 21287, USA
- Sol Goldman Pancreatic Cancer Research Center, Department of Oncology, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
- Department of Epidemiology, Bloomberg School of Public Health, The Johns Hopkins University School of Medicine, Baltimore, MD, 21231, USA
| | - James R Eshleman
- Sol Goldman Pancreatic Cancer Research Center, Department of Pathology, The Johns Hopkins University School of Medicine, Carnegie 415, 600 North Wolfe Street, Baltimore, MD, 21287, USA
- Sol Goldman Pancreatic Cancer Research Center, Department of Oncology, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Scott E Kern
- Sol Goldman Pancreatic Cancer Research Center, Department of Pathology, The Johns Hopkins University School of Medicine, Carnegie 415, 600 North Wolfe Street, Baltimore, MD, 21287, USA
- Sol Goldman Pancreatic Cancer Research Center, Department of Oncology, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Ralph H Hruban
- Sol Goldman Pancreatic Cancer Research Center, Department of Pathology, The Johns Hopkins University School of Medicine, Carnegie 415, 600 North Wolfe Street, Baltimore, MD, 21287, USA.
- Sol Goldman Pancreatic Cancer Research Center, Department of Oncology, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA.
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26
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Dai CL, Vazifeh MM, Yeang CH, Tachet R, Wells RS, Vilar MG, Daly MJ, Ratti C, Martin AR. Population Histories of the United States Revealed through Fine-Scale Migration and Haplotype Analysis. Am J Hum Genet 2020; 106:371-388. [PMID: 32142644 PMCID: PMC7058830 DOI: 10.1016/j.ajhg.2020.02.002] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2019] [Accepted: 02/05/2020] [Indexed: 12/11/2022] Open
Abstract
The population of the United States is shaped by centuries of migration, isolation, growth, and admixture between ancestors of global origins. Here, we assemble a comprehensive view of recent population history by studying the ancestry and population structure of more than 32,000 individuals in the US using genetic, ancestral birth origin, and geographic data from the National Geographic Genographic Project. We identify migration routes and barriers that reflect historical demographic events. We also uncover the spatial patterns of relatedness in subpopulations through the combination of haplotype clustering, ancestral birth origin analysis, and local ancestry inference. Examples of these patterns include substantial substructure and heterogeneity in Hispanics/Latinos, isolation-by-distance in African Americans, elevated levels of relatedness and homozygosity in Asian immigrants, and fine-scale structure in European descents. Taken together, our results provide detailed insights into the genetic structure and demographic history of the diverse US population.
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Affiliation(s)
- Chengzhen L Dai
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Mohammad M Vazifeh
- Senseable City Lab, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Chen-Hsiang Yeang
- Institute of Statistical Science, Academia Sinica, Nankang, Taipei, Taiwan
| | - Remi Tachet
- Senseable City Lab, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | | | - Miguel G Vilar
- Genographic Project, National Geographic Society, Washington, DC 20036, USA
| | - Mark J Daly
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Carlo Ratti
- Senseable City Lab, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Alicia R Martin
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.
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27
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High-resolution inference of genetic relationships among Jewish populations. Eur J Hum Genet 2020; 28:804-814. [PMID: 31919450 DOI: 10.1038/s41431-019-0542-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2018] [Revised: 09/25/2019] [Accepted: 10/13/2019] [Indexed: 11/08/2022] Open
Abstract
Recent studies have used genome-wide single-nucleotide polymorphisms (SNPs) to investigate relationships among various Jewish populations and their non-Jewish historical neighbors, often focusing on small subsets of populations from a limited geographic range or relatively small samples within populations. Here, building on the significant progress that has emerged from genomic SNP studies in the placement of Jewish populations in relation to non-Jewish populations, we focus on population structure among Jewish populations. In particular, we examine Jewish population-genetic structure in samples that span much of the historical range of Jewish populations in Europe, the Middle East, North Africa, and South Asia. Combining 429 newly genotyped samples from 29 Jewish and 3 non-Jewish populations with previously reported genotypes on Jewish and non-Jewish populations, we investigate variation in 2789 individuals from 114 populations at 486,592 genome-wide autosomal SNPs. Using multidimensional scaling analysis, unsupervised model-based clustering, and population trees, we find that, genetically, most Jewish samples fall into four major clusters that largely represent four culturally defined groupings, namely the Ashkenazi, Mizrahi, North African, and Sephardi subdivisions of the Jewish population. We detect high-resolution population structure, including separation of the Ashkenazi and Sephardi groups and distinctions among populations within the Mizrahi and North African groups. Our results refine knowledge of Jewish population-genetic structure and contribute to a growing understanding of the distinctive genetic ancestry evident in closely related but historically separate Jewish communities.
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28
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Chakchouk I, Zhang D, Zhang Z, Francioli LC, Santos-Cortez RLP, Schrauwen I, Leal SM. Disparities in discovery of pathogenic variants for autosomal recessive non-syndromic hearing impairment by ancestry. Eur J Hum Genet 2019; 27:1456-1465. [PMID: 31053783 PMCID: PMC6777454 DOI: 10.1038/s41431-019-0417-2] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2018] [Revised: 04/01/2019] [Accepted: 04/16/2019] [Indexed: 12/22/2022] Open
Abstract
Hearing impairment (HI) is characterized by extensive genetic heterogeneity. To determine the population-specific contribution of known autosomal recessive nonsyndromic (ARNS)HI genes and variants to HI etiology; pathogenic and likely pathogenic (PLP) ARNSHI variants were selected from ClinVar and the Deafness Variation Database and their frequencies were obtained from gnomAD for seven populations. ARNSHI prevalence due to PLP variants varies greatly by population ranging from 96.9 affected per 100,000 individuals for Ashkenazi Jews to 5.2 affected per 100,000 individuals for Africans/African Americans. For Europeans, Finns have the lowest prevalence due to ARNSHI PLP variants with 9.5 affected per 100,000 individuals. For East Asians, Latinos, non-Finish Europeans, and South Asians, ARNSHI prevalence due to PLP variants ranges from 17.1 to 33.7 affected per 100,000 individuals. ARNSHI variants that were previously reported in a single ancestry or family were observed in additional populations, e.g., USH1C p.(Q723*) reported in a Chinese family was the most prevalent pathogenic variant observed in gnomAD for African/African Americans. Variability between populations is due to how extensively ARNSHI has been studied, ARNSHI prevalence and ancestry specific ARNSHI variant architecture which is impacted by population history. Our study demonstrates that additional gene and variant discovery studies are necessary for all populations and particularly for individuals of African ancestry.
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Affiliation(s)
- Imen Chakchouk
- Center for Statistical Genetics, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Di Zhang
- Center for Statistical Genetics, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Zhihui Zhang
- Center for Statistical Genetics, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
- Center for Statistical Genetics, Department of Neurology, Gertrude H. Sergievsky Center, Columbia University Medical Center, New York, NY, USA
| | - Laurent C Francioli
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
| | | | - Isabelle Schrauwen
- Center for Statistical Genetics, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
- Center for Statistical Genetics, Department of Neurology, Gertrude H. Sergievsky Center, Columbia University Medical Center, New York, NY, USA
| | - Suzanne M Leal
- Center for Statistical Genetics, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
- Center for Statistical Genetics, Department of Neurology, Gertrude H. Sergievsky Center, Columbia University Medical Center, New York, NY, USA.
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29
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Gladstein AL, Hammer MF. Substructured Population Growth in the Ashkenazi Jews Inferred with Approximate Bayesian Computation. Mol Biol Evol 2019; 36:1162-1171. [PMID: 30840069 DOI: 10.1093/molbev/msz047] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
The Ashkenazi Jews (AJ) are a population isolate sharing ancestry with both European and Middle Eastern populations that has likely resided in Central Europe since at least the tenth century. Between the 11th and 16th centuries, the AJ population expanded eastward leading to two culturally distinct communities in Western/Central and Eastern Europe. Our aim was to determine whether the western and eastern groups are genetically distinct, and if so, what demographic processes contributed to population differentiation. We used Approximate Bayesian Computation to choose among models of AJ history and to infer demographic parameter values, including divergence times, effective population sizes, and levels of gene flow. For the ABC analysis, we used allele frequency spectrum and identical by descent-based statistics to capture information on a wide timescale. We also mitigated the effects of ascertainment bias when performing ABC on SNP array data by jointly modeling and inferring SNP discovery. We found that the most likely model was population differentiation between Eastern and Western AJ ∼400 years ago. The differentiation between the Eastern and Western AJ could be attributed to more extreme population growth in the Eastern AJ (0.250 per generation) than the Western AJ (0.069 per generation).
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Affiliation(s)
- Ariella L Gladstein
- Department of Ecology, Evolution and Biology, University of Arizona, Tucson, AZ
| | - Michael F Hammer
- Arizona Research Laboratory Division of Biotechnology, University of Arizona, Tucson, AZ
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30
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Yardumian A, Schurr TG. The Geography of Jewish Ethnogenesis. JOURNAL OF ANTHROPOLOGICAL RESEARCH 2019. [DOI: 10.1086/702709] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
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31
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Haber M, Doumet-Serhal C, Scheib CL, Xue Y, Mikulski R, Martiniano R, Fischer-Genz B, Schutkowski H, Kivisild T, Tyler-Smith C. A Transient Pulse of Genetic Admixture from the Crusaders in the Near East Identified from Ancient Genome Sequences. Am J Hum Genet 2019; 104:977-984. [PMID: 31006515 PMCID: PMC6506814 DOI: 10.1016/j.ajhg.2019.03.015] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2019] [Accepted: 03/18/2019] [Indexed: 11/12/2022] Open
Abstract
During the medieval period, hundreds of thousands of Europeans migrated to the Near East to take part in the Crusades, and many of them settled in the newly established Christian states along the Eastern Mediterranean coast. Here, we present a genetic snapshot of these events and their aftermath by sequencing the whole genomes of 13 individuals who lived in what is today known as Lebanon between the 3rd and 13th centuries CE. These include nine individuals from the “Crusaders’ pit” in Sidon, a mass burial in South Lebanon identified from the archaeology as the grave of Crusaders killed during a battle in the 13th century CE. We show that all of the Crusaders’ pit individuals were males; some were Western Europeans from diverse origins, some were locals (genetically indistinguishable from present-day Lebanese), and two individuals were a mixture of European and Near Eastern ancestries, providing direct evidence that the Crusaders admixed with the local population. However, these mixtures appear to have had limited genetic consequences since signals of admixture with Europeans are not significant in any Lebanese group today—in particular, Lebanese Christians are today genetically similar to local people who lived during the Roman period which preceded the Crusades by more than four centuries.
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Hamada T, Yuan C, Yurgelun MB, Perez K, Khalaf N, Morales-Oyarvide V, Babic A, Nowak JA, Rubinson DA, Giannakis M, Ng K, Kraft P, Stampfer MJ, Giovannucci EL, Fuchs CS, Ogino S, Wolpin BM. Family history of cancer, Ashkenazi Jewish ancestry, and pancreatic cancer risk. Br J Cancer 2019; 120:848-854. [PMID: 30867564 PMCID: PMC6474278 DOI: 10.1038/s41416-019-0426-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2018] [Revised: 02/25/2019] [Accepted: 02/27/2019] [Indexed: 02/07/2023] Open
Abstract
Background Individuals with a family history of cancer may be at increased risk of pancreatic cancer. Ashkenazi Jewish (AJ) individuals carry increased risk for pancreatic cancer and other cancer types. Methods We examined the association between family history of cancer, AJ heritage, and incident pancreatic cancer in 49 410 male participants of the prospective Health Professionals Follow-up Study. Hazard ratios (HRs) were estimated using multivariable-adjusted Cox proportional hazards models. Results During 1.1 million person-years (1986–2016), 452 participants developed pancreatic cancer. Increased risk of pancreatic cancer was observed in individuals with a family history of pancreatic (HR, 2.79; 95% confidence interval [CI], 1.28–6.07) or breast cancer (HR, 1.40; 95% CI, 1.01–1.94). There was a trend towards higher risk of pancreatic cancer in relation to a family history of colorectal cancer (HR, 1.21; 95% CI, 0.95–1.55) or AJ heritage (HR, 1.29; 95% CI, 0.94–1.77). The risk was highly elevated among AJ men with a family history of breast or colorectal cancer (HR, 2.61 [95% CI, 1.41–4.82] and 1.92 [95% CI, 1.05–3.49], respectively). Conclusion Family history of pancreatic cancer was associated with increased risk of this malignancy. Family history of breast or colorectal cancer was associated with the increased risk among AJ men.
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Affiliation(s)
- Tsuyoshi Hamada
- Department of Oncologic Pathology, Dana-Farber Cancer Institute and Harvard Medical School, 450 Brookline Avenue, Boston, MA, 02215, USA
| | - Chen Yuan
- Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, 450 Brookline Avenue, Boston, MA, 02215, USA.,Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA, 02115, USA
| | - Matthew B Yurgelun
- Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, 450 Brookline Avenue, Boston, MA, 02215, USA
| | - Kimberly Perez
- Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, 450 Brookline Avenue, Boston, MA, 02215, USA
| | - Natalia Khalaf
- Division of Gastroenterology, Hepatology, and Endoscopy, Brigham and Women's Hospital and Harvard Medical School, 75 Francis Street, Boston, MA, 02115, USA
| | - Vicente Morales-Oyarvide
- Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, 450 Brookline Avenue, Boston, MA, 02215, USA
| | - Ana Babic
- Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, 450 Brookline Avenue, Boston, MA, 02215, USA
| | - Jonathan A Nowak
- Program in MPE Molecular Pathological Epidemiology, Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, 75 Francis Street, Boston, MA, 02115, USA
| | - Douglas A Rubinson
- Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, 450 Brookline Avenue, Boston, MA, 02215, USA
| | - Marios Giannakis
- Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, 450 Brookline Avenue, Boston, MA, 02215, USA.,Broad Institute of Massachusetts Institute of Technology and Harvard, 415 Main Street, Cambridge, MA, 02142, USA.,Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 75 Francis Street, Boston, MA, 02115, USA
| | - Kimmie Ng
- Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, 450 Brookline Avenue, Boston, MA, 02215, USA
| | - Peter Kraft
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA, 02115, USA.,Department of Biostatistics, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA, 02115, USA
| | - Meir J Stampfer
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA, 02115, USA.,Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 181 Longwood Avenue, Boston, MA, 02115, USA.,Department of Nutrition, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA, 02115, USA
| | - Edward L Giovannucci
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA, 02115, USA.,Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 181 Longwood Avenue, Boston, MA, 02115, USA.,Department of Nutrition, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA, 02115, USA
| | - Charles S Fuchs
- Yale Cancer Center, 333 Cedar Street, New Haven, CT, 06510, USA.,Department of Medicine, Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06510, USA.,Smilow Cancer Hospital, 20 York Street, New Haven, CT, 06519, USA
| | - Shuji Ogino
- Department of Oncologic Pathology, Dana-Farber Cancer Institute and Harvard Medical School, 450 Brookline Avenue, Boston, MA, 02215, USA.,Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA, 02115, USA.,Program in MPE Molecular Pathological Epidemiology, Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, 75 Francis Street, Boston, MA, 02115, USA.,Broad Institute of Massachusetts Institute of Technology and Harvard, 415 Main Street, Cambridge, MA, 02142, USA
| | - Brian M Wolpin
- Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, 450 Brookline Avenue, Boston, MA, 02215, USA.
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Assessment of coding region variants in Kuwaiti population: implications for medical genetics and population genomics. Sci Rep 2018; 8:16583. [PMID: 30409984 PMCID: PMC6224454 DOI: 10.1038/s41598-018-34815-8] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2017] [Accepted: 10/16/2018] [Indexed: 02/07/2023] Open
Abstract
Consanguineous populations of the Arabian Peninsula have been underrepresented in global efforts that catalogue human exome variability. We sequenced 291 whole exomes of unrelated, healthy native Arab individuals from Kuwait to a median coverage of 45X and characterised 170,508 single-nucleotide variants (SNVs), of which 21.7% were ‘personal’. Up to 12% of the SNVs were novel and 36% were population-specific. Half of the SNVs were rare and 54% were missense variants. The study complemented the Greater Middle East Variome by way of reporting many additional Arabian exome variants. The study corroborated Kuwaiti population genetic substructures previously derived using genome-wide genotype data and illustrated the genetic relatedness among Kuwaiti population subgroups, Middle Eastern, European and Ashkenazi Jewish populations. The study mapped 112 rare and frequent functional variants relating to pharmacogenomics and disorders (recessive and common) to the phenotypic characteristics of Arab population. Comparative allele frequency data and carrier distributions of known Arab mutations for 23 disorders seen among Arabs, of putative OMIM-listed causal mutations for 12 disorders observed among Arabs but not yet characterized for genetic basis in Arabs, and of 17 additional putative mutations for disorders characterized for genetic basis in Arab populations are presented for testing in future Arab studies.
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Su T, Wang W, Li P, Zhang B, Li P, Xin X, Sun H, Yu Y, Zhang D, Zhao X, Wen C, Zhou G, Wang Y, Zheng H, Yu S, Zhang F. A Genomic Variation Map Provides Insights into the Genetic Basis of Spring Chinese Cabbage (Brassica rapa ssp. pekinensis) Selection. MOLECULAR PLANT 2018; 11:1360-1376. [PMID: 30217779 DOI: 10.1016/j.molp.2018.08.006] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/07/2018] [Revised: 08/22/2018] [Accepted: 08/31/2018] [Indexed: 05/08/2023]
Abstract
Chinese cabbage is the most consumed leafy crop in East Asian countries. However, premature bolting induced by continuous low temperatures severely decreases the yield and quality of the Chinese cabbage, and therefore restricts its planting season and geographic distribution. In the past 40 years, spring Chinese cabbage with strong winterness has been selected to meet the market demand. Here, we report a genome variation map of Chinese cabbage generated from the resequencing data of 194 geographically diverse accessions of three ecotypes. In-depth analyses of the selection sweeps and genome-wide patterns revealed that spring Chinese cabbage was selected from a specific population of autumn Chinese cabbage around the area of Shandong peninsula in northern China. We identified 23 genomic loci that underwent intensive selection, and further demonstrated by gene expression and haplotype analyses that the incorporation of elite alleles of VERNALISATION INSENTIVE 3.1 (BrVIN3.1) and FLOWER LOCUS C 1 (BrFLC1) is a determinant genetic source of variation during selection. Moreover, we showed that the quantitative response of BrVIN3.1 to cold due to the sequence variations in the cis elements of the BrVIN3.1 promoter significantly contributes to bolting-time variation in Chinese cabbage. Collectively, our study provides valuable insights into the genetic basis of spring Chinese cabbage selection and will facilitate the breeding of bolting-resistant varieties by molecular-marker-assisted selection, transgenic or gene editing approaches.
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Affiliation(s)
- Tongbing Su
- Beijing Vegetable Research Center (BVRC), Beijing Academy of Agriculture and Forestry Science (BAAFS), Beijing 100097, China; Department of Crop Genetics, John Innes Centre, Norwich NR4 7UH, UK; Key Laboratory of Biology and Genetic Improvement of Horticultural Crops (North China), Ministry of Agriculture, Beijing 100097, China; Beijing Key Laboratory of Vegetable Germplasm Improvement, Beijing 100097, China
| | - Weihong Wang
- Beijing Vegetable Research Center (BVRC), Beijing Academy of Agriculture and Forestry Science (BAAFS), Beijing 100097, China; Key Laboratory of Biology and Genetic Improvement of Horticultural Crops (North China), Ministry of Agriculture, Beijing 100097, China; Beijing Key Laboratory of Vegetable Germplasm Improvement, Beijing 100097, China
| | - Peirong Li
- Beijing Vegetable Research Center (BVRC), Beijing Academy of Agriculture and Forestry Science (BAAFS), Beijing 100097, China; Key Laboratory of Biology and Genetic Improvement of Horticultural Crops (North China), Ministry of Agriculture, Beijing 100097, China; Beijing Key Laboratory of Vegetable Germplasm Improvement, Beijing 100097, China
| | - Bin Zhang
- Beijing Key Laboratory of Vegetable Germplasm Improvement, Beijing 100097, China
| | - Pan Li
- Key Laboratory of Biology and Genetic Improvement of Horticultural Crops (North China), Ministry of Agriculture, Beijing 100097, China
| | - Xiaoyun Xin
- Beijing Vegetable Research Center (BVRC), Beijing Academy of Agriculture and Forestry Science (BAAFS), Beijing 100097, China
| | - Honghe Sun
- Beijing Vegetable Research Center (BVRC), Beijing Academy of Agriculture and Forestry Science (BAAFS), Beijing 100097, China; Key Laboratory of Biology and Genetic Improvement of Horticultural Crops (North China), Ministry of Agriculture, Beijing 100097, China; Beijing Key Laboratory of Vegetable Germplasm Improvement, Beijing 100097, China
| | - Yangjun Yu
- Beijing Vegetable Research Center (BVRC), Beijing Academy of Agriculture and Forestry Science (BAAFS), Beijing 100097, China; Key Laboratory of Biology and Genetic Improvement of Horticultural Crops (North China), Ministry of Agriculture, Beijing 100097, China; Beijing Key Laboratory of Vegetable Germplasm Improvement, Beijing 100097, China
| | - Deshuang Zhang
- Beijing Vegetable Research Center (BVRC), Beijing Academy of Agriculture and Forestry Science (BAAFS), Beijing 100097, China; Key Laboratory of Biology and Genetic Improvement of Horticultural Crops (North China), Ministry of Agriculture, Beijing 100097, China; Beijing Key Laboratory of Vegetable Germplasm Improvement, Beijing 100097, China
| | - Xiuyun Zhao
- Beijing Vegetable Research Center (BVRC), Beijing Academy of Agriculture and Forestry Science (BAAFS), Beijing 100097, China; Key Laboratory of Biology and Genetic Improvement of Horticultural Crops (North China), Ministry of Agriculture, Beijing 100097, China; Beijing Key Laboratory of Vegetable Germplasm Improvement, Beijing 100097, China
| | - Changlong Wen
- Beijing Vegetable Research Center (BVRC), Beijing Academy of Agriculture and Forestry Science (BAAFS), Beijing 100097, China; Key Laboratory of Biology and Genetic Improvement of Horticultural Crops (North China), Ministry of Agriculture, Beijing 100097, China; Beijing Key Laboratory of Vegetable Germplasm Improvement, Beijing 100097, China
| | - Gang Zhou
- Biomarker Technologies Corporation, Beijing, China
| | - Yuntong Wang
- Biomarker Technologies Corporation, Beijing, China
| | | | - Shuancang Yu
- Beijing Vegetable Research Center (BVRC), Beijing Academy of Agriculture and Forestry Science (BAAFS), Beijing 100097, China; Key Laboratory of Biology and Genetic Improvement of Horticultural Crops (North China), Ministry of Agriculture, Beijing 100097, China; Beijing Key Laboratory of Vegetable Germplasm Improvement, Beijing 100097, China.
| | - Fenglan Zhang
- Beijing Vegetable Research Center (BVRC), Beijing Academy of Agriculture and Forestry Science (BAAFS), Beijing 100097, China; Key Laboratory of Biology and Genetic Improvement of Horticultural Crops (North China), Ministry of Agriculture, Beijing 100097, China; Beijing Key Laboratory of Vegetable Germplasm Improvement, Beijing 100097, China.
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Jin SC, Homsy J, Zaidi S, Lu Q, Morton S, DePalma SR, Zeng X, Qi H, Chang W, Sierant MC, Hung WC, Haider S, Zhang J, Knight J, Bjornson RD, Castaldi C, Tikhonoa IR, Bilguvar K, Mane SM, Sanders SJ, Mital S, Russell M, Gaynor W, Deanfield J, Giardini A, Porter GA, Srivastava D, Lo CW, Shen Y, Watkins WS, Yandell M, Yost HJ, Tristani-Firouzi M, Newburger JW, Roberts AE, Kim R, Zhao H, Kaltman JR, Goldmuntz E, Chung WK, Seidman JG, Gelb BD, Seidman CE, Lifton RP, Brueckner M. Contribution of rare inherited and de novo variants in 2,871 congenital heart disease probands. Nat Genet 2017; 49:1593-1601. [PMID: 28991257 PMCID: PMC5675000 DOI: 10.1038/ng.3970] [Citation(s) in RCA: 516] [Impact Index Per Article: 73.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2017] [Accepted: 09/15/2017] [Indexed: 12/17/2022]
Abstract
Congenital heart disease (CHD) is the leading cause of mortality from birth defects. Here, exome sequencing of a single cohort of 2,871 CHD probands, including 2,645 parent-offspring trios, implicated rare inherited mutations in 1.8%, including a recessive founder mutation in GDF1 accounting for ∼5% of severe CHD in Ashkenazim, recessive genotypes in MYH6 accounting for ∼11% of Shone complex, and dominant FLT4 mutations accounting for 2.3% of Tetralogy of Fallot. De novo mutations (DNMs) accounted for 8% of cases, including ∼3% of isolated CHD patients and ∼28% with both neurodevelopmental and extra-cardiac congenital anomalies. Seven genes surpassed thresholds for genome-wide significance, and 12 genes not previously implicated in CHD had >70% probability of being disease related. DNMs in ∼440 genes were inferred to contribute to CHD. Striking overlap between genes with damaging DNMs in probands with CHD and autism was also found.
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Affiliation(s)
- Sheng Chih Jin
- Department of Genetics; Yale University School of Medicine, New Haven, CT, USA
| | - Jason Homsy
- Department of Genetics, Harvard Medical School, Boston, MA, USA
- Cardiovascular Division, Brigham and Women’s Hospital, Boston, MA, USA
| | - Samir Zaidi
- Department of Genetics; Yale University School of Medicine, New Haven, CT, USA
| | - Qiongshi Lu
- Department of Biostatistics; Yale School of Public Health, New Haven, CT, USA
| | - Sarah Morton
- Division of Newborn Medicine, Department of Medicine, Boston Children’s Hospital, Boston, USA
| | | | - Xue Zeng
- Department of Genetics; Yale University School of Medicine, New Haven, CT, USA
| | - Hongjian Qi
- Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY, USA
| | - Weni Chang
- Department of Pediatrics, Columbia University Medical Center, New York, NY, USA
| | - Michael C. Sierant
- Department of Genetics; Yale University School of Medicine, New Haven, CT, USA
| | - Wei-Chien Hung
- Department of Genetics; Yale University School of Medicine, New Haven, CT, USA
| | - Shozeb Haider
- Department of Computational Chemistry, University College London School of Pharmacy, WC1N1AX, UK
| | - Junhui Zhang
- Department of Genetics; Yale University School of Medicine, New Haven, CT, USA
| | - James Knight
- Yale Center for Genome Analysis, Yale University, New Haven, CT, USA
| | | | | | - Irina R. Tikhonoa
- Yale Center for Genome Analysis, Yale University, New Haven, CT, USA
| | - Kaya Bilguvar
- Yale Center for Genome Analysis, Yale University, New Haven, CT, USA
| | - Shrikant M. Mane
- Yale Center for Genome Analysis, Yale University, New Haven, CT, USA
| | - Stephan J. Sanders
- Department of Psychiatry, University of California San Francisco, San Francisco, CA, USA
| | - Seema Mital
- Department of Pediatrics, The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada
| | - Mark Russell
- Division of Pediatric Cardiology, University of Michigan, Ann Arbor, MI, USA
| | - William Gaynor
- Department of Pediatric Cardiac Surgery, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - John Deanfield
- Department of Cardiology, University College London and Great Ormond Street Hospital, London, UK
| | - Alessandro Giardini
- Department of Cardiology, University College London and Great Ormond Street Hospital, London, UK
| | - George A. Porter
- Department of Pediatrics, University of Rochester Medical Center, The School of Medicine and Dentistry, Rochester, NY, USA
| | - Deepak Srivastava
- Gladstone Institute of Cardiovascular Disease, San Francisco, CA 94158, USA
- Roddenberry Stem Cell Center at Gladstone, San Francisco, CA 94158, USA
- Departments of Pediatrics and Biochemistry & Biophysics, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Cecelia W. Lo
- Department of Developmental Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15201, USA
| | - Yufeng Shen
- Departments of Systems Biology and Biomedical Informatics, Columbia University Medical Center, New York, NY, USA
| | - W. Scott Watkins
- Department of Human Genetics, Eccles Institute of Human Genetics, University of Utah and School of Medicine, Salt Lake City, UT, USA
| | - Mark Yandell
- Department of Human Genetics, Eccles Institute of Human Genetics, University of Utah and School of Medicine, Salt Lake City, UT, USA
- USTAR Center for Genetic Discovery, University of Utah, Salt Lake City, UT, USA
| | - H. Joseph Yost
- Department of Human Genetics, Eccles Institute of Human Genetics, University of Utah and School of Medicine, Salt Lake City, UT, USA
| | | | - Jane W. Newburger
- Department of Cardiology, Boston Children’s Hospital, Boston, MA, USA
| | - Amy E. Roberts
- Department of Cardiology, Boston Children’s Hospital, Boston, MA, USA
| | - Richard Kim
- Pediatric Cardiac Surgery, Children’s Hospital of Los Angeles, Los Angeles, CA, USA
| | - Hongyu Zhao
- Department of Biostatistics; Yale School of Public Health, New Haven, CT, USA
| | - Jonathan R. Kaltman
- Heart Development and Structural Diseases Branch, Division of Cardiovascular Sciences, NHLBI/NIH, Bethesda, MD, USA
| | - Elizabeth Goldmuntz
- Department of Pediatrics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Wendy K. Chung
- Departments of Pediatrics and Medicine, Columbia University Medical Center, New York, NY, USA
| | | | - Bruce D. Gelb
- Mindich Child Health and Development Institute and Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Christine E. Seidman
- Department of Genetics, Harvard Medical School, Boston, MA, USA
- Cardiovascular Division, Brigham and Women’s Hospital, Boston, MA, USA
- Howard Hughes Medical Institute, Harvard University, Boston, MA, USA
| | - Richard P. Lifton
- Department of Genetics; Yale University School of Medicine, New Haven, CT, USA
- Laboratory of Human Genetics and Genomics, The Rockefeller University, New York, NY, USA
| | - Martina Brueckner
- Department of Genetics; Yale University School of Medicine, New Haven, CT, USA
- Department of Pediatrics, Yale University School of Medicine, New Haven, CT, USA
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Kang JTL, Goldberg A, Edge MD, Behar DM, Rosenberg NA. Consanguinity Rates Predict Long Runs of Homozygosity in Jewish Populations. Hum Hered 2017; 82:87-102. [PMID: 28910803 DOI: 10.1159/000478897] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2017] [Accepted: 06/14/2017] [Indexed: 11/19/2022] Open
Abstract
OBJECTIVES Recent studies have highlighted the potential of analyses of genomic sharing to produce insight into the demographic processes affecting human populations. We study runs of homozygosity (ROH) in 18 Jewish populations, examining these groups in relation to 123 non-Jewish populations sampled worldwide. METHODS By sorting ROH into 3 length classes (short, intermediate, and long), we evaluate the impact of demographic processes on genomic patterns in Jewish populations. RESULTS We find that the portion of the genome appearing in long ROH - the length class most directly related to recent consanguinity - closely accords with data gathered from interviews during the 1950s on frequencies of consanguineous unions in various Jewish groups. CONCLUSION The high correlation between 1950s consanguinity levels and coverage by long ROH explains differences across populations in ROH patterns. The dissection of ROH into length classes and the comparison to consanguinity data assist in understanding a number of additional phenomena, including similarities of Jewish populations to Middle Eastern, European, and Central and South Asian non-Jewish populations in short ROH patterns, relative lengths of identity-by-descent tracts in different Jewish groups, and the "population isolate" status of the Ashkenazi Jews.
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López S, Thomas MG, van Dorp L, Ansari-Pour N, Stewart S, Jones AL, Jelinek E, Chikhi L, Parfitt T, Bradman N, Weale ME, Hellenthal G. The Genetic Legacy of Zoroastrianism in Iran and India: Insights into Population Structure, Gene Flow, and Selection. Am J Hum Genet 2017; 101:353-368. [PMID: 28844488 PMCID: PMC5590844 DOI: 10.1016/j.ajhg.2017.07.013] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2017] [Accepted: 07/24/2017] [Indexed: 11/24/2022] Open
Abstract
Zoroastrianism is one of the oldest extant religions in the world, originating in Persia (present-day Iran) during the second millennium BCE. Historical records indicate that migrants from Persia brought Zoroastrianism to India, but there is debate over the timing of these migrations. Here we present genome-wide autosomal, Y chromosome, and mitochondrial DNA data from Iranian and Indian Zoroastrians and neighboring modern-day Indian and Iranian populations and conduct a comprehensive genome-wide genetic analysis in these groups. Using powerful haplotype-based techniques, we find that Zoroastrians in Iran and India have increased genetic homogeneity relative to other sampled groups in their respective countries, consistent with their current practices of endogamy. Despite this, we infer that Indian Zoroastrians (Parsis) intermixed with local groups sometime after their arrival in India, dating this mixture to 690–1390 CE and providing strong evidence that Iranian Zoroastrian ancestry was maintained primarily through the male line. By making use of the rich information in DNA from ancient human remains, we also highlight admixture in the ancestors of Iranian Zoroastrians dated to 570 BCE–746 CE, older than admixture seen in any other sampled Iranian group, consistent with a long-standing isolation of Zoroastrians from outside groups. Finally, we report results, and challenges, from a genome-wide scan to identify genomic regions showing signatures of positive selection in present-day Zoroastrians that might correlate to the prevalence of particular diseases among these communities.
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Elhaik E. Editorial: Population Genetics of Worldwide Jewish People. Front Genet 2017; 8:101. [PMID: 28804494 PMCID: PMC5532521 DOI: 10.3389/fgene.2017.00101] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2017] [Accepted: 07/14/2017] [Indexed: 11/13/2022] Open
Affiliation(s)
- Eran Elhaik
- Department of Animal and Plant Sciences, University of SheffieldSheffield, United Kingdom
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EINHORN YARON, WEISSGLAS-VOLKOV DAPHNA, CARMI SHAI, OSTRER HARRY, FRIEDMAN EITAN, SHOMRON NOAM. Differential analysis of mutations in the Jewish population and their implications for diseases. Genet Res (Camb) 2017; 99:e3. [PMID: 28502252 PMCID: PMC6865140 DOI: 10.1017/s0016672317000015] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2016] [Revised: 01/10/2017] [Accepted: 01/31/2017] [Indexed: 12/19/2022] Open
Abstract
Sequencing large cohorts of ethnically homogeneous individuals yields genetic insights with implications for the entire population rather than a single individual. In order to evaluate the genetic basis of certain diseases encountered at high frequency in the Ashkenazi Jewish population (AJP), as well as to improve variant annotation among the AJP, we examined the entire exome, focusing on specific genes with known clinical implications in 128 Ashkenazi Jews and compared these data to other non-Jewish populations (European, African, South Asian and East Asian). We targeted American College of Medical Genetics incidental finding recommended genes and the Catalogue of Somatic Mutations in Cancer (COSMIC) germline cancer-related genes. We identified previously known disease-causing variants and discovered potentially deleterious variants in known disease-causing genes that are population specific or substantially more prevalent in the AJP, such as in the ATP and HGFAC genes associated with colorectal cancer and pancreatic cancer, respectively. Additionally, we tested the advantage of utilizing the database of the AJP when assigning pathogenicity to rare variants of independent whole-exome sequencing data of 49 Ashkenazi Jew early-onset breast cancer (BC) patients. Importantly, population-based filtering using our AJP database enabled a reduction in the number of potential causal variants in the BC cohort by 36%. Taken together, population-specific sequencing of the AJP offers valuable, clinically applicable information and improves AJP filter annotation.
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Affiliation(s)
- YARON EINHORN
- Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | | | - SHAI CARMI
- Braun School of Public Health and Community Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - HARRY OSTRER
- Department of Pathology, Albert Einstein College of Medicine, Bronx, NY, USA
| | - EITAN FRIEDMAN
- Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
- Susanne Levy Gertner Oncogenetics Unit, Sheba Medical Center, Tel-Hashomer, Israel
| | - NOAM SHOMRON
- Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
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Xue J, Lencz T, Darvasi A, Pe’er I, Carmi S. The time and place of European admixture in Ashkenazi Jewish history. PLoS Genet 2017; 13:e1006644. [PMID: 28376121 PMCID: PMC5380316 DOI: 10.1371/journal.pgen.1006644] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2016] [Accepted: 02/18/2017] [Indexed: 12/21/2022] Open
Abstract
The Ashkenazi Jewish (AJ) population is important in genetics due to its high rate of Mendelian disorders. AJ appeared in Europe in the 10th century, and their ancestry is thought to comprise European (EU) and Middle-Eastern (ME) components. However, both the time and place of admixture are subject to debate. Here, we attempt to characterize the AJ admixture history using a careful application of new and existing methods on a large AJ sample. Our main approach was based on local ancestry inference, in which we first classified each AJ genomic segment as EU or ME, and then compared allele frequencies along the EU segments to those of different EU populations. The contribution of each EU source was also estimated using GLOBETROTTER and haplotype sharing. The time of admixture was inferred based on multiple statistics, including ME segment lengths, the total EU ancestry per chromosome, and the correlation of ancestries along the chromosome. The major source of EU ancestry in AJ was found to be Southern Europe (≈60–80% of EU ancestry), with the rest being likely Eastern European. The inferred admixture time was ≈30 generations ago, but multiple lines of evidence suggest that it represents an average over two or more events, pre- and post-dating the founder event experienced by AJ in late medieval times. The time of the pre-bottleneck admixture event, which was likely Southern European, was estimated to ≈25–50 generations ago. The Ashkenazi Jewish population has resided in Europe for much of its 1000-year existence. However, its ethnic and geographic origins are controversial, due to the scarcity of reliable historical records. Previous genetic studies have found links to Middle-Eastern and European ancestries, but the admixture history has not been studied in detail yet, partly due to technical difficulties in disentangling signals from multiple admixture events. Here, we present an in-depth analysis of the sources of European gene flow and the time of admixture events by using multiple new and existing methods and extensive simulations. Our results suggest a model of at least two events of European admixture. One event slightly pre-dated a late medieval founder event and was likely from a Southern European source. Another event post-dated the founder event and likely occurred in Eastern Europe. These results, as well as the methods introduced, will be highly valuable for geneticists and other researchers interested in Ashkenazi Jewish origins.
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Affiliation(s)
- James Xue
- Department of Computer Science, Columbia University, New York, New York, United States of America
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts, United States of America
| | - Todd Lencz
- Center for Psychiatric Neuroscience, The Feinstein Institute for Medical Research, North Shore-Long Island Jewish Health System, Manhasset, New York, United States of America
- Department of Psychiatry, Division of Research, The Zucker Hillside Hospital Division of the North Shore–Long Island Jewish Health System, Glen Oaks, New York, United States of America
- Departments of Psychiatry and Molecular Medicine, Hofstra Northwell School of Medicine, Hempstead, New York, United States of America
| | - Ariel Darvasi
- Department of Genetics, The Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Itsik Pe’er
- Department of Computer Science, Columbia University, New York, New York, United States of America
- Department of Systems Biology, Columbia University, New York, New York, United States of America
| | - Shai Carmi
- Braun School of Public Health and Community Medicine, The Hebrew University of Jerusalem, Ein Kerem, Jerusalem, Israel
- * E-mail:
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Cole AM, Cox S, Jeong C, Petousi N, Aryal DR, Droma Y, Hanaoka M, Ota M, Kobayashi N, Gasparini P, Montgomery H, Robbins P, Di Rienzo A, Cavalleri GL. Genetic structure in the Sherpa and neighboring Nepalese populations. BMC Genomics 2017; 18:102. [PMID: 28103797 PMCID: PMC5248489 DOI: 10.1186/s12864-016-3469-5] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2016] [Accepted: 12/23/2016] [Indexed: 12/31/2022] Open
Abstract
Background We set out to describe the fine-scale population structure across the Eastern region of Nepal. To date there is relatively little known about the genetic structure of the Sherpa residing in Nepal and their genetic relationship with the Nepalese. We assembled dense genotype data from a total of 1245 individuals representing Nepal and a variety of different populations resident across the greater Himalayan region including Tibet, China, India, Pakistan, Kazakhstan, Uzbekistan, Tajikistan and Kirghizstan. We performed analysis of principal components, admixture and homozygosity. Results We identified clear substructure across populations resident in the Himalayan arc, with genetic structure broadly mirroring geographical features of the region. Ethnic subgroups within Nepal show distinct genetic structure, on both admixture and principal component analysis. We detected differential proportions of ancestry from northern Himalayan populations across Nepalese subgroups, with the Nepalese Rai, Magar and Tamang carrying the greatest proportions of Tibetan ancestry. Conclusions We show that populations dwelling on the Himalayan plateau have had a clear impact on the Northern Indian gene pool. We illustrate how the Sherpa are a remarkably isolated population, with little gene flow from surrounding Nepalese populations. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-3469-5) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Amy M Cole
- Department of Molecular and Cellular Therapeutics, The Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Sean Cox
- Centre for Human Health and Performance, and Institute for Sport, Exercise and Health, University College London, London, UK
| | - Choongwon Jeong
- Department of Human Genetics, University of Chicago, Chicago, USA
| | - Nayia Petousi
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK
| | - Dhana R Aryal
- Paropakar Maternity and Women's Hospital, Thapathali, Kathmandu, Nepal
| | - Yunden Droma
- First Department of Medicine, Shinshu University School of Medicine, Matsumoto, Japan
| | - Masayuki Hanaoka
- First Department of Medicine, Shinshu University School of Medicine, Matsumoto, Japan
| | - Masao Ota
- Department of Legal Medicine, Shinshu University School of Medicine, Matsumoto, Japan
| | - Nobumitsu Kobayashi
- Department of Legal Medicine, Shinshu University School of Medicine, Matsumoto, Japan
| | - Paolo Gasparini
- University of Triests, Trieste, Italy.,Division of Experimental Genetics, Sidra, Doha, Qatar
| | - Hugh Montgomery
- Centre for Human Health and Performance, and Institute for Sport, Exercise and Health, University College London, London, UK
| | - Peter Robbins
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK
| | - Anna Di Rienzo
- Department of Human Genetics, University of Chicago, Chicago, USA
| | - Gianpiero L Cavalleri
- Department of Molecular and Cellular Therapeutics, The Royal College of Surgeons in Ireland, Dublin, Ireland.
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42
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Shen QK, Sulaiman X, Yao YG, Peng MS, Zhang YP. Was ADH1B under Selection in European Populations? Am J Hum Genet 2016; 99:1217-1219. [PMID: 27814524 DOI: 10.1016/j.ajhg.2016.09.017] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2016] [Accepted: 09/20/2016] [Indexed: 11/18/2022] Open
Affiliation(s)
- Quan-Kuan Shen
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming 650223, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming 650204, China
| | | | - Yong-Gang Yao
- KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming 650223, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming 650204, China; Key Laboratory of Animal Models and Human Disease Mechanisms, Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Kunming 650223, China
| | - Min-Sheng Peng
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming 650223, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming 650204, China.
| | - Ya-Ping Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming 650223, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming 650204, China; State Key Laboratory for Conservation and Utilization of Bio-Resources, Yunnan University, Kunming 650091, China.
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43
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Harvey PD, Aslan M, Du M, Zhao H, Siever LJ, Pulver A, Gaziano JM, Concato J. Factor structure of cognition and functional capacity in two studies of schizophrenia and bipolar disorder: Implications for genomic studies. Neuropsychology 2016; 30:28-39. [PMID: 26710094 DOI: 10.1037/neu0000245] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
OBJECTIVE Impairments in cognition and everyday functioning are common in schizophrenia and bipolar disorder (BPD). In this article, we present factor analyses of cognitive and functional capacity (FC) measures based on 2 studies of schizophrenia (SCZ) and bipolar I disorder (BPI) using similar methods. The overall goal of these analyses was to determine whether performance-based assessments should be examined individually, or aggregated on the basis of the correlational structure of the tests, as well as to evaluate the similarity of factor structures of SCZ and BPI. METHOD Veterans Affairs Cooperative Studies Program Study #572 (Harvey et al., 2014) evaluated cognitive and FC measures among 5,414 BPI and 3,942 SCZ patients. A 2nd study evaluated similar neuropsychological (NP) and FC measures among 368 BPI and 436 SCZ patients. Principal components analysis, as well as exploratory and CFAs, were used to examine the data. RESULTS Analyses in both datasets suggested that NP and FC measures were explained by a single underlying factor in BPI and SCZ patients, both when analyzed separately or as in a combined sample. The factor structure in both studies was similar, with or without inclusion of FC measures; homogeneous loadings were observed for that single factor across cognitive and FC domains across the samples. CONCLUSION The empirically derived factor model suggests that NP performance and FC are best explained as a single latent trait applicable to people with SCZ and BPD. This single measure may enhance the robustness of the analyses relating genomic data to performance-based phenotypes.
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Affiliation(s)
- Philip D Harvey
- Department of Research Service, Bruce W. Carter Miami Veterans Affairs Medical Center
| | - Mihaela Aslan
- Clinical Epidemiology Research Center, Veterans Affairs Connecticut Healthcare System
| | - Mengtian Du
- Department of Statistics, Yale Graduate School of Arts and Sciences, Yale University
| | - Hongyu Zhao
- Clinical Epidemiology Research Center, Veterans Affairs Connecticut Healthcare System
| | - Larry J Siever
- Department of Psychiatry Service, James J. Peters Veterans Affairs Medical Center
| | - Ann Pulver
- Department of Epidemiology, Bloomberg School of Public Health
| | - J Michael Gaziano
- Massachusetts Veteran Epidemiology Research and Information Center, Veterans Affairs Boston Healthcare System
| | - John Concato
- Clinical Epidemiology Research Center, Veterans Affairs Connecticut Healthcare System
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44
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Downie JM, Tashi T, Lorenzo FR, Feusier JE, Mir H, Prchal JT, Jorde LB, Koul PA. A Genome-Wide Search for Greek and Jewish Admixture in the Kashmiri Population. PLoS One 2016; 11:e0160614. [PMID: 27490348 PMCID: PMC4973929 DOI: 10.1371/journal.pone.0160614] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2016] [Accepted: 07/21/2016] [Indexed: 11/18/2022] Open
Abstract
The Kashmiri population is an ethno-linguistic group that resides in the Kashmir Valley in northern India. A longstanding hypothesis is that this population derives ancestry from Jewish and/or Greek sources. There is historical and archaeological evidence of ancient Greek presence in India and Kashmir. Further, some historical accounts suggest ancient Hebrew ancestry as well. To date, it has not been determined whether signatures of Greek or Jewish admixture can be detected in the Kashmiri population. Using genome-wide genotyping and admixture detection methods, we determined there are no significant or substantial signs of Greek or Jewish admixture in modern-day Kashmiris. The ancestry of Kashmiri Tibetans was also determined, which showed signs of admixture with populations from northern India and west Eurasia. These results contribute to our understanding of the existing population structure in northern India and its surrounding geographical areas.
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Affiliation(s)
- Jonathan M. Downie
- Department of Human Genetics, University of Utah School of Medicine, Salt Lake City, Utah, United States of America
- * E-mail:
| | - Tsewang Tashi
- Division of Hematology and Hematologic Malignancies, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, Utah, United States of America
| | - Felipe Ramos Lorenzo
- Division of Hematology and Hematologic Malignancies, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, Utah, United States of America
| | - Julie Ellen Feusier
- Department of Human Genetics, University of Utah School of Medicine, Salt Lake City, Utah, United States of America
| | - Hyder Mir
- Department of Internal & Pulmonary Medicine, Sher-i-Kashmir Institute of Medical Sciences, Srinagar, Jammu and Kashmir, India
| | - Josef T. Prchal
- Division of Hematology and Hematologic Malignancies, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, Utah, United States of America
| | - Lynn B. Jorde
- Department of Human Genetics, University of Utah School of Medicine, Salt Lake City, Utah, United States of America
| | - Parvaiz A. Koul
- Department of Internal & Pulmonary Medicine, Sher-i-Kashmir Institute of Medical Sciences, Srinagar, Jammu and Kashmir, India
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45
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Elhaik E. In Search of the jüdische Typus: A Proposed Benchmark to Test the Genetic Basis of Jewishness Challenges Notions of "Jewish Biomarkers". Front Genet 2016; 7:141. [PMID: 27547215 PMCID: PMC4974603 DOI: 10.3389/fgene.2016.00141] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2016] [Accepted: 07/20/2016] [Indexed: 11/13/2022] Open
Abstract
The debate as to whether Jewishness is a biological trait inherent from an "authentic" "Jewish type" (jüdische Typus) ancestor or a system of beliefs has been raging for over two centuries. While the accumulated biological and anthropological evidence support the latter argument, recent genetic findings, bolstered by the direct-to-consumer genetic industry, purport to identify Jews or quantify one's Jewishness from genomic data. To test the merit of claims that Jews and non-Jews are genetically distinguishable, we propose a benchmark where genomic data of Jews and non-Jews are hybridized over two generations and the observed and predicted Jewishness of the terminal offspring according to either the Orthodox religious law (Halacha) or the Israeli Law of Return are compared. Members of academia, the public, and 23andMe were invited to use the benchmark to test claims that Jews are genetically distinct from non-Jews. Here, we report the findings from these trials. We also compare the genomic similarity of ∼300 individuals from nearly thirty Afro-Eurasian Jewish communities to a simulated jüdische Typus population. The results are discussed in light of modern trends in the genetics of Jews and related fields and provide a tentative answer to the ageless question "who is a Jew?"
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Affiliation(s)
- Eran Elhaik
- Department of Animal and Plant Sciences, University of Sheffield Sheffield, UK
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46
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Waldman YY, Biddanda A, Dubrovsky M, Campbell CL, Oddoux C, Friedman E, Atzmon G, Halperin E, Ostrer H, Keinan A. The genetic history of Cochin Jews from India. Hum Genet 2016; 135:1127-43. [PMID: 27377974 PMCID: PMC5020127 DOI: 10.1007/s00439-016-1698-y] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2016] [Accepted: 06/12/2016] [Indexed: 12/03/2022]
Abstract
Cochin Jews form a small and unique community on the Malabar coast in southwest India. While the arrival time of any putative Jewish ancestors of the community has been speculated to have taken place as far back as biblical times (King Solomon’s era), a Jewish community in the Malabar coast has been documented only since the 9th century CE. Here, we explore the genetic history of Cochin Jews by collecting and genotyping 21 community members and combining the data with that of 707 individuals from 72 other Indian, Jewish, and Pakistani populations, together with additional individuals from worldwide populations. We applied comprehensive genome-wide analyses based on principal component analysis, FST, ADMIXTURE, identity-by-descent sharing, admixture linkage disequilibrium decay, haplotype sharing, allele sharing autocorrelation decay and contrasting the X chromosome with the autosomes. We find that, as reported by several previous studies, the genetics of Cochin Jews resembles that of local Indian populations. However, we also identify considerable Jewish genetic ancestry that is not present in any other Indian or Pakistani populations (with the exception of the Jewish Bene Israel, which we characterized previously). Combined, Cochin Jews have both Jewish and Indian ancestry. Specifically, we detect a significant recent Jewish gene flow into this community 13–22 generations (~470–730 years) ago, with contributions from Yemenite, Sephardi, and Middle-Eastern Jews, in accordance with historical records. Genetic analyses also point to high endogamy and a recent population bottleneck in this population, which might explain the increased prevalence of some recessive diseases in Cochin Jews.
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Affiliation(s)
- Yedael Y Waldman
- Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY, 14853, USA
- Department of Molecular Microbiology and Biotechnology, Tel Aviv University, Ramat Aviv, 6997801, Tel Aviv, Israel
| | - Arjun Biddanda
- Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY, 14853, USA
| | - Maya Dubrovsky
- Danek Gertner Institute of Human Genetics, Chaim Sheba Medical Center, Tel Hashomer, 52621, Ramat Gan, Israel
- Sackler School of Medicine, Tel Aviv University, Ramat Aviv, 6997801, Tel Aviv, Israel
| | | | - Carole Oddoux
- Department of Pathology, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
| | - Eitan Friedman
- Danek Gertner Institute of Human Genetics, Chaim Sheba Medical Center, Tel Hashomer, 52621, Ramat Gan, Israel
- Sackler School of Medicine, Tel Aviv University, Ramat Aviv, 6997801, Tel Aviv, Israel
| | - Gil Atzmon
- Department of Medicine, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
- Department of Human Biology, Faculty of Natural Sciences, University of Haifa, Haifa, Israel
| | - Eran Halperin
- Department of Molecular Microbiology and Biotechnology, Tel Aviv University, Ramat Aviv, 6997801, Tel Aviv, Israel
- The Blavatnik School of Computer Science, Tel Aviv University, Ramat Aviv, 6997801, Tel Aviv, Israel
- International Computer Science Institute, Berkeley, CA, 94704, USA
| | - Harry Ostrer
- Department of Pathology, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
- Department of Pediatrics, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
| | - Alon Keinan
- Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY, 14853, USA.
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Das R, Wexler P, Pirooznia M, Elhaik E. Localizing Ashkenazic Jews to Primeval Villages in the Ancient Iranian Lands of Ashkenaz. Genome Biol Evol 2016; 8:1132-49. [PMID: 26941229 PMCID: PMC4860683 DOI: 10.1093/gbe/evw046] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/29/2016] [Indexed: 12/11/2022] Open
Abstract
The Yiddish language is over 1,000 years old and incorporates German, Slavic, and Hebrew elements. The prevalent view claims Yiddish has a German origin, whereas the opposing view posits a Slavic origin with strong Iranian and weak Turkic substrata. One of the major difficulties in deciding between these hypotheses is the unknown geographical origin of Yiddish speaking Ashkenazic Jews (AJs). An analysis of 393 Ashkenazic, Iranian, and mountain Jews and over 600 non-Jewish genomes demonstrated that Greeks, Romans, Iranians, and Turks exhibit the highest genetic similarity with AJs. The Geographic Population Structure analysis localized most AJs along major primeval trade routes in northeastern Turkey adjacent to primeval villages with names that may be derived from "Ashkenaz." Iranian and mountain Jews were localized along trade routes on the Turkey's eastern border. Loss of maternal haplogroups was evident in non-Yiddish speaking AJs. Our results suggest that AJs originated from a Slavo-Iranian confederation, which the Jews call "Ashkenazic" (i.e., "Scythian"), though these Jews probably spoke Persian and/or Ossete. This is compatible with linguistic evidence suggesting that Yiddish is a Slavic language created by Irano-Turko-Slavic Jewish merchants along the Silk Roads as a cryptic trade language, spoken only by its originators to gain an advantage in trade. Later, in the 9th century, Yiddish underwent relexification by adopting a new vocabulary that consists of a minority of German and Hebrew and a majority of newly coined Germanoid and Hebroid elements that replaced most of the original Eastern Slavic and Sorbian vocabularies, while keeping the original grammars intact.
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Affiliation(s)
- Ranajit Das
- Department of Animal and Plant Sciences, University of Sheffield, Sheffield, UK Manipal Centre for Natural Sciences (MCNS), Manipal University, Manipal, Karnataka, India
| | - Paul Wexler
- Department of Linguistics, Tel Aviv University, Tel-Aviv, Israel
| | - Mehdi Pirooznia
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University
| | - Eran Elhaik
- Department of Animal and Plant Sciences, University of Sheffield, Sheffield, UK
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48
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Goes FS, McGrath J, Avramopoulos D, Wolyniec P, Pirooznia M, Ruczinski I, Nestadt G, Kenny EE, Vacic V, Peters I, Lencz T, Darvasi A, Mulle JG, Warren ST, Pulver AE. Genome-wide association study of schizophrenia in Ashkenazi Jews. Am J Med Genet B Neuropsychiatr Genet 2015. [PMID: 26198764 DOI: 10.1002/ajmg.b.32349] [Citation(s) in RCA: 149] [Impact Index Per Article: 16.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
Schizophrenia is a common, clinically heterogeneous disorder associated with lifelong morbidity and early mortality. Several genetic variants associated with schizophrenia have been identified, but the majority of the heritability remains unknown. In this study, we report on a case-control sample of Ashkenazi Jews (AJ), a founder population that may provide additional insights into genetic etiology of schizophrenia. We performed a genome-wide association analysis (GWAS) of 592 cases and 505 controls of AJ ancestry ascertained in the US. Subsequently, we performed a meta-analysis with an Israeli AJ sample of 913 cases and 1640 controls, followed by a meta-analysis and polygenic risk scoring using summary results from Psychiatric GWAS Consortium 2 schizophrenia study. The U.S. AJ sample showed strong evidence of polygenic inheritance (pseudo-R(2) ∼9.7%) and a SNP-heritability estimate of 0.39 (P = 0.00046). We found no genome-wide significant associations in the U.S. sample or in the combined US/Israeli AJ meta-analysis of 1505 cases and 2145 controls. The strongest AJ specific associations (P-values in 10(-6) -10(-7) range) were in the 22q 11.2 deletion region and included the genes TBX1, GLN1, and COMT. Supportive evidence (meta P < 1 × 10(-4) ) was also found for several previously identified genome-wide significant findings, including the HLA region, CNTN4, IMMP2L, and GRIN2A. The meta-analysis of the U.S. sample with the PGC2 results provided initial genome-wide significant evidence for six new loci. Among the novel potential susceptibility genes is PEPD, a gene involved in proline metabolism, which is associated with a Mendelian disorder characterized by developmental delay and cognitive deficits.
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Affiliation(s)
- Fernando S Goes
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - John McGrath
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Dimitrios Avramopoulos
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland.,Institute of Genetic Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Paula Wolyniec
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Mehdi Pirooznia
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Ingo Ruczinski
- Department of Biostatistics, Bloomberg School of Public Health, Baltimore, Maryland
| | - Gerald Nestadt
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Eimear E Kenny
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York City, New York.,Department of Genetics and Genome Sciences, Icahn School of Medicine at Mount Sinai, New York City, New York.,Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York City, New York.,Center of Statistical Genetics, Icahn School of Medicine at Mount Sinai, New York City, New York
| | | | - Inga Peters
- Department of Genetics and Genome Sciences, Icahn School of Medicine at Mount Sinai, New York City, New York
| | - Todd Lencz
- Division of Research, Department of Psychiatry, The Zucker Hillside Hospital Division of the North Shore-Long Island Jewish Health System, Glen Oaks, New York.,Center for Psychiatric Neuroscience, The Feinstein Institute for Medical Research, Manhasset, New York.,Department of Psychiatry and Behavioral Sciences, Albert Einstein College of Medicine of Yeshiva University, Bronx, New York.,Department of Psychiatry, Hofstra University School of Medicine, Hempstead, New York.,Department of Molecular Medicine, Hofstra University School of Medicine, Hempstead, New York
| | - Ariel Darvasi
- Department of Genetics, The Institute of Life Sciences, The Hebrew University of Jerusalem, Givat Ram, Jerusalem, Israel
| | - Jennifer G Mulle
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia
| | - Stephen T Warren
- Departments of Human Genetics, Pediatrics and Biochemistry, Emory University, Atlanta, Georgia
| | - Ann E Pulver
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland
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49
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Johansson MM, Van Geystelen A, Larmuseau MHD, Djurovic S, Andreassen OA, Agartz I, Jazin E. Microarray Analysis of Copy Number Variants on the Human Y Chromosome Reveals Novel and Frequent Duplications Overrepresented in Specific Haplogroups. PLoS One 2015; 10:e0137223. [PMID: 26322892 PMCID: PMC4554990 DOI: 10.1371/journal.pone.0137223] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2015] [Accepted: 08/13/2015] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND The human Y chromosome is almost always excluded from genome-wide investigations of copy number variants (CNVs) due to its highly repetitive structure. This chromosome should not be forgotten, not only for its well-known relevance in male fertility, but also for its involvement in clinical phenotypes such as cancers, heart failure and sex specific effects on brain and behaviour. RESULTS We analysed Y chromosome data from Affymetrix 6.0 SNP arrays and found that the signal intensities for most of 8179 SNP/CN probes in the male specific region (MSY) discriminated between a male, background signals in a female and an isodicentric male containing a large deletion of the q-arm and a duplication of the p-arm of the Y chromosome. Therefore, this SNP/CN platform is suitable for identification of gain and loss of Y chromosome sequences. In a set of 1718 males, we found 25 different CNV patterns, many of which are novel. We confirmed some of these variants by PCR or qPCR. The total frequency of individuals with CNVs was 14.7%, including 9.5% with duplications, 4.5% with deletions and 0.7% exhibiting both. Hence, a novel observation is that the frequency of duplications was more than twice the frequency of deletions. Another striking result was that 10 of the 25 detected variants were significantly overrepresented in one or more haplogroups, demonstrating the importance to control for haplogroups in genome-wide investigations to avoid stratification. NO-M214(xM175) individuals presented the highest percentage (95%) of CNVs. If they were not counted, 12.4% of the rest included CNVs, and the difference between duplications (8.9%) and deletions (2.8%) was even larger. CONCLUSIONS Our results demonstrate that currently available genome-wide SNP platforms can be used to identify duplications and deletions in the human Y chromosome. Future association studies of the full spectrum of Y chromosome variants will demonstrate the potential involvement of gain or loss of Y chromosome sequence in different human phenotypes.
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Affiliation(s)
- Martin M. Johansson
- Department of Organismal Biology, EBC, Uppsala University, Uppsala, Sweden
- * E-mail: (MMJ); (EJ)
| | - Anneleen Van Geystelen
- Laboratory of Socioecology and Social Evolution, Department of Biology, KU Leuven, Leuven, Belgium
| | - Maarten H. D. Larmuseau
- Laboratory of Socioecology and Social Evolution, Department of Biology, KU Leuven, Leuven, Belgium
- Forensic Biomedical Sciences, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
- NORMENT, KG Jebsen Centre for Psychosis Research, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Ole A. Andreassen
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ingrid Agartz
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
| | - Elena Jazin
- Department of Organismal Biology, EBC, Uppsala University, Uppsala, Sweden
- * E-mail: (MMJ); (EJ)
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Campbell MC, Hirbo JB, Townsend JP, Tishkoff SA. The peopling of the African continent and the diaspora into the new world. Curr Opin Genet Dev 2015; 29:120-32. [PMID: 25461616 DOI: 10.1016/j.gde.2014.09.003] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2014] [Revised: 09/03/2014] [Accepted: 09/05/2014] [Indexed: 12/22/2022]
Abstract
Africa is the birthplace of anatomically modern humans, and is the geographic origin of human migration across the globe within the last 100,000 years. The history of African populations has consisted of a number of demographic events that have influenced patterns of genetic and phenotypic variation across the continent. With the increasing amount of genomic data and corresponding developments in computational methods, researchers are able to explore long-standing evolutionary questions, expanding our understanding of human history within and outside of Africa. This review will summarize some of the recent findings regarding African demographic history, including the African Diaspora, and will briefly explore their implications for disease susceptibility in populations of African descent.
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