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Blanc J, Berg JJ. Testing for differences in polygenic scores in the presence of confounding. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.03.12.532301. [PMID: 36993707 PMCID: PMC10055004 DOI: 10.1101/2023.03.12.532301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Polygenic scores have become an important tool in human genetics, enabling the prediction of individuals' phenotypes from their genotypes. Understanding how the pattern of differences in polygenic score predictions across individuals intersects with variation in ancestry can provide insights into the evolutionary forces acting on the trait in question, and is important for understanding health disparities. However, because most polygenic scores are computed using effect estimates from population samples, they are susceptible to confounding by both genetic and environmental effects that are correlated with ancestry. The extent to which this confounding drives patterns in the distribution of polygenic scores depends on patterns of population structure in both the original estimation panel and in the prediction/test panel. Here, we use theory from population and statistical genetics, together with simulations, to study the procedure of testing for an association between polygenic scores and axes of ancestry variation in the presence of confounding. We use a general model of genetic relatedness to describe how confounding in the estimation panel biases the distribution of polygenic scores in a way that depends on the degree of overlap in population structure between panels. We then show how this confounding can bias tests for associations between polygenic scores and important axes of ancestry variation in the test panel. Specifically, for any given test, there exists a single axis of population structure in the GWAS panel that needs to be controlled for in order to protect the test. Based on this result, we propose a new approach for directly estimating this axis of population structure in the GWAS panel. We then use simulations to compare the performance of this approach to the standard approach in which the principal components of the GWAS panel genotypes are used to control for stratification.
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Affiliation(s)
- Jennifer Blanc
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
| | - Jeremy J. Berg
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
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2
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Szpiech ZA. selscan 2.0: scanning for sweeps in unphased data. Bioinformatics 2024; 40:btae006. [PMID: 38180866 PMCID: PMC10789311 DOI: 10.1093/bioinformatics/btae006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Revised: 12/26/2023] [Accepted: 01/03/2024] [Indexed: 01/07/2024] Open
Abstract
SUMMARY Several popular haplotype-based statistics for identifying recent or ongoing positive selection in genomes require knowledge of haplotype phase. Here, we provide an update to selscan which implements a re-definition of these statistics for use in unphased data. AVAILABILITY AND IMPLEMENTATION Source code and binaries are freely available at https://github.com/szpiech/selscan, implemented in C/C++, and supported on Linux, Windows, and MacOS.
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Affiliation(s)
- Zachary A Szpiech
- Department of Biology, Penn State University, University Park, PA 16802, United States
- Institute for Computational and Data Sciences, Penn State University, University Park, PA 16802, United States
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3
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Gao Z. Unveiling recent and ongoing adaptive selection in human populations. PLoS Biol 2024; 22:e3002469. [PMID: 38236800 PMCID: PMC10796035 DOI: 10.1371/journal.pbio.3002469] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2024] Open
Abstract
Genome-wide scans for signals of selection have become a routine part of the analysis of population genomic variation datasets and have resulted in compelling evidence of selection during recent human evolution. This Essay spotlights methodological innovations that have enabled the detection of selection over very recent timescales, even in contemporary human populations. By harnessing large-scale genomic and phenotypic datasets, these new methods use different strategies to uncover connections between genotype, phenotype, and fitness. This Essay outlines the rationale and key findings of each strategy, discusses challenges in interpretation, and describes opportunities to improve detection and understanding of ongoing selection in human populations.
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Affiliation(s)
- Ziyue Gao
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
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4
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Gloss AD, Steiner MC, Novembre J, Bergelson J. The design of mapping populations: Impacts of geographic scale on genetic architecture and mapping efficacy for defense and immunity. CURRENT OPINION IN PLANT BIOLOGY 2023; 74:102399. [PMID: 37307746 PMCID: PMC10441534 DOI: 10.1016/j.pbi.2023.102399] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/27/2022] [Revised: 04/29/2023] [Accepted: 05/15/2023] [Indexed: 06/14/2023]
Abstract
Genome-wide association studies (GWAS) have yielded tremendous insight into the genetic architecture of trait variation. However, the collections of loci they uncover are far from exhaustive. As many of the complicating factors that confound or limit the efficacy of GWAS are exaggerated over broad geographic scales, a shift toward more analyses using mapping panels sampled from narrow geographic localities ("local" populations) could provide novel, complementary insights. Here, we present an overview of the major complicating factors, review mounting evidence from genomic analyses that these factors are pervasive, and synthesize theoretical and empirical evidence for the power of GWAS in local populations.
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Affiliation(s)
- Andrew D Gloss
- Department of Biology, Center for Genomics and Systems Biology, New York University, New York, NY, USA.
| | | | - John Novembre
- Department of Human Genetics, University of Chicago, Chicago, IL, USA; Department of Ecology & Evolution, University of Chicago, Chicago, IL, USA
| | - Joy Bergelson
- Department of Biology, Center for Genomics and Systems Biology, New York University, New York, NY, USA.
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5
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Park S. Height-Related Polygenic Variants Are Associated with Metabolic Syndrome Risk and Interact with Energy Intake and a Rice-Main Diet to Influence Height in KoGES. Nutrients 2023; 15:nu15071764. [PMID: 37049604 PMCID: PMC10096788 DOI: 10.3390/nu15071764] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 04/01/2023] [Accepted: 04/02/2023] [Indexed: 04/08/2023] Open
Abstract
Adult height is inversely related to metabolic syndrome (MetS) risk, but its genetic impacts have not been revealed. The present study aimed to examine the hypothesis that adult height-related genetic variants interact with lifestyle to influence adult height and are associated with MetS risk in adults aged >40 in Korea during 2010–2014. Participants were divided into short stature (SS; control) and tall stature (TS; case) by the 85th percentile of adult height. The genetic variants linked to adult height were screened from a genome-wide association study in a city hospital-based cohort (n = 58,701) and confirmed in Ansan/Ansung plus rural cohorts (n = 13,783) among the Korean Genome and Epidemiology Study. Genetic variants that interacted with each other were identified using the generalized multifactor dimensionality reduction (GMDR) analysis. The interaction between the polygenic risk score (PRS) of the selected genetic variants and lifestyles was examined. Adult height was inversely associated with MetS, cardiovascular diseases, and liver function. The PRS, including zinc finger and BTB domain containing 38 (ZBTB38)_rs6762722, polyadenylate-binding protein-interacting protein-2B (PAIP2B)_rs13034890, carboxypeptidase Z (CPZ)_rs3756173, and latent-transforming growth factor beta-binding protein-1 (LTBP1)_rs4630744, was positively associated with height by 1.29 times and inversely with MetS by 0.894 times after adjusting for covariates. In expression quantitative trait loci, the gene expression of growth/differentiation factor-5 (GDF5)_rs224331, non-SMC condensin I complex subunit G (NCAPG)_rs2074974, ligand-dependent nuclear receptor corepressor like (LCORL)_rs7700107, and insulin-like growth factor-1 receptor (IGF1R)_rs2871865 was inversely linked to their risk allele in the tibial nerve and brain. The gene expression of PAIP2B_rs13034890 and a disintegrin and metalloproteinase with thrombospondin motifs-like-3 (ADAMTSL3)_rs13034890 was positively related to it. The PRS was inversely associated with MetS, hyperglycemia, HbA1c, and white blood cell counts. The wild type of GDF5_rs224331 (Ala276) lowered binding energy with rugosin A, D, and E (one of the hydrolyzable tannins) but not the mutated one (276Ser) in the in-silico analysis. The PRS interacted with energy intake and rice-main diet; PRS impact was higher in the high energy intake and the low rice-main diet. In conclusion, the PRS for adult height interacted with energy intake and diet patterns to modulate height and was linked to height and MetS by modulating their expression in the tibial nerve and brain.
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Affiliation(s)
- Sunmin Park
- Department of Food and Nutrition, Obesity/Diabetes Research Center, Hoseo University, 165 Sechul-Ri, BaeBang-Yup, Asan-Si 336-795, ChungNam-Do, Republic of Korea
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6
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Perchard R, Murray PG, Clayton PE. Approach to the Patient With Short Stature: Genetic Testing. J Clin Endocrinol Metab 2023; 108:1007-1017. [PMID: 36355576 DOI: 10.1210/clinem/dgac637] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Revised: 10/24/2022] [Indexed: 11/12/2022]
Abstract
The first step in the evaluation of the short child is to decide whether growth parameters in the context of the history are abnormal or a variant of normal. If growth is considered abnormal, system and hormonal tests are likely to be required, followed by more directed testing, such as skeletal survey and/or genetic screening with karyotype or microarray. In a small percentage of short children in whom a diagnosis has not been reached, this will need to be followed by detailed genetic analysis; currently, exome sequencing using targeted panels relevant to the phenotype is the commonly used test. Clinical scenarios are presented that illustrate how such genetic testing can be used to establish a molecular diagnosis, and how that diagnosis contributes to the management of the short child. New genetic causes for short stature are being recognized on a frequent basis, while the clinical spectrum for known genes is being extended. We recommend that an international repository for short stature conditions is established for new findings to aid dissemination of knowledge, but also to help in the definition of the clinical spectrum both for new and established conditions.
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Affiliation(s)
- Reena Perchard
- Department of Developmental Biology and Medicine, University of Manchester, Manchester M13 9PL, UK
- Department of Paediatric Endocrinology, Royal Manchester Children's Hospital, Manchester M13 9WL, UK
- Manchester Academic Health Science Centre, Manchester M13 9PL, UK
| | - Philip George Murray
- Department of Developmental Biology and Medicine, University of Manchester, Manchester M13 9PL, UK
- Department of Paediatric Endocrinology, Royal Manchester Children's Hospital, Manchester M13 9WL, UK
- Manchester Academic Health Science Centre, Manchester M13 9PL, UK
| | - Peter Ellis Clayton
- Department of Developmental Biology and Medicine, University of Manchester, Manchester M13 9PL, UK
- Department of Paediatric Endocrinology, Royal Manchester Children's Hospital, Manchester M13 9WL, UK
- Manchester Academic Health Science Centre, Manchester M13 9PL, UK
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7
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Idiopathic Short Stature: What to Expect from Genomic Investigations. ENDOCRINES 2023. [DOI: 10.3390/endocrines4010001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
Short stature is a common concern for physicians caring for children. In traditional investigations, about 70% of children are healthy, without producing clinical and laboratory findings that justify their growth disorder, being classified as having constitutional short stature or idiopathic short stature (ISS). In such scenarios, the genetic approach has emerged as a great potential method to understand ISS. Over the last 30 years, several genes have been identified as being responsible for isolated short stature, with almost all of them being inherited in an autosomal-dominant pattern. Most of these defects are in genes related to the growth plate, followed by genes related to the growth hormone (GH)–insulin-like growth factor 1 (IGF1) axis and RAS-MAPK pathway. These patients usually do not have a specific phenotype, which hinders the use of a candidate gene approach. Through multigene sequencing analyses, it has been possible to provide an answer for short stature in 10–30% of these cases, with great impacts on treatment and follow-up, allowing the application of the concept of precision medicine in patients with ISS. This review highlights the historic aspects and provides an update on the monogenic causes of idiopathic short stature and suggests what to expect from genomic investigations in this field.
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8
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Hofmeister RJ, Rubinacci S, Ribeiro DM, Buil A, Kutalik Z, Delaneau O. Parent-of-Origin inference for biobanks. Nat Commun 2022; 13:6668. [PMID: 36335127 PMCID: PMC9637181 DOI: 10.1038/s41467-022-34383-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 10/24/2022] [Indexed: 11/06/2022] Open
Abstract
Identical genetic variations can have different phenotypic effects depending on their parent of origin. Yet, studies focusing on parent-of-origin effects have been limited in terms of sample size due to the lack of parental genomes or known genealogies. We propose a probabilistic approach to infer the parent-of-origin of individual alleles that does not require parental genomes nor prior knowledge of genealogy. Our model uses Identity-By-Descent sharing with second- and third-degree relatives to assign alleles to parental groups and leverages chromosome X data in males to distinguish maternal from paternal groups. We combine this with robust haplotype inference and haploid imputation to infer the parent-of-origin for 26,393 UK Biobank individuals. We screen 99 phenotypes for parent-of-origin effects and replicate the discoveries of 6 GWAS studies, confirming signals on body mass index, type 2 diabetes, standing height and multiple blood biomarkers, including the known maternal effect at the MEG3/DLK1 locus on platelet phenotypes. We also report a novel maternal effect at the TERT gene on telomere length, thereby providing new insights on the heritability of this phenotype. All our summary statistics are publicly available to help the community to better characterize the molecular mechanisms leading to parent-of-origin effects and their implications for human health.
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Affiliation(s)
- Robin J Hofmeister
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.,Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland
| | - Simone Rubinacci
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.,Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland
| | - Diogo M Ribeiro
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.,Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland
| | - Alfonso Buil
- Institute of Biological Psychiatry, Mental Health Services, Copenhagen University Hospital, Copenhagen, Denmark.,Lundbeck Foundation GeoGenetics Centre, GLOBE Institute, University of Copenhagen, Copenhagen, Denmark
| | - Zoltán Kutalik
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.,Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland.,University Center for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland
| | - Olivier Delaneau
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland. .,Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland.
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9
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Abraham A, LaBella AL, Capra JA, Rokas A. Mosaic patterns of selection in genomic regions associated with diverse human traits. PLoS Genet 2022; 18:e1010494. [PMID: 36342969 PMCID: PMC9671423 DOI: 10.1371/journal.pgen.1010494] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 11/17/2022] [Accepted: 10/21/2022] [Indexed: 11/09/2022] Open
Abstract
Natural selection shapes the genetic architecture of many human traits. However, the prevalence of different modes of selection on genomic regions associated with variation in traits remains poorly understood. To address this, we developed an efficient computational framework to calculate positive and negative enrichment of different evolutionary measures among regions associated with complex traits. We applied the framework to summary statistics from >900 genome-wide association studies (GWASs) and 11 evolutionary measures of sequence constraint, population differentiation, and allele age while accounting for linkage disequilibrium, allele frequency, and other potential confounders. We demonstrate that this framework yields consistent results across GWASs with variable sample sizes, numbers of trait-associated SNPs, and analytical approaches. The resulting evolutionary atlas maps diverse signatures of selection on genomic regions associated with complex human traits on an unprecedented scale. We detected positive enrichment for sequence conservation among trait-associated regions for the majority of traits (>77% of 290 high power GWASs), which included reproductive traits. Many traits also exhibited substantial positive enrichment for population differentiation, especially among hair, skin, and pigmentation traits. In contrast, we detected widespread negative enrichment for signatures of balancing selection (51% of GWASs) and absence of enrichment for evolutionary signals in regions associated with late-onset Alzheimer's disease. These results support a pervasive role for negative selection on regions of the human genome that contribute to variation in complex traits, but also demonstrate that diverse modes of evolution are likely to have shaped trait-associated loci. This atlas of evolutionary signatures across the diversity of available GWASs will enable exploration of the relationship between the genetic architecture and evolutionary processes in the human genome.
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Affiliation(s)
- Abin Abraham
- Vanderbilt University Medical Center, Vanderbilt University, Nashville, Tennessee, United States of America
| | - Abigail L. LaBella
- Department of Biological Sciences, Vanderbilt University, Nashville, Tennessee, United States of America
- Evolutionary Studies Initiative, Vanderbilt University, Nashville, Tennessee, United States of America
- Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, North Carolina, United States of America
- North Carolina Research Center, Kannapolis, North Carolina, United States of America
| | - John A. Capra
- Bakar Computational Health Sciences Institute, University of California, San Francisco, California, United States of America
- Department of Epidemiology and Biostatistics, University of California, San Francisco, California, United States of America
| | - Antonis Rokas
- Department of Biological Sciences, Vanderbilt University, Nashville, Tennessee, United States of America
- Evolutionary Studies Initiative, Vanderbilt University, Nashville, Tennessee, United States of America
- Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America
- Vanderbilt Genetics Institute, Vanderbilt University, Nashville, Tennessee, United States of America
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10
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Genetic Variation among Pharmacogenes in the Sardinian Population. Int J Mol Sci 2022; 23:ijms231710058. [PMID: 36077453 PMCID: PMC9456055 DOI: 10.3390/ijms231710058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 08/25/2022] [Accepted: 08/29/2022] [Indexed: 11/22/2022] Open
Abstract
Pharmacogenetics (PGx) aims to identify the genetic factors that determine inter-individual differences in response to drug treatment maximizing efficacy while decreasing the risk of adverse events. Estimating the prevalence of PGx variants involved in drug response, is a critical preparatory step for large-scale implementation of a personalized medicine program in a target population. Here, we profiled pharmacogenetic variation in fourteen clinically relevant genes in a representative sample set of 1577 unrelated sequenced Sardinians, an ancient island population that accounts for genetic variation in Europe as a whole, and, at the same time is enriched in genetic variants that are very rare elsewhere. To this end, we used PGxPOP, a PGx allele caller based on the guidelines created by the Clinical Pharmacogenetics Implementation Consortium (CPIC), to identify the main phenotypes associated with the PGx alleles most represented in Sardinians. We estimated that 99.43% of Sardinian individuals might potentially respond atypically to at least one drug, that on average each individual is expected to have an abnormal response to about 17 drugs, and that for 27 drugs the fraction of the population at risk of atypical responses to therapy is more than 40%. Finally, we identified 174 pharmacogenetic variants for which the minor allele frequency was at least 10% higher among Sardinians as compared to other European populations, a fact that may contribute to substantial interpopulation variability in drug response phenotypes. This study provides baseline information for further large-scale pharmacogenomic investigations in the Sardinian population and underlines the importance of PGx characterization of diverse European populations, such as Sardinians.
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11
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The genomic origins of the world's first farmers. Cell 2022; 185:1842-1859.e18. [PMID: 35561686 PMCID: PMC9166250 DOI: 10.1016/j.cell.2022.04.008] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Revised: 03/04/2022] [Accepted: 04/06/2022] [Indexed: 11/24/2022]
Abstract
The precise genetic origins of the first Neolithic farming populations in Europe and Southwest Asia, as well as the processes and the timing of their differentiation, remain largely unknown. Demogenomic modeling of high-quality ancient genomes reveals that the early farmers of Anatolia and Europe emerged from a multiphase mixing of a Southwest Asian population with a strongly bottlenecked western hunter-gatherer population after the last glacial maximum. Moreover, the ancestors of the first farmers of Europe and Anatolia went through a period of extreme genetic drift during their westward range expansion, contributing highly to their genetic distinctiveness. This modeling elucidates the demographic processes at the root of the Neolithic transition and leads to a spatial interpretation of the population history of Southwest Asia and Europe during the late Pleistocene and early Holocene.
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12
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Mocci S, Littera R, Tranquilli S, Provenzano A, Mascia A, Cannas F, Lai S, Giuressi E, Chessa L, Angioni G, Campagna M, Firinu D, Del Zompo M, La Nasa G, Perra A, Giglio S. A Protective HLA Extended Haplotype Outweighs the Major COVID-19 Risk Factor Inherited From Neanderthals in the Sardinian Population. Front Immunol 2022; 13:891147. [PMID: 35514995 PMCID: PMC9063452 DOI: 10.3389/fimmu.2022.891147] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Accepted: 03/24/2022] [Indexed: 11/13/2022] Open
Abstract
Sardinia has one of the lowest incidences of hospitalization and related mortality in Europe and yet a very high frequency of the Neanderthal risk locus variant on chromosome 3 (rs35044562), considered to be a major risk factor for a severe SARS-CoV-2 disease course. We evaluated 358 SARS-CoV-2 patients and 314 healthy Sardinian controls. One hundred and twenty patients were asymptomatic, 90 were pauci-symptomatic, 108 presented a moderate disease course and 40 were severely ill. All patients were analyzed for the Neanderthal-derived genetic variants reported as being protective (rs1156361) or causative (rs35044562) for severe illness. The β°39 C>T Thalassemia variant (rs11549407), HLA haplotypes, KIR genes, KIRs and their HLA class I ligand combinations were also investigated. Our findings revealed an increased risk for severe disease in Sardinian patients carrying the rs35044562 high risk variant [OR 5.32 (95% CI 2.53 - 12.01), p = 0.000]. Conversely, the protective effect of the HLA-A*02:01, B*18:01, DRB*03:01 three-loci extended haplotype in the Sardinian population was shown to efficiently contrast the high risk of a severe and devastating outcome of the infection predicted for carriers of the Neanderthal locus [OR 15.47 (95% CI 5.8 - 41.0), p < 0.0001]. This result suggests that the balance between risk and protective immunogenetic factors plays an important role in the evolution of COVID-19. A better understanding of these mechanisms may well turn out to be the biggest advantage in the race for the development of more efficient drugs and vaccines.
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Affiliation(s)
- Stefano Mocci
- Medical Genetics Unit, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
| | - Roberto Littera
- Medical Genetics Unit, R. Binaghi Hospital, Local Public Health and Social Care Unit (ASSL) of Cagliari, Cagliari, Italy.,Association for the Advancement of Research on Transplantation O.d.V., Non Profit Organisation, Cagliari, Italy
| | - Stefania Tranquilli
- Medical Genetics Unit, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
| | - Aldesia Provenzano
- Medical Genetics Unit, Department of Experimental and Clinical Biomedical Sciences "Mario Serio", University of Florence, Florence, Italy
| | - Alessia Mascia
- Medical Genetics Unit, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
| | - Federica Cannas
- Medical Genetics Unit, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
| | - Sara Lai
- Medical Genetics Unit, R. Binaghi Hospital, Local Public Health and Social Care Unit (ASSL) of Cagliari, Cagliari, Italy
| | - Erika Giuressi
- Medical Genetics Unit, R. Binaghi Hospital, Local Public Health and Social Care Unit (ASSL) of Cagliari, Cagliari, Italy
| | - Luchino Chessa
- Association for the Advancement of Research on Transplantation O.d.V., Non Profit Organisation, Cagliari, Italy.,Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy.,Liver Unit, Department of Internal Medicine, University Hospital of Cagliari, Cagliari, Italy
| | - Goffredo Angioni
- Structure of Infectious Diseases Unit, SS Trinità Hospital, Cagliari, Italy
| | - Marcello Campagna
- Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
| | - Davide Firinu
- Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
| | - Maria Del Zompo
- Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy
| | - Giorgio La Nasa
- Hematology Unit, Businco Hospital, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
| | - Andrea Perra
- Association for the Advancement of Research on Transplantation O.d.V., Non Profit Organisation, Cagliari, Italy.,Unit of Oncology and Molecular Pathology, Department of Biomedical Sciences, University of Cagliari, Monserrato, Italy
| | - Sabrina Giglio
- Medical Genetics Unit, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy.,Medical Genetics Unit, R. Binaghi Hospital, Local Public Health and Social Care Unit (ASSL) of Cagliari, Cagliari, Italy.,Centre for Research University Services (CeSAR, Centro Servizi di Ateneo per la Ricerca), University of Cagliari, Monserrato, Italy
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13
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Age Assessment in Children and Adolescents by Measuring the Open Apices in Teeth: A New Sardinian Formula. Dent J (Basel) 2022; 10:dj10040050. [PMID: 35448044 PMCID: PMC9028070 DOI: 10.3390/dj10040050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Revised: 03/04/2022] [Accepted: 03/21/2022] [Indexed: 02/01/2023] Open
Abstract
Age estimation in children is fundamental in both clinical and forensic fields. The aim of this study was to evaluate the accuracy of the Cameriere’s European and Italian formulae for age estimation in Sardinian children and adolescents, a genetically isolated population. A sample of 202 orthopantomograms of healthy Sardinian children and adolescents (100 females and 102 males) aged between 6 and 17 years was retrospectively evaluated. The seven left mandibular teeth were assessed with the Cameriere’s European and Italian formulae. The teeth with closed apex (N0) were counted and, in the teeth with open apex, the distance between the inner sides was calculated. All variables showed a significant and negative correlation with age except N0 and g. Sex (g), the variables s, N0, and the first-order interaction between them, contributed substantially to the age measurement (p < 0.001). Although the value of x5 had a low prediction level, it generated the following multiple linear regression formula, specific for the Sardinian sample: Age = 10.372 + 0.469 g + 0.810 N0 − 1.079 s − 0.398 s ∙ N0 − 0.326 × 5. Only the Sardinian and European formulae allowed to obtain an acceptable interclass agreement (both the lower and upper >0.7). The results showed that the European formula could be accurate for assessing age in this sample of children and adolescents.
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14
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Charney E. The "Golden Age" of Behavior Genetics? PERSPECTIVES ON PSYCHOLOGICAL SCIENCE 2022; 17:1188-1210. [PMID: 35180032 DOI: 10.1177/17456916211041602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The search for genetic risk factors underlying the presumed heritability of all human behavior has unfolded in two phases. The first phase, characterized by candidate-gene-association (CGA) studies, has fallen out of favor in the behavior-genetics community, so much so that it has been referred to as a "cautionary tale." The second and current iteration is characterized by genome-wide association studies (GWASs), single-nucleotide polymorphism (SNP) heritability estimates, and polygenic risk scores. This research is guided by the resurrection of, or reemphasis on, Fisher's "infinite infinitesimal allele" model of the heritability of complex phenotypes, first proposed over 100 years ago. Despite seemingly significant differences between the two iterations, they are united in viewing the discovery of risk alleles underlying heritability as a matter of finding differences in allele frequencies. Many of the infirmities that beset CGA studies persist in the era of GWASs, accompanied by a host of new difficulties due to the human genome's underlying complexities and the limitations of Fisher's model in the postgenomics era.
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Affiliation(s)
- Evan Charney
- The Samuel DuBois Cook Center on Social Equity, Duke University
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15
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Pośpiech E, Teisseyre P, Mielniczuk J, Branicki W. Predicting Physical Appearance from DNA Data-Towards Genomic Solutions. Genes (Basel) 2022; 13:genes13010121. [PMID: 35052461 PMCID: PMC8774670 DOI: 10.3390/genes13010121] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Revised: 01/03/2022] [Accepted: 01/04/2022] [Indexed: 02/04/2023] Open
Abstract
The idea of forensic DNA intelligence is to extract from genomic data any information that can help guide the investigation. The clues to the externally visible phenotype are of particular practical importance. The high heritability of the physical phenotype suggests that genetic data can be easily predicted, but this has only become possible with less polygenic traits. The forensic community has developed DNA-based predictive tools by employing a limited number of the most important markers analysed with targeted massive parallel sequencing. The complexity of the genetics of many other appearance phenotypes requires big data coupled with sophisticated machine learning methods to develop accurate genomic predictors. A significant challenge in developing universal genomic predictive methods will be the collection of sufficiently large data sets. These should be created using whole-genome sequencing technology to enable the identification of rare DNA variants implicated in phenotype determination. It is worth noting that the correctness of the forensic sketch generated from the DNA data depends on the inclusion of an age factor. This, however, can be predicted by analysing epigenetic data. An important limitation preventing whole-genome approaches from being commonly used in forensics is the slow progress in the development and implementation of high-throughput, low DNA input sequencing technologies. The example of palaeoanthropology suggests that such methods may possibly be developed in forensics.
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Affiliation(s)
- Ewelina Pośpiech
- Malopolska Centre of Biotechnology, Jagiellonian University, 30-387 Kraków, Poland;
| | - Paweł Teisseyre
- Institute of Computer Science, Polish Academy of Sciences, 01-248 Warsaw, Poland; (P.T.); (J.M.)
- Faculty of Mathematics and Information Science, Warsaw University of Technology, 00-662 Warsaw, Poland
| | - Jan Mielniczuk
- Institute of Computer Science, Polish Academy of Sciences, 01-248 Warsaw, Poland; (P.T.); (J.M.)
- Faculty of Mathematics and Information Science, Warsaw University of Technology, 00-662 Warsaw, Poland
| | - Wojciech Branicki
- Malopolska Centre of Biotechnology, Jagiellonian University, 30-387 Kraków, Poland;
- Central Forensic Laboratory of the Police, 00-583 Warsaw, Poland
- Correspondence: ; Tel.: +48-126-645-024
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16
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Sohail M, Izarraras-Gomez A, Ortega-Del Vecchyo D. Populations, Traits, and Their Spatial Structure in Humans. Genome Biol Evol 2021; 13:evab272. [PMID: 34894236 PMCID: PMC8715524 DOI: 10.1093/gbe/evab272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/06/2021] [Indexed: 11/16/2022] Open
Abstract
The spatial distribution of genetic variants is jointly determined by geography, past demographic processes, natural selection, and its interplay with environmental variation. A fraction of these genetic variants are "causal alleles" that affect the manifestation of a complex trait. The effect exerted by these causal alleles on complex traits can be independent or dependent on the environment. Understanding the evolutionary processes that shape the spatial structure of causal alleles is key to comprehend the spatial distribution of complex traits. Natural selection, past population size changes, range expansions, consanguinity, assortative mating, archaic introgression, admixture, and the environment can alter the frequencies, effect sizes, and heterozygosities of causal alleles. This provides a genetic axis along which complex traits can vary. However, complex traits also vary along biogeographical and sociocultural axes which are often correlated with genetic axes in complex ways. The purpose of this review is to consider these genetic and environmental axes in concert and examine the ways they can help us decipher the variation in complex traits that is visible in humans today. This initiative necessarily implies a discussion of populations, traits, the ability to infer and interpret "genetic" components of complex traits, and how these have been impacted by adaptive events. In this review, we provide a history-aware discussion on these topics using both the recent and more distant past of our academic discipline and its relevant contexts.
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Affiliation(s)
- Mashaal Sohail
- Department of Human Genetics, University of Chicago, USA
- Centro de Ciencias Genómicas (CCG), Universidad Nacional Autónoma de México (UNAM), Cuernavaca, Morelos, México
| | - Alan Izarraras-Gomez
- Laboratorio Internacional de Investigación sobre el Genoma Humano (LIIGH), Universidad Nacional Autónoma de México (UNAM), Juriquilla, Querétaro, México
| | - Diego Ortega-Del Vecchyo
- Laboratorio Internacional de Investigación sobre el Genoma Humano (LIIGH), Universidad Nacional Autónoma de México (UNAM), Juriquilla, Querétaro, México
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17
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Chiang CWK. The Opportunities and Challenges of Integrating Population Histories Into Genetic Studies for Diverse Populations: A Motivating Example From Native Hawaiians. Front Genet 2021; 12:643883. [PMID: 34646295 PMCID: PMC8503554 DOI: 10.3389/fgene.2021.643883] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2020] [Accepted: 08/19/2021] [Indexed: 11/25/2022] Open
Abstract
There is a well-recognized need to include diverse populations in genetic studies, but several obstacles continue to be prohibitive, including (but are not limited to) the difficulty of recruiting individuals from diverse populations in large numbers and the lack of representation in available genomic references. These obstacles notwithstanding, studying multiple diverse populations would provide informative, population-specific insights. Using Native Hawaiians as an example of an understudied population with a unique evolutionary history, I will argue that by developing key genomic resources and integrating evolutionary thinking into genetic epidemiology, we will have the opportunity to efficiently advance our knowledge of the genetic risk factors, ameliorate health disparity, and improve healthcare in this underserved population.
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Affiliation(s)
- Charleston W K Chiang
- Department of Population and Public Health Sciences, Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States.,Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, United States
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18
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Allele frequency differentiation at height-associated SNPs among continental human populations. Eur J Hum Genet 2021; 29:1542-1548. [PMID: 34267339 PMCID: PMC8484658 DOI: 10.1038/s41431-021-00938-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Revised: 06/20/2021] [Accepted: 06/28/2021] [Indexed: 02/07/2023] Open
Abstract
Methods to detect polygenic adaptation have recently been shown to be sensitive to uncorrected stratification in GWAS, thereby casting doubts on whether polygenic adaptation is prevalent among humans. Consistent with a signal of adaptation at human height loci, the mean FST among African, East Asian, and European populations was shown to be significantly higher at height-associated SNPs than that at non-associated SNPs. This conclusion was reached, however, using height-associated SNPs ascertained from a GWAS design impacted by residual confounding due to uncorrected stratification. Specifically, we show here that the estimated effect sizes are significantly correlated with population structure across continents, potentially explaining the elevated differentiation previously reported. We alleviated these concerns of confounding by ascertaining height-associated SNPs from two biobank GWAS (UK Biobank, UKB, and Biobank Japan, BBJ), where measures to control for confounding in GWAS are more effective. Consistent with a global signature of polygenic adaptation, we found that compared to non-associated SNPs, frequencies of height-associated SNPs are indeed significantly more differentiated among continental populations from both the 1000 Genomes Project (p = 0.0012 for UKB and p = 0.0265 for BBJ), and the Human Genome Diversity Project (p = 0.0225 for UKB and p = 0.0032 for BBJ). However, we found no significant difference among continental populations in polygenic height scores. Through simulations, we found that polygenic score-based statistics could lose power in detecting polygenic adaptation in presence of independent converging selections, thereby potentially explaining the inconsistent results based on FST and polygenic scores.
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19
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Saitou M, Resendez S, Pradhan AJ, Wu F, Lie NC, Hall NJ, Zhu Q, Reinholdt L, Satta Y, Speidel L, Nakagome S, Hanchard NA, Churchill G, Lee C, Atilla-Gokcumen GE, Mu X, Gokcumen O. Sex-specific phenotypic effects and evolutionary history of an ancient polymorphic deletion of the human growth hormone receptor. SCIENCE ADVANCES 2021; 7:eabi4476. [PMID: 34559564 PMCID: PMC8462886 DOI: 10.1126/sciadv.abi4476] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Accepted: 08/04/2021] [Indexed: 06/13/2023]
Abstract
The common deletion of the third exon of the growth hormone receptor gene (GHRd3) in humans is associated with birth weight, growth after birth, and time of puberty. However, its evolutionary history and the molecular mechanisms through which it affects phenotypes remain unresolved. We present evidence that this deletion was nearly fixed in the ancestral population of anatomically modern humans and Neanderthals but underwent a recent adaptive reduction in frequency in East Asia. We documented that GHRd3 is associated with protection from severe malnutrition. Using a novel mouse model, we found that, under calorie restriction, Ghrd3 leads to the female-like gene expression in male livers and the disappearance of sexual dimorphism in weight. The sex- and diet-dependent effects of GHRd3 in our mouse model are consistent with a model in which the allele frequency of GHRd3 varies throughout human evolution as a response to fluctuations in resource availability.
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Affiliation(s)
- Marie Saitou
- Department of Biological Sciences, University at Buffalo, Buffalo, NY, USA
| | - Skyler Resendez
- Department of Biological Sciences, University at Buffalo, Buffalo, NY, USA
| | | | - Fuguo Wu
- Department of Ophthalmology, Ross Eye Institute, Jacobs School of Medicine and Biological Sciences, University at Buffalo, Buffalo, NY, USA
| | - Natasha C. Lie
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Nancy J. Hall
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Qihui Zhu
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | | | - Yoko Satta
- Department of Evolutionary Studies of Biosystems, SOKENDAI (Graduate University for Advanced Studies), Kanagawa Prefecture, Japan
| | - Leo Speidel
- University College London, Genetics Institute, London, UK
- The Francis Crick Institute, London, UK
| | | | - Neil A. Hanchard
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | | | - Charles Lee
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
- Precision Medicine Center, The First Affiliated Hospital of Xi’an Jiaotong University, Shaanxi, People’s Republic of China
| | | | - Xiuqian Mu
- Department of Ophthalmology, Ross Eye Institute, Jacobs School of Medicine and Biological Sciences, University at Buffalo, Buffalo, NY, USA
| | - Omer Gokcumen
- Department of Biological Sciences, University at Buffalo, Buffalo, NY, USA
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20
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Mittal M, Gupta P, Kalra S, Bantwal G, Garg MK. Short Stature: Understanding the Stature of Ethnicity in Height Determination. Indian J Endocrinol Metab 2021; 25:381-388. [PMID: 35300450 PMCID: PMC8923322 DOI: 10.4103/ijem.ijem_197_21] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/08/2021] [Revised: 07/18/2021] [Accepted: 10/20/2021] [Indexed: 02/02/2023] Open
Abstract
Height is a polygenic trait with a high degree of heritability. Most (95%) children with short stature (defined as height below the third percentile) and poor growth (growth velocity <5 cm/year) do not have an endocrine disorder. The genetic basis for stature potential has been evaluated in recent years and is increasingly being recognized as a major basis for variation in height between different ethnic populations. Numerous genome-wide association studies have identified hundreds of loci linked to human growth. Apart from the genetic factors, various environmental, nutritional, hormonal, and socioeconomic factors also influence the height, and stature of individuals varies between different geographical locations and ethnic groups. Ethnically different populations might respond differently to the same environmental factors and thus the final height in different ethnic groups is different. This review covers in detail the short stature of African Pygmies and Andamanese Islanders along with the possible causative factors responsible for the variation in height in these ethnic groups.
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Affiliation(s)
- Madhukar Mittal
- Department of Endocrinology and Metabolism, All India Institute of Medical Sciences, Jodhpur, Rajasthan, India
| | - Parul Gupta
- Department of Endocrinology and Metabolism, All India Institute of Medical Sciences, Jodhpur, Rajasthan, India
| | - Sanjay Kalra
- Department of Endocrinology, Bharti Hospital and BRIDE, Karnal, Haryana, India
| | - Ganapathi Bantwal
- Department of Endocrinology, St. John's Medical College Hospital, Bengaluru, Karnataka, India
| | - Mahendra K Garg
- Department of Endocrinology and Metabolism, All India Institute of Medical Sciences, Jodhpur, Rajasthan, India
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21
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Irving-Pease EK, Muktupavela R, Dannemann M, Racimo F. Quantitative Human Paleogenetics: What can Ancient DNA Tell us About Complex Trait Evolution? Front Genet 2021; 12:703541. [PMID: 34422004 PMCID: PMC8371751 DOI: 10.3389/fgene.2021.703541] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Accepted: 07/08/2021] [Indexed: 12/13/2022] Open
Abstract
Genetic association data from national biobanks and large-scale association studies have provided new prospects for understanding the genetic evolution of complex traits and diseases in humans. In turn, genomes from ancient human archaeological remains are now easier than ever to obtain, and provide a direct window into changes in frequencies of trait-associated alleles in the past. This has generated a new wave of studies aiming to analyse the genetic component of traits in historic and prehistoric times using ancient DNA, and to determine whether any such traits were subject to natural selection. In humans, however, issues about the portability and robustness of complex trait inference across different populations are particularly concerning when predictions are extended to individuals that died thousands of years ago, and for which little, if any, phenotypic validation is possible. In this review, we discuss the advantages of incorporating ancient genomes into studies of trait-associated variants, the need for models that can better accommodate ancient genomes into quantitative genetic frameworks, and the existing limits to inferences about complex trait evolution, particularly with respect to past populations.
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Affiliation(s)
- Evan K. Irving-Pease
- Lundbeck Foundation GeoGenetics Centre, GLOBE Institute, University of Copenhagen, Copenhagen, Denmark
| | - Rasa Muktupavela
- Lundbeck Foundation GeoGenetics Centre, GLOBE Institute, University of Copenhagen, Copenhagen, Denmark
| | - Michael Dannemann
- Center for Genomics, Evolution and Medicine, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Fernando Racimo
- Lundbeck Foundation GeoGenetics Centre, GLOBE Institute, University of Copenhagen, Copenhagen, Denmark
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22
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Kim HI, Ye B, Staples J, Marcketta A, Gao C, Shuldiner AR, Van Hout CV. Genome-wide survey of parent-of-origin-specific associations across clinical traits derived from electronic health records. HGG ADVANCES 2021; 2:100039. [PMID: 35047837 PMCID: PMC8756508 DOI: 10.1016/j.xhgg.2021.100039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Accepted: 05/31/2021] [Indexed: 11/03/2022] Open
Abstract
Parent-of-origin (PoO) effects refer to the differential phenotypic impacts of genetic variants dependent on their parental inheritance due to imprinting. While PoO effects can influence complex traits, they may be poorly captured by models that do not differentiate the parental origin of the variant. The aim of this study was to conduct a genome-wide screen for PoO effects on a broad range of clinical traits derived from electronic health records (EHR) in the DiscovEHR study enriched with familial relationships. Using pairwise kinship estimates from genetic data and demographic data, we identified 22,051 offspring among 134,049 individuals in the DiscovEHR study. PoO of ~9 million variants was assigned in the offspring by comparing offspring and parental genotypes and haplotypes. We then performed genome-wide PoO association analyses across 154 quantitative and 611 binary traits extracted from EHR. Of the 732 significant PoO associations identified (p < 5 × 10-8), we attempted to replicate 274 PoO associations in the UK Biobank study with 5,015 offspring and replicated 9 PoO associations (p < 0.05). In summary, our study implements a bioinformatic and statistical approach to examine PoO effects genome-wide in a large population study enriched with familial relationships and systematically characterizes PoO effects on hundreds of clinical traits derived from EHR. Our results suggest that, while the statistical power to detect PoO effects remains modest yet, accurately modeling PoO effects has the potential to find new associations that may have been missed by the standard additive model, further enhancing the mechanistic understanding of genetic influence on complex traits.
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Affiliation(s)
- Hye In Kim
- Regeneron Genetics Center, Tarrytown, NY 10591, USA
| | - Bin Ye
- Regeneron Genetics Center, Tarrytown, NY 10591, USA
| | | | | | - Chuan Gao
- Regeneron Genetics Center, Tarrytown, NY 10591, USA
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23
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Heilbron K, Mozaffari SV, Vacic V, Yue P, Wang W, Shi J, Jubb AM, Pitts SJ, Wang X. Advancing drug discovery using the power of the human genome. J Pathol 2021; 254:418-429. [PMID: 33748968 PMCID: PMC8251523 DOI: 10.1002/path.5664] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2020] [Revised: 03/11/2021] [Accepted: 03/16/2021] [Indexed: 12/31/2022]
Abstract
Human genetics plays an increasingly important role in drug development and population health. Here we review the history of human genetics in the context of accelerating the discovery of therapies, present examples of how human genetics evidence supports successful drug targets, and discuss how polygenic risk scores could be beneficial in various clinical settings. We highlight the value of direct-to-consumer platforms in the era of fast-paced big data biotechnology, and how diverse genetic and health data can benefit society. © 2021 23andMe, Inc. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.
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Geographic variation in the polygenic score of height in Japan. Hum Genet 2021; 140:1097-1108. [PMID: 33900438 DOI: 10.1007/s00439-021-02281-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Accepted: 04/12/2021] [Indexed: 10/21/2022]
Abstract
A geographical gradient of height has existed in Japan for approximately 100 years. People in northern Japan tend to be taller than those in southern Japan. The differences in annual temperature and day length between the northern and southern prefectures of Japan have been suggested as possible causes of the height gradient. Although height is well known to be a polygenic trait with high heritability, the genetic contributions to the gradient have not yet been explored. Polygenic score (PS) is calculated by aggregating the effects of genetic variants identified by genome-wide association studies (GWASs) to predict the traits of individual subjects. Here, we calculated the PS of height for 10,840 Japanese individuals from all 47 prefectures in Japan. The median height PS for each prefecture was significantly correlated with the mean height of females and males obtained from another independent Japanese nation-wide height dataset, suggesting genetic contribution to the observed height gradient. We also found that individuals and prefectures genetically closer to continental East Asian ancestry tended to have a higher PS; modern Japanese people are considered to have originated as result of admixture between indigenous Jomon people and immigrants from continental East Asia. Another PS analysis based on the GWAS using only the mainland Japanese was conducted to evaluate the effect of population stratification on PS. The result also supported genetic contribution to height, and indicated that the PS might be affected by a bias due to population stratification even in a relatively homogenous population like Japanese.
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Abstract
Canalization refers to the evolution of populations such that the number of individuals who deviate from the optimum trait, or experience disease, is minimized. In the presence of rapid cultural, environmental, or genetic change, the reverse process of decanalization may contribute to observed increases in disease prevalence. This review starts by defining relevant concepts, drawing distinctions between the canalization of populations and robustness of individuals. It then considers evidence pertaining to three continuous traits and six domains of disease. In each case, existing genetic evidence for genotype-by-environment interactions is insufficient to support a strong inference of decanalization, but we argue that the advent of genome-wide polygenic risk assessment now makes an empirical evaluation of the role of canalization in preventing disease possible. Finally, the contributions of both rare and common variants to congenital abnormality and adult onset disease are considered in light of a new kerplunk model of genetic effects.
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Affiliation(s)
- Greg Gibson
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia 30332, USA;
| | - Kristine A Lacek
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia 30332, USA;
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26
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Chen M, Sidore C, Akiyama M, Ishigaki K, Kamatani Y, Schlessinger D, Cucca F, Okada Y, Chiang CWK. Evidence of Polygenic Adaptation in Sardinia at Height-Associated Loci Ascertained from the Biobank Japan. Am J Hum Genet 2020; 107:60-71. [PMID: 32533944 PMCID: PMC7332648 DOI: 10.1016/j.ajhg.2020.05.014] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2019] [Accepted: 05/19/2020] [Indexed: 01/31/2023] Open
Abstract
Adult height is one of the earliest putative examples of polygenic adaptation in humans. However, this conclusion was recently challenged because residual uncorrected stratification from large-scale consortium studies was considered responsible for the previously noted genetic difference. It thus remains an open question whether height loci exhibit signals of polygenic adaptation in any human population. We re-examined this question, focusing on one of the shortest European populations, the Sardinians, in addition to mainland European populations. We utilized height-associated loci from the Biobank Japan (BBJ) dataset to further alleviate concerns of biased ascertainment of GWAS loci and showed that the Sardinians remain significantly shorter than expected under neutrality (∼0.22 standard deviation shorter than Utah residents with ancestry from northern and western Europe [CEU] on the basis of polygenic height scores, p = 3.89 × 10-4). We also found the trajectory of polygenic height scores between the Sardinian and the British populations diverged over at least the last 10,000 years (p = 0.0082), consistent with a signature of polygenic adaptation driven primarily by the Sardinian population. Although the polygenic score-based analysis showed a much subtler signature in mainland European populations, we found a clear and robust adaptive signature in the UK population by using a haplotype-based statistic, the trait singleton density score (tSDS), driven by the height-increasing alleles (p = 9.1 × 10-4). In summary, by ascertaining height loci in a distant East Asian population, we further supported the evidence of polygenic adaptation at height-associated loci among the Sardinians. In mainland Europeans, the adaptive signature was detected in haplotype-based analysis but not in polygenic score-based analysis.
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Affiliation(s)
- Minhui Chen
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA.
| | - Carlo Sidore
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche, Monserrato 09042, Cagliari, Italy
| | - Masato Akiyama
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan; Department of Ocular Pathology and Imaging Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, Japan
| | - Kazuyoshi Ishigaki
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan
| | - Yoichiro Kamatani
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan; Kyoto-McGill International Collaborative School in Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto 606-8501, Japan
| | - David Schlessinger
- Laboratory of Genetics and Genomics, National Institute on Aging, US National Institutes of Health, Baltimore, MD 21224, USA
| | - Francesco Cucca
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche, Monserrato 09042, Cagliari, Italy
| | - Yukinori Okada
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan; Department of Statistical Genetics, Osaka University Graduate School of Medicine, Osaka 565-0871, Japan
| | - Charleston W K Chiang
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA; Quantitative and Computational Biology Section, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA.
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27
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Lin YJ, Cheng CF, Wang CH, Liang WM, Tang CH, Tsai LP, Chen CH, Wu JY, Hsieh AR, Lee MTM, Lin TH, Liao CC, Huang SM, Zhang Y, Tsai CH, Tsai FJ. Genetic Architecture Associated With Familial Short Stature. J Clin Endocrinol Metab 2020; 105:5805154. [PMID: 32170311 DOI: 10.1210/clinem/dgaa131] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/09/2019] [Accepted: 03/10/2020] [Indexed: 12/21/2022]
Abstract
CONTEXT Human height is an inheritable, polygenic trait under complex and multilocus genetic regulation. Familial short stature (FSS; also called genetic short stature) is the most common type of short stature and is insufficiently known. OBJECTIVE To investigate the FSS genetic profile and develop a polygenic risk predisposition score for FSS risk prediction. DESIGN AND SETTING The FSS participant group of Han Chinese ancestry was diagnosed by pediatric endocrinologists in Taiwan. PATIENTS AND INTERVENTIONS The genetic profiles of 1163 participants with FSS were identified by using a bootstrapping subsampling and genome-wide association studies (GWAS) method. MAIN OUTCOME MEASURES Genetic profile, polygenic risk predisposition score for risk prediction. RESULTS Ten novel genetic single nucleotide polymorphisms (SNPs) and 9 reported GWAS human height-related SNPs were identified for FSS risk. These 10 novel SNPs served as a polygenic risk predisposition score for FSS risk prediction (area under the curve: 0.940 in the testing group). This FSS polygenic risk predisposition score was also associated with the height reduction regression tendency in the general population. CONCLUSION A polygenic risk predisposition score composed of 10 genetic SNPs is useful for FSS risk prediction and the height reduction tendency. Thus, it might contribute to FSS risk in the Han Chinese population from Taiwan.
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Affiliation(s)
- Ying-Ju Lin
- Genetic Center, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan
- School of Chinese Medicine, China Medical University, Taichung, Taiwan
| | - Chi-Fung Cheng
- Genetic Center, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan
- Department of Health Services Administration, China Medical University, Taichung, Taiwan
| | - Chung-Hsing Wang
- Children's Hospital of China Medical University, Taichung, Taiwan
| | - Wen-Miin Liang
- Department of Health Services Administration, China Medical University, Taichung, Taiwan
| | - Chih-Hsin Tang
- Graduate Institute of Biomedical Sciences, China Medical University, Taichung, Taiwan
| | - Li-Ping Tsai
- Department of Pediatrics, Taipei Tzu Chi Hospital, New Taipei City, Taiwan
| | - Chien-Hsiun Chen
- School of Chinese Medicine, China Medical University, Taichung, Taiwan
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - Jer-Yuarn Wu
- School of Chinese Medicine, China Medical University, Taichung, Taiwan
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - Ai-Ru Hsieh
- Department of Statistics, Tamkang University, New Taipei City, Taiwan
| | | | - Ting-Hsu Lin
- Genetic Center, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan
| | - Chiu-Chu Liao
- Genetic Center, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan
| | - Shao-Mei Huang
- Genetic Center, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan
| | - Yanfei Zhang
- Genomic Medicine Institute, Geisinger, Danville, Pennsylvania, USA
| | - Chang-Hai Tsai
- Department of Biotechnology and Bioinformatics, Asia University, Taichung, Taiwan
| | - Fuu-Jen Tsai
- Genetic Center, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan
- School of Chinese Medicine, China Medical University, Taichung, Taiwan
- Children's Hospital of China Medical University, Taichung, Taiwan
- Department of Biotechnology and Bioinformatics, Asia University, Taichung, Taiwan
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28
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McQuillan MA, Zhang C, Tishkoff SA, Platt A. The importance of including ethnically diverse populations in studies of quantitative trait evolution. Curr Opin Genet Dev 2020; 62:30-35. [PMID: 32604012 PMCID: PMC7942184 DOI: 10.1016/j.gde.2020.05.037] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2020] [Revised: 05/26/2020] [Accepted: 05/28/2020] [Indexed: 10/24/2022]
Abstract
For many traits, human variation is less a matter of categorical differences than quantitative variation, such as height, where individuals fall along a continuum from short to tall. Most recent studies utilize large population-based samples with whole-genome sequences to study the evolution of these traits and have made significant progress implementing a broad spectrum of techniques. However, relatively few studies of quantitative trait evolution include ethnically diverse populations, which often harbor the highest levels of genetic and phenotypic diversity. Thus, our ability to draw inferences about quantitative trait adaptation has been limited. Here, we review recent studies examining human quantitative trait adaptation, and argue that including ethnically diverse populations, particularly from Africa, will be especially informative for our understanding of how humans adapt to the world around them.
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Affiliation(s)
- Michael A McQuillan
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Chao Zhang
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Sarah A Tishkoff
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Biology, School of Arts and Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA.
| | - Alexander Platt
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
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29
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A positively selected FBN1 missense variant reduces height in Peruvian individuals. Nature 2020; 582:234-239. [PMID: 32499652 PMCID: PMC7410362 DOI: 10.1038/s41586-020-2302-0] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2019] [Accepted: 03/10/2020] [Indexed: 01/21/2023]
Abstract
On average, Peruvian individuals are among the shortest in the world1. Here we show that Native American ancestry is associated with reduced height in an ethnically diverse group of Peruvian individuals, and identify a population-specific, missense variant in the FBN1 gene (E1297G) that is significantly associated with lower height. Each copy of the minor allele (frequency of 4.7%) reduces height by 2.2 cm (4.4 cm in homozygous individuals). To our knowledge, this is the largest effect size known for a common height-associated variant. FBN1 encodes the extracellular matrix protein fibrillin 1, which is a major structural component of microfibrils. We observed less densely packed fibrillin-1-rich microfibrils with irregular edges in the skin of individuals who were homozygous for G1297 compared with individuals who were homozygous for E1297. Moreover, we show that the E1297G locus is under positive selection in non-African populations, and that the E1297 variant shows subtle evidence of positive selection specifically within the Peruvian population. This variant is also significantly more frequent in coastal Peruvian populations than in populations from the Andes or the Amazon, which suggests that short stature might be the result of adaptation to factors that are associated with the coastal environment in Peru.
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30
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Granot-Hershkovitz E, Wu P, Karasik D, Peter I, Peloso GM, Levy D, Vasan RS, Adrienne Cupples L, Liu CT, Meigs JB, Siscovick DS, Dupuis J, Friedlander Y, Hochner H. Searching for parent-of-origin effects on cardiometabolic traits in imprinted genomic regions. Eur J Hum Genet 2020; 28:646-655. [PMID: 31896779 PMCID: PMC7170899 DOI: 10.1038/s41431-019-0568-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2019] [Revised: 12/12/2019] [Accepted: 12/17/2019] [Indexed: 11/08/2022] Open
Abstract
Cardiometabolic traits pose a major global public health burden. Large-scale genome-wide association studies (GWAS) have identified multiple loci accounting for up to 30% of the genetic variance in complex traits such as cardiometabolic traits. However, the contribution of parent-of-origin effects (POEs) to complex traits has been largely ignored in GWAS. Family-based studies enable the assessment of POEs in genetic association analyses. We investigated POEs on a range of complex traits in 3 family-based studies. The discovery phase was carried out in large pedigrees from the Kibbutzim Family Study (n = 901 individuals) and in 872 parent-offspring trios from the Jerusalem Perinatal Study. Focusing on imprinted genomic regions, we examined parent-specific associations with 12 complex traits (i.e., body-size, blood pressure, lipids), mostly cardiometabolic risk traits. Forty five of the 11,967 SNPs initially found to have POE were evaluated for replication (p value < 1 × 10-4) in Framingham Heart Study families (max n = 8000 individuals). Three common variants yielded evidence of POE in the meta-analysis. Two variants, located on chr6 in the HLA region, showed a paternal effect on height (rs1042136: βpaternal = -0.023, p value = 1.5 × 10-8 and rs1431403: βpaternal = -0.011, p value = 5.4 × 10-6). The corresponding maternally-derived effects were statistically nonsignificant. The variant rs9332053, located on chr13 in RCBTB2 gene, demonstrated a maternal effect on hip circumference (βmaternal = -4.24, p value = 9.6 × 10-6; βpaternal = 1.29, p value = 0.23). These findings provide evidence for the utility of incorporating POEs into association studies of cardiometabolic traits, especially anthropometric traits. The study highlights the benefits of using family-based data for deciphering the genetic architecture of complex traits.
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Affiliation(s)
| | - Peitao Wu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA
| | - David Karasik
- Azrieli Faculty of Medicine, Bar-Ilan University, Safed, Israel
| | - Inga Peter
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Gina M Peloso
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA
| | - Daniel Levy
- Boston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, 01702, USA
- The Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, NIH, Bethesda, MD, USA
| | - Ramachandran S Vasan
- Boston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, 01702, USA
- Sections of Preventive medicine and Epidemiology, and cardiovascular medicine, Departments of Medicine and Epidemiology, Boston University Schools of Medicine and Public health, Boston, MA, 02118, USA
| | - L Adrienne Cupples
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA
- Boston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, 01702, USA
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA
| | - James B Meigs
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - David S Siscovick
- Institute for Urban Health, New York Academy of Medicine, New York, NY, USA
| | - Josée Dupuis
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA
- Boston University's and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, 01702, USA
| | - Yechiel Friedlander
- Braun School of Public Health, The Hebrew University of Jerusalem, 99112102, Jerusalem, Israel
| | - Hagit Hochner
- Braun School of Public Health, The Hebrew University of Jerusalem, 99112102, Jerusalem, Israel.
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31
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Hejase HA, Dukler N, Siepel A. From Summary Statistics to Gene Trees: Methods for Inferring Positive Selection. Trends Genet 2020; 36:243-258. [PMID: 31954511 PMCID: PMC7177178 DOI: 10.1016/j.tig.2019.12.008] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2019] [Revised: 11/15/2019] [Accepted: 12/11/2019] [Indexed: 01/01/2023]
Abstract
Methods to detect signals of natural selection from genomic data have traditionally emphasized the use of simple summary statistics. Here, we review a new generation of methods that consider combinations of conventional summary statistics and/or richer features derived from inferred gene trees and ancestral recombination graphs (ARGs). We also review recent advances in methods for population genetic simulation and ARG reconstruction. Finally, we describe opportunities for future work on a variety of related topics, including the genetics of speciation, estimation of selection coefficients, and inference of selection on polygenic traits. Together, these emerging methods offer promising new directions in the study of natural selection.
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Affiliation(s)
- Hussein A Hejase
- Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA.
| | - Noah Dukler
- Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Adam Siepel
- Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
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32
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Floris M, Sanna D, Castiglia P, Putzu C, Sanna V, Pazzola A, De Miglio MR, Sanges F, Pira G, Azara A, Lampis E, Serra A, Carru C, Steri M, Costanza F, Bisail M, Muroni MR. MTHFR, XRCC1 and OGG1 genetic polymorphisms in breast cancer: a case-control study in a population from North Sardinia. BMC Cancer 2020; 20:234. [PMID: 32192442 PMCID: PMC7083022 DOI: 10.1186/s12885-020-06749-w] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2020] [Accepted: 03/12/2020] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Despite conflicting results, considerable evidence suggests the association between single nucleotide polymorphisms in MTHFR, XRCC1 and OGG1 genes and, risk of developing breast cancer. Here a case-control study is reported, including 135 breat cancer patients and 112 healthy women, all representative of Northern Sardinian population. METHODS Polymerase chain reaction/restriction fragment length polymorphism method was used to determine the genotypes of five polymorphisms: MTHFR C677T (rs1801133) and A1298C (rs1801131), XRCC1 Arg194Trp (rs1799782) and Arg399Gln (rs25487) and OGG1 Ser326Cys (rs1052133). Allelic, genotypic and haplotype association analyses with disease risk and clinicopathological parameters were performed. RESULTS A nominally significant association with breast cancer risk was observed for MTHFR C677T polymorphism heterozygous genotype in the codominant model (OR: 0.57, 95% CI: 0.32-1.00, p = 0.049) and for Cys/Cys genotype of the OGG1 Ser326Cys polymorphism in the recessive model (OR: 0.23, 95% CI: 0.05-1.11, p = 0.0465). No significant differences were found at genotype-level for A1298C polymorphism of the MTHFR gene and Arg194Trp and Arg399Gln of the XRCC1 gene. Furthermore, the OGG1 and XRCC1 rs25487 polymorphisms were nominally associated with PgR, Her2 status and with sporadic breast cancer, respectively. CONCLUSIONS Based on genetic characteristics of individuals included in this study, results suggest that MTHFR CT and OGG1 Cys/Cys genotypes have a protective effect that may have an influence on breast cancer risk in a representative Northern Sardinian population.
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Affiliation(s)
- Matteo Floris
- Department of Biomedical Sciences, University of Sassari, Sassari, Italy.
| | - Daria Sanna
- Department of Biomedical Sciences, University of Sassari, Sassari, Italy
| | - Paolo Castiglia
- Department of Medical, Surgical and Experimental Sciences, University of Sassari, Sassari, Italy
| | - Carlo Putzu
- Division of Medical Oncology, AOU Sassari, Sassari, Italy
| | - Valeria Sanna
- Division of Medical Oncology, AOU Sassari, Sassari, Italy
| | | | - Maria Rosaria De Miglio
- Department of Medical, Surgical and Experimental Sciences, University of Sassari, Sassari, Italy
| | - Francesca Sanges
- Department of Biomedical Sciences, University of Sassari, Sassari, Italy
| | - Giovanna Pira
- Department of Biomedical Sciences, University of Sassari, Sassari, Italy
| | - Antonio Azara
- Department of Medical, Surgical and Experimental Sciences, University of Sassari, Sassari, Italy
| | - Emanuele Lampis
- Department of Medical, Surgical and Experimental Sciences, University of Sassari, Sassari, Italy
| | | | - Ciriaco Carru
- Department of Biomedical Sciences, University of Sassari, Sassari, Italy
| | - Maristella Steri
- Institute for Genetic and Biomedical Research, National Research Council (CNR), Monserrato, Cagliari, Italy
| | - Flavia Costanza
- Department of Biomedical Sciences, University of Sassari, Sassari, Italy
| | | | - Maria Rosaria Muroni
- Department of Medical, Surgical and Experimental Sciences, University of Sassari, Sassari, Italy.
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33
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Abstract
PURPOSE OF REVIEW The goal of the review is to provide a comprehensive overview of the current understanding of the mechanisms underlying variation in human stature. RECENT FINDINGS Human height is an anthropometric trait that varies considerably within human populations as well as across the globe. Historically, much research focus was placed on understanding the biology of growth plate chondrocytes and how modifications to core chondrocyte proliferation and differentiation pathways potentially shaped height attainment in normal as well as pathological contexts. Recently, much progress has been made to improve our understanding regarding the mechanisms underlying the normal and pathological range of height variation within as well as between human populations, and today, it is understood to reflect complex interactions among a myriad of genetic, environmental, and evolutionary factors. Indeed, recent improvements in genetics (e.g., GWAS) and breakthroughs in functional genomics (e.g., whole exome sequencing, DNA methylation analysis, ATAC-sequencing, and CRISPR) have shed light on previously unknown pathways/mechanisms governing pathological and common height variation. Additionally, the use of an evolutionary perspective has also revealed important mechanisms that have shaped height variation across the planet. This review provides an overview of the current knowledge of the biological mechanisms underlying height variation by highlighting new research findings on skeletal growth control with an emphasis on previously unknown pathways/mechanisms influencing pathological and common height variation. In this context, this review also discusses how evolutionary forces likely shaped the genomic architecture of height across the globe.
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Affiliation(s)
| | - Terence D Capellini
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, USA.
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
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34
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Akiyama M, Ishigaki K, Sakaue S, Momozawa Y, Horikoshi M, Hirata M, Matsuda K, Ikegawa S, Takahashi A, Kanai M, Suzuki S, Matsui D, Naito M, Yamaji T, Iwasaki M, Sawada N, Tanno K, Sasaki M, Hozawa A, Minegishi N, Wakai K, Tsugane S, Shimizu A, Yamamoto M, Okada Y, Murakami Y, Kubo M, Kamatani Y. Characterizing rare and low-frequency height-associated variants in the Japanese population. Nat Commun 2019; 10:4393. [PMID: 31562340 PMCID: PMC6764965 DOI: 10.1038/s41467-019-12276-5] [Citation(s) in RCA: 101] [Impact Index Per Article: 20.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2018] [Accepted: 08/27/2019] [Indexed: 12/29/2022] Open
Abstract
Human height is a representative phenotype to elucidate genetic architecture. However, the majority of large studies have been performed in European population. To investigate the rare and low-frequency variants associated with height, we construct a reference panel (N = 3,541) for genotype imputation by integrating the whole-genome sequence data from 1,037 Japanese with that of the 1000 Genomes Project, and perform a genome-wide association study in 191,787 Japanese. We report 573 height-associated variants, including 22 rare and 42 low-frequency variants. These 64 variants explain 1.7% of the phenotypic variance. Furthermore, a gene-based analysis identifies two genes with multiple height-increasing rare and low-frequency nonsynonymous variants (SLC27A3 and CYP26B1; PSKAT-O < 2.5 × 10−6). Our analysis shows a general tendency of the effect sizes of rare variants towards increasing height, which is contrary to findings among Europeans, suggesting that height-associated rare variants are under different selection pressure in Japanese and European populations. Thousands of genetic loci are known to associate with human height, but these are mainly based on studies in European ancestry populations. Here, Akiyama et al. construct a genotype reference panel for the Japanese population followed by GWAS and report 573 height associated variants in 191,787 Japanese.
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Affiliation(s)
- Masato Akiyama
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan.,Department of Ophthalmology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, 812-8582, Japan.,Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan
| | - Kazuyoshi Ishigaki
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan
| | - Saori Sakaue
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan.,Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Tokyo, 113-8655, Japan
| | - Yukihide Momozawa
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan
| | - Momoko Horikoshi
- Laboratory for Endocrinology, Metabolism and Kidney Diseases, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan
| | - Makoto Hirata
- Laboratory of Genome Technology, Human Genome Center, Institute of Medical Science, The University of Tokyo, Tokyo, 108-8639, Japan
| | - Koichi Matsuda
- Laboratory of Clinical Genome Sequencing, Department of Computational Biology and Medical Sciences, Graduate school of Frontier Sciences, The University of Tokyo, Tokyo, 108-8639, Japan
| | - Shiro Ikegawa
- Laboratory for Bone and Joint Diseases, RIKEN Center for Integrative Medical Sciences, Tokyo, 108-8639, Japan
| | - Atsushi Takahashi
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan.,Department of Genomic Medicine, Research Institute, National Cerebral and Cardiovascular Center, Osaka, 565-8565, Japan
| | - Masahiro Kanai
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan.,Department of Biomedical Informatics, Harvard Medical School, Boston, MA02115, USA
| | - Sadao Suzuki
- Nagoya City University Graduate School of Medical Sciences, Nagoya, 467-8601, Japan
| | - Daisuke Matsui
- Department of Epidemiology for Community Health and Medicine, Kyoto Prefectural University of Medicine, Graduate School of Medical Science, Kyoto, 602-8566, Japan
| | - Mariko Naito
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, 466-8550, Japan.,Department of Oral Epidemiology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, 734-8553, Japan
| | - Taiki Yamaji
- Division of Epidemiology, Center for Public Health Sciences, National Cancer Center, Tokyo, 104-0045, Japan
| | - Motoki Iwasaki
- Division of Epidemiology, Center for Public Health Sciences, National Cancer Center, Tokyo, 104-0045, Japan
| | - Norie Sawada
- Division of Epidemiology, Center for Public Health Sciences, National Cancer Center, Tokyo, 104-0045, Japan
| | - Kozo Tanno
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Iwate, 028-3694, Japan.,Department of Hygiene and Preventive Medicine, School of Medicine, Iwate Medical University, Iwate, 028-3694, Japan
| | - Makoto Sasaki
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Iwate, 028-3694, Japan
| | - Atsushi Hozawa
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, 980-8573, Japan.,Graduate School of Medicine, Tohoku University, Sendai, 980-8575, Japan
| | - Naoko Minegishi
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, 980-8573, Japan.,Graduate School of Medicine, Tohoku University, Sendai, 980-8575, Japan
| | - Kenji Wakai
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, 466-8550, Japan
| | - Shoichiro Tsugane
- Center for Public Health Sciences, National Cancer Center, Tokyo, 104-0045, Japan
| | - Atsushi Shimizu
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Iwate, 028-3694, Japan
| | - Masayuki Yamamoto
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, 980-8573, Japan.,Graduate School of Medicine, Tohoku University, Sendai, 980-8575, Japan
| | - Yukinori Okada
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan.,Department of Statistical Genetics, Osaka University Graduate School of Medicine, Osaka, 565-0871, Japan.,Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Osaka, 565-0871, Japan
| | - Yoshinori Murakami
- Division of Molecular Pathology, The Institute of Medical Science, The University of Tokyo, Tokyo, 108-8639, Japan
| | - Michiaki Kubo
- RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan
| | - Yoichiro Kamatani
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan. .,Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan. .,Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, 108-8639, Japan.
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35
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Kalstø SM, Siland JE, Rienstra M, Christophersen IE. Atrial Fibrillation Genetics Update: Toward Clinical Implementation. Front Cardiovasc Med 2019; 6:127. [PMID: 31552271 PMCID: PMC6743416 DOI: 10.3389/fcvm.2019.00127] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2019] [Accepted: 08/12/2019] [Indexed: 12/16/2022] Open
Abstract
Atrial fibrillation (AF) is the most common heart rhythm disorder worldwide and may have serious cardiovascular health consequences. AF is associated with increased risk of stroke, dementia, heart failure, and death. There are several known robust, clinical risk predictors for AF, such as male sex, increasing age, and hypertension; however, during the last couple of decades, a substantive genetic component has also been established. Over the last 10 years, the discovery of novel AF-related genetic variants has accelerated, increasing our understanding of mechanisms behind AF. Current studies are focusing on mapping the polygenic structure of AF, improving risk prediction, therapeutic development, and patient-specific management. Nevertheless, it is still difficult for clinicians to interpret the role of genetics in AF prediction and management. Here, we provide an overview of relevant topics within the genetics of AF and attempt to provide some guidance on how to interpret genetic advances and their implementation into clinical decision-making.
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Affiliation(s)
- Silje Madeleine Kalstø
- Department of Medical Research, Bærum Hospital, Vestre Viken Hospital Trust, Rud, Norway
| | - Joylene Elisabeth Siland
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Michiel Rienstra
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Ingrid E Christophersen
- Department of Medical Research, Bærum Hospital, Vestre Viken Hospital Trust, Rud, Norway.,The Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
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36
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Analysis of the genetic basis of height in large Jewish nuclear families. PLoS Genet 2019; 15:e1008082. [PMID: 31283753 PMCID: PMC6638967 DOI: 10.1371/journal.pgen.1008082] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2018] [Revised: 07/18/2019] [Accepted: 03/11/2019] [Indexed: 12/26/2022] Open
Abstract
Despite intensive study, most of the specific genetic factors that contribute to variation in human height remain undiscovered. We conducted a family-based linkage study of height in a unique cohort of very large nuclear families from a founder (Jewish) population. This design allowed for increased power to detect linkage, compared to previous family-based studies. Loci we identified in discovery families could explain an estimated lower bound of 6% of the variance in height in validation families. We showed that these loci are not tagging known common variants associated with height. Rather, we suggest that the observed signals arise from variants with large effects that are rare globally but elevated in frequency in the Jewish population. Rare variants with large effects have been suggested to account for some of the missing heritability of height, but detection of such variants in genome-wide association studies (GWAS) requires very large sample sizes due to their low frequencies. Here, we designed a unique study of height, in which we sought to increase the effective frequency of rare variants in our sample. This was done by assembling a cohort of very large nuclear families, with an average of 12 and a maximum of 20 siblings per nuclear family. In this design, any variant segregating in our cohort has a minimum expected frequency of ~1%, regardless of its frequency in the general population. In addition, we recruited all participants from a founder (Jewish) population, in which some variants that are rare in a cosmopolitan population can rise to high frequencies. To further increase power, we developed methods to obtain highly accurate height measurements, genotype calls, and inheritance pattern reconstructions. These factors allowed us to detect many more QTLs than previous family-based studies of height, despite a modest sample size of only 397 participants. The approach described in this paper provides insights into the genetic basis of height and the roles of population-specific vs. cosmopolitan variants, and may serve as a complement to GWAS for genetic investigations of other complex traits.
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37
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Keith RA, Mitchell-Olds T. Antagonistic selection and pleiotropy constrain the evolution of plant chemical defenses. Evolution 2019; 73:947-960. [PMID: 30950034 PMCID: PMC6652176 DOI: 10.1111/evo.13728] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2018] [Accepted: 03/13/2019] [Indexed: 01/24/2023]
Abstract
When pleiotropy is present, genetic correlations may constrain the evolution of ecologically important traits. We used a quantitative genetics approach to investigate constraints on the evolution of secondary metabolites in a wild mustard, Boechera stricta. Much of the genetic variation in chemical composition of glucosinolates in B. stricta is controlled by a single locus, BCMA1/3. In a large-scale common garden experiment under natural conditions, we quantified fitness and glucosinolate profile in two leaf types and in fruits. We estimated genetic variances and covariances (the G-matrix) and selection on chemical profile in each tissue. Chemical composition of defenses was strongly genetically correlated between tissues. We found antagonistic selection between defense composition in leaves and fruits: compounds that were favored in leaves were disadvantageous in fruits. The positive genetic correlations and antagonistic selection led to strong constraints on the evolution of defenses in leaves and fruits. In a hypothetical population with no genetic variation at BCMA1/3, we found no evidence for genetic constraints, indicating that pleiotropy affecting chemical profile in multiple tissues drives constraints on the evolution of secondary metabolites.
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Affiliation(s)
- Rose A. Keith
- University Program in Genetics and Genomics, Duke University, Durham, North Carolina, 27708, United States
- Biology Department, Duke University, Durham, North Carolina, 27708, United States
| | - Thomas Mitchell-Olds
- University Program in Genetics and Genomics, Duke University, Durham, North Carolina, 27708, United States
- Biology Department, Duke University, Durham, North Carolina, 27708, United States
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38
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Evidence for Recent Polygenic Selection on Educational Attainment and Intelligence Inferred from Gwas Hits: A Replication of Previous Findings Using Recent Data. PSYCH 2019. [DOI: 10.3390/psych1010005] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023] Open
Abstract
Genetic variants identified by three large genome-wide association studies (GWAS) of educational attainment (EA) were used to test a polygenic selection model. Weighted and unweighted polygenic scores (PGS) were calculated and compared across populations using data from the 1000 Genomes (n = 26), HGDP-CEPH (n = 52) and gnomAD (n = 8) datasets. The PGS from the largest EA GWAS was highly correlated to two previously published PGSs (r = 0.96–0.97, N = 26). These factors are both highly predictive of average population IQ (r = 0.9, N = 23) and Learning index (r = 0.8, N = 22) and are robust to tests of spatial autocorrelation. Monte Carlo simulations yielded highly significant p values. In the gnomAD samples, the correlation between PGS and IQ was almost perfect (r = 0.98, N = 8), and ANOVA showed significant population differences in allele frequencies with positive effect. Socioeconomic variables slightly improved the prediction accuracy of the model (from 78–80% to 85–89%), but the PGS explained twice as much of the variance in IQ compared to socioeconomic variables. In both 1000 Genomes and gnomAD, there was a weak trend for lower GWAS significance SNPs to be less predictive of population IQ. Additionally, a subset of SNPs were found in the HGDP-CEPH sample (N = 127). The analysis of this sample yielded a positive correlation with latitude and a low negative correlation with distance from East Africa. This study provides robust results after accounting for spatial autocorrelation with Fst distances and random noise via an empirical Monte Carlo simulation using null SNPs.
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39
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Mozaffari SV, DeCara JM, Shah SJ, Sidore C, Fiorillo E, Cucca F, Lang RM, Nicolae DL, Ober C. Parent-of-origin effects on quantitative phenotypes in a large Hutterite pedigree. Commun Biol 2019; 2:28. [PMID: 30675526 PMCID: PMC6338666 DOI: 10.1038/s42003-018-0267-4] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2018] [Accepted: 12/14/2018] [Indexed: 12/22/2022] Open
Abstract
The impact of the parental origin of associated alleles in GWAS has been largely ignored. Yet sequence variants could affect traits differently depending on whether they are inherited from the mother or the father, as in imprinted regions, where identical inherited DNA sequences can have different effects based on the parental origin. To explore parent-of-origin effects (POEs), we studied 21 quantitative phenotypes in a large Hutterite pedigree to identify variants with single parent (maternal-only or paternal-only) effects, and then variants with opposite parental effects. Here we show that POEs, which can be opposite in direction, are relatively common in humans, have potentially important clinical effects, and will be missed in traditional GWAS. We identified POEs with 11 phenotypes, most of which are risk factors for cardiovascular disease. Many of the loci identified are characteristic of imprinted regions and are associated with the expression of nearby genes.
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Affiliation(s)
- Sahar V. Mozaffari
- Department of Human Genetics, University of Chicago, Chicago, IL 60637 USA
- Committee on Genetics, Genomics, and Systems Biology, University of Chicago, Chicago, IL 60637 USA
| | - Jeanne M. DeCara
- Department of Medicine, University of Chicago, Chicago, IL 60637 USA
| | - Sanjiv J. Shah
- Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611 USA
| | - Carlo Sidore
- Istituto di Ricerca Genetica e Biomedica (IRGB), CNR, Monserrato, 09042 Italy
| | - Edoardo Fiorillo
- Istituto di Ricerca Genetica e Biomedica (IRGB), CNR, Monserrato, 09042 Italy
| | - Francesco Cucca
- Istituto di Ricerca Genetica e Biomedica (IRGB), CNR, Monserrato, 09042 Italy
- Dipartimento di Scienze Biomediche, Universita di Sassari, Sassari, 07100 Italy
| | - Roberto M. Lang
- Department of Medicine, University of Chicago, Chicago, IL 60637 USA
| | - Dan L. Nicolae
- Department of Human Genetics, University of Chicago, Chicago, IL 60637 USA
- Committee on Genetics, Genomics, and Systems Biology, University of Chicago, Chicago, IL 60637 USA
- Department of Medicine, University of Chicago, Chicago, IL 60637 USA
- Department of Statistics, University of Chicago, Chicago, IL 60637 USA
| | - Carole Ober
- Department of Human Genetics, University of Chicago, Chicago, IL 60637 USA
- Committee on Genetics, Genomics, and Systems Biology, University of Chicago, Chicago, IL 60637 USA
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40
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Berg JJ, Harpak A, Sinnott-Armstrong N, Joergensen AM, Mostafavi H, Field Y, Boyle EA, Zhang X, Racimo F, Pritchard JK, Coop G. Reduced signal for polygenic adaptation of height in UK Biobank. eLife 2019; 8:39725. [PMID: 30895923 PMCID: PMC6428572 DOI: 10.7554/elife.39725] [Citation(s) in RCA: 210] [Impact Index Per Article: 42.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2018] [Accepted: 01/15/2019] [Indexed: 01/27/2023] Open
Abstract
Several recent papers have reported strong signals of selection on European polygenic height scores. These analyses used height effect estimates from the GIANT consortium and replication studies. Here, we describe a new analysis based on the the UK Biobank (UKB), a large, independent dataset. We find that the signals of selection using UKB effect estimates are strongly attenuated or absent. We also provide evidence that previous analyses were confounded by population stratification. Therefore, the conclusion of strong polygenic adaptation now lacks support. Moreover, these discrepancies highlight (1) that methods for correcting for population stratification in GWAS may not always be sufficient for polygenic trait analyses, and (2) that claims of differences in polygenic scores between populations should be treated with caution until these issues are better understood. Editorial note This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter).
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Affiliation(s)
- Jeremy J Berg
- Department of Biological SciencesColumbia UniversityNew YorkUnited States
| | - Arbel Harpak
- Department of Biological SciencesColumbia UniversityNew YorkUnited States,Department of BiologyStanford UniversityStanfordUnited States
| | | | - Anja Moltke Joergensen
- Lundbeck GeoGenetics Centre, Department of BiologyUniversity of CopenhagenCopenhagenDenmark
| | | | - Yair Field
- Department of GeneticsStanford UniversityStanfordUnited States
| | | | - Xinjun Zhang
- Department of AnthropologyUniversity of California, DavisDavisUnited States
| | - Fernando Racimo
- Lundbeck GeoGenetics Centre, Department of BiologyUniversity of CopenhagenCopenhagenDenmark
| | - Jonathan K Pritchard
- Department of BiologyStanford UniversityStanfordUnited States,Howard Hughes Medical Institute, Stanford UniversityStanfordUnited States
| | - Graham Coop
- Center for Population BiologyUniversity of California, DavisDavisUnited States,Department of Evolution and EcologyUniversity of California, DavisDavisUnited States
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41
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Fenster CB, Ballou JD, Dudash MR, Eldridge MDB, Frankham R, Lacy RC, Ralls K, Sunnucks P. Conservation and Genetics. THE YALE JOURNAL OF BIOLOGY AND MEDICINE 2018; 91:491-501. [PMID: 30588214 PMCID: PMC6302618] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Humans are responsible for a cataclysm of species extinction that will change the world as we see it, and will adversely affect human health and wellbeing. We need to understand at individual and societal levels why species conservation is important. Accepting the premise that species have value, we need to next consider the mechanisms underlying species extinction and what we can do to reverse the process. One of the last stages of species extinction is the reduction of a species to a few populations of relatively few individuals, a scenario that leads invariably to inbreeding and its adverse consequences, inbreeding depression. Inbreeding depression can be so severe that populations become at risk of extinction not only because of the expression of harmful recessive alleles (alleles having no phenotypic effect when in the heterozygous condition, e.g., Aa, where a is the recessive allele), but also because of their inability to respond genetically with sufficient speed to adapt to changing environmental conditions. However, new conservation approaches based on foundational quantitative and population genetic theory advocate for active genetic management of fragmented populations by facilitating gene movements between populations, i.e., admixture, or genetic rescue. Why species conservation is critical, the genetic consequences of small population size that often lead to extinction, and possible solutions to the problem of small population size are discussed and presented.
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Affiliation(s)
- Charles B. Fenster
- Department of Biology and Microbiology, South Dakota State University, Brookings, SD
| | - Jonathan D. Ballou
- Center for Conservation Genomics, Smithsonian Conservation Biology Institute, Washington, DC
| | - Michele R. Dudash
- Department of Natural Resource Management, South Dakota State University, Brookings, SD
| | - Mark D. B. Eldridge
- Australian Museum Research Institute, Australian Museum, Sydney, NSW, Australia
| | - Richard Frankham
- Macquarie University and Australian Museum, Sydney, NSW, Australia
| | | | - Katherine Ralls
- Center for Conservation Genomics, Smithsonian Conservation Biology Institute, Washington, DC
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Abstract
The population of the Mediterranean island of Sardinia has made important contributions to genome-wide association studies of complex disease traits and, based on ancient DNA (aDNA) studies of mainland Europe, Sardinia is hypothesized to be a unique refuge for early Neolithic ancestry. To provide new insights on the genetic history of this flagship population, we analyzed 3,514 whole-genome sequenced individuals from Sardinia. We find Sardinian samples show elevated levels of shared ancestry with Basque individuals, especially samples from the more historically isolated regions of Sardinia. Our analysis also uniquely illuminates how levels of genetic similarity with mainland aDNA samples varies subtly across the island. Together, our results indicate within-island sub-structure and sex-biased processes have substantially impacted the genetic history of Sardinia. These results give new insight to the demography of ancestral Sardinians and help further the understanding of sharing of disease risk alleles between Sardinia and mainland populations.
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43
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Mozaffari SV, Stein MM, Magnaye KM, Nicolae DL, Ober C. Parent of origin gene expression in a founder population identifies two new candidate imprinted genes at known imprinted regions. PLoS One 2018; 13:e0203906. [PMID: 30204804 PMCID: PMC6133383 DOI: 10.1371/journal.pone.0203906] [Citation(s) in RCA: 8] [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: 07/04/2018] [Accepted: 08/29/2018] [Indexed: 11/18/2022] Open
Abstract
Genomic imprinting is the phenomena that leads to silencing of one copy of a gene inherited from a specific parent. Mutations in imprinted regions have been involved in diseases showing parent of origin effects. Identifying genes with evidence of parent of origin expression patterns in family studies allows the detection of more subtle imprinting. Here, we use allele specific expression in lymphoblastoid cell lines from 306 Hutterites related in a single pedigree to provide formal evidence for parent of origin effects. We take advantage of phased genotype data to assign parent of origin to RNA-seq reads in individuals with gene expression data. Our approach identified known imprinted genes, two putative novel imprinted genes, PXDC1 and PWAR6, and 14 genes with asymmetrical parent of origin gene expression. We used gene expression in peripheral blood leukocytes (PBL) to validate our findings, and then confirmed imprinting control regions (ICRs) using DNA methylation levels in the PBLs.
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Affiliation(s)
- Sahar V. Mozaffari
- Committee on Genetics, Genomics & Systems Biology, University of Chicago, Chicago, Illinois, United States of America
- Department of Human Genetics, University of Chicago, Chicago, Illinois, United States of America
| | - Michelle M. Stein
- Department of Human Genetics, University of Chicago, Chicago, Illinois, United States of America
| | - Kevin M. Magnaye
- Department of Human Genetics, University of Chicago, Chicago, Illinois, United States of America
| | - Dan L. Nicolae
- Committee on Genetics, Genomics & Systems Biology, University of Chicago, Chicago, Illinois, United States of America
- Department of Human Genetics, University of Chicago, Chicago, Illinois, United States of America
- Department of Statistics, University of Chicago, Chicago, Illinois, United States of America
| | - Carole Ober
- Committee on Genetics, Genomics & Systems Biology, University of Chicago, Chicago, Illinois, United States of America
- Department of Human Genetics, University of Chicago, Chicago, Illinois, United States of America
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44
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Jeong C, Witonsky DB, Basnyat B, Neupane M, Beall CM, Childs G, Craig SR, Novembre J, Di Rienzo A. Detecting past and ongoing natural selection among ethnically Tibetan women at high altitude in Nepal. PLoS Genet 2018; 14:e1007650. [PMID: 30188897 PMCID: PMC6143271 DOI: 10.1371/journal.pgen.1007650] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2018] [Revised: 09/18/2018] [Accepted: 08/21/2018] [Indexed: 12/21/2022] Open
Abstract
Adaptive evolution in humans has rarely been characterized for its whole set of components, i.e. selective pressure, adaptive phenotype, beneficial alleles and realized fitness differential. We combined approaches for detecting polygenic adaptations and for mapping the genetic bases of physiological and fertility phenotypes in approximately 1000 indigenous ethnically Tibetan women from Nepal, adapted to high altitude. The results of genome-wide association analyses and tests for polygenic adaptations showed evidence of positive selection for alleles associated with more pregnancies and live births and evidence of negative selection for those associated with higher offspring mortality. Lower hemoglobin level did not show clear evidence for polygenic adaptation, despite its strong association with an EPAS1 haplotype carrying selective sweep signals.
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Affiliation(s)
- Choongwon Jeong
- Department of Human Genetics, University of Chicago, Chicago, Illinois, United States of America
| | - David B. Witonsky
- Department of Human Genetics, University of Chicago, Chicago, Illinois, United States of America
| | - Buddha Basnyat
- Oxford University Clinical Research Unit, Patan Hospital, Kathmandu, Nepal
| | | | - Cynthia M. Beall
- Department of Anthropology, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Geoff Childs
- Department of Anthropology, Washington University in St. Louis, St. Louis, Missouri, United States of America
| | - Sienna R. Craig
- Department of Anthropology, Dartmouth College, Hanover, New Hampshire, United States of America
| | - John Novembre
- Department of Human Genetics, University of Chicago, Chicago, Illinois, United States of America
| | - Anna Di Rienzo
- Department of Human Genetics, University of Chicago, Chicago, Illinois, United States of America
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45
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Delitala AP, Steri M, Fiorillo E, Marongiu M, Lakatta EG, Schlessinger D, Cucca F. Adipocytokine correlations with thyroid function and autoimmunity in euthyroid sardinians. Cytokine 2018; 111:189-193. [PMID: 30173124 DOI: 10.1016/j.cyto.2018.08.027] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2018] [Revised: 08/13/2018] [Accepted: 08/24/2018] [Indexed: 12/19/2022]
Abstract
OBJECTIVE Cytokines release by adipocytes could interact with TSH secretion. We evaluated the relationship between adipocytokines and TSH. We further tested for association of cytokines and thyroid autoimmunity. METHODS We conducted a cross-sectional study in a community-based sample including 5385 individuals (2964 female) with TSH within the reference range. Subjects who reported taking thyroid medications or drugs that alter thyroid function were excluded. TSH, FT4, adiponectin, leptin, antibody against thyroperoxidase and against thyroglobulin were measured. Linear and logistic regression models were used to test for association. RESULTS Females had higher adiponectin and leptin level and increased frequency of thyroid antibodies. In multiple regression analysis TSH was directly associated with leptin (β = 0.003, p = 0.001) and the presence of circulating antibody against thyroperoxidase (β = 0.315, p < 0.001), but negatively associated with age (β = -0.012, p < 0.001) and FT4 (β = -0.359, p < 0.001). Adiponectin, the presence of antibody against thyroglobulin and smoking habit were not associated with TSH levels (p = 0.223, p = 0.174 and p = 0.788, respectively). Logistic regression analysis revealed that higher adiponectin levels were associated with thyroid autoimmunity. CONCLUSIONS Leptin is positively associated with TSH levels in euthyroid individuals, suggesting an effect of the adipokine on TSH secretion. Our results support the hypothesis that the leptin and pituitary-thyroid axis might interact in the context of energy homeostasis. The effect of adiponectin on thyroid autoimmunity will require more studies.
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Affiliation(s)
- Alessandro P Delitala
- Istituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale delle Ricerche, c/o Cittadella Universitaria di Monserrato, Cagliari, Italy.
| | - Maristella Steri
- Istituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale delle Ricerche, c/o Cittadella Universitaria di Monserrato, Cagliari, Italy
| | - Edoardo Fiorillo
- Istituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale delle Ricerche, c/o Cittadella Universitaria di Monserrato, Cagliari, Italy
| | - Michele Marongiu
- Istituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale delle Ricerche, c/o Cittadella Universitaria di Monserrato, Cagliari, Italy
| | - Edward G Lakatta
- Laboratory Cardiovascular Sciences, Intramural Research Programme, National Insitute on Aging (NIA) - NIH, Baltimore, USA
| | | | - Francesco Cucca
- Istituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale delle Ricerche, c/o Cittadella Universitaria di Monserrato, Cagliari, Italy; Department of Biomedical Sciences, Azienda Ospedaliero-Universitaria di Sassari, Sassari, Italy
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46
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Tucci S, Vohr SH, McCoy RC, Vernot B, Robinson MR, Barbieri C, Nelson BJ, Fu W, Purnomo GA, Sudoyo H, Eichler EE, Barbujani G, Visscher PM, Akey JM, Green RE. Evolutionary history and adaptation of a human pygmy population of Flores Island, Indonesia. Science 2018; 361:511-516. [PMID: 30072539 PMCID: PMC6709593 DOI: 10.1126/science.aar8486] [Citation(s) in RCA: 39] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2017] [Accepted: 06/22/2018] [Indexed: 12/21/2022]
Abstract
Flores Island, Indonesia, was inhabited by the small-bodied hominin species Homo floresiensis, which has an unknown evolutionary relationship to modern humans. This island is also home to an extant human pygmy population. Here we describe genome-scale single-nucleotide polymorphism data and whole-genome sequences from a contemporary human pygmy population living on Flores near the cave where H. floresiensis was found. The genomes of Flores pygmies reveal a complex history of admixture with Denisovans and Neanderthals but no evidence for gene flow with other archaic hominins. Modern individuals bear the signatures of recent positive selection encompassing the FADS (fatty acid desaturase) gene cluster, likely related to diet, and polygenic selection acting on standing variation that contributed to their short-stature phenotype. Thus, multiple independent instances of hominin insular dwarfism occurred on Flores.
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Affiliation(s)
- Serena Tucci
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA
- Lewis-Sigler Institute, Princeton University, Princeton, NJ, USA
- Department of Life Sciences and Biotechnologies, University of Ferrara, Ferrara, Italy
| | - Samuel H Vohr
- Department of Biomolecular Engineering, University of California, Santa Cruz, CA, USA
| | - Rajiv C McCoy
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA
- Lewis-Sigler Institute, Princeton University, Princeton, NJ, USA
| | - Benjamin Vernot
- Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
| | - Matthew R Robinson
- Department of Computational Biology, Génopode, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Génopode, Quatier Sorge, Lausanne, Switzerland
| | - Chiara Barbieri
- Department of Linguistic and Cultural Evolution, Max Planck Institute for the Science of Human History, Jena, Germany
- Department of Evolutionary Biology and Environmental Studies, University of Zurich, Switzerland
| | - Brad J Nelson
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Wenqing Fu
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Gludhug A Purnomo
- Genome Diversity and Diseases Laboratory, Eijkman Institute for Molecular Biology, Jakarta, Indonesia
| | - Herawati Sudoyo
- Genome Diversity and Diseases Laboratory, Eijkman Institute for Molecular Biology, Jakarta, Indonesia
- Department of Medical Biology, Faculty of Medicine, University of Indonesia, Jakarta, Indonesia
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
| | - Guido Barbujani
- Department of Life Sciences and Biotechnologies, University of Ferrara, Ferrara, Italy
| | - Peter M Visscher
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
| | - Joshua M Akey
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA.
- Lewis-Sigler Institute, Princeton University, Princeton, NJ, USA
| | - Richard E Green
- Department of Biomolecular Engineering, University of California, Santa Cruz, CA, USA.
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47
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Floris M, Olla S, Schlessinger D, Cucca F. Genetic-Driven Druggable Target Identification and Validation. Trends Genet 2018; 34:558-570. [PMID: 29803319 PMCID: PMC6088790 DOI: 10.1016/j.tig.2018.04.004] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2018] [Revised: 04/13/2018] [Accepted: 04/23/2018] [Indexed: 12/19/2022]
Abstract
Choosing the right biological target is the critical primary decision for the development of new drugs. Systematic genetic association testing of both human diseases and quantitative traits, along with resultant findings of coincident associations between them, is becoming a powerful approach to infer drug targetable candidates and generate in vitro tests to identify compounds that can modulate them therapeutically. Here, we discuss opportunities and challenges, and infer criteria for the optimal use of genetic findings in the drug discovery pipeline.
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Affiliation(s)
- Matteo Floris
- Dipartimento di Scienze Biomediche, Università degli Studi di Sassari, Sassari, Italy; IRGB-CNR, Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche (CNR), Monserrato, Cagliari, Italy
| | - Stefania Olla
- IRGB-CNR, Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche (CNR), Monserrato, Cagliari, Italy
| | - David Schlessinger
- Laboratory of Genetics, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Francesco Cucca
- Dipartimento di Scienze Biomediche, Università degli Studi di Sassari, Sassari, Italy; IRGB-CNR, Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche (CNR), Monserrato, Cagliari, Italy.
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48
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Guo J, Wu Y, Zhu Z, Zheng Z, Trzaskowski M, Zeng J, Robinson MR, Visscher PM, Yang J. Global genetic differentiation of complex traits shaped by natural selection in humans. Nat Commun 2018; 9:1865. [PMID: 29760457 PMCID: PMC5951811 DOI: 10.1038/s41467-018-04191-y] [Citation(s) in RCA: 46] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2017] [Accepted: 04/12/2018] [Indexed: 11/09/2022] Open
Abstract
There are mean differences in complex traits among global human populations. We hypothesize that part of the phenotypic differentiation is due to natural selection. To address this hypothesis, we assess the differentiation in allele frequencies of trait-associated SNPs among African, Eastern Asian, and European populations for ten complex traits using data of large sample size (up to ~405,000). We show that SNPs associated with height ([Formula: see text]), waist-to-hip ratio ([Formula: see text]), and schizophrenia ([Formula: see text]) are significantly more differentiated among populations than matched "control" SNPs, suggesting that these trait-associated SNPs have undergone natural selection. We further find that SNPs associated with height ([Formula: see text]) and schizophrenia ([Formula: see text]) show significantly higher variance in linkage disequilibrium (LD) scores across populations than control SNPs. Our results support the hypothesis that natural selection has shaped the genetic differentiation of complex traits, such as height and schizophrenia, among worldwide populations.
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Affiliation(s)
- Jing Guo
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Yang Wu
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Zhihong Zhu
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Zhili Zheng
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia.,The Eye Hospital, School of Ophthalmology and Optometry, Wenzhou Medical University, 325027, Zhejiang, China
| | - Maciej Trzaskowski
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Jian Zeng
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Matthew R Robinson
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia.,Department of Computational Biology, University of Lausanne, 1011, Lausanne, Switzerland
| | - Peter M Visscher
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia.,Queensland Brain Institute, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Jian Yang
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia. .,Queensland Brain Institute, The University of Queensland, Brisbane, QLD, 4072, Australia.
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49
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Liao P, Satten GA, Hu YJ. Robust inference of population structure from next-generation sequencing data with systematic differences in sequencing. Bioinformatics 2018; 34:1157-1163. [PMID: 29186324 PMCID: PMC6031038 DOI: 10.1093/bioinformatics/btx708] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2017] [Revised: 09/29/2017] [Accepted: 11/24/2017] [Indexed: 12/30/2022] Open
Abstract
Motivation Inferring population structure is important for both population genetics and genetic epidemiology. Principal components analysis (PCA) has been effective in ascertaining population structure with array genotype data but can be difficult to use with sequencing data, especially when low depth leads to uncertainty in called genotypes. Because PCA is sensitive to differences in variability, PCA using sequencing data can result in components that correspond to differences in sequencing quality (read depth and error rate), rather than differences in population structure. We demonstrate that even existing methods for PCA specifically designed for sequencing data can still yield biased conclusions when used with data having sequencing properties that are systematically different across different groups of samples (i.e. sequencing groups). This situation can arise in population genetics when combining sequencing data from different studies, or in genetic epidemiology when using historical controls such as samples from the 1000 Genomes Project. Results To allow inference on population structure using PCA in these situations, we provide an approach that is based on using sequencing reads directly without calling genotypes. Our approach is to adjust the data from different sequencing groups to have the same read depth and error rate so that PCA does not generate spurious components representing sequencing quality. To accomplish this, we have developed a subsampling procedure to match the depth distributions in different sequencing groups, and a read-flipping procedure to match the error rates. We average over subsamples and read flips to minimize loss of information. We demonstrate the utility of our approach using two datasets from 1000 Genomes, and further evaluate it using simulation studies. Availability and implementation TASER-PC software is publicly available at http://web1.sph.emory.edu/users/yhu30/software.html. Contact yijuan.hu@emory.edu. Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Peizhou Liao
- Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, USA
| | - Glen A Satten
- Division of Reproductive Health, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Yi-Juan Hu
- Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, USA
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Abstract
Adult height and growth patterns are largely genetically programmed. Studies in twins have indicated that the heritability of height is high (>80%), suggesting that genetic variation is the main determinant of stature. Height exhibits a normal (Gaussian) distribution according to sex, age, and ancestry. Short stature is usually defined as a height which is 2 standard deviations (S.D.) less than the mean height of a specific population. This definition includes 2.3% of the population and usually includes healthy individuals. In this group of short stature non-syndromic conditions, the genetic influence occurs polygenically or oligogenically. As a rule, each common genetic variant accounts for a small effect (1mm) on individual height variation. Recently, several studies demonstrated that some rare variants can cause greater effect on height, without causing a syndromic condition. In more extreme cases, height SDS below 2.5 or 3 (which would comprise approximately 0.6 and 0.1% of the population, respectively) is frequently associated with syndromic conditions and are usually caused by a monogenic defect. More than 1,000 inherited/genetic diseases have growth disorder as an important phenotype. These conditions are usually responsible for syndromic short stature. In the coming years, we expect to discover several genetic causes of short stature, thereby explaining the phenotype of what we currently classify as short stature of unknown cause. These discoveries will have a profound impact on the follow-up and treatment of these children.
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Affiliation(s)
- Michelle Grunauer
- Pediatric Intensive Care Unit, Hospital de los Valles, Escuela de Medicina, Universidad San Francisco de Quito (USFQ), Quito, Ecuador
| | - Alexander A L Jorge
- Unidade de Endocrinologia Genetica (LIM25), Hospital das Clinicas da Faculdade de Medicina da Universidade de São Paulo (FMUSP), Sao Paulo, Brazil.
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