151
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The distribution of common-variant effect sizes. Nat Genet 2021; 53:1243-1249. [PMID: 34326547 DOI: 10.1038/s41588-021-00901-3] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Accepted: 06/23/2021] [Indexed: 01/08/2023]
Abstract
The genetic effect-size distribution of a disease describes the number of risk variants, the range of their effect sizes and sample sizes that will be required to discover them. Accurate estimation has been a challenge. Here I propose Fourier Mixture Regression (FMR), validating that it accurately estimates real and simulated effect-size distributions. Applied to summary statistics for ten diseases (average [Formula: see text]), FMR estimates that 100,000-1,000,000 cases will be required for genome-wide significant SNPs to explain 50% of SNP heritability. In such large studies, genome-wide significance becomes increasingly conservative, and less stringent thresholds achieve high true positive rates if confounding is controlled. Across traits, polygenicity varies, but the range of their effect sizes is similar. Compared with effect sizes in the top 10% of heritability, including most discovered thus far, those in the bottom 10-50% are orders of magnitude smaller and more numerous, spanning a large fraction of the genome.
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152
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Yang R, Guo X, Zhu D, Tan C, Bian C, Ren J, Huang Z, Zhao Y, Cai G, Liu D, Wu Z, Wang Y, Li N, Hu X. Accelerated deciphering of the genetic architecture of agricultural economic traits in pigs using a low-coverage whole-genome sequencing strategy. Gigascience 2021; 10:giab048. [PMID: 34282453 PMCID: PMC8290195 DOI: 10.1093/gigascience/giab048] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Revised: 03/21/2021] [Accepted: 06/15/2021] [Indexed: 11/20/2022] Open
Abstract
BACKGROUND Uncovering the genetic architecture of economic traits in pigs is important for agricultural breeding. However, high-density haplotype reference panels are unavailable in most agricultural species, limiting accurate genotype imputation in large populations. Moreover, the infinitesimal model of quantitative traits implies that weak association signals tend to be spread across most of the genome, further complicating the genetic analysis. Hence, there is a need to develop new methods for sequencing large cohorts without large reference panels. RESULTS We describe a Tn5-based highly accurate, cost- and time-efficient, low-coverage sequencing method to obtain 11.3 million whole-genome single-nucleotide polymorphisms in 2,869 Duroc boars at a mean depth of 0.73×. On the basis of these single-nucleotide polymorphisms, a genome-wide association study was performed, resulting in 14 quantitative trait loci (QTLs) for 7 of 21 important agricultural traits in pigs. These QTLs harbour genes, such as ABCD4 for total teat number and HMGA1 for back fat thickness, and provided a starting point for further investigation. The inheritance models of the different traits varied greatly. Most follow the minor-polygene model, but this can be attributed to different reasons, such as the shaping of genetic architecture by artificial selection for this population and sufficiently interconnected minor gene regulatory networks. CONCLUSIONS Genome-wide association study results for 21 important agricultural traits identified 14 QTLs/genes and showed their genetic architectures, providing guidance for genetic improvement harnessing genomic features. The Tn5-based low-coverage sequencing method can be applied to large-scale genome studies for any species without a good reference panel and can be used for agricultural breeding.
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Affiliation(s)
- Ruifei Yang
- State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, No. 2 Yuanmingyuan west road, Haidian district, Beijing 100193, China
| | - Xiaoli Guo
- State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, No. 2 Yuanmingyuan west road, Haidian district, Beijing 100193, China
| | - Di Zhu
- State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, No. 2 Yuanmingyuan west road, Haidian district, Beijing 100193, China
| | - Cheng Tan
- National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, No. 483 Wushan road, Tianhe district, Guangdong 510640, China
| | - Cheng Bian
- State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, No. 2 Yuanmingyuan west road, Haidian district, Beijing 100193, China
| | - Jiangli Ren
- State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, No. 2 Yuanmingyuan west road, Haidian district, Beijing 100193, China
| | - Zhuolin Huang
- State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, No. 2 Yuanmingyuan west road, Haidian district, Beijing 100193, China
| | - Yiqiang Zhao
- State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, No. 2 Yuanmingyuan west road, Haidian district, Beijing 100193, China
| | - Gengyuan Cai
- National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, No. 483 Wushan road, Tianhe district, Guangdong 510640, China
| | - Dewu Liu
- National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, No. 483 Wushan road, Tianhe district, Guangdong 510640, China
| | - Zhenfang Wu
- National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, No. 483 Wushan road, Tianhe district, Guangdong 510640, China
| | - Yuzhe Wang
- State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, No. 2 Yuanmingyuan west road, Haidian district, Beijing 100193, China
- National Research Facility for Phenotypic and Genotypic Analysis of Model Animals (Beijing), China Agricultural University, No. 2 Yuanmingyuan west road, Haidian district, Beijing 100193, China
| | - Ning Li
- State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, No. 2 Yuanmingyuan west road, Haidian district, Beijing 100193, China
| | - Xiaoxiang Hu
- State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, No. 2 Yuanmingyuan west road, Haidian district, Beijing 100193, China
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153
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Babiker A, Al Noaim K, Al Swaid A, Alfadhel M, Deeb A, Martín-Rivada Á, Barrios V, Pérez-Jurado LA, Alfares A, Al Alwan I, Argente J. Short stature with low insulin-like growth factor 1 availability due to pregnancy-associated plasma protein A2 deficiency in a Saudi family. Clin Genet 2021; 100:601-606. [PMID: 34272725 DOI: 10.1111/cge.14030] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2021] [Revised: 07/13/2021] [Accepted: 07/15/2021] [Indexed: 01/02/2023]
Abstract
In 2016 a new syndrome with postnatal short stature and low IGF1 bioavailability caused by biallelic loss-of-function mutations in the gene encoding the metalloproteinase pregnancy-associated plasma protein A2 (PAPP-A2) was described in two families. Here we report two siblings of a third family from Saudi Arabia with postnatal growth retardation and decreased IGF1 availability due to a new homozygous nonsense mutation (p.Glu886* in exon 7) in PAPPA2. The two affected males showed progressively severe short stature starting around 8 years of age, moderate microcephaly, decreased bone mineral density, and high circulating levels of total IGF1, IGFBP3, and the IGF acid-labile subunit (IGFALS), with decreased free IGF1 concentrations. Interestingly, circulating IGF2 and IGFBP5 were not increased. An increase in growth velocity and height was seen in the prepuberal patient in response to rhIGF1. These patients contribute to the confirmation of the clinical picture associated with PAPP-A2 deficiency and that the PAPPA2 gene should be studied in all patients with short stature with this characteristic phenotype. Hence, pediatric endocrinologists should measure circulating PAPP-A2 levels in the study of short stature as very low or undetectable levels of this protein can help to focus the diagnosis and treatment.
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Affiliation(s)
- Amir Babiker
- King Abdullah Specialized Children's Hospital, King Abdulaziz Medical City, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia.,College of Medicine, King Saud bin Abdul-Aziz University for Health Sciences, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia.,King Abdullah International Medical Research Center, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia
| | - Khalid Al Noaim
- King Abdullah Specialized Children's Hospital, King Abdulaziz Medical City, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia.,Department of Pediatrics, College of Medicine, King Faisal University, Al-Ahsa, Saudi Arabia
| | - Abdulrahman Al Swaid
- King Abdullah Specialized Children's Hospital, King Abdulaziz Medical City, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia.,College of Medicine, King Saud bin Abdul-Aziz University for Health Sciences, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia.,King Abdullah International Medical Research Center, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia
| | - Majid Alfadhel
- King Abdullah Specialized Children's Hospital, King Abdulaziz Medical City, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia.,College of Medicine, King Saud bin Abdul-Aziz University for Health Sciences, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia.,King Abdullah International Medical Research Center, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia
| | - Asma Deeb
- Pediatric Endocrine Division, Sheikh Shakhbout Medical City, Abu Dhabi & Khalifa University, Abu Dhabi, United Arab Emirates
| | - Álvaro Martín-Rivada
- Department of Pediatrics & Pediatric Endocrinology, Hospital Infantil Universitario Niño Jesús, Instituto de Investigación La Princesa, Universidad Autónoma de Madrid, Madrid, Spain
| | - Vicente Barrios
- Department of Pediatrics & Pediatric Endocrinology, Hospital Infantil Universitario Niño Jesús, Instituto de Investigación La Princesa, Universidad Autónoma de Madrid, Madrid, Spain.,Centro de Investigación Biomédica en Red (CIBER) de Fisiopatología de la Obesidad y Nutriciόn (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
| | - Luis A Pérez-Jurado
- Genetics Unit, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain.,Service of Genetics, Hospital del Mar and Hospital del Mar Research Institute (IMIM), Barcelona, Spain.,CIBER de Enfermedades Raras (CIBERER), Instituto de Salud Carlos III, Barcelona, Spain
| | - Ahmed Alfares
- King Abdullah International Medical Research Center, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia.,Departement of Laboratory and Pathology Medicine, King Abdullah International Medical Research Center, Riyadh, Saudi Arabia.,Departement of Pediatrics, College of Medicine, Qassim University, Buraidah, Saudi Arabia
| | - Ibrahim Al Alwan
- King Abdullah Specialized Children's Hospital, King Abdulaziz Medical City, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia.,College of Medicine, King Saud bin Abdul-Aziz University for Health Sciences, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia.,King Abdullah International Medical Research Center, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia
| | - Jesús Argente
- Department of Pediatrics & Pediatric Endocrinology, Hospital Infantil Universitario Niño Jesús, Instituto de Investigación La Princesa, Universidad Autónoma de Madrid, Madrid, Spain.,Centro de Investigación Biomédica en Red (CIBER) de Fisiopatología de la Obesidad y Nutriciόn (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain.,IMDEA. Food Institute, CEIUAM+CSI, Madrid, Spain
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154
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Lin E, Tsai SJ, Kuo PH, Liu YL, Yang AC, Conomos MP, Thornton TA. Genome-wide association study in the Taiwan biobank identifies four novel genes for human height: NABP2, RASA2, RNF41 and SLC39A5. Hum Mol Genet 2021; 30:2362-2369. [PMID: 34270706 DOI: 10.1093/hmg/ddab202] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Revised: 06/13/2021] [Accepted: 07/12/2021] [Indexed: 11/13/2022] Open
Abstract
Numerous genome-wide association studies (GWASs) have been conducted for the identification of genetic variants involved with human height. The vast majority of these studies, however, have been conducted in populations of European ancestry. Here, we report the first GWAS of adult height in the Taiwan Biobank using a discovery sample of 14 571 individuals and an independent replication sample of 20 506 individuals. From our analysis we generalize to the Taiwanese population genome-wide significant associations with height and 18 previously identified genes in European and non-Taiwanese East Asian populations. We also identify and replicate, at the genome-wide significance level, associated variants for height in four novel genes at two loci that have not previously been reported: RASA2 on chromosome 3 and NABP2, RNF41, and SLC39A5 at 12q13.3 on chromosome 12. RASA2 and RNF41 are strong candidates for having a role in height with copy number and loss of function variants in RASA2 previously found to be associated with short stature disorders, and decreased expression of the RNF41 gene resulting in insulin resistance in skeletal muscle. The results from our analysis of the Taiwan Biobank underscore the potential for the identification of novel genetic discoveries in underrepresented worldwide populations, even for traits, such as height, that have been extensively investigated in large-scale studies of European ancestry populations.
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Affiliation(s)
- Eugene Lin
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA.,Department of Electrical & Computer Engineering, University of Washington, Seattle, WA 98195, USA.,Graduate Institute of Biomedical Sciences, China Medical University, Taichung, Taiwan
| | - Shih-Jen Tsai
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan.,Division of Psychiatry, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Po-Hsiu Kuo
- Department of Public Health, Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan
| | - Yu-Li Liu
- Center for Neuropsychiatric Research, National Health Research Institutes, Miaoli County, Taiwan
| | - Albert C Yang
- Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan.,Division of Interdisciplinary Medicine and Biotechnology, Beth Israel Deaconess Medical Center/Harvard Medical School, Boston, MA 02215, USA
| | - Matthew P Conomos
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Timothy A Thornton
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
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155
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Detection of 15-bp Deletion Mutation within PLAG1 Gene and Its Effects on Growth Traits in Goats. Animals (Basel) 2021; 11:ani11072064. [PMID: 34359192 PMCID: PMC8300177 DOI: 10.3390/ani11072064] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Revised: 07/08/2021] [Accepted: 07/08/2021] [Indexed: 12/13/2022] Open
Abstract
Simple Summary Goats have always served as an important domesticated livestock. PLAG1 is a major gene that affects the stature and growth of animals. Body size traits are very important for goats as it directly affects the economic characteristics of meat and cashmere production. This study showed that the 15-base pair (bp) InDel (rs637141549) can significantly affect growth traits such as body weight, height, height at hip cross, chest circumference, hip width and body index of goats through the detection of large samples (n = 1581) in four indigenous breeds. Accordingly, it is suggested that the deletion mutation can be used as a potential molecular marker that significantly affects goat growth traits. Moreover, the 15bp deletion mutation can be used as a potential molecular marker, which significantly affects the growth traits of goats and plays an important role in animal husbandry production. Abstract Stature and weight are important growth and development traits for animals, which also significantly affect the productivity of livestock. Polymorphic adenoma gene 1 (PLAG1) is located in the growth-related quantitative trait nucleotides (QTN), and its variation has been determined to significantly affect the body stature of bovines. This study found that novel 15-bp InDel could significantly influence important growth traits in goats. The frequencies of genotypes of the 15-bp mutation and relationship with core growth traits such as body weight, body height, height at hip cross, chest circumference, hip width and body index were explored in 1581 individuals among 4 Chinese native goat breeds. The most frequent genotypes of Shaanbei white Cashmere goat (SWCG), Inner Mongolia White Cashmere goat (IMCG) and Guanzhong Dairy goat (GZDG) were II genotypes (insertion/insertion), and the frequency of ID genotype (insertion/deletion) was found to be slightly higher than that of II genotype in Hainan Black goat (HNBG), showing that the frequency of the I allele was higher than that of the D allele. In adult goats, there were significant differences between 15-bp variation and body weight, chest circumference and body height traits in SWCG (p < 0.05). Furthermore, the locus was also found to be significantly correlated with the body index of HNBG (p = 0.044) and hip width in GZDG (p = 0.002). In regard to lambs, there were significant differences in height at the hip cross of SWCG (p = 0.036) and hip width in IMWC (p = 0.005). The corresponding results suggest that the 15-bp InDel mutation of PLAG1 is associated with the regulation of important growth characteristics of both adult and lamb of goats, which may serve as efficient molecular markers for goat breeding.
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156
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Medina R, Wogan GOU, Bi K, Termignoni-García F, Bernal MH, Jaramillo-Correa JP, Wang IJ, Vázquez-Domínguez E. Phenotypic and genomic diversification with isolation by environment along elevational gradients in a neotropical treefrog. Mol Ecol 2021; 30:4062-4076. [PMID: 34160853 DOI: 10.1111/mec.16035] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2020] [Revised: 06/10/2021] [Accepted: 06/16/2021] [Indexed: 01/03/2023]
Abstract
Understanding how geographic and environmental heterogeneity drive local patterns of genetic variation is a major goal of ecological genomics and a key question in evolutionary biology. The tropical Andes and inter-Andean valleys are shaped by markedly heterogeneous landscapes, where species experience strong selective processes. We examined genome-wide SNP data together with behavioural and ecological traits (mating calls and body size) known to contribute to genetic isolation in anurans in the banana tree-dwelling frog, Boana platanera, distributed across an environmental gradient in Central Colombia (northern South America). Here, we analysed the relationships between environmentally (temperature and precipitation) associated genetic and phenotypic differentiation and the potential drivers of isolation by environment along an elevation gradient. We identified candidate SNPs associated with temperature and body size, which follow a clinal pattern of genome-wide differentiation tightly coupled with phenotypic variation: as elevation increases, B. platanera exhibits larger body size and longer call duration with more pulses but lower pulse rate and frequency. Thus, the environmental landscape has rendered a scenario where isolation by environment and candidate loci show concordance with phenotypic divergence in this tropical frog along an elevation gradient in the Colombian Andes. Our study sets the basis for evaluating the role of temperature in the genetic structure and local adaptation in tropical treefrogs and its putative effect on life cycle (embryos, tadpoles, adults) along elevation gradients.
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Affiliation(s)
- Ricardo Medina
- Departamento de Ecología de la Biodiversidad, Instituto de Ecología, Universidad Nacional Autónoma de México, Coyoacán, Ciudad de México, México.,Posgrado en Ciencias Biológicas, Universidad Nacional Autónoma de México, Coyoacán, Ciudad de México, México.,Grupo de Herpetología, Eco-Fisiología & Etología, Departamento de Biología, Universidad del Tolima, Altos de Santa Helena, Ibagué, Colombia
| | - Guinevere O U Wogan
- Department of Environmental Science, Policy, and Management, College of Natural Resources, University of California, Berkeley, California, USA.,Department of Integrative Biology, Oklahoma State University, Oklahoma, USA
| | - Ke Bi
- Museum of Vertebrate Zoology, University of California, Berkeley, California, USA.,Computational Genomics Resource Laboratory (CGRL, California Institute for Quantitative Biosciences (QB3, University of California, Berkeley, California, USA
| | - Flavia Termignoni-García
- Department of Organismic and Evolutionary Biology (OEB, Harvard University, Cambridge, Massachusetts, USA
| | - Manuel Hernando Bernal
- Grupo de Herpetología, Eco-Fisiología & Etología, Departamento de Biología, Universidad del Tolima, Altos de Santa Helena, Ibagué, Colombia
| | - Juan P Jaramillo-Correa
- Departamento de Ecología de la Biodiversidad, Instituto de Ecología, Universidad Nacional Autónoma de México, Coyoacán, Ciudad de México, México
| | - Ian J Wang
- Department of Environmental Science, Policy, and Management, College of Natural Resources, University of California, Berkeley, California, USA
| | - Ella Vázquez-Domínguez
- Departamento de Ecología de la Biodiversidad, Instituto de Ecología, Universidad Nacional Autónoma de México, Coyoacán, Ciudad de México, México
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157
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Upners EN, Busch AS, Almstrup K, Petersen JH, Assens M, Main KM, Jensen RB, Juul A. Does height and IGF-I determine pubertal timing in girls? Pediatr Res 2021; 90:176-183. [PMID: 33142306 DOI: 10.1038/s41390-020-01215-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Revised: 07/08/2020] [Accepted: 09/23/2020] [Indexed: 11/09/2022]
Abstract
BACKGROUND Pubertal timing is closely linked to growth regulated by the growth hormone/insulin-like factor (GH/IGF) axis that includes IGF-regulating factors such as pregnancy-associated plasma protein-A/A2 (PAPP-A/PAPP-A2) and stanniocalcin 2 (STC2). We investigated the association between height, IGF-I concentration, and PAPPA, PAPPA2, and STC2 genotypes on the timing of female pubertal milestones. METHODS Height, IGF-I, and genotypes were analyzed in 1382 Danish girls from the general population, 67 patients with tall stature (height ≥2 SD), and 124 patients with short stature (height ≤-2 SD). The main outcomes were breast stage and menarche. RESULTS Thelarche occurred significantly earlier in patients with tall stature (mean age 9.37 years [95% confidence interval (CI) 8.87-9.87]) and later in patients with short stature (11.07 years [95% CI 10.7-11.43]) compared with girls within the normal range (9.96 years [95% CI 9.85-10.07]) (p = 0.02 and p < 0.01, respectively). Girls with higher IGF-I levels experienced thelarche and menarche earlier compared with the rest of the cohort (p < 0.01). Genotypes were not associated with age at thelarche nor menarche, but the PAPPA2 minor allele carriers were shorter compared with major allele carriers, p = 0.03. CONCLUSIONS Height and IGF-I, but not PAPP-A, PAPP-A2, and STC2 genotypes, were negatively associated with age at thelarche and menarche. IMPACT Girls with tall and short stature enter puberty earlier and later compared with girls with normal height. Girls with higher insulin-growth factor-I in childhood enter puberty earlier. Pubertal timing is influenced by longitudinal growth and IGF-I levels earlier in childhood. Childhood growth and the levels of IGF-I in childhood may be biomarkers of pubertal timing.
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Affiliation(s)
- Emmie N Upners
- Department of Growth and Reproduction, Rigshospitalet, University of Copenhagen, Blegdamsvej 9, 2100, Copenhagen, Denmark. .,International Center for Research and Research Training in Endocrine Disruption of Male Reproduction and Child Health (EDMaRC), Rigshospitalet, University of Copenhagen, Blegdamsvej 9, 2100, Copenhagen, Denmark.
| | - Alexander S Busch
- Department of Growth and Reproduction, Rigshospitalet, University of Copenhagen, Blegdamsvej 9, 2100, Copenhagen, Denmark.,International Center for Research and Research Training in Endocrine Disruption of Male Reproduction and Child Health (EDMaRC), Rigshospitalet, University of Copenhagen, Blegdamsvej 9, 2100, Copenhagen, Denmark
| | - Kristian Almstrup
- Department of Growth and Reproduction, Rigshospitalet, University of Copenhagen, Blegdamsvej 9, 2100, Copenhagen, Denmark.,International Center for Research and Research Training in Endocrine Disruption of Male Reproduction and Child Health (EDMaRC), Rigshospitalet, University of Copenhagen, Blegdamsvej 9, 2100, Copenhagen, Denmark
| | - Jørgen H Petersen
- Department of Growth and Reproduction, Rigshospitalet, University of Copenhagen, Blegdamsvej 9, 2100, Copenhagen, Denmark.,International Center for Research and Research Training in Endocrine Disruption of Male Reproduction and Child Health (EDMaRC), Rigshospitalet, University of Copenhagen, Blegdamsvej 9, 2100, Copenhagen, Denmark
| | - Maria Assens
- Department of Growth and Reproduction, Rigshospitalet, University of Copenhagen, Blegdamsvej 9, 2100, Copenhagen, Denmark.,International Center for Research and Research Training in Endocrine Disruption of Male Reproduction and Child Health (EDMaRC), Rigshospitalet, University of Copenhagen, Blegdamsvej 9, 2100, Copenhagen, Denmark
| | - Katharina M Main
- Department of Growth and Reproduction, Rigshospitalet, University of Copenhagen, Blegdamsvej 9, 2100, Copenhagen, Denmark.,International Center for Research and Research Training in Endocrine Disruption of Male Reproduction and Child Health (EDMaRC), Rigshospitalet, University of Copenhagen, Blegdamsvej 9, 2100, Copenhagen, Denmark
| | - Rikke B Jensen
- Department of Growth and Reproduction, Rigshospitalet, University of Copenhagen, Blegdamsvej 9, 2100, Copenhagen, Denmark.,International Center for Research and Research Training in Endocrine Disruption of Male Reproduction and Child Health (EDMaRC), Rigshospitalet, University of Copenhagen, Blegdamsvej 9, 2100, Copenhagen, Denmark
| | - Anders Juul
- Department of Growth and Reproduction, Rigshospitalet, University of Copenhagen, Blegdamsvej 9, 2100, Copenhagen, Denmark.,International Center for Research and Research Training in Endocrine Disruption of Male Reproduction and Child Health (EDMaRC), Rigshospitalet, University of Copenhagen, Blegdamsvej 9, 2100, Copenhagen, Denmark
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158
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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: 13] [Impact Index Per Article: 3.3] [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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159
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Xue H, Shen X, Pan W. Constrained maximum likelihood-based Mendelian randomization robust to both correlated and uncorrelated pleiotropic effects. Am J Hum Genet 2021; 108:1251-1269. [PMID: 34214446 PMCID: PMC8322939 DOI: 10.1016/j.ajhg.2021.05.014] [Citation(s) in RCA: 208] [Impact Index Per Article: 52.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2021] [Accepted: 05/25/2021] [Indexed: 12/23/2022] Open
Abstract
With the increasing availability of large-scale GWAS summary data on various complex traits and diseases, there have been tremendous interests in applications of Mendelian randomization (MR) to investigate causal relationships between pairs of traits using SNPs as instrumental variables (IVs) based on observational data. In spite of the potential significance of such applications, the validity of their causal conclusions critically depends on some strong modeling assumptions required by MR, which may be violated due to the widespread (horizontal) pleiotropy. Although many MR methods have been proposed recently to relax the assumptions by mainly dealing with uncorrelated pleiotropy, only a few can handle correlated pleiotropy, in which some SNPs/IVs may be associated with hidden confounders, such as some heritable factors shared by both traits. Here we propose a simple and effective approach based on constrained maximum likelihood and model averaging, called cML-MA, applicable to GWAS summary data. To deal with more challenging situations with many invalid IVs with only weak pleiotropic effects, we modify and improve it with data perturbation. Extensive simulations demonstrated that the proposed methods could control the type I error rate better while achieving higher power than other competitors. Applications to 48 risk factor-disease pairs based on large-scale GWAS summary data of 3 cardio-metabolic diseases (coronary artery disease, stroke, and type 2 diabetes), asthma, and 12 risk factors confirmed its superior performance.
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Affiliation(s)
- Haoran Xue
- School of Statistics, University of Minnesota, Minneapolis, MN 55455, USA; Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN 55455, USA
| | - Xiaotong Shen
- School of Statistics, University of Minnesota, Minneapolis, MN 55455, USA
| | - Wei Pan
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN 55455, USA.
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Liu Y, Zhang X, Lee J, Smelser D, Cade B, Chen H, Zhou H, Kirchner HL, Lin X, Mukherjee S, Hillman D, Liu CT, Redline S, Sofer T. Genome-wide association study of neck circumference identifies sex-specific loci independent of generalized adiposity. Int J Obes (Lond) 2021; 45:1532-1541. [PMID: 33907307 PMCID: PMC8236408 DOI: 10.1038/s41366-021-00817-2] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Revised: 03/06/2021] [Accepted: 04/09/2021] [Indexed: 02/02/2023]
Abstract
BACKGROUND/OBJECTIVES Neck circumference, an index of upper airway fat, has been suggested to be an important measure of body-fat distribution with unique associations with health outcomes such as obstructive sleep apnea and metabolic disease. This study aims to study the genetic bases of neck circumference. METHODS We conducted a multi-ethnic genome-wide association study of neck circumference, adjusted and unadjusted for BMI, in up to 15,090 European Ancestry (EA) and African American (AA) individuals. Because sexually dimorphic associations have been observed for anthropometric traits, we conducted both sex-combined and sex-specific analysis. RESULTS We identified rs227724 near the Noggin (NOG) gene as a possible quantitative locus for neck circumference in men (N = 8831, P = 1.74 × 10-9) but not in women (P = 0.08). The association was replicated in men (N = 1554, P = 0.045) in an independent dataset. This locus was previously reported to be associated with human height and with self-reported snoring. We also identified rs13087058 on chromosome 3 as a suggestive locus in sex-combined analysis (N = 15090, P = 2.94 × 10-7; replication P =0.049). This locus was also associated with electrocardiogram-assessed PR interval and is a cis-expression quantitative locus for the PDZ Domain-containing ring finger 2 (PDZRN3) gene. Both NOG and PDZRN3 interact with members of transforming growth factor-beta superfamily signaling proteins. CONCLUSIONS Our study suggests that neck circumference may have unique genetic basis independent of BMI.
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Affiliation(s)
- Yaowu Liu
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Xiaoyu Zhang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Jiwon Lee
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
| | - Diane Smelser
- Department of Molecular and Functional Genomics, Geisinger Clinic, Danville, PA, USA
| | - Brian Cade
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Han Chen
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
- Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Hufeng Zhou
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - H Lester Kirchner
- Department of Population Health Sciences, Geisinger Clinic, Danville, PA, USA
| | - Xihong Lin
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Statistics, Harvard University, Cambridge, MA, USA
| | - Sutapa Mukherjee
- Sleep Health Service, Respiratory and Sleep Services, Southern Adelaide Local Health Network, Adelaide, SA, Australia
- Adelaide Institute for Sleep Health, Flinders Health and Medical Research Institute, College of Medicine and Public Health, Flinders University, Adelaide, SA, Australia
| | - David Hillman
- School of Human Sciences, The University of Western Australia, Perth, WA, Australia
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Tamar Sofer
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA.
- Department of Medicine, Harvard Medical School, Boston, MA, USA.
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161
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Justice AE, Young K, Gogarten SM, Sofer T, Graff M, Love SAM, Wang Y, Klimentidis YC, Cruz M, Guo X, Hartwig F, Petty L, Yao J, Allison MA, Below JE, Buchanan TA, Chen YDI, Goodarzi MO, Hanis C, Highland HM, Hsueh WA, Ipp E, Parra E, Palmas W, Raffel LJ, Rotter JI, Tan J, Taylor KD, Valladares A, Xiang AH, Sánchez-Johnsen L, Isasi CR, North KE. Genome-wide association study of body fat distribution traits in Hispanics/Latinos from the HCHS/SOL. Hum Mol Genet 2021; 30:2190-2204. [PMID: 34165540 PMCID: PMC8561424 DOI: 10.1093/hmg/ddab166] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Revised: 06/16/2021] [Accepted: 06/17/2021] [Indexed: 01/02/2023] Open
Abstract
Central obesity is a leading health concern with a great burden carried by ethnic minority populations, especially Hispanics/Latinos. Genetic factors contribute to the obesity burden overall and to inter-population differences. We aimed to identify the loci associated with central adiposity measured as waist-to-hip ratio (WHR), waist circumference (WC) and hip circumference (HIP) adjusted for body mass index (adjBMI) by using the Hispanic Community Health Study/Study of Latinos (HCHS/SOL); determine if differences in associations differ by background group within HCHS/SOL and determine whether previously reported associations generalize to HCHS/SOL. Our analyses included 7472 women and 5200 men of mainland (Mexican, Central and South American) and Caribbean (Puerto Rican, Cuban and Dominican) background residing in the USA. We performed genome-wide association analyses stratified and combined across sexes using linear mixed-model regression. We identified 16 variants for waist-to-hip ratio adjusted for body mass index (WHRadjBMI), 22 for waist circumference adjusted for body mass index (WCadjBMI) and 28 for hip circumference adjusted for body mass index (HIPadjBMI), which reached suggestive significance (P < 1 × 10-6). Many loci exhibited differences in strength of associations by ethnic background and sex. We brought a total of 66 variants forward for validation in cohorts (N = 34 161) with participants of Hispanic/Latino, African and European descent. We confirmed four novel loci (P < 0.05 and consistent direction of effect, and P < 5 × 10-8 after meta-analysis), including two for WHRadjBMI (rs13301996, rs79478137); one for WCadjBMI (rs3168072) and one for HIPadjBMI (rs28692724). Also, we generalized previously reported associations to HCHS/SOL, (8 for WHRadjBMI, 10 for WCadjBMI and 12 for HIPadjBMI). Our study highlights the importance of large-scale genomic studies in ancestrally diverse Hispanic/Latino populations for identifying and characterizing central obesity susceptibility that may be ancestry-specific.
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Affiliation(s)
- Anne E Justice
- Department of Population Health Sciences, Geisinger Health System, Danville, PA 17822, USA,Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27516, USA,To whom correspondence should be addressed at: Department of Population Health Sciences, Geisinger Health System, Danville, PA 17822, USA. Tel: +1 5702141009; Fax: +1 5702143071;
| | - Kristin Young
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27516, USA
| | | | - Tamar Sofer
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Misa Graff
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27516, USA
| | - Shelly Ann M Love
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27516, USA
| | - Yujie Wang
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27516, USA
| | - Yann C Klimentidis
- Department of Epidemiology and Biostatistics, University of Arizona, Tucson, AZ 85724, USA
| | - Miguel Cruz
- Unidad de Investigacion Medica en Bioquimica, Hospital de Especialidades, Centro Medico Nacional Siglo XXI (CMNSXX1)-IMSS, Mexico City 06720, Mexico
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Fernando Hartwig
- Center for Epidemiological Research, Universidade Federal de Pelotas, Pelotas 96020, Brazil
| | - Lauren Petty
- Division of Genetic Medicine, Department of Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Jie Yao
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Matthew A Allison
- Division of Preventive Medicine, Department of Family Medicine, University of California San Diego, La Jolla, CA 92093, USA
| | - Jennifer E Below
- Division of Genetic Medicine, Department of Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Thomas A Buchanan
- Department of Medicine, Keck School of Medicine and Diabetes and Obesity Research Institute, University of Southern California, Los Angeles, CA 90033, USA
| | - Yii-Der Ida Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Mark O Goodarzi
- Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Craig Hanis
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Heather M Highland
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27516, USA
| | - Willa A Hsueh
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Wexner Medical Center, The Ohio State University, Columbus, OH 43210, USA
| | - Eli Ipp
- Department of Medicine, Endocrinology, Diabetes & Metabolism, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Esteban Parra
- Department of Anthropology, University of Toronto at Mississauga, Mississauga, ON L5L 1C6, Canada
| | - Walter Palmas
- Department of Medicine, Columbia University Medical Center, New York, NY 10032, USA
| | - Leslie J Raffel
- Department of PediatrIcs, Division of Genetic and Genomic Medicine, University of California, Irvine, CA 92868, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Jingyi Tan
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Adan Valladares
- Unidad de Investigacion Medica en Bioquimica, Hospital de Especialidades, Centro Medico Nacional Siglo XXI (CMNSXX1)-IMSS, Mexico City 06720, Mexico
| | - Anny H Xiang
- Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA 91101, USA
| | - Lisa Sánchez-Johnsen
- Department of Family Medicine, Rush University Medical Center, Chicago, IL 60612, USA
| | - Carmen R Isasi
- Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, NY 10467, USA,Department of Pediatrics, Albert Einstein College of Medicine, Bronx, NY 10467, USA
| | - Kari E North
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27516, USA
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Wang K, Wu P, Wang S, Ji X, Chen D, Jiang A, Xiao W, Gu Y, Jiang Y, Zeng Y, Xu X, Li X, Tang G. Genome-wide DNA methylation analysis in Chinese Chenghua and Yorkshire pigs. BMC Genom Data 2021; 22:21. [PMID: 34134626 PMCID: PMC8207654 DOI: 10.1186/s12863-021-00977-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Accepted: 06/07/2021] [Indexed: 11/10/2022] Open
Abstract
Background The Chinese Chenghua pig (CHP) is a typical Chinese domestic fatty pig breed with superior meat quality characteristics, while the Yorkshire pig (YP) has the characteristics of fast growth and a high rate of lean meat. Long term natural selection and artificial selection resulted in great phenotypic differences between the two breeds, including growth, development, production performance, meat quality, and coat color. However, genome-wide DNA methylation differences between CHP and YP remain unclear. Results DNA methylation data were generated for muscle tissues of CHP and YP using reduced representation bisulfite sequencing (RRBS). In this study, a total of 2,416,211 CpG sites were identified. Besides, the genome-wide DNA methylation analysis revealed 722 differentially methylated regions (DMRs) and 466 differentially methylated genes (DMGs) in pairwise CHP vs. YP comparison. Six key genomic regions (Sus scrofa chromosome (SSC)1:253.47–274.23 Mb, SSC6:148.71–169.49 Mb, SSC7:0.25–9.86 Mb, SSC12:43.06–61.49 Mb, SSC14:126.43–140.95 Mb, and SSC18:49.17–54.54 Mb) containing multiple DMRs were identified, and differences of methylation patterns in these regions may be related to phenotypic differences between CHP and YP. Based on the functional analysis of DMGs, 8 DMGs (ADCY1, AGBL4, EXOC2, FUBP3, PAPPA2, PIK3R1, MGMT and MYH8) were considered as important candidate genes associated with muscle development and meat quality traits in pigs. Conclusions This study explored the difference in meat quality between CHP and YP from the epigenetic point of view, which has important reference significance for the local pork industry and pork food processing. Supplementary Information The online version contains supplementary material available at 10.1186/s12863-021-00977-0.
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Affiliation(s)
- Kai Wang
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, China
| | - Pingxian Wu
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, China
| | - Shujie Wang
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, China
| | - Xiang Ji
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, China
| | - Dong Chen
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, China
| | - Anan Jiang
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, China
| | - Weihang Xiao
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, China
| | - Yiren Gu
- Sichuan Animal Science Academy, Chengdu, 610066, China
| | - Yanzhi Jiang
- College of Life Science, Sichuan Agricultural University, Yaan, China
| | | | - Xu Xu
- Sichuan Animal Husbandry Station, Chengdu, 610041, China
| | - Xuewei Li
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, China
| | - Guoqing Tang
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, China.
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163
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Cheng Y, Li W, Gui R, Wang C, Song J, Wang Z, Wang X, Shen Y, Wang Z, Hao L. Dual Characters of GH-IGF1 Signaling Pathways in Radiotherapy and Post-radiotherapy Repair of Cancers. Front Cell Dev Biol 2021; 9:671247. [PMID: 34178997 PMCID: PMC8220142 DOI: 10.3389/fcell.2021.671247] [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: 02/24/2021] [Accepted: 05/17/2021] [Indexed: 12/02/2022] Open
Abstract
Radiotherapy remains one of the most important cancer treatment modalities. In the course of radiotherapy for tumor treatment, the incidental irradiation of adjacent tissues could not be completely avoided. DNA damage is one of the main factors of cell death caused by ionizing radiation, including single-strand (SSBs) and double-strand breaks (DSBs). The growth hormone-Insulin-like growth factor 1 (GH-IGF1) axis plays numerous roles in various systems by promoting cell proliferation and inhibiting apoptosis, supporting its effects in inducing the development of multiple cancers. Meanwhile, the GH-IGF1 signaling involved in DNA damage response (DDR) and DNA damage repair determines the radio-resistance of cancer cells subjected to radiotherapy and repair of adjacent tissues damaged by radiotherapy. In the present review, we firstly summarized the studies on GH-IGF1 signaling in the development of cancers. Then we discussed the adverse effect of GH-IGF1 signaling in radiotherapy to cancer cells and the favorable impact of GH-IGF1 signaling on radiation damage repair to adjacent tissues after irradiation. This review further summarized recent advances on research into the molecular mechanism of GH-IGF1 signaling pathway in these effects, expecting to specify the dual characters of GH-IGF1 signaling pathways in radiotherapy and post-radiotherapy repair of cancers, subsequently providing theoretical basis of their roles in increasing radiation sensitivity during cancer radiotherapy and repairing damage after radiotherapy.
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Affiliation(s)
- Yunyun Cheng
- NHC Key Laboratory of Radiobiology, School of Public Health, Jilin University, Changchun, China
| | - Wanqiao Li
- NHC Key Laboratory of Radiobiology, School of Public Health, Jilin University, Changchun, China
| | - Ruirui Gui
- NHC Key Laboratory of Radiobiology, School of Public Health, Jilin University, Changchun, China
| | - Chunli Wang
- College of Animal Science, Jilin University, Changchun, China
| | - Jie Song
- College of Animal Science, Jilin University, Changchun, China
| | - Zhaoguo Wang
- College of Animal Science, Jilin University, Changchun, China
| | - Xue Wang
- The First Hospital of Jilin University, Changchun, China
| | - Yannan Shen
- NHC Key Laboratory of Radiobiology, School of Public Health, Jilin University, Changchun, China
| | - Zhicheng Wang
- NHC Key Laboratory of Radiobiology, School of Public Health, Jilin University, Changchun, China
| | - Linlin Hao
- College of Animal Science, Jilin University, Changchun, China
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164
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Crone B, Krause AM, Hornsby WE, Willer CJ, Surakka I. Translating genetic association of lipid levels for biological and clinical application. Cardiovasc Drugs Ther 2021; 35:617-626. [PMID: 33604704 PMCID: PMC8272953 DOI: 10.1007/s10557-021-07156-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/09/2021] [Indexed: 12/11/2022]
Abstract
PURPOSE OF REVIEW This review focuses on the foundational evidence from the last two decades of lipid genetics research and describes the current status of data-driven approaches for transethnic GWAS, fine-mapping, transcriptome informed fine-mapping, and disease prediction. RECENT FINDINGS Current lipid genetics research aims to understand the association mechanisms and clinical relevance of lipid loci as well as to capture population specific associations found in global ancestries. Recent genome-wide trans-ethnic association meta-analyses have identified 118 novel lipid loci reaching genome-wide significance. Gene-based burden tests of whole exome sequencing data have identified three genes-PCSK9, LDLR, and APOB-with significant rare variant burden associated with familial dyslipidemia. Transcriptome-wide association studies discovered five previously unreported lipid-associated loci. Additionally, the predictive power of genome-wide genetic risk scores amalgamating the polygenic determinants of lipid levels can potentially be used to increase the accuracy of coronary artery disease prediction. CONCLUSIONS Lipids are one of the most successful group of traits in the era of genome-wide genetic discovery for identification of novel loci and plausible drug targets. However, a substantial fraction of lipid trait heritability remains unexplained. Further analysis of diverse ancestries and state of the art methods for association locus refinement could potentially reveal some of this missing heritability and increase the clinical application of the genomic association results.
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Affiliation(s)
- Bradley Crone
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Amelia M Krause
- Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Michigan Medicine, Ann Arbor, MI, USA
| | - Whitney E Hornsby
- Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Michigan Medicine, Ann Arbor, MI, USA
| | - Cristen J Willer
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA
- Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Michigan Medicine, Ann Arbor, MI, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Ida Surakka
- Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Michigan Medicine, Ann Arbor, MI, USA.
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165
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Liu J, Yang W, Luo H, Ma Y, Zhao H, Dan X. Brain-derived neurotrophic factor Val66Met polymorphism is associated with mild cognitive impairment in elderly patients with type 2 diabetes: a case-controlled study. Aging Clin Exp Res 2021; 33:1659-1666. [PMID: 32892314 DOI: 10.1007/s40520-020-01687-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Accepted: 08/17/2020] [Indexed: 12/14/2022]
Abstract
BACKGROUND Brain-derived neurotrophic factor (BDNF) Val66Met polymorphism is reported to be associated with cognitive dysfunction, an important comorbidity factor in patients with type 2 diabetes mellitus (T2DM), especially in elderly populations, however, the underlying pathophysiological mechanisms are unclear. AIM This study was performed to investigate the association between BDNF Val66Met polymorphism and mild cognitive impairment (MCI) in elderly patients with T2DM. METHODS In total, 105 MCI and 105 normal cognition controls of T2DM patients were enrolled; all of the patients underwent neuropsychological assessments. BDNF Val66Met polymorphism was genotyped via TaqMan SNP genotyping assay. Data from clinical and laboratory-based examinations were collected. RESULTS The frequency of the BDNF Met allele was significantly higher in the MCI group than in the controls. Multiple regression analysis indicated an association of the Met allele with MCI in patients with T2DM (OR = 2.54; 95% CI 1.33-4.84; p = 0.005). Stratified by educational level, the BDNF Met allele was significantly associated with MCI in elderly T2DM patients (OR = 3.29; 95% CI 1.26-8.57; p = 0.015) among the group of low educational levels (< 12 years); however, the association was insignificant among those with higher educational levels. DISCUSSION BDNF Met allele carriers showed a higher frequency of MCI than Val/Val homozygotes in elderly T2DM patients. However, this association was only significant in patients with low education levels. CONCLUSION BDNF Val66Met polymorphism may have a potential role in MCI in elderly T2DM patients, especially those with low educational levels.
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Affiliation(s)
- Jia Liu
- Department of Geriatric Medicine, Xuanwu Hospital, The Capital Medical University, 45 Changchun Street, Xicheng District, Beijing, 100053, China
| | - Wei Yang
- Department of Geriatric Medicine, Xuanwu Hospital, The Capital Medical University, 45 Changchun Street, Xicheng District, Beijing, 100053, China.
| | - Hongyu Luo
- Department of Geriatric Medicine, Xuanwu Hospital, The Capital Medical University, 45 Changchun Street, Xicheng District, Beijing, 100053, China
| | - Yixin Ma
- Department of Geriatric Medicine, Xuanwu Hospital, The Capital Medical University, 45 Changchun Street, Xicheng District, Beijing, 100053, China
| | - Huan Zhao
- Department of Geriatric Medicine, Xuanwu Hospital, The Capital Medical University, 45 Changchun Street, Xicheng District, Beijing, 100053, China
| | - Xiaojuan Dan
- Department of Neurology, Xuanwu Hospital, The Capital Medical University, Beijing, China
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166
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Dissecting polygenic signals from genome-wide association studies on human behaviour. Nat Hum Behav 2021; 5:686-694. [PMID: 33986517 DOI: 10.1038/s41562-021-01110-y] [Citation(s) in RCA: 53] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Accepted: 03/31/2021] [Indexed: 02/03/2023]
Abstract
Genome-wide association studies on human behavioural traits are producing large amounts of polygenic signals with significant predictive power and potentially useful biological clues. Behavioural traits are more distal and are less directly under biological control compared with physical characteristics, which makes the associated genetic effects harder to interpret. The results of genome-wide association studies for human behaviour are likely made up of a composite of signals from different sources. While sample sizes continue to increase, we outline additional steps that need to be taken to better delineate the origin of the increasingly stronger polygenic signals. In addition to genetic effects on the traits themselves, the major sources of polygenic signals are those that are associated with correlated traits, environmental effects and ascertainment bias. Advances in statistical approaches that disentangle polygenic effects from different traits as well as extending data collection to families and social circles with better geographical coverage will probably contribute to filling the gap of knowledge between genetic effects and behavioural outcomes.
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167
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Sun C, Kovacs P, Guiu-Jurado E. Genetics of Body Fat Distribution: Comparative Analyses in Populations with European, Asian and African Ancestries. Genes (Basel) 2021; 12:genes12060841. [PMID: 34072523 PMCID: PMC8228180 DOI: 10.3390/genes12060841] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Revised: 05/26/2021] [Accepted: 05/27/2021] [Indexed: 12/16/2022] Open
Abstract
Preferential fat accumulation in visceral vs. subcutaneous depots makes obese individuals more prone to metabolic complications. Body fat distribution (FD) is regulated by genetics. FD patterns vary across ethnic groups independent of obesity. Asians have more and Africans have less visceral fat compared with Europeans. Consequently, Asians tend to be more susceptible to type 2 diabetes even with lower BMIs when compared with Europeans. To date, genome-wide association studies (GWAS) have identified more than 460 loci related to FD traits. However, the majority of these data were generated in European populations. In this review, we aimed to summarize recent advances in FD genetics with a focus on comparisons between European and non-European populations (Asians and Africans). We therefore not only compared FD-related susceptibility loci identified in three ethnicities but also discussed whether known genetic variants might explain the FD pattern heterogeneity across different ancestries. Moreover, we describe several novel candidate genes potentially regulating FD, including NID2, HECTD4 and GNAS, identified in studies with Asian populations. It is of note that in agreement with current knowledge, most of the proposed FD candidate genes found in Asians belong to the group of developmental genes.
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Affiliation(s)
- Chang Sun
- Medical Department III-Endocrinology, Nephrology, Rheumatology, University of Leipzig Medical Center, 04103 Leipzig, Germany
| | - Peter Kovacs
- Medical Department III-Endocrinology, Nephrology, Rheumatology, University of Leipzig Medical Center, 04103 Leipzig, Germany
| | - Esther Guiu-Jurado
- Medical Department III-Endocrinology, Nephrology, Rheumatology, University of Leipzig Medical Center, 04103 Leipzig, Germany
- Deutsches Zentrum für Diabetesforschung, 85764 Neuherberg, Germany
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168
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Liu J, Zhou J, Li J, Bao H. Identification of candidate genes associated with slaughter traits in F2 chicken population using genome-wide association study. Anim Genet 2021; 52:532-535. [PMID: 34028062 DOI: 10.1111/age.13079] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/29/2021] [Indexed: 12/23/2022]
Abstract
Slaughter traits are crucial economic traits of chickens. We performed a GWAS to discover critical loci and candidate genes for 21 slaughter traits in an F2 chicken population resulting from crossing Luxi gamecocks and recessive white feather broilers. We found some SNPs and genes which were significantly associated with keel length, head length, body slope length, bilateral leg weight without shin, bilateral foot weight, subcutaneous fat thickness, heart weight, muscular stomach weight and glandular stomach weight. This study provides references for further investigation of slaughter traits and molecular breeding in chicken.
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Affiliation(s)
- J Liu
- National Engineering Laboratory for Animal Breeding, Beijing Key Laboratory of Animal Genetic Improvement, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - J Zhou
- National Engineering Laboratory for Animal Breeding, Beijing Key Laboratory of Animal Genetic Improvement, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - J Li
- National Engineering Laboratory for Animal Breeding, Beijing Key Laboratory of Animal Genetic Improvement, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - H Bao
- National Engineering Laboratory for Animal Breeding, Beijing Key Laboratory of Animal Genetic Improvement, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
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169
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Cho HW, Jin HS, Eom YB. A Genome-Wide Association Study of Novel Genetic Variants Associated With Anthropometric Traits in Koreans. Front Genet 2021; 12:669215. [PMID: 34054925 PMCID: PMC8155599 DOI: 10.3389/fgene.2021.669215] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Accepted: 03/31/2021] [Indexed: 11/13/2022] Open
Abstract
Most previous genome-wide association studies (GWAS) have identified genetic variants associated with anthropometric traits. However, most of the evidence were reported in European populations. Anthropometric traits such as height and body fat distribution are significantly affected by gender and genetic factors. Here we performed GWAS involving 64,193 Koreans to identify the genetic factors associated with anthropometric phenotypes including height, weight, body mass index, waist circumference, hip circumference, and waist-to-hip ratio. We found nine novel single-nucleotide polymorphisms (SNPs) and 59 independent genetic signals in genomic regions that were reported previously. Of the 19 SNPs reported previously, eight genetic variants at RP11-513I15.6 and one genetic variant at the RP11-977G19.10 region and six Asian-specific genetic variants were newly found. We compared our findings with those of previous studies in other populations. Five overlapping genetic regions (PAN2, ANKRD52, RNF41, HGMA1, and C6orf106) had been reported previously but none of the SNPs were independently identified in the current study. Seven of the nine newly found novel loci associated with height in women revealed a statistically significant skeletal expression of quantitative trait loci. Our study provides additional insight into the genetic effects of anthropometric phenotypes in East Asians.
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Affiliation(s)
- Hye-Won Cho
- Department of Medical Sciences, Graduate School, Soonchunhyang University, Asan-si, South Korea
| | - Hyun-Seok Jin
- Department of Biomedical Laboratory Science, College of Life and Health Sciences, Hoseo University, Asan-si, South Korea
| | - Yong-Bin Eom
- Department of Medical Sciences, Graduate School, Soonchunhyang University, Asan-si, South Korea.,Department of Biomedical Laboratory Science, College of Medical Sciences, Soonchunhyang University, Asan-si, South Korea
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170
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Long-read sequencing of 3,622 Icelanders provides insight into the role of structural variants in human diseases and other traits. Nat Genet 2021; 53:779-786. [PMID: 33972781 DOI: 10.1038/s41588-021-00865-4] [Citation(s) in RCA: 158] [Impact Index Per Article: 39.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2019] [Accepted: 04/05/2021] [Indexed: 01/05/2023]
Abstract
Long-read sequencing (LRS) promises to improve the characterization of structural variants (SVs). We generated LRS data from 3,622 Icelanders and identified a median of 22,636 SVs per individual (a median of 13,353 insertions and 9,474 deletions). We discovered a set of 133,886 reliably genotyped SV alleles and imputed them into 166,281 individuals to explore their effects on diseases and other traits. We discovered an association of a rare deletion in PCSK9 with lower low-density lipoprotein (LDL) cholesterol levels, compared to the population average. We also discovered an association of a multiallelic SV in ACAN with height; we found 11 alleles that differed in the number of a 57-bp-motif repeat and observed a linear relationship between the number of repeats carried and height. These results show that SVs can be accurately characterized at the population scale using LRS data in a genome-wide non-targeted approach and demonstrate how SVs impact phenotypes.
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171
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Bouchard C. Genetics of Obesity: What We Have Learned Over Decades of Research. Obesity (Silver Spring) 2021; 29:802-820. [PMID: 33899337 DOI: 10.1002/oby.23116] [Citation(s) in RCA: 89] [Impact Index Per Article: 22.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Revised: 12/15/2020] [Accepted: 12/16/2020] [Indexed: 12/14/2022]
Abstract
There is a genetic component to human obesity that accounts for 40% to 50% of the variability in body weight status but that is lower among normal weight individuals (about 30%) and substantially higher in the subpopulation of individuals with obesity and severe obesity (about 60%-80%). The appreciation that heritability varies across classes of BMI represents an important advance. After controlling for BMI, ectopic fat and fat distribution traits are characterized by heritability levels ranging from 30% to 55%. Defects in at least 15 genes are the cause of monogenic obesity cases, resulting mostly from deficiencies in the leptin-melanocortin signaling pathway. Approximately two-thirds of the BMI heritability can be imputed to common DNA variants, whereas low-frequency and rare variants explain the remaining fraction. Diminishing allele effect size is observed as the number of obesity-associated variants expands, with most BMI-increasing or -decreasing alleles contributing only a few grams or less to body weight. Obesity-promoting alleles exert minimal effects in normal weight individuals but have larger effects in individuals with a proneness to obesity, suggesting a higher penetrance; however, it is not known whether these larger effect sizes precede obesity or are caused by an obese state. The obesity genetic risk is conditioned by thousands of DNA variants that make genetically based obesity prevention and treatment a major challenge.
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Affiliation(s)
- Claude Bouchard
- Pennington Biomedical Research Center, Baton Rouge, Louisiana, USA
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172
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Hormozdiari F, Jung J, Eskin E, J. Joo JW. MARS: leveraging allelic heterogeneity to increase power of association testing. Genome Biol 2021; 22:128. [PMID: 33931127 PMCID: PMC8086090 DOI: 10.1186/s13059-021-02353-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2020] [Accepted: 04/15/2021] [Indexed: 11/10/2022] Open
Abstract
In standard genome-wide association studies (GWAS), the standard association test is underpowered to detect associations between loci with multiple causal variants with small effect sizes. We propose a statistical method, Model-based Association test Reflecting causal Status (MARS), that finds associations between variants in risk loci and a phenotype, considering the causal status of variants, only requiring the existing summary statistics to detect associated risk loci. Utilizing extensive simulated data and real data, we show that MARS increases the power of detecting true associated risk loci compared to previous approaches that consider multiple variants, while controlling the type I error.
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Affiliation(s)
- Farhad Hormozdiari
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, 02115 MA USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Junghyun Jung
- Department of Life Science, Dongguk University-Seoul, Seoul, 04620 South Korea
| | - Eleazar Eskin
- Department of Computer Science, University of California, Los Angeles, Los Angeles, 90095 CA USA
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, 90095 CA USA
| | - Jong Wha J. Joo
- Department of Computer Science and Engineering, Dongguk University-Seoul, Seoul, 04620 South Korea
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173
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Silpa MV, König S, Sejian V, Malik PK, Nair MRR, Fonseca VFC, Maia ASC, Bhatta R. Climate-Resilient Dairy Cattle Production: Applications of Genomic Tools and Statistical Models. Front Vet Sci 2021; 8:625189. [PMID: 33996959 PMCID: PMC8117237 DOI: 10.3389/fvets.2021.625189] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Accepted: 03/15/2021] [Indexed: 01/02/2023] Open
Abstract
The current changing climate trend poses a threat to the productive efficacy and welfare of livestock across the globe. This review is an attempt to synthesize information pertaining to the applications of various genomic tools and statistical models that are available to identify climate-resilient dairy cows. The different functional and economical traits which govern milk production play a significant role in determining the cost of milk production. Thus, identification of these traits may revolutionize the breeding programs to develop climate-resilient dairy cattle. Moreover, the genotype–environment interaction also influences the performance of dairy cattle especially during a challenging situation. The recent advancement in molecular biology has led to the development of a few biotechnological tools and statistical models like next-generation sequencing (NGS), microarray technology, whole transcriptome analysis, and genome-wide association studies (GWAS) which can be used to quantify the molecular mechanisms which govern the climate resilience capacity of dairy cows. Among these, the most preferred option for researchers around the globe was GWAS as this approach jointly takes into account all the genotype, phenotype, and pedigree information of farm animals. Furthermore, selection signatures can also help to demarcate functionally important regions in the genome which can be used to detect potential loci and candidate genes that have undergone positive selection in complex milk production traits of dairy cattle. These identified biomarkers can be incorporated in the existing breeding policies using genomic selection to develop climate-resilient dairy cattle.
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Affiliation(s)
- Mullakkalparambil Velayudhan Silpa
- Institute of Animal Breeding and Genetics, Justus-Liebig-Universität Gießen, Gießen, Germany.,Center for Climate Resilient Animal Adaptation Studies, Indian Council of Agricultural Research-National Institute of Animal Nutrition and Physiology, Bangalore, India
| | - Sven König
- Institute of Animal Breeding and Genetics, Justus-Liebig-Universität Gießen, Gießen, Germany
| | - Veerasamy Sejian
- Center for Climate Resilient Animal Adaptation Studies, Indian Council of Agricultural Research-National Institute of Animal Nutrition and Physiology, Bangalore, India
| | - Pradeep Kumar Malik
- Center for Climate Resilient Animal Adaptation Studies, Indian Council of Agricultural Research-National Institute of Animal Nutrition and Physiology, Bangalore, India
| | - Mini Ravi Reshma Nair
- Center for Climate Resilient Animal Adaptation Studies, Indian Council of Agricultural Research-National Institute of Animal Nutrition and Physiology, Bangalore, India
| | - Vinicius F C Fonseca
- Innovation Group of Thermal Comfort and Animal Welfare (INOBIO-MANERA), Animal Science Department, Universidade Federal da Paraíba, Areia, Brazil.,Brain Function Research Group, Faculty of Health Sciences, School of Physiology, University of the Witwatersrand, Johannesburg, South Africa
| | - Alex Sandro Campos Maia
- Innovation Group of Thermal Comfort and Animal Welfare (INOBIO-MANERA), Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista (Unesp), São Paulo, Brazil
| | - Raghavendra Bhatta
- Center for Climate Resilient Animal Adaptation Studies, Indian Council of Agricultural Research-National Institute of Animal Nutrition and Physiology, Bangalore, India
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174
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Ayoz K, Ayday E, Cicek AE. Genome Reconstruction Attacks Against Genomic Data-Sharing Beacons. PROCEEDINGS ON PRIVACY ENHANCING TECHNOLOGIES. PRIVACY ENHANCING TECHNOLOGIES SYMPOSIUM 2021; 2021:28-48. [PMID: 34746296 PMCID: PMC8570374 DOI: 10.2478/popets-2021-0036] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Sharing genome data in a privacy-preserving way stands as a major bottleneck in front of the scientific progress promised by the big data era in genomics. A community-driven protocol named genomic data-sharing beacon protocol has been widely adopted for sharing genomic data. The system aims to provide a secure, easy to implement, and standardized interface for data sharing by only allowing yes/no queries on the presence of specific alleles in the dataset. However, beacon protocol was recently shown to be vulnerable against membership inference attacks. In this paper, we show that privacy threats against genomic data sharing beacons are not limited to membership inference. We identify and analyze a novel vulnerability of genomic data-sharing beacons: genome reconstruction. We show that it is possible to successfully reconstruct a substantial part of the genome of a victim when the attacker knows the victim has been added to the beacon in a recent update. In particular, we show how an attacker can use the inherent correlations in the genome and clustering techniques to run such an attack in an efficient and accurate way. We also show that even if multiple individuals are added to the beacon during the same update, it is possible to identify the victim's genome with high confidence using traits that are easily accessible by the attacker (e.g., eye color or hair type). Moreover, we show how a reconstructed genome using a beacon that is not associated with a sensitive phenotype can be used for membership inference attacks to beacons with sensitive phenotypes (e.g., HIV+). The outcome of this work will guide beacon operators on when and how to update the content of the beacon and help them (along with the beacon participants) make informed decisions.
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175
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Grummer JA, Whitlock MC, Schulte PM, Taylor EB. Growth genes are implicated in the evolutionary divergence of sympatric piscivorous and insectivorous rainbow trout (Oncorhynchus mykiss). BMC Ecol Evol 2021; 21:63. [PMID: 33888062 PMCID: PMC8063319 DOI: 10.1186/s12862-021-01795-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Accepted: 04/12/2021] [Indexed: 12/26/2022] Open
Abstract
Background Identifying ecologically significant phenotypic traits and the genomic mechanisms that underly them are crucial steps in understanding traits associated with population divergence. We used genome-wide data to identify genomic regions associated with key traits that distinguish two ecomorphs of rainbow trout (Oncorhynchus mykiss)—insectivores and piscivores—that coexist for the non-breeding portion of the year in Kootenay Lake, southeastern British Columbia. “Gerrards” are large-bodied, rapidly growing piscivores with high metabolic rates that spawn north of Kootenay Lake in the Lardeau River, in contrast to the insectivorous populations that are on average smaller in body size, with lower growth and metabolic rates, mainly forage on aquatic insects, and spawn in tributaries immediately surrounding Kootenay Lake. We used pool-seq data representing ~ 60% of the genome and 80 fish per population to assess the level of genomic divergence between ecomorphs and to identify and interrogate loci that may play functional or selective roles in their divergence. Results Genomic divergence was high between sympatric insectivores and piscivores (\documentclass[12pt]{minimal}
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\begin{document}$$F_{\text{ST}}$$\end{document}FST = 0.188), and in fact higher than between insectivorous populations from Kootenay Lake and the Blackwater River (\documentclass[12pt]{minimal}
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\begin{document}$$F_{\text{ST}}$$\end{document}FST = 0.159) that are > 500 km apart. A window-based \documentclass[12pt]{minimal}
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\begin{document}$$F_{\text{ST}}$$\end{document}FST analysis did not reveal “islands” of genomic differentiation; however, the window with highest \documentclass[12pt]{minimal}
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\begin{document}$$F_{\text{ST}}$$\end{document}FST estimate did include a gene associated with insulin secretion. Although we explored the use of the “Local score” approach to identify genomic outlier regions, this method was ultimately not used because simulations revealed a high false discovery rate (~ 20%). Gene ontology (GO) analysis identified several growth processes as enriched in genes occurring in the ~ 200 most divergent genomic windows, indicating many loci of small effect involved in growth and growth-related metabolic processes are associated with the divergence of these ecomorphs. Conclusion Our results reveal a high degree of genomic differentiation between piscivorous and insectivorous populations and indicate that the large body piscivorous phenotype is likely not due to one or a few loci of large effect. Rather, the piscivore phenotype may be controlled by several loci of small effect, thus highlighting the power of whole-genome resequencing in identifying genomic regions underlying population-level phenotypic divergences. Supplementary Information The online version contains supplementary material available at 10.1186/s12862-021-01795-9.
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Affiliation(s)
- Jared A Grummer
- Department of Zoology and Biodiversity Research Centre, University of British Columbia, 6270 University Blvd., Vancouver, BC, V6T 1Z4, Canada.
| | - Michael C Whitlock
- Department of Zoology and Biodiversity Research Centre, University of British Columbia, 6270 University Blvd., Vancouver, BC, V6T 1Z4, Canada
| | - Patricia M Schulte
- Department of Zoology and Biodiversity Research Centre, University of British Columbia, 6270 University Blvd., Vancouver, BC, V6T 1Z4, Canada
| | - Eric B Taylor
- Department of Zoology and Biodiversity Research Centre, University of British Columbia, 6270 University Blvd., Vancouver, BC, V6T 1Z4, Canada.,Beaty Biodiversity Museum, University of British Columbia, 6270 University Blvd., Vancouver, BC, V6T 1Z4, Canada
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176
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Cirillo F, Catellani C, Lazzeroni P, Sartori C, Street ME. The Role of MicroRNAs in Influencing Body Growth and Development. Horm Res Paediatr 2021; 93:7-15. [PMID: 31914447 DOI: 10.1159/000504669] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/18/2019] [Accepted: 11/08/2019] [Indexed: 11/19/2022] Open
Abstract
Body growth and development are regulated among others by genetic and epigenetic factors. MicroRNAs (miRNAs) are epigenetic regulators of gene expression that act at the post-transcriptional level, thereby exerting a strong influence on regulatory gene networks. Increasing studies suggest the importance of miRNAs in the regulation of the growth plate and growth hormone (GH)-insulin-like growth factor (IGF) axis during the life course in a broad spectrum of animal species, contributing to longitudinal growth. This review summarizes the role of miRNAs in regulating growth in different in vitro and in vivo models acting on GH, GH receptor (GHR), IGFs, and IGF1R genes besides current knowledge in humans, and highlights that this regulatory system is of importance for growth.
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Affiliation(s)
- Francesca Cirillo
- Department of Mother and Child, Azienda USL - IRCCS di Reggio Emilia, Reggio Emilia, Italy
| | - Cecilia Catellani
- Department of Mother and Child, Azienda USL - IRCCS di Reggio Emilia, Reggio Emilia, Italy
| | - Pietro Lazzeroni
- Department of Mother and Child, Azienda USL - IRCCS di Reggio Emilia, Reggio Emilia, Italy
| | - Chiara Sartori
- Department of Mother and Child, Azienda USL - IRCCS di Reggio Emilia, Reggio Emilia, Italy
| | - Maria Elisabeth Street
- Department of Mother and Child, Azienda USL - IRCCS di Reggio Emilia, Reggio Emilia, Italy,
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177
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Estrada K, Froelich S, Wuster A, Bauer CR, Sterling T, Clark WT, Ru Y, Trinidad M, Nguyen HP, Luu AR, Wendt DJ, Yogalingam G, Yu GK, LeBowitz JH, Cardon LR. Identifying therapeutic drug targets using bidirectional effect genes. Nat Commun 2021; 12:2224. [PMID: 33850126 PMCID: PMC8044152 DOI: 10.1038/s41467-021-21843-8] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Accepted: 02/12/2021] [Indexed: 01/15/2023] Open
Abstract
Prioritizing genes for translation to therapeutics for common diseases has been challenging. Here, we propose an approach to identify drug targets with high probability of success by focusing on genes with both gain of function (GoF) and loss of function (LoF) mutations associated with opposing effects on phenotype (Bidirectional Effect Selected Targets, BEST). We find 98 BEST genes for a variety of indications. Drugs targeting those genes are 3.8-fold more likely to be approved than non-BEST genes. We focus on five genes (IGF1R, NPPC, NPR2, FGFR3, and SHOX) with evidence for bidirectional effects on stature. Rare protein-altering variants in those genes result in significantly increased risk for idiopathic short stature (ISS) (OR = 2.75, p = 3.99 × 10-8). Finally, using functional experiments, we demonstrate that adding an exogenous CNP analog (encoded by NPPC) rescues the phenotype, thus validating its potential as a therapeutic treatment for ISS. Our results show the value of looking for bidirectional effects to identify and validate drug targets.
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Affiliation(s)
| | | | | | | | | | | | - Yuanbin Ru
- BioMarin Pharmaceutical Inc., Novato, CA, USA
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178
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Graff M, Justice AE, Young KL, Marouli E, Zhang X, Fine RS, Lim E, Buchanan V, Rand K, Feitosa MF, Wojczynski MK, Yanek LR, Shao Y, Rohde R, Adeyemo AA, Aldrich MC, Allison MA, Ambrosone CB, Ambs S, Amos C, Arnett DK, Atwood L, Bandera EV, Bartz T, Becker DM, Berndt SI, Bernstein L, Bielak LF, Blot WJ, Bottinger EP, Bowden DW, Bradfield JP, Brody JA, Broeckel U, Burke G, Cade BE, Cai Q, Caporaso N, Carlson C, Carpten J, Casey G, Chanock SJ, Chen G, Chen M, Chen YDI, Chen WM, Chesi A, Chiang CWK, Chu L, Coetzee GA, Conti DV, Cooper RS, Cushman M, Demerath E, Deming SL, Dimitrov L, Ding J, Diver WR, Duan Q, Evans MK, Falusi AG, Faul JD, Fornage M, Fox C, Freedman BI, Garcia M, Gillanders EM, Goodman P, Gottesman O, Grant SFA, Guo X, Hakonarson H, Haritunians T, Harris TB, Harris CC, Henderson BE, Hennis A, Hernandez DG, Hirschhorn JN, McNeill LH, Howard TD, Howard B, Hsing AW, Hsu YHH, Hu JJ, Huff CD, Huo D, Ingles SA, Irvin MR, John EM, Johnson KC, Jordan JM, Kabagambe EK, Kang SJ, Kardia SL, Keating BJ, Kittles RA, Klein EA, Kolb S, Kolonel LN, et alGraff M, Justice AE, Young KL, Marouli E, Zhang X, Fine RS, Lim E, Buchanan V, Rand K, Feitosa MF, Wojczynski MK, Yanek LR, Shao Y, Rohde R, Adeyemo AA, Aldrich MC, Allison MA, Ambrosone CB, Ambs S, Amos C, Arnett DK, Atwood L, Bandera EV, Bartz T, Becker DM, Berndt SI, Bernstein L, Bielak LF, Blot WJ, Bottinger EP, Bowden DW, Bradfield JP, Brody JA, Broeckel U, Burke G, Cade BE, Cai Q, Caporaso N, Carlson C, Carpten J, Casey G, Chanock SJ, Chen G, Chen M, Chen YDI, Chen WM, Chesi A, Chiang CWK, Chu L, Coetzee GA, Conti DV, Cooper RS, Cushman M, Demerath E, Deming SL, Dimitrov L, Ding J, Diver WR, Duan Q, Evans MK, Falusi AG, Faul JD, Fornage M, Fox C, Freedman BI, Garcia M, Gillanders EM, Goodman P, Gottesman O, Grant SFA, Guo X, Hakonarson H, Haritunians T, Harris TB, Harris CC, Henderson BE, Hennis A, Hernandez DG, Hirschhorn JN, McNeill LH, Howard TD, Howard B, Hsing AW, Hsu YHH, Hu JJ, Huff CD, Huo D, Ingles SA, Irvin MR, John EM, Johnson KC, Jordan JM, Kabagambe EK, Kang SJ, Kardia SL, Keating BJ, Kittles RA, Klein EA, Kolb S, Kolonel LN, Kooperberg C, Kuller L, Kutlar A, Lange L, Langefeld CD, Le Marchand L, Leonard H, Lettre G, Levin AM, Li Y, Li J, Liu Y, Liu Y, Liu S, Lohman K, Lotay V, Lu Y, Maixner W, Manson JE, McKnight B, Meng Y, Monda KL, Monroe K, Moore JH, Mosley TH, Mudgal P, Murphy AB, Nadukuru R, Nalls MA, Nathanson KL, Nayak U, N'Diaye A, Nemesure B, Neslund-Dudas C, Neuhouser ML, Nyante S, Ochs-Balcom H, Ogundiran TO, Ogunniyi A, Ojengbede O, Okut H, Olopade OI, Olshan A, Padhukasahasram B, Palmer J, Palmer CD, Palmer ND, Papanicolaou G, Patel SR, Pettaway CA, Peyser PA, Press MF, Rao DC, Rasmussen-Torvik LJ, Redline S, Reiner AP, Rhie SK, Rodriguez-Gil JL, Rotimi CN, Rotter JI, Ruiz-Narvaez EA, Rybicki BA, Salako B, Sale MM, Sanderson M, Schadt E, Schreiner PJ, Schurmann C, Schwartz AG, Shriner DA, Signorello LB, Singleton AB, Siscovick DS, Smith JA, Smith S, Speliotes E, Spitz M, Stanford JL, Stevens VL, Stram A, Strom SS, Sucheston L, Sun YV, Tajuddin SM, Taylor H, Taylor K, Tayo BO, Thun MJ, Tucker MA, Vaidya D, Van Den Berg DJ, Vedantam S, Vitolins M, Wang Z, Ware EB, Wassertheil-Smoller S, Weir DR, Wiencke JK, Williams SM, Williams LK, Wilson JG, Witte JS, Wrensch M, Wu X, Yao J, Zakai N, Zanetti K, Zemel BS, Zhao W, Zhao JH, Zheng W, Zhi D, Zhou J, Zhu X, Ziegler RG, Zmuda J, Zonderman AB, Psaty BM, Borecki IB, Cupples LA, Liu CT, Haiman CA, Loos R, Ng MCY, North KE. Discovery and fine-mapping of height loci via high-density imputation of GWASs in individuals of African ancestry. Am J Hum Genet 2021; 108:564-582. [PMID: 33713608 PMCID: PMC8059339 DOI: 10.1016/j.ajhg.2021.02.011] [Show More Authors] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2020] [Accepted: 02/09/2021] [Indexed: 01/21/2023] Open
Abstract
Although many loci have been associated with height in European ancestry populations, very few have been identified in African ancestry individuals. Furthermore, many of the known loci have yet to be generalized to and fine-mapped within a large-scale African ancestry sample. We performed sex-combined and sex-stratified meta-analyses in up to 52,764 individuals with height and genome-wide genotyping data from the African Ancestry Anthropometry Genetics Consortium (AAAGC). We additionally combined our African ancestry meta-analysis results with published European genome-wide association study (GWAS) data. In the African ancestry analyses, we identified three novel loci (SLC4A3, NCOA2, ECD/FAM149B1) in sex-combined results and two loci (CRB1, KLF6) in women only. In the African plus European sex-combined GWAS, we identified an additional three novel loci (RCCD1, G6PC3, CEP95) which were equally driven by AAAGC and European results. Among 39 genome-wide significant signals at known loci, conditioning index SNPs from European studies identified 20 secondary signals. Two of the 20 new secondary signals and none of the 8 novel loci had minor allele frequencies (MAF) < 5%. Of 802 known European height signals, 643 displayed directionally consistent associations with height, of which 205 were nominally significant (p < 0.05) in the African ancestry sex-combined sample. Furthermore, 148 of 241 loci contained ≤20 variants in the credible sets that jointly account for 99% of the posterior probability of driving the associations. In summary, trans-ethnic meta-analyses revealed novel signals and further improved fine-mapping of putative causal variants in loci shared between African and European ancestry populations.
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Affiliation(s)
- Mariaelisa Graff
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
| | - Anne E Justice
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Population Health Services, Geisinger Health, Danville, PA 17822, USA
| | - Kristin L Young
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Eirini Marouli
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK; Centre for Genomic Health, Life Sciences, Queen Mary University of London, London EC1M 6BQ, UK
| | - Xinruo Zhang
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | | | - Elise Lim
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
| | - Victoria Buchanan
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Kristin Rand
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Mary F Feitosa
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO 63108, USA
| | - Mary K Wojczynski
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO 63108, USA
| | - Lisa R Yanek
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Yaming Shao
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Rebecca Rohde
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Adebowale A Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Melinda C Aldrich
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University School of Medicine, Nashville, TN 37232, USA; Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN 37232, USA; Department of Thoracic Surgery, Vanderbilt University School of Medicine, Nashville, TN 37232, USA
| | - Matthew A Allison
- Department of Family Medicine and Public Health, University of California San Diego, La Jolla, CA 92093, USA
| | - Christine B Ambrosone
- Department of Cancer Prevention and Control, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14263, USA
| | - Stefan Ambs
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA
| | - Christopher Amos
- Department of Epidemiology, Division of Cancer Prevention and Population Sciences, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Donna K Arnett
- School of Public Health, University of Kentucky, Lexington, KY 40563, USA
| | - Larry Atwood
- Framingham Heart Study, Boston University School of Medicine, Boston, MA 02118, USA
| | - Elisa V Bandera
- Department of Population Science, Rutgers Cancer Institute of New Jersey, New Brunswick, NJ 08903, USA
| | - Traci Bartz
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA 98101, USA; Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Diane M Becker
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Sonja I Berndt
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA
| | - Leslie Bernstein
- Division of Biomarkers of Early Detection and Prevention, Department of Population Sciences, Beckman Research Institute of the City of Hope, Duarte, CA 91010, USA
| | - Lawrence F Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - William J Blot
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University School of Medicine, Nashville, TN 37232, USA; Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN 37232, USA; International Epidemiology Institute, Rockville, MD 20850, USA
| | - Erwin P Bottinger
- The Charles R. Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Donald W Bowden
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA; Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA; Center for Diabetes Research, Wake Forest school of Medicine, Winston-Salem, NC 27157, USA
| | - Jonathan P Bradfield
- Center for Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA 98101, USA
| | - Ulrich Broeckel
- Department of Pediatrics, Section of Genomic Pediatrics, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Gregory Burke
- Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA
| | - Brian E Cade
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA 02115, USA; Harvard Medical School, Boston, MA 02115, USA
| | - Qiuyin Cai
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University School of Medicine, Nashville, TN 37232, USA; Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN 37232, USA
| | - Neil Caporaso
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA
| | - Chris Carlson
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - John Carpten
- Department of Translational Genomics, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Graham Casey
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA; Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA 90033, USA
| | - Stephen J Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA
| | - Guanjie Chen
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Minhui Chen
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Yii-Der I Chen
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Wei-Min Chen
- Department of Public Health Sciences and Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA 22908, USA
| | - Alessandra Chesi
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - 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
| | - Lisa Chu
- Cancer Prevention Institute of California, Fremont, CA 94538, USA
| | - Gerry A Coetzee
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA; Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA 90033, USA; Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, LA 90033, USA
| | - David V Conti
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Richard S Cooper
- Department of Public Health Sciences, Stritch School of Medicine, Loyola University Chicago Stritch School of Medicine, Maywood, IL 60153, USA
| | - Mary Cushman
- Department of Medicine, University of Vermont College of Medicine, Burlington, VT 05405, USA
| | - Ellen Demerath
- Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, MN 55455, USA
| | - Sandra L Deming
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University School of Medicine, Nashville, TN 37232, USA; Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN 37232, USA
| | - Latchezar Dimitrov
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA
| | - Jingzhong Ding
- Section on Gerontology and Geriatric Medicine, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA
| | - W Ryan Diver
- Epidemiology Research Program, American Cancer Society, Atlanta, GA 30303, USA
| | - Qing Duan
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Michele K Evans
- Health Disparities Research Section, Clinical Research Branch, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
| | - Adeyinka G Falusi
- Institute for Medical Research and Training, University of Ibadan, Ibadan, Nigeria
| | - Jessica D Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI 48104, USA
| | - Myriam Fornage
- Center for Human Genetics, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Caroline Fox
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA; Framingham Heart Study, Framingham, MA 01702, USA; Division of Endocrinology and Metabolism, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Barry I Freedman
- Department of Internal Medicine, Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA
| | - Melissa Garcia
- National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
| | - Elizabeth M Gillanders
- Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD 20892, USA
| | - Phyllis Goodman
- SWOG Statistical Center, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Omri Gottesman
- The Charles R. Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Struan F A Grant
- Center for Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia Research Institute, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Pediatrics, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Hakon Hakonarson
- Center for Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Pediatrics, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA
| | - Talin Haritunians
- Medical Genetics Institute, Cedars Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Tamara B Harris
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Bethesda, MD 20892, USA
| | - Curtis C Harris
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA
| | - Brian E Henderson
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA; Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA 90033, USA
| | - Anselm Hennis
- Department of Preventive Medicine, Stony Brook University, Stony Brook, NY 11794, USA; Chronic Disease Research Centre and Faculty of Medical Sciences, University of West Indies, Bridgetown, Barbados; Ministry of Health, Bridgetown, Barbados
| | - Dena G Hernandez
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA
| | - Joel N Hirschhorn
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, MA 02115, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Lorna Haughton McNeill
- Department of Health Disparities Research, Division of OVP, Cancer Prevention and Population Sciences, and Center for Community Implementation and Dissemination Research, Duncan Family Institute, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Timothy D Howard
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA
| | | | - Ann W Hsing
- Cancer Prevention Institute of California, Fremont, CA 94538, USA; Department of Medicine, Stanford Prevention Research Center and Cancer Institute, Stanford, CA 94305, USA
| | - Yu-Han H Hsu
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, MA 02115, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Jennifer J Hu
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, USA; Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Chad D Huff
- Department of Epidemiology, Division of Cancer Prevention and Population Sciences, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Dezheng Huo
- Department of Public Health Sciences, University of Chicago, Chicago, IL 60637, USA
| | - Sue A Ingles
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA; Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA 90033, USA
| | - Marguerite R Irvin
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - Esther M John
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA 94304, USA
| | - Karen C Johnson
- Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Joanne M Jordan
- Thurston Arthritis Research Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Edmond K Kabagambe
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - Sun J Kang
- Genetic Epidemiology Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA
| | - Sharon L Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Brendan J Keating
- Institute for Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Rick A Kittles
- Division of Health Equities, Department of Population Sciences, City of Hope Medical Center, Duarte, CA 91010, USA
| | - Eric A Klein
- Department of Urology, Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Suzanne Kolb
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Laurence N Kolonel
- Epidemiology Program, Cancer Research Center, University of Hawaii Cancer Center, Honolulu, HI 96813, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Lewis Kuller
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Abdullah Kutlar
- Sickle Cell Center, Medical College of Georgia, Augusta University, Augusta, GA 30912, USA
| | - Leslie Lange
- Division of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Carl D Langefeld
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA
| | - Loic Le Marchand
- Epidemiology Program, Cancer Research Center, University of Hawaii Cancer Center, Honolulu, HI 96813, USA
| | - Hampton Leonard
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA; Data Tecnica Int'l, LLC, Glen Echo, MD 20812, USA
| | - Guillaume Lettre
- Montreal Heart Institute, Montréal, QC H1T 1C8, Canada; Department of Medicine, Université de Montréal, Montréal, QC H1T 1C8, Canada
| | - Albert M Levin
- Department of Public Health Sciences, Henry Ford Health System, Detroit, MI 48202, USA
| | - Yun Li
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jin Li
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Palo Alto, CA 94304, USA
| | - Yongmei Liu
- Department of Medicine, Division of Cardiology, Duke Molecular Physiology Institute, Duke University Medical Center, Durham, NC 27701, USA
| | - Youfang Liu
- Thurston Arthritis Research Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Simin Liu
- Department of Epidemiology, Brown University, Providence, RI 02912, USA
| | - Kurt Lohman
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA
| | - Vaneet Lotay
- The Charles R. Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Yingchang Lu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University School of Medicine, Nashville, TN 37232, USA; The Charles R. Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - William Maixner
- Center for Translational Pain Medicine, Department of Anesthesiology, Duke University Medical Center, Durham, NC 27710, USA
| | - JoAnn E Manson
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Barbara McKnight
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA 98101, USA; Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Yan Meng
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Keri L Monda
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; The Center for Observational Research, Amgen, Inc., Thousand Oaks, CA 91320, USA
| | - Kris Monroe
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Jason H Moore
- Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Thomas H Mosley
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - Poorva Mudgal
- Center for Diabetes Research, Wake Forest school of Medicine, Winston-Salem, NC 27157, USA
| | - Adam B Murphy
- Department of Urology, Northwestern University, Chicago, IL 60611, USA
| | - Rajiv Nadukuru
- The Charles R. Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Mike A Nalls
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA; Data Tecnica Int'l, LLC, Glen Echo, MD 20812, USA
| | | | - Uma Nayak
- Department of Public Health Sciences and Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA 22908, USA
| | | | - Barbara Nemesure
- Department of Preventive Medicine, Stony Brook University, Stony Brook, NY 11794, USA
| | | | - Marian L Neuhouser
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Sarah Nyante
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA
| | - Heather Ochs-Balcom
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, The State University of New York, Buffalo, NY 14214, USA
| | - Temidayo O Ogundiran
- Department of Surgery, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Adesola Ogunniyi
- Department of Medicine, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Oladosu Ojengbede
- Centre for Population and Reproductive Health, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Hayrettin Okut
- Center for Diabetes Research, Wake Forest school of Medicine, Winston-Salem, NC 27157, USA
| | - Olufunmilayo I Olopade
- Center for Clinical Cancer Genetics and Global Health, University of Chicago Medical Center, Chicago, IL 60637, USA
| | - Andrew Olshan
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA
| | - Badri Padhukasahasram
- Center for Health Policy and Health Services Research, Henry Ford Health System, Detroit, MI 48202, USA
| | - Julie Palmer
- Slone Epidemiology Center, Boston University School of Medicine, Boston, MA 02118, USA
| | - Cameron D Palmer
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, MA 02115, USA
| | - Nicholette D Palmer
- Department of Biochemistry, School of Medicine, Wake Forest University, Winston-Salem, NC 27157, USA
| | - George Papanicolaou
- Division of Cardiovascular Sciences, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Sanjay R Patel
- Department of Medicine, University of Pittsburgh, Pittsburgh, PA 15260, USA
| | - Curtis A Pettaway
- Department of Urology, The University of Texas M.D. Anderson Cancer Center, Houston, TX 77030, USA
| | - Patricia A Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Michael F Press
- Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA 90033, USA
| | - D C Rao
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Laura J Rasmussen-Torvik
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Susan Redline
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Alex P Reiner
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Suhn K Rhie
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA; Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA 90033, USA
| | - Jorge L Rodriguez-Gil
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, USA; Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Charles N Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Edward A Ruiz-Narvaez
- Department of Nutritional Sciences, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA
| | - Benjamin A Rybicki
- Department of Public Health Sciences, Henry Ford Health System, Detroit, MI 48202, USA
| | - Babatunde Salako
- Centre for Population and Reproductive Health, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Michele M Sale
- Department of Public Health Sciences and Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA 22908, USA
| | - Maureen Sanderson
- Department of Family and Community Medicine, Meharry Medical College, Nashville, TN 37208, USA
| | - Eric Schadt
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Pamela J Schreiner
- Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, MN 55455, USA
| | - Claudia Schurmann
- The Charles R. Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Ann G Schwartz
- Department of Oncology, Wayne State University School of Medicine, Detroit, MI 48201, USA; Karmanos Cancer Institute, Detroit, MI 48201, USA
| | - Daniel A Shriner
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Lisa B Signorello
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University School of Medicine, Nashville, TN 37232, USA; Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN 37232, USA; International Epidemiology Institute, Rockville, MD 20850, USA
| | - Andrew B Singleton
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA
| | | | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA; Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI 48104, USA
| | - Shad Smith
- Center for Translational Pain Medicine, Department of Anesthesiology, Duke University Medical Center, Durham, NC 27710, USA
| | - Elizabeth Speliotes
- Division of Gastroenterology and Hepatology, University of Michigan Health System, Ann Arbor, MI 48109, USA; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Margaret Spitz
- Department of Epidemiology, Division of Cancer Prevention and Population Sciences, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Janet L Stanford
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA; Department of Epidemiology, University of Washington School of Public Health, Seattle, WA 98195, USA
| | - Victoria L Stevens
- Epidemiology Research Program, American Cancer Society, Atlanta, GA 30303, USA
| | - Alex Stram
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Sara S Strom
- Department of Epidemiology, Division of Cancer Prevention and Population Sciences, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Lara Sucheston
- Department of Cancer Prevention and Control, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14263, USA
| | - Yan V Sun
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Salman M Tajuddin
- National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
| | - Herman Taylor
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - Kira Taylor
- Department of Epidemiology and Population Health, School of Public Health and Information Sciences, University of Louisville, Louisville, KY 40202, USA
| | - Bamidele O Tayo
- Department of Public Health Sciences, Stritch School of Medicine, Loyola University Chicago Stritch School of Medicine, Maywood, IL 60153, USA
| | - Michael J Thun
- Epidemiology Research Program, American Cancer Society, Atlanta, GA 30303, USA
| | - Margaret A Tucker
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA
| | - Dhananjay Vaidya
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
| | - David J Van Den Berg
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA; Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA 90033, USA
| | - Sailaja Vedantam
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, MA 02115, USA
| | - Mara Vitolins
- Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA
| | - Zhaoming Wang
- Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Erin B Ware
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA; Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI 48104, USA
| | - Sylvia Wassertheil-Smoller
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - David R Weir
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI 48104, USA
| | - John K Wiencke
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Scott M Williams
- Departments of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH 44106, USA
| | - L Keoki Williams
- Center for Health Policy and Health Services Research, Henry Ford Health System, Detroit, MI 48202, USA; Department of Internal Medicine, Henry Ford Health System, Detroit, MI 48202, USA
| | - James G Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - John S Witte
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Urology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Margaret Wrensch
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Xifeng Wu
- Department of Epidemiology, Division of Cancer Prevention and Population Sciences, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Jie Yao
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Neil Zakai
- Department of Medicine, University of Vermont College of Medicine, Burlington, VT 05405, USA
| | - Krista Zanetti
- Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD 20892, USA
| | - Babette S Zemel
- Department of Pediatrics, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA; Division of Gastroenterology, Hepatology and Nutrition, The Children's Hospital of Philadelphia, Philadelphia, PA 19146, USA
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Jing Hua Zhao
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge CB2 0QQ, UK
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University School of Medicine, Nashville, TN 37232, USA; Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN 37232, USA
| | - Degui Zhi
- School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Jie Zhou
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Xiaofeng Zhu
- Departments of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Regina G Ziegler
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA
| | - Joe Zmuda
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Alan B Zonderman
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Bethesda, MD 20892, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA 98101, USA
| | - Ingrid B Borecki
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO 63108, USA; BioData Catalyst Program, National Heart, Lung, and Blood Institute, Bethesda, MD 20892, USA
| | - L Adrienne Cupples
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA; Framingham Heart Study, Boston University School of Medicine, Boston, MA 02118, USA
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
| | - Christopher A Haiman
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA; Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA 90033, USA
| | - Ruth Loos
- The Charles R. Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; The Mindich Child Health Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Maggie C Y Ng
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA; Center for Diabetes Research, Wake Forest school of Medicine, Winston-Salem, NC 27157, USA
| | - Kari E North
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
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Silberstein M, Nesbit N, Cai J, Lee PH. Pathway analysis for genome-wide genetic variation data: Analytic principles, latest developments, and new opportunities. J Genet Genomics 2021; 48:173-183. [PMID: 33896739 PMCID: PMC8286309 DOI: 10.1016/j.jgg.2021.01.007] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Revised: 01/24/2021] [Accepted: 01/25/2021] [Indexed: 12/23/2022]
Abstract
Pathway analysis, also known as gene-set enrichment analysis, is a multilocus analytic strategy that integrates a priori, biological knowledge into the statistical analysis of high-throughput genetics data. Originally developed for the studies of gene expression data, it has become a powerful analytic procedure for in-depth mining of genome-wide genetic variation data. Astonishing discoveries were made in the past years, uncovering genes and biological mechanisms underlying common and complex disorders. However, as massive amounts of diverse functional genomics data accrue, there is a pressing need for newer generations of pathway analysis methods that can utilize multiple layers of high-throughput genomics data. In this review, we provide an intellectual foundation of this powerful analytic strategy, as well as an update of the state-of-the-art in recent method developments. The goal of this review is threefold: (1) introduce the motivation and basic steps of pathway analysis for genome-wide genetic variation data; (2) review the merits and the shortcomings of classic and newly emerging integrative pathway analysis tools; and (3) discuss remaining challenges and future directions for further method developments.
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Affiliation(s)
- Micah Silberstein
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Nicholas Nesbit
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Jacquelyn Cai
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Phil H Lee
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Department of Psychiatry, Harvard Medical School, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
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180
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Herman JD, Wang C, Loos C, Yoon H, Rivera J, Dieterle ME, Haslwanter D, Jangra RK, Bortz RH, Bar KJ, Julg B, Chandran K, Lauffenburger D, Pirofski LA, Alter G. Functional Antibodies in COVID-19 Convalescent Plasma. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2021:2021.03.08.21253157. [PMID: 33758875 PMCID: PMC7987034 DOI: 10.1101/2021.03.08.21253157] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/14/2023]
Abstract
In the absence of an effective vaccine or monoclonal therapeutic, transfer of convalescent plasma (CCP) was proposed early in the SARS-CoV-2 pandemic as an easily accessible therapy. However, despite the global excitement around this historically valuable therapeutic approach, results from CCP trials have been mixed and highly debated. Unlike other therapeutic interventions, CCP represents a heterogeneous drug. Each CCP unit is unique and collected from an individual recovered COVID-19 patient, making the interpretation of therapeutic benefit more complicated. While the prevailing view in the field would suggest that it is administration of neutralizing antibodies via CCP that centrally provides therapeutic benefit to newly infected COVID-19 patients, many hospitalized COVID-19 patients already possess neutralizing antibodies. Importantly, the therapeutic benefit of antibodies can extend far beyond their simple ability to bind and block infection, especially related to their ability to interact with the innate immune system. In our work we deeply profiled the SARS-CoV-2-specific Fc-response in CCP donors, along with the recipients prior to and after CCP transfer, revealing striking SARS-CoV-2 specific Fc-heterogeneity across CCP units and their recipients. However, CCP units possessed more functional antibodies than acute COVID-19 patients, that shaped the evolution of COVID-19 patient humoral profiles via distinct immunomodulatory effects that varied by pre-existing SARS-CoV-2 Spike (S)-specific IgG titers in the patients. Our analysis identified surprising influence of both S and Nucleocapsid (N) specific antibody functions not only in direct antiviral activity but also in anti-inflammatory effects. These findings offer insights for more comprehensive interpretation of correlates of immunity in ongoing large scale CCP trials and for the design of next generation therapeutic design.
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Affiliation(s)
- Jonathan D. Herman
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA
- Division of Infectious Disease, Brigham and Women’s Hospital, Boston, MA, USA
| | - Chuangqi Wang
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Carolin Loos
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Hyunah Yoon
- Division of Infectious Diseases, Department of Medicine. Albert Einstein College of Medicine and Montefiore Medical Center, Bronx, NY,USA
| | - Johanna Rivera
- Division of Infectious Diseases, Department of Medicine. Albert Einstein College of Medicine and Montefiore Medical Center, Bronx, NY,USA
- Department of Microbiology and Immunology. Albert Einstein College of Medicine, Bronx, NY, USA
| | - M. Eugenia Dieterle
- Department of Microbiology and Immunology. Albert Einstein College of Medicine, Bronx, NY, USA
| | - Denise Haslwanter
- Department of Microbiology and Immunology. Albert Einstein College of Medicine, Bronx, NY, USA
| | - Rohit K. Jangra
- Department of Microbiology and Immunology. Albert Einstein College of Medicine, Bronx, NY, USA
| | - Robert H. Bortz
- Department of Microbiology and Immunology. Albert Einstein College of Medicine, Bronx, NY, USA
| | - Katharine J. Bar
- Department of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Boris Julg
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA
| | - Kartik Chandran
- Department of Microbiology and Immunology. Albert Einstein College of Medicine, Bronx, NY, USA
| | - Douglas Lauffenburger
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Liise-anne Pirofski
- Division of Infectious Diseases, Department of Medicine. Albert Einstein College of Medicine and Montefiore Medical Center, Bronx, NY,USA
- Department of Microbiology and Immunology. Albert Einstein College of Medicine, Bronx, NY, USA
| | - Galit Alter
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA
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181
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Gates AJ, Gysi DM, Kellis M, Barabási AL. A wealth of discovery built on the Human Genome Project - by the numbers. Nature 2021; 590:212-215. [PMID: 33568828 DOI: 10.1038/d41586-021-00314-6] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
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182
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Foss-Skiftesvik J, Hagen CM, Mathiasen R, Adamsen D, Bækvad-Hansen M, Børglum AD, Nordentoft M, Werge T, Christiansen M, Schmiegelow K, Juhler M, Mortensen PB, Hougaard DM, Bybjerg-Grauholm J. Genome-wide association study across pediatric central nervous system tumors implicates shared predisposition and points to 1q25.2 (PAPPA2) and 11p12 (LRRC4C) as novel candidate susceptibility loci. Childs Nerv Syst 2021; 37:819-830. [PMID: 33226468 DOI: 10.1007/s00381-020-04946-3] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Accepted: 10/26/2020] [Indexed: 12/31/2022]
Abstract
INTRODUCTION Central nervous system (CNS) tumors constitute the most common form of solid neoplasms in children, but knowledge on genetic predisposition is sparse. In particular, whether susceptibility attributable to common variants is shared across CNS tumor types in children has not been investigated. The purpose of this study was to explore potential common genetic risk variants exhibiting pleiotropic effects across pediatric CNS tumors. We also investigated whether such susceptibility differs between early and late onset of disease. METHOD A Danish nationwide genome-wide association study (GWAS) of 1,097 consecutive patients (< 15 years of age) with CNS tumors and a cohort of 4,745 population-based controls. RESULTS For both the overall cohort and patients diagnosed after the age of four, the strongest association was rs12064625 which maps to PAPPA2 at 1q25.2 (p = 3.400 × 10-7 and 9.668 × 10-8, respectively). PAPPA2 regulates local bioavailability of insulin-like growth factor I (IGF-I). IGF-I is fundamental to CNS development and is involved in tumorigenesis across a wide range of different cancers. For the younger children, the strongest association was provided by rs11036373 mapping to LRRC4C at 11p12 (p = 7.620 × 10-7), which encoded protein acts as an axon guidance molecule during CNS development and has not formerly been associated with brain tumors. DISCUSSION This GWAS indicates shared susceptibility attributable to common variants across pediatric CNS tumor types. Variations in genetic loci with roles in CNS development appear to be involved, possibly via altered IGF-I related pathways.
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Affiliation(s)
- Jon Foss-Skiftesvik
- Department of Neurosurgery, Copenhagen University Hospital Rigshospitalet, Blegdamsvej 9, 2100, Copenhagen Ø, Denmark.
- Danish Center for Neonatal Screening, Department of Congenital Diseases, Statens Serum Institut, Copenhagen, Denmark.
- Department of Pediatrics and Adolescent Medicine, Rigshospitalet University Hospital, Copenhagen, Denmark.
| | - Christian Munch Hagen
- Danish Center for Neonatal Screening, Department of Congenital Diseases, Statens Serum Institut, Copenhagen, Denmark
- Institute of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Copenhagen, Denmark
| | - René Mathiasen
- Department of Pediatrics and Adolescent Medicine, Rigshospitalet University Hospital, Copenhagen, Denmark
| | - Dea Adamsen
- Danish Center for Neonatal Screening, Department of Congenital Diseases, Statens Serum Institut, Copenhagen, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Copenhagen, Denmark
| | - Marie Bækvad-Hansen
- Danish Center for Neonatal Screening, Department of Congenital Diseases, Statens Serum Institut, Copenhagen, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Copenhagen, Denmark
| | - Anders D Børglum
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Copenhagen, Denmark
- Department of Biomedicine, Aarhus University and Centre for Integrative Sequencing, iSEQ, Aarhus, Denmark
- Aarhus Genome Center, Aarhus, Denmark
| | - Merete Nordentoft
- Institute of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Copenhagen, Denmark
- Mental Health Centre Copenhagen, Copenhagen University Hospital, Copenhagen, Denmark
| | - Thomas Werge
- Institute of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Copenhagen, Denmark
- Institute of Biological Psychiatry, Mental Health Centre Sct. Hans, Mental Health Services Copenhagen, Roskilde, Denmark
| | - Michael Christiansen
- Danish Center for Neonatal Screening, Department of Congenital Diseases, Statens Serum Institut, Copenhagen, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Copenhagen, Denmark
| | - Kjeld Schmiegelow
- Department of Pediatrics and Adolescent Medicine, Rigshospitalet University Hospital, Copenhagen, Denmark
- Institute of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Marianne Juhler
- Department of Neurosurgery, Copenhagen University Hospital Rigshospitalet, Blegdamsvej 9, 2100, Copenhagen Ø, Denmark
- Institute of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Neurosurgery, Aarhus University Hospital, Aarhus, Denmark
| | - Preben Bo Mortensen
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Copenhagen, Denmark
- National Centre for Register-based Research, Department of Economics and Business Economics, Aarhus University, Aarhus, Denmark
- Centre for Integrated Register-Based Research, Aarhus University, Aarhus, Denmark
| | - David Michael Hougaard
- Danish Center for Neonatal Screening, Department of Congenital Diseases, Statens Serum Institut, Copenhagen, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Copenhagen, Denmark
| | - Jonas Bybjerg-Grauholm
- Danish Center for Neonatal Screening, Department of Congenital Diseases, Statens Serum Institut, Copenhagen, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Copenhagen, Denmark
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183
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Mekić S, Gunn DA, Jacobs LC, Hijnen D, Ikram MA, Mayes AE, Nijsten T, Pardo LM. Genetic Susceptibility to Dry Skin in a General Middle-Aged to Elderly Population: A GWAS. J Invest Dermatol 2021; 141:2077-2079.e5. [PMID: 33640410 DOI: 10.1016/j.jid.2020.12.033] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2020] [Revised: 12/29/2020] [Accepted: 12/30/2020] [Indexed: 12/01/2022]
Affiliation(s)
- Selma Mekić
- Department of Dermatology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - David A Gunn
- Unilever Research and Development, Colworth Science Park, Sharnbrook, United Kingdom
| | - Leonie C Jacobs
- Department of Dermatology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - DirkJan Hijnen
- Department of Dermatology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Andrew E Mayes
- Unilever Research and Development, Colworth Science Park, Sharnbrook, United Kingdom
| | - Tamar Nijsten
- Department of Dermatology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands.
| | - Luba M Pardo
- Department of Dermatology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
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184
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Chen Z, Boehnke M, Wen X, Mukherjee B. Revisiting the genome-wide significance threshold for common variant GWAS. G3 (BETHESDA, MD.) 2021; 11:jkaa056. [PMID: 33585870 PMCID: PMC8022962 DOI: 10.1093/g3journal/jkaa056] [Citation(s) in RCA: 89] [Impact Index Per Article: 22.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/18/2020] [Accepted: 11/05/2020] [Indexed: 11/23/2022]
Abstract
Over the last decade, GWAS meta-analyses have used a strict P-value threshold of 5 × 10-8 to classify associations as significant. Here, we use our current understanding of frequently studied traits including lipid levels, height, and BMI to revisit this genome-wide significance threshold. We compare the performance of studies using the P = 5 × 10-8 threshold in terms of true and false positive rate to other multiple testing strategies: (1) less stringent P-value thresholds, (2) controlling the FDR with the Benjamini-Hochberg and Benjamini-Yekutieli procedure, and (3) controlling the Bayesian FDR with posterior probabilities. We applied these procedures to re-analyze results from the Global Lipids and GIANT GWAS meta-analysis consortia and supported them with extensive simulation that mimics the empirical data. We observe in simulated studies with sample sizes ∼20,000 and >120,000 that relaxing the P-value threshold to 5 × 10-7 increased discovery at the cost of 18% and 8% of additional loci being false positive results, respectively. FDR and Bayesian FDR are well controlled for both sample sizes with a few exceptions that disappear under a less stringent definition of true positives and the two approaches yield similar results. Our work quantifies the value of using a relaxed P-value threshold in large studies to increase their true positive discovery but also show the excess false positive rates due to such actions in modest-sized studies. These results may guide investigators considering different thresholds in replication studies and downstream work such as gene-set enrichment or pathway analysis. Finally, we demonstrate the viability of FDR-controlling procedures in GWAS.
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Affiliation(s)
- Zhongsheng Chen
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109-2029, USA
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109-2029, USA
| | - Xiaoquan Wen
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109-2029, USA
| | - Bhramar Mukherjee
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109-2029, USA
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185
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Wang X, Zhang H, Huang M, Tang J, Yang L, Yu Z, Li D, Li G, Jiang Y, Sun Y, Wei S, Xu P, Ren J. Whole-genome SNP markers reveal conservation status, signatures of selection, and introgression in Chinese Laiwu pigs. Evol Appl 2021; 14:383-398. [PMID: 33664783 PMCID: PMC7896721 DOI: 10.1111/eva.13124] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2020] [Revised: 08/18/2020] [Accepted: 08/19/2020] [Indexed: 12/18/2022] Open
Abstract
Laiwu pigs are a Chinese indigenous breed that is renowned for its exceptionally high intramuscular fat content (average greater than 6%), providing an excellent genetic resource for the genetic improvement of meat quality of modern commercial pigs. To uncover genetic diversity, population structure, signature of selection, and potential exotic introgression in this breed, we sampled 238 Laiwu pigs from a state-supported conservation population and genotyped these individuals using GeneSeek 80K SNP BeadChip. We then conducted in-depth population genetics analyses for the Laiwu pig in a context of 1,116 pigs from 42 Eurasian diverse breeds. First, we show that the current Laiwu population has more abundant genetic diversity than the population of 18 years ago likely due to gene flow from European commercial breeds. Both neighbor-joining (NJ) and principal component analyses indicate the introgression of European haplotypes into Laiwu pigs. The admixture analysis reveals that an average 26.66% of Laiwu genetic components are of European origin. Then, we assigned the tested individuals to different families according to their clustering patterns in the NJ tree and proposed a family-based conservation strategy to reduce the risk of inbreeding depression in Laiwu pigs. Next, we explored three statistics (ROH and iHS and EigenGWAS) to identify a list of candidate genes for fat deposition, reproduction, and growth in Laiwu pigs. Last, we detected a strong signature of introgression from European pigs into Laiwu pigs at the GPC6 locus that regulates the growth of developing long bones. Further association analyses indicate that the introgressed GPC6 haplotype likely contributed to the improvement of growth performance in Laiwu pigs. Altogether, this study not only benefits the better conservation of the Laiwu pig, but also advances our knowledge of the poorly understood effect of human-mediated introgression on phenotypic traits in Chinese indigenous pigs.
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Affiliation(s)
- Xiaopeng Wang
- Guangdong Laboratory for Lingnan Modern AgricultureCollege of Animal ScienceSouth China Agricultural UniversityGuangzhouChina
| | - Hui Zhang
- Guangdong Laboratory for Lingnan Modern AgricultureCollege of Animal ScienceSouth China Agricultural UniversityGuangzhouChina
| | - Min Huang
- Guangdong Laboratory for Lingnan Modern AgricultureCollege of Animal ScienceSouth China Agricultural UniversityGuangzhouChina
| | - Jianhong Tang
- Guangdong Laboratory for Lingnan Modern AgricultureCollege of Animal ScienceSouth China Agricultural UniversityGuangzhouChina
| | - Lijuan Yang
- Guangdong Laboratory for Lingnan Modern AgricultureCollege of Animal ScienceSouth China Agricultural UniversityGuangzhouChina
| | - Zhiqiang Yu
- Guangdong Laboratory for Lingnan Modern AgricultureCollege of Animal ScienceSouth China Agricultural UniversityGuangzhouChina
| | - Desen Li
- Guangdong Laboratory for Lingnan Modern AgricultureCollege of Animal ScienceSouth China Agricultural UniversityGuangzhouChina
| | - Guixin Li
- Guangdong Laboratory for Lingnan Modern AgricultureCollege of Animal ScienceSouth China Agricultural UniversityGuangzhouChina
| | - Yongchuang Jiang
- Guangdong Laboratory for Lingnan Modern AgricultureCollege of Animal ScienceSouth China Agricultural UniversityGuangzhouChina
| | - Yanxiao Sun
- Jinan Conservation Farm for Laiwu PigsJinanChina
| | - Shudong Wei
- Jinan Conservation Farm for Laiwu PigsJinanChina
| | - Pan Xu
- School of Animal Science and TechnologyJiangsu Agri‐animal Husbandry Vocational CollegeTaizhouChina
| | - Jun Ren
- Guangdong Laboratory for Lingnan Modern AgricultureCollege of Animal ScienceSouth China Agricultural UniversityGuangzhouChina
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186
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A hypomorphic variant in EYS detected by genome-wide association study contributes toward retinitis pigmentosa. Commun Biol 2021; 4:140. [PMID: 33514863 PMCID: PMC7846782 DOI: 10.1038/s42003-021-01662-9] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2020] [Accepted: 01/06/2021] [Indexed: 12/26/2022] Open
Abstract
The genetic basis of Japanese autosomal recessive retinitis pigmentosa (ARRP) remains largely unknown. Herein, we applied a 2-step genome-wide association study (GWAS) in 640 Japanese patients. Meta-GWAS identified three independent peaks at P < 5.0 × 10−8, all within the major ARRP gene EYS. Two of the three were each in linkage disequilibrium with a different low frequency variant (allele frequency < 0.05); a known founder Mendelian mutation (c.4957dupA, p.S1653Kfs*2) and a non-synonymous variant (c.2528 G > A, p.G843E) of unknown significance. mRNA harboring c.2528 G > A failed to restore rhodopsin mislocalization induced by morpholino-mediated knockdown of eys in zebrafish, consistent with the variant being pathogenic. c.2528 G > A solved an additional 7.0% of Japanese ARRP cases. The third peak was in linkage disequilibrium with a common non-synonymous variant (c.7666 A > T, p.S2556C), possibly representing an unreported disease-susceptibility signal. GWAS successfully unraveled genetic causes of a rare monogenic disorder and identified a high frequency variant potentially linked to development of local genome therapeutics. Koji Nishiguchi et al. identify three genetic variants within the EYS gene that are associated with retinitis pigmentosa using a genome-wide association study. They demonstrate that one of these variants (G843E) causes retinal dysfunction in zebrafish, suggesting a causal role for EYS in retinitis pigmentosa.
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187
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Ponomarenko I, Reshetnikov E, Polonikov A, Verzilina I, Sorokina I, Yermachenko A, Dvornyk V, Churnosov M. Candidate Genes for Age at Menarche Are Associated With Uterine Leiomyoma. Front Genet 2021; 11:512940. [PMID: 33552117 PMCID: PMC7863975 DOI: 10.3389/fgene.2020.512940] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2019] [Accepted: 10/14/2020] [Indexed: 12/23/2022] Open
Abstract
Age at menarche (AAM) is an important marker of the pubertal development and function of the hypothalamic-pituitary-ovarian system. It was reported as a possible factor for a risk of uterine leiomyoma (UL). However, while more than 350 loci for AAM have been determined by genome-wide association studies (GWASs) to date, no studies of these loci for their association with UL have been conducted so far. In this study, we analyzed 52 candidate loci for AAM for possible association with UL in a sample of 569 patients and 981 controls. The results of the study suggested that 23 out of the 52 studied polymorphisms had association with UL. Locus rs7759938 LIN28B was individually associated with the disease according to the dominant model. Twenty loci were associated with UL within 11 most significant models of intergenic interactions. Nine loci involved in 16 most significant models of interactions between single-nucleotide polymorphism (SNP), induced abortions, and chronic endometritis were associated with UL. Among the 23 loci associated with UL, 16 manifested association also with either AAM (7 SNPs) or height and/or body mass index (BMI) (13 SNPs). The above 23 SNPs and 514 SNPs linked to them have non-synonymous, regulatory, and expression quantitative trait locus (eQTL) significance for 35 genes, which play roles in the pathways related to development of the female reproductive organs and hormone-mediated signaling [false discovery rate (FDR) ≤ 0.05]. This is the first study reporting associations of candidate genes for AAM with UL.
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Affiliation(s)
- Irina Ponomarenko
- Department of Medical Biological Disciplines, Belgorod State University, Belgorod, Russia
| | - Evgeny Reshetnikov
- Department of Medical Biological Disciplines, Belgorod State University, Belgorod, Russia
| | - Alexey Polonikov
- Department of Biology, Medical Genetics and Ecology, Kursk State Medical University, Kursk, Russia
| | - Irina Verzilina
- Department of Medical Biological Disciplines, Belgorod State University, Belgorod, Russia
| | - Inna Sorokina
- Department of Social Epidemiology, Pierre Louis Institute of Epidemiology and Public Health, Sorbonne Universités, Paris, France
| | - Anna Yermachenko
- Department of Social Epidemiology, Pierre Louis Institute of Epidemiology and Public Health, Sorbonne Universités, Paris, France
| | - Volodymyr Dvornyk
- Department of Life Sciences, College of Science and General Studies, Alfaisal University, Riyadh, Saudi Arabia
| | - Mikhail Churnosov
- Department of Medical Biological Disciplines, Belgorod State University, Belgorod, Russia
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188
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Fang J, Zhang D, Cao JW, Zhang L, Liu CX, Xing YP, Wang F, Xu HY, Wang SC, Ling Y, Wang W, Zhang YR, Zhou HM. Pathways involved in pony body size development. BMC Genomics 2021; 22:58. [PMID: 33461495 PMCID: PMC7814589 DOI: 10.1186/s12864-020-07323-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Accepted: 12/14/2020] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND The mechanism of body growth in mammals is poorly understood. Here, we investigated the regulatory networks involved in body growth through transcriptomic analysis of pituitary and epiphyseal tissues of smaller sized Debao ponies and Mongolian horses at the juvenile and adult stages. RESULTS We found that growth hormone receptor (GHR) was expressed at low levels in long bones, although growth hormone (GH) was highly expressed in Debao ponies compared with Mongolian horses. Moreover, significant downregulated of the GHR pathway components m-RAS and ATF3 was found in juvenile ponies, which slowed the proliferation of bone osteocytes. However, WNT2 and PLCβ2 were obviously upregulated in juvenile Debao ponies, which led to premature mineralization of the bone extracellular matrix. Furthermore, we found that the WNT/Ca2+ pathway may be responsible for regulating body growth. GHR was demonstrated by q-PCR and Western blot analyses to be expressed at low levels in long bones of Debao ponies. Treatment with WNT antagonistI decreased the expression of WNT pathway components (P < 0.05) in vitro. Transduction of ATDC5 cells with a GHR-RNAi lentiviral vector decreased the expression of the GHR pathway components (P < 0.05). Additionally, the expression of the IGF-1 gene in the liver was lower in Debao ponies than in Mongolian horses at the juvenile and adult stages. Detection of plasma hormone concentrations showed that Debao ponies expressed higher levels of IGF-1 as juveniles and higher levels of GH as adults than Mongolian horses, indicating that the hormone regulation in Debao ponies differs from that in Mongolian horses. CONCLUSION Our work provides insights into the genetic regulation of short stature growth in mammals and can provide useful information for the development of therapeutic strategies for small size.
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Affiliation(s)
- Jun Fang
- College of Life Sciences, Inner Mongolia Agricultural University, No. 306 Zhaowuda Road, Hohhot, 010018, China
| | - Dong Zhang
- College of Life Sciences, Inner Mongolia Agricultural University, No. 306 Zhaowuda Road, Hohhot, 010018, China
| | - Jun Wei Cao
- College of Life Sciences, Inner Mongolia Agricultural University, No. 306 Zhaowuda Road, Hohhot, 010018, China
| | - Li Zhang
- College of Life Sciences, Inner Mongolia Agricultural University, No. 306 Zhaowuda Road, Hohhot, 010018, China
| | - Chun Xia Liu
- College of Life Sciences, Inner Mongolia Agricultural University, No. 306 Zhaowuda Road, Hohhot, 010018, China
| | - Yan Ping Xing
- College of Life Sciences, Inner Mongolia Agricultural University, No. 306 Zhaowuda Road, Hohhot, 010018, China
| | - Feng Wang
- College of Life Sciences, Inner Mongolia Agricultural University, No. 306 Zhaowuda Road, Hohhot, 010018, China
| | - Hong Yang Xu
- College of Life Sciences, Inner Mongolia Agricultural University, No. 306 Zhaowuda Road, Hohhot, 010018, China
| | - Shi Chao Wang
- College of Life Sciences, Inner Mongolia Agricultural University, No. 306 Zhaowuda Road, Hohhot, 010018, China
| | - Yu Ling
- College of Life Sciences, Inner Mongolia Agricultural University, No. 306 Zhaowuda Road, Hohhot, 010018, China
| | - Wei Wang
- College of Life Sciences, Inner Mongolia Agricultural University, No. 306 Zhaowuda Road, Hohhot, 010018, China
| | - Yan Ru Zhang
- College of Life Sciences, Inner Mongolia Agricultural University, No. 306 Zhaowuda Road, Hohhot, 010018, China.
| | - Huan Min Zhou
- College of Life Sciences, Inner Mongolia Agricultural University, No. 306 Zhaowuda Road, Hohhot, 010018, China.
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189
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Wang B, Liu X, Xu S, Liu Z, Zhu Y, Zhang X, Xu R. Sporadic Parkinson's Disease Potential Risk Loci Identified in Han Ancestry of Chinese Mainland. Front Aging Neurosci 2021; 12:603793. [PMID: 33510632 PMCID: PMC7835639 DOI: 10.3389/fnagi.2020.603793] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2020] [Accepted: 11/30/2020] [Indexed: 11/13/2022] Open
Abstract
Recent investigations demonstrated that genetic factors might play an important role in sporadic Parkinson's disease (sPD). To clarify the specific loci susceptibility to sPD, we analyze the relationship between 30 candidate single nucleotide polymorphisms (SNPs) and sPD in the population of Han ancestry from Chinese mainland (HACM) by using genome-wide association study, sequenom massARRAY, DNA sequence, and biological information analysis. Results showed that the subjects carrying the T allele of rs863108 and rs28499371 exhibited a decreased risk for sPD. The subjects carrying the T allele of rs80315856 exhibited an increased risk for sPD. The A/T genotype of rs863108 and the C/T genotype of rs28499371 were a potential increased risk for sPD, and the G/T genotype of rs80315856 and T/T genotype of rs2270568 were a potential decreased risk for sPD. The minor allele frequency (MAF) of rs80315856 and rs2270568 was higher in sPD. The T allele of rs80315856 and rs2270568 might be a risk locus for sPD. Our data suggested that the alteration of these SNPs might play some roles through changing/affecting LINC01524/LOC105372666, DMRT2/SMARCA2, PLEKHN1, and FLJ23172/FNDC3B genes in the pathogenesis of sPD.
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Affiliation(s)
- Bo Wang
- Department of Neurology, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Xin Liu
- Department of Neurology, Jiangxi Provincial People's Hospital, The Affiliated People's Hospital of Nanchang University, Nanchang, China
| | - Shengyuan Xu
- Department of Neurology, Jiangxi Provincial People's Hospital, The Affiliated People's Hospital of Nanchang University, Nanchang, China
| | - Zheng Liu
- Department of Neurology, First Affiliated Hospital of Gannan Medical University, Ganzhou, China
| | - Yu Zhu
- Department of Neurology, Jiangxi Provincial People's Hospital, The Affiliated People's Hospital of Nanchang University, Nanchang, China
| | - Xiong Zhang
- Department of Neurology, Maoming People's Hospital, Maoming, China
| | - Renshi Xu
- Department of Neurology, The First Affiliated Hospital of Nanchang University, Nanchang, China.,Department of Neurology, Jiangxi Provincial People's Hospital, The Affiliated People's Hospital of Nanchang University, Nanchang, China
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190
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Song L, Pan S, Zhang Z, Jia L, Chen WH, Zhao XM. STAB: a spatio-temporal cell atlas of the human brain. Nucleic Acids Res 2021; 49:D1029-D1037. [PMID: 32976581 PMCID: PMC7778989 DOI: 10.1093/nar/gkaa762] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2020] [Revised: 08/17/2020] [Accepted: 09/03/2020] [Indexed: 12/11/2022] Open
Abstract
The human brain is the most complex organ consisting of billions of neuronal and non-neuronal cells that are organized into distinct anatomical and functional regions. Elucidating the cellular and transcriptome architecture underlying the brain is crucial for understanding brain functions and brain disorders. Thanks to the single-cell RNA sequencing technologies, it is becoming possible to dissect the cellular compositions of the brain. Although great effort has been made to explore the transcriptome architecture of the human brain, a comprehensive database with dynamic cellular compositions and molecular characteristics of the human brain during the lifespan is still not available. Here, we present STAB (a Spatio-Temporal cell Atlas of the human Brain), a database consists of single-cell transcriptomes across multiple brain regions and developmental periods. Right now, STAB contains single-cell gene expression profiling of 42 cell subtypes across 20 brain regions and 11 developmental periods. With STAB, the landscape of cell types and their regional heterogeneity and temporal dynamics across the human brain can be clearly seen, which can help to understand both the development of the normal human brain and the etiology of neuropsychiatric disorders. STAB is available at http://stab.comp-sysbio.org.
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Affiliation(s)
- Liting Song
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China
| | - Shaojun Pan
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China
| | - Zichao Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China
| | - Longhao Jia
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China
| | - Wei-Hua Chen
- Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology (HUST), Wuhan 430074, Hubei, China
| | - Xing-Ming Zhao
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China
- Research Institute of Intelligent Complex Systems, Fudan University, Shanghai 200433, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Ministry of Education, Shanghai 200433, China
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191
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Lee HJ, Chung YJ, Jang S, Seo DW, Lee HK, Yoon D, Lim D, Lee SH. Genome-wide identification of major genes and genomic prediction using high-density and text-mined gene-based SNP panels in Hanwoo (Korean cattle). PLoS One 2020; 15:e0241848. [PMID: 33264312 PMCID: PMC7710051 DOI: 10.1371/journal.pone.0241848] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2020] [Accepted: 10/21/2020] [Indexed: 11/24/2022] Open
Abstract
It was hypothesized that single-nucleotide polymorphisms (SNPs) extracted from text-mined genes could be more tightly related to causal variant for each trait and that differentially weighting of this SNP panel in the GBLUP model could improve the performance of genomic prediction in cattle. Fitting two GRMs constructed by text-mined SNPs and SNPs except text-mined SNPs from 777k SNPs set (exp_777K) as different random effects showed better accuracy than fitting one GRM (Im_777K) for six traits (e.g. backfat thickness: + 0.002, eye muscle area: + 0.014, Warner–Bratzler Shear Force of semimembranosus and longissimus dorsi: + 0.024 and + 0.068, intramuscular fat content of semimembranosus and longissimus dorsi: + 0.008 and + 0.018). These results can suggest that attempts to incorporate text mining into genomic predictions seem valuable, and further study using text mining can be expected to present the significant results.
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Affiliation(s)
- Hyo Jun Lee
- Division of Animal and Dairy Science, Chungnam National University, Daejeon, Korea
| | - Yoon Ji Chung
- Division of Animal and Dairy Science, Chungnam National University, Daejeon, Korea
| | - Sungbong Jang
- Department of Animal and Dairy Science, University of Georgia, Athens, GA, United States of America
| | - Dong Won Seo
- Division of Animal and Dairy Science, Chungnam National University, Daejeon, Korea
| | - Hak Kyo Lee
- Department of Animal Biotechnology, Chonbuk National University, Jeonju, Korea
| | - Duhak Yoon
- Department of Animal Science, Kyungpook National University, Sangju, Korea
| | - Dajeong Lim
- Animal Genome & Bioinformatics, National Institute of Animal Science, Wanju, Korea
- * E-mail: (DL); (SHL)
| | - Seung Hwan Lee
- Division of Animal and Dairy Science, Chungnam National University, Daejeon, Korea
- * E-mail: (DL); (SHL)
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192
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Xu J, Fu Y, Hu Y, Yin L, Tang Z, Yin D, Zhu M, Yu M, Li X, Zhou Y, Zhao S, Liu X. Whole genome variants across 57 pig breeds enable comprehensive identification of genetic signatures that underlie breed features. J Anim Sci Biotechnol 2020; 11:115. [PMID: 33292532 PMCID: PMC7713148 DOI: 10.1186/s40104-020-00520-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Accepted: 10/19/2020] [Indexed: 01/15/2023] Open
Abstract
Background A large number of pig breeds are distributed around the world, their features and characteristics vary among breeds, and they are valuable resources. Understanding the underlying genetic mechanisms that explain across-breed variation can help breeders develop improved pig breeds. Results In this study, we performed GWAS using a standard mixed linear model with three types of genome variants (SNP, InDel, and CNV) that were identified from public, whole-genome, sequencing data sets. We used 469 pigs of 57 breeds, and we identified and analyzed approximately 19 million SNPs, 1.8 million InDels, and 18,016 CNVs. We defined six biological phenotypes by the characteristics of breed features to identify the associated genome variants and candidate genes, which included coat color, ear shape, gradient zone, body weight, body length, and body height. A total of 37 candidate genes was identified, which included 27 that were reported previously (e.g., PLAG1 for body weight), but the other 10 were newly detected candidate genes (e.g., ADAMTS9 for coat color). Conclusion Our study indicated that using GWAS across a modest number of breeds with high density genome variants provided efficient mapping of complex traits. Supplementary Information Supplementary information accompanies this paper at 10.1186/s40104-020-00520-8.
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Affiliation(s)
- Jingya Xu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, PR China
| | - Yuhua Fu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, PR China
| | - Yan Hu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, PR China
| | - Lilin Yin
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, PR China
| | - Zhenshuang Tang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, PR China
| | - Dong Yin
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, PR China
| | - Mengjin Zhu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, PR China
| | - Mei Yu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, PR China
| | - Xinyun Li
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, PR China
| | - Yang Zhou
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, PR China.
| | - Shuhong Zhao
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, PR China.
| | - Xiaolei Liu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, PR China.
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193
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Novel missense variants in FGFR1 and FGFR3 causes short stature in enrolled families from Pakistan. Meta Gene 2020. [DOI: 10.1016/j.mgene.2020.100778] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
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194
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Fujimoto M, Andrew M, Dauber A. Disorders caused by genetic defects associated with GH-dependent genes: PAPPA2 defects. Mol Cell Endocrinol 2020; 518:110967. [PMID: 32739295 PMCID: PMC7609568 DOI: 10.1016/j.mce.2020.110967] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/12/2020] [Revised: 07/24/2020] [Accepted: 07/24/2020] [Indexed: 12/28/2022]
Abstract
Growth hormone (GH) and its mediator, insulin-like growth factor-1 (IGF-1), have long been recognized as central to human growth physiology. IGF-1 is known to complex with IGF binding proteins as well as with the acid labile subunit (ALS) in order to prolong its half-life in circulation. Factors regulating the bioavailability of IGF-1 (i.e. the balance between free and bound IGF-1) were less well understood. Recently, pregnancy-associated plasma protein-A2 (PAPP-A2) was discovered as a protease which specifically cleaves IGF-binding protein (IGFBP)-3 and -5. PAPP-A2 deficient patients present with characteristic findings including growth failure, elevated total IGF-1 and -2, IGFBPs, and ALS, but decreased percentage of free to total IGF-1. Additionally, patients with PAPP-A2 deficiency have impairments in glucose metabolism and bone mineral density (BMD). Treatment with recombinant human IGF-1 (rhIGF-1) improved height SD scores, growth velocity, body composition, and dysglycemia. Mouse models recapitulate many of the human findings of PAPP-A2 deficiency. This review summarizes the function of PAPP-A2 and its contribution to the GH-IGF axis through an examination of PAPP-A2 deficient patients and mouse models, thereby emphasizing the importance of the regulation of IGF-1 bioavailability in human growth.
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Affiliation(s)
- Masanobu Fujimoto
- Division of Pediatrics and Perinatology, Tottori University Faculty of Medicine, Yonago, Tottori, 683-8504, Japan
| | - Melissa Andrew
- Division of Endocrinology, Children's National Hospital, Washington, DC, 20010, USA
| | - Andrew Dauber
- Division of Endocrinology, Children's National Hospital, Washington, DC, 20010, USA; Department of Pediatrics, George Washington University School of Medicine and Health Sciences, Washington, DC, 20052, USA.
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195
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Landi E, Karabatas L, Scaglia P, Pisciottano F, Gutiérrez M, Ramírez L, Bergadá I, Rey RA, Jasper HG, Domené HM, Plazas PV, Domené S. Expression of acid-labile subunit (ALS) in developing and adult zebrafish and its role in dorso-ventral patterning during development. Gen Comp Endocrinol 2020; 299:113591. [PMID: 32828812 DOI: 10.1016/j.ygcen.2020.113591] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Revised: 07/28/2020] [Accepted: 08/18/2020] [Indexed: 11/24/2022]
Abstract
Mammalian acid-labile subunit (ALS) is a serum protein that binds binary complexes between Insulin-like growth factors (IGFs) and Insulin-like growth factor-binding proteins (IGFBPs) extending their half-life and keeping them in the vasculature. Human ALS deficiency (ACLSD), due to homozygous or compound heterozygous mutations in IGFALS, leads to moderate short stature with reduced levels of IGF-I and IGFBP-3. There is only one corresponding zebrafish ortholog gene and it has not yet been studied. In this study we elucidate the role of igfals during zebrafish development. In zebrafish embryos igfals mRNA is expressed throughout development, mainly in the brain and subsequently also in the gut and swimbladder. To determine its role during development, we knocked down igfals gene product using morpholinos (MOs). Igfals morphant embryos displayed dorsalization in different degrees of severity, including a shortened trunk and loss of tail. Furthermore, co-injection of human IGFALS (hIGFALS) mRNA was able to rescue the MO-induced phenotype. Finally, overexpression of either hIGFALS or zebrafish igfals (zigfals) mRNA leads to ventralization of embryos including a reduced head and enlarged tail. These findings suggest that als plays an important role in dorso-ventral patterning during zebrafish development.
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Affiliation(s)
- Estefanía Landi
- Centro de Investigaciones Endocrinológicas "Dr. César Bergadá" (CEDIE), CONICET-FEI-División de Endocrinología, Hospital de Niños Ricardo Gutiérrez, C1425EFD Buenos Aires, Argentina.
| | - Liliana Karabatas
- Centro de Investigaciones Endocrinológicas "Dr. César Bergadá" (CEDIE), CONICET-FEI-División de Endocrinología, Hospital de Niños Ricardo Gutiérrez, C1425EFD Buenos Aires, Argentina.
| | - Paula Scaglia
- Centro de Investigaciones Endocrinológicas "Dr. César Bergadá" (CEDIE), CONICET-FEI-División de Endocrinología, Hospital de Niños Ricardo Gutiérrez, C1425EFD Buenos Aires, Argentina.
| | - Francisco Pisciottano
- Instituto de Biología y Medicina Experimental (IBYME), Vuelta de Obligado 2490, C1428ADN Buenos Aires, Argentina.
| | - Mariana Gutiérrez
- Centro de Investigaciones Endocrinológicas "Dr. César Bergadá" (CEDIE), CONICET-FEI-División de Endocrinología, Hospital de Niños Ricardo Gutiérrez, C1425EFD Buenos Aires, Argentina.
| | - Laura Ramírez
- Centro de Investigaciones Endocrinológicas "Dr. César Bergadá" (CEDIE), CONICET-FEI-División de Endocrinología, Hospital de Niños Ricardo Gutiérrez, C1425EFD Buenos Aires, Argentina.
| | - Ignacio Bergadá
- Centro de Investigaciones Endocrinológicas "Dr. César Bergadá" (CEDIE), CONICET-FEI-División de Endocrinología, Hospital de Niños Ricardo Gutiérrez, C1425EFD Buenos Aires, Argentina.
| | - Rodolfo A Rey
- Centro de Investigaciones Endocrinológicas "Dr. César Bergadá" (CEDIE), CONICET-FEI-División de Endocrinología, Hospital de Niños Ricardo Gutiérrez, C1425EFD Buenos Aires, Argentina.
| | - Héctor Guillermo Jasper
- Centro de Investigaciones Endocrinológicas "Dr. César Bergadá" (CEDIE), CONICET-FEI-División de Endocrinología, Hospital de Niños Ricardo Gutiérrez, C1425EFD Buenos Aires, Argentina.
| | - Horacio Mario Domené
- Centro de Investigaciones Endocrinológicas "Dr. César Bergadá" (CEDIE), CONICET-FEI-División de Endocrinología, Hospital de Niños Ricardo Gutiérrez, C1425EFD Buenos Aires, Argentina.
| | - Paola Viviana Plazas
- Instituto de Farmacología, Facultad de Medicina, Universidad de Buenos Aires (UBA), Paraguay 2155, C1121ABG Buenos Aires, Argentina.
| | - Sabina Domené
- Centro de Investigaciones Endocrinológicas "Dr. César Bergadá" (CEDIE), CONICET-FEI-División de Endocrinología, Hospital de Niños Ricardo Gutiérrez, C1425EFD Buenos Aires, Argentina.
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196
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Integrative bioinformatic analyses of genome-wide association studies for understanding the genetic bases of human height. Biologia (Bratisl) 2020. [DOI: 10.2478/s11756-020-00550-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
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197
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Łopuszańska-Dawid M, Szklarska A. Growth change in Polish women: Reduction of the secular trends? PLoS One 2020; 15:e0242074. [PMID: 33253200 PMCID: PMC7703883 DOI: 10.1371/journal.pone.0242074] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Accepted: 10/27/2020] [Indexed: 11/19/2022] Open
Abstract
The aim of the study was to analyse changes in the average height of adult Polish women born in 1931-2001 in the aspect of dynamically changing economic and socio-economic conditions of the living environment. An ethnically homogeneous group of 6,028 adult women from large Polish cities, born in 1931-2001, living between 1931 and 2020, were examined using the same research methods and research equipment. All women were divided into eight birth cohorts. The Kruskal-Wallis test and multiple regression analyses were used. Root Mean Square Standardized Effect (RMSSE), critical value of the test, and test power were calculated. The average height of women born during 70 years of the study increased by 9.63 cm, from 158.22 cm (SD = 5.57 cm) to 167.85 cm (SD = 6.91 cm) (H = 1084.84, p<0.001). The intensity of the intergenerational trend in subsequent cohorts of years of birth varied strongly between decades, averaging 1.34 cm/decade. The body height in women increased significantly up to the height of those born between 1970 and 1979 and then the trend weakened noticeably, although it remained positive. The observed secular trend confirms positive changes in the standard of living of Polish women between 1931 and 2020. Improving living conditions allow people to fully achieve their genetically determined growth potential.
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Affiliation(s)
- Monika Łopuszańska-Dawid
- Józef Pilsudski University of Physical Education in Warsaw, Faculty of Physical Education, Department of Human Biology, Warsaw, Poland
| | - Alicja Szklarska
- Polish Academy of Sciences, Poland, Palace of Culture and Science, Warsaw, Poland
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198
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Zheng XD, Cheng J, Qin WJ, Balsai N, Shang XJ, Zhang MT, Chen HQ. Whole Transcriptome Analysis Identifies the Taxonomic Status of a New Chinese Native Cattle Breed and Reveals Genes Related to Body Size. Front Genet 2020; 11:562855. [PMID: 33240316 PMCID: PMC7670488 DOI: 10.3389/fgene.2020.562855] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2020] [Accepted: 09/11/2020] [Indexed: 11/15/2022] Open
Abstract
Wandong (WD) cattle has recently been identified as a new Chinese native cattle breed by the National Commission for Livestock and Poultry Genetic Resources. The population size of this breed is less than 10,000. WD cattle and Dabieshan (DB) cattle are sympatric but are raised in different ecological environments, on mountains and plains, respectively, and the body sizes of these two breeds are markedly different. Blood samples were obtained from 8 adult female WD cattle and 7 adult female DB cattle (24 months old). The total RNA was extracted from leukocyte cells, and sequencing experiments were conducted on the Illumina HiSeqTM 4000 platform. After the removal of one outlier sample from the WD cattle breed as determined by principal component analysis (PCA), phylogenetic and population structure analyses indicated that WD and DB cattle formed a distinct Central China cattle group and showed evidence of hybridization between Bos. taurus and Bos. indicus. The immune-regulator CD48 (P = 1.3E-6) was associated with breed-specific traits according to loss-of-function variant enrichment analysis. In addition, 113 differentially expressed genes were identified between the two breeds, many of which are associated with the regulation of body growth, which is the major difference between the two breeds. This study showed that WD cattle belong to the group of hybrids between Bos. Taurus and Bos. indicus, and one novel gene associated with breed traits and multiple differentially expressed genes between these two closely related breeds was identified. The results provide insights into the genetic mechanisms that underlie economically important traits, such as body size, in cattle.
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Affiliation(s)
- Xiao-Dong Zheng
- School of Animal Science and Technology, Anhui Agricultural University, Hefei, China.,Key Laboratory of Anhui Local Livestock and Poultry Genetic Resources Conservation and Biobreeding, Hefei, China.,Department of Dermatology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.,Key Laboratory of Dermatology (Anhui Medical University), Ministry of Education, Hefei, China.,Key Laboratory of Major Autoimmune Diseases, Hefei, China
| | - Jin Cheng
- School of Animal Science and Technology, Anhui Agricultural University, Hefei, China.,Key Laboratory of Anhui Local Livestock and Poultry Genetic Resources Conservation and Biobreeding, Hefei, China
| | - Wen-Juan Qin
- School of Animal Science and Technology, Anhui Agricultural University, Hefei, China.,Key Laboratory of Anhui Local Livestock and Poultry Genetic Resources Conservation and Biobreeding, Hefei, China.,International Immunization Center, Anhui Agricultural University, Hefei, China
| | - Nyamsuren Balsai
- School of Animal Science and Technology, Anhui Agricultural University, Hefei, China.,Key Laboratory of Anhui Local Livestock and Poultry Genetic Resources Conservation and Biobreeding, Hefei, China
| | - Xuan-Jian Shang
- School of Animal Science and Technology, Anhui Agricultural University, Hefei, China.,Key Laboratory of Anhui Local Livestock and Poultry Genetic Resources Conservation and Biobreeding, Hefei, China
| | - Meng-Ting Zhang
- School of Animal Science and Technology, Anhui Agricultural University, Hefei, China.,Key Laboratory of Anhui Local Livestock and Poultry Genetic Resources Conservation and Biobreeding, Hefei, China
| | - Hong-Quan Chen
- School of Animal Science and Technology, Anhui Agricultural University, Hefei, China.,Key Laboratory of Anhui Local Livestock and Poultry Genetic Resources Conservation and Biobreeding, Hefei, China.,International Immunization Center, Anhui Agricultural University, Hefei, China
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199
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Population-Matched Transcriptome Prediction Increases TWAS Discovery and Replication Rate. iScience 2020; 23:101850. [PMID: 33313492 PMCID: PMC7721644 DOI: 10.1016/j.isci.2020.101850] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Revised: 11/12/2020] [Accepted: 11/18/2020] [Indexed: 12/11/2022] Open
Abstract
Most genome-wide association studies (GWAS) and transcriptome-wide association studies (TWAS) focus on European populations; however, these results cannot always be accurately applied to non-European populations due to genetic architecture differences. Using GWAS summary statistics in the Population Architecture using Genomics and Epidemiology study, which comprises ∼50,000 Hispanic/Latinos, African Americans, Asians, Native Hawaiians, and Native Americans, we perform TWAS to determine gene-trait associations. We compared results using three transcriptome prediction models derived from Multi-Ethnic Study of Atherosclerosis populations: the African American and Hispanic/Latino (AFHI) model, the European (EUR) model, and the African American, Hispanic/Latino, and European (ALL) model. We identified 240 unique significant trait-associated genes. We found more significant, colocalized genes that replicate in larger cohorts when applying the AFHI model than the EUR or ALL model. Thus, TWAS with population-matched transcriptome models have more power for discovery and replication, demonstrating the need for more transcriptome studies in diverse populations. TWAS mechanistically extends GWAS findings in diverse populations Population-matched transcriptome models detect more replicable associations Colocalization shows GWAS variants likely act through gene expression regulation More GWAS and transcriptome modeling in diverse populations are needed
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200
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Xiao L, Yuan Z, Jin S, Wang T, Huang S, Zeng P. Multiple-Tissue Integrative Transcriptome-Wide Association Studies Discovered New Genes Associated With Amyotrophic Lateral Sclerosis. Front Genet 2020; 11:587243. [PMID: 33329728 PMCID: PMC7714931 DOI: 10.3389/fgene.2020.587243] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2020] [Accepted: 10/26/2020] [Indexed: 12/12/2022] Open
Abstract
Genome-wide association studies (GWAS) have identified multiple causal genes associated with amyotrophic lateral sclerosis (ALS); however, the genetic architecture of ALS remains completely unknown and a large number of causal genes have yet been discovered. To full such gap in part, we implemented an integrative analysis of transcriptome-wide association study (TWAS) for ALS to prioritize causal genes with summary statistics from 80,610 European individuals and employed 13 GTEx brain tissues as reference transcriptome panels. The summary-level TWAS analysis with single brain tissue was first undertaken and then a flexible p-value combination strategy, called summary data-based Cauchy Aggregation TWAS (SCAT), was proposed to pool association signals from single-tissue TWAS analysis while protecting against highly positive correlation among tests. Extensive simulations demonstrated SCAT can produce well-calibrated p-value for the control of type I error and was often much more powerful to identify association signals across various scenarios compared with single-tissue TWAS analysis. Using SCAT, we replicated three ALS-associated genes (i.e., ATXN3, SCFD1, and C9orf72) identified in previous GWASs and discovered additional five genes (i.e., SLC9A8, FAM66D, TRIP11, JUP, and RP11-529H20.6) which were not reported before. Furthermore, we discovered the five associations were largely driven by genes themselves and thus might be new genes which were likely related to the risk of ALS. However, further investigations are warranted to verify these results and untangle the pathophysiological function of the genes in developing ALS.
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Affiliation(s)
- Lishun Xiao
- Department of Epidemiology and Biostatistics, Xuzhou Medical University, Xuzhou, China
| | - Zhongshang Yuan
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Siyi Jin
- Department of Epidemiology and Biostatistics, Xuzhou Medical University, Xuzhou, China
| | - Ting Wang
- Department of Epidemiology and Biostatistics, Xuzhou Medical University, Xuzhou, China
| | - Shuiping Huang
- Department of Epidemiology and Biostatistics, Xuzhou Medical University, Xuzhou, China.,Center for Medical Statistics and Data Analysis, School of Public Health, Xuzhou Medical University, Xuzhou, China
| | - Ping Zeng
- Department of Epidemiology and Biostatistics, Xuzhou Medical University, Xuzhou, China.,Center for Medical Statistics and Data Analysis, School of Public Health, Xuzhou Medical University, Xuzhou, China
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