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Antonio-Aguirre B, Ling C, Singh MS. Very Large Cystoid Macular Lesions Identified Using Outlier Analysis of Genetically Confirmed Inherited Retinal Disease Cases. Ophthalmic Genet 2023; 44:430-436. [PMID: 37246744 DOI: 10.1080/13816810.2023.2212757] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Revised: 04/30/2023] [Accepted: 05/07/2023] [Indexed: 05/30/2023]
Abstract
BACKGROUND Cystoid macular lesions (CML) in inherited retinal diseases (IRDs) can contribute to vision impairment. Studying the morphologic range and outlier presentations of CML may inform clinical associations, mechanistic research, and trial design. Thus, we aim to describe the distribution of optical coherence tomography (OCT) parameters in IRD cases with CML and identify phenotype-genotype associations in very large cystoid macular lesions (VLCML). MATERIALS AND METHODS This cross-sectional study retrieved clinical information from electronic records from January 2020 to December 2021. VLCML cases were identified using the robust distance (Mahalanobis) of the correlation between central foveal thickness (CFT) and total macular volume (TMV) and a 99.9% probability ellipse. The distribution of OCT parameters was calculated by genotype and phenotype. RESULTS We included 173 eyes of 103 subjects. The median age was 55.9 (interquartile range [IQR], 37.9, 63.7) and 47.6% (49/103) were females. Patients had disease-causing mutations in 30 genes. The most common genes included USH2A (n = 18), RP1 (n = 12), and ABCA4 (n = 11). Robust distance analysis showed that the prevalence of VLCML was 1.94% (n = 2 patients, 4 eyes). VLCML was seen in cases of NR2E3 (119-2A>C) and BEST1 (1120_1121insG) mutations. The median CFT in cases without VLCML was 269 µm (IQR 209, 318.50) while the median for VLCML cases was 1,490 µm (IQR 1,445.50, 1,548.00) (P < .001). CONCLUSIONS Subjects with different IRD genotypes may develop VLCMLs. Future studies could consider the range and outlier values of CML foveal thickness when determining inclusion criteria and biostatistical plans for observational and interventional studies.
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Affiliation(s)
| | - Carlthan Ling
- Department of Ophthalmology and Visual Sciences, University of Maryland Medical Center, Baltimore, Maryland, USA
| | - Mandeep S Singh
- Wilmer Eye Institute, Johns Hopkins Hospital, Baltimore, Maryland, USA
- Department of Genetic Medicine, Johns Hopkins University, Baltimore, Maryland, USA
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2
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Martin-Fernandez L, Garcia-Martínez I, Lopez S, Martinez-Perez A, Vilalta N, Plaza M, Moret C, Viñuela A, Brown AA, Panousis NI, Buil A, Dermitzakis ET, Corrales I, Souto JC, Vidal F, Soria JM. Multiallelic Copy Number Variation in ORM1 is Associated with Plasma Cell-Free DNA Levels as an Intermediate Phenotype for Venous Thromboembolism. Thromb Haemost 2023; 123:438-452. [PMID: 36696913 DOI: 10.1055/s-0043-1760844] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
Venous thromboembolism (VTE) is a common disease with high heritability. However, only a small portion of the genetic variance of VTE can be explained by known genetic risk factors. Neutrophil extracellular traps (NETs) have been associated with prothrombotic activity. Therefore, the genetic basis of NETs could reveal novel risk factors for VTE. A recent genome-wide association study of plasma cell-free DNA (cfDNA) levels in the Genetic Analysis of Idiopathic Thrombophilia 2 (GAIT-2) Project showed a significant associated locus near ORM1. We aimed to further explore this candidate region by next-generation sequencing, copy number variation (CNV) quantification, and expression analysis using an extreme phenotype sampling design involving 80 individuals from the GAIT-2 Project. The RETROVE study with 400 VTE cases and 400 controls was used to replicate the results. A total of 105 genetic variants and a multiallelic CNV (mCNV) spanning ORM1 were identified in GAIT-2. Of these, 17 independent common variants, a region of 22 rare variants, and the mCNV were significantly associated with cfDNA levels. In addition, eight of these common variants and the mCNV influenced ORM1 expression. The association of the mCNV and cfDNA levels was replicated in RETROVE (p-value = 1.19 × 10-6). Additional associations between the mCNV and thrombin generation parameters were identified. Our results reveal that increased mCNV dosages in ORM1 decreased gene expression and upregulated cfDNA levels. Therefore, the mCNV in ORM1 appears to be a novel marker for cfDNA levels, which could contribute to VTE risk.
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Affiliation(s)
- Laura Martin-Fernandez
- Genomics of Complex Diseases Unit, Research Institute Hospital de la Santa Creu i Sant Pau, IIB-Sant Pau, Barcelona, Spain
- Congenital Coagulopathies Laboratory, Blood and Tissue Bank, Barcelona, Spain
- Fundación Española de Trombosis y Hemostasia (FETH), Madrid, Spain
- Transfusional Medicine, Vall d'Hebron Research Institute, Universitat Autònoma de Barcelona (VHIR-UAB), Barcelona, Spain
| | - Iris Garcia-Martínez
- Congenital Coagulopathies Laboratory, Blood and Tissue Bank, Barcelona, Spain
- Transfusional Medicine, Vall d'Hebron Research Institute, Universitat Autònoma de Barcelona (VHIR-UAB), Barcelona, Spain
| | - Sonia Lopez
- Genomics of Complex Diseases Unit, Research Institute Hospital de la Santa Creu i Sant Pau, IIB-Sant Pau, Barcelona, Spain
| | - Angel Martinez-Perez
- Genomics of Complex Diseases Unit, Research Institute Hospital de la Santa Creu i Sant Pau, IIB-Sant Pau, Barcelona, Spain
| | - Noelia Vilalta
- Hemostasis and Thrombosis Unit, Department of Hematology, Hospital de la Santa Creu i Sant Pau, IIB-Sant Pau, Barcelona, Spain
| | - Melania Plaza
- Hemostasis and Thrombosis Unit, Department of Hematology, Hospital de la Santa Creu i Sant Pau, IIB-Sant Pau, Barcelona, Spain
| | - Carla Moret
- Hemostasis and Thrombosis Unit, Department of Hematology, Hospital de la Santa Creu i Sant Pau, IIB-Sant Pau, Barcelona, Spain
| | - Ana Viñuela
- Biosciences Institute, Faculty of Medicine, Newcastle University, Newcastle Upon Tyne, United Kingdom
| | - Andrew A Brown
- Population Health and Genomics, University of Dundee, Dundee, Scotland, United Kingdom
| | - Nikolaos I Panousis
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, South Cambridgeshire, United Kingdom
- Department of Genetic Medicine and Development, University of Geneva, Geneva, Switzerland
| | - Alfonso Buil
- Institute of Biological Psychiatry, Mental Health Sct. Hans Hospital, Roskilde, Denmark
| | | | - Irene Corrales
- Congenital Coagulopathies Laboratory, Blood and Tissue Bank, Barcelona, Spain
- Transfusional Medicine, Vall d'Hebron Research Institute, Universitat Autònoma de Barcelona (VHIR-UAB), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Instituto Carlos III (ISCIII), Madrid, Spain
| | - Juan Carlos Souto
- Hemostasis and Thrombosis Unit, Department of Hematology, Hospital de la Santa Creu i Sant Pau, IIB-Sant Pau, Barcelona, Spain
| | - Francisco Vidal
- Congenital Coagulopathies Laboratory, Blood and Tissue Bank, Barcelona, Spain
- Transfusional Medicine, Vall d'Hebron Research Institute, Universitat Autònoma de Barcelona (VHIR-UAB), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Instituto Carlos III (ISCIII), Madrid, Spain
| | - Jose Manuel Soria
- Genomics of Complex Diseases Unit, Research Institute Hospital de la Santa Creu i Sant Pau, IIB-Sant Pau, Barcelona, Spain
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3
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Che M, Han P, Lawless JF. Improving estimation efficiency for two-phase, outcome-dependent sampling studies. Electron J Stat 2023. [DOI: 10.1214/23-ejs2124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/08/2023]
Affiliation(s)
- Menglu Che
- Department of Biostatistics, School of Public Health, Yale University
| | - Peisong Han
- Department of Biostatistics, School of Public Health, University of Michigan
| | - Jerald F. Lawless
- Department of Statistics and Actuarial Science, University of Waterloo
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4
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Zhong W, Kollipara A, Liu Y, Wang Y, O’Connell CM, Poston TB, Yount K, Wiesenfeld HC, Hillier SL, Li Y, Darville T, Zheng X. Genetic susceptibility loci for Chlamydia trachomatis endometrial infection influence expression of genes involved in T cell function, tryptophan metabolism and epithelial integrity. Front Immunol 2022; 13:1001255. [PMID: 36248887 PMCID: PMC9562917 DOI: 10.3389/fimmu.2022.1001255] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2022] [Accepted: 09/09/2022] [Indexed: 11/13/2022] Open
Abstract
Objectives Identify genetic loci of enhanced susceptibility to Chlamydial trachomatis (Ct) upper genital tract infection in women. Methods We performed an integrated analysis of DNA genotypes and blood-derived mRNA profiles from 200 Ct-exposed women to identify expression quantitative trait loci (eQTL) and determine their association with endometrial chlamydial infection using a mediation test. We further evaluated the effect of a lead eQTL on the expression of CD151 by immune cells from women with genotypes associated with low and high whole blood expression of CD151, respectively. Results We identified cis-eQTLs modulating mRNA expression of 81 genes (eGenes) associated with altered risk of ascending infection. In women with endometrial infection, eGenes involved in proinflammatory signaling were upregulated. Downregulated eGenes included genes involved in T cell functions pivotal for chlamydial control. eGenes encoding molecules linked to metabolism of tryptophan, an essential chlamydial nutrient, and formation of epithelial tight junctions were also downregulated in women with endometrial infection. A lead eSNP rs10902226 was identified regulating CD151, a tetrospanin molecule important for immune cell adhesion and migration and T cell proliferation. Further in vitro experiments showed that women with a CC genotype at rs10902226 had reduced rates of endometrial infection with increased CD151 expression in whole blood and T cells when compared to women with a GG genotype. Conclusions We discovered genetic variants associated with altered risk for Ct ascension. A lead eSNP for CD151 is a candidate genetic marker for enhanced CD4 T cell function and reduced susceptibility.
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Affiliation(s)
- Wujuan Zhong
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Avinash Kollipara
- Department of Pediatrics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Yutong Liu
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Yuhan Wang
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Catherine M. O’Connell
- Department of Pediatrics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Taylor B. Poston
- Department of Pediatrics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Kacy Yount
- Department of Pediatrics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Harold C. Wiesenfeld
- The University of Pittsburgh School of Medicine and the Magee-Womens Research Institute, Pittsburgh, PA, United States
| | - Sharon L. Hillier
- The University of Pittsburgh School of Medicine and the Magee-Womens Research Institute, Pittsburgh, PA, United States
| | - Yun Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Toni Darville
- Department of Pediatrics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Xiaojing Zheng
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Department of Pediatrics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
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5
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Jones AC, Patki A, Claas SA, Tiwari HK, Chaudhary NS, Absher DM, Lange LA, Lange EM, Zhao W, Ratliff SM, Kardia SLR, Smith JA, Irvin MR, Arnett DK. Differentially Methylated DNA Regions and Left Ventricular Hypertrophy in African Americans: A HyperGEN Study. Genes (Basel) 2022; 13:genes13101700. [PMID: 36292585 PMCID: PMC9601679 DOI: 10.3390/genes13101700] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2022] [Revised: 09/15/2022] [Accepted: 09/20/2022] [Indexed: 11/16/2022] Open
Abstract
Left ventricular (LV) hypertrophy (LVH) is an independent risk factor for cardiovascular disease, and African Americans experience a disparate high risk of LVH. Genetic studies have identified potential candidate genes and variants related to the condition. Epigenetic modifications may continue to help unravel disease mechanisms. We used methylation and echocardiography data from 636 African Americans selected from the Hypertension Genetic Epidemiology Network (HyperGEN) to identify differentially methylated regions (DMRs) associated with LVH. DNA extracted from whole blood was assayed on Illumina Methyl450 arrays. We fit linear mixed models to examine associations between co-methylated regions and LV traits, and we then conducted single CpG analyses within significant DMRs. We identified associations between DMRs and ejection fraction (XKR6), LV internal diastolic dimension (TRAK1), LV mass index (GSE1, RPS15 A, PSMD7), and relative wall thickness (DNHD1). In single CpG analysis, CpG sites annotated to TRAK1 and DNHD1 were significant. These CpGs were not associated with LV traits in replication cohorts but the direction of effect for DNHD1 was consistent across cohorts. Of note, DNHD1, GSE1, and PSMD7 may contribute to cardiac structural function. Future studies should evaluate relationships between regional DNA methylation patterns and the development of LVH.
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Affiliation(s)
- Alana C. Jones
- Department of Epidemiology, School of Public Health, University of Alabama-Birmingham, Birmingham, AL 35233, USA
| | - Amit Patki
- Department of Biostatistics, School of Public Health, University of Alabama-Birmingham, Birmingham, AL 35233, USA
| | - Steven A. Claas
- Department of Epidemiology, College of Public Health, University of Kentucky, Lexington, KY 40506, USA
| | - Hemant K. Tiwari
- Department of Biostatistics, School of Public Health, University of Alabama-Birmingham, Birmingham, AL 35233, USA
| | - Ninad S. Chaudhary
- Department of Epidemiology, School of Public Health, University of Alabama-Birmingham, Birmingham, AL 35233, USA
- Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, University of Texas Health Science Center, Houston, TX 77030, USA
| | - Devin M. Absher
- Hudson Alpha Institute of Biotechnology, Huntsville, AL 35806, USA
| | - Leslie A. Lange
- Department of Epidemiology, School of Public Health, University of Colorado, Aurora, CO 80045, USA
- Department of Biomedical Informatics, School of Medicine, University of Colorado, Aurora, CO 80045, USA
| | - Ethan M. Lange
- Department of Biomedical Informatics, School of Medicine, University of Colorado, Aurora, CO 80045, USA
- Department of Biostatistics and Informatics, School of Public Health, University of Colorado, Aurora, CO 80045, USA
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Scott M. Ratliff
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Sharon L. R. Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Jennifer A. Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Marguerite R. Irvin
- Department of Epidemiology, School of Public Health, University of Alabama-Birmingham, Birmingham, AL 35233, USA
- Correspondence:
| | - Donna K. Arnett
- Department of Epidemiology, College of Public Health, University of Kentucky, Lexington, KY 40506, USA
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6
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Cheng S, Cheng B, Liu L, Yang X, Meng P, Yao Y, Pan C, Zhang J, Li C, Zhang H, Chen Y, Zhang Z, Wen Y, Jia Y, Zhang F. Exome-wide screening identifies novel rare risk variants for major depression disorder. Mol Psychiatry 2022; 27:3069-3074. [PMID: 35365804 DOI: 10.1038/s41380-022-01536-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/28/2021] [Revised: 03/08/2022] [Accepted: 03/16/2022] [Indexed: 11/09/2022]
Abstract
Despite thousands of common genetic loci of major depression disorders (MDD) have been identified by GWAS to date, a large proportion of genetic variation predisposing to MDD remains unaccounted for. By utilizing the newly released UK Biobank 200,643 exome dataset, we conducted an exome-wide association study to identify rare risk variants contributing to MDD. After quality control, 120,033 participants with MDD polygenic risk scores (PRS) values were included. The individuals with lower 30% quantile of the PRS value were filtered for case and control selecting. Then the cases were set as the individuals with upper 10% quantile of the PHQ depression score and lower 10% quantile were set as controls. Finally, 1612 cases and 1612 controls were included in this study. The variants were annotated by ANNOVRA software. After exclusions, 34,761 qualifying variants, including 148 frameshift variant, 335 non-frameshift variant, 33,758 nonsynonymous, 91 start-loss, 393 stop-gain, 36 stop-loss variants were imported into the SKAT R-package to perform single variants, gene-based burden and robust burden tests with minor allele frequency (MAF) < 0.01. Single variant association testing identified one variant, rs4057749 (P = 5.39 × 10-9), within OR8B4 gene at an exome-wide significance level. The gene-based burden test of the exonic variants identified genome-wide significant associations in OR8B4 (PSKAT = 6.23 × 10-5, PSKAT Robust = 4.49 × 10-5), TRAPPC11 (PSKAT = 0.014, PSKAT Robust = 0.015), SBK3 (PSKAT = 0.020, PSKAT Robust = 0.025) and TNRC6B (PSKAT = 0.026, PSKAT Robust = 0.036). We identified multiple novel rare risk variants contributing to MDD in the individuals with lower PRS of MDD. The findings can help to broaden the genetic insights of the MDD pathogenesis.
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Affiliation(s)
- Shiqiang Cheng
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Xi'an Jiaotong University, Xi'an, China.,Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, Xi'an, China.,Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an Jiaotong University, Xi'an, China
| | - Bolun Cheng
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Xi'an Jiaotong University, Xi'an, China.,Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, Xi'an, China.,Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an Jiaotong University, Xi'an, China
| | - Li Liu
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Xi'an Jiaotong University, Xi'an, China.,Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, Xi'an, China.,Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an Jiaotong University, Xi'an, China
| | - Xuena Yang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Xi'an Jiaotong University, Xi'an, China.,Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, Xi'an, China.,Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an Jiaotong University, Xi'an, China
| | - Peilin Meng
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Xi'an Jiaotong University, Xi'an, China.,Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, Xi'an, China.,Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an Jiaotong University, Xi'an, China
| | - Yao Yao
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Xi'an Jiaotong University, Xi'an, China.,Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, Xi'an, China.,Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an Jiaotong University, Xi'an, China
| | - Chuyu Pan
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Xi'an Jiaotong University, Xi'an, China.,Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, Xi'an, China.,Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an Jiaotong University, Xi'an, China
| | - Jingxi Zhang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Xi'an Jiaotong University, Xi'an, China.,Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, Xi'an, China.,Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an Jiaotong University, Xi'an, China
| | - Chun'e Li
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Xi'an Jiaotong University, Xi'an, China.,Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, Xi'an, China.,Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an Jiaotong University, Xi'an, China
| | - Huijie Zhang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Xi'an Jiaotong University, Xi'an, China.,Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, Xi'an, China.,Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an Jiaotong University, Xi'an, China
| | - Yujing Chen
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Xi'an Jiaotong University, Xi'an, China.,Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, Xi'an, China.,Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an Jiaotong University, Xi'an, China
| | - Zhen Zhang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Xi'an Jiaotong University, Xi'an, China.,Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, Xi'an, China.,Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an Jiaotong University, Xi'an, China
| | - Yan Wen
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Xi'an Jiaotong University, Xi'an, China.,Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, Xi'an, China.,Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an Jiaotong University, Xi'an, China
| | - Yumeng Jia
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Xi'an Jiaotong University, Xi'an, China.,Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, Xi'an, China.,Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an Jiaotong University, Xi'an, China
| | - Feng Zhang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Xi'an Jiaotong University, Xi'an, China. .,Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, Xi'an, China. .,Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an Jiaotong University, Xi'an, China.
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7
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Fine Mapping and Functional Analysis of the Gene PcTYR, Involved in Control of Cap Color of Pleurotus cornucopiae. Appl Environ Microbiol 2022; 88:e0217321. [PMID: 35289641 DOI: 10.1128/aem.02173-21] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Oyster mushrooms have a high biological efficiency and are easy to cultivate, which is why they are produced all over the world. Cap color is an important commercial trait for oyster mushrooms. Little is known about the genetic mechanism of the cap color trait in oyster mushrooms, which limits molecular breeding for the improvement of cap color-type cultivars. In this study, a 0.8-Mb major quantitative trait locus (QTL) region controlling cap color in the oyster mushroom Pleurotus cornucopiae was mapped on chromosome 7 through bulked-segregant analysis sequencing (BSA-seq) and extreme-phenotype genome-wide association studies (XP-GWAS). Candidate genes were further selected by comparative transcriptome analysis, and a tyrosinase gene (PcTYR) was identified as the highest-confidence candidate gene. Overexpression of PcTYR resulted in a significantly darker cap color, while the cap color of RNA interference (RNAi) strains for this gene was significantly lighter than that of the wild-type (WT) strains, suggesting that PcTYR plays an essential role in cap color formation. This is the first report about fine mapping and functional verification of a gene controlling cap color in oyster mushrooms. This will enhance our understanding of the genetic basis for cap color formation in oyster mushrooms and will facilitate molecular breeding for cap color. IMPORTANCE Oyster mushrooms are widely cultivated and consumed over the world for their easy cultivation and high biological efficiency (mushroom fresh weight/substrate dry weight × 100%). Fruiting bodies with dark caps are more and more popular according to consumer preferences, but dark varieties are rarely seen on the market. Little is known about the genetic mechanism of the cap color trait in oyster mushrooms, which limits molecular breeding for the improvement of cap color-type cultivars. A major QTL of cap color in oyster mushroom P. cornucopiae was fine mapped by using bulked-segregant analysis (BSA) and extreme-phenotype genome-wide association study (XP-GWAS) analysis. A candidate gene PcTYR coding tyrosinase was further identified with the help of comparative transcriptome analysis. qPCR analysis and genetic transformation tests proved that PcTYR played an essential role in cap color formation. This study will contribute to revealing the genetic mechanism of cap color formation in mushrooms, thereby facilitating molecular breeding for cap color trait.
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8
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Gravio CD, Tao R, Schildcrout JS. Design and analysis of two-phase studies with multivariate longitudinal data. Biometrics 2022. [PMID: 35014029 DOI: 10.1111/biom.13616] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Revised: 11/03/2021] [Accepted: 12/10/2021] [Indexed: 11/27/2022]
Abstract
Two-phase studies are crucial when outcome and covariate data are available in a first phase sample (e.g., a cohort study), but costs associated with retrospective ascertainment of a novel exposure limit the size of the second phase sample, in whom the exposure is collected. For longitudinal outcomes, one class of two-phase studies stratifies subjects based on an outcome vector summary (e.g., an average or a slope over time) and oversamples subjects in the extreme value strata while undersampling subjects in the medium value stratum. Based on the choice of the summary, two-phase studies for longitudinal data can increase efficiency of time-varying and/or time-fixed exposure parameter estimates. In this manuscript, we extend efficient, two-phase study designs to multivariate longitudinal continuous outcomes, and we detail two analysis approaches. The first approach is a multiple imputation analysis that combines complete data from subjects selected for phase two with the incomplete data from those not selected. The second approach is a conditional maximum likelihood analysis that is intended for applications where only data from subjects selected for phase two are available. Importantly, we show that both approaches can be applied to secondary analyses of previously conducted two-phase studies. We examine finite sample operating characteristics of the two approaches and use the Lung Health Study (Connett et al., 1993) to examine genetic associations with lung function decline over time. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Chiara Di Gravio
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee, 37232, U.S.A
| | - Ran Tao
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee, 37232, U.S.A.,Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee, 37232, U.S.A
| | - Jonathan S Schildcrout
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee, 37232, U.S.A
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9
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Espin-Garcia O, Craiu RV, Bull SB. Two-phase sample selection strategies for design and analysis in post-genome-wide association fine-mapping studies. Stat Med 2021; 40:6792-6817. [PMID: 34596256 PMCID: PMC9293221 DOI: 10.1002/sim.9211] [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: 04/01/2020] [Revised: 09/13/2021] [Accepted: 09/14/2021] [Indexed: 11/08/2022]
Abstract
Post-GWAS analysis, in many cases, focuses on fine-mapping targeted genetic regions discovered at GWAS-stage; that is, the aim is to pinpoint potential causal variants and susceptibility genes for complex traits and disease outcomes using next-generation sequencing (NGS) technologies. Large-scale GWAS cohorts are necessary to identify target regions given the typically modest genetic effect sizes. In this context, two-phase sampling design and analysis is a cost-reduction technique that utilizes data collected during phase 1 GWAS to select an informative subsample for phase 2 sequencing. The main goal is to make inference for genetic variants measured via NGS by efficiently combining data from phases 1 and 2. We propose two approaches for selecting a phase 2 design under a budget constraint. The first method identifies sampling fractions that select a phase 2 design yielding an asymptotic variance covariance matrix with certain optimal characteristics, for example, smallest trace, via Lagrange multipliers (LM). The second relies on a genetic algorithm (GA) with a defined fitness function to identify exactly a phase 2 subsample. We perform comprehensive simulation studies to evaluate the empirical properties of the proposed designs for a genetic association study of a quantitative trait. We compare our methods against two ranked designs: residual-dependent sampling and a recently identified optimal design. Our findings demonstrate that the proposed designs, GA in particular, can render competitive power in combined phase 1 and 2 analysis compared with alternative designs while preserving type 1 error control. These results are especially evident under the more practical scenario where design values need to be defined a priori and are subject to misspecification. We illustrate the proposed methods in a study of triglyceride levels in the North Finland Birth Cohort of 1966. R code to reproduce our results is available at github.com/egosv/TwoPhase_postGWAS.
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Affiliation(s)
- Osvaldo Espin-Garcia
- Department of Biostatistics, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada.,Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Radu V Craiu
- Department of Statistical Sciences, Faculty of Arts and Sciences, University of Toronto, Toronto, Ontario, Canada
| | - Shelley B Bull
- Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.,Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, Ontario, Canada
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10
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Impact of rare and common genetic variation in the interleukin-1 pathway on human cytokine responses. Genome Med 2021; 13:94. [PMID: 34034819 PMCID: PMC8145796 DOI: 10.1186/s13073-021-00907-w] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Accepted: 05/11/2021] [Indexed: 01/26/2023] Open
Abstract
Background The interleukin (IL)-1 pathway is primarily associated with innate immunological defense and plays a major role in the induction and regulation of inflammation. Both common and rare genetic variation in this pathway underlies various inflammation-mediated diseases, but the role of rare variants relative to common variants in immune response variability in healthy individuals remains unclear. Methods We performed molecular inversion probe sequencing on 48 IL-1 pathway-related genes in 463 healthy individuals from the Human Functional Genomics Project. We functionally grouped common and rare variants, over gene, subpathway, and inflammatory levels and performed the Sequence Kernel Association Test to test for association with in vitro stimulation-induced cytokine responses; specifically, IL-1β and IL-6 cytokine measurements upon stimulations that represent an array of microbial infections: lipopolysaccharide (LPS), phytohaemagglutinin (PHA), Candida albicans (C. albicans), and Staphylococcus aureus (S. aureus). Results We identified a burden of NCF4 rare variants with PHA-induced IL-6 cytokine and showed that the respective carriers are in the 1% lowest IL-6 producers. Collapsing rare variants in IL-1 subpathway genes produces a bidirectional association with LPS-induced IL-1β cytokine levels, which is reflected by a significant Spearman correlation. On the inflammatory level, we identified a burden of rare variants in genes encoding for proteins with an anti-inflammatory function with S. aureus-induced IL-6 cytokine. In contrast to these rare variant findings which were based on different types of stimuli, common variant associations were exclusively identified with C. albicans-induced cytokine over various levels of grouping, from the gene, to subpathway, to inflammatory level. Conclusions In conclusion, this study shows that functionally grouping common and rare genetic variants enables the elucidation IL-1-mediated biological mechanisms, specifically, for IL-1β and IL-6 cytokine responses induced by various stimuli. The framework used in this study may allow for the analysis of rare and common genetic variants in a wider variety of (non-immune) complex phenotypes and therefore has the potential to contribute to better understanding of unresolved, complex traits and diseases. Supplementary Information The online version contains supplementary material available at 10.1186/s13073-021-00907-w.
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11
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Johnsen PV, Riemer-Sørensen S, DeWan AT, Cahill ME, Langaas M. A new method for exploring gene-gene and gene-environment interactions in GWAS with tree ensemble methods and SHAP values. BMC Bioinformatics 2021; 22:230. [PMID: 33947323 PMCID: PMC8097909 DOI: 10.1186/s12859-021-04041-7] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Accepted: 02/22/2021] [Indexed: 01/08/2023] Open
Abstract
Background The identification of gene–gene and gene–environment interactions in genome-wide association studies is challenging due to the unknown nature of the interactions and the overwhelmingly large number of possible combinations. Parametric regression models are suitable to look for prespecified interactions. Nonparametric models such as tree ensemble models, with the ability to detect any unspecified interaction, have previously been difficult to interpret. However, with the development of methods for model explainability, it is now possible to interpret tree ensemble models efficiently and with a strong theoretical basis. Results We propose a tree ensemble- and SHAP-based method for identifying as well as interpreting potential gene–gene and gene–environment interactions on large-scale biobank data. A set of independent cross-validation runs are used to implicitly investigate the whole genome. We apply and evaluate the method using data from the UK Biobank with obesity as the phenotype. The results are in line with previous research on obesity as we identify top SNPs previously associated with obesity. We further demonstrate how to interpret and visualize interaction candidates. Conclusions The new method identifies interaction candidates otherwise not detected with parametric regression models. However, further research is needed to evaluate the uncertainties of these candidates. The method can be applied to large-scale biobanks with high-dimensional data. Supplementary Information The online version contains supplementary material available at 10.1186/s12859-021-04041-7.
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Affiliation(s)
- Pål V Johnsen
- SINTEF DIGITAL, Forskningsveien 1, 0373, Oslo, Norway. .,Department of Mathematical Sciences, Norwegian University of Science and Technology, A. Getz vei 1, 7491, Trondheim, Norway.
| | | | - Andrew Thomas DeWan
- Department of Chronic Disease Epidemiology and Center for Perinatal, Pediatric and Environmental Epidemiology, Yale School of Public Health, 1 Church Street, New Haven, CT, 06510, USA.,Gemini Center for Sepsis Research, Department of Circulation and Medical Imaging, NTNU, Norwegian University of Science and Technology, Prinsesse Kristinas gate 3, 7030, Trondheim, Norway
| | - Megan E Cahill
- Department of Chronic Disease Epidemiology and Center for Perinatal, Pediatric and Environmental Epidemiology, Yale School of Public Health, 1 Church Street, New Haven, CT, 06510, USA
| | - Mette Langaas
- Department of Mathematical Sciences, Norwegian University of Science and Technology, A. Getz vei 1, 7491, Trondheim, Norway
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12
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Soave D, Lawless JF, Awadalla P. Score tests for scale effects, with application to genomic analysis. Stat Med 2021; 40:3808-3822. [PMID: 33908071 DOI: 10.1002/sim.9000] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2020] [Revised: 04/01/2021] [Accepted: 04/07/2021] [Indexed: 11/07/2022]
Abstract
Tests for variance or scale effects due to covariates are used in many areas and recently, in genomic and genetic association studies. We study score tests based on location-scale models with arbitrary error distributions that allow incorporation of additional adjustment covariates. Tests based on Gaussian and Laplacian double generalized linear models are examined in some detail. Numerical properties of the tests under Gaussian and other error distributions are examined. Our results show that the use of model-based asymptotic distributions with score tests for scale effects does not control type 1 error well in many settings of practical relevance. We consider simple statistics based on permutation distribution approximations, which correspond to well-known statistics derived by another approach. They are shown to give good type 1 error control under different error distributions and under covariate distribution imbalance. The methods are illustrated through a differential gene expression analysis involving breast cancer tumor samples.
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Affiliation(s)
- David Soave
- Department of Mathematics, Wilfrid Laurier University, Waterloo, Ontario, Canada.,Computational Biology Program, Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Jerald F Lawless
- Department of Statistics and Actuarial Science, University of Waterloo, Waterloo, Ontario, Canada
| | - Philip Awadalla
- Computational Biology Program, Ontario Institute for Cancer Research, Toronto, Ontario, Canada.,Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
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13
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Liu M, Xie Z, Costello CA, Zhang W, Chen L, Qi D, Furey A, Randell EW, Rahman P, Zhai G. Metabolomic analysis coupled with extreme phenotype sampling identified that lysophosphatidylcholines are associated with multisite musculoskeletal pain. Pain 2021; 162:600-608. [PMID: 32833795 PMCID: PMC7808366 DOI: 10.1097/j.pain.0000000000002052] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Revised: 08/07/2020] [Accepted: 08/11/2020] [Indexed: 12/18/2022]
Abstract
ABSTRACT Musculoskeletal pain often occurs simultaneously at multiple anatomical sites. The aim of the study was to identify metabolic biomarkers for multisite musculoskeletal pain (MSMP) by metabolomics with an extreme phenotype sampling strategy. The study participants (n = 610) were derived from the Newfoundland Osteoarthritis Study. Musculoskeletal pain was assessed using a self-reported pain questionnaire where painful sites were circled on a manikin by participants and the total number of painful sites were calculated. Targeted metabolomic profiling on fasting plasma samples was performed using the Biocrates AbsoluteIDQ p180 kit. Plasma cytokine concentrations including tumor necrosis factor-α, interleukin-6, interleukin-1β, and macrophage migration inhibitory factor were assessed by enzyme-linked immunosorbent assay. Data on blood cholesterol profiles were retrieved from participants' medical records. Demographic, anthropological, and clinical information was self-reported. The number of reported painful sites ranged between 0 and 21. Two hundred and five participants were included in the analysis comprising 83 who had ≥7 painful sites and 122 who had ≤1 painful site. Women and younger people were more likely to have MSMP (P ≤ 0.02). Multisite musculoskeletal pain was associated with a higher risk of having incontinence, worse functional status and longer period of pain, and higher levels of low-density lipoprotein and non-high-density lipoprotein cholesterol (all P ≤ 0.03). Among the 186 metabolites measured, 2 lysophosphatidylcholines, 1 with 26 carbons with no double bond and 1 with 28 carbons with 1 double bond, were significantly and positively associated with MSMP after adjusting for multiple testing with the Bonferroni method (P ≤ 0.0001) and could be considered as novel metabolic markers for MSMP.
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Affiliation(s)
- Ming Liu
- Discipline of Genetics, Faculty of Medicine, Memorial University of Newfoundland, St. John's, NL, Canada
| | - Zikun Xie
- Discipline of Genetics, Faculty of Medicine, Memorial University of Newfoundland, St. John's, NL, Canada
- Department of Orthopaedics, Xiangya Hospital, Central South University, Changsha, China
| | - Christie A. Costello
- Discipline of Genetics, Faculty of Medicine, Memorial University of Newfoundland, St. John's, NL, Canada
| | - Weidong Zhang
- Discipline of Genetics, Faculty of Medicine, Memorial University of Newfoundland, St. John's, NL, Canada
- School of Pharmaceutical Sciences, Jilin University, Changchun, China
| | - Liujun Chen
- College of Pharmacy, University of Manitoba, Winnipeg, Canada
| | - Dake Qi
- College of Pharmacy, University of Manitoba, Winnipeg, Canada
| | - Andrew Furey
- Discipline of Surgery, Faculty of Medicine, Memorial University of Newfoundland, St. John's, NL, Canada
| | - Edward W. Randell
- Discipline of Laboratory Medicine, Faculty of Medicine, Memorial University of Newfoundland, St. John's, NL, Canada
| | - Proton Rahman
- Discipline of Medicine, Faculty of Medicine, Memorial University of Newfoundland, St. John's, NL, Canada
| | - Guangju Zhai
- Discipline of Genetics, Faculty of Medicine, Memorial University of Newfoundland, St. John's, NL, Canada
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14
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Zhai G, Sun X, Randell EW, Liu M, Wang N, Tolstykh I, Rahman P, Torner J, Lewis CE, Nevitt MC, Guermazi A, Roemer F, Felson DT. Phenylalanine Is a Novel Marker for Radiographic Knee Osteoarthritis Progression: The MOST Study. J Rheumatol 2021; 48:123-128. [PMID: 32358162 PMCID: PMC8039838 DOI: 10.3899/jrheum.200054] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/21/2020] [Indexed: 12/20/2022]
Abstract
OBJECTIVE To identify plasma markers associated with an increased risk of radiographic knee osteoarthritis(OA) progression using a metabolomics approach. METHODS Study participants were from the Multicenter Osteoarthritis Study (MOST) and were categorized into 2 groups based on the presence of baseline radiographic OA. Subjects in group 1 had unilateral knee OA and subjects in group 2 had bilateral knee OA. Progression was defined as a half-grade or greater worsening in joint space width at 30-month follow-up. For group 1, a participant progressed when their OA knee showed radiographic progression and the contralateral knee developed OA; for group 2, a participant progressed when both knees with OA showed radiographic progression. Metabolomic profiling was performed on plasma samples collected at baseline and logistic regression was performed to test the association between each metabolite and knee OA progression after adjustment for age, sex, BMI, and clinic site. Significance was defined as P ≤ 0.0003 in the combined analysis. RESULTS There were 234 progressors (57 in group 1 and 177 in group 2) and 322 nonprogressors (206 in group 1 and 116 in group 2) included in the analyses. Among 157 metabolites studied, we found that odds of progression were 1.46 times higher per SD increase of phenylalanine level (95% CI 1.20-1.77, P = 0.0001) in the combined analysis. Sex-specific analysis showed that an association was seen in women (P = 0.0002) but not in men. CONCLUSION Our data suggest that phenylalanine might be a novel plasma marker for higher risk of bilateral radiographic knee OA progression in women.
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Affiliation(s)
- Guangju Zhai
- G. Zhai, PhD, M. Liu, MSc, Discipline of Genetics, Faculty of Medicine, Memorial University of Newfoundland, St. John's, Newfoundland, Canada;
| | - Xianbang Sun
- X. Sun, MS, Department of Rheumatology, Boston University School of Medicine, Boston, USA
| | - Edward W Randell
- E. Randell, PhD, Division of Laboratory Medicine, Faculty of Medicine, Memorial University of Newfoundland, St. John's, Newfoundland, Canada
| | - Ming Liu
- G. Zhai, PhD, M. Liu, MSc, Discipline of Genetics, Faculty of Medicine, Memorial University of Newfoundland, St. John's, Newfoundland, Canada
| | - Na Wang
- N. Wang, PhD, Biostatistics and Epidemiology Data Analytics Center, Boston University School of Public Health, Boston, USA
| | - Irina Tolstykh
- I. Tolstykh, MS, M.C. Nevitt, PhD, MPH, Epidemiology and Biostatistics, University of California, San Francisco, USA
| | - Proton Rahman
- P. Rahman, MD, Discipline of Medicine, Faculty of Medicine, Memorial University of Newfoundland, St. John's, Newfoundland, Canada
| | - James Torner
- J. Torner, PhD, Department of Epidemiology, University of Iowa, Iowa City, Iowa, USA
| | - Cora E Lewis
- C.E. Lewis, MD, Department of Epidemiology, University of Alabama, Birmingham, USA
| | - Michael C Nevitt
- I. Tolstykh, MS, M.C. Nevitt, PhD, MPH, Epidemiology and Biostatistics, University of California, San Francisco, USA
| | - Ali Guermazi
- A. Guermazi, MD, PhD, F. Roemer, MD, Department of Radiology, Boston University School of Medicine, Boston, USA
| | - Frank Roemer
- A. Guermazi, MD, PhD, F. Roemer, MD, Department of Radiology, Boston University School of Medicine, Boston, USA
| | - David T Felson
- D.T. Felson, MD, MPH, Department of Rheumatology, Boston University School of Medicine, Boston, USA, and NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Manchester University NHS Foundation Trust, Manchester, UK
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15
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Swietlik EM, Prapa M, Martin JM, Pandya D, Auckland K, Morrell NW, Gräf S. 'There and Back Again'-Forward Genetics and Reverse Phenotyping in Pulmonary Arterial Hypertension. Genes (Basel) 2020; 11:E1408. [PMID: 33256119 PMCID: PMC7760524 DOI: 10.3390/genes11121408] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Revised: 11/17/2020] [Accepted: 11/23/2020] [Indexed: 02/07/2023] Open
Abstract
Although the invention of right heart catheterisation in the 1950s enabled accurate clinical diagnosis of pulmonary arterial hypertension (PAH), it was not until 2000 when the landmark discovery of the causative role of bone morphogenetic protein receptor type II (BMPR2) mutations shed new light on the pathogenesis of PAH. Since then several genes have been discovered, which now account for around 25% of cases with the clinical diagnosis of idiopathic PAH. Despite the ongoing efforts, in the majority of patients the cause of the disease remains elusive, a phenomenon often referred to as "missing heritability". In this review, we discuss research approaches to uncover the genetic architecture of PAH starting with forward phenotyping, which in a research setting should focus on stable intermediate phenotypes, forward and reverse genetics, and finally reverse phenotyping. We then discuss potential sources of "missing heritability" and how functional genomics and multi-omics methods are employed to tackle this problem.
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Affiliation(s)
- Emilia M. Swietlik
- Department of Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK; (E.M.S.); (M.P.); (J.M.M.); (D.P.); (K.A.); (N.W.M.)
- Royal Papworth Hospital NHS Foundation Trust, Cambridge CB2 0AY, UK
- Addenbrooke’s Hospital NHS Foundation Trust, Cambridge CB2 0QQ, UK
| | - Matina Prapa
- Department of Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK; (E.M.S.); (M.P.); (J.M.M.); (D.P.); (K.A.); (N.W.M.)
- Addenbrooke’s Hospital NHS Foundation Trust, Cambridge CB2 0QQ, UK
| | - Jennifer M. Martin
- Department of Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK; (E.M.S.); (M.P.); (J.M.M.); (D.P.); (K.A.); (N.W.M.)
| | - Divya Pandya
- Department of Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK; (E.M.S.); (M.P.); (J.M.M.); (D.P.); (K.A.); (N.W.M.)
| | - Kathryn Auckland
- Department of Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK; (E.M.S.); (M.P.); (J.M.M.); (D.P.); (K.A.); (N.W.M.)
| | - Nicholas W. Morrell
- Department of Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK; (E.M.S.); (M.P.); (J.M.M.); (D.P.); (K.A.); (N.W.M.)
- Royal Papworth Hospital NHS Foundation Trust, Cambridge CB2 0AY, UK
- Addenbrooke’s Hospital NHS Foundation Trust, Cambridge CB2 0QQ, UK
- NIHR BioResource for Translational Research, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK
| | - Stefan Gräf
- Department of Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK; (E.M.S.); (M.P.); (J.M.M.); (D.P.); (K.A.); (N.W.M.)
- NIHR BioResource for Translational Research, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0PT, UK
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16
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Bao J, Yu Y, Li H, Hawks J, Szatkowski G, Dade B, Wang H, Liu P, Brutnell T, Spehar B, Tye-Murray N. Evidence for independent peripheral and central age-related hearing impairment. J Neurosci Res 2020; 98:1800-1814. [PMID: 32415883 DOI: 10.1002/jnr.24639] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2019] [Revised: 03/12/2020] [Accepted: 04/10/2020] [Indexed: 11/11/2022]
Abstract
Deleterious age-related changes in the central auditory nervous system have been referred to as central age-related hearing impairment (ARHI) or central presbycusis. Central ARHI is often assumed to be the consequence of peripheral ARHI. However, it is possible that certain aspects of central ARHI are independent from peripheral ARHI. A confirmation of this possibility could lead to significant improvements in current rehabilitation practices. The major difficulty in addressing this issue arises from confounding factors, such as other age-related changes in both the cochlea and central non-auditory brain structures. Because gap detection is a common measure of central auditory temporal processing, and gap detection thresholds are less influenced by changes in other brain functions such as learning and memory, we investigated the potential relationship between age-related peripheral hearing loss (i.e., audiograms) and age-related changes in gap detection. Consistent with previous studies, a significant difference was found for gap detection thresholds between young and older adults. However, among older adults, no significant associations were observed between gap detection ability and several other independent variables including the pure tone audiogram average, the Wechsler Adult Intelligence Scale-Vocabulary score, gender, and age. Statistical analyses showed little or no contributions from these independent variables to gap detection thresholds. Thus, our data indicate that age-related decline in central temporal processing is largely independent of peripheral ARHI.
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Affiliation(s)
- Jianxin Bao
- Department of Anatomy and Neurobiology, Northeast Ohio Medical University, Rootstown, OH, USA
| | - Yan Yu
- The First People's Hospital of Zhangjiagang, Zhangjiagang, China
| | - Hui Li
- Department of Anatomy and Neurobiology, Northeast Ohio Medical University, Rootstown, OH, USA
| | - John Hawks
- Department of Anatomy and Neurobiology, Northeast Ohio Medical University, Rootstown, OH, USA
| | - Grace Szatkowski
- Department of Anatomy and Neurobiology, Northeast Ohio Medical University, Rootstown, OH, USA
| | - Bethany Dade
- Department of Anatomy and Neurobiology, Northeast Ohio Medical University, Rootstown, OH, USA
| | - Hao Wang
- Department of Statistics, Iowa State University, Ames, IA, USA
| | - Peng Liu
- Department of Statistics, Iowa State University, Ames, IA, USA
| | - Thomas Brutnell
- Department of Research and Development, Gateway Biotechnology Inc., St. Louis. MO, USA
| | - Brent Spehar
- Department of Otolaryngology-Head and Neck Surgery, Washington University in St. Louis, St. Louis, MO, USA
| | - Nancy Tye-Murray
- Department of Otolaryngology-Head and Neck Surgery, Washington University in St. Louis, St. Louis, MO, USA
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17
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A genetic profile of refractory individuals with major depressive disorder and their responsiveness to transcranial magnetic stimulation. Brain Stimul 2020; 13:1091-1093. [PMID: 32387243 DOI: 10.1016/j.brs.2020.04.019] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2020] [Accepted: 04/28/2020] [Indexed: 01/13/2023] Open
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18
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McClelland EK, Chan MTT, Lin X, Sakhrani D, Vincelli F, Kim JH, Heath DD, Devlin RH. Loci associated with variation in gene expression and growth in juvenile salmon are influenced by the presence of a growth hormone transgene. BMC Genomics 2020; 21:185. [PMID: 32106818 PMCID: PMC7045383 DOI: 10.1186/s12864-020-6586-0] [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: 03/29/2019] [Accepted: 02/17/2020] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Growth regulation is a complex process influenced by genetic and environmental factors. We examined differences between growth hormone (GH) transgenic (T) and non-transgenic (NT) coho salmon to elucidate whether the same loci were involved in controlling body size and gene expression phenotypes, and to assess whether physiological transformations occurring from GH transgenesis were under the influence of alternative pathways. The following genomic techniques were used to explore differences between size classes within and between transgenotypes (T vs. NT): RNA-Seq/Differentially Expressed Gene (DEG) analysis, quantitative PCR (qPCR) and OpenArray analysis, Genotyping-by-Sequencing, and Genome-Wide Association Study (GWAS). RESULTS DEGs identified in comparisons between the large and small tails of the size distributions of T and NT salmon (NTLarge, NTSmall, TLarge and TSmall) spanned a broad range of biological processes, indicating wide-spread influence of the transgene on gene expression. Overexpression of growth hormone led to differences in regulatory loci between transgenotypes and size classes. Expression levels were significantly greater in T fish at 16 of 31 loci and in NT fish for 10 loci. Eleven genes exhibited different mRNA levels when the interaction of size and transgenotype was considered (IGF1, IGFBP1, GH, C3-4, FAS, FAD6, GLUT1, G6PASE1, GOGAT, MID1IP1). In the GWAS, 649 unique SNPs were significantly associated with at least one study trait, with most SNPs associated with one of the following traits: C3_4, ELA1, GLK, IGF1, IGFBP1, IGFII, or LEPTIN. Only 1 phenotype-associated SNP was found in common between T and NT fish, and there were no SNPs in common between transgenotypes when size was considered. CONCLUSIONS Multiple regulatory loci affecting gene expression were shared between fast-growing and slow-growing fish within T or NT groups, but no such regulatory loci were found to be shared between NT and T groups. These data reveal how GH overexpression affects the regulatory responses of the genome resulting in differences in growth, physiological pathways, and gene expression in T fish compared with the wild type. Understanding the complexity of regulatory gene interactions to generate phenotypes has importance in multiple fields ranging from applications in selective breeding to quantifying influences on evolutionary processes.
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Affiliation(s)
- Erin Kathleen McClelland
- Fisheries and Oceans Canada, 4160 Marine Drive, West Vancouver, BC, V7V 1N6, Canada. .,, EKM Consulting 730 Drake St, Nanaimo, BC, V9S 2T1, Canada.
| | - Michelle T T Chan
- Fisheries and Oceans Canada, 4160 Marine Drive, West Vancouver, BC, V7V 1N6, Canada
| | - Xiang Lin
- Fisheries and Oceans Canada, 4160 Marine Drive, West Vancouver, BC, V7V 1N6, Canada
| | - Dionne Sakhrani
- Fisheries and Oceans Canada, 4160 Marine Drive, West Vancouver, BC, V7V 1N6, Canada
| | - Felicia Vincelli
- Great Lakes Institute for Environmental Research, University of Windsor, 401 Sunset Ave, Windsor, ON, N9B 3P4, Canada
| | - Jin-Hyoung Kim
- Fisheries and Oceans Canada, 4160 Marine Drive, West Vancouver, BC, V7V 1N6, Canada.,Korea Polar Research Institute (KOPRI), 26, Songdomirae-ro, Yeonsu-gu, Incheon, 21990, South Korea
| | - Daniel D Heath
- Great Lakes Institute for Environmental Research, University of Windsor, 401 Sunset Ave, Windsor, ON, N9B 3P4, Canada
| | - Robert H Devlin
- Fisheries and Oceans Canada, 4160 Marine Drive, West Vancouver, BC, V7V 1N6, Canada
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19
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Qiu C, Yu F, Su K, Zhao Q, Zhang L, Xu C, Hu W, Wang Z, Zhao L, Tian Q, Wang Y, Deng H, Shen H. Multi-omics Data Integration for Identifying Osteoporosis Biomarkers and Their Biological Interaction and Causal Mechanisms. iScience 2020; 23:100847. [PMID: 32058959 PMCID: PMC6997862 DOI: 10.1016/j.isci.2020.100847] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Revised: 11/22/2019] [Accepted: 01/13/2020] [Indexed: 12/31/2022] Open
Abstract
Osteoporosis is characterized by low bone mineral density (BMD). The advancement of high-throughput technologies and integrative approaches provided an opportunity for deciphering the mechanisms underlying osteoporosis. Here, we generated genomic, transcriptomic, methylomic, and metabolomic datasets from 119 subjects with high (n = 61) and low (n = 58) BMDs. By adopting sparse multiple discriminative canonical correlation analysis, we identified an optimal multi-omics biomarker panel with 74 differentially expressed genes (DEGs), 75 differentially methylated CpG sites (DMCs), and 23 differential metabolic products (DMPs). By linking genetic data, we identified 199 targeted BMD-associated expression/methylation/metabolite quantitative trait loci (eQTLs/meQTLs/metaQTLs). The reconstructed networks/pathways showed extensive biomarker interactions, and a substantial proportion of these biomarkers were enriched in RANK/RANKL, MAPK/TGF-β, and WNT/β-catenin pathways and G-protein-coupled receptor, GTP-binding/GTPase, telomere/mitochondrial activities that are essential for bone metabolism. Five biomarkers (FADS2, ADRA2A, FMN1, RABL2A, SPRY1) revealed causal effects on BMD variation. Our study provided an innovative framework and insights into the pathogenesis of osteoporosis.
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Affiliation(s)
- Chuan Qiu
- Center for Bioinformatics and Genomics, Department of Biostatistics and Data Science, School of Public Health and Tropical Medicine, Tulane University, New Orleans 70112, LA, USA
| | - Fangtang Yu
- Center for Bioinformatics and Genomics, Department of Biostatistics and Data Science, School of Public Health and Tropical Medicine, Tulane University, New Orleans 70112, LA, USA
| | - Kuanjui Su
- Center for Bioinformatics and Genomics, Department of Biostatistics and Data Science, School of Public Health and Tropical Medicine, Tulane University, New Orleans 70112, LA, USA
| | - Qi Zhao
- Department of Preventive Medicine, College of Medicine, University of Tennessee Health Science Center, Memphis 38163, TN, USA
| | - Lan Zhang
- Center for Bioinformatics and Genomics, Department of Biostatistics and Data Science, School of Public Health and Tropical Medicine, Tulane University, New Orleans 70112, LA, USA
| | - Chao Xu
- Department of Biostatistics and Epidemiology, University of Oklahoma Health Sciences Center, Oklahoma City 73104, OK, USA
| | - Wenxing Hu
- Department of Biomedical Engineering, Tulane University, New Orleans 70118, LA, USA
| | - Zun Wang
- Center for Bioinformatics and Genomics, Department of Biostatistics and Data Science, School of Public Health and Tropical Medicine, Tulane University, New Orleans 70112, LA, USA; Xiangya Nursing School, Central South University, Changsha 410013, China
| | - Lanjuan Zhao
- Center for Bioinformatics and Genomics, Department of Biostatistics and Data Science, School of Public Health and Tropical Medicine, Tulane University, New Orleans 70112, LA, USA
| | - Qing Tian
- Center for Bioinformatics and Genomics, Department of Biostatistics and Data Science, School of Public Health and Tropical Medicine, Tulane University, New Orleans 70112, LA, USA
| | - Yuping Wang
- Department of Biomedical Engineering, Tulane University, New Orleans 70118, LA, USA
| | - Hongwen Deng
- Center for Bioinformatics and Genomics, Department of Biostatistics and Data Science, School of Public Health and Tropical Medicine, Tulane University, New Orleans 70112, LA, USA; School of Basic Medical Science, Central South University, Changsha 410013, China
| | - Hui Shen
- Center for Bioinformatics and Genomics, Department of Biostatistics and Data Science, School of Public Health and Tropical Medicine, Tulane University, New Orleans 70112, LA, USA.
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Alexandre PA, Porto-Neto LR, Karaman E, Lehnert SA, Reverter A. Pooled genotyping strategies for the rapid construction of genomic reference populations1. J Anim Sci 2019; 97:4761-4769. [PMID: 31710679 PMCID: PMC6915231 DOI: 10.1093/jas/skz344] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2019] [Accepted: 11/06/2019] [Indexed: 01/24/2023] Open
Abstract
The growing concern with the environment is making important for livestock producers to focus on selection for efficiency-related traits, which is a challenge for commercial cattle herds due to the lack of pedigree information. To explore a cost-effective opportunity for genomic evaluations of commercial herds, this study compared the accuracy of bulls' genomic estimated breeding values (GEBV) using different pooled genotype strategies. We used ten replicates of previously simulated genomic and phenotypic data for one low (t1) and one moderate (t2) heritability trait of 200 sires and 2,200 progeny. Sire's GEBV were calculated using a univariate mixed model, with a hybrid genomic relationship matrix (h-GRM) relating sires to: 1) 1,100 pools of 2 animals; 2) 440 pools of 5 animals; 3) 220 pools of 10 animals; 4) 110 pools of 20 animals; 5) 88 pools of 25 animals; 6) 44 pools of 50 animals; and 7) 22 pools of 100 animals. Pooling criteria were: at random, grouped sorting by t1, grouped sorting by t2, and grouped sorting by a combination of t1 and t2. The same criteria were used to select 110, 220, 440, and 1,100 individual genotypes for GEBV calculation to compare GEBV accuracy using the same number of individual genotypes and pools. Although the best accuracy was achieved for a given trait when pools were grouped based on that same trait (t1: 0.50-0.56, t2: 0.66-0.77), pooling by one trait impacted negatively on the accuracy of GEBV for the other trait (t1: 0.25-0.46, t2: 0.29-0.71). Therefore, the combined measure may be a feasible alternative to use the same pools to calculate GEBVs for both traits (t1: 0.45-0.57, t2: 0.62-0.76). Pools of 10 individuals were identified as representing a good compromise between loss of accuracy (~10%-15%) and cost savings (~90%) from genotype assays. In addition, we demonstrated that in more than 90% of the simulations, pools present higher sires' GEBV accuracy than individual genotypes when the number of genotype assays is limited (i.e., 110 or 220) and animals are assigned to pools based on phenotype. Pools assigned at random presented the poorest results (t1: 0.07-0.45, t2: 0.14-0.70). In conclusion, pooling by phenotype is the best approach to implementing genomic evaluation using commercial herd data, particularly when pools of 10 individuals are evaluated. While combining phenotypes seems a promising strategy to allow more flexibility to the estimates made using pools, more studies are necessary in this regard.
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Affiliation(s)
- Pâmela A Alexandre
- Agriculture & Food, Commonwealth Scientific and Industrial Research Organization, Brisbane, QLD, Australia
| | - Laercio R Porto-Neto
- Agriculture & Food, Commonwealth Scientific and Industrial Research Organization, Brisbane, QLD, Australia
| | - Emre Karaman
- Center for Quantitative Genetics and Genomics, Aarhus University, Tjele, Denmark
| | - Sigrid A Lehnert
- Agriculture & Food, Commonwealth Scientific and Industrial Research Organization, Brisbane, QLD, Australia
| | - Antonio Reverter
- Agriculture & Food, Commonwealth Scientific and Industrial Research Organization, Brisbane, QLD, Australia
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Bis-Brewer DM, Fazal S, Züchner S. Genetic modifiers and non-Mendelian aspects of CMT. Brain Res 2019; 1726:146459. [PMID: 31525351 DOI: 10.1016/j.brainres.2019.146459] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2019] [Revised: 09/04/2019] [Accepted: 09/12/2019] [Indexed: 12/14/2022]
Abstract
Charcot-Marie-Tooth (CMT) neuropathies are amongst the most common inherited diseases in neurology. While great strides have been made to identify the genesis of these diseases, a diagnostic gap of 30-60% remains. Classic models of genetic causation may be limited to fully close this gap and, thus, we review the current state and future role of alternative, non-Mendelian forms of genetics in CMT. Promising synergies exist to further define the full genetic architecture of inherited neuropathies, including affordable whole-genome sequencing, increased data aggregation and clinical collaboration, improved bioinformatics and statistical methodology, and vastly improved computational resources. Given the recent advances in genetic therapies for rare diseases, it becomes a matter of urgency to diagnose CMT patients with great fidelity. Otherwise, they will not be able to benefit from such therapeutic options, or worse, suffer harm when pathogenicity of genetic variation is falsely evaluated. In addition, the newly identified modifier and risk genes may offer alternative targets for pharmacotherapy of inherited and, potentially, even acquired forms of neuropathies.
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Affiliation(s)
- Dana M Bis-Brewer
- Dr. John T. Macdonald Foundation, Department of Human Genetics and John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Sarah Fazal
- Dr. John T. Macdonald Foundation, Department of Human Genetics and John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Stephan Züchner
- Dr. John T. Macdonald Foundation, Department of Human Genetics and John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA.
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Oliynyk RT. Evaluating the Potential of Younger Cases and Older Controls Cohorts to Improve Discovery Power in Genome-Wide Association Studies of Late-Onset Diseases. J Pers Med 2019; 9:jpm9030038. [PMID: 31336617 PMCID: PMC6789773 DOI: 10.3390/jpm9030038] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2019] [Revised: 07/15/2019] [Accepted: 07/16/2019] [Indexed: 11/25/2022] Open
Abstract
For more than a decade, genome-wide association studies have been making steady progress in discovering the causal gene variants that contribute to late-onset human diseases. Polygenic late-onset diseases in an aging population display a risk allele frequency decrease at older ages, caused by individuals with higher polygenic risk scores becoming ill proportionately earlier and bringing about a change in the distribution of risk alleles between new cases and the as-yet-unaffected population. This phenomenon is most prominent for diseases characterized by high cumulative incidence and high heritability, examples of which include Alzheimer’s disease, coronary artery disease, cerebral stroke, and type 2 diabetes, while for late-onset diseases with relatively lower prevalence and heritability, exemplified by cancers, the effect is significantly lower. In this research, computer simulations have demonstrated that genome-wide association studies of late-onset polygenic diseases showing high cumulative incidence together with high initial heritability will benefit from using the youngest possible age-matched cohorts. Moreover, rather than using age-matched cohorts, study cohorts combining the youngest possible cases with the oldest possible controls may significantly improve the discovery power of genome-wide association studies.
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Affiliation(s)
- Roman Teo Oliynyk
- Centre for Computational Evolution, University of Auckland, Auckland 1010, New Zealand.
- Department of Computer Science, University of Auckland, Auckland 1010, New Zealand.
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23
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Oliynyk RT. Age-related late-onset disease heritability patterns and implications for genome-wide association studies. PeerJ 2019; 7:e7168. [PMID: 31231601 PMCID: PMC6573810 DOI: 10.7717/peerj.7168] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2018] [Accepted: 05/22/2019] [Indexed: 01/06/2023] Open
Abstract
Genome-wide association studies (GWASs) and other computational biology techniques are gradually discovering the causal gene variants that contribute to late-onset human diseases. After more than a decade of genome-wide association study efforts, these can account for only a fraction of the heritability implied by familial studies, the so-called "missing heritability" problem. Computer simulations of polygenic late-onset diseases (LODs) in an aging population have quantified the risk allele frequency decrease at older ages caused by individuals with higher polygenic risk scores (PRSs) becoming ill proportionately earlier. This effect is most prominent for diseases characterized by high cumulative incidence and high heritability, examples of which include Alzheimer's disease, coronary artery disease, cerebral stroke, and type 2 diabetes. The incidence rate for LODs grows exponentially for decades after early onset ages, guaranteeing that the cohorts used for GWASs overrepresent older individuals with lower PRSs, whose disease cases are disproportionately due to environmental causes such as old age itself. This mechanism explains the decline in clinical predictive power with age and the lower discovery power of familial studies of heritability and GWASs. It also explains the relatively constant-with-age heritability found for LODs of lower prevalence, exemplified by cancers.
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Affiliation(s)
- Roman Teo Oliynyk
- Centre for Computational Evolution, University of Auckland, Auckland, New Zealand
- Department of Computer Science, University of Auckland, Auckland, New Zealand
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