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Pleiotropic associations of heterozygosity for the SERPINA1 Z allele in the UK Biobank

Katherine A. Fawcett, Kijoung Song, Guoqing Qian, Aliki-Eleni Farmaki, Richard Packer, Catherine John, Nick Shrine, Raquel Granell, Sue Ring, Nicholas J. Timpson, Laura M. Yerges-Armstrong, Richard Eastell, Louise V. Wain, Robert A. Scott, Martin D. Tobin, Ian P. Hall
ERJ Open Research 2021 7: 00049-2021; DOI: 10.1183/23120541.00049-2021
Katherine A. Fawcett
1Dept of Health Sciences, University of Leicester, Leicester, UK
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Kijoung Song
2Human Genetics, GlaxoSmithKline, Collegeville, PA, USA
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Guoqing Qian
3Dept of General Internal Medicine, Ningbo First Hospital, Ningbo City, Zhejiang Province, China
4Division of Respiratory Medicine, University of Nottingham, and NIHR Nottingham BRC, NUH NHS Trust, Nottingham, UK
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Aliki-Eleni Farmaki
5MRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, University College London, London, UK
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  • ORCID record for Aliki-Eleni Farmaki
Richard Packer
1Dept of Health Sciences, University of Leicester, Leicester, UK
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Catherine John
1Dept of Health Sciences, University of Leicester, Leicester, UK
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Nick Shrine
1Dept of Health Sciences, University of Leicester, Leicester, UK
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Raquel Granell
6Medical Research Council Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
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Sue Ring
6Medical Research Council Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
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Nicholas J. Timpson
6Medical Research Council Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
7Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
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Laura M. Yerges-Armstrong
2Human Genetics, GlaxoSmithKline, Collegeville, PA, USA
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Richard Eastell
8Dept of Oncology and Metabolism, University of Sheffield, Sheffield, UK
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Louise V. Wain
1Dept of Health Sciences, University of Leicester, Leicester, UK
9National Institute for Health Research, Leicester Respiratory Biomedical Research Centre, Glenfield Hospital, Leicester, UK
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Robert A. Scott
10Human Genetics – R&D, GSK Medicines Research Centre, Stevenage, UK
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Martin D. Tobin
1Dept of Health Sciences, University of Leicester, Leicester, UK
9National Institute for Health Research, Leicester Respiratory Biomedical Research Centre, Glenfield Hospital, Leicester, UK
11These authors contributed equally
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  • For correspondence: kaf19@leicester.ac.uk
Ian P. Hall
4Division of Respiratory Medicine, University of Nottingham, and NIHR Nottingham BRC, NUH NHS Trust, Nottingham, UK
11These authors contributed equally
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  • For correspondence: kaf19@leicester.ac.uk
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    FIGURE 1

    Traits associated with the SERPINA1 Z allele in UK Biobank. Traits displayed are those with a false discovery rate (FDR) <0.01 from phenome-wide association study of 2411 phenotypes across 379 101 UK Biobank participants using the a) heterozygous model for the Z allele (wild-type versus heterozygous individuals) and b) recessive model for the Z allele (wild-type and heterozygous individuals versus individuals homozygous for the Z allele). HES: hospital episode statistics; FBC: full blood count; FVC: forced vital capacity; FEV1: forced expiratory volume in 1 s; PEF: peak expiratory flow; ENT: ear, nose and throat.

Tables

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  • TABLE 1

    Association between the SERPINA1 Z allele and blood biomarkers in unrelated, European UK Biobank participants

    BiomarkerHeterozygous genetic modelRecessive genetic model
    β±sep-valueβ±sep-value
    Alanine aminotransferase U·L−11.163±0.1122.95×10−253.037±1.2460.015
    Albumin g·L−10.712±0.0223.11×10−2290.306±0.2430.208
    Alkaline phosphatase U·L−12.968±0.2135.81×10−442.379±2.3730.316
    Apolipoprotein B g·L−1−0.0037±0.00210.0820.042±0.0240.086
    Apolipoprotein A g·L−1−0.0045±0.00190.0200.019±0.0220.375
    Aspartate aminotransferase U·L−10.707±0.0862.27×10−166.353±0.9563.04×10−11
    C-reactive protein mg·L−1−0.174±0.0361.11×10−60.192±0.3960.628
    Calcium mmol·L−10.012±0.000804.01×10−500.01±0.0090.265
    Cholesterol mmol·L−10.0051±0.00920.5760.19±0.1020.063
    Creatinine μmol·L−1−0.067±0.1290.601−0.94±1.4350.512
    Cystatin C mg·L−10.0090±0.00138.91×10−120.019±0.0150.204
    Direct bilirubin μmol·L−10.041±0.00731.64×10−80.158±0.0790.046
    eGFR#−0.241±0.1570.125−1.810±1.7320.296
    γ-Glutamyltransferase U·L−10.253±0.3420.4608.045±3.8180.035
    Glucose mmol·L−1−0.0032±0.0100.758−0.133±0.1140.244
    HbA1c mmol·mol−1−0.187±0.0523.40×10−4−1.781±0.5882.46×10−3
    HDL–cholesterol mmol·L−10.0015±0.00300.6050.142±0.0332.01×10−5
    IGF-1 nmol·L−1−0.212±0.0452.35×10−6−2.245±0.57.19×10−6
    LDL direct mmol·L−10.011±0.0070.1130.115±0.0790.145
    Lipoprotein A nmol·L−1−0.324±0.4520.474−0.151±5.1150.976
    Oestradiol pmol·L−19.577±8.4410.25788.051±96.1440.360
    Phosphate mmol·L−10.0027±0.00130.042−0.014±0.0150.352
    Rheumatoid factor IU·mL−10.113±0.5290.832−3.27±5.70.566
    SHBG nmol·L−14.531±0.2181.06×10−9540.573±2.4025.33×10−64
    Testosterone nmol·L−10.37±0.0231.84×10−572.986±0.2586.96×10−31
    Total bilirubin μmol·L−10.146±0.0353.54×10−50.52±0.3910.184
    Total protein g·L−10.578±0.0351.06×10−620.459±0.3820.229
    Triglycerides mmol·L−1−0.023±0.00824.69×10−3−0.324±0.0924.21×10−4
    Urate μmol·L−11.096±0.560.050−1.325±6.2520.832
    Urea mmol·L−10.051±0.0112.69×10−60.06±0.1220.620
    Vitamin D nmol·L−1−0.041±0.1750.816−2.547±1.9550.193

    Results are based on linear regression adjusting for sex, age, age2, ancestry-based principal components and genotyping array. The heterozygous or recessive genetic model was also included in the regression as shown. eGFR: estimated glomerular filtration rate; HbA1c: glycated haemoglobin; HDL: high-density lipoprotein; IGF: insulin-like growth factor; LDL: low-density lipoprotein; SHBG: sex hormone-binding globulin. #: calculated using the following formula: if cystatin C (cys)≤0.8, then eGFR=133*((cys/0.8)**−0.499)*(0.996**age)*[0.932 if female]; whereas if cys>0.8, then eGFR=133*((cys/0.8)**−1.328)*(0.996**age)*[0.932 if female].

    • TABLE 2

      Association between the SERPINA1 Z allele and height, lung function traits, and COPD in unrelated, European UK Biobank participants

      Genetic modelSmoking statusTest/comparison nHeight cmFEV1 mLFEV1/FVCFVC mLCOPD#COPD GOLD 1–4¶
      β±sep-valueβ±sep-valueβ±sep-valueβ±sep-valueOR (95% CI)p-valueOR (95% CI)p-value
      HetAll11 877/291 3831.023±0.0593.91×10−689.26±4.530.0410.00091±0.000570.1089.38±5.430.0841.05 (0.96–1.14)0.2681.04 (0.98–1.09)0.171
      Ever-smokers5357/133 7791.027±0.0878.53×10−32−2.63±7.050.709−0.0017±0.000910.0625.47±8.280.5091.16 (1.05–1.29)0.0051.12 (1.04–1.20)0.001
      Never-smokers6520/157 6041.022±0.0793.03×10−3819.36±5.849.21×10−40.0031±0.000711.22×10−512.77±7.150.0740.87 (0.75–1.01)0.0700.93 (0.86–1.02)0.113
      RecAll93/303 2601.644±0.6500.011−249.21±50.226.96×10−7−0.051±0.00633.54×10−16−132.16±60.090.0287.42 (4.29–12.27)5.67×10−144.58 (2.93–7.05)8.67×10−12
      Ever-smokers35/139 1361.242±1.0620.242−379.21±85.549.30×10−6−0.081±0.0112.00×10−13−177.95±100.350.0769.19 (4.19–19.00)6.27×10−96.13 (3.07–12.29)2.30×10−7
      Never-smokers58/164 1241.873±0.8210.023−174.68±60.680.004−0.034±0.00744.95×10−6−107.69±74.230.1475.98 (2.66–12.03)2.69×10−63.68 (2.01–6.47)1.11×10−5

      Results are based on linear (or logistic, in the case of COPD) regression adjusting for sex, age, age2, ancestry-based principal components, genotyping array and, in the case of lung function and COPD, standing height. The heterozygote (Het) or recessive (Rec) genetic model was also included in the regression as shown. FEV1: forced expiratory volume in 1 s; FVC: forced vital capacity; GOLD: Global Initiative for Chronic Obstructive Lung Disease. #: spirometrically defined as FEV1/FVC <0.7 and FEV1<80% predicted; ¶: defined as FEV1/FVC <0.7.

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        Supplementary material 00049-2021.SUPPLEMENT

        Table S1 00049-2021.TableS1

        Table S2 00049-2021.TableS2

        Table S3 00049-2021.TableS3

        Table S4 00049-2021.TableS4

        Table S5 00049-2021.TableS5

        Table S6 00049-2021.TableS6

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      Pleiotropic associations of heterozygosity for the SERPINA1 Z allele in the UK Biobank
      Katherine A. Fawcett, Kijoung Song, Guoqing Qian, Aliki-Eleni Farmaki, Richard Packer, Catherine John, Nick Shrine, Raquel Granell, Sue Ring, Nicholas J. Timpson, Laura M. Yerges-Armstrong, Richard Eastell, Louise V. Wain, Robert A. Scott, Martin D. Tobin, Ian P. Hall
      ERJ Open Research Apr 2021, 7 (2) 00049-2021; DOI: 10.1183/23120541.00049-2021

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      Pleiotropic associations of heterozygosity for the SERPINA1 Z allele in the UK Biobank
      Katherine A. Fawcett, Kijoung Song, Guoqing Qian, Aliki-Eleni Farmaki, Richard Packer, Catherine John, Nick Shrine, Raquel Granell, Sue Ring, Nicholas J. Timpson, Laura M. Yerges-Armstrong, Richard Eastell, Louise V. Wain, Robert A. Scott, Martin D. Tobin, Ian P. Hall
      ERJ Open Research Apr 2021, 7 (2) 00049-2021; DOI: 10.1183/23120541.00049-2021
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