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Axiom biobank array

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The Axiom Biobank array is a high-throughput genotyping platform developed by Thermo Fisher Scientific. It is designed for large-scale genomic studies, enabling efficient and accurate genotyping of a comprehensive set of genetic markers. The core function of the Axiom Biobank array is to provide a reliable and cost-effective solution for genome-wide association studies and other genetic research applications.

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Axiom® Customized Biobank Genotyping Arrays Axiom Biobank Plus Genotyping Array Axiom Spain Biobank Array Axiom-Taiwan Biobank Array Plate Axiom Biobank Genotyping Array Axiom-Taiwan Biobank Array Plate (TWB chip; Axiom 815K Spanish Biobank array BioBank Array Axiom array

36 protocols using axiom biobank array

1

Genetic Insights into Primary Aldosteronism

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The UKB is composed of health-related information from ~500 000 individuals aged between 40 and 69 years recruited from across the United Kingdom from 2006 to 2010.16 (link) The patient registration process and GWAS data are described elsewhere.16 (link) Briefly, we used the genomic data based on genotyping either by the Applied Biosystems UK BiLEVE Axiom Array or by the Applied Biosystems UK Biobank Axiom Array and imputation using a combination of the Haplotype Reference Consortium, UK10K, and 1KG Phase 3 reference panels.17 (link) Variants imputed with Rsq >0.7 and a MAF >0.5% were used for the analysis. We included only individuals of British ancestry who passed QC (Method S2).
The definition of cases for PA was based on the International Classification of Diseases, Tenth Revision code of E26.0 (primary hyperaldosteronism). The cases for hypertension and controls were defined similarly to those in the Japanese cohort (Method S2). Eventually, we included 84 PA cases, 195 922 hypertension cases, and 180 314 controls in this study.
Naito T., Inoue K., Sonehara K., Baba R., Kodama T., Otagaki Y., Okada A., Itcho K., Kobuke K., Kishimoto S., Yamamoto K., Morisaki T., Higashi Y., Hinata N., Arihiro K., Hattori N., Okada Y, & Oki K. (2023). Genetic Risk of Primary Aldosteronism and Its Contribution to Hypertension: A Cross-Ancestry Meta-Analysis of Genome-Wide Association Studies. Circulation, 147(14), 1097-1109.
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2

UK Biobank Genotype Data Preprocessing

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The UK Biobank database received ethical approval from the National Research Ethics Service Committee North West-Haydock (reference 11/NW/0382), and all procedures adhered to the World Medical Association Guidelines. All participants provided informed consent. The cohort comprises individuals aged between 40 and 69 years, primarily of White British ancestry, with a minority representing other ancestries. Approximately 50,000 participants were analyzed using the Applied Biosystems UK BiLEVE Axiom Array by Affymetrix, while the remaining around 450,000 participants were run on the Applied Biosystems UK Biobank Axiom Array, which shares 95% marker content with the former (Bycroft et al. 2018 (link)).
The genotype data we downloaded comprised 93,095,623 imputed SNPs for 487,411 individuals. We conducted the following preprocessing steps on the genotype data: initially, we excluded SNPs with a minor allele frequency (MAF) of less than 0.01 and an imputation INFO score of less than 0.8. Subsequently, we retained SNPs with a genotype call probability greater than 0.9 using the qctool. We also ensured that only biallelic SNPs were included. Finally, we excluded SNPs with a P value of less than 10−6 based on Hardy–Weinberg equilibrium testing and those with a genotype missing rate greater than 0.05 for both White and non-White British populations.
Wang J., Ma S., Yu P, & He X. (2023). Evolution of Human Brain Left–Right Asymmetry: Old Genes with New Functions. Molecular Biology and Evolution, 40(9), msad181.
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3

UKBB Genotyping Protocol

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Data acquisition and quality control (QC) have been described.22 (link) Briefly, UKBB participants were genotyped on two similar arrays (95% probe overlap): 438,427 samples (95 batches) were genotyped with the Applied Biosystems UK Biobank Axiom Array (825,927 probes) and 49,950 samples (11 batches) were genotyped with the Applied Biosystems UK BiLEVE Axiom Array by Affymetrix (807,411 probes). All results in this study are based on the human genome reference build GRCh37/hg19.
Auwerx C., Lepamets M., Sadler M.C., Patxot M., Stojanov M., Baud D., Mägi R., Porcu E., Reymond A, & Kutalik Z. (2022). The individual and global impact of copy-number variants on complex human traits. American Journal of Human Genetics, 109(4), 647-668.
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4

Genotyping and Imputation Protocol

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Participants were genotyped using the Applied Biosystems UK BiLEVE Axiom Array (807,411 markers tested for 49,950 participants) or Applied Biosystems UK Biobank Axiom Array (825,927 markers tested for 438,427 participants) by Affymetrix. These arrays share more than 95% of single-nucleotide polymorphisms (SNP) tested. Imputation was performed with SHAPEIT3 and IMPUTE3 based on merged UK10K and 1000 Genomes phase 3 panels.
Long L., He H., Shen Q., Peng H., Zhou X., Wang H., Zhang S., Qin S., Lu Z., Zhu Y., Tian J., Chang J., Miao X., Shen N, & Zhong R. (2022). Birthweight, genetic risk, and gastrointestinal cancer incidence: a prospective cohort study. Annals of Medicine, 55(1), 62-71.
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5

UK Biobank Genotype Data Preprocessing

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The UK Biobank database received ethical approval from the National Research Ethics Service Committee North West-Haydock (reference 11/NW/0382), and all procedures adhered to the World Medical Association Guidelines. All participants provided informed consent. The cohort comprises individuals aged between 40 and 69 years, primarily of White British ancestry, with a minority representing other ancestries. Approximately 50,000 participants were analyzed using the Applied Biosystems UK BiLEVE Axiom Array by Affymetrix, while the remaining around 450,000 participants were run on the Applied Biosystems UK Biobank Axiom Array, which shares 95% marker content with the former (Bycroft et al. 2018 (link)).
The genotype data we downloaded comprised 93,095,623 imputed SNPs for 487,411 individuals. We conducted the following preprocessing steps on the genotype data: initially, we excluded SNPs with a minor allele frequency (MAF) of less than 0.01 and an imputation INFO score of less than 0.8. Subsequently, we retained SNPs with a genotype call probability greater than 0.9 using the qctool. We also ensured that only biallelic SNPs were included. Finally, we excluded SNPs with a P value of less than 10−6 based on Hardy–Weinberg equilibrium testing and those with a genotype missing rate greater than 0.05 for both White and non-White British populations.
Wang J., Ma S., Yu P, & He X. (2023). Evolution of Human Brain Left–Right Asymmetry: Old Genes with New Functions. Molecular Biology and Evolution, 40(9), msad181.
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6

UK Biobank Genotyping and Imputation

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Genotyping, quality control (QC), and imputation were performed centrally by UKBB, and details are fully described elsewhere (79 (link)). Briefly, genotype data are available for 488,377 individuals, 49,950 of whom were genotyped using the Applied Biosystems U.K. BiLEVE Axiom Array by Affymetrix [containing 807,411 markers (81 (link))]. The remaining 438,427 individuals were genotyped using the Applied Biosystems U.K. Biobank Axiom Array by Affymetrix (containing 825,927 markers). Both arrays were specifically designed for use in the UKBB project and share ~95% of marker content. Phasing was performed using SHAPEIT3, and imputation was conducted using IMPUTE4. For imputation, the Haplotype Reference Consortium (HRC) panel (82 (link)) was used wherever possible, and for SNPs not in that reference panel, a merged UK10K + 1000 Genomes reference panel was used. SNPs were imputed from both panels, but the HRC imputation was preferentially used for SNPs present in both panels. Both SNPs selected as instruments in this study demonstrated high imputation quality in UKBB (info scores of 0.98 and 0.95 for rs7209826 and rs188810925, respectively).
Bovijn J., Krebs K., Chen C.Y., Boxall R., Censin J.C., Ferreira T., Pulit S.L., Glastonbury C.A., Laber S., Millwood I.Y., Lin K., Li L., Chen Z., Milani L., Smith G.D., Walters R.G., Mägi R., Neale B.M., Lindgren C.M, & Holmes M.V. (2020). Evaluating the cardiovascular safety of sclerostin inhibition using evidence from meta-analysis of clinical trials and human genetics. Science translational medicine, 12(549), eaay6570.
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7

Genotyping and Quality Control for GWAS

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Genetic data of the participants were genotyped using custom arrays, Affymetrix UK BiLEVE Axiom array or Affymetrix UK Biobank Axiom array which share 95% of marker content. The genotyping methods, arrays and quality-control procedures have been extensively described previously.24 SNPs with a minor allele frequency smaller than 0·5% or an INFO-score smaller than 0·3 were excluded from the association analysis.
Benjamins J.W., Yeung M.W., van de Vegte Y.J., Said M.A., van der Linden T., Ties D., Juarez-Orozco L.E., Verweij N, & van der Harst P. (2021). Genomic insights in ascending aortic size and distensibility. EBioMedicine, 75, 103783.
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8

Genome-wide Genotyping in UK Biobank

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Genome-wide genotyping was previously performed in the UK Biobank using two genotyping arrays sharing 95% of marker content: Applied Biosystems UK BiLEVE Axiom Array (807,411 markers in 49,950 participants) and Applied Biosystems UK Biobank Axiom Array (825,927 markers in 438,427 participants) both by Affymetrix (Santa Clara, CA)42 (link). Variants used in the present analysis include those also imputed using the Haplotype Reference Consortium reference panel of up to 39M SNPs43 (link),44 .
Zekavat S.M., Aragam K., Emdin C., Khera A.V., Klarin D., Zhao H, & Natarajan P. (2019). Genetic Association of Finger Photoplethysmography-Derived Arterial Stiffness Index with Blood Pressure and Coronary Artery Disease. Arteriosclerosis, thrombosis, and vascular biology, 39(6), 1253-1261.
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9

High-Resolution HLA Genotyping and Analysis

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Genotyping of samples was performed using two similar SNP genotyping arrays sharing 95% of marker content, the Affymetrix UK Biobank Axiom array for about 450,000 samples and the Affymetrix UK BiLEVE Axiom array for about 50,000 samples. HLA alleles (at four-digit resolution) for the classical class I and class II locus were imputed by the HLA∗IMP:02 algorithm, and a multi-population reference panel was used.21 (link) A total of 211 HLA class I alleles, of which 53 are in the HLA-A locus, 126 are in the HLA-B locus, 32 are in the HLA-C locus, and a total of 135 HLA class II alleles, of which 59 are in the HLA-DRB1 locus, 18 are in the HLA-DQB1 locus, 14 are in the HLA-DQA1 locus, 36 are in the HLA-DPB1 locus, 8 are in the HLA-DPA1 locus were included. A posterior probability cutoff of 0.5 was used to filter the imputed HLA alleles with poor quality. For each HLA locus, the successful genotyping rate is over 97.7%. Individuals with two different alleles at the four-digit resolution of a specific locus were defined as heterozygotes. Assuming each HLA class I and HLA class II locus has the same contribution to antigen presentation,13 (link) the total number of heterozygotes at the HLA class I and class II locus was counted and analysed in this study.
Wang Q.L., Wang T.M., Deng C.M., Zhang W.L., He Y.Q., Xue W.Q., Liao Y., Yang D.W., Zheng M.Q, & Jia W.H. (2023). Association of HLA diversity with the risk of 25 cancers in the UK Biobank. eBioMedicine, 92, 104588.
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10

UK Biobank: Genetic and Phenotypic Profiling

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UK Biobank recruited over 500,000 participants aged 40-70 years from 2006 to 2010. A wide range of genetic and phenotypic data were collected at recruitment (baseline) and mortality and disease diagnoses were updated through linkages to death certificates, cancer registry and hospital admission records [24 (link), 25 (link)].
The DNA from blood samples was genotyped using Affymetrix UK BiLEVE Axiom array for the first ~50,000 participants and Affymetrix UK Biobank Axiom array for the rest of the cohort - the two arrays sharing over 95% marker content [25 (link)]. The two ApoE isoform coding SNPs, rs429358 and rs7412, on chromosome 19, were actually genotyped and the participant genotypes at these two locations were used to determine ApoE genotypes.
Kuo C.L., Pilling L.C., Atkins J.L., Kuchel G.A, & Melzer D. (2020). ApoE e2 and aging-related outcomes in 379,000 UK Biobank participants. Aging (Albany NY), 12(12), 12222-12233.
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