At the time of enrollment, 30 mL of blood were collected from all of the participants for use in direct DNA extraction and storage of plasma. Genotype data were collected using an Illumina Expanded Multi-Ethnic Genotyping Array50 with custom content (MEGAex+3k) or an Illumina Global Screening Array51 (GSA). The MEGAex chip includes over 2 million markers, whereas the GSA chip includes a base quantity of 660,000 markers. When performing chip genotyping, we also included customized content of up to 6,000 variants to the MEGAex chip, including over 1,100 novel variants that have already been identified from our previous Amish whole-exome sequencing (WES) and whole-genome sequencing (WGS) studies and other associated variants from GWAS and the National Institute on Aging’s Alzheimer’s Disease Sequencing Project52 (link),53 (ADSP) studies that are not already on the chip. After genotype data were attained, imputation was performed based on a Haplotype Reference Consortium (HRC) panel.54 (link),55 (link) We investigated genetic relationships of individuals within the overall study population by calculating kinship coefficients using KING version 2.26.56 (link) Furthermore, we compared the average genetic relationship across subpopulations based on recruitment site and cognitive status.
Expanded multi ethnic genotyping array
Manufactured by Illumina
Sourced in United States
The Expanded Multi-Ethnic Genotyping Array is a laboratory equipment product designed for high-throughput genotyping. It provides a comprehensive coverage of genetic variants across diverse global populations.
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Lab products found in correlation
6 protocols using expanded multi ethnic genotyping array
1
Amish Genetic Profiling Protocol
2
Genetic Ancestry and ApoE4 Risk Analysis
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Genome-wide single-nucleotide polymorphism (SNP) genotyping was processed on three different platforms: Expanded Multi-Ethnic Genotyping Array, Illumina 1Mduo (v3) and the Global Screening Array (Illumina, San Diego, CA, USA). ApoE genotyping was performed as in Saunders et al. [30 (link)]. Quality control analyses were performed using the PLINK software, v.2. [31 (link)]. The samples with a call rate less than 90% and with excess or insufficient heterozygosity (+/- 3 standard deviations) were excluded. Sex concordance was checked using X chromosome data. To eliminate duplicate and related samples, relatedness among the samples was estimated by using identity by descent (IBD). SNPs with minor allele frequencies less than 0.01 and SNPs available in samples with the call rate less than 97%, or those not in Hardy-Weinberg equilibrium (p<1.e-5), were eliminated from further analysis [32 (link)]. Further details of the QC analysis can be found in the Supplement (S1 Table ).
To explore the reasons for the differences in ε4 allele risk between the populations we first assessed the genetic ancestry (LA and GA), and then tested the effect of LA and GA on the ε4 allele by building three logistic regression models.
To explore the reasons for the differences in ε4 allele risk between the populations we first assessed the genetic ancestry (LA and GA), and then tested the effect of LA and GA on the ε4 allele by building three logistic regression models.
3
Genetic Analysis of Iberian Ancestry
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Genetic analysis was conducted in a subsample of the GCAT cohort (GCATcore) that is fully genotyped by SNP-array and imputation. This subsample included 4988 unrelated participants with Iberian ethnicity, determined by self-described ethnicity, and supervised ancestry inference by Principal Components Analysis (PCA), as previously described by Galván Femenía et al. [39 (link)]. Genotyping was completed using the Infinium Expanded Multi-Ethnic Genotyping Array (MEGAEX) (ILLUMINA, San Diego, CA, USA). Then, we imputed both SNVs and SVs, with IMPUTE2, and using the GCAT|Panel as reference [40 (link)], an ancestry-geographically matched panel generated by whole-genome sequencing. The final core set included a total of 10,216,971 variants with MAF ≥ 0.01 and INFO score ≥ 0.7 (21,620 SVs, and 10,195,351 SNVs and small indels). All data are available at EGA (Study ID EGAS00001003018).
4
PRS Validation for Hypothyroidism Risk
5
Validation of Genetic Variants and Inversions
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The validation of SNV and indels was performed using genotypes calls generated by WGS and genotyping data from SNP-array techniques in 570 GCAT samples. We include QCed genotypes generated in the GCAT cohort with the Infinium Expanded Multi-Ethnic Genotyping Array (MEGAEx) (ILLUMINA, San Diego, California, USA) as described elsewhere 18 (link) (i.e. 732,978 SNPs and 1,168 indels). Genotypes from both strategies were compared by (i) chromosome and position at base-pair resolution and (ii) REF/ALT alleles; the recall and genotype concordance for each individual sample was calculated.
Inversions were validated using the most recent benchmark set of validated human polymorphic inversions from the InvFEST porject 24 . We considered 59 experimentally genotyped inversions generated by non-homologous mechanisms 24 . Allele frequency (using CEU and TSI European populations) and length concordance was determined using an overlapping window of ±1Kb around the inversion breakpoints. Accuracy of inversion genotyping was compared for the 785 WGS samples using the available reference panel of experimentally-resolved genotypes 24 . Genotypes in GCAT samples were imputed with IMPUTE2 30 with a posterior probability ≥ 0.8 and were classified as missing otherwise. Missing genotypes were recovered if they had a perfect tag SNP in the reference panel (r 2 = 1).
Inversions were validated using the most recent benchmark set of validated human polymorphic inversions from the InvFEST porject 24 . We considered 59 experimentally genotyped inversions generated by non-homologous mechanisms 24 . Allele frequency (using CEU and TSI European populations) and length concordance was determined using an overlapping window of ±1Kb around the inversion breakpoints. Accuracy of inversion genotyping was compared for the 785 WGS samples using the available reference panel of experimentally-resolved genotypes 24 . Genotypes in GCAT samples were imputed with IMPUTE2 30 with a posterior probability ≥ 0.8 and were classified as missing otherwise. Missing genotypes were recovered if they had a perfect tag SNP in the reference panel (r 2 = 1).
6
Amish Genetics Study Genotyping
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At time of enrollment, 30 milliliters of blood were collected from all participants for use in direct DNA extraction and storage of plasma. Genotype data were collected using an Illumina Expanded Multi-Ethnic Genotyping Array 45 with custom content (MEGAex+3k) or an Illumina Global Screening Array 46 (GSA). The MEGAex chip includes over 2 million markers whereas the GSA chip includes a base quantity of 660,000 markers. When performing chip genotyping, we also included customized content of up to 6,000 variants to the MEGAex chip, including over 1,100 novel varaints that have already been identified from our previous Amish whole exome sequencing (WES) and whole genome sequencing (WGS) studies and other associated variants from GWAS and the National Institute on Aging's Alzheimer's Disease Sequencing Project 47, 48 (link) (ADSP) studies that are not already on the chip. After genotype data were attained, imputation was performed based on a Haplotype Reference Consortium (HRC) panel. 49, 50 We investigated genetic relationships of individuals within the overall study population by calculating kinship coefficients using KING 2.26. 51 (link) Further, we compared the average genetic relationship across subpopulations based on recruitment site and cognitive status.
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