Showing papers by "Adam Auton published in 2020"

Avoiding dynastic, assortative mating, and population stratification biases in Mendelian randomization through within-family analyses

Abstract: Estimates from Mendelian randomization studies of unrelated individuals can be biased due to uncontrolled confounding from familial effects. Here we describe methods for within-family Mendelian randomization analyses and use simulation studies to show that family-based analyses can reduce such biases. We illustrate empirically how familial effects can affect estimates using data from 61,008 siblings from the Nord-Trondelag Health Study and UK Biobank and replicated our findings using 222,368 siblings from 23andMe. Both Mendelian randomization estimates using unrelated individuals and within family methods reproduced established effects of lower BMI reducing risk of diabetes and high blood pressure. However, while Mendelian randomization estimates from samples of unrelated individuals suggested that taller height and lower BMI increase educational attainment, these effects were strongly attenuated in within-family Mendelian randomization analyses. Our findings indicate the necessity of controlling for population structure and familial effects in Mendelian randomization studies.

Genetic Consequences of the Transatlantic Slave Trade in the Americas.

Abstract: According to historical records of transatlantic slavery, traders forcibly deported an estimated 12.5 million people from ports along the Atlantic coastline of Africa between the 16th and 19th centuries, with global impacts reaching to the present day, more than a century and a half after slavery's abolition. Such records have fueled a broad understanding of the forced migration from Africa to the Americas yet remain underexplored in concert with genetic data. Here, we analyzed genotype array data from 50,281 research participants, which-combined with historical shipping documents-illustrate that the current genetic landscape of the Americas is largely concordant with expectations derived from documentation of slave voyages. For instance, genetic connections between people in slave trading regions of Africa and disembarkation regions of the Americas generally mirror the proportion of individuals forcibly moved between those regions. While some discordances can be explained by additional records of deportations within the Americas, other discordances yield insights into variable survival rates and timing of arrival of enslaved people from specific regions of Africa. Furthermore, the greater contribution of African women to the gene pool compared to African men varies across the Americas, consistent with literature documenting regional differences in slavery practices. This investigation of the transatlantic slave trade, which is broad in scope in terms of both datasets and analyses, establishes genetic links between individuals in the Americas and populations across Atlantic Africa, yielding a more comprehensive understanding of the African roots of peoples of the Americas.

Trans-ethnic analysis reveals genetic and non-genetic associations with COVID-19 susceptibility and severity

Abstract: COVID-19 presents with a wide range of severity, from asymptomatic in some individuals to fatal in others. Based on a study of over one million 23andMe research participants, we report genetic and non-genetic associations with testing positive for COVID-19, respiratory symptoms, and hospitalization. Risk factors for hospitalization include advancing age, male sex, elevated body mass index, lower socio-economic status, non-European ancestry, and pre-existing cardio-metabolic and respiratory conditions. Using trans-ethnic genome-wide association studies, we identify a strong association between blood type and COVID-19 diagnosis, as well as a gene-rich locus on chr3p21.31 that is more strongly associated with outcome severity. While non-European ancestry was found to be a significant risk factor for hospitalization after adjusting for socio-demographics and pre-existing health conditions, we did not find evidence that these two primary genetic associations explain differences between populations in terms of risk for severe COVID-19 outcomes.

Genome-wide association and multi-omic analyses reveal ACTN2 as a gene linked to heart failure.

Abstract: Heart failure is a major public health problem affecting over 23 million people worldwide. In this study, we present the results of a large scale meta-analysis of heart failure GWAS and replication in a comparable sized cohort to identify one known and two novel loci associated with heart failure. Heart failure sub-phenotyping shows that a new locus in chromosome 1 is associated with left ventricular adverse remodeling and clinical heart failure, in response to different initial cardiac muscle insults. Functional characterization and fine-mapping of that locus reveal a putative causal variant in a cardiac muscle specific regulatory region activated during cardiomyocyte differentiation that binds to the ACTN2 gene, a crucial structural protein inside the cardiac sarcolemma (Hi-C interaction p-value = 0.00002). Genome-editing in human embryonic stem cell-derived cardiomyocytes confirms the influence of the identified regulatory region in the expression of ACTN2. Our findings extend our understanding of biological mechanisms underlying heart failure. Heart failure has a heterogeneous etiology and the genetic underpinnings are not well understood. Here, Arvanitis et al. perform GWAS meta-analysis including 10,976 heart failure cases and 437,573 controls, identify new loci near ABO and ACTN2 and show that deletion of a ACTN2 enhancer leads to reduced ACTN2 expression in differentiating cardiomyocytes.

Genome-wide Study Identifies Association between HLA-B∗55:01 and Self-Reported Penicillin Allergy.

Abstract: Summary Hypersensitivity reactions to drugs are often unpredictable and can be life threatening, underscoring a need for understanding their underlying mechanisms and risk factors. The extent to which germline genetic variation influences the risk of commonly reported drug allergies such as penicillin allergy remains largely unknown. We extracted data from the electronic health records of more than 600,000 participants from the UK, Estonian, and Vanderbilt University Medical Center’s BioVU biobanks to study the role of genetic variation in the occurrence of self-reported penicillin hypersensitivity reactions. We used imputed SNP to HLA typing data from these cohorts to further fine map the human leukocyte antigen (HLA) association and replicated our results in 23andMe’s research cohort involving a total of 1.12 million individuals. Genome-wide meta-analysis of penicillin allergy revealed two loci, including one located in the HLA region on chromosome 6. This signal was further fine-mapped to the HLA-B∗55:01 allele (OR 1.41 95% CI 1.33–1.49, p value 2.04 × 10−31) and confirmed by independent replication in 23andMe’s research cohort (OR 1.30 95% CI 1.25–1.34, p value 1.00 × 10−47). The lead SNP was also associated with lower lymphocyte counts and in silico follow-up suggests a potential effect on T-lymphocytes at HLA-B∗55:01. We also observed a significant hit in PTPN22 and the GWAS results correlated with the genetics of rheumatoid arthritis and psoriasis. We present robust evidence for the role of an allele of the major histocompatibility complex (MHC) I gene HLA-B in the occurrence of penicillin allergy.

Fast and robust identity-by-descent inference with the templated positional Burrows-Wheeler transform

Abstract: Estimating the genomic location and length of identical-by-descent (IBD) segments among individuals is a crucial step in many genetic analyses. However, the exponential growth in the size of biobank and direct-to-consumer (DTC) genetic data sets makes accurate IBD inference a significant computational challenge. Here we present the templated positional Burrows-Wheeler transform (TPBWT) to make fast IBD estimates robust to genotype and phasing errors. Using haplotype data simulated over pedigrees with realistic genotyping and phasing errors we show that the TPBWT outperforms other state-of-the-art IBD inference algorithms in terms of speed and accuracy. For each phase-aware method, we explore the false positive and false negative rates of inferring IBD by segment length and characterize the types of error commonly found. Our results highlight the fragility of most phased IBD inference methods; the accuracy of IBD estimates can be highly sensitive to the quality of haplotype phasing. Additionally we compare the performance of the TPBWT against a widely used phase-free IBD inference approach that is robust to phasing errors. We introduce both in-sample and out-of-sample TPBWT-based IBD inference algorithms and demonstrate their computational efficiency on massive-scale datasets with millions of samples. Furthermore we describe the binary file format for TPBWT-compressed haplotypes that results in fast and efficient out-of-sample IBD computes against very large cohort panels. Finally, we demonstrate the utility of the TPBWT in a brief empirical analysis exploring geographic patterns of haplotype sharing within Mexico. Hierarchical clustering of IBD shared across regions within Mexico reveals geographically structured haplotype sharing and a strong signal of isolation by distance. Our software implementation of the TPBWT is freely available for non-commercial use in the code repository https://github.com/23andMe/phasedibd.

Genome-wide study identifies association between HLA-B*55:01 and penicillin allergy

Abstract: Background Hypersensitivity reactions to drugs are often unpredictable and can be life-threatening, underscoring a need for understanding the underlying mechanisms and risk factors. The extent to which germline genetic variation influences the risk of commonly reported drug allergies such as penicillin allergy remains largely unknown. Methods We extracted data from the electronic health records of 52,000 Estonian and 500,000 UK biobank participants to study the role of genetic variation in the occurrence of penicillin hypersensitivity reactions. We used imputed SNP to HLA typing data from up to 22,554 and 488,377 individuals from the Estonian and UK cohorts, respectively, to further fine-map the human leukocyte antigen (HLA) association and replicated our results in two additional cohorts involving a total of 1.14 million individuals. Results Genome-wide meta-analysis of penicillin allergy revealed a significant association located in the HLA region on chromosome 6. The signal was further fine-mapped to the HLA-B*55:01 allele (OR 1.47 95% CI 1.37-1.58, P-value 4.63×10−26) and confirmed by independent replication in two cohorts. The meta-analysis of all four cohorts in the study revealed a strong association of HLA-B*55:01 allele with self-reported penicillin allergy (OR 1.33 95% CI 1.29-1.37, P-value 2.23×10−72). In silico follow-up suggests a potential effect on T lymphocytes at HLA-B*55:01. Conclusion We present the first robust evidence for the role of an allele of the major histocompatibility complex (MHC) I gene HLA-B in the occurrence of penicillin allergy.