Mixed-model admixture mapping identifies smoking-dependent loci of lung function in African Americans

UGT1A1*28 polymorphism and the risk of toxicity and disease progression in patients with breast cancer receiving sacituzumab govitecan

BACKGROUND

Sacituzumab govitecan (sacituzumab) emerged as an important agent in metastatic and locally recurrent HER2-negative breast cancer treatment. UGT1A1 polymorphisms have also been shown to predict sacituzumab toxicity.

METHODS

In this retrospective study, we sought to evaluate the associations between UGT1A1 status, toxicity, and therapeutic outcomes in sacituzumab recipients with advanced breast cancer who underwent genotype testing for UGT1A1 alleles (N = 68).

RESULTS

We found 17 (25%) of our patients to be homozygous for UGT1A1*28 and 24 (35.3%) were heterozygous. Of seven African American patients with triple-negative breast cancer, five were homozygous for UGT1A1*28 and two were heterozygous. Patients with a homozygous UGT1A1*28 genotype were significantly more likely to have treatment terminated because of adverse effects. However, the polymorphism was not associated with treatment discontinuation because of disease progression.

CONCLUSION

This retrospective, real-world analysis suggests potential clinical utility in UGT1A1 testing for patients receiving sacituzumab, but future trials are needed to confirm the association between genotypes and treatment outcomes.

Estimating heritability explained by local ancestry and evaluating stratification bias in admixture mapping from summary statistics

The heritability explained by local ancestry markers in an admixed population (hγ2) provides crucial insight into the genetic architecture of a complex disease or trait. Estimation of hγ2 can be susceptible to biases due to population structure in ancestral populations. Here, we present heritability estimation from admixture mapping summary statistics (HAMSTA), an approach that uses summary statistics from admixture mapping to infer heritability explained by local ancestry while adjusting for biases due to ancestral stratification. Through extensive simulations, we demonstrate that HAMSTA hγ2 estimates are approximately unbiased and are robust to ancestral stratification compared to existing approaches. In the presence of ancestral stratification, we show a HAMSTA-derived sampling scheme provides a calibrated family-wise error rate (FWER) of ∼5% for admixture mapping, unlike existing FWER estimation approaches. We apply HAMSTA to 20 quantitative phenotypes of up to 15,988 self-reported African American individuals in the Population Architecture using Genomics and Epidemiology (PAGE) study. We observe hˆγ2 in the 20 phenotypes range from 0.0025 to 0.033 (mean hˆγ2 = 0.012 ± 9.2 × 10-4), which translates to hˆ2 ranging from 0.062 to 0.85 (mean hˆ2 = 0.30 ± 0.023). Across these phenotypes we find little evidence of inflation due to ancestral population stratification in current admixture mapping studies (mean inflation factor of 0.99 ± 0.001). Overall, HAMSTA provides a fast and powerful approach to estimate genome-wide heritability and evaluate biases in test statistics of admixture mapping studies.

Admixture mapping implicates 13q33.3 as ancestry-of-origin locus for Alzheimer disease in Hispanic and Latino populations

Alzheimer disease (AD) is the most common form of senile dementia, with high incidence late in life in many populations including Caribbean Hispanic (CH) populations. Such admixed populations, descended from more than one ancestral population, can present challenges for genetic studies, including limited sample sizes and unique analytical constraints. Therefore, CH populations and other admixed populations have not been well represented in studies of AD, and much of the genetic variation contributing to AD risk in these populations remains unknown. Here, we conduct genome-wide analysis of AD in multiplex CH families from the Alzheimer Disease Sequencing Project (ADSP). We developed, validated, and applied an implementation of a logistic mixed model for admixture mapping with binary traits that leverages genetic ancestry to identify ancestry-of-origin loci contributing to AD. We identified three loci on chromosome 13q33.3 associated with reduced risk of AD, where associations were driven by Native American (NAM) ancestry. This AD admixture mapping signal spans the FAM155A, ABHD13, TNFSF13B, LIG4, and MYO16 genes and was supported by evidence for association in an independent sample from the Alzheimer's Genetics in Argentina-Alzheimer Argentina consortium (AGA-ALZAR) study with considerable NAM ancestry. We also provide evidence of NAM haplotypes and key variants within 13q33.3 that segregate with AD in the ADSP whole-genome sequencing data. Interestingly, the widely used genome-wide association study approach failed to identify associations in this region. Our findings underscore the potential of leveraging genetic ancestry diversity in recently admixed populations to improve genetic mapping, in this case for AD-relevant loci.

Estimating heritability explained by local ancestry and evaluating stratification bias in admixture mapping from summary statistics

The heritability explained by local ancestry markers in an admixed population h γ 2 provides crucial insight into the genetic architecture of a complex disease or trait. Estimation of h γ 2 can be susceptible to biases due to population structure in ancestral populations. Here, we present a novel approach, Heritability estimation from Admixture Mapping Summary STAtistics (HAMSTA), which uses summary statistics from admixture mapping to infer heritability explained by local ancestry while adjusting for biases due to ancestral stratification. Through extensive simulations, we demonstrate that HAMSTA h γ 2 estimates are approximately unbiased and are robust to ancestral stratification compared to existing approaches. In the presence of ancestral stratification, we show a HAMSTA-derived sampling scheme provides a calibrated family-wise error rate (FWER) of ~5% for admixture mapping, unlike existing FWER estimation approaches. We apply HAMSTA to 20 quantitative phenotypes of up to 15,988 self-reported African American individuals in the Population Architecture using Genomics and Epidemiology (PAGE) study. We observe h ˆ γ 2 in the 20 phenotypes range from 0.0025 to 0.033 (mean h ˆ γ 2 = 0.012 + / - 9.2 × 10 - 4 ), which translates to h ˆ 2 ranging from 0.062 to 0.85 (mean h ˆ 2 = 0.30 + / - 0.023 ). Across these phenotypes we find little evidence of inflation due to ancestral population stratification in current admixture mapping studies (mean inflation factor of 0.99 +/- 0.001). Overall, HAMSTA provides a fast and powerful approach to estimate genome-wide heritability and evaluate biases in test statistics of admixture mapping studies.

Gene-environment interactions in childhood asthma revisited; expanding the interaction concept

Investigation of gene-environment interactions (GxE) may provide important insights into the gene regulatory framework in response to environmental factors of relevance for childhood asthma. Over the years, different methodological strategies have been applied, more recently using genome-wide approaches. The best example to date is the major asthma locus on the 17q12-21 chromosome region, viral infections, and airway epithelium processes where recent studies have shed much light on mechanisms in childhood asthma. However, there are challenges with the traditional single variant-single exposure interaction models, as they do not encompass the complexity and cumulative effects of multiple exposures or multiple genetic variants. As such, we need to redefine our traditional GxE thinking, and we propose in this review to expand the GxE concept by also evaluating other omics layers, such as epigenetics, transcriptomics, metabolomics, and proteomics. In addition, host factors such as age, gender, and other exposures are very likely to influence GxE effects and need firmly to be considered in future studies.

Admixture mapping reveals the association between Native American ancestry at 3q13.11 and reduced risk of Alzheimer's disease in Caribbean Hispanics

BACKGROUND

Genetic studies have primarily been conducted in European ancestry populations, identifying dozens of loci associated with late-onset Alzheimer's disease (AD). However, much of AD's heritability remains unexplained; as the prevalence of AD varies across populations, the genetic architecture of the disease may also vary by population with the presence of novel variants or loci.

METHODS

We conducted genome-wide analyses of AD in a sample of 2565 Caribbean Hispanics to better understand the genetic contribution to AD in this population. Statistical analysis included both admixture mapping and association testing. Evidence for differential gene expression within regions of interest was collected from independent transcriptomic studies comparing AD cases and controls in samples with primarily European ancestry.

RESULTS

Our genome-wide association study of AD identified no loci reaching genome-wide significance. However, a genome-wide admixture mapping analysis that tests for association between a haplotype's ancestral origin and AD status detected a genome-wide significant association with chromosome 3q13.11 (103.7-107.7Mb, P = 8.76E-07), driven by a protective effect conferred by the Native American ancestry (OR = 0.58, 95%CI = 0.47-0.73). Within this region, two variants were significantly associated with AD after accounting for the number of independent tests (rs12494162, P = 2.33E-06; rs1731642, P = 6.36E-05). The significant admixture mapping signal is composed of 15 haplotype blocks spanning 5 protein-coding genes (ALCAM, BBX, CBLB, CCDC54, CD47) and four brain-derived topologically associated domains, and includes markers significantly associated with the expression of ALCAM, BBX, CBLB, and CD47 in the brain. ALCAM and BBX were also significantly differentially expressed in the brain between AD cases and controls with European ancestry.

CONCLUSION

These results provide multiethnic evidence for a relationship between AD and multiple genes at 3q13.11 and illustrate the utility of leveraging genetic ancestry diversity via admixture mapping for new insights into AD.

Race and Genetics: Somber History, Troubled Present

Following the completion of the Human Genome Project (HGP) in 2003, advances in DNA sequencing technologies further popularized the field of genomics and brought its social ramifications to the fore. Scholars across disciplines recently voiced serious concerns about the re-emergence of genomic research that might be used to justify racism. In this piece, I trace the history of attempts to biologize the concept of race and its diffused presence in today's genomic research. I then include a brief analysis inspired by concepts from the field of Science and Technology Studies (STS) to suggest selected ways to produce better scientific knowledge. The text highlights historic landmarks of interest to science practitioners curious about the ways science of the past co-shapes science of the present. I then argue that science has never been isolated from the socio-political climate it is produced in; instead, it has been morphed by its surroundings and historically used as a potent tool to justify systemic oppression.