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Baseline lung function, quantified as forced expiratory volume in the first second of exhalation (FEV 1 ), is a standard diagnostic criterion used by clinicians to identify and classify lung diseases. Using whole-genome sequencing data from the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine project, we identified a novel genetic association with FEV 1 on chromosome 12 in 867 African American children with asthma ( P = 1.26 × 10 -8 , β = 0.302). Conditional analysis within 1 Mb of the tag signal (rs73429450) yielded one major and two other weaker independent signals within this peak. We explored statistical and functional evidence for all variants in linkage disequilibrium with the three independent signals and yielded nine variants as the most likely candidates responsible for the association with FEV 1 Hi-C data and expression QTL analysis demonstrated that these variants physically interacted with KITLG (KIT ligand, also known as SCF ), and their minor alleles were associated with increased expression of the KITLG gene in nasal epithelial cells. Gene-by-air-pollution interaction analysis found that the candidate variant rs58475486 interacted with past-year ambient sulfur dioxide exposure ( P = 0.003, β = 0.32). This study identified a novel protective genetic association with FEV 1 , possibly mediated through KITLG , in African American children with asthma. This is the first study that has identified a genetic association between lung function and KITLG , which has established a role in orchestrating allergic inflammation in asthma., (Copyright © 2020 by the Genetics Society of America.)

Background: More than 180 single nucleotide polymorphisms (SNPs) associated with breast cancer susceptibility have been identified; these SNPs can be combined into polygenic risk scores (PRS) to predict breast cancer risk. Because most SNPs were identified in predominantly European populations, little is known about the performance of PRS in non-Europeans. We tested the performance of a 180-SNP PRS in Latinas, a large ethnic group with variable levels of Indigenous American, European, and African ancestry., Methods: We conducted a pooled case-control analysis of US Latinas and Latin American women (4658 cases and 7622 controls). We constructed a 180-SNP PRS consisting of SNPs associated with breast cancer risk (P < 5 × 10-8). We evaluated the association between the PRS and breast cancer risk using multivariable logistic regression, and assessed discrimination using an area under the receiver operating characteristic curve. We also assessed PRS performance across quartiles of Indigenous American genetic ancestry. All statistical tests were two-sided., Results: Of 180 SNPs tested, 142 showed directionally consistent associations compared with European populations, and 39 were nominally statistically significant (P < .05). The PRS was associated with breast cancer risk, with an odds ratio per SD increment of 1.58 (95% confidence interval [CI = 1.52 to 1.64) and an area under the receiver operating characteristic curve of 0.63 (95% CI = 0.62 to 0.64). The discrimination of the PRS was similar between the top and bottom quartiles of Indigenous American ancestry., Conclusions: The 180-SNP PRS predicts breast cancer risk in Latinas, with similar performance as reported for Europeans. The performance of the PRS did not vary substantially according to Indigenous American ancestry., (© The Author(s) 2019. Published by Oxford University Press.)

Native American genetic variation remains underrepresented in most catalogs of human genome sequencing data. Previous genotyping efforts have revealed that Mexico's Indigenous population is highly differentiated and substructured, thus potentially harboring higher proportions of private genetic variants of functional and biomedical relevance. Here we have targeted the coding fraction of the genome and characterized its full site frequency spectrum by sequencing 76 exomes from five Indigenous populations across Mexico. Using diffusion approximations, we modeled the demographic history of Indigenous populations from Mexico with northern and southern ethnic groups splitting 7.2 KYA and subsequently diverging locally 6.5 and 5.7 KYA, respectively. Selection scans for positive selection revealed BCL2L13 and KBTBD8 genes as potential candidates for adaptive evolution in Rarámuris and Triquis, respectively. BCL2L13 is highly expressed in skeletal muscle and could be related to physical endurance, a well-known phenotype of the northern Mexico Rarámuri. The KBTBD8 gene has been associated with idiopathic short stature and we found it to be highly differentiated in Triqui, a southern Indigenous group from Oaxaca whose height is extremely low compared to other Native populations., (© The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.)

Statistical models in medical and population genetics typically assume that individuals assort randomly in a population. While this simplifies model complexity, it contradicts an increasing body of evidence of nonrandom mating in human populations. Specifically, it has been shown that assortative mating is significantly affected by genomic ancestry. In this work, we examine the effects of ancestry-assortative mating on the linkage disequilibrium between local ancestry tracks of individuals in an admixed population. To accomplish this, we develop an extension to the Wright-Fisher model that allows for ancestry-based assortative mating. We show that ancestry-assortment perturbs the distribution of local ancestry linkage disequilibrium (LAD) and the variance of ancestry in a population as a function of the number of generations since admixture. This assortment effect can induce errors in demographic inference of admixed populations when methods assume random mating. We derive closed form formulae for LAD under an assortative-mating model with and without migration. We observe that LAD depends on the correlation of global ancestry of couples in each generation, the migration rate of each of the ancestral populations, the initial proportions of ancestral populations, and the number of generations since admixture. We also present the first direct evidence of ancestry-assortment in African Americans and examine LAD in simulated and real admixed population data of African Americans. We find that demographic inference under the assumption of random mating significantly underestimates the number of generations since admixture, and that accounting for assortative mating using the patterns of LAD results in estimates that more closely agrees with the historical narrative., (Copyright © 2017 by the Genetics Society of America.)

Motivation: Approaches to identifying new risk loci, training risk prediction models, imputing untyped variants and fine-mapping causal variants from summary statistics of genome-wide association studies are playing an increasingly important role in the human genetics community. Current summary statistics-based methods rely on global 'best guess' reference panels to model the genetic correlation structure of the dataset being studied. This approach, especially in admixed populations, has the potential to produce misleading results, ignores variation in local structure and is not feasible when appropriate reference panels are missing or small. Here, we develop a method, Adapt-Mix, that combines information across all available reference panels to produce estimates of local genetic correlation structure for summary statistics-based methods in arbitrary populations., Results: We applied Adapt-Mix to estimate the genetic correlation structure of both admixed and non-admixed individuals using simulated and real data. We evaluated our method by measuring the performance of two summary statistics-based methods: imputation and joint-testing. When using our method as opposed to the current standard of 'best guess' reference panels, we observed a 28% decrease in mean-squared error for imputation and a 73.7% decrease in mean-squared error for joint-testing., Availability and Implementation: Our method is publicly available in a software package called ADAPT-Mix available at https://github.com/dpark27/adapt&#95;mix., (© The Author 2015. Published by Oxford University Press.)

Background: Acute lymphoblastic leukemia (ALL) is the most common cancer in children and the incidence of ALL varies by ethnicity. Although accumulating evidence indicates inherited predisposition to ALL, the genetic basis of ALL susceptibility in diverse ancestry has not been comprehensively examined., Methods: We performed a multiethnic genome-wide association study in 1605 children with ALL and 6661 control subjects after adjusting for population structure, with validation in three replication series of 845 case subjects and 4316 control subjects. Association was tested by two-sided logistic regression., Results: A novel ALL susceptibility locus at 10p12.31-12.2 (BMI1-PIP4K2A, rs7088318, P = 1.1 × 10(-11)) was identified in the genome-wide association study, with independent replication in European Americans, African Americans, and Hispanic Americans (P = .001, .009, and .04, respectively). Association was also validated at four known ALL susceptibility loci: ARID5B, IKZF1, CEBPE, and CDKN2A/2B. Associations at ARID5B, IKZF1, and BMI1-PIP4K2A variants were consistent across ethnicity, with multiple independent signals at IKZF1 and BMI1-PIP4K2A loci. The frequency of ARID5B and BMI1-PIP4K2A variants differed by ethnicity, in parallel with ethnic differences in ALL incidence. Suggestive evidence for modifying effects of age on genetic predisposition to ALL was also observed. ARID5B, IKZF1, CEBPE, and BMI1-PIP4K2A variants cumulatively conferred strong predisposition to ALL, with children carrying six to eight copies of risk alleles at a ninefold (95% confidence interval = 6.9 to 11.8) higher ALL risk relative to those carrying zero to one risk allele at these four single nucleotide polymorphisms., Conclusions: These findings indicate strong associations between inherited genetic variation and ALL susceptibility in children and shed new light on ALL molecular etiology in diverse ancestry.

Analyses of genetic polymorphism data have the potential to be highly informative about the demographic history of Native American populations, but due to a combination of historical and political factors, there are essentially no autosomal sequence polymorphism data from any Native American group. However, there are many resequencing studies involving Latinos, whose genomes contain segments inherited from their Native American ancestors. In this study, we introduce a new method for estimating local ancestry across the genomes of admixed individuals and show how this method, along with dense genotyping and targeted resequencing, can be used to assay genetic variation in ancestral Native American groups. We analyze roughly 6 Mb of resequencing data from 22 Mexican Americans to provide the first large-scale view of sequence level variation in Native Americans. We observe low levels of diversity and high levels of linkage disequilibrium in the Native American-derived sequences, consistent with a recent severe population bottleneck associated with the initial peopling of the Americas. Using two different computational approaches, one novel, we estimate that this bottleneck occurred roughly 12.5 Kya; when uncertainty in the estimation process is taken into account, our results are consistent with archeological estimates for the colonization of the Americas.

Low-frequency right prefrontal repetitive transcranial magnetic stimulation (rTMS) appears to have antidepressant properties although the effectiveness of this treatment in clinical practice has not been assessed nor have the optimal stimulation parameters been adequately defined. A total of 130 patients with treatment-resistant depression were randomized to either 1- or 2-Hz rTMS over the right prefrontal cortex (PFC) for 2 wk with a possible further 2 wk extension. Non-responders were randomized to either 5- or 10-Hz left PFC rTMS. Overall, 66 patients (51%) achieved response and 35 (27%) remission criteria. For right-sided treatment, depression significantly improved but there was no between-group difference. Twenty-eight (42%) patients in the 1-Hz group and 33 (53%) patients in the 2-Hz group achieved response criteria (chi2=1.40, p>0.05). Depression symptom scores also improved for patients who crossed over to left-sided treatment but there was no significant difference in response between 5- and 10-Hz rTMS. Despite a heterogeneous sample, a significant proportion of patients met clinical response criteria following treatment but response to 1 and 2 Hz did not differ. 2-Hz right PFC rTMS has antidepressant properties but offers no advantage over 1 Hz despite doubling pulse number.