Estimating prevalence of human traits among populations from polygenic risk scores.

The genetic basis of phenotypic variation across populations has not been well explained for most traits. Several factors may cause disparities, from variation in environments to divergent population genetic structure. We hypothesized that a population-level polygenic risk score (PRS) can explain phenotypic variation among geographic populations based solely on risk allele frequencies. We applied a population-specific PRS (psPRS) to 26 populations from the 1000 Genomes to four phenotypes: lactase persistence (LP), melanoma, multiple sclerosis (MS) and height. Our models assumed additive genetic architecture among the polymorphisms in the psPRSs, as is convention. Linear psPRSs explained a significant proportion of trait variance ranging from 0.32 for height in men to 0.88 for melanoma. The best models for LP and height were linear, while those for melanoma and MS were nonlinear. As not all variants in a PRS may confer similar, or even any, risk among diverse populations, we also filtered out SNPs to assess whether variance explained was improved using psPRSs with fewer SNPs. Variance explained usually improved with fewer SNPs in the psPRS and was as high as 0.99 for height in men using only 548 of the initial 4208 SNPs. That reducing SNPs improves psPRSs performance may indicate that missing heritability is partially due to complex architecture that does not mandate additivity, undiscovered variants or spurious associations in the databases. We demonstrated that PRS-based analyses can be used across diverse populations and phenotypes for population prediction and that these comparisons can identify the universal risk variants.

Differential asthma odds following respiratory infection in children from three minority populations.

RATIONALE: Severe early-life respiratory illnesses, particularly those caused by respiratory syncytial virus (RSV) and human rhinovirus (HRV), are strongly associated with the development of asthma in children. Puerto Rican children in particular have a strikingly high asthma burden. However, prior studies of the potential associations between early-life respiratory illnesses and asthma in Puerto Rican and other minority populations have been limited. OBJECTIVES: We sought to determine whether early-life respiratory illness was associated with asthma in Puerto Rican, Mexican American, and African American children. METHODS: Using a logistic regression analysis, we examined the association between early-life respiratory illnesses (report of upper respiratory infection (URI), pneumonia, bronchitis, and bronchiolitis/RSV) within the first two years of life and physician-diagnosed asthma after the age of two in a large cohort of Puerto Rican, Mexican American, and African American children. MEASUREMENTS AND MAIN RESULTS: While early-life respiratory illnesses were associated with greater asthma odds in Puerto Ricans, Mexican Americans, and African Americans, these associations were stronger among Puerto Rican children. Specifically, in Puerto Ricans, the odds was 6.15 (95% CI: 4.21-9.05) if the child reported at least one of the following respiratory illness: URI, pneumonia, bronchitis or bronchiolitis. The odds were also higher in Puerto Ricans when considering these conditions separately. CONCLUSIONS: We observed population-specific associations between early-life respiratory illnesses and asthma, which were especially significant and stronger in Puerto Ricans. Taken together with the known high burden of RSV in Puerto Rico, our results may help explain the high burden of asthma in Puerto Ricans.