Diet, height, and health

Yeboah, Joseph

doi:10.3945/ajcn.117.161562

Cited by 2 publications

(2 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As a truly polygenetic trait, human height is both complex and highly heritable [ 29 , 30 ]. In addition to the 4388 variants currently found to associate with this phenotype by GWAS, height is also dependent on environmental factors, including diet (Additional file 15 : Table S4) [ 70 ]. Visualization LocusZoom showed the SNPs are widely distributed across the genome (Additional file 3 : Figure S3) [ 46 ].…”

Section: Methodsmentioning

confidence: 99%

Estimating prevalence of human traits among populations from polygenic risk scores

et al. 2021

View full text Add to dashboard Cite

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.

show abstract

Section: Methodsmentioning

confidence: 99%

Estimating prevalence of human traits among populations from polygenic risk scores

et al. 2021

View full text Add to dashboard Cite

show abstract

“…As a truly polygenetic trait, human height is both complex and highly heritable (Lango Allen et al 2010;Lettre 2011). In addition to the 4,388 variants currently found to associate with this phenotype by GWAS, height is also dependent on environmental factors, including diet (Table S4) (Yeboah 2017). There are also differences in average height between men and women and between global populations.…”

Section: Heightmentioning

confidence: 99%

Estimating Prevalence of Human Traits Among Populations From Polygenic Risk Scores

Graham

Plotkin

Muglia

et al. 2021

Preprint

View full text Add to dashboard Cite

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 psPRS, 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 were as high as 0.99 for height in men using only 548 of the initial 4208 SNPs. That reducing SNPs improves psPRS 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.

show abstract

Diet, height, and health

Cited by 2 publications

References 9 publications

Estimating prevalence of human traits among populations from polygenic risk scores

Estimating prevalence of human traits among populations from polygenic risk scores

Estimating Prevalence of Human Traits Among Populations From Polygenic Risk Scores

Contact Info

Product

Resources

About