Dataset Information

Association of genetic variants with self-assessed color categories in Brazilians.

ABSTRACT: The Brazilian population was formed by extensive admixture of three different ancestral roots: Amerindians, Europeans and Africans. Our previous work has shown that at an individual level, ancestry, as estimated using molecular markers, was a poor predictor of color in Brazilians. We now investigate if SNPs known to be associated with human skin pigmentation can be used to predict color in Brazilians. For that, we studied the association of fifteen SNPs, previously known to be linked with skin color, in 243 unrelated Brazilian individuals self-identified as White, Browns or Blacks from Rio de Janeiro and 212 unrelated Brazilian individuals self-identified as White or Blacks from São Paulo. The significance of association of SNP genotypes with self-assessed color was evaluated using partial regression analysis. After controlling for ancestry estimates as covariates, only four SNPs remained significantly associated with skin pigmentation: rs1426654 and rs2555364 within SLC24A5, rs16891982 at SLC45A2 and rs1042602 at TYR. These loci are known to be involved in melanin synthesis or transport of melanosomes. We found that neither genotypes of these SNPs, nor their combination with biogeographical ancestry in principal component analysis, could predict self-assessed color in Brazilians at an individual level. However, significant correlations did emerge at group level, demonstrating that even though elements other than skin, eye and hair pigmentation do influence self-assessed color in Brazilians, the sociological act of self-classification is still substantially dependent of genotype at these four SNPs.

SUBMITTER: Durso DF

PROVIDER: S-EPMC3885524 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Association of genetic variants with self-assessed color categories in Brazilians.

Durso Danielle Fernandes DF Bydlowski Sergio Paulo SP Hutz Mara Helena MH Suarez-Kurtz Guilherme G Magalhães Tiago R TR Pena Sérgio Danilo Junho SD

PloS one 20140108 1

The Brazilian population was formed by extensive admixture of three different ancestral roots: Amerindians, Europeans and Africans. Our previous work has shown that at an individual level, ancestry, as estimated using molecular markers, was a poor predictor of color in Brazilians. We now investigate if SNPs known to be associated with human skin pigmentation can be used to predict color in Brazilians. For that, we studied the association of fifteen SNPs, previously known to be linked with skin c ...[more]

PMID: 24416183

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Project description:Semen analysis is central in infertility investigation. Manual assessment of sperm motility according to the WHO recommendations is the golden standard, and extensive training is a requirement for accurate and reproducible results. Deep convolutional neural networks (DCNN) are especially suitable for image classification. In this study, we evaluated the performance of the DCNN ResNet-50 in predicting the proportion of sperm in the WHO motility categories. Two models were evaluated using tenfold cross-validation with 65 video recordings of wet semen preparations from an external quality assessment programme for semen analysis. The corresponding manually assessed data was obtained from several of the reference laboratories, and the mean values were used for training of the DCNN models. One model was trained to predict the three categories progressive motility, non-progressive motility, and immotile spermatozoa. Another model was used in predicting four categories, where progressive motility was differentiated into rapid and slow. The resulting average mean absolute error (MAE) was 0.05 and 0.07, and the average ZeroR baseline was 0.09 and 0.10 for the three-category and the four-category model, respectively. Manual and DCNN-predicted motility was compared by Pearson's correlation coefficient and by difference plots. The strongest correlation between the mean manually assessed values and DCNN-predicted motility was observed for % progressively motile spermatozoa (Pearson's r = 0.88, p < 0.001) and % immotile spermatozoa (r = 0.89, p < 0.001). For rapid progressive motility, the correlation was moderate (Pearson's r = 0.673, p < 0.001). The median difference between manual and predicted progressive motility was 0 and 2 for immotile spermatozoa. The largest bias was observed at high and low percentages of progressive and immotile spermatozoa. The DCNN-predicted value was within the range of the interlaboratory variation of the results for most of the samples. In conclusion, DCNN models were able to predict the proportion of spermatozoa into the WHO motility categories with significantly lower error than the baseline. The best correlation between the manual and the DCNN-predicted motility values was found for the categories progressive and immotile. Of note, there was considerable variation between the mean motility values obtained for each category by the reference laboratories, especially for rapid progressive motility, which impacts the training of the DCNN models.

Dataset Information

Association of genetic variants with self-assessed color categories in Brazilians.

Publications

Association of genetic variants with self-assessed color categories in Brazilians.

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