Ancestry adjusted ANOVA tests for association between Melanin Index (MI)^a and genotypes in two admixed Brazilian populations.

a<p>ANOVA tests performed on 1/MI.</p>b<p>Not tested due to scarcity of data (only n = 4 individuals with genotype CC).</p

Subtypes of Native American ancestry and leading causes of death: Mapuche ancestry-specific associations with gallbladder cancer risk in Chile

<div><p>Latin Americans are highly heterogeneous regarding the type of Native American ancestry. Consideration of specific associations with common diseases may lead to substantial advances in unraveling of disease etiology and disease prevention.</p><p>Here we investigate possible associations between the type of Native American ancestry and leading causes of death. After an aggregate-data study based on genome-wide genotype data from 1805 admixed Chileans and 639,789 deaths, we validate an identified association with gallbladder cancer relying on individual data from 64 gallbladder cancer patients, with and without a family history, and 170 healthy controls. Native American proportions were markedly underestimated when the two main types of Native American ancestry in Chile, originated from the Mapuche and Aymara indigenous peoples, were combined together. Consideration of the type of Native American ancestry was crucial to identify disease associations. Native American ancestry showed no association with gallbladder cancer mortality (P = 0.26). By contrast, each 1% increase in the Mapuche proportion represented a 3.7% increased mortality risk by gallbladder cancer (95%CI 3.1–4.3%, P = 6×10⁻²⁷). Individual-data results and extensive sensitivity analyses confirmed the association between Mapuche ancestry and gallbladder cancer. Increasing Mapuche proportions were also associated with an increased mortality due to asthma and, interestingly, with a decreased mortality by diabetes. The mortality due to skin, bladder, larynx, bronchus and lung cancers increased with increasing Aymara proportions. Described methods should be considered in future studies on human population genetics and human health. Complementary individual-based studies are needed to apportion the genetic and non-genetic components of associations identified relying on aggregate-data.</p></div

Genetic principal component analyses of individuals used in the aggregate-data study to investigate the relationship between the type of Native American ancestry and disease-specific mortality risks (panels A-D), and scatter plots of estimated Native American proportions using different reference individuals as surrogates of Native American ancestry: 9 Mapuche and 9 Aymara reference individuals versus samples from the Americans in the Human Genome Diversity Project, supervised ADMIXTURE analysis (panel E) and unsupervised ADMIXTURE analysis with four ancestral populations (panel F).

<p>Genetic principal component analyses of individuals used in the aggregate-data study to investigate the relationship between the type of Native American ancestry and disease-specific mortality risks (panels A-D), and scatter plots of estimated Native American proportions using different reference individuals as surrogates of Native American ancestry: 9 Mapuche and 9 Aymara reference individuals versus samples from the Americans in the Human Genome Diversity Project, supervised ADMIXTURE analysis (panel E) and unsupervised ADMIXTURE analysis with four ancestral populations (panel F).</p

Maps with average regional African, European, Native American, Aymara and Mapuche proportions, and regional mortality rates due to gallbladder cancer in Chile.

<p>Maps with average regional African, European, Native American, Aymara and Mapuche proportions, and regional mortality rates due to gallbladder cancer in Chile.</p

Genetic principal component analyses of individuals used in the validation study to investigate the relationship between Mapuche proportions and gallbladder cancer risk, using Mapuche and Aymara individuals as surrogates of the two largest indigenous peoples in Chile (panels A-C).

<p>Gallbladder cancer cases are represented by black dots and unaffected subjects by grey dots. Fig 4D represents the pedigrees of the four families included in the validation study (Gallbladder cancer cases genotyped in the study are represented by black dots, unaffected genotyped subjects by grey dots, non-genotyped gallbladder cancer cases by red dots and unaffected non-genotyped subjects by empty circles).</p

Estimated hazard ratios of being diagnosed with gallbladder cancer in the validation study.

<p>Estimated hazard ratios of being diagnosed with gallbladder cancer in the validation study.</p

Venn diagram with results from a stepwise forward model selection to identify the ancestry components showing the most significant associations with disease-specific mortality rates.

<p>Mapuche ancestry (reddish) showed the most significant associations with mortality rates due to 12 ICD10-disease categories and the Aymara component (in blue) was selected for 19 categories.</p

Total number of deaths and standardized mortality ratios (SMR) due to respiratory, digestive and endocrine diseases by 1% increase in the Native American (HGDP), Mapuche and Aymara proportions.

<p>Total number of deaths and standardized mortality ratios (SMR) due to respiratory, digestive and endocrine diseases by 1% increase in the Native American (HGDP), Mapuche and Aymara proportions.</p

Total number of deaths and standardized mortality ratios (SMR) due to diseases of the circulatory system and to neoplasms by 1% increase in the Native American (HGDP), Mapuche and Aymara proportions.

<p>Total number of deaths and standardized mortality ratios (SMR) due to diseases of the circulatory system and to neoplasms by 1% increase in the Native American (HGDP), Mapuche and Aymara proportions.</p

Estimated average Native American, Mapuche and Aymara proportions, and differences in the ancestry components by age class, gender, educational level, socioeconomic status, salary and region.

<p>Estimated average Native American, Mapuche and Aymara proportions, and differences in the ancestry components by age class, gender, educational level, socioeconomic status, salary and region.</p