Race is frequently used by clinicians and biomedical researchers to
make inferences about an individual’s ancestry and to predict whether
an individual carries specific genetic risk factors that influence health.
The extent to which race is useful for making such predictions depends on
how well race corresponds with genetic inferences of ancestry, how frequently
common diseases in different racial groups are influenced by the same vs different
gene variants, and whether such variants have the same effects in different
racial groups. New studies of human genetic variation show that while genetic
ancestry is highly correlated with geographic ancestry, its correlation with
race is modest. Therefore, while data on the correspondence of race, ancestry,
and health-related traits are still limited, particularly in minority populations,
geographic ancestry and explicit genetic information are alternatives to race
that appear to be more accurate predictors of genetic risk factors that influence
health. Making accurate ancestry inferences is crucial because common diseases
and drug responses are sometimes influenced by gene variants that vary in
frequency or differ altogether among racial groups. Thus, operationalizing
alternatives to race for clinicians will be an important step toward providing
more personalized health care.
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Distributions of the reduction in blood pressure observed in African
Americans and European Americans after treatment with an angiotensin-converting
enzyme (ACE) inhibitor. One hypothetical explanation for the mean difference
in treatment response is that a genetic risk variant predictive of a positive
response to treatment is more common in European Americans (individuals to
the right of the dotted line) than in African Americans. Note, however, that
some African Americans also have the genetic risk variant and that many African
Americans and European Americans who do not have the genetic risk variant
have a similar response to treatment (ie, overlap between distributions).
In this case, race might not be considered a good predictor of genetic risk
or response to treatment. Based on original concept by Seghal.9
(A) A network depicting the genetic relatedness among individuals (circles)
with self-identified ancestry from Africa (20), Asia (19), and Europe (20)
genotyped for 250 coding single nucleotide polymorphisms (SNPs) for which
the less common allele has a frequency of at least 10% (Bamshad et al32). The length of each branch (black lines) is proportional
to genetic distance between individuals and populations. Distinguishing individuals
by race (shaded areas) obscures this variation in ancestry. The distance between
any 2 circles of the same color (solid lines) is large and reflects high within-population
variance, whereas the distance between clusters (dotted lines) is small and
reflects low between-population variance. Individuals with a higher proportion
of ancestry from more than one population (individual 2) are connected directly
to the branches between clusters. (B) The genetic distance between individuals
is reflected by the sum of the branch lengths between individuals. The genetic
distance between individuals from different populations, such as individuals
1 and 3, is slightly greater than the genetic distance between individuals
within the same population, such as individuals 1 and 2. Thus, despite the
high within-population variance, individuals from different populations are,
on average, more different from one another than individuals from the same
population. (C) Inferred ancestry proportions for individuals (circles) used
in panel A genotyped for 500 coding SNPs with a minor allele frequency of
at least 10%. The distance of each circle to an apex is proportional to the
degree of ancestry in African Americans, Asian Americans, or European Americans.
The degree to which the circles are clustered within a population reflects
the degree of admixture and structure within a population. The circles representing
African Americans are less tightly clustered because the proportion of ancestry
among individuals is more varied than in Asian Americans and European Americans.
Distinguishing individuals by race (shaded areas) obscures this variation
in ancestry. Data source for panels B and C, Bamshad et al.32
Comparison of common SNPs identified by resequencing 3873 genes in 17
Hispanics, 20 African Americans, 19 Asian Americans, and 20 European Americans.
(A) The proportion of SNPs that are common (ie, ≥10%) in at least one population
but found in both populations is high overall but varies from 72% to 96%.
A modest proportion of common SNPs that are common in at least one population
are absent in the other population. For example, only 4% of SNPs common in
European Americans or Hispanics are not present in both populations, whereas
28% of SNPs common in African Americans or Asian Americans are not present
in both populations. (B) The proportion of common SNPs common in both populations
compared with SNPs common in only each population compared. Overall, only
a modest proportion (44%-72%) of SNPs common in one population are common
in both populations. A substantial proportion of common SNPs in African Americans
are common only in African Americans. Data source: Genaissance Pharmaceuticals
Inc, New Haven, Conn, unpublished data, August 2005.
Comparison of the frequencies of single nucleotide polymorphisms (SNPs)
shared among 17 Hispanics, 20 African Americans, 19 Asian Americans, and 20
European Americans in whom 3873 genes were resequenced. The less frequent
SNP in the combined population was designated as the minor SNP, and the frequency
of the minor SNP was calculated in each population for the 63 012 SNPs
analyzed. Single nucleotide polymorphisms with significant differences (z>1.65, P<.05) between populations
that are common in both populations are shown as blue data points. Single
nucleotide polymorphisms with significant differences in frequency (z>1.65, P<.05) between populations
that are common in only one population are shown as red dark and pale data
points. Black data points represent SNPs that are common and that do not differ
significantly in frequency between populations. A Spearman rank correlation
coefficient between the minor allele frequencies of each SNP were estimated
for each population pairwise comparison. Data source: Genaissance Pharmaceuticals
Inc, New Haven, Conn, unpublished data, August 2005.
Country-Specific Mortality and Growth Failure in Infancy and Yound Children and Association With Material Stature
Use interactive graphics and maps to view and sort country-specific infant and early dhildhood mortality and growth failure data and their association with maternal
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