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Molecular Biology of the Cell by Bruce Alberts, Alexander Johnson, Julian Lewis, David Morgan, Martin Raff, Keith Roberts, Peter Walter by by Bruce Alberts, Alexander Johnson, Julian Lewis, David Morg

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STUDYING GENE EXPRESSION AND FUNCTION

493

Polymorphisms Can Aid the Search for Mutations Associated with

Disease

Mutations that give rise, in a reproducible way, to rare but clearly defined abnormalities,

such as albinism, hemophilia, or congenital deafness, can often be identified

by studies of affected families. Such single-gene, or monogenic, disorders

are often referred to as Mendelian because their pattern of inheritance is easy to

track. Moreover, individuals who inherit the causative mutation will exhibit the

abnormality irrespective of environmental factors such as diet or exercise. But for

many common diseases, the genetic roots are more complex. Instead of a single

allele of a single gene, such disorders stem from a combination of contributions

from multiple genes. And often, environmental factors have strong influences

on the severity of the disorder. For these multigenic conditions, such as diabetes

or arthritis, population studies are often helpful in tracking down the genes that

increase the risk of getting the disease.

In population studies, investigators collect DNA samples from a large number

of people who have the disease and compare them to samples from a group of

people who do not have the disease. They look for variants—SNPs, for example—

that are more common among the people who have the disease. Because DNA

sequences that are close together on a chromosome tend to be inherited together,

the presence of such SNPs could indicate that an allele that increases the risk of

the disease might lie nearby (Figure 8–51). Although, in principle, the disease

could be caused by the SNP itself, the culprit is much more likely to be a change

that is merely linked to the SNP as part of a haplotype block.

Such genome-wide association studies have been used to search for genes that

predispose individuals to common diseases, including diabetes, coronary artery

disease, rheumatoid arthritis, and even depression. For many of these conditions,

the DNA polymorphisms identified increase the risk of disease only slightly.

Moreover, environmental factors (diet, exercise, for example) play an important

role in the onset and severity of the disease. Nonetheless, the identification of

genes affected by these polymorphisms is leading to a mechanistic understanding

of some of our most common disorders.

Genomics Is Accelerating the Discovery of Rare Mutations That

Predispose Us to Serious Disease

The genetic variants that have thus far allowed us to identify some of the genes

that increase our risk of disease are common ones. They arose long ago in our evolutionary

past and are now present, in one form or another, in a substantial portion

(1% or more) of the population. Such polymorphisms are thought to account

healthy individuals

individual A

B

C

D

E

affected individuals

individual A

B

C

D

E

Figure 8–51 Genes that affect the

risk of developing a common disease

can often be tracked down through

linkage to SNPs. Here, the patterns

of SNPs are compared between two

sets of individuals—a set of healthy

controls and a set affected by a particular

common disease. A segment of a

typical chromosome is shown. For most

polymorphic sites in this segment, it is

a random matter whether an individual

has one SNP variant (red vertical bars)

or another (blue vertical bars); this same

randomness is seen both for the control

group and for the affected individuals.

However, in the part of the chromosome

that is shaded in darker gray, a bias is

seen: most normal individuals have the

blue SNP variants, whereas most affected

individuals have the red SNP variants.

This suggests that this region contains,

or is close to, a gene that is genetically

linked to these red SNP variants and that

predisposes individuals to the disease.

Using carefully selected controls and

thousands of affected individuals, this

approach can help track down diseaserelated

genes, even when they confer only

a slight increase in the risk of developing

the disease.

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