A short case study based on genetics - Science
There is an attached file with questions related to genetics. They dont need to be written professionally, but detailed explanations would be very good.
genetics_hw.docx
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Introduction
To date different risk factors have been identified regarding the likelihood of contracting
COVID-19, the disease caused by the SARS-CoV-2 virus. For example, there is a lower risk
of contracting COVID-19 if you remain 2 metres away from someone who is known to be
infected. The risk becomes much greater if you are in close contact with someone who has
been infected with the virus because the virus is known to be carried on particles expelled
from the respiratory system of the infected person, and can remain viable (active) on surfaces
for up to several days. And yet, some who are exposed to people infected with the virus do
not seem to be as likely to get COVID-19 as others. Why is this?
It is possible that natural differences in our cells influence the risk of getting a disease after
you are exposed. For example, it has been shown that some viruses like the hepatitis C virus
and the norovirus take advantage of the differences in proteins found on the surfaces of our
cells. These proteins are known as antigens and are shown in figure 1 below. These
differences can have interesting consequences regarding who gets sick and who does not
when they are exposed to the virus.
Figure 1. Red blood cells with antigens on the surface of their membranes.
https://i.stack.imgur.com/ObHfP.jpg
The idea that proteins called antigens found on your cells influence whether or not you get
sick has also been associated with blood type. This is because your blood type is determined
by the presence of antigens as shown in the table below.
If you have blood type A, your blood cells express the A antigen. If you have blood type B,
your blood cells express the B antigen. If you have blood type AB it means you express both
A and B antigens on the surface of your blood cells. If you have blood type O you do not
express any antigens at all.
The genetics of blood types
Your blood type and thus the presence of these antigens are determined by a gene which has
three different alleles - A, B and O. The table below shows the different possible
combinations of alleles (genotypes) that you could inherit from your mother and father to get
different blood types.
Mother’s alleles
Father’s alleles
A
B
O
A
AA
AB
AO
B
AB
BB
BO
O
AO
BO
OO
Alleles A and B are both dominant - meaning if you inherit one copy of each, you will
express both of them and have blood genotype AB. Allele O is recessive - meaning the only
way to have type O blood is if you inherit two copies of this allele and have blood genotype
OO.
Questions:
Use your understanding of genetics and Punnett squares to answer the following questions
about blood types.
1. The Punnett square below shows the result of a cross between a mother who is
heterozygous for blood type A and a father who is heterozygous for blood type B.
Mother’s alleles
Father’s alleles
A
O
B
AB
BO
O
AO
OO
a) What are the chances of producing offspring with the following blood types:
Blood type O? __________
Blood type AB? __________
b) What is the blood type of the offspring that have the genotype AO?
2. Predict the genotypes and phenotypes for a cross between a mother who is homozygous
for blood type A and a father who is blood type O.
3. A father is questioning the paternity of his child. He has blood type B, the mother has
blood type AB and the son has blood type A. Is it possible that the child could be his? If so,
under what conditions?
What does this have to do with COVID-19?
Blood antigen proteins such as A and B can be expressed by many of the body’s cells like the
lungs and intestines and are known to act as places where viruses can attach to your cells.
Thus, a person’s blood type may be associated with how likely they are to get sick, even if
that disease does not directly impact blood cells.
In a study that was released by Zhao et al. (2020), the authors investigated a potential
relationship between blood type and risk of being hospitalized with COVID-19. They looked
at the blood types of patients and people who died and compared that to controls (people
without COVID-19) in both Wuhan and Shenzen.
The scientists collected and checked the blood types from 1,775 patients with COVID-19,
including 206 dead cases, at the Jinyintan Hospital in Wuhan, Hubei province, China.
Another 285 patients were recruited from Shenzhen Third Peoples Hospital, Guangdong
province, China. Blood types were also checked for 3,694 normal people from Wuhan City
and 23,386 normal people from Shenzhen City to be used as “controls.”
The following is a table of the data they collected as well as two graphs that visually show
the data.
The ABO blood group distribution in patients with COVID-19 and normal controls.
Data from Wuhan Jinyintan Hospital
Percentage of Individuals with Each Blood Type
Controls
(people in Wuhan area)
A
B
AB
O
32.16\%
24.91\%
9.10\%
33.84\%
Patients
37.75\%
26.42\%
10.03\%
25.80\%
Deaths
41.26\%
24.27\%
9.22\%
25.24\%
Data from Shenzen Third Peoples Hospital
Percentage of Individuals with Each Blood Type
A
B
AB
O
Controls
(people in Shenzen area)
28.77\%
25.14\%
7.32\%
38.77\%
Patients
28.77\%
29.12\%
13.68\%
28.42\%
Figure 1. The ABO blood group distribution in patients with COVID-19 and normal controls
from Wuhan area and Wuhan Jinyintan Hospital.
Figure 2. The ABO blood group distribution in patients with COVID-19 and normal controls
from Shenzen area and Shenzen Third People’s Hospital.
Questions:
Use the data in the table and graphs to answer the following questions.
1. What conclusions can you draw about the differences in the chances of getting sick with
COVID-19 based on blood type?
2. Compared to data from the Wuhan Jinyintan Hospital, some data are missing from the
Shenzhen Third People’s Hospital. What are these missing data and how does this impact
the conclusions you can make from this study?
3. How could the study by Zhao et al. (2020) be improved to make it more accurate?
4. Do you think there is any danger in presenting “raw” data like that presented in the table
to the public? Why or why not?
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