Course of Laboratory Medicine
Medical School course F - Faculty of Pharmacy and Medicine
Prof. Andrea Bellelli

      To register your attendance please type in your surname and matricola number.
Notice that your attendance will be registered only if you completed the reading, questions, and audios, and that you cannot interrupt and resume the session (but you can repeat it as many times as you like). Remember to press the [send] button before leaving this page! A confirmation message will appear at the end of this page.
      A comment section has been added at the end of this lecture. Adding a comment or question does not require registration with your matricola number, feel free to comment whenever you like.

     In this purely theoretical exercise, we shall investigate one among the possible causes of inter-individual variability.

The reaction scheme
      Let us suppose that the terminal part of a metabolic pathway converts irreversibly metabolyte A into metabolyte B and then into terminal product C that is excreted. The reaction scheme is as follows:
A → B → C

      Reaction 1 irreversibly converts A to B and is catalyzed by enzyme E1; reaction irreversibly 2 converts B to C and is catalyzed by enzyme E2.
      We further suppose that the concentration of metabolyte A is regulated by a negative feedback mechanism and is maintained constant. Moreover since product C is excreted and the reactions leading to its production are irreversible, we can neglect its concentration. We want to investigate the steady-state concentration of metabolyte B.
      Let us assume that both E1 and E2 operate under steady-state conditions and obey a simple Michaelis and Menten equation. The rate of change of the concentration of metabolyte B is described by the following differential kinetic equation:
          (eqn. 1)
where the first term describes the rate of formation of B from A (whose concentration is assumed to be constant) and the second term describes the rate of degradation of B. Vmax,1 and KM,1 are the Michaelis and Menten parameters for E1 and Vmax,2 and KM,2 those for E2.

      Under steady-state conditions, the concentration of B is constant, i.e. the differential equation describing its change equals zero. Thus, we can solve the above equation for [B] to obtain:
          (eqn. 2)

      The above formula allows us to calculate the concentration of metabolyte B for any set of conditions. For example, if we assume the following set of parameters:
steady-state concentration of A       KM,1       Vmax,1       KM,2       Vmax,2      
1 mM 1 mM 10 s-1 1 mM 10 s-1
we can easily calculate from eqn. 2 that the steady-state concentration of B is 1 mM.

Presence of allelic variants of the enzyme(s) and their distribution in the population
      Let us assume that in the population under study there are two genetic variants of E1 and two of E2, that we call E1, e1, E2 and e2 respectively. All variants are functional, but they differ because of slight changes in Vmax and KM, e.g.:
E1: Vmax,1=11 s-1; KM,1=0.9 mM                   e1: Vmax,1=9 s-1; KM,1=1.1 mM
E2: Vmax,2=11 s-1; KM,2=0.9 mM                   e2: Vmax,2=9 s-1; KM,2=1.1 mM

      Let us further assume that the concentration of each enzyme is constant and that function of enzyme 1 in the heterozygous individual having an equimolar mixture of E1 and e1 can be approximated by a Michaelis and Menten equation with averaged parameters (i.e. Vmax,1=10 s-1; KM,1=1 mM). The same applies to the function of enzyme 2. These approximations are very rough, but sufficient for our present purpose:

      To simulate the distribution of the concentration of B in the population we need one further information, namely the gene frequencies for E1 and e1, E2 and e2. Let us assume that the gene frequencies are 50% for each gene; the Hardy-Weinberg law allows us to calculate the phenotype frequencies as follows:
E1E1: 0.52=0.25       E1e1: 0.5 x 0.5 x 2 = 0.5       e1e1: 0.52=0.25
E2E2: 0.52=0.25       E2e2: 0.5 x 0.5 x 2 = 0.5       e2e2: 0.52=0.25

      The frequencies of the different two-gene phenotypes are then calculated by multiplying those of the pertinent single-gene phenotypes; e.g.:
E1e1 / E2e2 = 0.5 x 0.5 = 0.25

      The distribution of metabolyte B concentration in the population can be calculated as follows:

1) A very simple model of a metabolic pathway including only three chemical intermediates and two enzymes, under the assumption of two very similar allelic variants of each enzyme, can generate a surprisingly wide variability of the intermediate metabolyte.
2) The distribution of the intermediate metabolyte concentration is described by a skewed Gaussian curve.
3) As predictable, the concentration of the intermediate metabolyte is highest in subjects whose genetic constitution is such that they are homozygous for the more effective variant of the producing enzyme (E1E1), and again homozygous for the less effective variant of the degrading enzyme (e2e2).
4) If the concentration of the intermediate metabolyte is in any way related to susceptibility to a specific disease the model would partially explain the incidence of the disease.
5) The frequencies of the highest and lowest values of the intermediate metabolyte concentrations do not correlate with the frequency of any single gene variant (because they correlate with the products of the gene frequencies).

Inter-population variability
      Human populations usually present different frequencies of the same alleles of the same genes. It is quite uncommon that an allele is present in a population and completely absent in another (if this happens, this points to a very ancient separation in the evolutionary history of Homo sapiens).
      We can easily simulate this condition using the same data we used for simulating inter-individual variability, but changing the gene frequencies. An important consequence of the above consideration is that it is very difficult to assign a single individual to any given population. What one can do is to estimate the probability that a single individual is a member of a given population. Obviously, the more allele variants and the more genes are considered, the more reliable this estimate is.

Variability within group and between groups
      An important statistical concept to be applied when a population is composed by two or more different groups is that of variability within and between. The total variability recorded in the entire population is estimated as the total deviance, DT:
DT = Σ (xi - xm)2
where x is the value of the parameter considered, and xm its average. If we divide DT by (N-1), where N represents the number of the members of the total population we obtain the total variance, σ2T of the population: σ2T = DT / (N-1).
      If the population is composed by two groups, each with its own deviance, we have:
D1 = Σ (x1,i - x1,m)2
D2 = Σ (x2,i - x2,m)2
where x1,i represents the individual values of parameter x in group 1 and x1,m the average value of parameter x in group 1; the same applies to x2,i and x2,m for group 2.
      The deviance within, DW is the sum of the deviance of each group with respect to its average value: DW = D1 + D2.
      The deviance between, DB is the deviance of the average of each group with respect to the average of parameter x in the total population times the number of elements in each group (in our example we only have two groups): DB = Σ Nj (xj,m - xm)2. Obviously the sum of the number of elements of each group equals the total population: N = Σ (Nj).
      The sum of the deviance within and the deviance between equals the total deviance of the population: DT = DB + DW.
      The above relationship is important: in some cases the DB may be large with respect to DW. For example if we compare the glycemias of a group of diabetic patients with that of a control group of healthy subjects we observe that DB >> DW, implying that there is a larger difference in the average values of glycemia in the two groups than there is in the glycemias of diabetic patients or healthy subjects. The opposite is usually found in human groups of healthy subjects, where DB << DW. For example, in cognitive tests measuring linguistic ability women usually score slightly better than men, but the deviance among women and the deviance among men are much larger than those between the averages of women and men. These two possible conditions are schematicaly represented below:

Populations are not races
      The concept of race applied to human populations has a releatively short (and infamous) history: it was initially used by De Gobineau in France and Knox in England (both circa 1850). A race is an artificial group, obtained in zootechnology or agriculture by rigorous control over reproduction. As a consequence it cannot be applied to human populations and we can state that human races do not exist. The difference between a race and a population or ethnic group is evident to genetists but quite subtle for non-specialists. We may explain this difference by comparing two examples, one for two populations, the other for two races.
      The distribution of blood groups in Italy is fairly homogeneous, except for Sardinia, which is different, as shown in the table below:
blood groups:0ABAB
Italy except Sardinia46%42%9%3%

      Clearly, the Sardinian population stands apart from the rest of Italy, but you cannot find this property in any single individual. A population differs from another because of the allelic frequencies of the same genes. Allele frequencies are properties of groups, not of individuals. Obviously, two populations differ because of the allele frequencies of a large number of genes, not only one.
      By contrast let's consider the case of two races, e.g. basset-hounds and terrier. All and every basset-hounds have a mutation of the gene FGFR3, and carry the same genetic defect of human achondroplasia, which causes a reduced growth of long bones. By contrast no terrier has this mutation. Thus race is a genetic property of the population and of each of its members. Clearly, a race can be maintained only if mating is strictly controlled, either by humans or by physical barriers. Again, two races of the same species differ because of allele variants of many genes, not only one.
      As a consequence of the above distinction, we can confidently state that an individual animal is a member of a specific race (and eventually how "pure" it is), whereas in the case of individual humans we can determine which alleles he/she posesses for relevant genes and infer the probability that he/she is a member of a population. Moreover, in order to define the human populations we also need non-genetic criteria (e.g. language or geographical considerations).
      Races, but not populations, have an impoverished gene pool. Applying strict control over mating one can further reduce the gene pool of a group of animals and obtain the strain. This is only done for laboratory animals; all individuals belonging to the same strain are genetically identical or almost so and they accept transplants from individuals of the same strain without rejection (which is not the case with animal of the same race).
      The genetic of populations is extremely important in medicine because different alleles may be differently related to susceptibility to diseases; thus disease prevalences may vary among different populations, because of their characteristic allele frequencies. This in turn affects the reliability of our diagnostic hypotheses, because the prevalence appears as the pre-test probability in Bayes' formula.

Questions and exercises:
1) Inter-human variability is a consequence of:
the distribution of allelic variants of the same genes
the presence of non-functional genes in the population
environmental factors

2) Inter-population variability is a consequence of:
different frequencies of (the same) allelic variants of genes
environmental factors
the presence of different genes in the different populations

3) The Hardy Weinberg law
describes the genotype frequencies
correlates the phenotype frequencies to the gene frequencies
describes allelic frequencies

4) The variability of analytes' concentrations among different individuals
is determined by stochastic phenomena
is genetically determined because of allelic variants of the analytes
is genetically determined because of allelic variants of the enzymes responsible of the metabolism of analytes

your score: 0
Attendance not registered because matricola was not entered.

You can type in a comment or question below (max. length=160 chars.):

All comments posted on the different subjects have been edited and moved to
this web page (for optimal reading try to have at least 80 characters per line)!

Thank you Professor (lecture on bilirubin and jaundice).

The fourth recorded part, the one on hyper and hypoglycemias is not working.
Bellelli: I checked and in my computer it seems to work. Can you better specify
the problem you observe?

This Presentation (electrolytes and blood pH) feels longer than previous lectures
Bellelli: it is indeed. Some subjects require more information than others. I was
thinking of splitting it in two nest year.

Bellelli in response to a question raised by email: when we compare the blood pH
with the standard pH we do not mean to compare the "normal" blood pH (7.4)
with the standard pH. Rather we compare the actual blood pH of the patient, with
the pH of the same blood sample equilibrated under standard conditions.
Thus, if we say that standard pH is lower than pH we mean that equilibriation with
40 mmHg CO2 has caused absorption of CO2 and has lowered the pH with respect
to its value before equilibration.

(Lipoproteins) Is the production of leptin an indirect cause of type 2 diabetes since
it works as a stimulus to have more adipose tissue that produces hormones?
Bellelli: in a sense yes, sustained increase of leptin causes the hypothalamus to adapt
and to stop responding. Obesity ensues and this in turn may cause an increase in the
production of resistin and other insulin-suppressing protein hormones produced by the
adipose tissue. However, this is quite an indirect link, and most probably other factors
contribute as well.

(Urea cycle) what is the meaning of "dissimilatory pathway"?
Bellelli: a dissimilatory pathway is a catabolic pathway whose function is not to produce
energy, but to produce some terminal metabolyte that must be excreted. Dissimilatory
pathways are necessary for those metabolytes that cannot be excreted as such by the
kidney or the liver because they are toxic or poorly soluble. Examples of metabolytes
that require transformation before being eliminated are heme-bilirubin, ammonia,
sulfur and nitrogen oxides, etc.

Talking about IDDM linked neuropathy can be the C peptide absence considered a cause of it??
Bellelli: The C peptide released during the maturation of insulin, besides being an indicator
of the severity of diabetes, plays some incompletely understood physiological roles. For
example it has been hypothesized that it may play a role in the reparation of the
atherosclerotic damage of the small arteries. Thus said, I am not aware that it plays a direct
role in preventing diabetic polyneuropathy. Diabetic neuropathy has at least two causes: the
microvascular damage of the arteries of the nerve (the vasa nervorum), and a direct
effect of hyperglycemia and decreased and irregular insulin supply on the nerve metabolism.
Diabetic neuropathy is observed in both IDDM and NIDDM, and requires several years to
develop. Since the levels of the C peptide differ in IDDM and NIDDM, this would suggest
that the role of the C peptide in diabetic neuropathy is not a major one. If you do have
better information please share it on this site!

In acute intermitted porphyria and congenital erythropoietic porphyria why do the end product
of the affected enzymes accumulate instead of their substrate??
Bellelli: First of all, congratulations! This is an excellent question.
Remember that a condition is which the heme is not produced is lethal in the foetus; thus
the affected enzyme(s) must maintain some functionality for the patient
to be born and to come to medical attention. All known genetic defects of heme
biosynthesis derange but do not block this metabolic pathway.
Congenital Erythropoietc Porphyria (CEP) is a genetic defect of uroporphyrinogen
III cosynthase. This protein associates to uroporphyrinogen synthase (which is present
and functional in CEP) and guarantees that the appropriate uroporphyrinogen isomer is produced
(i.e. uroporphyrinogen III). In the absence of a functional uroporphyrinogen III
cosynthase other possible isomers of uroporphyrinogen are produced together with
uroporpyrinogen III, mostly uroporphyrinogen I. The isomers of uroporphyrinogen
that are produced differ because of the positions of propionate and acetate side chains,
and this in turn is due to the pseudo symmetric structure of porphobilinogen. Only
isomer III can be further used to produce protoporphyrin IX. Thus in the
case of CEP we observe accumulation of abnormal uroporphyrinogen derivatives, which, as
you correctly observed are the products of the enzymatic synthesis operated by
uroporphyrinogen synthase.
The case of Acute Intermittent Porphyria (AIP) is similar, although there may be variants
of this disease. What happens is that either the affected enzyme is a variant that does not
properly associate with uroporphyrinogen III cosynthase or presents active site mutations
that impair the proper alignement of the phoprphobilinogen substrates. In either case
abnormal isomers of uroporphyrinogen are produced, as in CEP.
Also remark that in both AIP and CEP we observe accumulation of the porphobilinogen
precursor: this is because the overall efficiency of the biosynthesis of uroporphyrinogens is
reduced. Thus: (i) less uroporphyrinogen is produced, and (ii) only a fraction of the
uroporphyrinogen that is produced is the correct isomer (uroporphyrinogen III).

is it possible to take gulonolactone oxidase to synthesize vitamin C
instead of vitamin C supplement?
Bellelli: no, this approach does not work. The main reason is that
the biosynthesis of vitamin C, as almost all other metabolic processes, occurs intracellularly.
If you administer the enzyme it will at most reach the extracellular fluid but will not be
transported inside the cells to any significant extent. Besides, there are other problems
in this type of therapy (e.g. the enzyme if administered orally, may be degraded by digestive
proteases; if administered parenterally, may cause the immune system to react against a
non-self protein). In theory one could think of a genetic modification of the inactive human
gene of gulonolactone oxidase, but the risk and cost of this intervention would not be
justified. In addition to these considerations, except for cases of shipwreckage or
other catastrophes, a proper diet or administration of tablets of vitamin C is effective,
risk-free and unexpensive, thus no alternative therapy is reasonable. However, I express my
congratulations for your search on the biosynthesis pathway of ascorbic acid.

Resorption and not reabsorption would lead to hypercalcemia ie bone matrix being broken down.
Bellelli: I am not sure to interpret your question correctly. Resorption indicates destruction of the bone matrix and release of calcium and
phosphate in the blood, thus it causes an increase of calcemia. Reabsorption usually means active transport of calcium from the renal tubuli to the blood, thus
it prevents calcium loss. It prevents hypocalcemia, and thus complement bone resorption. To avoid confusion it is better use the terms "bone resorption" and "
renal reabsorption of calcium". If you have a defect in renal reabsorption, parthyroid hormone will be released to maintain a normal calcium level by means of
bone resorption; the drawback is osteoporosis.

In Reed and Frost model: I haven't understood what is the relationship
between K and R reproductive index. Thank you Professor!
Bellelli: in the Reed and Frost model K is the theoretical upper limit of
R0. R the reproductive index is the ratio (new cases)/(old cases) measured after
one serial generation time. R0 is the value of R one measures at the beginning
of the epidemics, when in principle all the population is susceptible.

      Home of this course

Slides of this lecture: