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[Bob] Hello, this is Dr. Bob Wildin.

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And today's lecture is on
Genetic Testing for Clinicians.

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First question we want to
ask is, why do testing?

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Why do geneticists or other clinicians

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do testing in the first place?

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I break these kind of into two groups.

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The first is indication-based testing,

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where we suspect a health problem

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or an increased risk for
an inherited problem,

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or we want some guidance on treatment

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for which genetic testing
is the appropriate means

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of gathering that information.

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The second approach is preemptive testing,

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and that is to say there
is no clinical symptoms

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or abnormal lab values but we want to test

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to see if there's a
genetic variation present

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that has health impacts or
health predictive value.

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And that group can be
broken into two parts,

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focus testing, which comes about

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as the result of additional
clinical information

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such as family history

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or family history of a particular disorder

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or a family history of someone
who has tested positive

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for a genetic variant of importance.

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And a broad net.

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So a wide screen for genetic variations

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that may have clinical importance

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even though you don't necessarily suspect

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any of those things being present

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or active at this time in
the individual being tested.

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So what is variation?

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Variation is defined by
reference to a standard.

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The standard may or may not be normal.

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But in the current versions
of sequence standards

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are typically tweaked in order

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to be as free as possible

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of known disease-associated
genetic variation.

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Variation occurs naturally without regard

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to functional consequence.

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It's part of what drives evolution.

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Variation is subject
to selective pressures.

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So certain variations
may be sort of bred out

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if they result in the inability

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to reproduce unless they
are able to be carried

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by other people and
passed on by other people

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without an impact on
their genetic fitness.

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Variation typically
originates in one member

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of a population, and
some other descendants

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will inherit that and pass it on.

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And that results in frequency differences

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in different population lineages,

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which we call founder effect,

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as the result of what we
call founder mutations.

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All right, we talked previously
about the word mutation.

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We tend to talk about a variant,

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a variation in genetic sequence

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that we can observe as a
variant instead of a mutation.

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A mutation is the process
which leads to the variation.

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However, that term is
frequently used synonymous

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to genetic variations.

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So, what are the different
kinds of variations

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or mutations that can occur?

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One is a deletion happening
where a single base

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or more than one base
is sort of subtracted

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from the string of letters.

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A second is an insertion,

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an added base along with its complement,

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when that added base strand is replicated.

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A substitution.

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And any base can be substituted

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with any of the three other bases.

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And then on replication,

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it is fixed by copying
the substituted base

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in place of the complement
of the original base.

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That's on a DNA sequence base scale.

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On a macro scale,

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there is a deletion shown here,

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where a segment of a
chromosome goes missing.

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A duplication, where a segment

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of a chromosome becomes duplicated.

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In this case, in a tandem
head to tail fashion.

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And inversion, where a
segment of a chromosome

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gets flipped in its own location.

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A substitution, where instead of

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something being duplicated on-site,

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it is simply moved from one location

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to another in the genome,

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in this case from chromosome
4 to chromosome 20.

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And that results in this substitution

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or interstitial translocation.

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A translocation involving
the ends of the chromosomes

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is involved here,

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and this is a reciprocal translocation

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where a segment from one chromosome

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is exchanged for a segment
from another chromosome.

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Those result in hybrid chromosomes.

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These last two result
in hybrid chromosomes,

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which in and of themselves are balanced,

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meaning they have no additional

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or deficit of genetic information

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or of the copy number
of each of the genes.

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That's in contrast to the duplication

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or the deletion over here,
which are unbalanced.

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So this is just reviewing
some of the stuff

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that we've talked about in other lectures.

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The de novo mutation is recognized

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because there is no family history

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in the case of a dominant condition.

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It is not present in the
DNA of either parent.

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It is evidence supporting
variant pathogenicity.

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And we'll talk a little
bit more about that later

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in the lecture.

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And there's one little
caveat with this feature

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of it not being present in
the DNA of either parent,

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and that is the question
of alternate paternity.

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So let's just review some of the basics

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in genetics so we can move
forward with the concept

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of genetic testing and
some of the technologies

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that are frequently employed.

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So of course, the genome is your DNA.

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It is all of the genetic
material in the nucleus

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plus the mitochondrial genome.

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I'll say that in the case of testing,

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often the mitochondrial genome is left out

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unless you specifically specify

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that you need to include
that in the analysis.

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Molecules of DNA that
contain coded instructions

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for how to build, maintain,
and replicate a human being.

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It is not identical,

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your genome in anyone but identical twins.

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It always contains benign variation

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and variation that can cause
or contribute to diseases.

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That is to say we all have some variance

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that may predispose to disease

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or we are carriers of recessive diseases,

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usually we are.

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And the genome is quite big,

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3,3 billion base pairs from mom

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and the same number of base
pairs roughly from dad.

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Okay, let's review chromosomes.

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So chromosomes are the
packets of genetic material

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which make up the genome and its sequence.

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It's the DNA sequence
packaged together by histones,

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rolled together to nucleosomes

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and tightly coiled to
make a chromosome, say,

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in this metaphase chromosome picture.

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Prophase or metaphase.

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The chromosomes are visualized
under the microscope,

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and then cut out and stuck
onto a piece of paper

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based on their banding
pattern and their length.

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And that's called a karyotype.

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Chromosomes in humans have 23 pairs.

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That's 22 pairs of autosomes

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and one pair of sex chromosomes.

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There are the packages of DNA,

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they have a consistent structure.

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All right, DNA replication
happens during cell division

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and during the production
of the germ cells.

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The replication occurs in a 5 prime

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to 3 prime direction on both strands.

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All you really need is
a template DNA strand.

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So these single-stranded
ones that are being unwound

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from the double-stranded template.

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You need nucleotides and you
need a DNA polymerase molecule,

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which will march along
and add those nucleotides

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to the growing nascent
chain to make the copy.

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Information is preserved,
but errors are made.

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Errors result in sequence variation

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when they are not corrected, okay?

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Let's review the Basic Gene
Structure: Exons and Introns.

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In that chromosome,

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there are thousands of genes,

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or hundreds to thousands of genes

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in a particular chromosome.

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And the gene is sort of the entire segment

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that incorporates the element

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which when inherited together

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encodes a protein in
its regulatory elements

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as well as additional DNA.

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The exons, which contain
the coding information

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of the DNA are those that
will code for proteins,

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are divided by introns,

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which will be spliced out after the DNA

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is transcribed into RNA.

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And once spliced out,

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that becomes a messenger RNA.

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So exons are the segments of the gene

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that contain code for proteins.

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Introns are the spacers.

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And the gene coding regions,

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or the exons are about 1
to 2% of the entire genome.

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That's the exome.

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All right, again, a little bit of review.

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We've talked about the transcription,

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splicing occurs at this point.

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The RNA, and now a
messenger RNA after splicing

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is used as an information
source for the ribosome

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to start and extend a
growing amino acid chain,

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which becomes a protein.

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Okay.

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Genes and the proteins they encode

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can break for a number of reason.

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They can cause disease
for a number of reason.

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One is too much signal.

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There's too much of the gene,

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there's too much of the protein activity,

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such as a gene duplication
or triplication,

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and that will change potentially
the developmental program.

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There can be too little signal.

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Let's say a gene is somewhat disabled,

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such as in metabolic disorders

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where there is less enzyme activity.

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And if you get well below
10% of enzyme activity,

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you may actually have a disease.

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A loss of function is when
there's no function left.

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Those are important, for example,

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in tumor suppressor genes.

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And gain of function is
important in cancer as well,

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when certain mutations result

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in intracellular growth
signaling molecules

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becoming constitutively active

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and giving their growth signal

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even when their upstream signaling pathway

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is not being activated.

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Finally, genes can
simply not be expressed,

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meaning that the gene has been deleted,

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the RNA is damaged in such
a way that it's eliminated

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by the cell, or the promoter
and regulatory elements

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are not present.

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Okay, so what about genetic testing?

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What are the categories of genetic

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and genomic variation
testing technologies?

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So I tend to sort of break
this down into groups

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based on my intent when I'm
thinking about the testing.

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The first is a scanning technology,

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and I use that when I'm not sure exactly

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what I'm looking for.

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I don't know, I can't
sort of shine the light

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in a direction where
a sound is coming from

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and know really what I'm looking for.

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So I've really gotta turn on
the light in the whole room

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and look at everything that's there,

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or everything that I can see

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with that particular technology.

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The second is a focused.

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So I want to look for
phenotype-associated variations.

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I have a phenotype, I
have a pretty good idea

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of which genes or which
variations may be important

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in that particular phenotype,

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and so I'm going to focus my evaluations

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into those areas of the
genome or those variations.

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A targeted assessment is when
there is specific information

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about where in the genome I need to look.

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Is there a specific variant
that's already been identified

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in a family member?

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Is there a specific gene?

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Is the only gene that's variant

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in this particular condition?

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An example is achondroplasia,

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where there's essentially one location

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in the gene, in the FGFR3 gene,

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where mutations occur that
cause that specific phenotype.

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So those are examples where
I would do a targeted test

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and look very narrowly.

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So examples of scanning
technology are a karyotype.

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We're looking at all the chromosomes

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00:14:55,950 --> 00:14:57,060
at a certain resolution.

268
00:14:57,060 --> 00:14:58,740
Chromosome microarray,
where you're looking

269
00:14:58,740 --> 00:15:00,120
at greater resolution.

270
00:15:00,120 --> 00:15:01,920
We're gonna talk more about that.

271
00:15:01,920 --> 00:15:03,450
Exome or genome sequencing,

272
00:15:03,450 --> 00:15:05,070
where you're really sort of scanning

273
00:15:05,070 --> 00:15:09,090
the entire genome sequence

274
00:15:09,090 --> 00:15:10,620
And a genotyping array,

275
00:15:10,620 --> 00:15:14,133
that covers many, many known
variants all over the genome.

276
00:15:15,510 --> 00:15:16,830
In the focus group,

277
00:15:16,830 --> 00:15:20,310
we might do a targeted
gene sequencing panel,

278
00:15:20,310 --> 00:15:22,110
multiple genes, for example,

279
00:15:22,110 --> 00:15:25,470
that might be associated
with long QT syndrome.

280
00:15:25,470 --> 00:15:29,250
So we know a handful of genes
that are important there.

281
00:15:29,250 --> 00:15:31,990
We'll look just at those
genes in a gene panel

282
00:15:32,970 --> 00:15:36,510
rather than looking at the
entire exome or genome.

283
00:15:36,510 --> 00:15:40,720
And then, we might use a
gene-specific chromosome microarray

284
00:15:41,640 --> 00:15:44,790
to look for copy number
variants in the exons

285
00:15:44,790 --> 00:15:46,500
of that gene only.

286
00:15:46,500 --> 00:15:50,580
So two reasons why you
might inactivate a gene.

287
00:15:50,580 --> 00:15:53,810
You created a mutation and a
promoter or within the gene,

288
00:15:53,810 --> 00:15:55,800
so the protein doesn't work.

289
00:15:55,800 --> 00:15:59,220
Another reason is that you've
deleted the gene entirely,

290
00:15:59,220 --> 00:16:01,050
or at least one copy of the gene.

291
00:16:01,050 --> 00:16:06,050
So there are so-called
deletion duplication assays,

292
00:16:06,450 --> 00:16:07,773
or del/dup assays,

293
00:16:08,670 --> 00:16:12,720
which we used to use a
technique called MLPA,

294
00:16:12,720 --> 00:16:16,773
and now we just use a targeted
chromosome microarray.

295
00:16:18,210 --> 00:16:20,883
The targeted technologies
are single gene sequencing,

296
00:16:21,810 --> 00:16:23,250
single exon sequencing,

297
00:16:23,250 --> 00:16:27,000
if you know exactly where
in the gene you wanna look.

298
00:16:27,000 --> 00:16:30,450
And then there are
technologies that can type

299
00:16:30,450 --> 00:16:32,310
a particular variant.

300
00:16:32,310 --> 00:16:34,350
Is this variant present? Is it not?

301
00:16:34,350 --> 00:16:37,080
Is this G to A variant present,

302
00:16:37,080 --> 00:16:42,080
or is the G to A variant absent?

303
00:16:42,450 --> 00:16:46,110
So those kinds of genotyping
technologies exist

304
00:16:46,110 --> 00:16:48,180
and can be used to look at, for example,

305
00:16:48,180 --> 00:16:52,590
common tumor mutations like the KRAS G12V,

306
00:16:52,590 --> 00:16:56,583
which is a mutation in the 12th codon,

307
00:16:57,510 --> 00:16:59,913
which changes the glycine to a valine.

308
00:17:01,290 --> 00:17:04,620
in a RAS signaling protein called K-Ras,

309
00:17:04,620 --> 00:17:06,990
and it's frequently observed, for example,

310
00:17:06,990 --> 00:17:08,613
in non-small cell lung cancer.

311
00:17:10,740 --> 00:17:13,350
All right, let's talk about the sort

312
00:17:13,350 --> 00:17:14,970
of development and the history

313
00:17:14,970 --> 00:17:19,970
of clinical variation detecting
technologies in genomics.

314
00:17:20,550 --> 00:17:21,510
From older to newer,

315
00:17:21,510 --> 00:17:26,370
there's the karyotype chromosome
number we could identify

316
00:17:26,370 --> 00:17:29,850
by the late 50s, 1950s.

317
00:17:29,850 --> 00:17:32,610
And then, as we developed
better techniques

318
00:17:32,610 --> 00:17:35,280
to band the chromosomes with stains,

319
00:17:35,280 --> 00:17:38,010
we could identify their structure.

320
00:17:38,010 --> 00:17:41,610
So the karyotype is useful
for looking for aneuploidy,

321
00:17:41,610 --> 00:17:43,530
for large deletions and duplications,

322
00:17:43,530 --> 00:17:48,000
for inversions because the band pattern

323
00:17:48,000 --> 00:17:51,840
is changed so that you can
recognize an inversion.

324
00:17:51,840 --> 00:17:54,630
And a balanced translocation,
for the same reason.

325
00:17:54,630 --> 00:17:56,070
The band patterns and the links

326
00:17:56,070 --> 00:17:58,353
to the chromosomes may change.

327
00:18:00,150 --> 00:18:01,620
RFLP, which stands

328
00:18:01,620 --> 00:18:05,190
for restriction fragment
length polymorphisms,

329
00:18:05,190 --> 00:18:06,450
and Southern blots,

330
00:18:06,450 --> 00:18:10,560
you may have learned about
in classes in high school

331
00:18:10,560 --> 00:18:13,320
or undergraduate college.

332
00:18:13,320 --> 00:18:15,750
We don't use them very much anymore.

333
00:18:15,750 --> 00:18:18,270
They still are occasionally used

334
00:18:18,270 --> 00:18:21,250
with a lab technique called Southern blot

335
00:18:22,260 --> 00:18:26,547
in order to follow diseases
as they run through

336
00:18:28,920 --> 00:18:31,440
a large family to see
whether we can figure out

337
00:18:31,440 --> 00:18:36,303
which part of the genome
the putative gene is in.

338
00:18:38,970 --> 00:18:41,820
Sanger sequencing is sort of
the gold standard sequencing,

339
00:18:41,820 --> 00:18:44,700
and I'll talk about it a little bit more.

340
00:18:44,700 --> 00:18:49,230
It is for sequencing
anywhere from single exons

341
00:18:49,230 --> 00:18:53,310
to single genes or maybe small gene panels

342
00:18:53,310 --> 00:18:54,603
of two or three genes.

343
00:18:55,710 --> 00:18:59,340
It is essentially a blinded,
base sequence variation.

344
00:18:59,340 --> 00:19:02,340
So you're looking for any
base sequences in there,

345
00:19:02,340 --> 00:19:04,020
not for very specific ones,

346
00:19:04,020 --> 00:19:06,820
until you get the sequence
and you can see what's there.

347
00:19:08,970 --> 00:19:11,610
Oligonucleotide probe hybridization.

348
00:19:11,610 --> 00:19:14,130
So you've probably heard of FISH,

349
00:19:14,130 --> 00:19:16,713
or fluorescence in situ hybridization,

350
00:19:17,550 --> 00:19:22,110
where probes that are actually much larger

351
00:19:22,110 --> 00:19:26,610
than oligonucleotides,
they're a couple of megabases

352
00:19:26,610 --> 00:19:31,140
in length usually, are used
on chromosomes in a karyotype

353
00:19:31,140 --> 00:19:33,060
to detect the presence or absence

354
00:19:33,060 --> 00:19:34,773
of a deletion or duplication.

355
00:19:36,000 --> 00:19:38,820
Small probes, oligonucleotide probes

356
00:19:38,820 --> 00:19:43,820
can be used to detect single
nucleotide variants, CNVs,

357
00:19:46,980 --> 00:19:50,743
SNVs, or a copy number variation

358
00:19:54,480 --> 00:19:57,840
in a technique called
a chromosome microarray

359
00:19:57,840 --> 00:20:00,690
or a SNP microarray.

360
00:20:00,690 --> 00:20:03,060
And I'm gonna talk more
about those in a moment.

361
00:20:03,060 --> 00:20:05,190
And then there are these
genotyping platforms

362
00:20:05,190 --> 00:20:06,540
which, as I mentioned,

363
00:20:06,540 --> 00:20:09,690
are looking only in a binary fashion

364
00:20:09,690 --> 00:20:14,690
to say is a particular spelling
change present or absent?

365
00:20:16,050 --> 00:20:18,480
These can be very widespread

366
00:20:18,480 --> 00:20:20,910
and look all over the genome
for lots of different variants.

367
00:20:20,910 --> 00:20:22,980
That's what you find in, for example,

368
00:20:22,980 --> 00:20:27,930
23andMe and other direct to consumer types

369
00:20:27,930 --> 00:20:29,193
of genetic testing.

370
00:20:30,300 --> 00:20:34,800
And those are also sometimes useful,

371
00:20:34,800 --> 00:20:37,023
although they're more
important in research.

372
00:20:39,090 --> 00:20:41,040
Finally, there's
next-generation sequencing,

373
00:20:41,040 --> 00:20:43,533
or NGS for short.

374
00:20:44,430 --> 00:20:49,380
It is basically a multiple modification

375
00:20:49,380 --> 00:20:54,380
of Sanger-type sequencing,
that uses automation,

376
00:20:54,750 --> 00:20:58,860
miniaturization, and is
very high throughput.

377
00:20:58,860 --> 00:21:02,760
The length of the sequence
reads are relatively short,

378
00:21:02,760 --> 00:21:07,290
on the order to of 100 to 150 bases.

379
00:21:07,290 --> 00:21:09,840
And as such, it requires a great deal

380
00:21:09,840 --> 00:21:14,790
of computation to assemble
those into a genome

381
00:21:14,790 --> 00:21:19,740
and it's really done by
matching up each read

382
00:21:19,740 --> 00:21:24,740
to its putative position
on a reference sequence,

383
00:21:25,950 --> 00:21:28,053
and then assembling it all together.

384
00:21:29,850 --> 00:21:33,660
Next-generation sequencing
can process entire genome

385
00:21:33,660 --> 00:21:37,293
or a selected subset such
as an exome or a gene panel.

386
00:21:38,850 --> 00:21:43,850
In addition, we can use
non-DNA-based technologies

387
00:21:45,690 --> 00:21:50,670
to identify genetic
variation in individuals.

388
00:21:50,670 --> 00:21:53,040
We can look at protein sequence.

389
00:21:53,040 --> 00:21:55,530
We can look to do electrophoresis

390
00:21:55,530 --> 00:21:59,010
to identify shifts in
electrophoretic mobility,

391
00:21:59,010 --> 00:22:03,960
which usually relates to
charge of the protein.

392
00:22:03,960 --> 00:22:06,903
We can use immuno detection
and a lot of other techniques.

393
00:22:08,280 --> 00:22:11,400
We can also test for the metabolic

394
00:22:11,400 --> 00:22:12,720
or functional consequences.

395
00:22:12,720 --> 00:22:17,720
So, example, look in
urine by mass spectrometry

396
00:22:20,506 --> 00:22:24,720
for metabolites that shouldn't be there

397
00:22:24,720 --> 00:22:27,723
or that give a clue to a
particular metabolic disorder.

398
00:22:29,190 --> 00:22:31,650
Okay, I'm gonna throw out
some clinical scenarios,

399
00:22:31,650 --> 00:22:33,390
I'm gonna go through this really quick.

400
00:22:33,390 --> 00:22:36,270
And if you want, you
can pause and and think

401
00:22:36,270 --> 00:22:37,870
about this a little bit further.

402
00:22:39,420 --> 00:22:43,470
First, you examine a 2 week
old infant at his first visit.

403
00:22:43,470 --> 00:22:45,840
He's small for dates, has microcephaly,

404
00:22:45,840 --> 00:22:50,840
brachycephaly, small ears with
overturned superior helix,

405
00:22:51,000 --> 00:22:52,590
up-slanting palpebral fissures,

406
00:22:52,590 --> 00:22:55,170
and a deep vertical
plantar crease directly

407
00:22:55,170 --> 00:22:57,510
between rays 1 and 2.

408
00:22:57,510 --> 00:22:59,640
That means if you look at
the bottom of his foot,

409
00:22:59,640 --> 00:23:01,200
there's a vertical crease,

410
00:23:01,200 --> 00:23:05,043
the top of which is between
his big toe and his next toe.

411
00:23:05,880 --> 00:23:07,953
You suspect blank syndrome.

412
00:23:11,850 --> 00:23:14,220
So I'm pausing to see if you
want to go forward with that.

413
00:23:14,220 --> 00:23:15,333
But we'll go forward.

414
00:23:16,200 --> 00:23:18,150
Which genetic test
technology would be best

415
00:23:18,150 --> 00:23:20,730
to confirm your diagnosis
and provide information

416
00:23:20,730 --> 00:23:22,500
on recurrence risk?

417
00:23:22,500 --> 00:23:25,083
Single gene sequencing of MECP2,

418
00:23:25,950 --> 00:23:29,190
karyotype, chromosome microarray,

419
00:23:29,190 --> 00:23:30,513
or exome sequencing?

420
00:23:31,590 --> 00:23:34,710
So you see, in this case you have to have

421
00:23:34,710 --> 00:23:38,940
some idea of what kind of
disorder you're looking for

422
00:23:38,940 --> 00:23:43,940
and what type of genetic
variation you would expect

423
00:23:44,370 --> 00:23:48,210
to find, type or types, in that disorder.

424
00:23:48,210 --> 00:23:52,470
In this case, we're looking at a case

425
00:23:52,470 --> 00:23:56,070
of Down syndrome, trisomy 21.

426
00:23:56,070 --> 00:23:58,113
And the answer is-

427
00:23:59,190 --> 00:24:00,543
Going backwards.

428
00:24:03,390 --> 00:24:07,320
Is not A, because in single
gene sequencing of MECP2

429
00:24:07,320 --> 00:24:09,313
won't confirm Down syndrome.

430
00:24:09,313 --> 00:24:11,490
A karyotype would be a really great choice

431
00:24:11,490 --> 00:24:13,893
because it is good at
picking up aneuploidy,

432
00:24:14,730 --> 00:24:17,523
and that's what you're
expecting in Down syndrome.

433
00:24:18,510 --> 00:24:21,810
A chromosome microarray is an okay choice.

434
00:24:21,810 --> 00:24:23,430
It would pick up Down syndrome,

435
00:24:23,430 --> 00:24:26,970
it would come back with
a report of Trisomy 21,

436
00:24:26,970 --> 00:24:31,380
but it is overkill if you're
really suspecting Down syndrome

437
00:24:31,380 --> 00:24:32,433
in this child.

438
00:24:33,360 --> 00:24:36,330
Exome sequencing isn't a good choice

439
00:24:36,330 --> 00:24:38,970
because exome sequencing
is not that sensitive

440
00:24:38,970 --> 00:24:41,400
to copy number variations.

441
00:24:41,400 --> 00:24:43,080
In this case, it might really tell you

442
00:24:43,080 --> 00:24:44,700
that Down syndrome is present,

443
00:24:44,700 --> 00:24:46,890
but exome sequencing is really designed

444
00:24:46,890 --> 00:24:51,890
to pick up variations in
the DNA sequence itself,

445
00:24:52,290 --> 00:24:54,153
not variations in the copy number.

446
00:24:57,390 --> 00:24:59,430
Okay, so here's another little quiz.

447
00:24:59,430 --> 00:25:01,170
What disorder has tall statures,

448
00:25:01,170 --> 00:25:03,330
small testes, delayed puberty,

449
00:25:03,330 --> 00:25:06,120
infertility, and gynecomastia?

450
00:25:06,120 --> 00:25:08,373
That is a disorder of copy number.

451
00:25:12,000 --> 00:25:14,493
How about Klinefelter syndrome, XXY?

452
00:25:17,010 --> 00:25:19,440
All right, so karyotypes
are good for aneuploidy,

453
00:25:19,440 --> 00:25:21,660
entire chromosome is
missing or duplicated.

454
00:25:21,660 --> 00:25:24,860
The most common ones
are Trisomy 21, 18, 13,

455
00:25:24,860 --> 00:25:26,730
Monosomy X, or Turner syndrome,

456
00:25:26,730 --> 00:25:28,143
and Klinefelter syndrome.

457
00:25:29,220 --> 00:25:31,170
Large deletions and duplications,

458
00:25:31,170 --> 00:25:32,370
such as you might see in

459
00:25:32,370 --> 00:25:35,880
a classical cri-du-chat syndrome, 5p-.

460
00:25:35,880 --> 00:25:38,100
If you haven't heard of cri-du-chat,

461
00:25:38,100 --> 00:25:40,260
walk into a big newborn nursery

462
00:25:40,260 --> 00:25:43,710
and listen for the baby who's tiny,

463
00:25:43,710 --> 00:25:45,663
who's cry sounds like a cat.

464
00:25:47,010 --> 00:25:49,890
Translocations and rearrangements,

465
00:25:49,890 --> 00:25:51,660
even when they're balanced,

466
00:25:51,660 --> 00:25:53,820
can be seen in karyotypes.

467
00:25:53,820 --> 00:25:56,970
And the balanced ones can predispose

468
00:25:56,970 --> 00:26:00,960
to unbalanced offspring
with copy number variations.

469
00:26:00,960 --> 00:26:03,720
Those will not be detected by technologies

470
00:26:03,720 --> 00:26:06,393
that look only for copy number variations.

471
00:26:07,560 --> 00:26:09,900
So let's talk about those technologies.

472
00:26:09,900 --> 00:26:13,320
The chromosome microarray, or CMA,

473
00:26:13,320 --> 00:26:16,020
which uses a technology

474
00:26:16,020 --> 00:26:19,890
called comparative genomic hybridization

475
00:26:19,890 --> 00:26:23,730
or array comparative
genomic hybridization.

476
00:26:23,730 --> 00:26:25,500
But CMA or chromosome microarray

477
00:26:25,500 --> 00:26:27,990
is much easier to say and it indicates

478
00:26:27,990 --> 00:26:30,870
that we're looking at the chromosome.

479
00:26:30,870 --> 00:26:34,380
So it's useful for looking
for copy number variants,

480
00:26:34,380 --> 00:26:38,670
deletions, duplications,
triplication, etc.

481
00:26:38,670 --> 00:26:40,860
And it has a higher
resolution than a karyotype,

482
00:26:40,860 --> 00:26:43,680
meaning we can find smaller deletions,

483
00:26:43,680 --> 00:26:46,413
duplications than we can with a karyotype.

484
00:26:48,029 --> 00:26:50,070
A variant on the chromosome microarray

485
00:26:50,070 --> 00:26:55,070
is a SNP array, which also has probes

486
00:26:55,110 --> 00:26:59,430
that will detect normal sequence variants.

487
00:26:59,430 --> 00:27:00,750
And as a result,

488
00:27:00,750 --> 00:27:04,620
show you when there are
regions of the genome

489
00:27:04,620 --> 00:27:09,090
where there is only one pattern

490
00:27:09,090 --> 00:27:13,590
of polymorphism in an individual.

491
00:27:13,590 --> 00:27:15,900
And those are regions of homozygosity.

492
00:27:15,900 --> 00:27:20,370
They point to either loss of a copy,

493
00:27:20,370 --> 00:27:22,980
but you can tell that on
the chromosome microarray.

494
00:27:22,980 --> 00:27:25,380
So if it's called a
region of homozygosity,

495
00:27:25,380 --> 00:27:27,990
it's not a copy number variation,

496
00:27:27,990 --> 00:27:32,990
it is a region which is
predicted to be inherited

497
00:27:34,800 --> 00:27:36,483
from a common ancestor.

498
00:27:37,560 --> 00:27:39,720
Small regions of homozygosity

499
00:27:39,720 --> 00:27:41,610
and small numbers of homo percentages,

500
00:27:41,610 --> 00:27:43,623
homozygosity across the genome,

501
00:27:44,820 --> 00:27:48,300
are fairly common,

502
00:27:48,300 --> 00:27:52,500
especially in regions where
people don't move around a lot.

503
00:27:52,500 --> 00:27:56,340
If you detect large
percentages of homozygosity

504
00:27:56,340 --> 00:27:58,440
in the genome, you suspect some degree

505
00:27:58,440 --> 00:28:02,343
of consanguinity or close
relatedness of the parents.

506
00:28:04,170 --> 00:28:06,240
Chromosome microarray is not sensitive

507
00:28:06,240 --> 00:28:07,950
for balanced translocations,

508
00:28:07,950 --> 00:28:10,350
no copy number variation.

509
00:28:10,350 --> 00:28:12,750
For simple inversions, no
copy number variations.

510
00:28:12,750 --> 00:28:14,910
And for small CNVs,

511
00:28:14,910 --> 00:28:17,883
say on the order of an exome or smaller,

512
00:28:18,960 --> 00:28:22,860
because it depends on having two

513
00:28:22,860 --> 00:28:26,700
or three or five contiguous probes

514
00:28:26,700 --> 00:28:28,743
that are in line with each other,

515
00:28:29,670 --> 00:28:33,480
showing the signal for a
deletion or duplication

516
00:28:33,480 --> 00:28:35,160
at the same time.

517
00:28:35,160 --> 00:28:37,560
So, I have two little pictures
over here on the right.

518
00:28:37,560 --> 00:28:42,360
One is of a person with
visual impairment using a cane

519
00:28:42,360 --> 00:28:47,360
to sample his environment
in a selective way.

520
00:28:49,170 --> 00:28:51,090
So the cane allows this person

521
00:28:51,090 --> 00:28:55,500
to see not every single surface

522
00:28:55,500 --> 00:28:58,050
in every single part of the sidewalk,

523
00:28:58,050 --> 00:29:01,110
but selections along that way.

524
00:29:01,110 --> 00:29:03,570
And that's essentially what
a chromosome microarray does.

525
00:29:03,570 --> 00:29:05,900
It has anywhere from 180,000

526
00:29:05,900 --> 00:29:10,900
to 800,000 small oligonucleotide probes

527
00:29:11,190 --> 00:29:15,450
that are designed to
hybridize all over the genome.

528
00:29:15,450 --> 00:29:20,450
And the technique tells
us whether they hybridize

529
00:29:20,700 --> 00:29:25,230
at the same rate more often or less often

530
00:29:25,230 --> 00:29:27,663
than a reference DNA.

531
00:29:28,770 --> 00:29:30,360
And so, in the picture here,

532
00:29:30,360 --> 00:29:34,170
this person has what
looks like a duplication,

533
00:29:34,170 --> 00:29:38,700
or 1.5 times the signal in fluorescence

534
00:29:38,700 --> 00:29:43,700
in this red segment from a
large number of probes in there.

535
00:29:43,710 --> 00:29:45,300
And this is 15q12,

536
00:29:45,300 --> 00:29:48,993
so this is probably the
Prader-Willi-Angelman syndrome area.

537
00:29:52,500 --> 00:29:53,587
Okay, here's a clinical scenario.

538
00:29:53,587 --> 00:29:57,570
You see a 24 month old
for a well child visit.

539
00:29:57,570 --> 00:30:00,120
She started walking at 18 months,

540
00:30:00,120 --> 00:30:03,990
most kids start walking
around 12 to 14 months,

541
00:30:03,990 --> 00:30:06,060
and she has not had her first word yet.

542
00:30:06,060 --> 00:30:08,190
Again, around 12 to 14 months

543
00:30:08,190 --> 00:30:10,440
is when you should expect that.

544
00:30:10,440 --> 00:30:12,180
She has borderline short stature,

545
00:30:12,180 --> 00:30:13,440
a short up-turned nose,

546
00:30:13,440 --> 00:30:15,903
and possibly low-set ears.

547
00:30:17,490 --> 00:30:20,400
What are the reasonable
possibilities for next steps?

548
00:30:20,400 --> 00:30:23,520
Refer to genetics for
dysmorphology evaluation,

549
00:30:23,520 --> 00:30:25,230
get a karyotype,

550
00:30:25,230 --> 00:30:27,180
do a chromosome microarray,

551
00:30:27,180 --> 00:30:28,413
or do hearing testing.

552
00:30:30,150 --> 00:30:32,280
Hearing testing's not a bad idea.

553
00:30:32,280 --> 00:30:34,020
If she's not had any speech,

554
00:30:34,020 --> 00:30:36,390
it's possible she's not developing speech

555
00:30:36,390 --> 00:30:38,240
because she has a hearing impairment.

556
00:30:39,090 --> 00:30:41,640
Referring to genetics for
dysmorphology evaluation

557
00:30:41,640 --> 00:30:44,610
seems reasonable because
she has some soft features

558
00:30:44,610 --> 00:30:46,410
and is developmentally delayed,

559
00:30:46,410 --> 00:30:48,870
and maybe those two things go together.

560
00:30:48,870 --> 00:30:50,770
And someone will recognize a syndrome.

561
00:30:51,832 --> 00:30:55,470
A karyotype probably isn't
gonna tell you very much.

562
00:30:55,470 --> 00:30:57,660
The yield on karyotypes for a patient

563
00:30:57,660 --> 00:31:00,860
with sort of relatively
subtle presentation like this

564
00:31:00,860 --> 00:31:02,640
is not very high.

565
00:31:02,640 --> 00:31:05,190
And you're not suspecting an aneuploidy

566
00:31:05,190 --> 00:31:08,313
because the features don't add
up to an aneuploidy disorder.

567
00:31:09,240 --> 00:31:12,420
Chromosome microarray turns
out to be a good choice too,

568
00:31:12,420 --> 00:31:14,520
because we know from experience

569
00:31:14,520 --> 00:31:17,760
that in the context of developmental delay

570
00:31:17,760 --> 00:31:19,803
not due to a single gene syndrome,

571
00:31:22,549 --> 00:31:25,770
the chromosome microarray will be positive

572
00:31:25,770 --> 00:31:28,743
in somewhere between
15 and 30% of patients.

573
00:31:32,430 --> 00:31:36,970
So, let's switch from the
copy number variation approach

574
00:31:38,880 --> 00:31:43,110
to thinking about disorders
caused by sequence variation.

575
00:31:43,110 --> 00:31:47,193
So, changes in the actual genetic code.

576
00:31:48,270 --> 00:31:50,160
So here's one.

577
00:31:50,160 --> 00:31:54,330
An individual with a copper-colored ring

578
00:31:54,330 --> 00:31:56,400
around the edge of the cornea,

579
00:31:56,400 --> 00:31:59,250
that's an almost pathognomonic sign

580
00:31:59,250 --> 00:32:03,810
for Wilson's disease, a
copper storage disorder

581
00:32:03,810 --> 00:32:07,443
that is a progressive
neurodegenerative disorder as well.

582
00:32:10,230 --> 00:32:13,230
Here's a disorder with thick, sticky mucus

583
00:32:13,230 --> 00:32:16,830
that blocks the airways and also blocking

584
00:32:16,830 --> 00:32:18,480
the pancreatic and bile ducts

585
00:32:18,480 --> 00:32:21,150
and causes pancreatic insufficiency

586
00:32:21,150 --> 00:32:24,090
and eventually type 1 diabetes.

587
00:32:24,090 --> 00:32:25,040
That would be what?

588
00:32:26,250 --> 00:32:28,743
Yes, cystic fibrosis.

589
00:32:30,750 --> 00:32:32,920
Here's a group of disorders,

590
00:32:32,920 --> 00:32:34,230
there's a weakened heart muscle

591
00:32:34,230 --> 00:32:37,503
and an enlarged ventricle
and a thin ventricular wall.

592
00:32:38,340 --> 00:32:41,613
That would be dilated cardiomyopathy.

593
00:32:43,620 --> 00:32:48,620
And what about a disorder
that predisposes to cancer?

594
00:32:49,740 --> 00:32:53,880
In this case, familial
adenomatous polyposis.

595
00:32:53,880 --> 00:32:58,690
This is a histology section
of a classical FAP polyp

596
00:33:00,660 --> 00:33:03,543
removed from a colon
of an affected person.

597
00:33:04,666 --> 00:33:06,120
A single polyp, not a big deal.

598
00:33:06,120 --> 00:33:07,533
Lots of polyps, big deal.

599
00:33:09,600 --> 00:33:12,300
All right, and what
about the technologies?

600
00:33:12,300 --> 00:33:14,970
Sanger sequencing I mentioned earlier.

601
00:33:14,970 --> 00:33:16,500
It's considered the gold standard,

602
00:33:16,500 --> 00:33:18,240
although that's rapidly being replaced

603
00:33:18,240 --> 00:33:21,150
by next-generation
sequencing as the quality

604
00:33:21,150 --> 00:33:26,150
and our understanding of how
the sequencing technology

605
00:33:27,840 --> 00:33:32,700
can work and how it can fail improves.

606
00:33:32,700 --> 00:33:37,700
And so, Sanger sequencing is
still considered the way to go.

607
00:33:39,000 --> 00:33:40,560
In the early part of my career,

608
00:33:40,560 --> 00:33:45,560
I used Sanger sequencing that
was quite manual process.

609
00:33:45,960 --> 00:33:49,200
The picture on the left
shows an autoradiogram,

610
00:33:49,200 --> 00:33:51,450
that's a piece of X-ray film

611
00:33:51,450 --> 00:33:53,970
on which I've laid a dried gel

612
00:33:53,970 --> 00:33:57,570
on which I had run sequencing reactions

613
00:33:57,570 --> 00:34:02,570
using radioactive P32
labeled DNA in four lanes.

614
00:34:04,050 --> 00:34:07,200
One lane for A, one lane for T,

615
00:34:07,200 --> 00:34:09,750
one lane for G, and one lane for C.

616
00:34:09,750 --> 00:34:14,343
And you simply sort of read
down from the top down.

617
00:34:16,290 --> 00:34:17,280
And in this case,

618
00:34:17,280 --> 00:34:20,490
you see a T-A-G-C pattern,

619
00:34:20,490 --> 00:34:22,983
as shown in that picture.

620
00:34:23,850 --> 00:34:26,220
On the right is a more modern form

621
00:34:26,220 --> 00:34:28,440
of Sanger sequencing or
a capillary sequencing,

622
00:34:28,440 --> 00:34:30,720
where instead of using radioactivity,

623
00:34:30,720 --> 00:34:35,163
there are fluorescent tags that are used.

624
00:34:36,000 --> 00:34:37,530
And those are run on

625
00:34:37,530 --> 00:34:42,210
a capillary electrophoresis
sequencing system.

626
00:34:42,210 --> 00:34:43,890
And at the bottom of the capillary,

627
00:34:43,890 --> 00:34:47,550
as the DNA fragments fly out,

628
00:34:47,550 --> 00:34:49,350
their fluorescence is measured

629
00:34:49,350 --> 00:34:50,490
and you get this tracing,

630
00:34:50,490 --> 00:34:53,040
and then you can read the
DNA sequence off of that.

631
00:34:54,420 --> 00:34:56,610
It's a relatively
low-throughput technology,

632
00:34:56,610 --> 00:34:58,410
it is highly reliable,

633
00:34:58,410 --> 00:35:01,260
and has a relatively high cost per base.

634
00:35:01,260 --> 00:35:04,710
So Sanger sequencing would
never have got us through

635
00:35:04,710 --> 00:35:07,560
the entire human genome project,

636
00:35:07,560 --> 00:35:09,870
although that's what we started with

637
00:35:09,870 --> 00:35:11,163
when the project began.

638
00:35:12,863 --> 00:35:16,050
Sanger sequencing is still used mostly

639
00:35:16,050 --> 00:35:19,650
for targeted mutation
testing of single exons,

640
00:35:19,650 --> 00:35:21,810
single gene, or sequential gene testing.

641
00:35:21,810 --> 00:35:23,250
So I'm gonna test this gene first,

642
00:35:23,250 --> 00:35:24,083
if that's negative,

643
00:35:24,083 --> 00:35:26,700
then I'm gonna test the
next most likely gene,

644
00:35:26,700 --> 00:35:27,600
sequence that one,

645
00:35:27,600 --> 00:35:29,070
and then if that's negative,

646
00:35:29,070 --> 00:35:31,070
I'll sequence the next most likely gene.

647
00:35:31,950 --> 00:35:32,942
Small gene panels.

648
00:35:32,942 --> 00:35:36,630
Two or three genes,
depending on their size,

649
00:35:36,630 --> 00:35:39,060
can be put into a panel

650
00:35:39,060 --> 00:35:41,673
and sequenced efficiently with Sanger.

651
00:35:43,200 --> 00:35:46,740
Sanger is also used for
sequencing parts of the genome

652
00:35:46,740 --> 00:35:50,760
that next-generation
sequencing is not very good at.

653
00:35:50,760 --> 00:35:54,960
So, filling in for
next-generation sequencing gaps

654
00:35:54,960 --> 00:35:58,290
or low-depth regions.

655
00:35:58,290 --> 00:35:59,940
And finally, choose for confirmation

656
00:35:59,940 --> 00:36:02,250
of important variants
detected by other methods

657
00:36:02,250 --> 00:36:05,283
such as next-generation sequencing.

658
00:36:06,660 --> 00:36:09,750
So what about next-generation
sequencing, or NGS?

659
00:36:09,750 --> 00:36:11,460
As I mentioned, it's short read,

660
00:36:11,460 --> 00:36:14,280
150 to 200 bases per read.

661
00:36:14,280 --> 00:36:15,360
It's massively parallel,

662
00:36:15,360 --> 00:36:17,610
so this is going on in a very micro-scale.

663
00:36:17,610 --> 00:36:18,900
As you see in the center picture,

664
00:36:18,900 --> 00:36:21,210
there's what's called a flow cell

665
00:36:21,210 --> 00:36:23,970
and there are thousands
and thousands and thousands

666
00:36:23,970 --> 00:36:27,210
of sequencing reactions going on

667
00:36:27,210 --> 00:36:29,823
in that one little slide apparatus.

668
00:36:31,110 --> 00:36:33,243
It is really good for high throughput,

669
00:36:34,110 --> 00:36:36,000
for lowest cost per base,

670
00:36:36,000 --> 00:36:38,610
for high general reliability,

671
00:36:38,610 --> 00:36:40,860
and it has, at present,

672
00:36:40,860 --> 00:36:43,620
the highest clinical market penetration

673
00:36:43,620 --> 00:36:47,887
in both research and clinical
sequencing laboratories.

674
00:36:49,860 --> 00:36:53,220
It has an advantage in
that it's pretty good

675
00:36:53,220 --> 00:36:57,930
at detecting mosaicism if
you are sequencing depth

676
00:36:57,930 --> 00:37:01,023
and your bioinformatics
pathway are tuned for that.

677
00:37:02,190 --> 00:37:03,750
All right?

678
00:37:03,750 --> 00:37:05,040
So in the left-hand picture,

679
00:37:05,040 --> 00:37:07,410
there is a picture of an
Illumina MySeq machine.

680
00:37:07,410 --> 00:37:11,310
We have two of these
in our laboratory here,

681
00:37:11,310 --> 00:37:14,070
along with a NextSeq machine

682
00:37:14,070 --> 00:37:18,930
which has several-fold increased capacity,

683
00:37:18,930 --> 00:37:20,643
sequencing capacity over that.

684
00:37:22,020 --> 00:37:24,030
That pales in comparison

685
00:37:24,030 --> 00:37:27,030
to the most recent Illumina
sequencing machine,

686
00:37:27,030 --> 00:37:32,030
which is a NovaSeq which
can sequence huge amounts

687
00:37:32,490 --> 00:37:35,193
of DNA simultaneously.

688
00:37:38,100 --> 00:37:40,020
All right, Gene Panel Sequencing.

689
00:37:40,020 --> 00:37:41,790
So I've mentioned that a few times.

690
00:37:41,790 --> 00:37:42,720
What does that really mean?

691
00:37:42,720 --> 00:37:44,400
So with Sanger sequencing,

692
00:37:44,400 --> 00:37:47,193
maybe 1, 2, 3, 4, 5 genes.

693
00:37:48,180 --> 00:37:51,090
It is guaranteed coverage of exons

694
00:37:51,090 --> 00:37:52,710
and their flanking sequence.

695
00:37:52,710 --> 00:37:57,510
So you have high confidence

696
00:37:57,510 --> 00:37:59,730
that the entire region you were targeting

697
00:37:59,730 --> 00:38:01,233
is being sequenced well.

698
00:38:02,970 --> 00:38:06,210
Next generation sequencing
can sequence anywhere

699
00:38:06,210 --> 00:38:09,930
from 2 to 100's of genes at once.

700
00:38:09,930 --> 00:38:13,440
And the cost of adding additional genes

701
00:38:13,440 --> 00:38:17,640
to that next generation
sequencing is not very high,

702
00:38:17,640 --> 00:38:20,370
although you need to decide in advance

703
00:38:20,370 --> 00:38:24,303
which groups of genes you
want to sequence together.

704
00:38:25,710 --> 00:38:27,120
Next generation sequencing often

705
00:38:27,120 --> 00:38:29,760
has some low-coverage areas,

706
00:38:29,760 --> 00:38:32,520
particularly in the first exons

707
00:38:32,520 --> 00:38:34,050
and in other GC-rich regions.

708
00:38:34,050 --> 00:38:35,910
So first exons tend to be GC-rich

709
00:38:35,910 --> 00:38:39,390
because they often have
regulatory elements

710
00:38:39,390 --> 00:38:43,150
in them and are areas
where methylation occurs

711
00:38:44,010 --> 00:38:47,310
that help regulate the
gene turning on and off.

712
00:38:47,310 --> 00:38:51,210
Those GC-rich regions
are substantially harder

713
00:38:51,210 --> 00:38:54,120
for next generation
sequencing technologies

714
00:38:54,120 --> 00:38:55,473
to sequence through,

715
00:38:56,340 --> 00:39:00,250
as are sequences with long
repeats of the same base

716
00:39:01,260 --> 00:39:06,130
or lots of repeats of
small numbers of bases.

717
00:39:09,630 --> 00:39:14,310
All right, what are the uses
for next-generation sequencing?

718
00:39:14,310 --> 00:39:16,050
The gene panel, I mentioned.

719
00:39:16,050 --> 00:39:17,760
Multiple genes associated with disorders

720
00:39:17,760 --> 00:39:19,500
with similar presentation.

721
00:39:19,500 --> 00:39:23,703
For example, cardiomyopathy,
hereditary neuropathy,

722
00:39:25,170 --> 00:39:28,620
early infantile epileptic encephalopathy,

723
00:39:28,620 --> 00:39:32,790
and tumor somatic mutations for therapy,

724
00:39:32,790 --> 00:39:37,790
as we talked about in the cancer module.

725
00:39:37,980 --> 00:39:39,660
So what all these have in panel,

726
00:39:39,660 --> 00:39:44,100
the reasons I'm sort of
giving you a landscape

727
00:39:44,100 --> 00:39:46,560
of this is for you to get the idea

728
00:39:46,560 --> 00:39:49,740
that a gene panel is
helpful when you don't have

729
00:39:49,740 --> 00:39:53,520
other tools to help you
differentiate down to the level

730
00:39:53,520 --> 00:39:57,750
of a single gene what is most likely

731
00:39:57,750 --> 00:40:01,830
to be changed and to allow you

732
00:40:01,830 --> 00:40:04,740
to do targeted genetic testing.

733
00:40:04,740 --> 00:40:06,300
So when you can't quite target it,

734
00:40:06,300 --> 00:40:07,590
but you know what the phenotype is,

735
00:40:07,590 --> 00:40:11,943
you can group the genes and
target those in a gene panel.

736
00:40:13,410 --> 00:40:15,300
Clinical Scenario.

737
00:40:15,300 --> 00:40:19,110
Your patient has an early
onset cardiomyopathy.

738
00:40:19,110 --> 00:40:21,330
Her father and her father's brother,

739
00:40:21,330 --> 00:40:22,710
her paternal uncle,

740
00:40:22,710 --> 00:40:25,650
and her brother also have cardiomyopathy,

741
00:40:25,650 --> 00:40:28,440
but some of them have a
dilated cardiomyopathy,

742
00:40:28,440 --> 00:40:30,933
and others have a
hypertrophic cardiomyopathy.

743
00:40:32,910 --> 00:40:35,340
What rationales support
doing genetic testing

744
00:40:35,340 --> 00:40:36,213
in your patient?

745
00:40:38,250 --> 00:40:40,740
A, she has a 21 year
old daughter who wants

746
00:40:40,740 --> 00:40:42,630
to know whether she's at risk,

747
00:40:42,630 --> 00:40:44,970
and whether she should use
reproductive technology

748
00:40:44,970 --> 00:40:47,490
to avoid passing on a disease

749
00:40:47,490 --> 00:40:52,020
like the cardiomyopathies in her family.

750
00:40:52,020 --> 00:40:54,480
B, you're unable to differentiate

751
00:40:54,480 --> 00:40:57,240
which of the molecular
genetically distinct forms

752
00:40:57,240 --> 00:40:59,580
of cardiomyopathy your patient might have.

753
00:40:59,580 --> 00:41:02,700
So you can not formulate
the best treatment plan

754
00:41:02,700 --> 00:41:06,480
when it matters what type of
cardiomyopathy is present.

755
00:41:06,480 --> 00:41:08,790
The prognosis may be different.

756
00:41:08,790 --> 00:41:10,740
The response to medications.

757
00:41:10,740 --> 00:41:15,740
The urgency for finding a
transplantation transplant donor,

758
00:41:16,110 --> 00:41:17,850
for example, may all differ depending

759
00:41:17,850 --> 00:41:19,413
on the type of cardiomyopathy.

760
00:41:20,880 --> 00:41:23,673
Her affected paternal uncle
lacks health insurance.

761
00:41:24,870 --> 00:41:27,090
D, you would use a different
pacemaker depending

762
00:41:27,090 --> 00:41:28,563
on what mutation she has.

763
00:41:29,790 --> 00:41:32,853
So the true answers here are A,

764
00:41:34,410 --> 00:41:37,260
we're talking about reproductive risks.

765
00:41:37,260 --> 00:41:42,260
And B, refining the
prognosis and predicting

766
00:41:43,620 --> 00:41:45,630
which medical approaches are going

767
00:41:45,630 --> 00:41:47,703
to be most effective for this patient.

768
00:41:51,900 --> 00:41:56,900
All right, exome sequencing
compared to genome sequencing.

769
00:41:58,710 --> 00:42:00,540
We're gonna start first by comparing

770
00:42:00,540 --> 00:42:03,870
the entire exome to the clinical exome.

771
00:42:03,870 --> 00:42:06,903
So the entire exome is about 20,000 genes.

772
00:42:08,400 --> 00:42:11,040
It is coding and non-coding exons,

773
00:42:11,040 --> 00:42:12,870
so just the exons.

774
00:42:12,870 --> 00:42:14,883
And all the non-exons, the introns,

775
00:42:15,842 --> 00:42:18,360
the DNA that's between genes,

776
00:42:18,360 --> 00:42:21,063
the regulatory regions and
so forth are not included.

777
00:42:22,560 --> 00:42:26,820
The clinical exome is about 6,000 genes

778
00:42:26,820 --> 00:42:30,030
that are known to be
associated with disease.

779
00:42:30,030 --> 00:42:31,770
Now, mind you, that the
number of genes associated

780
00:42:31,770 --> 00:42:33,900
with the disease keeps
increasing every month

781
00:42:33,900 --> 00:42:35,940
so it's hard to keep up with that,

782
00:42:35,940 --> 00:42:38,850
but the clinical exome basically says,

783
00:42:38,850 --> 00:42:41,610
well, there's a bunch of
genes we know are out there,

784
00:42:41,610 --> 00:42:44,820
but we haven't associated
them with diseases yet

785
00:42:44,820 --> 00:42:46,920
so sequencing them doesn't give us

786
00:42:46,920 --> 00:42:50,430
any clinically important information.

787
00:42:50,430 --> 00:42:53,100
So you may find that the clinical exome

788
00:42:53,100 --> 00:42:55,290
is what you're going to get out

789
00:42:55,290 --> 00:42:57,933
of a commercial testing laboratory.

790
00:42:59,880 --> 00:43:03,840
Furthermore, when you look
at the clinical exome,

791
00:43:03,840 --> 00:43:08,370
you always are asked about
what is the clinical phenotype.

792
00:43:08,370 --> 00:43:12,360
And in fact, rather than
looking at all 6,000 genes,

793
00:43:12,360 --> 00:43:14,640
there's a computer that
looks at them for things

794
00:43:14,640 --> 00:43:15,960
that might be suspicious.

795
00:43:15,960 --> 00:43:17,283
But for the most part,

796
00:43:18,360 --> 00:43:20,430
based on the clinical presentation

797
00:43:20,430 --> 00:43:22,440
that you outline in the paperwork

798
00:43:22,440 --> 00:43:25,380
that you submit with the test,

799
00:43:25,380 --> 00:43:28,020
the laboratory will look at a subset

800
00:43:28,020 --> 00:43:30,060
of the clinical exome,

801
00:43:30,060 --> 00:43:33,240
that is the genes that
are known to overlap

802
00:43:33,240 --> 00:43:36,660
with the clinical phenotype
that you have described.

803
00:43:36,660 --> 00:43:38,580
So it's really, really important

804
00:43:38,580 --> 00:43:41,580
that you fully describe
the clinical phenotype well

805
00:43:41,580 --> 00:43:44,550
when you order a clinical exome test

806
00:43:44,550 --> 00:43:47,193
because otherwise,
you're gonna get garbage.

807
00:43:49,170 --> 00:43:52,620
The other tweak on the exome,

808
00:43:52,620 --> 00:43:53,970
which is often done,

809
00:43:53,970 --> 00:43:58,970
is to also sequence the
exome of both parents.

810
00:43:59,520 --> 00:44:02,070
And the reason for doing this is twofold.

811
00:44:02,070 --> 00:44:05,620
First, if there is a new genetic change

812
00:44:07,350 --> 00:44:09,870
from one generation to the next,

813
00:44:09,870 --> 00:44:12,840
so the patient has a
genetic change in a gene

814
00:44:12,840 --> 00:44:15,300
which neither of their parents has,

815
00:44:15,300 --> 00:44:16,830
that would be a de nova mutation

816
00:44:16,830 --> 00:44:18,750
and that's one of those levels of evidence

817
00:44:18,750 --> 00:44:22,050
that we talked about
that pushes you toward

818
00:44:22,050 --> 00:44:24,393
that genetic variation being pathogenic.

819
00:44:26,370 --> 00:44:30,630
The second reason is because
if you find two variations

820
00:44:30,630 --> 00:44:33,480
in a gene that you know to be associated

821
00:44:33,480 --> 00:44:34,920
with recessive disease,

822
00:44:34,920 --> 00:44:36,780
you don't know whether
they're on the same copy.

823
00:44:36,780 --> 00:44:39,000
In other words, those two genetic changes

824
00:44:39,000 --> 00:44:42,480
both came from mom or both came from dad

825
00:44:42,480 --> 00:44:45,030
or one of them came from mom
and one of them came from dad.

826
00:44:45,030 --> 00:44:47,130
The latter is what you would see

827
00:44:47,130 --> 00:44:49,920
when both copies of the gene are disrupted

828
00:44:49,920 --> 00:44:53,940
and you are expected to
have clinical disease.

829
00:44:53,940 --> 00:44:57,900
So having that so-called trio sequencing,

830
00:44:57,900 --> 00:45:01,560
the patient, the mother, and
the father makes up the trio,

831
00:45:01,560 --> 00:45:06,420
helps those who are
interpreting your exome sequence

832
00:45:06,420 --> 00:45:08,913
do a much better job
in the interpretation.

833
00:45:11,160 --> 00:45:14,430
So the clinical exome is
then mostly coding exons

834
00:45:14,430 --> 00:45:17,490
plus 10 or 15 bases into
the flanking introns.

835
00:45:17,490 --> 00:45:21,540
Now why do they do about
those flanking sequences

836
00:45:21,540 --> 00:45:24,180
just into the introns?

837
00:45:24,180 --> 00:45:26,700
That's because sequence variations there

838
00:45:26,700 --> 00:45:31,700
can disrupt splicing of the
RNA transcript into the mRNA,

839
00:45:33,660 --> 00:45:36,390
and then you have disrupted exons

840
00:45:36,390 --> 00:45:38,280
in your messenger RNA and the protein

841
00:45:38,280 --> 00:45:39,603
will come out different.

842
00:45:42,180 --> 00:45:43,560
All right, a clinical scenario.

843
00:45:43,560 --> 00:45:45,510
Your patient has multi-system disease,

844
00:45:45,510 --> 00:45:47,580
all non-genetic testing has failed

845
00:45:47,580 --> 00:45:51,330
to come up with a unifying
underlying process to explain it,

846
00:45:51,330 --> 00:45:53,700
and the specialists involved

847
00:45:53,700 --> 00:45:55,740
are uneasy giving advanced treatment

848
00:45:55,740 --> 00:45:58,053
since they aren't sure what the cause is.

849
00:45:59,100 --> 00:46:02,460
So this is something that
comes up fairly frequently

850
00:46:02,460 --> 00:46:05,500
in genetics and probably not infrequently

851
00:46:06,603 --> 00:46:08,223
in primary care as well.

852
00:46:09,120 --> 00:46:14,070
And it's just a picture
where it's fairly clear

853
00:46:14,070 --> 00:46:16,170
you've tried all the usual avenues,

854
00:46:16,170 --> 00:46:19,350
you've consulted all
the usual specialists,

855
00:46:19,350 --> 00:46:23,190
and it's still you have sort
of descriptive diagnoses,

856
00:46:23,190 --> 00:46:25,230
but you've really never come up

857
00:46:25,230 --> 00:46:29,343
with an underlying process
that is explaining all of them.

858
00:46:31,320 --> 00:46:34,680
So, what rationales
support doing exome testing

859
00:46:34,680 --> 00:46:36,180
in your patient?

860
00:46:36,180 --> 00:46:38,970
A, continued reliance
on traditional testing

861
00:46:38,970 --> 00:46:40,620
and repeat specialist visits

862
00:46:40,620 --> 00:46:42,420
will only consume more healthcare dollars

863
00:46:42,420 --> 00:46:44,223
without advancing her management.

864
00:46:45,450 --> 00:46:48,030
B, she has a 3% to 5%
chance of having more

865
00:46:48,030 --> 00:46:49,950
than one rare disorder,

866
00:46:49,950 --> 00:46:51,450
explaining the difficulty

867
00:46:51,450 --> 00:46:54,840
in understanding her complex phenotype.

868
00:46:54,840 --> 00:46:57,300
C, she can have an extremely rare disorder

869
00:46:57,300 --> 00:47:00,030
that will never be diagnosed clinically.

870
00:47:00,030 --> 00:47:02,700
And D, there are specific
treatments available

871
00:47:02,700 --> 00:47:04,953
for almost all genetic disorders.

872
00:47:09,210 --> 00:47:11,133
So which rationales would you pick?

873
00:47:12,000 --> 00:47:13,353
So I would pick A,

874
00:47:14,340 --> 00:47:17,160
that you've kind of exhausted
what traditional testing

875
00:47:17,160 --> 00:47:19,443
and specialist evaluation can do,

876
00:47:20,760 --> 00:47:23,460
and just doing more of the same

877
00:47:23,460 --> 00:47:25,383
isn't going to get you any further.

878
00:47:27,120 --> 00:47:28,800
Interestingly, in the last few years,

879
00:47:28,800 --> 00:47:31,110
we've recognized that B is also true.

880
00:47:31,110 --> 00:47:33,840
So one of the reasons we
have a hard time recognizing

881
00:47:33,840 --> 00:47:36,150
what's going on in a complex patient

882
00:47:36,150 --> 00:47:38,040
is that they have more than one disease

883
00:47:38,040 --> 00:47:39,783
going on simultaneously.

884
00:47:41,970 --> 00:47:43,950
And both of those diseases can be rare,

885
00:47:43,950 --> 00:47:46,560
and our chances of figuring that out

886
00:47:46,560 --> 00:47:51,560
and teasing out those different
phenotypes is pretty low.

887
00:47:54,330 --> 00:47:55,890
She could have an extremely rare disorder

888
00:47:55,890 --> 00:47:57,510
that will never be diagnosed clinically.

889
00:47:57,510 --> 00:47:58,593
That's also true.

890
00:48:00,150 --> 00:48:01,830
D, not so much.

891
00:48:01,830 --> 00:48:03,780
There are not specific
treatments available

892
00:48:03,780 --> 00:48:05,643
for almost all genetic disorders.

893
00:48:07,620 --> 00:48:08,940
All right, so when do you

894
00:48:08,940 --> 00:48:11,610
wanna use next generation sequencing?

895
00:48:11,610 --> 00:48:15,510
The exome, all the exomes in genome plus

896
00:48:15,510 --> 00:48:17,640
the protein coding segments

897
00:48:17,640 --> 00:48:20,190
and those little bits of
flanking sequence next

898
00:48:20,190 --> 00:48:21,993
to the exomes in the introns.

899
00:48:25,796 --> 00:48:27,780
When the presentation is rare

900
00:48:27,780 --> 00:48:29,970
and you suspect a genetic cause,

901
00:48:29,970 --> 00:48:32,553
it's an unrecognized disorder or area.

902
00:48:33,570 --> 00:48:36,180
Other testing failed to diagnose.

903
00:48:36,180 --> 00:48:38,460
You suspect more than one disease.

904
00:48:38,460 --> 00:48:40,800
And sometimes, you just wanna
end the diagnostic odyssey.

905
00:48:40,800 --> 00:48:42,870
This has been going on for a long time,

906
00:48:42,870 --> 00:48:44,820
the patient's upset we're expending more

907
00:48:44,820 --> 00:48:46,470
and more healthcare dollars.

908
00:48:46,470 --> 00:48:50,733
And sometimes it's enormously relieving

909
00:48:52,830 --> 00:48:54,720
for the patient and their family

910
00:48:54,720 --> 00:48:56,010
to come to an answer,

911
00:48:56,010 --> 00:48:58,773
even if the answer means
there's nothing they can do.

912
00:49:01,770 --> 00:49:05,160
The whole genome is basically the exome

913
00:49:05,160 --> 00:49:07,230
plus everything else,

914
00:49:07,230 --> 00:49:11,280
and we really don't use that
much in clinical care yet.

915
00:49:11,280 --> 00:49:14,130
But as the price for
genome testing comes down,

916
00:49:14,130 --> 00:49:16,600
and as our understanding
of how to interpret

917
00:49:17,820 --> 00:49:21,850
the sequence variations
in between the axons

918
00:49:23,010 --> 00:49:25,770
and in between the genes,
we will want to be doing

919
00:49:25,770 --> 00:49:27,510
this more and more because we

920
00:49:27,510 --> 00:49:31,000
are missing structural variations

921
00:49:31,890 --> 00:49:35,010
and variations in regulatory regions

922
00:49:35,010 --> 00:49:40,010
that may explain some of
the areas where we expect

923
00:49:41,610 --> 00:49:44,250
to find something in a
gene panel or an exome,

924
00:49:44,250 --> 00:49:45,083
and we don't.

925
00:49:45,930 --> 00:49:48,570
So the whole genome is an exome
plus the non-coding regions.

926
00:49:48,570 --> 00:49:52,740
It's about 75 times larger than the exome

927
00:49:52,740 --> 00:49:57,570
and probably costs about 30 times more,

928
00:49:57,570 --> 00:50:00,030
maybe less than that, to sequence,

929
00:50:00,030 --> 00:50:02,610
because it's just that much larger.

930
00:50:02,610 --> 00:50:05,370
The potential to detect
clinically important defects

931
00:50:05,370 --> 00:50:08,580
in gene regulation is there,

932
00:50:08,580 --> 00:50:12,000
and it can be used when it's
really, really important

933
00:50:12,000 --> 00:50:14,490
to diagnose when loss of function

934
00:50:14,490 --> 00:50:16,230
and coding regions are normal

935
00:50:16,230 --> 00:50:19,413
and when you can convince
insurance to pay for it.

936
00:50:20,790 --> 00:50:24,570
I would not waste my time on
that at this point in time,

937
00:50:24,570 --> 00:50:26,670
but fast forward a couple of years,

938
00:50:26,670 --> 00:50:28,080
three years, four years,

939
00:50:28,080 --> 00:50:30,603
we may be seeing that
coming down the pike.

940
00:50:32,250 --> 00:50:35,883
Remember that when you
sequence the germline DNA,

941
00:50:36,750 --> 00:50:40,650
you are sequencing DNA
that essentially represents

942
00:50:40,650 --> 00:50:42,690
your genetic instructions.

943
00:50:42,690 --> 00:50:44,130
So when you sequence that,

944
00:50:44,130 --> 00:50:46,170
the information that you get for that

945
00:50:46,170 --> 00:50:49,650
is good for the patient's life, right?

946
00:50:49,650 --> 00:50:51,960
So it's not gonna change over time

947
00:50:51,960 --> 00:50:53,280
like other kinds of tests,

948
00:50:53,280 --> 00:50:56,880
like cholesterol levels or sodium levels,

949
00:50:56,880 --> 00:50:58,740
things that you test repeatedly.

950
00:50:58,740 --> 00:51:02,040
So once you have a really good sequence

951
00:51:02,040 --> 00:51:06,210
of your exome or, hopefully
in the future, your genome,

952
00:51:06,210 --> 00:51:08,310
that test won't have to be done again.

953
00:51:08,310 --> 00:51:12,570
So the cost of those tests
can be amortized over time

954
00:51:12,570 --> 00:51:16,110
as additional queries are
made on the information

955
00:51:16,110 --> 00:51:20,103
that was generated in the
initial sequencing test.

956
00:51:22,020 --> 00:51:26,960
Okay, so when we get a report
back from a genetic test,

957
00:51:28,140 --> 00:51:31,290
it will contain information about variants

958
00:51:31,290 --> 00:51:36,240
that are felt to be of
significance, all right?

959
00:51:36,240 --> 00:51:40,390
We have a standardized process now

960
00:51:41,310 --> 00:51:45,450
that we use to classify genetic variants

961
00:51:45,450 --> 00:51:47,763
in terms of their clinical importance.

962
00:51:48,720 --> 00:51:52,920
And that classification
assumes at the beginning

963
00:51:52,920 --> 00:51:57,570
that it's a variant of
uncertain unknown significance.

964
00:51:57,570 --> 00:52:02,570
A VUS, and some people will
call that a VUS, right?

965
00:52:03,540 --> 00:52:07,860
I call it a V-U-S, variant
of uncertain significance.

966
00:52:07,860 --> 00:52:09,810
So our classification scheme

967
00:52:09,810 --> 00:52:14,810
is based on two axis of information.

968
00:52:14,820 --> 00:52:17,640
One is pathogenicity,

969
00:52:17,640 --> 00:52:22,640
how likely is this variant
to be the pathogenic source

970
00:52:23,280 --> 00:52:27,840
of this disease, and what's
the level of evidence

971
00:52:27,840 --> 00:52:30,543
for that pathogenicity or lack thereof.

972
00:52:31,590 --> 00:52:33,873
So this creates sort of a graph,

973
00:52:35,250 --> 00:52:37,050
which we're doing not as a graph

974
00:52:37,050 --> 00:52:40,740
but in sort of stepwise bins.

975
00:52:40,740 --> 00:52:44,490
And so, as you get some information

976
00:52:44,490 --> 00:52:47,310
that this variant may be pathogenic,

977
00:52:47,310 --> 00:52:51,570
you can move it up from
VUS to likely pathogenic,

978
00:52:51,570 --> 00:52:54,330
you get more information, more evidence,

979
00:52:54,330 --> 00:52:58,899
you can move it up to a
classification of pathogenic.

980
00:52:58,899 --> 00:53:03,660
If you get evidence that it
is probably not pathogenic

981
00:53:03,660 --> 00:53:06,930
but you're not sure, you can
move it to likely benign,

982
00:53:06,930 --> 00:53:09,690
and then you can move it further,

983
00:53:09,690 --> 00:53:11,403
with more evidence, to benign.

984
00:53:12,720 --> 00:53:15,030
The types of evidence that are used

985
00:53:15,030 --> 00:53:17,100
include a population frequency,

986
00:53:17,100 --> 00:53:19,770
so variants that are fairly frequent

987
00:53:19,770 --> 00:53:23,880
in the population in
individuals who are healthy

988
00:53:23,880 --> 00:53:27,903
are unlikely to be the cause
of a rare genetic disease,

989
00:53:29,460 --> 00:53:31,830
unless we're talking about
a recessive disorder,

990
00:53:31,830 --> 00:53:33,360
in which case a significant fraction

991
00:53:33,360 --> 00:53:35,100
of the population could be carrying it

992
00:53:35,100 --> 00:53:39,423
and it could be a recessive
pathogenic mutation.

993
00:53:44,070 --> 00:53:46,890
If this variant is
reported in this disease

994
00:53:46,890 --> 00:53:50,580
and is not reported in people
who don't have the disease,

995
00:53:50,580 --> 00:53:55,263
that's a mark on the plus
column for pathogenicity.

996
00:53:56,370 --> 00:53:57,360
On the other hand,

997
00:53:57,360 --> 00:53:59,820
if people that's reported in this disease

998
00:53:59,820 --> 00:54:02,820
but it's also reported
in an equal frequency

999
00:54:02,820 --> 00:54:05,070
of people who don't have the disease,

1000
00:54:05,070 --> 00:54:08,553
then it moves more
toward the benign column.

1001
00:54:09,990 --> 00:54:11,790
If it tracks with the disease in family,

1002
00:54:11,790 --> 00:54:14,850
a so-called co-segregation of the disease

1003
00:54:14,850 --> 00:54:17,430
and the variant in large families,

1004
00:54:17,430 --> 00:54:22,230
or especially if that
happens in multiple families,

1005
00:54:22,230 --> 00:54:26,673
that is evidence to support
pathogenicity of the disease.

1006
00:54:27,900 --> 00:54:32,220
If introducing the
genetic variant into cells

1007
00:54:32,220 --> 00:54:35,340
causes a biochemical or
a protein function change

1008
00:54:35,340 --> 00:54:37,380
that you can measure in the laboratory,

1009
00:54:37,380 --> 00:54:40,050
a so-called functional assay,

1010
00:54:40,050 --> 00:54:43,953
that is further evidence
that it may be pathogenic.

1011
00:54:45,120 --> 00:54:47,160
And as I mentioned twice already,

1012
00:54:47,160 --> 00:54:51,150
if it is new in an
individual with the disease,

1013
00:54:51,150 --> 00:54:52,590
it wasn't present in their parents

1014
00:54:52,590 --> 00:54:54,780
and neither of their parents are affected,

1015
00:54:54,780 --> 00:54:58,380
that's another sort of element

1016
00:54:58,380 --> 00:55:02,470
that leads of evidence
that can help you decide

1017
00:55:04,380 --> 00:55:06,813
that it might be pathogenic.

1018
00:55:08,880 --> 00:55:11,580
Okay, I've added this little clock

1019
00:55:11,580 --> 00:55:16,170
to remind me to tell you
that the evidence space

1020
00:55:16,170 --> 00:55:19,830
for these ratings changes over time

1021
00:55:19,830 --> 00:55:23,820
as more information is
gathered about populations,

1022
00:55:23,820 --> 00:55:25,560
about families with the disease,

1023
00:55:25,560 --> 00:55:27,660
and about protein function

1024
00:55:27,660 --> 00:55:30,810
and the impacts of the
variation on protein function

1025
00:55:30,810 --> 00:55:32,970
as that's studied further.

1026
00:55:32,970 --> 00:55:37,770
So a classification at one point in time

1027
00:55:37,770 --> 00:55:41,700
may actually be different
two or three years later.

1028
00:55:41,700 --> 00:55:43,650
So, for the most part,

1029
00:55:43,650 --> 00:55:45,900
that's going to be moving
things from variants

1030
00:55:45,900 --> 00:55:48,990
of uncertain significance
up to likely pathogenic

1031
00:55:48,990 --> 00:55:53,730
or pathogenic or to
likely benign or benign.

1032
00:55:53,730 --> 00:55:56,190
But occasionally, things
will have been classified

1033
00:55:56,190 --> 00:56:00,450
as likely pathogenic
or pathogenic early on,

1034
00:56:00,450 --> 00:56:03,420
and new evidence arises that says,

1035
00:56:03,420 --> 00:56:06,090
eh, not so much, we really
now think it's benign

1036
00:56:06,090 --> 00:56:07,350
or likely benign,

1037
00:56:07,350 --> 00:56:08,910
and so they get moved down

1038
00:56:08,910 --> 00:56:13,230
in the pathogenicity
classification system.

1039
00:56:13,230 --> 00:56:15,630
The important point is that once you have

1040
00:56:15,630 --> 00:56:17,070
a result like this,

1041
00:56:17,070 --> 00:56:21,150
you may have to revisit its classification

1042
00:56:21,150 --> 00:56:25,140
at a later point in time
in order to be certain

1043
00:56:25,140 --> 00:56:26,910
that you are interpreting it

1044
00:56:26,910 --> 00:56:29,250
with the current understanding

1045
00:56:29,250 --> 00:56:31,143
of its importance for disease.

1046
00:56:34,590 --> 00:56:37,500
So what strategies might
you use for a variant

1047
00:56:37,500 --> 00:56:40,290
if you get a report back
that has on it a variant

1048
00:56:40,290 --> 00:56:42,480
of uncertain significance?

1049
00:56:42,480 --> 00:56:47,040
One is to ignore it, and that's okay.

1050
00:56:47,040 --> 00:56:49,650
One is to wait and revisit.

1051
00:56:49,650 --> 00:56:53,070
One is to see if your
patient wants to participate

1052
00:56:53,070 --> 00:56:56,250
in research studies
that might help clarify

1053
00:56:56,250 --> 00:56:58,383
whether it is pathogenic or not.

1054
00:57:00,450 --> 00:57:05,450
You can get online and go
to one of several websites

1055
00:57:08,640 --> 00:57:11,940
where you can put in your genetic VUS

1056
00:57:11,940 --> 00:57:14,310
and your disease phenotype

1057
00:57:14,310 --> 00:57:17,310
and try to find other
individuals across the world

1058
00:57:17,310 --> 00:57:18,960
who have also been tested,

1059
00:57:18,960 --> 00:57:22,863
have been found to have the same variant,

1060
00:57:23,730 --> 00:57:25,890
and compare whether they
have the same disease

1061
00:57:25,890 --> 00:57:28,950
or the same phenotype that you do.

1062
00:57:28,950 --> 00:57:31,920
So that's a new tool
that's kind of interesting,

1063
00:57:31,920 --> 00:57:35,583
and then sort of
crowdsourcing evidence base.

1064
00:57:36,930 --> 00:57:40,080
In general, we do not base therapy

1065
00:57:40,080 --> 00:57:42,840
on a variant of uncertain significance.

1066
00:57:42,840 --> 00:57:45,060
We do not test relatives for a variant

1067
00:57:45,060 --> 00:57:46,200
of uncertain significance

1068
00:57:46,200 --> 00:57:50,580
unless we're in the process
of trying to gather evidence

1069
00:57:50,580 --> 00:57:52,530
to see whether it's significant or not.

1070
00:57:53,580 --> 00:57:56,010
And we don't generally tell a patient

1071
00:57:56,010 --> 00:57:58,500
that we know the cause of their disease.

1072
00:57:58,500 --> 00:58:00,150
So I'll tell a really quick story,

1073
00:58:00,150 --> 00:58:05,150
that there was a lawsuit in Oregon State

1074
00:58:06,360 --> 00:58:10,530
where a practitioner did a test

1075
00:58:14,550 --> 00:58:19,550
to look for lynch syndrome
and found an MLH1 variant.

1076
00:58:22,470 --> 00:58:26,160
They made two mistakes.

1077
00:58:26,160 --> 00:58:30,090
First, they decided that the variant,

1078
00:58:30,090 --> 00:58:32,790
since it was found and reported,

1079
00:58:32,790 --> 00:58:34,890
was important and that
meant that the patient

1080
00:58:34,890 --> 00:58:37,683
had lynch syndrome when
in fact it was a VUS.

1081
00:58:38,520 --> 00:58:39,900
The second mistake that they made

1082
00:58:39,900 --> 00:58:41,610
was not understanding lynch syndrome

1083
00:58:41,610 --> 00:58:46,610
and the phenotype spectrum.

1084
00:58:47,190 --> 00:58:51,060
They believed that that
resulted in a high risk

1085
00:58:51,060 --> 00:58:54,600
of breast cancer and performed
bilateral mastectomy.

1086
00:58:54,600 --> 00:58:56,793
In fact, that was inappropriate.

1087
00:58:58,050 --> 00:59:01,590
Hundreds of thousands of
dollars changed hands in court

1088
00:59:01,590 --> 00:59:06,153
as the result of that
misinterpretation of genetic testing.

1089
00:59:07,620 --> 00:59:09,180
All right, here's a clinical scenario.

1090
00:59:09,180 --> 00:59:12,030
Your patient says he had
genetic testing five years ago,

1091
00:59:12,030 --> 00:59:14,100
and nothing was found.

1092
00:59:14,100 --> 00:59:17,040
What questions do you
wanna ask about the result?

1093
00:59:17,040 --> 00:59:19,980
What technology was used for the test,

1094
00:59:19,980 --> 00:59:21,330
what type of test was it?

1095
00:59:21,330 --> 00:59:23,100
That sounds reasonable.

1096
00:59:23,100 --> 00:59:25,260
Did they report any VUS,s?

1097
00:59:25,260 --> 00:59:27,780
That sounds reasonable
because you might want

1098
00:59:27,780 --> 00:59:29,430
to look at those VUS's again

1099
00:59:29,430 --> 00:59:31,880
and see if their categorization
has been changed.

1100
00:59:33,240 --> 00:59:35,283
Was the test a consumer-oriented one?

1101
00:59:36,210 --> 00:59:37,260
Yeah, that's important,

1102
00:59:37,260 --> 00:59:40,650
because the consumer-oriented tests

1103
00:59:40,650 --> 00:59:44,540
are generally not done in
CLIA certified laboratories.

1104
00:59:44,540 --> 00:59:46,920
In other words, they're not
done in medical laboratories,

1105
00:59:46,920 --> 00:59:50,250
and the results from those are not usable

1106
00:59:50,250 --> 00:59:52,083
in clinical medicine by law.

1107
00:59:53,040 --> 00:59:55,350
If you want to use that information,

1108
00:59:55,350 --> 00:59:59,640
you have to confirm by
retesting for those variations

1109
00:59:59,640 --> 01:00:01,983
in a CLIA certified laboratory.

1110
01:00:04,380 --> 01:00:06,330
And also, where's the
test result documented?

1111
01:00:06,330 --> 01:00:08,370
Because, as we'll talk about,

1112
01:00:08,370 --> 01:00:09,870
you'll get a lot more information

1113
01:00:09,870 --> 01:00:11,790
by looking at the documentation,

1114
01:00:11,790 --> 01:00:14,850
the actual report from the test,

1115
01:00:14,850 --> 01:00:17,940
and getting a copy of that than you will

1116
01:00:17,940 --> 01:00:20,640
from talking to the patient themselves.

1117
01:00:20,640 --> 01:00:22,770
And you will have that in your records

1118
01:00:22,770 --> 01:00:25,510
so you can validate what you did

1119
01:00:26,370 --> 01:00:28,233
on the basis of that result.

1120
01:00:29,940 --> 01:00:34,260
Okay, let's talk about those reports.

1121
01:00:34,260 --> 01:00:36,630
Understanding testing results

1122
01:00:36,630 --> 01:00:39,480
as they reported in clinical tests.

1123
01:00:39,480 --> 01:00:41,380
We'll talk about variant nomenclature,

1124
01:00:42,630 --> 01:00:45,330
what is the meaning of
a reference sequence,

1125
01:00:45,330 --> 01:00:49,530
what it is that is varied
from the reference,

1126
01:00:49,530 --> 01:00:52,950
what's the clinical
significance of that variation,

1127
01:00:52,950 --> 01:00:54,120
what may have been missed,

1128
01:00:54,120 --> 01:00:55,623
and what are your next steps?

1129
01:00:57,540 --> 01:01:00,150
So describing sequence variation type

1130
01:01:00,150 --> 01:01:01,740
and location in the genome.

1131
01:01:01,740 --> 01:01:05,400
So we want to say, you have this variant.

1132
01:01:05,400 --> 01:01:06,750
How do we do that?

1133
01:01:06,750 --> 01:01:07,920
How do we say, this,

1134
01:01:07,920 --> 01:01:11,370
and how does everybody
recognize what, this, means?

1135
01:01:11,370 --> 01:01:15,120
I'm gonna use here a
postal address analogy

1136
01:01:15,120 --> 01:01:18,600
to describe roughly how that's done,

1137
01:01:18,600 --> 01:01:21,633
and then I'll show how it's
actually done in genomics.

1138
01:01:23,070 --> 01:01:24,600
First of all, you have to have an agency

1139
01:01:24,600 --> 01:01:26,430
that defines the standard

1140
01:01:26,430 --> 01:01:31,430
of how you communicate that information.

1141
01:01:32,220 --> 01:01:33,270
And in this case,

1142
01:01:33,270 --> 01:01:35,100
for postal address in the United States,

1143
01:01:35,100 --> 01:01:37,173
it's the United States Postal Service.

1144
01:01:39,090 --> 01:01:41,793
There are actually two types of addresses.

1145
01:01:42,690 --> 01:01:43,560
To simplify it,

1146
01:01:43,560 --> 01:01:46,980
there's a street address
and a P.O. Box, right?

1147
01:01:46,980 --> 01:01:48,900
So for the street address,

1148
01:01:48,900 --> 01:01:51,660
we might have 111 Colchester Avenue

1149
01:01:51,660 --> 01:01:53,883
in Burlington, Vermont with a zip code.

1150
01:01:55,380 --> 01:01:58,680
This is showing a segment of the country,

1151
01:01:58,680 --> 01:02:00,540
a region, so to speak,

1152
01:02:00,540 --> 01:02:01,620
that we wanna look at,

1153
01:02:01,620 --> 01:02:06,620
and then a more specific
position in that region.

1154
01:02:06,720 --> 01:02:08,460
And in this case,

1155
01:02:08,460 --> 01:02:09,780
for a street address,

1156
01:02:09,780 --> 01:02:13,350
we put the number in
front of the street name.

1157
01:02:13,350 --> 01:02:14,730
So there are conventions here

1158
01:02:14,730 --> 01:02:18,603
that help you differentiate
what kind of address it is.

1159
01:02:20,010 --> 01:02:22,683
And for a P.O. Box address,

1160
01:02:24,690 --> 01:02:27,060
you might have an address like this.

1161
01:02:27,060 --> 01:02:29,910
So in the same way you have the
same segment of the country,

1162
01:02:29,910 --> 01:02:32,490
it's a different segment 'cause
I'm in South Burlington now,

1163
01:02:32,490 --> 01:02:34,830
and I have a different zip code,

1164
01:02:34,830 --> 01:02:39,240
and I have a P.O. Box with a number.

1165
01:02:39,240 --> 01:02:41,730
So how is that number different
from the other number?

1166
01:02:41,730 --> 01:02:44,880
The position of the number
follows the word P.O. Box.

1167
01:02:44,880 --> 01:02:47,340
So that's the convention, all right?

1168
01:02:47,340 --> 01:02:50,760
There are ways we can sort of avoid trying

1169
01:02:50,760 --> 01:02:53,343
to mix up these different
types of addresses.

1170
01:02:54,510 --> 01:02:56,670
All right, so let's talk about

1171
01:02:56,670 --> 01:03:00,930
different nomenclature systems

1172
01:03:00,930 --> 01:03:03,360
for different types of test results.

1173
01:03:03,360 --> 01:03:04,980
So we're gonna talk about cytogenetics

1174
01:03:04,980 --> 01:03:07,140
and copy number variants on this slide.

1175
01:03:07,140 --> 01:03:09,020
The agency is HGVS,

1176
01:03:09,020 --> 01:03:11,700
or the Human Genome Variation Society.

1177
01:03:11,700 --> 01:03:15,420
And ISCN is the international system

1178
01:03:15,420 --> 01:03:17,862
for cytogenetic notation.

1179
01:03:17,862 --> 01:03:21,780
And you can look it up
in books, basically.

1180
01:03:21,780 --> 01:03:25,500
A chromosome variation
starts out with the count

1181
01:03:25,500 --> 01:03:26,790
of chromosomes per cell.

1182
01:03:26,790 --> 01:03:31,380
So, we look under the
microscope at a cell prep,

1183
01:03:31,380 --> 01:03:33,270
and when we count the
number of chromosomes there,

1184
01:03:33,270 --> 01:03:35,430
we're actually counting
the number of centromeres.

1185
01:03:35,430 --> 01:03:37,140
And in a normal cell,

1186
01:03:37,140 --> 01:03:39,840
we would count 46, right?

1187
01:03:39,840 --> 01:03:41,163
Two pairs of 23.

1188
01:03:43,050 --> 01:03:45,240
We then look among those chromosomes

1189
01:03:45,240 --> 01:03:46,680
and identify the sex chromosomes,

1190
01:03:46,680 --> 01:03:51,180
and we say, what is this
sex chromosome constitution

1191
01:03:51,180 --> 01:03:52,230
of that cell?

1192
01:03:52,230 --> 01:03:56,760
It's either an X + Y, an X and an X.

1193
01:03:56,760 --> 01:03:58,080
Or in the case of Turner syndrome,

1194
01:03:58,080 --> 01:04:00,240
an X without a second X.

1195
01:04:00,240 --> 01:04:02,040
Or in the case of Klinefelter syndrome,

1196
01:04:02,040 --> 01:04:04,080
two Xs and a Y, okay?

1197
01:04:04,080 --> 01:04:07,500
So those are listed subsequently.

1198
01:04:07,500 --> 01:04:09,630
And then, abnormal stuff,

1199
01:04:09,630 --> 01:04:11,880
like a translocation, or
in this case an inversion,

1200
01:04:11,880 --> 01:04:15,630
because you're going from 2p to 2q,

1201
01:04:15,630 --> 01:04:19,413
are described after that initial part.

1202
01:04:20,520 --> 01:04:21,900
And that can get quite complicated,

1203
01:04:21,900 --> 01:04:24,350
now I'm not going to go
into the details of that.

1204
01:04:25,620 --> 01:04:30,620
So chromosome microarray has a related,

1205
01:04:31,590 --> 01:04:35,820
but not similar to nomenclature.

1206
01:04:35,820 --> 01:04:40,820
It typically starts with the
abbreviation arr in advance.

1207
01:04:42,660 --> 01:04:45,780
If you see FISH reports,

1208
01:04:45,780 --> 01:04:48,240
you might see FISH or something like that,

1209
01:04:48,240 --> 01:04:52,710
or ISH in there to show you

1210
01:04:52,710 --> 01:04:54,960
what kind of an technology it is.

1211
01:04:54,960 --> 01:04:58,020
So that is the array comparative
genomic hybridization

1212
01:04:58,020 --> 01:04:59,613
on the chromosome microarray.

1213
01:05:00,690 --> 01:05:02,160
If there's a copy number variant,

1214
01:05:02,160 --> 01:05:05,160
it will tell you what the
chromosome band position is,

1215
01:05:05,160 --> 01:05:07,950
what position on chromosome 22 it is,

1216
01:05:07,950 --> 01:05:12,690
and it's followed by a pair
of numbers in parentheses.

1217
01:05:12,690 --> 01:05:14,820
There will be a lower
number and a higher number.

1218
01:05:14,820 --> 01:05:19,820
And those tell you the sequence
position on chromosome 22,

1219
01:05:22,200 --> 01:05:26,643
which is the start and end
of the copy number variation.

1220
01:05:27,960 --> 01:05:32,960
That parenthesis group is
followed by a times and a number.

1221
01:05:36,330 --> 01:05:41,330
And that basically says this
segment of chromosome 22

1222
01:05:44,520 --> 01:05:48,600
only had one copy number
instead of the expected two.

1223
01:05:48,600 --> 01:05:52,110
So x1 tells you it was
a deletion, all right?

1224
01:05:52,110 --> 01:05:54,720
Or copy number of variation of a loss.

1225
01:05:54,720 --> 01:05:56,490
Deletion or loss.

1226
01:05:56,490 --> 01:06:01,490
If it was times 3, it
would be also unexpected

1227
01:06:03,360 --> 01:06:06,870
and it would suggest that
there was a duplication

1228
01:06:06,870 --> 01:06:11,253
or gain of copy number, all right?

1229
01:06:13,200 --> 01:06:15,450
So that's the basic nomenclature.

1230
01:06:15,450 --> 01:06:19,590
I do not expect you to remember
or memorize all of this,

1231
01:06:19,590 --> 01:06:22,830
I just want you to have a vague concept

1232
01:06:22,830 --> 01:06:24,360
that you've seen this before

1233
01:06:24,360 --> 01:06:29,283
when you see these reports
coming across your desk.

1234
01:06:31,050 --> 01:06:32,050
I'm gonna skip that.

1235
01:06:33,930 --> 01:06:37,410
All right, what about sequence variation?

1236
01:06:37,410 --> 01:06:40,080
We talked about cytogenetic
and copy number variation,

1237
01:06:40,080 --> 01:06:42,720
let's talk about sequence variations.

1238
01:06:42,720 --> 01:06:46,980
HGVS is the agency that defines
the nomenclature standards.

1239
01:06:46,980 --> 01:06:48,330
You can look them online,

1240
01:06:48,330 --> 01:06:53,330
they have a website, varnomen.hgvs.org.

1241
01:06:54,690 --> 01:06:56,797
Within their site, there
is a quote unquote,

1242
01:06:56,797 --> 01:06:58,830
"simple description" of the nomenclature

1243
01:06:58,830 --> 01:07:00,063
for sequence variation.

1244
01:07:02,250 --> 01:07:04,260
It may be worth reading.

1245
01:07:04,260 --> 01:07:07,833
It's not something that
you learn terribly quickly,

1246
01:07:08,670 --> 01:07:11,280
but I think it is helpful
to begin to look at these

1247
01:07:11,280 --> 01:07:14,460
and try to parse them so that over time

1248
01:07:14,460 --> 01:07:16,350
you're gonna become more
and more comfortable

1249
01:07:16,350 --> 01:07:17,853
with what they mean.

1250
01:07:20,280 --> 01:07:25,170
Okay, so we're gonna break
this up into two parts.

1251
01:07:25,170 --> 01:07:27,510
I'm gonna talk first
about the reference type

1252
01:07:27,510 --> 01:07:28,343
and the location.

1253
01:07:28,343 --> 01:07:30,240
So what is the reference sequence?

1254
01:07:30,240 --> 01:07:33,183
What are we saying has changed?

1255
01:07:34,950 --> 01:07:39,690
What are we saying is the standard

1256
01:07:39,690 --> 01:07:42,000
which we're noticing has changed

1257
01:07:42,000 --> 01:07:44,700
in this particular patient's sequence?

1258
01:07:44,700 --> 01:07:46,770
So what is the reference
sequence that defined

1259
01:07:46,770 --> 01:07:49,713
what is expected at the
specific genome location?

1260
01:07:51,060 --> 01:07:54,240
So we want to provide a unique identifier

1261
01:07:54,240 --> 01:07:56,460
that points to that reference sequence.

1262
01:07:56,460 --> 01:07:59,463
Otherwise, when we specify a position,

1263
01:08:01,578 --> 01:08:02,970
we won't be specifying anything

1264
01:08:02,970 --> 01:08:07,263
that's unique and re-identifiable, okay?

1265
01:08:09,720 --> 01:08:14,720
And then we want to specify
whether the reference sequence

1266
01:08:14,880 --> 01:08:19,140
is in a genomic sequence, a chromosome,

1267
01:08:19,140 --> 01:08:24,140
in which case we prefix
the sequence position

1268
01:08:24,810 --> 01:08:26,463
with a "g." for genome.

1269
01:08:27,420 --> 01:08:30,030
If it's in a cDNA sequence,

1270
01:08:30,030 --> 01:08:32,607
in which case we prefix it with a "c."

1271
01:08:34,950 --> 01:08:36,750
Or if it's in a protein sequence,

1272
01:08:36,750 --> 01:08:39,420
in which case we prefix it with a "p."

1273
01:08:39,420 --> 01:08:42,213
All of those are lowercase, all right?

1274
01:08:43,860 --> 01:08:48,030
So, and then we say what is
the location in the sequence?

1275
01:08:48,030 --> 01:08:51,090
So that first position
in the reference sequence

1276
01:08:51,090 --> 01:08:52,770
is location number 1.

1277
01:08:52,770 --> 01:08:57,770
So that's the 1st base in
the nucleic acid sequences 1.

1278
01:08:57,900 --> 01:09:00,420
And with respect to chromosomes,

1279
01:09:00,420 --> 01:09:02,820
that is the first base that's recorded

1280
01:09:02,820 --> 01:09:05,760
in the reference sequence
starting from the tip

1281
01:09:05,760 --> 01:09:08,280
of the short arm of the
chromosome, or the P arm.

1282
01:09:08,280 --> 01:09:10,260
So we're kinda going from left to right

1283
01:09:10,260 --> 01:09:11,910
when you lay the chromosome on its side

1284
01:09:11,910 --> 01:09:13,533
with the P arm to its left.

1285
01:09:14,820 --> 01:09:18,090
An example then would be we're gonna say

1286
01:09:18,090 --> 01:09:20,910
it's a segment called chromosome 2,

1287
01:09:20,910 --> 01:09:24,060
it's a colon, it's a genome sequence,

1288
01:09:24,060 --> 01:09:25,773
that's what the g. tells us.

1289
01:09:27,180 --> 01:09:30,573
It tells us this a specific
sequence position, which is-

1290
01:09:32,400 --> 01:09:33,630
Let's see, where's my commas?

1291
01:09:33,630 --> 01:09:35,243
Commas go there and there.

1292
01:09:35,243 --> 01:09:40,243
326,890,112 bases into the
sequence from the P arm.

1293
01:09:42,810 --> 01:09:47,810
And the reference base
at that position, is a g.

1294
01:09:51,180 --> 01:09:52,980
So there's a guanine at that position

1295
01:09:52,980 --> 01:09:54,303
in the reference sequence.

1296
01:09:56,070 --> 01:09:59,460
In the case of a cDNA sequence,

1297
01:09:59,460 --> 01:10:04,460
the position 1 is the "A"
of ATG initiation codon

1298
01:10:04,470 --> 01:10:05,463
for the cDNA.

1299
01:10:07,080 --> 01:10:12,080
cDNA .167A tells you
that there is an adenine,

1300
01:10:12,750 --> 01:10:17,043
again, a base, at position
167 in that cDNA sequence.

1301
01:10:17,970 --> 01:10:21,930
That may correlate with
this place on the genome.

1302
01:10:21,930 --> 01:10:24,060
So a lotta times you're given both

1303
01:10:24,060 --> 01:10:29,060
a genome reference sequence
and a cDNA reference position

1304
01:10:29,700 --> 01:10:31,173
that correlates with that.

1305
01:10:34,260 --> 01:10:36,930
In a protein sequence,

1306
01:10:36,930 --> 01:10:38,430
the 1st methionine,

1307
01:10:38,430 --> 01:10:41,310
the 1st amino acid position
in the protein chain encoded

1308
01:10:41,310 --> 01:10:45,420
by that ATG is position number 1.

1309
01:10:45,420 --> 01:10:46,830
So here's an example.

1310
01:10:46,830 --> 01:10:50,160
Protein sequence glycine 55.

1311
01:10:50,160 --> 01:10:54,750
So there's a glycine at amino
acid 55 in the sequence.

1312
01:10:54,750 --> 01:10:58,627
It can also be written as p.G55.

1313
01:11:00,210 --> 01:11:05,210
G is the single letter amino
acid code for glycine, okay?

1314
01:11:07,620 --> 01:11:09,180
You can see how this can be confused,

1315
01:11:09,180 --> 01:11:11,310
because here's a G and here's a G,

1316
01:11:11,310 --> 01:11:15,030
so you need to be able to differentiate

1317
01:11:15,030 --> 01:11:18,150
what is a position in a DNA

1318
01:11:18,150 --> 01:11:20,370
and what is a position in a protein

1319
01:11:20,370 --> 01:11:23,613
so you can properly interpret
the single amino acid codes.

1320
01:11:25,650 --> 01:11:28,470
All right, so here's an
example of a sequence

1321
01:11:28,470 --> 01:11:30,540
for chromosome 11.

1322
01:11:30,540 --> 01:11:33,480
This is a reference sequence,

1323
01:11:33,480 --> 01:11:38,010
and you can get to it by
going to the nucleotide core

1324
01:11:38,010 --> 01:11:40,920
or what's called RefSeq.

1325
01:11:40,920 --> 01:11:42,230
And you can recognize it

1326
01:11:42,230 --> 01:11:44,793
'cause it's a nucleotide sequence,

1327
01:11:46,140 --> 01:11:51,140
and anything that ends in
11 here is chromosome 11.

1328
01:11:51,600 --> 01:11:55,503
If it says 02, it's
chromosome 2 et cetera.

1329
01:11:57,480 --> 01:12:00,930
And base position 1 here
in that sequence is an N.

1330
01:12:00,930 --> 01:12:03,420
So in the case of the reference sequence

1331
01:12:03,420 --> 01:12:07,410
for chromosome 11, the tip
of the P arm is very messy,

1332
01:12:07,410 --> 01:12:09,990
and so the sequence actually begins

1333
01:12:09,990 --> 01:12:11,580
with a whole bunch of Ns,

1334
01:12:11,580 --> 01:12:13,200
which means we don't know which base

1335
01:12:13,200 --> 01:12:14,790
or it could be any base.

1336
01:12:14,790 --> 01:12:16,980
At some point, a couple of pages down,

1337
01:12:16,980 --> 01:12:20,643
you'll enter actual ACGT sequence.

1338
01:12:22,230 --> 01:12:26,100
Okay, what about the reference sequence?

1339
01:12:26,100 --> 01:12:29,190
So, I just gave you
information about that.

1340
01:12:29,190 --> 01:12:31,500
And this NCBI reference sequence

1341
01:12:31,500 --> 01:12:36,500
is what you might quote for that, okay?

1342
01:12:36,930 --> 01:12:41,370
So, a couple of things
are important there.

1343
01:12:41,370 --> 01:12:44,798
One is that you need to get

1344
01:12:44,798 --> 01:12:47,100
the reference sequence version right.

1345
01:12:47,100 --> 01:12:52,100
So this is the genome build, hg19,

1346
01:12:52,170 --> 01:12:53,940
that's the British nomenclature.

1347
01:12:53,940 --> 01:12:56,850
And the US nomenclature,
or the NCBI nomenclature,

1348
01:12:56,850 --> 01:13:00,840
is GRch38, or build 38.

1349
01:13:00,840 --> 01:13:04,560
And those may have suffixes
like decimal suffixes

1350
01:13:04,560 --> 01:13:08,460
to them as well that you really
don't have to worry about.

1351
01:13:08,460 --> 01:13:11,670
So that tells you that this number

1352
01:13:11,670 --> 01:13:16,590
you can look up with
confidence in that genome build

1353
01:13:16,590 --> 01:13:20,580
in that genome build's
sequence for chromosome 2

1354
01:13:20,580 --> 01:13:22,050
and you know exactly which base

1355
01:13:22,050 --> 01:13:23,883
you're talking about, always.

1356
01:13:26,340 --> 01:13:27,630
Okay, so that's the version

1357
01:13:27,630 --> 01:13:32,630
of the reference human genome sequence,

1358
01:13:33,540 --> 01:13:36,693
the segment of the
human genome chromosome,

1359
01:13:37,620 --> 01:13:39,810
and the position in
the reference sequence,

1360
01:13:39,810 --> 01:13:42,843
so thinking back to those
US postal addresses.

1361
01:13:44,310 --> 01:13:46,530
And then, the base found at the reference

1362
01:13:46,530 --> 01:13:49,530
at that position is really
for your convenience,

1363
01:13:49,530 --> 01:13:52,440
because once you have
this other information,

1364
01:13:52,440 --> 01:13:54,870
you could go find that base

1365
01:13:54,870 --> 01:13:57,840
in that whole chromosome sequence

1366
01:13:57,840 --> 01:14:00,210
and you would be able to
determine what the base was.

1367
01:14:00,210 --> 01:14:02,493
But it's written there
for your convenience.

1368
01:14:04,200 --> 01:14:09,200
A cDNA sequence is also given a reference.

1369
01:14:10,530 --> 01:14:15,530
Those have the letter M in
the reference sequence name

1370
01:14:19,170 --> 01:14:22,710
as an mRNA sequence.

1371
01:14:22,710 --> 01:14:25,980
You'll also see X in the
first position there.

1372
01:14:25,980 --> 01:14:30,090
Those are alternative cDNA sequences,

1373
01:14:30,090 --> 01:14:32,280
they're old cDNA sequences.

1374
01:14:32,280 --> 01:14:33,870
You wanna pay attention to the N,

1375
01:14:33,870 --> 01:14:35,103
which is the standard.

1376
01:14:36,660 --> 01:14:38,700
And then you have c.345G.

1377
01:14:38,700 --> 01:14:41,580
Again, you can look up position 345

1378
01:14:41,580 --> 01:14:43,920
in that reference sequence

1379
01:14:43,920 --> 01:14:45,180
and see that it's a G,

1380
01:14:45,180 --> 01:14:50,180
but it's presented here
for your convenience.

1381
01:14:50,640 --> 01:14:55,290
Notice that in nucleic acid sequences,

1382
01:14:55,290 --> 01:14:58,657
you have the position and
then the reference base

1383
01:15:00,870 --> 01:15:02,013
at that position.

1384
01:15:08,400 --> 01:15:09,233
All right.

1385
01:15:10,920 --> 01:15:11,753
Okay.

1386
01:15:13,380 --> 01:15:17,130
And then the variation is
added onto the end of those.

1387
01:15:17,130 --> 01:15:19,740
So you've told at where we're going,

1388
01:15:19,740 --> 01:15:22,680
which chromosome version we're looking at,

1389
01:15:22,680 --> 01:15:24,690
which chromosome we're looking at,

1390
01:15:24,690 --> 01:15:25,920
which sequence position,

1391
01:15:25,920 --> 01:15:28,890
what the base and the
reference sequence is,

1392
01:15:28,890 --> 01:15:33,000
and now we wanna say, what
did we observe in our patient?

1393
01:15:33,000 --> 01:15:35,516
So for nucleic acid sequences-

1394
01:15:35,516 --> 01:15:38,183
(alarm beeping)

1395
01:15:48,900 --> 01:15:51,820
For nucleic acid sequences we have

1396
01:15:54,100 --> 01:15:57,840
a system of adding a open, I'm sorry,

1397
01:15:57,840 --> 01:16:00,720
a greater than sign and
the base that we observed,

1398
01:16:00,720 --> 01:16:02,160
or the bases that we observed.

1399
01:16:02,160 --> 01:16:06,480
So, example for a genomic
would be a G to A change.

1400
01:16:06,480 --> 01:16:11,433
And the cDNA, an A to an T change, okay?

1401
01:16:14,010 --> 01:16:17,853
In the case of protein,

1402
01:16:18,690 --> 01:16:20,370
it's a little bit different.

1403
01:16:20,370 --> 01:16:23,790
We have the P, we have the
Gly, the 55, the location.

1404
01:16:23,790 --> 01:16:26,400
And if it's changed glycine to proline,

1405
01:16:26,400 --> 01:16:31,400
then the variation is listed after

1406
01:16:33,510 --> 01:16:36,390
the sequence position here.

1407
01:16:36,390 --> 01:16:38,070
That's in a three letter amino acid code.

1408
01:16:38,070 --> 01:16:41,250
That's the same thing in a
one letter amino acid code.

1409
01:16:41,250 --> 01:16:42,650
And you'll see both of them.

1410
01:16:43,950 --> 01:16:47,987
So, the difference here is that there's

1411
01:16:49,800 --> 01:16:53,160
a little bit of rearrangement
in the order of things.

1412
01:16:53,160 --> 01:16:58,160
We have the position coming
just before the variant

1413
01:16:58,860 --> 01:17:03,860
in the protein and just after
the reference base in the DNA.

1414
01:17:11,070 --> 01:17:13,800
So there's a little bit of
difference in the order.

1415
01:17:13,800 --> 01:17:15,900
You have your G, your C, and your P,

1416
01:17:15,900 --> 01:17:17,163
that helps you too.

1417
01:17:18,030 --> 01:17:23,030
And then there is also
the greater than symbol,

1418
01:17:23,430 --> 01:17:26,040
which is only seen in
the nucleic acid ones.

1419
01:17:26,040 --> 01:17:30,570
And again, this position is between

1420
01:17:30,570 --> 01:17:35,570
the reference amino acid
and the variant amino acid

1421
01:17:36,660 --> 01:17:38,673
in your protein.

1422
01:17:48,060 --> 01:17:49,590
Variants come in different forms.

1423
01:17:49,590 --> 01:17:51,600
There's heterozygous variants found

1424
01:17:51,600 --> 01:17:53,550
on one of two copies.

1425
01:17:53,550 --> 01:17:57,300
Homozygous, the same variant
was found on both copies.

1426
01:17:57,300 --> 01:17:59,820
There was no non-variant copy.

1427
01:17:59,820 --> 01:18:02,160
Compound heterozygous,
two variants were found

1428
01:18:02,160 --> 01:18:03,060
in the same gene,

1429
01:18:03,060 --> 01:18:07,113
presumed to be on different
copies in trans versus cis.

1430
01:18:08,340 --> 01:18:10,890
And hemizygous, the variant was found,

1431
01:18:10,890 --> 01:18:12,660
no normal copy was found,

1432
01:18:12,660 --> 01:18:15,300
and there appears to be only
one copy of the segment.

1433
01:18:15,300 --> 01:18:17,910
That's typically in the
Y chromosome in males.

1434
01:18:17,910 --> 01:18:20,790
I'm sorry, in the X chromosome
in males that should be.

1435
01:18:20,790 --> 01:18:22,863
But it occurs in other scenarios too.

1436
01:18:23,730 --> 01:18:27,810
So this is important when
you look at the test result

1437
01:18:27,810 --> 01:18:31,560
to know if you're dealing
with a recessive disorder,

1438
01:18:31,560 --> 01:18:33,770
whether you've only found a carrier state,

1439
01:18:33,770 --> 01:18:35,340
or you found enough evidence

1440
01:18:35,340 --> 01:18:37,113
to say the patient may be affected.

1441
01:18:40,740 --> 01:18:41,573
So what does it mean?

1442
01:18:41,573 --> 01:18:44,793
What are the parts of
a test result report?

1443
01:18:46,020 --> 01:18:49,230
In addition to the
nomenclature that you'll see,

1444
01:18:49,230 --> 01:18:50,310
that we've just talked about,

1445
01:18:50,310 --> 01:18:53,820
you'll see a section which
is an interpretation.

1446
01:18:53,820 --> 01:18:57,750
Now the interpretation will
put in prose what was observed.

1447
01:18:57,750 --> 01:19:01,170
In other words, it will
it will sort of replicate

1448
01:19:01,170 --> 01:19:05,190
what the nomenclature says,
but in kinda real words.

1449
01:19:05,190 --> 01:19:08,100
It will tell you what was
found or was not found.

1450
01:19:08,100 --> 01:19:09,750
For example, you may have been looking

1451
01:19:09,750 --> 01:19:13,110
for a specific variant
that had been observed

1452
01:19:13,110 --> 01:19:14,250
in a family member,

1453
01:19:14,250 --> 01:19:16,917
and it will tell you that
they looked for that variant

1454
01:19:16,917 --> 01:19:18,570
but they didn't observe it.

1455
01:19:18,570 --> 01:19:22,050
So that was a negative test
for that familial variant.

1456
01:19:22,050 --> 01:19:24,300
What is the predictive effect on the cDNA

1457
01:19:24,300 --> 01:19:28,680
and on the protein if it's
in a protein coding region?

1458
01:19:28,680 --> 01:19:30,630
What is the pathogenicity rating?

1459
01:19:30,630 --> 01:19:33,480
Again, a variant of unknown significance.

1460
01:19:33,480 --> 01:19:37,623
Benign, likely benign, likely
pathogenic, and pathogenic.

1461
01:19:38,760 --> 01:19:41,400
What is the evidence supporting the rating

1462
01:19:41,400 --> 01:19:44,580
and the references for that evidence?

1463
01:19:44,580 --> 01:19:46,473
So you can go look it up yourself.

1464
01:19:47,370 --> 01:19:50,160
And what is the predicted
clinical significance?

1465
01:19:50,160 --> 01:19:55,160
So the laboratory person has
a landscape of information,

1466
01:19:56,700 --> 01:20:00,470
which is the clinical
information you gave them

1467
01:20:03,540 --> 01:20:05,193
when you requested the test.

1468
01:20:06,120 --> 01:20:07,830
They don't have any other information,

1469
01:20:07,830 --> 01:20:09,510
unless it's a local laboratory

1470
01:20:09,510 --> 01:20:13,440
where they can look up in
your EHR more information

1471
01:20:13,440 --> 01:20:15,930
about the patient if they have questions.

1472
01:20:15,930 --> 01:20:18,270
So the predicted clinical significance

1473
01:20:18,270 --> 01:20:21,510
may be circumscribed
because they don't have

1474
01:20:21,510 --> 01:20:23,460
all the information that you do.

1475
01:20:23,460 --> 01:20:25,890
So you may have to take a look at that

1476
01:20:25,890 --> 01:20:30,663
and decide for yourself whether
that's appropriate or not.

1477
01:20:31,560 --> 01:20:34,200
And then, it will usually
include a recommended

1478
01:20:34,200 --> 01:20:35,973
or suggested clinical actions.

1479
01:20:38,130 --> 01:20:39,990
That may be genetic counseling,

1480
01:20:39,990 --> 01:20:42,420
that may be testing a family member,

1481
01:20:42,420 --> 01:20:45,900
that may be doing an additional test

1482
01:20:45,900 --> 01:20:49,200
which covers things that
this test didn't cover

1483
01:20:49,200 --> 01:20:53,373
or which will help you clarify
the result on this test.

1484
01:20:54,900 --> 01:20:59,130
Finally, it should tell you
the methods that were used.

1485
01:20:59,130 --> 01:21:01,620
This can be a lot of
fine print and detail,

1486
01:21:01,620 --> 01:21:03,240
but sometimes you have to read through it

1487
01:21:03,240 --> 01:21:05,373
to make sure you understand what you got.

1488
01:21:07,080 --> 01:21:09,690
It will include, for
example, in a gene panel,

1489
01:21:09,690 --> 01:21:14,690
the genes that were covered
and what coverage was obtained.

1490
01:21:16,470 --> 01:21:18,540
In other words, were there gaps

1491
01:21:18,540 --> 01:21:23,540
in the sequence that was obtained
with this particular run?

1492
01:21:23,820 --> 01:21:27,450
It will tell you the reference
sequence identification

1493
01:21:27,450 --> 01:21:30,870
which you need in order
to figure out exactly

1494
01:21:30,870 --> 01:21:34,740
what the position part of
the nomenclature means.

1495
01:21:34,740 --> 01:21:37,470
And it will tell you what the capabilities

1496
01:21:37,470 --> 01:21:39,453
and the limitations of the test are.

1497
01:21:43,200 --> 01:21:47,430
So, I wanna end by just sort
of summarizing the process

1498
01:21:47,430 --> 01:21:50,080
that you might go through
when using genetic testing.

1499
01:21:50,940 --> 01:21:52,140
First, you have to decide.

1500
01:21:52,140 --> 01:21:54,630
You have to decide how are you gonna use

1501
01:21:54,630 --> 01:21:57,330
the information that you
can get out of the test.

1502
01:21:57,330 --> 01:21:59,280
You have to decide on the right technology

1503
01:21:59,280 --> 01:22:02,220
with the greatest
sensitivity and specificity

1504
01:22:02,220 --> 01:22:07,050
for the types of genetic variants
that you are looking for.

1505
01:22:07,050 --> 01:22:10,590
You have to use the most
cost-effective steps

1506
01:22:10,590 --> 01:22:13,977
for detecting all the
likely types of variants,

1507
01:22:13,977 --> 01:22:17,010
and that may be doing one small test first

1508
01:22:17,010 --> 01:22:18,420
then following up with a bigger test.

1509
01:22:18,420 --> 01:22:21,150
That might be starting
out with a bigger test.

1510
01:22:21,150 --> 01:22:24,270
It really depends on
the clinical situation.

1511
01:22:24,270 --> 01:22:27,810
You might be concerned
about turnaround time.

1512
01:22:27,810 --> 01:22:31,620
So the turnaround time for
a chromosome microarray

1513
01:22:31,620 --> 01:22:33,180
is a week or two.

1514
01:22:33,180 --> 01:22:37,127
Turnaround time for a small gene panel

1515
01:22:39,930 --> 01:22:43,710
might be three to six weeks.

1516
01:22:43,710 --> 01:22:48,240
A turnaround time for
an exome or a trio exome

1517
01:22:48,240 --> 01:22:51,570
might be six to 18 weeks.

1518
01:22:51,570 --> 01:22:55,170
So you need to think about
what is going to work

1519
01:22:55,170 --> 01:22:57,513
for your particular clinical situation.

1520
01:22:58,350 --> 01:23:01,470
And you have to have some
sense that the laboratory

1521
01:23:01,470 --> 01:23:03,330
that you're going to is trusted.

1522
01:23:03,330 --> 01:23:06,780
And I won't talk about
it being CLIA certified,

1523
01:23:06,780 --> 01:23:08,430
CAP certified, all of those things

1524
01:23:08,430 --> 01:23:11,643
that we look for in clinical laboratories,

1525
01:23:12,690 --> 01:23:14,160
but you have to have a sense

1526
01:23:14,160 --> 01:23:16,323
that this laboratory
knows what it's doing.

1527
01:23:17,970 --> 01:23:20,340
For most genetic tests you
need to preauthorize them

1528
01:23:20,340 --> 01:23:22,650
with the payer, the patient's payer,

1529
01:23:22,650 --> 01:23:26,130
or find some way to minimize

1530
01:23:26,130 --> 01:23:27,990
the out-of-pocket expense for the patient,

1531
01:23:27,990 --> 01:23:29,700
and a lotta the commercial laboratories

1532
01:23:29,700 --> 01:23:32,010
will have mechanisms for this.

1533
01:23:32,010 --> 01:23:34,080
You may need to write a
letter of medical necessity

1534
01:23:34,080 --> 01:23:39,080
to the payer to justify
getting this a test approved.

1535
01:23:43,800 --> 01:23:45,990
You need to organize the sampling

1536
01:23:45,990 --> 01:23:48,570
which happens after the
preauthorization is obtained.

1537
01:23:48,570 --> 01:23:51,360
So you can't simply do
this in the same visit

1538
01:23:51,360 --> 01:23:52,830
with your patient saying,

1539
01:23:52,830 --> 01:23:54,330
ah, we're gonna do this genetic test.

1540
01:23:54,330 --> 01:23:56,460
Order the genetic test,
send him to the laboratory.

1541
01:23:56,460 --> 01:23:57,293
You can't do that.

1542
01:23:57,293 --> 01:23:58,800
You have to have 'em come back

1543
01:23:58,800 --> 01:24:02,520
for a blood or some kind of sampling.

1544
01:24:02,520 --> 01:24:04,290
And that's just the way things work

1545
01:24:04,290 --> 01:24:05,703
with insurance these days.

1546
01:24:06,960 --> 01:24:08,580
Then you have to review the report

1547
01:24:08,580 --> 01:24:09,510
when you get it back.

1548
01:24:09,510 --> 01:24:11,430
Review it carefully and
go through the elements

1549
01:24:11,430 --> 01:24:13,530
that we talked about in this lecture.

1550
01:24:13,530 --> 01:24:16,350
And then, if you're not
really clear about it,

1551
01:24:16,350 --> 01:24:18,390
consult a genetics professional.

1552
01:24:18,390 --> 01:24:20,460
You can either refer the patient

1553
01:24:20,460 --> 01:24:23,040
or you might be able to just call us up

1554
01:24:23,040 --> 01:24:24,960
and say, you know, can you look at this

1555
01:24:24,960 --> 01:24:27,690
and answer a couple of
quick questions for me?

1556
01:24:27,690 --> 01:24:30,030
Usually we're willing to do that.

1557
01:24:30,030 --> 01:24:32,670
So, I'm gonna stop here,

1558
01:24:32,670 --> 01:24:35,370
because that's been a
really lot of information.

1559
01:24:35,370 --> 01:24:37,530
As I said earlier,

1560
01:24:37,530 --> 01:24:40,080
I don't expect you to
remember all of this,

1561
01:24:40,080 --> 01:24:41,670
I want you to be exposed to it

1562
01:24:41,670 --> 01:24:44,010
because this is all coming down the pike.

1563
01:24:44,010 --> 01:24:45,810
Geneticists are used to it.

1564
01:24:45,810 --> 01:24:48,810
It's gonna be seen more
and more in primary care

1565
01:24:48,810 --> 01:24:50,490
and in other specialties.

1566
01:24:50,490 --> 01:24:52,860
And so, it's important to really have

1567
01:24:52,860 --> 01:24:57,420
this grounding in it
so that you can develop

1568
01:24:57,420 --> 01:24:59,253
and learn further in the future.

1569
01:25:00,210 --> 01:25:02,360
I'm Dr. Bob Wildin,
thank you for learning.