1
00:00:00,000 --> 00:00:02,760
[Narrator] Here we're going
to dive into the genetics

2
00:00:02,760 --> 00:00:05,550
of some of the specific
psychiatric disorders

3
00:00:05,550 --> 00:00:07,710
that were covered in the textbook chapters

4
00:00:07,710 --> 00:00:09,810
that were assigned for this module.

5
00:00:09,810 --> 00:00:12,450
So certainly not everything,
not by a long shot,

6
00:00:12,450 --> 00:00:14,250
but just going to hit on some

7
00:00:14,250 --> 00:00:18,100
of the more common psychiatric disorders

8
00:00:20,106 --> 00:00:22,320
that have some genetic components

9
00:00:22,320 --> 00:00:24,060
that have been identified in them.

10
00:00:24,060 --> 00:00:27,210
And we'll use those as basically models

11
00:00:27,210 --> 00:00:30,450
for understanding how
genetics may play a role

12
00:00:30,450 --> 00:00:32,280
in different psychiatric disorders,

13
00:00:32,280 --> 00:00:37,200
and basically the state
of the field as of now

14
00:00:37,200 --> 00:00:39,810
and where it may be moving in the future.

15
00:00:39,810 --> 00:00:41,460
So just to get started here,

16
00:00:41,460 --> 00:00:43,560
as I mentioned in the previous lecture,

17
00:00:43,560 --> 00:00:45,510
it is not nature or nurture.

18
00:00:45,510 --> 00:00:48,660
It is always nature and
nurture, especially,

19
00:00:48,660 --> 00:00:51,240
especially when we're talking
about psychiatric disorders.

20
00:00:51,240 --> 00:00:53,250
These are multifactorial,

21
00:00:53,250 --> 00:00:56,100
meaning both environment
and genetics play a role.

22
00:00:56,100 --> 00:00:57,000
They're polygenic,

23
00:00:57,000 --> 00:00:59,490
which means there are many
different genes likely involved,

24
00:00:59,490 --> 00:01:01,080
and there are complex disorders

25
00:01:01,080 --> 00:01:04,050
involving an interplay of
genetics and environment.

26
00:01:04,050 --> 00:01:06,630
So if we look here in the top right corner

27
00:01:06,630 --> 00:01:10,320
of the slide with this Venn diagram

28
00:01:10,320 --> 00:01:12,390
of nature on one side,
nurture on the other,

29
00:01:12,390 --> 00:01:15,330
this intersection here should
actually be really, really big

30
00:01:15,330 --> 00:01:18,360
because most diseases and most disorders

31
00:01:18,360 --> 00:01:20,010
that humans experience

32
00:01:20,010 --> 00:01:22,500
fall into the category of
being affected by both,

33
00:01:22,500 --> 00:01:25,350
actually almost all of them
I would venture to say,

34
00:01:25,350 --> 00:01:29,250
have components of both
to varying extents, right?

35
00:01:29,250 --> 00:01:32,250
So when we talked about heritability,

36
00:01:32,250 --> 00:01:33,750
remember that term

37
00:01:33,750 --> 00:01:36,840
that can be a bit confusing to understand.

38
00:01:36,840 --> 00:01:38,610
But when we're talking
about heritability here,

39
00:01:38,610 --> 00:01:42,420
we're trying to distinguish
the amount that has caused,

40
00:01:42,420 --> 00:01:46,500
the amount of the variability

41
00:01:46,500 --> 00:01:47,970
within that particular trait.

42
00:01:47,970 --> 00:01:50,580
So within having the disorder
or not having the disorder,

43
00:01:50,580 --> 00:01:52,320
that can be attributed to,

44
00:01:52,320 --> 00:01:54,870
specifically to genetics
versus environments.

45
00:01:54,870 --> 00:01:57,060
And you're really not seeing anything

46
00:01:57,060 --> 00:01:59,610
either being 100% or 0%.

47
00:01:59,610 --> 00:02:00,900
Everything is in between.

48
00:02:00,900 --> 00:02:03,630
It's in between, you know,
there's some of both.

49
00:02:03,630 --> 00:02:06,570
So that's where we're coming from here

50
00:02:06,570 --> 00:02:08,130
and that's what we're
trying to understand.

51
00:02:08,130 --> 00:02:10,500
It's not to say in any of this material,

52
00:02:10,500 --> 00:02:11,830
is it ever to say

53
00:02:14,585 --> 00:02:16,210
that any of these disorders

54
00:02:17,190 --> 00:02:19,470
are exclusively genetic diseases,

55
00:02:19,470 --> 00:02:21,360
meaning that a person will inherit it.

56
00:02:21,360 --> 00:02:23,040
They have, you know,

57
00:02:23,040 --> 00:02:25,530
there's nothing can be
done either for them

58
00:02:25,530 --> 00:02:28,230
or, you know, either
to prevent the disease

59
00:02:28,230 --> 00:02:29,490
or cause the disease.

60
00:02:29,490 --> 00:02:31,020
It's either going to happen
to a person or it's not.

61
00:02:31,020 --> 00:02:33,930
It's not like cystic
fibrosis, say, for example,

62
00:02:33,930 --> 00:02:35,280
or sickle cell anemia,

63
00:02:35,280 --> 00:02:38,970
where you are inheriting a
mutation from your parents

64
00:02:38,970 --> 00:02:41,760
and you will develop the disease.

65
00:02:41,760 --> 00:02:44,040
And there really isn't
anything can be done

66
00:02:44,040 --> 00:02:45,390
to prevent that from happening

67
00:02:45,390 --> 00:02:47,640
'cause that's really a
fully genetic disease.

68
00:02:49,153 --> 00:02:52,680
And it's also not like something

69
00:02:52,680 --> 00:02:55,140
that would be completely just controlled

70
00:02:55,140 --> 00:02:57,360
by the environment, right?

71
00:02:57,360 --> 00:02:59,965
I mean, it's not on one
extreme or the other.

72
00:02:59,965 --> 00:03:02,730
These psychiatric
disorders, in particular,

73
00:03:02,730 --> 00:03:06,480
fall really squarely in
between both nature and nurture

74
00:03:06,480 --> 00:03:08,530
or genetics and environment, if you will.

75
00:03:09,840 --> 00:03:11,700
When we're looking at these disorders,

76
00:03:11,700 --> 00:03:15,840
it comes back a lot to
the same pathways involved

77
00:03:15,840 --> 00:03:17,880
in disruption of
neurotransmitter signaling

78
00:03:17,880 --> 00:03:20,280
or receptors in neural cells.

79
00:03:20,280 --> 00:03:23,910
And these are regulated by
proteins coded for in our genes,

80
00:03:23,910 --> 00:03:27,270
which would be the nature
component of things, so to speak.

81
00:03:27,270 --> 00:03:30,990
And this commonly contributes
to psychiatric disorders.

82
00:03:30,990 --> 00:03:35,010
And also our neural cells, at
the same time, are programmed

83
00:03:35,010 --> 00:03:40,010
specifically to respond to
environmental cues like stress

84
00:03:40,260 --> 00:03:43,560
or a good situation or a bad situation

85
00:03:43,560 --> 00:03:45,270
or something potentially harmful

86
00:03:45,270 --> 00:03:47,670
or something potentially beneficial.

87
00:03:47,670 --> 00:03:50,460
We are programmed to be able

88
00:03:50,460 --> 00:03:51,597
to respond to that.

89
00:03:51,597 --> 00:03:52,680
And that response,

90
00:03:52,680 --> 00:03:55,350
that affects the
neurotransmitter signaling,

91
00:03:55,350 --> 00:03:58,140
it affects the receptors,
it affects the neural cells,

92
00:03:58,140 --> 00:03:59,623
and that's not genetic.

93
00:03:59,623 --> 00:04:02,460
That's in response to the environment.

94
00:04:02,460 --> 00:04:05,490
So you have both at play at the same time.

95
00:04:05,490 --> 00:04:06,630
They're both in, like,

96
00:04:06,630 --> 00:04:08,820
really intimately
connected with one another

97
00:04:08,820 --> 00:04:13,710
and affect each other to,
you know, varying degrees.

98
00:04:13,710 --> 00:04:17,790
So this is, again, this is
where we're coming from.

99
00:04:17,790 --> 00:04:20,520
Inheritance has been linked
with psychiatric disorders

100
00:04:20,520 --> 00:04:22,320
since the early 20th century.

101
00:04:22,320 --> 00:04:24,990
However, the actual
pathways and genes involved

102
00:04:24,990 --> 00:04:27,300
are only now starting to be understood.

103
00:04:27,300 --> 00:04:29,520
So while it was seen,

104
00:04:29,520 --> 00:04:34,520
it was appreciated even in,
like, you know, the early 1900s,

105
00:04:34,620 --> 00:04:37,920
that in families that have a history

106
00:04:37,920 --> 00:04:40,020
where there are individuals who present

107
00:04:40,020 --> 00:04:45,020
with schizophrenia, for
example, that there will be,

108
00:04:45,513 --> 00:04:47,520
they're more likely to have
individuals in that family

109
00:04:47,520 --> 00:04:49,170
who will also have schizophrenia.

110
00:04:49,170 --> 00:04:51,720
That it was, it seems to be inherited,

111
00:04:51,720 --> 00:04:52,920
at least to some extent.

112
00:04:54,540 --> 00:04:56,760
Now, unfortunately,

113
00:04:56,760 --> 00:05:00,300
what that also fed into
at that particular time

114
00:05:00,300 --> 00:05:02,880
in our history, not to get
too far off on a tangent,

115
00:05:02,880 --> 00:05:04,140
but just to provide you

116
00:05:04,140 --> 00:05:05,910
a little bit of historical context here,

117
00:05:05,910 --> 00:05:09,750
eugenics was actually used to,

118
00:05:09,750 --> 00:05:11,670
as sort of the rationale

119
00:05:11,670 --> 00:05:14,080
for why many individuals

120
00:05:15,600 --> 00:05:18,390
were basically, against their will,

121
00:05:18,390 --> 00:05:22,860
were put into these sanitariums

122
00:05:22,860 --> 00:05:26,280
or insane asylums, if you will,

123
00:05:26,280 --> 00:05:30,420
that again, involuntary,
against their will,

124
00:05:30,420 --> 00:05:32,880
simply because, and they
have a family history

125
00:05:32,880 --> 00:05:35,880
of having a mental illness.

126
00:05:35,880 --> 00:05:39,510
Because, say, for example,
their mother or their father,

127
00:05:39,510 --> 00:05:41,160
even some extreme examples,

128
00:05:41,160 --> 00:05:43,440
say, their mother or their
father was an alcoholic

129
00:05:43,440 --> 00:05:45,960
or had schizophrenia

130
00:05:45,960 --> 00:05:49,350
or, you know, had some issue
that they were dealing with,

131
00:05:49,350 --> 00:05:51,810
then they might, say, for example,

132
00:05:51,810 --> 00:05:54,300
that, well, since your parents had it

133
00:05:54,300 --> 00:05:55,680
or one of your parents had it,

134
00:05:55,680 --> 00:05:56,790
you are more likely to have it.

135
00:05:56,790 --> 00:05:59,910
So we're just going to go
ahead and take the step

136
00:05:59,910 --> 00:06:03,120
of putting you into an
asylum against your will

137
00:06:03,120 --> 00:06:06,000
because we know most likely
you'll develop this as well.

138
00:06:06,000 --> 00:06:08,520
And many times they didn't.
Many times they didn't.

139
00:06:08,520 --> 00:06:10,320
I mean, except for the
stress that was caused

140
00:06:10,320 --> 00:06:12,900
by being put into an
asylum against their will,

141
00:06:12,900 --> 00:06:17,580
which, no doubt, can lead
to the environmental side

142
00:06:17,580 --> 00:06:21,660
of developing different
psychiatric disorders.

143
00:06:21,660 --> 00:06:23,820
The genetics, it's not a one-to-one,

144
00:06:23,820 --> 00:06:25,170
it's not like we're looking, again,

145
00:06:25,170 --> 00:06:27,420
it's not like we're looking
at Mendelian diseases here

146
00:06:27,420 --> 00:06:30,660
where we can actually
predict exactly the risk

147
00:06:30,660 --> 00:06:32,010
of a person developing it,

148
00:06:32,010 --> 00:06:35,730
or can we say that you for sure
will develop this disorder.

149
00:06:35,730 --> 00:06:36,930
Not at all.

150
00:06:36,930 --> 00:06:39,240
And unfortunately that was the
approach taken at the time.

151
00:06:39,240 --> 00:06:42,450
And it was an extreme measure,
of course, that was taken.

152
00:06:42,450 --> 00:06:45,210
And much of it was related to,

153
00:06:45,210 --> 00:06:48,060
had underpinnings of motivations

154
00:06:48,060 --> 00:06:51,750
of racism and classism as well

155
00:06:51,750 --> 00:06:56,750
that motivated individuals to persecute

156
00:06:56,970 --> 00:07:00,430
those of particular nationalities or races

157
00:07:01,771 --> 00:07:05,046
or socioeconomic status,

158
00:07:05,046 --> 00:07:08,100
and use the justification of genetics.

159
00:07:08,100 --> 00:07:11,940
So just to remain, keep that in your mind

160
00:07:11,940 --> 00:07:14,193
that historical context of that.

161
00:07:14,193 --> 00:07:16,080
That happened in the United States

162
00:07:16,080 --> 00:07:20,250
in and around 1920s, '30s, that timeframe.

163
00:07:20,250 --> 00:07:22,110
So this was not that long ago.

164
00:07:22,110 --> 00:07:25,230
And it even happened in Vermont.

165
00:07:25,230 --> 00:07:28,650
There definitely, there's a
history of the eugenics movement

166
00:07:28,650 --> 00:07:30,180
specifically in Vermont as well.

167
00:07:30,180 --> 00:07:32,400
So if you're ever interested
in learning more about that,

168
00:07:32,400 --> 00:07:33,233
please let me know

169
00:07:33,233 --> 00:07:35,340
because I do actually
have some good resources

170
00:07:35,340 --> 00:07:38,610
that you may be interested
in reading more about.

171
00:07:38,610 --> 00:07:40,650
So let's go back to the
pathway that I mentioned,

172
00:07:40,650 --> 00:07:42,330
the neurotransmitters,

173
00:07:42,330 --> 00:07:45,450
and how this has really been associated

174
00:07:45,450 --> 00:07:48,090
with a number of different
psychiatric disorders.

175
00:07:48,090 --> 00:07:50,190
Mutations in genes that encode proteins

176
00:07:50,190 --> 00:07:54,000
involved in making sensing,
secreting, reuptaking,

177
00:07:54,000 --> 00:07:55,740
and degrading neurotransmitters

178
00:07:55,740 --> 00:07:58,320
are commonly associated
with psychiatric disorders.

179
00:07:58,320 --> 00:08:00,180
So as you can appreciate then,

180
00:08:00,180 --> 00:08:02,130
there are many different genes.

181
00:08:02,130 --> 00:08:03,600
Even though we're looking at one pathway,

182
00:08:03,600 --> 00:08:05,400
we're saying we're looking
at neurotransmitters.

183
00:08:05,400 --> 00:08:09,870
Well, it's not just the genes
that encode neurotransmitters,

184
00:08:09,870 --> 00:08:12,900
it's also the genes that encode
neurotransmitter receptors,

185
00:08:12,900 --> 00:08:14,970
the genes that encode the proteins

186
00:08:14,970 --> 00:08:17,700
that are necessary for
secreting neurotransmitters,

187
00:08:17,700 --> 00:08:19,680
those that are necessary for sensing them,

188
00:08:19,680 --> 00:08:22,800
for reuptaking them, for
all the different effects.

189
00:08:22,800 --> 00:08:24,690
I mean, we're talking
hundreds of genes here.

190
00:08:24,690 --> 00:08:28,110
This isn't a small set of,
you know, a couple of genes.

191
00:08:28,110 --> 00:08:29,820
It's many different genes,

192
00:08:29,820 --> 00:08:32,190
and they each may play a small role

193
00:08:32,190 --> 00:08:34,170
in the likelihood of developing

194
00:08:34,170 --> 00:08:35,870
a particular psychiatric disorder.

195
00:08:37,110 --> 00:08:38,550
These are also common targets

196
00:08:38,550 --> 00:08:40,560
for treating conditions like depression.

197
00:08:40,560 --> 00:08:42,840
However, these treatments
will only work in people

198
00:08:42,840 --> 00:08:45,420
who have the targeted pathway disrupted,

199
00:08:45,420 --> 00:08:47,550
leading to a future
role of genetic testing

200
00:08:47,550 --> 00:08:50,070
and targeted treatment
of psychiatric disorders.

201
00:08:50,070 --> 00:08:52,440
So, for example, you're treating someone

202
00:08:52,440 --> 00:08:56,190
who has depression with an SSRI.

203
00:08:56,190 --> 00:08:59,340
If the individual does not
actually have any issue

204
00:08:59,340 --> 00:09:01,500
with their serotonin levels,

205
00:09:01,500 --> 00:09:03,180
and in fact this was caused

206
00:09:03,180 --> 00:09:06,690
by something other than
serotonin reuptake,

207
00:09:06,690 --> 00:09:09,960
then the drug isn't actually
going to really be effective

208
00:09:09,960 --> 00:09:12,082
in that person because you're not,

209
00:09:12,082 --> 00:09:14,940
the pharmacologic agent

210
00:09:14,940 --> 00:09:17,610
isn't targeting the proper pathway.

211
00:09:17,610 --> 00:09:19,950
So while a person may have,

212
00:09:19,950 --> 00:09:22,170
you may have 10 people
who all have depression,

213
00:09:22,170 --> 00:09:25,000
they all might have
depression that's the result

214
00:09:27,231 --> 00:09:30,090
of something going wrong in
different parts of the pathway.

215
00:09:30,090 --> 00:09:31,890
And each pharmacologic agent

216
00:09:31,890 --> 00:09:35,430
may only target one or
two parts of the pathway.

217
00:09:35,430 --> 00:09:37,740
And if that person isn't
being affected, you know,

218
00:09:37,740 --> 00:09:40,230
doesn't have an alteration
in that part of the pathway,

219
00:09:40,230 --> 00:09:42,390
then the drug's really not
going to have an effect.

220
00:09:42,390 --> 00:09:46,890
And I think that contributes
a lot to why there is

221
00:09:46,890 --> 00:09:50,640
failure to respond to certain
therapies in individuals,

222
00:09:50,640 --> 00:09:53,460
and it can take a while to find
the right therapy for them.

223
00:09:53,460 --> 00:09:56,970
So the hope is that in
the future, certainly,

224
00:09:56,970 --> 00:09:58,980
with the increased information

225
00:09:58,980 --> 00:10:01,680
that we'll have from
research and genetics,

226
00:10:01,680 --> 00:10:03,960
and better development of genetic testing,

227
00:10:03,960 --> 00:10:05,760
potentially we can come up

228
00:10:05,760 --> 00:10:08,370
with those targeted treatments
for psychiatric disorders

229
00:10:08,370 --> 00:10:12,330
similar to what we're
experiencing now in oncology,

230
00:10:12,330 --> 00:10:13,953
where we talked about last week,

231
00:10:16,445 --> 00:10:19,890
where you have those very
specific targeted therapies,

232
00:10:19,890 --> 00:10:22,770
say, for example,
targeting the EGF receptor

233
00:10:22,770 --> 00:10:25,140
when it's being overexpressed
or overactivated.

234
00:10:25,140 --> 00:10:27,090
We know a specific person, you know,

235
00:10:27,090 --> 00:10:29,280
we can take a biopsy of a person's tumor,

236
00:10:29,280 --> 00:10:32,670
we can identify, yes, they have a mutation

237
00:10:32,670 --> 00:10:35,220
or a duplication that's
leading to EGF receptor

238
00:10:35,220 --> 00:10:36,960
being overactivated.

239
00:10:36,960 --> 00:10:38,700
So this therapy will work.

240
00:10:38,700 --> 00:10:40,050
The hope is that in the future,

241
00:10:40,050 --> 00:10:43,200
and I think this is a reasonable
hope, that in the future,

242
00:10:43,200 --> 00:10:46,650
we'll be able to do something
similar for individuals

243
00:10:46,650 --> 00:10:48,090
with psychiatric disorders.

244
00:10:48,090 --> 00:10:49,770
Certainly in that case,

245
00:10:49,770 --> 00:10:52,200
what we would likely
be looking at would be

246
00:10:52,200 --> 00:10:54,150
a germline mutation.

247
00:10:54,150 --> 00:10:55,530
So it's something that they've inherited,

248
00:10:55,530 --> 00:10:56,670
and as opposed to cancer

249
00:10:56,670 --> 00:11:00,750
where it's gonna be different
in every person's cell.

250
00:11:00,750 --> 00:11:03,060
In this case, you could actually take

251
00:11:03,060 --> 00:11:05,460
just a cheek swab, spit sample, whatever,

252
00:11:05,460 --> 00:11:07,290
and test their DNA,

253
00:11:07,290 --> 00:11:10,500
and look for maybe
disruption of certain genes

254
00:11:10,500 --> 00:11:12,270
that are related to specific pathways

255
00:11:12,270 --> 00:11:14,700
so that now we can find
targeted therapeutics.

256
00:11:14,700 --> 00:11:16,800
And as I'm sure you can appreciate,

257
00:11:16,800 --> 00:11:18,120
the faster you get someone

258
00:11:18,120 --> 00:11:20,250
on an effective pharmacologic therapy

259
00:11:20,250 --> 00:11:22,110
for something like depression

260
00:11:22,110 --> 00:11:23,940
or any of these psychiatric disorders,

261
00:11:23,940 --> 00:11:25,527
the more effective it's going to be

262
00:11:25,527 --> 00:11:27,773
and the better it's going
to be for that patient.

263
00:11:29,100 --> 00:11:31,590
So connections between
different psychiatric disorders,

264
00:11:31,590 --> 00:11:32,940
this was an interesting paper

265
00:11:32,940 --> 00:11:34,470
that was published in Nature Genetics,

266
00:11:34,470 --> 00:11:37,050
and they were looking at
heritability of schizophrenia,

267
00:11:37,050 --> 00:11:40,350
bipolar disorder, ADHD, autism, and MDD

268
00:11:40,350 --> 00:11:43,710
in a large and diverse population pool.

269
00:11:43,710 --> 00:11:46,050
So not only were they looking at,

270
00:11:46,050 --> 00:11:48,030
again, remember what heritability is?

271
00:11:48,030 --> 00:11:51,900
Heritability is looking at the,

272
00:11:51,900 --> 00:11:54,390
it's sort of like those twin
studies that we talked about.

273
00:11:54,390 --> 00:11:58,350
So what portion of the variants
that we see in a population

274
00:11:58,350 --> 00:12:01,170
can be attributed to genetic variation

275
00:12:01,170 --> 00:12:03,870
as opposed to environment.

276
00:12:03,870 --> 00:12:05,160
So what we see here is,

277
00:12:05,160 --> 00:12:07,620
you can see on the right
hand side in the graph

278
00:12:07,620 --> 00:12:09,210
that they showed in that paper,

279
00:12:09,210 --> 00:12:14,210
ADHD, bipolar, schizophrenia,
MDD, autism spectrum disorder

280
00:12:14,340 --> 00:12:17,940
are all quite heritable on their own.

281
00:12:17,940 --> 00:12:20,100
They have heritability anywhere

282
00:12:20,100 --> 00:12:24,690
from about 15% to about 30%.

283
00:12:24,690 --> 00:12:27,150
And this is heritability attributed

284
00:12:27,150 --> 00:12:30,060
to the specific single
nucleotide polymorphisms

285
00:12:30,060 --> 00:12:30,893
that they were exploring.

286
00:12:30,893 --> 00:12:33,540
This is not total heritability. Okay?

287
00:12:33,540 --> 00:12:34,950
So let's make an important
distinction here.

288
00:12:34,950 --> 00:12:35,857
So when you look at this and you say,

289
00:12:35,857 --> 00:12:39,600
"Well, wait, this is showing
that autism spectrum disorder

290
00:12:39,600 --> 00:12:42,150
has a heritability of only 15%."

291
00:12:42,150 --> 00:12:44,610
Well, no, that's 15%
that can be attributed

292
00:12:44,610 --> 00:12:47,790
to these specific single
nucleotide polymorphisms

293
00:12:47,790 --> 00:12:49,200
that they were exploring.

294
00:12:49,200 --> 00:12:52,500
So this was not really, the
study was not done with twins,

295
00:12:52,500 --> 00:12:57,420
it was actually done looking
at specific sequences

296
00:12:57,420 --> 00:13:00,640
that they thought might be involved

297
00:13:01,928 --> 00:13:03,810
in developing these disorders.

298
00:13:03,810 --> 00:13:06,430
Mostly because they are commonly

299
00:13:07,500 --> 00:13:09,210
variants in the population.

300
00:13:09,210 --> 00:13:12,750
And what what I mean by that
is that if you look within,

301
00:13:12,750 --> 00:13:15,780
say, 100 people, and you look
within the stretch of DNA,

302
00:13:15,780 --> 00:13:17,640
there's a high likelihood
that any two people

303
00:13:17,640 --> 00:13:21,300
will have actually different
sequences at that location

304
00:13:21,300 --> 00:13:24,810
as opposed to the average
region of our genomes

305
00:13:24,810 --> 00:13:26,790
where we compare to one another

306
00:13:26,790 --> 00:13:29,760
and we'll see that they're
like exactly the same.

307
00:13:29,760 --> 00:13:32,220
In certain stretches, they're
more likely to be different.

308
00:13:32,220 --> 00:13:34,170
And so they're looking at those stretches,

309
00:13:34,170 --> 00:13:37,130
which are called common SNPs

310
00:13:37,130 --> 00:13:39,960
or common single nucleotide polymorphisms.

311
00:13:39,960 --> 00:13:42,210
And so they just looked at some of those.

312
00:13:42,210 --> 00:13:44,940
And that means that

313
00:13:44,940 --> 00:13:46,770
when we look at the
heritability estimates here,

314
00:13:46,770 --> 00:13:48,240
this is not total heritability,

315
00:13:48,240 --> 00:13:52,050
this is heritability that can
be attributed to these SNPs,

316
00:13:52,050 --> 00:13:53,220
to these specific SNPs.

317
00:13:53,220 --> 00:13:54,540
What does that tell us?

318
00:13:54,540 --> 00:13:57,330
It tells us that these
SNPs don't, are not,

319
00:13:57,330 --> 00:14:02,050
the total contribution of the genetic part

320
00:14:04,398 --> 00:14:07,200
of development of these
different diseases.

321
00:14:07,200 --> 00:14:11,190
So that means there are
other stretches of DNA

322
00:14:11,190 --> 00:14:12,330
that they did not look at

323
00:14:12,330 --> 00:14:14,220
that are contributing in some way

324
00:14:14,220 --> 00:14:17,520
to the developments of these disorders.

325
00:14:17,520 --> 00:14:20,700
Okay, hopefully that's pretty clear.

326
00:14:20,700 --> 00:14:23,490
So again, this is not total heritability

327
00:14:23,490 --> 00:14:25,020
because it's not based on twin studies.

328
00:14:25,020 --> 00:14:28,560
This is heritability based
only on the select SNPs

329
00:14:28,560 --> 00:14:31,020
that they decided to look at in the study.

330
00:14:31,020 --> 00:14:33,960
But what they did find, which
was kind of interesting,

331
00:14:33,960 --> 00:14:37,061
was that there are some co-heritabilities,

332
00:14:37,061 --> 00:14:37,950
and what does that mean?

333
00:14:37,950 --> 00:14:39,690
Well, that is actually telling us

334
00:14:39,690 --> 00:14:43,470
that certain of these
SNPs that they looked at

335
00:14:43,470 --> 00:14:45,180
can not only increase the likelihood

336
00:14:45,180 --> 00:14:46,350
of one of these diseases,

337
00:14:46,350 --> 00:14:47,820
but can actually increase the likelihood

338
00:14:47,820 --> 00:14:51,930
of maybe two or more of these
different diseases together.

339
00:14:51,930 --> 00:14:54,380
So a single gene or, you know,

340
00:14:54,380 --> 00:14:56,670
in this case there are
several different genes

341
00:14:56,670 --> 00:14:57,750
that this applies to,

342
00:14:57,750 --> 00:15:00,660
but, say, a single gene
can actually increase

343
00:15:00,660 --> 00:15:03,510
not just the likelihood of
developing schizophrenia,

344
00:15:03,510 --> 00:15:05,010
but can also increase the likelihood

345
00:15:05,010 --> 00:15:07,320
of developing bipolar disorder.

346
00:15:07,320 --> 00:15:09,570
And why do we really care about this?

347
00:15:09,570 --> 00:15:12,210
Well, it tells us a couple
of interesting things.

348
00:15:12,210 --> 00:15:15,750
It tells us that for one thing,

349
00:15:15,750 --> 00:15:19,050
potentially someone who is
at risk for schizophrenia

350
00:15:19,050 --> 00:15:21,870
is also at a higher risk for
developing bipolar disorder

351
00:15:21,870 --> 00:15:24,510
because they seem to
share similar pathways,

352
00:15:24,510 --> 00:15:27,810
but also tells us the molecular
etiology of these disorders

353
00:15:27,810 --> 00:15:29,250
may have some overlap.

354
00:15:29,250 --> 00:15:33,180
So while clinically we define
them as two separate diseases,

355
00:15:33,180 --> 00:15:36,600
they're actually, you know,
it's probably some spectrum

356
00:15:36,600 --> 00:15:40,230
that they're part of
the same disease family

357
00:15:40,230 --> 00:15:42,180
from a molecular perspective.

358
00:15:42,180 --> 00:15:43,710
But from a phenotype perspective,

359
00:15:43,710 --> 00:15:45,150
when we actually look at two patients,

360
00:15:45,150 --> 00:15:47,430
we define them as two separate diseases,

361
00:15:47,430 --> 00:15:49,380
Schizophrenia, bipolar disorder.

362
00:15:49,380 --> 00:15:52,470
But really it's more shades of gray.

363
00:15:52,470 --> 00:15:53,790
It's not that black and white.

364
00:15:53,790 --> 00:15:57,270
Because they share similar
genes, they share the same genes.

365
00:15:57,270 --> 00:15:59,970
In some cases that will contribute

366
00:15:59,970 --> 00:16:01,560
to either of these diseases.

367
00:16:01,560 --> 00:16:03,990
So what would make a
person become schizophrenic

368
00:16:03,990 --> 00:16:07,740
versus developing bipolar disorder?

369
00:16:07,740 --> 00:16:11,070
Well, we don't really know,
but that probably has,

370
00:16:11,070 --> 00:16:14,610
you can probably attribute
a lot of that to environment

371
00:16:14,610 --> 00:16:17,820
and also the combination
of the other genes

372
00:16:17,820 --> 00:16:20,550
that are involved in
inheriting that disorder.

373
00:16:20,550 --> 00:16:23,100
Remember there are 30, 40, 50, 60,

374
00:16:23,100 --> 00:16:24,300
however many different genes

375
00:16:24,300 --> 00:16:27,420
that may be implicated in
each of these diseases.

376
00:16:27,420 --> 00:16:29,940
While they may share some of those genes,

377
00:16:29,940 --> 00:16:30,810
there are other genes

378
00:16:30,810 --> 00:16:35,130
that only will contribute
to bipolar disorder

379
00:16:35,130 --> 00:16:37,410
or only will contribute to schizophrenia.

380
00:16:37,410 --> 00:16:39,660
And so it's those combinations

381
00:16:39,660 --> 00:16:41,730
of the different variants in those genes

382
00:16:41,730 --> 00:16:43,320
that will likely push a person

383
00:16:43,320 --> 00:16:45,180
more towards one or the other,

384
00:16:45,180 --> 00:16:48,300
in addition to their
environmental influences.

385
00:16:48,300 --> 00:16:50,610
Plus then we have to consider,

386
00:16:50,610 --> 00:16:51,810
again, it's not black and white.

387
00:16:51,810 --> 00:16:53,670
It's not schizophrenia
and bipolar disorder,

388
00:16:53,670 --> 00:16:55,650
two completely different diseases.

389
00:16:55,650 --> 00:16:58,803
They're actually, they share
some molecular pathways.

390
00:17:01,740 --> 00:17:04,410
So let's go back to, for
a moment, to epigenetics.

391
00:17:04,410 --> 00:17:06,990
You all remember that, hopefully
very fondly, (chuckles)

392
00:17:06,990 --> 00:17:09,360
from our earlier modules when we talked

393
00:17:09,360 --> 00:17:12,900
about DNA methylation and
histone modifications.

394
00:17:12,900 --> 00:17:17,310
So DNA methylation has
been really a hot topic

395
00:17:17,310 --> 00:17:19,260
in the psychiatric disorders.

396
00:17:19,260 --> 00:17:21,420
And remember the DNA methylation patterns

397
00:17:21,420 --> 00:17:23,790
are formed in our cells over our lifetime,

398
00:17:23,790 --> 00:17:25,830
especially in the first 12 years of life.

399
00:17:25,830 --> 00:17:27,960
If you look at this graph on the right,

400
00:17:27,960 --> 00:17:31,710
you see that this is the
percentage of DNA methylation

401
00:17:31,710 --> 00:17:36,150
that we have, percentage of cytosines

402
00:17:36,150 --> 00:17:38,520
that are methylated in our cells,

403
00:17:38,520 --> 00:17:41,700
depending upon the stage of our life.

404
00:17:41,700 --> 00:17:44,970
And so what we can see is that
there's this huge increase

405
00:17:44,970 --> 00:17:46,830
from when time of conception,

406
00:17:46,830 --> 00:17:48,810
when there's virtually no methylation

407
00:17:48,810 --> 00:17:53,130
to basically, you know,
one, two years old.

408
00:17:53,130 --> 00:17:54,720
And then there's another increase

409
00:17:54,720 --> 00:17:58,353
between five and 20-ish years old,

410
00:17:59,521 --> 00:18:00,990
17, 20 years old.

411
00:18:00,990 --> 00:18:04,230
And so we're accumulating
these over our lifetime.

412
00:18:04,230 --> 00:18:08,100
Remember that DNA methylation
patterns can be influenced

413
00:18:08,100 --> 00:18:11,730
by response to our environmental cues.

414
00:18:11,730 --> 00:18:13,980
So again, here's another place,

415
00:18:13,980 --> 00:18:17,940
environment and genetics
getting cozy with one another,

416
00:18:17,940 --> 00:18:20,190
affecting one another
in many different ways.

417
00:18:20,190 --> 00:18:22,590
So it's never just nature or nurture,

418
00:18:22,590 --> 00:18:24,570
it's both together all the time,

419
00:18:24,570 --> 00:18:26,100
and just affecting each other in ways

420
00:18:26,100 --> 00:18:28,260
we probably don't even
fully understand yet.

421
00:18:28,260 --> 00:18:29,093
But in this case,

422
00:18:29,093 --> 00:18:31,200
we do kind of understand a
little bit about methylation.

423
00:18:31,200 --> 00:18:34,110
So we do know that stress can,

424
00:18:34,110 --> 00:18:37,200
stress and diets,

425
00:18:37,200 --> 00:18:41,220
and sort of overall health and well-being,

426
00:18:41,220 --> 00:18:43,740
and probably other factors
we don't yet understand

427
00:18:43,740 --> 00:18:45,900
can influence methylation patterns.

428
00:18:45,900 --> 00:18:47,160
And as you can see,

429
00:18:47,160 --> 00:18:49,710
those methylation
patterns are very dynamic

430
00:18:49,710 --> 00:18:51,993
and being set in childhood.

431
00:18:53,370 --> 00:18:56,310
And let's link that back
to a recent research

432
00:18:56,310 --> 00:18:58,830
which showed specific
DNA methylation patterns

433
00:18:58,830 --> 00:19:01,410
are present in adults with PTSD

434
00:19:01,410 --> 00:19:04,050
who suffered abuse as children

435
00:19:04,050 --> 00:19:06,780
that are different from those with PTSD

436
00:19:06,780 --> 00:19:08,550
who did not experience child abuse.

437
00:19:08,550 --> 00:19:11,340
So what does this tell us?
What does this tell us?

438
00:19:11,340 --> 00:19:13,800
This tells us that child abuse

439
00:19:13,800 --> 00:19:17,070
actually affects our DNA
methylation patterns,

440
00:19:17,070 --> 00:19:21,390
which can affect the way in
which we respond to situations,

441
00:19:21,390 --> 00:19:26,390
to develop disorders or
can recover from disorders,

442
00:19:26,550 --> 00:19:29,370
how, you know, different diseases

443
00:19:29,370 --> 00:19:31,500
will actually present in us.

444
00:19:31,500 --> 00:19:34,260
All of this can be affected
by what we experience,

445
00:19:34,260 --> 00:19:36,480
especially in childhood.

446
00:19:36,480 --> 00:19:39,180
And so what the study was looking at

447
00:19:39,180 --> 00:19:41,340
was individuals who have PTSD.

448
00:19:41,340 --> 00:19:42,960
And they divided them into two groups,

449
00:19:42,960 --> 00:19:46,233
those who had experienced
child abuse, those who had not.

450
00:19:47,160 --> 00:19:49,140
And then they looked at
DNA methylation patterns

451
00:19:49,140 --> 00:19:50,670
and gene expression between those.

452
00:19:50,670 --> 00:19:52,110
And what they found was that, huh,

453
00:19:52,110 --> 00:19:54,570
well, the gene expression
levels in certain genes

454
00:19:54,570 --> 00:19:57,180
are very different between
these two individuals

455
00:19:57,180 --> 00:19:58,920
or between these two
groups of individuals,

456
00:19:58,920 --> 00:20:01,080
even though they both have PTSD.

457
00:20:01,080 --> 00:20:02,820
So what could be causing that?

458
00:20:02,820 --> 00:20:05,220
They looked then at DNA
methylation patterns

459
00:20:05,220 --> 00:20:07,860
between those two individual,
two groups of individuals.

460
00:20:07,860 --> 00:20:10,110
Well, what they found was
that they're very different.

461
00:20:10,110 --> 00:20:13,920
And that individuals who
experienced child abuse

462
00:20:13,920 --> 00:20:15,630
actually have relatively similar

463
00:20:15,630 --> 00:20:17,790
DNA methylation patterns to one another,

464
00:20:17,790 --> 00:20:20,430
presumably because of the
stress that they experienced

465
00:20:20,430 --> 00:20:22,920
during a time when their
DNA methylation patterns

466
00:20:22,920 --> 00:20:25,500
were being established and set.

467
00:20:25,500 --> 00:20:27,720
And that affects gene expression,

468
00:20:27,720 --> 00:20:31,350
which affects what the
disease etiology most likely.

469
00:20:31,350 --> 00:20:34,950
So maybe this will help to
inform how we treat PTSD,

470
00:20:34,950 --> 00:20:37,110
how we treat individuals

471
00:20:37,110 --> 00:20:39,000
who have different psychiatric disorders

472
00:20:39,000 --> 00:20:43,710
who did experience childhood
abuse or had different,

473
00:20:43,710 --> 00:20:46,050
maybe experienced malnutrition as a child

474
00:20:46,050 --> 00:20:51,000
or had different kinds of
stress in their life as a child.

475
00:20:51,000 --> 00:20:53,160
It's really fascinating to me,

476
00:20:53,160 --> 00:20:57,750
and I included another reading
on this that's related to,

477
00:20:57,750 --> 00:21:00,300
a press release that's related

478
00:21:00,300 --> 00:21:03,540
to this particular publication.

479
00:21:03,540 --> 00:21:04,560
You're more than welcome to,

480
00:21:04,560 --> 00:21:05,670
of course, read the publication.

481
00:21:05,670 --> 00:21:07,530
It just gets very detailed.

482
00:21:07,530 --> 00:21:09,390
And so I didn't include
the actual publication,

483
00:21:09,390 --> 00:21:10,980
but, of course, you're more
than welcome to look at that.

484
00:21:10,980 --> 00:21:13,170
But the press release really captures

485
00:21:13,170 --> 00:21:15,780
the impact of that study.

486
00:21:15,780 --> 00:21:18,210
And this is definitely the direction

487
00:21:18,210 --> 00:21:22,470
in which psychiatric disorder
genetic research is going.

488
00:21:22,470 --> 00:21:24,540
It's not just looking at our genetic code,

489
00:21:24,540 --> 00:21:26,763
but also looking at our epigenetic code.

490
00:21:28,710 --> 00:21:30,930
So let's take a look at
some specific disorders.

491
00:21:30,930 --> 00:21:32,700
So bipolar disorder,

492
00:21:32,700 --> 00:21:34,380
there are a number of different genes

493
00:21:34,380 --> 00:21:37,080
that have been associated
with bipolar disorder

494
00:21:37,080 --> 00:21:41,190
including COMT, which degrades
catecholamines like dopamine.

495
00:21:41,190 --> 00:21:44,250
And allelic variation can
affect emotional regulation

496
00:21:44,250 --> 00:21:47,793
through excess of dopamine
associated with mania phase.

497
00:21:49,020 --> 00:21:52,110
MAOA is another gene
which degrades serotonin.

498
00:21:52,110 --> 00:21:55,290
So an excess of serotonin
can impact reward pathways

499
00:21:55,290 --> 00:21:58,290
and lead to aggression
and emotional instability.

500
00:21:58,290 --> 00:22:00,210
There was also another paper,

501
00:22:00,210 --> 00:22:03,900
a publication that came out
that was looking at MAOA,

502
00:22:03,900 --> 00:22:07,590
and potentially its DNA
methylation patterns,

503
00:22:07,590 --> 00:22:12,480
which may be influenced
in childhood as well.

504
00:22:12,480 --> 00:22:16,893
So just to summarize briefly
what that publication showed,

505
00:22:18,180 --> 00:22:21,840
again, getting back to the
influence of childhood stress

506
00:22:21,840 --> 00:22:24,540
and childhood abuse on
DNA methylation patterns

507
00:22:24,540 --> 00:22:28,530
which can affect adult
presentation of disease,

508
00:22:28,530 --> 00:22:31,710
what they saw was that in individuals

509
00:22:31,710 --> 00:22:35,430
who were abused as children,

510
00:22:35,430 --> 00:22:39,420
that they were more likely
to be aggressive as adults.

511
00:22:39,420 --> 00:22:42,600
And also, that those individuals

512
00:22:42,600 --> 00:22:45,330
who were aggressive as adults,

513
00:22:45,330 --> 00:22:49,440
who experienced childhood abuse

514
00:22:49,440 --> 00:22:52,750
had different patterns of
methylation on their MAOA gene

515
00:22:54,270 --> 00:22:56,340
compared to individuals
who were aggressive,

516
00:22:56,340 --> 00:22:58,530
who did not experience childhood abuse

517
00:22:58,530 --> 00:23:02,070
or compared to individuals,
and so basically,

518
00:23:02,070 --> 00:23:04,620
or compared to individuals
who are not aggressive.

519
00:23:04,620 --> 00:23:07,950
That it was the abuse
itself, the childhood abuse,

520
00:23:07,950 --> 00:23:12,480
which can actually set into action

521
00:23:12,480 --> 00:23:13,410
a chain of events,

522
00:23:13,410 --> 00:23:15,480
which basically means the childhood abuse

523
00:23:15,480 --> 00:23:17,850
leads to changes in DNA
methylation patterns

524
00:23:17,850 --> 00:23:20,100
in genes like MAOA.

525
00:23:20,100 --> 00:23:22,920
And then that sets for that individual,

526
00:23:22,920 --> 00:23:24,390
for the rest of their lifetime,

527
00:23:24,390 --> 00:23:27,120
how their MAOA gene is
going to be expressed.

528
00:23:27,120 --> 00:23:28,860
And when they reach adulthood,

529
00:23:28,860 --> 00:23:31,350
their MAOA gene is misexpressed

530
00:23:31,350 --> 00:23:33,510
leading to increased aggression.

531
00:23:33,510 --> 00:23:36,960
And you can imagine the cycle of abuse

532
00:23:36,960 --> 00:23:39,570
that potentially could result from that.

533
00:23:39,570 --> 00:23:43,530
So even cycles of
childhood abuse in families

534
00:23:43,530 --> 00:23:47,010
can also be contributed
to genetic aspects.

535
00:23:47,010 --> 00:23:50,220
But those genetic aspects are determined

536
00:23:50,220 --> 00:23:53,010
or significantly
influenced by environment.

537
00:23:53,010 --> 00:23:54,660
So it's a cycle in many ways,

538
00:23:54,660 --> 00:23:56,760
like a vicious cycle that feeds on itself.

539
00:23:56,760 --> 00:23:59,790
So just an interesting perspective,

540
00:23:59,790 --> 00:24:02,010
I think, to keep in mind with that,

541
00:24:02,010 --> 00:24:05,160
and the importance of
childhood development

542
00:24:05,160 --> 00:24:07,530
and stress on children,

543
00:24:07,530 --> 00:24:09,720
not just in that phase
of their development,

544
00:24:09,720 --> 00:24:11,163
but also as adults.

545
00:24:12,120 --> 00:24:16,050
The HTR2A gene, improper
DNA methylation of this gene

546
00:24:16,050 --> 00:24:19,050
is associated with schizophrenia
and bipolar disorder.

547
00:24:19,050 --> 00:24:20,130
So there's another one

548
00:24:20,130 --> 00:24:22,650
that's has DNA methylation implicated.

549
00:24:22,650 --> 00:24:25,080
the S100B, improper gene expression

550
00:24:25,080 --> 00:24:26,910
associated with bipolar disorder.

551
00:24:26,910 --> 00:24:29,580
The mechanism for this is unclear.

552
00:24:29,580 --> 00:24:32,260
And so this gene was identified

553
00:24:33,420 --> 00:24:35,430
through some of those linkage studies

554
00:24:35,430 --> 00:24:38,130
and through some of the
genome-wide association studies.

555
00:24:38,130 --> 00:24:40,260
So it was not a candidate gene approach.

556
00:24:40,260 --> 00:24:41,850
So we don't really know why

557
00:24:41,850 --> 00:24:44,280
this particular gene would be involved

558
00:24:44,280 --> 00:24:47,970
or what it's actually
doing in bipolar disorder,

559
00:24:47,970 --> 00:24:51,273
but it has been shown to be associated.

560
00:24:52,440 --> 00:24:53,880
The CLOCK gene, you write about this

561
00:24:53,880 --> 00:24:56,490
or you will read about
this in the textbook,

562
00:24:56,490 --> 00:24:59,490
this is related to circadian rhythm,

563
00:24:59,490 --> 00:25:00,690
it's a transcription factor.

564
00:25:00,690 --> 00:25:01,860
We all remember those, right?

565
00:25:01,860 --> 00:25:04,260
Transcription factor
regulates expression of genes

566
00:25:04,260 --> 00:25:06,570
associated with circadian regulation.

567
00:25:06,570 --> 00:25:08,580
It may be associated with bipolar disorder

568
00:25:08,580 --> 00:25:09,810
and sleep disturbances,

569
00:25:09,810 --> 00:25:12,420
as well as cognitive
tasks and moral judgments.

570
00:25:12,420 --> 00:25:17,343
So you can see how this
would significantly influence

571
00:25:19,612 --> 00:25:21,240
the development and expression

572
00:25:21,240 --> 00:25:23,400
of something like bipolar disorder.

573
00:25:23,400 --> 00:25:26,100
You, if there's a mutation

574
00:25:26,100 --> 00:25:28,830
or misexpression of a
transcription factor,

575
00:25:28,830 --> 00:25:30,330
remember what those do?

576
00:25:30,330 --> 00:25:34,920
They regulate the expression
of many different genes.

577
00:25:34,920 --> 00:25:38,010
So it's like a master regulator
is what we would call this.

578
00:25:38,010 --> 00:25:39,600
So if you screw up,

579
00:25:39,600 --> 00:25:41,760
or something gets screwed
up in this master regulator,

580
00:25:41,760 --> 00:25:43,980
it's not just screwing up that one protein

581
00:25:43,980 --> 00:25:45,240
that this gene codes for,

582
00:25:45,240 --> 00:25:48,240
it's screwing up the expression
for all the different genes

583
00:25:48,240 --> 00:25:51,210
this particular transcription
factor regulates.

584
00:25:51,210 --> 00:25:52,500
And that can be a lot.

585
00:25:52,500 --> 00:25:54,660
So this is one of the biggies,

586
00:25:54,660 --> 00:25:57,813
most likely big genes that is,

587
00:25:58,830 --> 00:26:00,300
well, I should, let me rephrase.

588
00:26:00,300 --> 00:26:01,860
The size of the gene doesn't matter.

589
00:26:01,860 --> 00:26:04,650
It's the influence this gene has

590
00:26:04,650 --> 00:26:06,540
most likely is quite significant

591
00:26:06,540 --> 00:26:08,390
because it is a transcription factor.

592
00:26:09,720 --> 00:26:11,280
Major depressive disorder.

593
00:26:11,280 --> 00:26:14,310
Heritability estimated at around 38%.

594
00:26:14,310 --> 00:26:17,730
Greater heritability in
those who develop MDD early,

595
00:26:17,730 --> 00:26:18,690
before the age of 30,

596
00:26:18,690 --> 00:26:20,400
and have significant number of recurrences

597
00:26:20,400 --> 00:26:24,900
or also who have severe
symptoms associated with it,

598
00:26:24,900 --> 00:26:27,930
those seem to have a
greater genetic influence

599
00:26:27,930 --> 00:26:32,370
than major depressive disorder
that occurs later in life

600
00:26:32,370 --> 00:26:34,243
or individuals who do not have

601
00:26:34,243 --> 00:26:35,850
a significant number of recurrences.

602
00:26:35,850 --> 00:26:38,460
So more mild symptoms

603
00:26:38,460 --> 00:26:41,610
that may not have as much
of a genetic component

604
00:26:41,610 --> 00:26:44,700
as the more severe form of MDD.

605
00:26:44,700 --> 00:26:47,280
It's thought to be influenced
by over 30 different genes,

606
00:26:47,280 --> 00:26:48,810
each contributing a small amount

607
00:26:48,810 --> 00:26:51,840
to the overall susceptibility
of the person to MDD,

608
00:26:51,840 --> 00:26:54,210
in addition to environmental influences.

609
00:26:54,210 --> 00:26:55,530
And several different loci.

610
00:26:55,530 --> 00:27:00,150
And remember loci is plural for locus.

611
00:27:00,150 --> 00:27:02,820
And a locus is a location on a chromosome.

612
00:27:02,820 --> 00:27:03,653
So that's all loci is,

613
00:27:03,653 --> 00:27:05,880
it's just a specific spot on a chromosome,

614
00:27:05,880 --> 00:27:07,590
as opposed to, you know,

615
00:27:07,590 --> 00:27:09,240
there may be a gene there, it may be some,

616
00:27:09,240 --> 00:27:12,870
it may be a region that regulates
the expression of a gene,

617
00:27:12,870 --> 00:27:16,323
but that's all loci is,
just plural for locus.

618
00:27:17,790 --> 00:27:20,880
Several different loci
have been linked with MDD

619
00:27:20,880 --> 00:27:23,010
through linkage studies, remember those?

620
00:27:23,010 --> 00:27:26,670
But none have yet conclusively
identified haplotypes

621
00:27:26,670 --> 00:27:29,100
or SNPs, which can be
used for risk assessment.

622
00:27:29,100 --> 00:27:32,190
Additional research will likely
identify these soon though.

623
00:27:32,190 --> 00:27:35,280
So remember that linkage studies,

624
00:27:35,280 --> 00:27:38,040
they help to narrow us in.

625
00:27:38,040 --> 00:27:42,480
We zoom in on the regions
that may be associated,

626
00:27:42,480 --> 00:27:45,360
that have some stretch of DNA in them

627
00:27:45,360 --> 00:27:49,530
that are associated with
development of the disease.

628
00:27:49,530 --> 00:27:54,330
So this is moving forward with
major depressive disorder,

629
00:27:54,330 --> 00:27:57,360
but it hasn't yet come
all the way to fruition

630
00:27:57,360 --> 00:28:01,020
so that we can say, for example,
if you have this haplotype,

631
00:28:01,020 --> 00:28:02,430
which remember what haplotype is,

632
00:28:02,430 --> 00:28:05,640
that's a set of alleles of genes

633
00:28:05,640 --> 00:28:07,920
that are either maybe

634
00:28:07,920 --> 00:28:10,720
or are close to in proximity

635
00:28:12,554 --> 00:28:15,810
to a gene that affects the inheritance

636
00:28:15,810 --> 00:28:17,103
of a particular disorder.

637
00:28:18,090 --> 00:28:19,560
So we haven't yet reached the point

638
00:28:19,560 --> 00:28:21,870
where we know which haplotypes

639
00:28:21,870 --> 00:28:26,160
are going to be associated
with greater risk of MDD.

640
00:28:26,160 --> 00:28:29,820
Candidate genes like the SLC6A4

641
00:28:29,820 --> 00:28:33,660
and 5-HTTLPR, which
affect serotonin transport

642
00:28:33,660 --> 00:28:35,550
have been implicated in MDD,

643
00:28:35,550 --> 00:28:37,710
but no conclusive
connections have been made

644
00:28:37,710 --> 00:28:40,320
between specific alleles and risk.

645
00:28:40,320 --> 00:28:42,780
So while we think these
genes are involved,

646
00:28:42,780 --> 00:28:43,950
they most likely are involved.

647
00:28:43,950 --> 00:28:47,160
We don't really know
which genetic variance,

648
00:28:47,160 --> 00:28:49,110
so which changes in the sequence

649
00:28:49,110 --> 00:28:51,842
we can point to and say,
"Yep, if you have this,

650
00:28:51,842 --> 00:28:53,580
you are more likely to develop MDD.

651
00:28:53,580 --> 00:28:54,413
Or your risk,

652
00:28:54,413 --> 00:28:57,360
it goes up from the risk
of the general population

653
00:28:57,360 --> 00:28:59,280
to this higher risk level.

654
00:28:59,280 --> 00:29:01,290
We don't know that just yet.

655
00:29:01,290 --> 00:29:05,460
So, but progress is
absolutely rapidly occurring

656
00:29:05,460 --> 00:29:06,870
and moving in that direction.

657
00:29:06,870 --> 00:29:11,370
So feel good in knowing that hopefully

658
00:29:11,370 --> 00:29:14,700
I'm doing a decent enough job

659
00:29:14,700 --> 00:29:16,800
of giving you some background

660
00:29:16,800 --> 00:29:18,330
so that when this does come out,

661
00:29:18,330 --> 00:29:20,070
and I am telling you it will,

662
00:29:20,070 --> 00:29:22,890
and you know, again, that
five to 10 year timeframe

663
00:29:22,890 --> 00:29:25,570
for sure, we will see significant changes

664
00:29:26,454 --> 00:29:30,393
in how diseases are or
these disorders are,

665
00:29:31,380 --> 00:29:33,090
you know, the risk
assessment is conducted,

666
00:29:33,090 --> 00:29:36,000
how they're diagnosed, and
even how they're treated,

667
00:29:36,000 --> 00:29:40,260
and you will have a solid, a
foundation and understanding

668
00:29:40,260 --> 00:29:43,653
of what has gone into that research,

669
00:29:45,030 --> 00:29:47,580
and what it actually means for the patient

670
00:29:47,580 --> 00:29:48,990
and for your practice.

671
00:29:48,990 --> 00:29:50,580
So that's good to know.

672
00:29:50,580 --> 00:29:53,430
Okay, moving on.

673
00:29:53,430 --> 00:29:55,770
Substance issues and addiction.

674
00:29:55,770 --> 00:29:59,070
So (chuckles) this gets
a little bit tricky

675
00:29:59,070 --> 00:30:01,110
because, depends upon the substance,

676
00:30:01,110 --> 00:30:05,670
depends upon the level of addiction

677
00:30:05,670 --> 00:30:07,203
and abuse that's occurring.

678
00:30:08,460 --> 00:30:11,640
Yeah. So it gets very complicated.

679
00:30:11,640 --> 00:30:14,010
Not that these others are
not complicated, (chuckles)

680
00:30:14,010 --> 00:30:15,570
obviously they all are,

681
00:30:15,570 --> 00:30:19,257
but this adds whole new levels
of complications to the mix.

682
00:30:19,257 --> 00:30:22,470
But some genetic variants
affect reward pathways

683
00:30:22,470 --> 00:30:25,800
requiring more stimulation
to achieve the same effect

684
00:30:25,800 --> 00:30:29,010
achieved in others who do not
require as much stimulation.

685
00:30:29,010 --> 00:30:31,920
So this could cause people to,

686
00:30:31,920 --> 00:30:36,240
basically need to take more
of a drug, need to do more,

687
00:30:36,240 --> 00:30:38,190
need more risk taking behaviors

688
00:30:38,190 --> 00:30:40,710
in order to get the same reward effect

689
00:30:40,710 --> 00:30:43,923
that others get from
less of that behavior.

690
00:30:45,420 --> 00:30:47,430
The presence of other
psychiatric disorders,

691
00:30:47,430 --> 00:30:49,680
which themselves have genetic influences

692
00:30:49,680 --> 00:30:51,720
may lead an individual to substance abuse

693
00:30:51,720 --> 00:30:54,360
making the etiology of
addiction and substance abuse

694
00:30:54,360 --> 00:30:56,343
a very complex picture.

695
00:30:57,720 --> 00:31:02,490
Given that many of you
practice in psychiatric,

696
00:31:02,490 --> 00:31:04,170
have a psychiatric practice,

697
00:31:04,170 --> 00:31:06,600
I, you know, hope this information

698
00:31:06,600 --> 00:31:08,460
will be useful to you as well.

699
00:31:08,460 --> 00:31:10,230
But I also appreciate that, really,

700
00:31:10,230 --> 00:31:13,690
regardless of where you
practice, given that

701
00:31:15,120 --> 00:31:19,230
Vermont has one of the highest
rates of substance abuse

702
00:31:19,230 --> 00:31:23,430
of really almost any kind of
substance in the United States,

703
00:31:23,430 --> 00:31:28,430
clearly this is an issue
that I would imagine,

704
00:31:28,980 --> 00:31:31,290
maybe if not just most,

705
00:31:31,290 --> 00:31:33,540
maybe even all of you have experience

706
00:31:33,540 --> 00:31:35,640
in one way or another with your patients

707
00:31:35,640 --> 00:31:37,110
or your patients' families

708
00:31:37,110 --> 00:31:39,860
when you're talking about
addiction or substance abuse.

709
00:31:41,250 --> 00:31:44,160
So hopefully you'll find this information

710
00:31:44,160 --> 00:31:45,600
useful to some extent

711
00:31:45,600 --> 00:31:50,580
or at least can give you a
different kind of perspective

712
00:31:50,580 --> 00:31:51,510
even if you don't,

713
00:31:51,510 --> 00:31:55,653
even if your practice isn't
in strictly in psychiatry.

714
00:31:56,580 --> 00:31:59,100
But yeah, it gets very complex

715
00:31:59,100 --> 00:32:00,600
because as you can appreciate,

716
00:32:00,600 --> 00:32:02,880
having some of these other
psychiatric disorders

717
00:32:02,880 --> 00:32:05,190
can actually lead a
person to be more likely

718
00:32:05,190 --> 00:32:09,600
to start to abuse certain substances

719
00:32:09,600 --> 00:32:11,700
and as a method of coping.

720
00:32:11,700 --> 00:32:15,210
And then you get this whole mixture

721
00:32:15,210 --> 00:32:18,360
of the genetic influence
that's contributing

722
00:32:18,360 --> 00:32:21,480
to those psychiatric,
other psychiatric disorders

723
00:32:21,480 --> 00:32:25,260
that also may be influencing
the likelihood of addiction,

724
00:32:25,260 --> 00:32:27,630
simply by the fact that it
increases their likelihood

725
00:32:27,630 --> 00:32:29,700
of developing these other
psychiatric disorders.

726
00:32:29,700 --> 00:32:31,560
So it's complex.

727
00:32:31,560 --> 00:32:33,210
Craving and withdrawal are affected

728
00:32:33,210 --> 00:32:36,270
by gene expression changes due
to an adaptation of the cells

729
00:32:36,270 --> 00:32:37,770
to the presence of the substance.

730
00:32:37,770 --> 00:32:40,590
So here, this is where, you know,

731
00:32:40,590 --> 00:32:43,200
the cells can become acclimated,

732
00:32:43,200 --> 00:32:45,960
and they're not as responsive

733
00:32:45,960 --> 00:32:48,060
to the same levels of the substance

734
00:32:48,060 --> 00:32:50,850
that the individual was
introducing previously.

735
00:32:50,850 --> 00:32:53,640
So the individual starts
taking more, doing more,

736
00:32:53,640 --> 00:32:55,620
increasing it, increasing the frequency,

737
00:32:55,620 --> 00:32:57,060
increasing the amounts.

738
00:32:57,060 --> 00:33:00,390
And that can lead to substance abuse

739
00:33:00,390 --> 00:33:03,660
because they're not
getting the same reward

740
00:33:03,660 --> 00:33:08,660
they were once experiencing
in their neural pathways

741
00:33:08,910 --> 00:33:11,046
with the same amount of substance

742
00:33:11,046 --> 00:33:12,496
that that they're taking now.

743
00:33:13,680 --> 00:33:15,090
Other substance abuse conditions

744
00:33:15,090 --> 00:33:17,640
may be related to
metabolism of the substance.

745
00:33:17,640 --> 00:33:18,900
This is an interesting one.

746
00:33:18,900 --> 00:33:22,350
The ALDH and the ADH,
the alcohol dehydrogenase

747
00:33:22,350 --> 00:33:25,143
and aldehyde dehydrogenase genes function,

748
00:33:26,070 --> 00:33:28,740
any dysfunction in those
genes reduces the risk

749
00:33:28,740 --> 00:33:32,460
of alcoholism by worsening
negative effects of alcohol

750
00:33:32,460 --> 00:33:34,920
and symptoms of hangover.

751
00:33:34,920 --> 00:33:37,990
So in individuals that you might see

752
00:33:39,510 --> 00:33:41,700
who, say, for example, don't feel well

753
00:33:41,700 --> 00:33:45,660
after drinking maybe one
or two drinks of alcohol

754
00:33:45,660 --> 00:33:49,890
or who start to experience,
you know, start to get flushed

755
00:33:49,890 --> 00:33:53,190
or feel exceptionally tired

756
00:33:53,190 --> 00:33:56,460
or have a bad hangover reaction,

757
00:33:56,460 --> 00:33:59,640
those people are less likely
to actually become alcoholics

758
00:33:59,640 --> 00:34:01,913
because they feel really
bad when they drink alcohol,

759
00:34:01,913 --> 00:34:03,180
(chuckles) which kind of makes sense.

760
00:34:03,180 --> 00:34:06,420
And that's part of what has contributed

761
00:34:06,420 --> 00:34:10,140
to the differences in alcoholism

762
00:34:10,140 --> 00:34:13,290
in different races and ethnicities.

763
00:34:13,290 --> 00:34:16,380
So if you look in Asian populations,

764
00:34:16,380 --> 00:34:18,180
there's a lower risk of,

765
00:34:18,180 --> 00:34:21,210
there's a lower incidence of alcoholism.

766
00:34:21,210 --> 00:34:25,470
And that's thought to be
affected, at least in part,

767
00:34:25,470 --> 00:34:29,280
by their alcohol dehydrogenase

768
00:34:29,280 --> 00:34:31,110
and aldehyde dehydrogenase genes,

769
00:34:31,110 --> 00:34:34,710
which they don't work as well
as, they're less efficient,

770
00:34:34,710 --> 00:34:35,940
that's the word I'm looking for, sorry.

771
00:34:35,940 --> 00:34:39,780
They're less efficient than
the aldehyde dehydrogenase

772
00:34:39,780 --> 00:34:42,750
and alcohol dehydrogenase proteins

773
00:34:42,750 --> 00:34:45,810
that are found in, say, Caucasians,

774
00:34:45,810 --> 00:34:48,180
for example, on average.

775
00:34:48,180 --> 00:34:49,860
It's on average, certainly.

776
00:34:49,860 --> 00:34:52,830
So as a result, there, you have,

777
00:34:52,830 --> 00:34:56,730
you may have seen this in
individuals or experienced this,

778
00:34:56,730 --> 00:35:01,560
where someone who is of Asian heritage

779
00:35:01,560 --> 00:35:05,223
that they, it's described as the,

780
00:35:06,330 --> 00:35:07,770
I think it's called the Asian flush,

781
00:35:07,770 --> 00:35:09,810
something like that,
where, you know, they'll,

782
00:35:09,810 --> 00:35:12,840
where in, say, in a typical situation,

783
00:35:12,840 --> 00:35:16,470
this is certainly not the
case, you know, universally,

784
00:35:16,470 --> 00:35:21,030
but in typical situation,
someone of Asian heritage

785
00:35:21,030 --> 00:35:25,020
drinks one or two servings of alcohol,

786
00:35:25,020 --> 00:35:28,230
they will start to have
a reddening of the face,

787
00:35:28,230 --> 00:35:31,140
they will flush, they'll
start to not feel well.

788
00:35:31,140 --> 00:35:33,690
And that reduces

789
00:35:33,690 --> 00:35:36,300
the reward effect of alcohol.

790
00:35:36,300 --> 00:35:37,133
And so there's just, you know,

791
00:35:37,133 --> 00:35:41,043
they're a lot less likely
to become alcoholic.

792
00:35:42,180 --> 00:35:44,310
You compare that with individuals

793
00:35:44,310 --> 00:35:47,180
who have high functioning alcohol

794
00:35:47,180 --> 00:35:50,400
or aldehyde dehydrogenase proteins.

795
00:35:50,400 --> 00:35:52,710
And basically that means

796
00:35:52,710 --> 00:35:54,360
that they're able to metabolize it well.

797
00:35:54,360 --> 00:35:56,940
So they don't get the
negative effects of alcohol,

798
00:35:56,940 --> 00:35:59,580
but they do get a lot of the
positive effects of alcohol,

799
00:35:59,580 --> 00:36:03,720
and that's going to
contribute to alcoholism.

800
00:36:03,720 --> 00:36:07,170
So these genes, they don't really,

801
00:36:07,170 --> 00:36:08,370
they don't code for proteins

802
00:36:08,370 --> 00:36:10,020
that affect anything in neurons.

803
00:36:10,020 --> 00:36:11,850
It has nothing to do
with the neurons there.

804
00:36:11,850 --> 00:36:13,890
That has more to do with,
you know, in the liver,

805
00:36:13,890 --> 00:36:16,200
the liver function being able to process

806
00:36:16,200 --> 00:36:19,200
and metabolize alcohol that,

807
00:36:19,200 --> 00:36:21,210
so basically what you can
see is that, you know,

808
00:36:21,210 --> 00:36:22,410
there's many different pathways

809
00:36:22,410 --> 00:36:26,310
that can contribute to addiction

810
00:36:26,310 --> 00:36:27,460
through different ways.

811
00:36:28,950 --> 00:36:32,070
And also pharmacogenomics
could prove valuable

812
00:36:32,070 --> 00:36:34,710
in treatment as successful
naltrexone response

813
00:36:34,710 --> 00:36:37,754
in alcoholism has been
linked with a specific SNP

814
00:36:37,754 --> 00:36:42,754
in the OPRM1 gene or the
mu opioid receptor gene.

815
00:36:43,020 --> 00:36:44,370
This is an interesting one

816
00:36:44,370 --> 00:36:48,360
because it may lead in
the future to a person

817
00:36:48,360 --> 00:36:52,170
who, say, is suffering from alcoholism

818
00:36:52,170 --> 00:36:54,450
and wants to try a naltrexone treatment.

819
00:36:54,450 --> 00:36:58,547
They can be tested for the specific SNP

820
00:36:58,547 --> 00:37:02,160
in the OPRM1 gene, and
identify whether or not

821
00:37:02,160 --> 00:37:06,423
they're more or less likely
to respond well to naltrexone.

822
00:37:08,580 --> 00:37:11,550
Heritability varies but is
significant in addiction

823
00:37:11,550 --> 00:37:12,840
to different agents.

824
00:37:12,840 --> 00:37:17,840
So if we're looking at the heritability,

825
00:37:17,970 --> 00:37:21,780
remember what heritability
is, of addiction to,

826
00:37:21,780 --> 00:37:24,450
and this was based on the addictive agent,

827
00:37:24,450 --> 00:37:28,440
and looking at many
different pairs of twins,

828
00:37:28,440 --> 00:37:31,500
what you can see is that they all have,

829
00:37:31,500 --> 00:37:35,610
all seem to have some
genetic component certainly.

830
00:37:35,610 --> 00:37:38,340
Some were, potentially,
some more than others,

831
00:37:38,340 --> 00:37:41,850
like cocaine and opiates addiction,

832
00:37:41,850 --> 00:37:44,760
may have a stronger genetic
component than the others.

833
00:37:44,760 --> 00:37:46,230
Though it's tough to say,

834
00:37:46,230 --> 00:37:50,910
we'd have to understand the populations

835
00:37:50,910 --> 00:37:52,500
that were used in these studies

836
00:37:52,500 --> 00:37:54,600
to better know how to interpret the data.

837
00:37:54,600 --> 00:37:57,550
But what we can say is that it
definitely appears as though

838
00:37:58,650 --> 00:38:02,710
each of these substance abuse conditions

839
00:38:03,600 --> 00:38:05,973
certainly has a genetic component to it.

840
00:38:08,460 --> 00:38:10,080
So pharmacogenomics,

841
00:38:10,080 --> 00:38:11,400
this is defined as the study

842
00:38:11,400 --> 00:38:13,710
of how drug efficacy or tolerability

843
00:38:13,710 --> 00:38:16,710
can be affected by genetic
variability in patients.

844
00:38:16,710 --> 00:38:21,570
So it's basically a way
to look at someone's,

845
00:38:21,570 --> 00:38:23,070
do a genetic test on someone.

846
00:38:23,070 --> 00:38:27,270
And the test results
can tell you, hopefully,

847
00:38:27,270 --> 00:38:29,370
whether or not this person would,

848
00:38:29,370 --> 00:38:32,790
for example, be a fast or
slow metabolizer of drug,

849
00:38:32,790 --> 00:38:35,460
and whether or not there's, you know,

850
00:38:35,460 --> 00:38:37,440
higher or lower likelihoods

851
00:38:37,440 --> 00:38:40,203
that they will have certain drug,

852
00:38:41,400 --> 00:38:44,343
negative drug interactions
that might be harmful to them.

853
00:38:45,570 --> 00:38:46,530
So how do they do this?

854
00:38:46,530 --> 00:38:48,960
Well, they're looking at genes

855
00:38:48,960 --> 00:38:53,960
in the cytochrome P450 family,
cytochrome P450 enzymes.

856
00:38:54,030 --> 00:38:57,843
So enzymes are just proteins
that have a specific function.

857
00:38:59,190 --> 00:39:02,010
So cytochrome P450 enzymes are responsible

858
00:39:02,010 --> 00:39:04,500
for phase one metabolism
of many different drugs,

859
00:39:04,500 --> 00:39:05,880
including antidepressants.

860
00:39:05,880 --> 00:39:10,260
And they, I mean, just the
list is massively long.

861
00:39:10,260 --> 00:39:13,890
You can look it up online for which drugs

862
00:39:13,890 --> 00:39:17,370
are affected by the
cytochrome P450 enzymes.

863
00:39:17,370 --> 00:39:20,340
But I'll tell you it's
most of them actually.

864
00:39:20,340 --> 00:39:23,860
So this is just basic drug metabolism

865
00:39:24,720 --> 00:39:25,553
in the body.

866
00:39:25,553 --> 00:39:27,540
It's not anything targeted
or anything like that,

867
00:39:27,540 --> 00:39:29,790
it's just breaking down the drug.

868
00:39:29,790 --> 00:39:32,750
So allelic variants in the different,

869
00:39:32,750 --> 00:39:35,910
so it's the shorthand for it is CYP450.

870
00:39:35,910 --> 00:39:39,930
So in the different CYP450 category

871
00:39:39,930 --> 00:39:41,520
or family of genes

872
00:39:41,520 --> 00:39:45,010
can affect a person's
individual metabolism

873
00:39:45,960 --> 00:39:47,220
of many different drugs.

874
00:39:47,220 --> 00:39:49,110
Some are rapid or ultra rapid

875
00:39:49,110 --> 00:39:51,510
or even slow metabolizers
or anywhere in between.

876
00:39:51,510 --> 00:39:54,090
And this information, as
you can imagine is really,

877
00:39:54,090 --> 00:39:56,790
can be really useful when deciding dosage

878
00:39:56,790 --> 00:39:58,203
to start a person on.

879
00:39:59,430 --> 00:40:02,220
Some tricyclic antidepressants
and anti-convulsants

880
00:40:02,220 --> 00:40:04,740
have been shown to induce or inhibit

881
00:40:04,740 --> 00:40:07,380
the activity of the CYP450 proteins.

882
00:40:07,380 --> 00:40:10,140
And in combination with a
rapid or slow metabolizer

883
00:40:10,140 --> 00:40:12,270
could lead to drug interactions.

884
00:40:12,270 --> 00:40:16,110
So you can imagine that
this could be a real problem

885
00:40:16,110 --> 00:40:18,630
if taking a tricyclic antidepressant

886
00:40:18,630 --> 00:40:21,100
either amped up or reduced

887
00:40:22,920 --> 00:40:25,500
this class of proteins, these CYP450s,

888
00:40:25,500 --> 00:40:29,220
induced or inhibited their
ability to metabolize

889
00:40:29,220 --> 00:40:31,530
all sorts of drugs, not
just the tricyclics,

890
00:40:31,530 --> 00:40:34,320
but any other drug that
a person might be taking,

891
00:40:34,320 --> 00:40:36,150
that could lead to a drug interaction

892
00:40:36,150 --> 00:40:38,190
because the tricyclic that you're taking,

893
00:40:38,190 --> 00:40:40,290
slowing down or speeding up metabolism

894
00:40:40,290 --> 00:40:41,850
of all the other drugs they're taking,

895
00:40:41,850 --> 00:40:44,370
which could lead to, if, for example,

896
00:40:44,370 --> 00:40:45,900
its slowed down metabolism

897
00:40:45,900 --> 00:40:48,330
could lead to a higher accumulation

898
00:40:48,330 --> 00:40:51,150
of the effective amount of the drug

899
00:40:51,150 --> 00:40:53,100
that's in a person's system,

900
00:40:53,100 --> 00:40:55,890
and could lead to basically
overdose for that person.

901
00:40:55,890 --> 00:41:00,093
Or if it's slow, if it
sped up there, the CYP450,

902
00:41:01,238 --> 00:41:02,970
it could just metabolize the drug too fast

903
00:41:02,970 --> 00:41:07,230
and then the level of the
drug they have in their system

904
00:41:07,230 --> 00:41:09,363
is going to be too low to be effective.

905
00:41:11,370 --> 00:41:12,930
Individual drug metabolism.

906
00:41:12,930 --> 00:41:14,760
So as I'm sure you're all aware,

907
00:41:14,760 --> 00:41:17,970
over 100,000 deaths and
2.2 million serious events

908
00:41:17,970 --> 00:41:22,050
occur each year in the US due
to adverse drug reactions.

909
00:41:22,050 --> 00:41:24,510
This correlates individual
genetic variation

910
00:41:24,510 --> 00:41:26,370
with individual drug metabolism

911
00:41:26,370 --> 00:41:29,280
to personalized dosing
and therapy selection.

912
00:41:29,280 --> 00:41:31,860
And it's focused on
individual drug metabolism

913
00:41:31,860 --> 00:41:34,440
and interactions to minimize
those adverse events

914
00:41:34,440 --> 00:41:36,750
and maximize efficacy.

915
00:41:36,750 --> 00:41:39,810
Over 100 drugs approved by the
FDA require genetic testing

916
00:41:39,810 --> 00:41:42,240
to determine dosing or therapy selection.

917
00:41:42,240 --> 00:41:43,920
And the common genes tested include

918
00:41:43,920 --> 00:41:47,040
the cytochrome P450
genes for drug metabolism

919
00:41:47,040 --> 00:41:50,370
and also the G6PD set of genes,

920
00:41:50,370 --> 00:41:53,703
which can affect drug interaction.

921
00:41:54,720 --> 00:41:58,290
Let's look at an example here
of one of the CYP450 genes.

922
00:41:58,290 --> 00:42:00,987
And so CYP450 is a class of genes,

923
00:42:00,987 --> 00:42:04,050
and there are many genes
that fall into that category.

924
00:42:04,050 --> 00:42:06,990
This is one of them, which is CYP2D6.

925
00:42:06,990 --> 00:42:09,150
Genetic variants are common

926
00:42:09,150 --> 00:42:13,590
and effect metabolism of
about 25% of all drugs.

927
00:42:13,590 --> 00:42:16,560
So like anything you would
ever prescribe for a patient,

928
00:42:16,560 --> 00:42:20,040
25% of them are going to be metabolized

929
00:42:20,040 --> 00:42:23,010
in part by this one gene,

930
00:42:23,010 --> 00:42:25,350
by the protein encoded by this one gene.

931
00:42:25,350 --> 00:42:28,140
That's pretty, it makes
it pretty important gene,

932
00:42:28,140 --> 00:42:31,230
and probably important
for a patient to know

933
00:42:31,230 --> 00:42:32,500
what his or her

934
00:42:35,100 --> 00:42:37,560
genetic variant is so that
they can better understand

935
00:42:37,560 --> 00:42:38,670
whether they are going to be

936
00:42:38,670 --> 00:42:42,210
a slow, intermediate,
normal or rapid metabolizer.

937
00:42:42,210 --> 00:42:47,210
And this is a diagram basically
showing what can happen

938
00:42:47,790 --> 00:42:50,333
for, say, for example, a slow metabolizer,

939
00:42:50,333 --> 00:42:52,230
and this represents about
10% of the population.

940
00:42:52,230 --> 00:42:54,900
So these are all actually
very common variants.

941
00:42:54,900 --> 00:42:56,700
So it's not as though it's a rarity.

942
00:42:56,700 --> 00:42:59,640
One out of 10,000 people
will be a slow metabolizer.

943
00:42:59,640 --> 00:43:01,290
No, it's 10%.

944
00:43:01,290 --> 00:43:06,180
10% of people have a variant
in their CYP2D6 gene,

945
00:43:06,180 --> 00:43:08,790
which slows down their
metabolism of the drugs

946
00:43:08,790 --> 00:43:12,840
that are metabolized
through this CYP2D6 pathway.

947
00:43:12,840 --> 00:43:16,380
What happens is that you
can, basically over time,

948
00:43:16,380 --> 00:43:19,800
can accumulate a toxic
dose of the drug or drugs

949
00:43:19,800 --> 00:43:22,410
that are present in the person.

950
00:43:22,410 --> 00:43:25,920
Then in the intermediate,
normal levels, you have,

951
00:43:25,920 --> 00:43:27,940
this is where about

952
00:43:29,490 --> 00:43:32,310
80% of folks fall into this category.

953
00:43:32,310 --> 00:43:34,350
And for those people,

954
00:43:34,350 --> 00:43:36,570
you know, it's generally okay.

955
00:43:36,570 --> 00:43:40,800
It may be sort of on the high side of the

956
00:43:40,800 --> 00:43:45,270
level of drug that is in the
body for the intermediates,

957
00:43:45,270 --> 00:43:48,150
but in any case, it still would be helpful

958
00:43:48,150 --> 00:43:50,700
to have that information for folks

959
00:43:50,700 --> 00:43:53,010
when you're prescribing drugs.

960
00:43:53,010 --> 00:43:56,340
Rapid metabolizers or even
ultra rapid metabolizers

961
00:43:56,340 --> 00:43:58,950
are about 7% of the population.

962
00:43:58,950 --> 00:44:00,810
And these folks will basically

963
00:44:00,810 --> 00:44:03,300
just metabolize the drug really quickly.

964
00:44:03,300 --> 00:44:05,910
So they're not, they don't
keep enough of it around.

965
00:44:05,910 --> 00:44:08,310
So the drug may be less effective.

966
00:44:08,310 --> 00:44:10,710
The concern with those
who are slow metabolizers

967
00:44:10,710 --> 00:44:12,180
would be safety concern,

968
00:44:12,180 --> 00:44:15,630
that potentially they're going to have

969
00:44:15,630 --> 00:44:18,930
present in their body a
toxic dosage of the drug.

970
00:44:18,930 --> 00:44:20,160
For the rapid metabolizers,

971
00:44:20,160 --> 00:44:21,690
the concern is more about efficacy,

972
00:44:21,690 --> 00:44:23,100
that they're not gonna have enough of it

973
00:44:23,100 --> 00:44:25,300
for the drug to do what
it's supposed to do.

974
00:44:26,940 --> 00:44:28,350
So what can you do with this information,

975
00:44:28,350 --> 00:44:29,850
not just about pharmacogenomics,

976
00:44:29,850 --> 00:44:33,060
but about all, everything we've
been talking about so far?

977
00:44:33,060 --> 00:44:35,370
Well, okay, so here's the
bottom line right now.

978
00:44:35,370 --> 00:44:37,110
No genetic tests are yet available

979
00:44:37,110 --> 00:44:39,210
for susceptibility to or etiology

980
00:44:39,210 --> 00:44:41,400
of bipolar disorder or MDD.

981
00:44:41,400 --> 00:44:43,560
However, this may change
in the next five years.

982
00:44:43,560 --> 00:44:48,000
So again, I really do believe
this is on the horizon.

983
00:44:48,000 --> 00:44:51,120
But as of right now,
there's no real guideline

984
00:44:51,120 --> 00:44:54,360
and no consistent genetic
test that's available

985
00:44:54,360 --> 00:44:58,840
that that's reliable, that's
been shown to be useful

986
00:45:00,129 --> 00:45:03,750
for basically diagnosing
or understanding the risk

987
00:45:03,750 --> 00:45:06,060
for some of these psychiatric disorders.

988
00:45:06,060 --> 00:45:07,380
Genetic tests are available

989
00:45:07,380 --> 00:45:09,300
to determine the alleles a patient has

990
00:45:09,300 --> 00:45:12,990
for various CYP450 genes known
to influence drug metabolism.

991
00:45:12,990 --> 00:45:15,450
And this may be useful in many
different clinical settings

992
00:45:15,450 --> 00:45:17,370
when considering dosage
and therapy selection.

993
00:45:17,370 --> 00:45:21,660
So even if you're not in
the psychiatric practice,

994
00:45:21,660 --> 00:45:24,630
I mean, this has to be, I would imagine,

995
00:45:24,630 --> 00:45:27,780
something that will come
up in really any practice,

996
00:45:27,780 --> 00:45:31,770
because those CYP450 genes are involved

997
00:45:31,770 --> 00:45:34,167
in metabolism of drugs
across the spectrum.

998
00:45:34,167 --> 00:45:36,039
And like, I mean, it's just,

999
00:45:36,039 --> 00:45:38,370
almost all drugs are metabolized

1000
00:45:38,370 --> 00:45:39,507
through one of these pathways.

1001
00:45:39,507 --> 00:45:41,700
And so this information can be helpful,

1002
00:45:41,700 --> 00:45:43,683
especially when getting the,

1003
00:45:44,790 --> 00:45:47,250
when there's that narrow window

1004
00:45:47,250 --> 00:45:50,910
between effective dose
and toxic dose for a drug,

1005
00:45:50,910 --> 00:45:52,530
it's going to really be useful

1006
00:45:52,530 --> 00:45:56,313
to, I would think, understand a person's,

1007
00:45:57,180 --> 00:45:59,880
you know, genetic predisposition

1008
00:45:59,880 --> 00:46:02,830
towards being a fast or slow metabolizer

1009
00:46:05,640 --> 00:46:08,610
through genetic testing
for their CYP450 genes.

1010
00:46:08,610 --> 00:46:10,560
And there are certain drugs

1011
00:46:10,560 --> 00:46:12,660
that actually really do require

1012
00:46:12,660 --> 00:46:13,830
that kind of genetic testing.

1013
00:46:13,830 --> 00:46:16,740
For example, warfarin does
require genetic testing,

1014
00:46:16,740 --> 00:46:17,820
not for CYP450,

1015
00:46:17,820 --> 00:46:19,080
but for another gene

1016
00:46:19,080 --> 00:46:22,350
that's directly involved
in its metabolism.

1017
00:46:22,350 --> 00:46:24,810
And there are other drugs

1018
00:46:24,810 --> 00:46:27,160
where on the label it
is certainly recommended

1019
00:46:28,299 --> 00:46:30,870
that a genetic test be completed

1020
00:46:30,870 --> 00:46:33,690
in order to better understand the dosing

1021
00:46:33,690 --> 00:46:36,480
that would be appropriate for a patient.

1022
00:46:36,480 --> 00:46:38,400
So what else can you do
with this information?

1023
00:46:38,400 --> 00:46:40,230
Educating patients on mood disorders

1024
00:46:40,230 --> 00:46:43,200
being complex diseases
affected by many factors,

1025
00:46:43,200 --> 00:46:45,060
including genetics and environment,

1026
00:46:45,060 --> 00:46:46,830
may be important for those who deem them

1027
00:46:46,830 --> 00:46:48,780
as character flaws.

1028
00:46:48,780 --> 00:46:50,940
But it is, of course, important to include

1029
00:46:50,940 --> 00:46:53,490
psychiatric disorders, and
family history, and pedigrees,

1030
00:46:53,490 --> 00:46:56,610
and is critical to identify
possible increased risk

1031
00:46:56,610 --> 00:47:00,240
for the patient just so that
they can have greater awareness

1032
00:47:00,240 --> 00:47:01,833
and can stay on top of it.

1033
00:47:03,480 --> 00:47:05,400
But on the other side of that,

1034
00:47:05,400 --> 00:47:08,820
genetic risk simply alerts a
patient to, and his clinician,

1035
00:47:08,820 --> 00:47:11,400
or his or her clinician to
maintain greater awareness

1036
00:47:11,400 --> 00:47:13,560
of signs and symptoms of the disorder.

1037
00:47:13,560 --> 00:47:14,940
And while nothing can be done

1038
00:47:14,940 --> 00:47:16,410
to change a person's genetic risk,

1039
00:47:16,410 --> 00:47:18,780
environmental influences
have a strong impact

1040
00:47:18,780 --> 00:47:20,580
on all psychiatric disorders,

1041
00:47:20,580 --> 00:47:22,260
and they may be modified.

1042
00:47:22,260 --> 00:47:25,680
Focusing on environmental
aspects may be most productive

1043
00:47:25,680 --> 00:47:27,240
because it gives you something to do,

1044
00:47:27,240 --> 00:47:29,520
something that they can affect.

1045
00:47:29,520 --> 00:47:32,010
Knowing about a genetic risk
for psychiatric disorder

1046
00:47:32,010 --> 00:47:34,890
may elicit anxiety, depression,

1047
00:47:34,890 --> 00:47:36,720
embarrassment, and hopelessness,

1048
00:47:36,720 --> 00:47:39,390
which can worsen the
patient's mental state.

1049
00:47:39,390 --> 00:47:41,580
Certainly others may
feel relief, take solace

1050
00:47:41,580 --> 00:47:42,930
or make better informed decisions

1051
00:47:42,930 --> 00:47:44,830
when they know more about their risks.

1052
00:47:46,524 --> 00:47:48,663
So this is, of course, a judgment call,

1053
00:47:50,355 --> 00:47:54,090
and one that is specific to, you know,

1054
00:47:54,090 --> 00:47:55,173
to each patient.

1055
00:47:56,490 --> 00:47:57,870
So let's summarize

1056
00:47:57,870 --> 00:48:01,680
some of what we talked
about in this lecture.

1057
00:48:01,680 --> 00:48:04,050
Differences in sequences
or expression of genes

1058
00:48:04,050 --> 00:48:05,790
that are involved in neural processes

1059
00:48:05,790 --> 00:48:08,430
like emotion regulation, reward pathways,

1060
00:48:08,430 --> 00:48:11,580
circadian rhythm, and
risk-taking can all contribute

1061
00:48:11,580 --> 00:48:14,220
to the development of
a psychiatric disorder.

1062
00:48:14,220 --> 00:48:15,870
However, environment is well known

1063
00:48:15,870 --> 00:48:17,430
to have a significant influence,

1064
00:48:17,430 --> 00:48:19,440
and may present
opportunities for treatment,

1065
00:48:19,440 --> 00:48:22,410
intervention, or prevention
of these disorders.

1066
00:48:22,410 --> 00:48:24,390
While few genetic tests are commonly used

1067
00:48:24,390 --> 00:48:26,220
in psychiatric medicine today,

1068
00:48:26,220 --> 00:48:28,440
there will likely be an
increase in genetic testing

1069
00:48:28,440 --> 00:48:29,970
to better estimate risk,

1070
00:48:29,970 --> 00:48:32,070
to understand which therapies
will be most effective,

1071
00:48:32,070 --> 00:48:33,873
and to estimate optimal dosing.

1072
00:48:34,860 --> 00:48:37,230
And that doesn't just go
for psychiatric disorders.

1073
00:48:37,230 --> 00:48:40,239
The optimal dosing certainly
can go across the spectrum

1074
00:48:40,239 --> 00:48:42,039
of, you know, the clinical spectrum.