Skeptical analysis of claims regarding neurobiological treatments for psychiatric disorders

Skeptical Optimism in Neurobiological Experimental
Treatments for Psychiatric Disorders
A critical analysis of claims and evidence
Timothy Judge
University of Pennsylvania
June 28, 2016

SKEPTICAL OPTIMISM Page 2/32
Table of Contents
INTRODUCTION……………………………………………………………………………3
1. CLINICAL PATHOLOGICAL CORRESPONDENCE: RATIONALE FOR DEEP BRAIN STIMULATION
TARGET SELECTION
I. Introduction…………………………………………………………………..……...4
II. Rationale One………………………………………………………………..5
III. Rationale Two…………………………………………………………..........8
IV. Conclusion………………………………………………………………...…14
V. References……………………………………………………………………………15
2. BIOMARKERS FOR NEUROPSYCHOLOGICAL ILLNESS: CRITERIA AND CHALLENGES
I. Introduction………………………………………………………………….20
II. Current Candidate for a Biomarker: Logical Analysis of Evidence
and Line of Reasoning………………………………………………………21
III. Inundation of Information: Research Reporting and Capitalizing
on a New Platform……………………………………………………...........26
IV. Current Limitations and Best Practices in the Search for a Biomarker……..29
CONCLUSION………………………………………………………………………..........31
ACKNOWLEDGEMENTS……………………………………………………………………32
APPENDIX………………………………………………………………………………....33
INTRODUCTION

The practice of science in the 21st
century is one of community, and scientific reporting is
an integral part of successful science. The exponential growth of knowledge, especially in the
biomedical field, can seem somewhat daunting, and there exists the danger that, in sorting
through the copious amounts of information, a particular idea we may be searching for could be
lost. Misconstrued findings and overstatement of results have the possibility to have huge
detrimental effects on the very people who have come to trust in modern medicine. These are
just some reasons why we must apply the same level of care and rigor that we allot to actual
experimentation to the reporting and discussion of the results of these studies. As a student of
the University of Pennsylvania, I am heartened by the fact that, in order to train the most
effective researchers, clinicians, and critical thinkers, Penn emphasizes critical writing and
critical reading at the same level as the technical aspects of various fields of study. It is as
important.
This white paper will inform you, as students, researchers, and future medical
practitioners and clinicians, of the importance of the accurate dissemination of information and
give you a glimpse of how the current state of reporting stands. There is some work to be done,
but, as a community we can take care to further the validity and reliability of scientific endeavor.
This paper will focus on a few studies from the field of neurobiology and critically examine how
they are reported.
The research is already almost overwhelming in scope and it is going to take all of us, as
researchers, clinicians, doctors, scientists, and informed public to sort through, make sense of it,
and to maximize our results and yield the best possible treatments for the most individuals.

CHAPTER 1 – CLINICAL PATHOLOGICAL CORRESPONDENCE: RATIONALE FOR DEEP BRAIN
STIMULATION TARGET SELECTION
I. Introduction
The first direct cortical stimulation in humans was performed in 1874, and since the late
1900s, deep brain stimulation (DBS) has been utilized by select physicians in order to reduce
tremors associated with certain motor conditions: including epilepsy, essential tremor, and
Parkinson’s disease (Kringelbach, 2007; Sironi, 2011). This procedure, which requires surgical
implantation of electrodes in the brain, is hypothesized to function by blocking electrical signals
from targeted areas in the brain (Benabid 2003). Since its advent, the Food and Drug
Administration has approved DBS for treatment-resistant Parkinson’s disease, essential tremor,
and dystonia, and research has been expanded to include patients suffering from psychiatric
disorders, such as schizophrenia and more recently, treatment-resistant depression (TRD)
(Gardner, 2013; Tekriwal & Baltuch, 2015). Currently, for psychiatric disorders, this
intervention is only used in an experimental capacity for patients who have not been responsive
to any other treatments, most notably in treatment-resistant depression. Although the biological
substrate for depression is unknown, researchers have hypothesized several targets for DBS, one
of which is the subcallosal cingulate gyrus (SCG) (Dougherty, 2003; Lozano, 2008; Hamani,
2009).
In 2012, Andres Lozano et al. conducted a multi-center study in order to provide
evidence that the subcallosal cingulate gyrus is an effective target for DBS, and to replicate their
results across centers. In describing the rationale for using DBS of the SCG as a treatment for
TRD, the authors write: “A number of structural and functional imaging studies have implicated
involvement of the SCG area and connections in the processing of acute sadness. Furthermore,
TRD is associated with hyperactivity in the SCG… [and] various interventions that alleviate
depression produce reductions in the blood flow or metabolic activity in this area” (Lozano,
2012). In making this argument, the authors cite literature from various sources to support their
findings. In the following chapter, which is an analysis of the validity and appropriateness of
those supporting citations, we can effectively conclude that the evidence is insufficient to declare
that the SCG is an effective target for DBS.

II. Rationale 1: “A number of structural and functional imaging studies have implicated
involvement of the SCG area and connections in the processing of acute sadness.”
The claim by Lozano, et al., that “A number of structural and functional imaging studies
have implicated involvement of the SCG area and connections in the processing of acute
sadness” (Lozano et al., 2012) while not necessarily false, is not sufficiently supported by the
evidence cited by the authors.
The first supporting citation that is used by Lozano et al. to support their claim, that the
subgenual cingulate has been implicated by neuroimaging research in the experience of sadness,
overextends the results of the study and does not support the claim. The study was led by
Antonio Damasio in 2000 and conducted at the PET Imaging Center at the University of Iowa
College of Medicine. In this study, “Subcortical and cortical brain activity during the feeling of
self-generated emotions,” the researchers predicted that recall of events with specific emotional
coloring (sadness, happiness, anger, and fear) would be associated with activation in areas
believed, a priori, to monitor and regulate homeostatic information, including the cingulate
cortex. Their within-subject analysis of PET imaging data from 41 healthy human participants
(i.e. without history of neurological or psychiatric disorder and not taking any medication)
contrasted metabolic activity during an emotionally neutral task - “recall of the beginning of an
unemotional but specific day” (Damasio et al., 2000, p. 1054) - with that of an emotionally
colored recollection, for example, the death of a close friend; they excluded participants who did
not report or show (through galvanic skin conductance response and heart rate measures)
significant emotional change. Indeed, the PET results did show activation in the anterior
cingulate associated with sadness; however, this area was neither selective for sadness nor
clearly identified as exclusively or primarily the subgenual portion. Happiness, anger, and
sadness were all associated with altered activity in the anterior cingulate; neither magnitude nor
average direction of effect distinguished sadness from the others, although a combination of
location and direction of change from baseline differentiated among the three, indicating a non-
linear pattern-based relationship - one that also involves other structures. Furthermore, as
assessed by the Talairach atlas client (Lancaster et al., 1997; Lancaster et al., 2000) the locations
of the maxima for the anterior cingulate activation reported in “sadness” are both labelled as
“Right Cerebrum, Limbic Lobe, Anterior Cingulate, White Matter,” compared to Dr. Mayberg’s
central target at (10, 22, -14), which it deems “Right Cerebrum, Frontal Lobe, Subcallosal Gyrus,
Gray Matter, Brodmann area 25.” In fact, the only specific reference to the subgenual area in
Damasio’s paper appears in the results section, and uses outside citations to implicate this area in
emotional processing, noting that “Lesion studies and structural and functional imaging of
depressed patients suggest involvement of the subgenual prefrontal sector in emotional
processing” (2000, p. 1053). The strongest language the authors use regarding their own data in
relation to this states, “The results support prior observations that sadness involves the ventral
and medial frontal cortices and the insula” (Damasio et al., 2000, p. 1053). This is a far cry from
the specificity and force one might have expected based on Dr. Mayberg’s assertion.
The next citation also fails to provide strong evidence for the claim made by Dr. Mayberg
in the Lozano, et al. paper and only weakly supports the claim definitively marking the
subcallosal cingulate gyrus in acute sadness. This study (George et al. 1995) looks at the brain
regions involved in normal states of transient happiness and sadness in healthy adult women.
With the use of PET scans George et al. observed significantly increased regional cerebral blood

flow (rCBF) associated with transient sadness in widespread limbic and paralimbic structures,
including the right medial frontal gyrus, left dorsolateral prefrontal cortex, bilateral cingulate
gyrus, caudate, putamen, thalamus, fornix, left insula, and left midline cerebellum. While this
article does support Dr. Mayberg’s statement in part, it has certainly been overstated. Dr.
Mayberg did modify her use of the term sadness with acute, differentiating it from chronic
depression. This is an important distinction, but it is still not clear whether transient sadness,
referred to in George et al. is the same as acute sadness. George et al. use healthy subjects and
prime them to feel momentary sadness. Thus the relevance to severely and chronically depressed
patients, Dr. Mayberg’s focus, is not clear. In her rationale Dr. Mayberg should define her terms
as she jumps between types of sadness and depression. These are not interchangeable.
Additionally, the cingulate gyrus was only one of the numerous areas of the brain implicated and
George et al. to suggest it as particular target of interest.
The third citation listed to support the claim presents somewhat stronger evidence, but
remains flawed. The study by Lozano et al (2012) references Mayberg et al. (1999) to support
the assertion that structural and imaging studies have suggested that the subcallosal cingulate
gyrus and other connections are involved in the processing of acute sadness in individuals. The
aim of the study conducted by Mayberg et al. (1999) was to investigate functional interactions
between specific limbic and neocortical regions that have been associated with shifts in a
negative mood state, in both disease and normal cases. To accomplish this, Dr. Mayberg
examined the functional change in these regions when provoking sadness in healthy and
depressed patients by using two positron emission tomography techniques. They found that once
sadness had been provoked, there was an increase in limbic-paralimbic blood flow in the
subgenual cingulate and anterior insula areas. When recovery from this sadness occurred, the
reverse pattern was observed as blood flow to these respective areas decreased. There was also a
statistically significant inverse correlation between subgenual cingulate activity and right
dorsolateral prefrontal activity. Based on these findings, it can be concluded that these
aforementioned changes occur with both transient and chronic changes in negative mood. The
findings also suggest that the interactions with the subgenual cingulate and right dorsolateral
prefrontal regions are necessary to mediate the relationship between mood and attention, as seen
in both healthy and depressed patients. The findings in the Dr. Mayberg paper can be considered
sound because more than one functional imaging approach was used. In addition, two separate
subject populations were used which strengthens the results. In terms of content, the work by
Lozano et al. is sufficiently supported by the cited study. Lozano et al. reference Dr. Mayberg’s
conclusion that the subgenual cingulate area is directly involved in the processing of acute
sadness which is used as the basis for targeting this area. However, it should be noted that Dr.
Mayberg is the second author listed in the Lozano paper. Since Dr. Mayberg is an integral
member of both research teams in both studies and, given the gravity of the the ethical
considerations of performing any experimental, invasive brain manipulation, a rigorous appraisal
of any confirmation or other biases is warranted. In addition, the study done with PET scans had
a sample size of eight women in the first experiment and eight men in the second. This is a very
small sample size. It is also unconventional to only use one gender for each experiment as is
done in this study.. The paper written by Mayberg et al. was published in 1999, and the paper
written by Lozano et al was published in 2012. Since the Mayberg paper was written 13 years
before Lozano’s paper, it calls into question the scientific relevance of these results if they have
not been repeated. The paper written by Mayberg, et al. also did not address any long term

deviations from the scans obtained. This is a cause for concern since Lozano, et al. uses this
study as the foundation for a 12-month long study.
The fourth piece of evidence that is provided by Lozano, et al. is another example of
overreach and is not adequate to decisively implicate the subgenual cingulate gyrus in acute
sadness. The research conducted by Pardo et al., (1993) aimed to explore whether acute transient
changes in mood are reflected in activation of discrete neuronal systems in the human brain.
Positron emission tomography (PET) was used measure cerebral blood flow in four men and
three women subjects under two different conditions. In the control condition patients were
simply asked to keep their eyes closed. In the active condition patients were asked to recall a
condition that would make them experience sadness and to avoid feelings of anger or anxiety.
Results showed a significant difference in regional CBF particularly in the inferior and
orbitofrontal cortices leading to the conclusion that inferior and orbitofrontal activation may
relate to experimental aspects of self-induced dysphoria. The authors of this publication are
funded by by a grant from the National Heart, Lung and Blood Institute and the Institute of
Neurological and Communicative Disorders and Stroke. It is important to note that the model
used in this research is self-induced depression in overall healthy patients and Lozano et al.
(2012) applies it to treatment resistant depression which may be misleading. While the the
subcallosal cingulate gyrus is not mentioned specifically by this research, it makes sense in the
context of when this research was published. In 1993, research was being conducted using
imaging to look at large regions of the brain in order to determine which areas were involved in
depression and other psychiatric disorders. Since the paper specifically mentions the inferior
frontal cortex, it is fair to assume that the subcallosal cingulate gyrus was included in this region.
However, it is a stretch for Lozano et al. (2012) to use this citation to argue for the specific
association between the subgenual cortex and acute sadness.
Finally, the last source Lozano et al. use to support their use of the subcallosal cingulate
gyrus as a target for deep brain stimulation to relieve treatment resistant depression fails as direct
evidence. The use of the functional imaging results from Cooper and Talbot’s 2006 paper is
found to be invalid after further investigation into the source’s findings. Although there is
strength in referencing parallel findings from researchers aside from Dr. Mayberg, in examining
the author's’ use of this reference to support the idea of the SCG area’s involvement in the
processing of acute sadness, there were multiple flaws in the utilized publication. Errors in the
research design are prevalent throughout. First, the subject model used only male individuals
with no medical history of major depression. This study thus had to create a research modality in
which they induced a “sad state” that they could measure via a visual analogue mood scale
(VAMS). This was seen as being the greatest weakness in utilizing this publication as reasoning
behind targeting the SCG. Another conflict is the exclusion criteria for the subjects, which
included “not having current evidence of a depressed mood based on a score greater than or
equal to 9 on the Beck Depression Inventory (BDI)” (Talbot 2006). The use of this does not fit as
good support because Dr. Mayberg is using patients who are not healthy, and therefore their
brain imaging will not read the same. The reference material authors even contrast the
differences seen in patients afflicted with major depressive disorder in past studies as showing
contrasting imaging patterns in neighboring structures of the cingulate cortex compared to
healthy subjects. This evidence should be taken into account when determining if the SCG is a
possible target for deep brain stimulation yet the researchers may have overlooked this data and
simply went with the neuroimaging patterns showing cingulate cortex involvement in depressed
states to justify their studies.

III. Rationale 2: “That this hyperactivity [of the SCG area] is significant in the pathogenesis of
depression is supported by the observation that various interventions that alleviate depression
produce reductions in the blood flow or metabolic activity in this area.”
The evidence that Lozano et al. cite to support the rationale that “the hyperactivity [of the
SCG area] is significant in the pathogenesis of depression is supported by the observations that
various interventions that alleviate depression produce reduction in the blood flow or metabolic
activity in this area” also does not stand up to critical analysis as definitive evidence and it is
misleading to represent it as such.
The first citation listed by Dr. Helen Mayberg and supporting authors is cited multiple
times and is an article in which Dr. Mayberg was a co-author. This study entitled, “Cerebral
metabolic correlates as potential predictors of response to anterior cingulotomy for treatment of
major depression (2003),” does not provide the necessary evidence to make the claim for which
it is cited and lacks the statistical power to be used as convincing support. The study utilizes
clinical data including patient demographics, diagnostic information, and fluorodeoxyglucose
positron emission tomography (FDGPET) images that were obtained retrospectively from the
hospital records of 13 patients (four men and nine women) who had undergone bilateral
stereotactic anterior cingulotomies at Massachusetts General Hospital (MGH) for severe,
treatment-refractory major depression (Dougherty et al, 2003). However, upon examining Dr.
Mayberg’s supporting document, it appears that this study, which was the first of its kind, serves
as a vantage point for future research rather than an appropriate citation for the aforementioned
claims. For example, Dougherty and the supporting authors claim, “given that this study
represents the first of its kind, we used relatively liberal statistical thresholds in the hope of
generating more refined hypotheses for future studies; more stringent thresholds together with
more circumscribed hypotheses are recommended for follow-up experiments (Dougherty et al,
2003). Furthermore, before sharing the results of this study the following note is made:
“Although a z score greater than 3.09 (p < 0.001, uncorrected for multiple comparisons) was
selected a priori as the threshold for statistical significance, such findings should not be taken as
strong evidence of reliable effects before corroboration, ideally by independent replication
(Dougherty et al, 2003). This suggests that the results should not be taken as a strong indication
of the effects of an anterior cingulotomy. For example, while a summary of the results indicated
that cerebral metabolism within territories of the left subgenual prefrontal cortex and the left
thalamus was significantly correlated with subsequent improvement in depressive symptom
severity following anterior cingulotomy in a cohort of patients with severe, treatment-refractory
major depression (Dougherty et al, 2003), it is a stretch to make the connection between anterior
cingulotomy and surefire reductions in depressive symptoms . In addition to this cohort being
small and heterogeneous, within the paper the following was claimed: “although data in the
current study indicate that those patients with treatment-refractory major depression with lower-
magnitude decrements in metabolism within the subgenual prefrontal cortex are more likely to
experience symptom improvement following anterior cingulotomy, alternative explanations are
possible (Dougherty et al, 2003). These alternative explanations are also accompanied by the
limitations of the study. In the absence of additional data, generalization to other indications for
cingulotomy or to other neurosurgical treatments for major depression is entirely unfounded
(Dougherty et al, 2003). Additionally, the statistical threshold applied is liberal and without
replication, does not provide enough evidence to suggest that this is a valid claim. Dougherty and

supporting authors also suggest the possibility that the significant relationship between measured
regional cerebral metabolic rate of glucose (rCMRG) and the Beck Depression Inventory (BDI)
score improvement is confounded by variables that cannot be readily accounted for within the
general linear model, such as diagnostic comorbidity or medication effects (Dougherty et al,
2003). Thus, while the evidence is indicative of the need of properly powered studies to
corroborate these claims, it does little to back up the claims of Dr. Mayberg’s clinical article.
This is just one of many examples of how evidence can be manipulated to support a scientific
agenda. Finally, it should be noted that a neurosurgical treatment for psychiatric illness is an
invasive procedure with only modest success rates. Specifically, data from MGH indicate that
53% of patients with major affective disorders respond to bilateral anterior cingulotomy
(Dougherty et al, 2003).
The next citation provided is misleading as evidence for this rationale. In the Lozano et
al. paper, the authors cite an article written by M.S. George et al. (1999) in order to defend the
usage of the SCG as a target in DBS. Citation number 8 in this paper is a study conducted at the
Medical University of South Carolina, and is lead by Dr. Mark S. George from the Department
of Radiology. The goal of this study was to use SPECT imaging in conjunction with repetitive
transcranial magnetic stimulation (rTMS) to measure the relative blood flow and metabolic
changes in the left prefrontal cortex, effectively to understand the neurobiological effects of TMS
(MS George et al., 1999). The article also discusses the ability of researchers to implement these
tools to map neural networks. In this study, the authors selected 8 healthy candidates (5 men and
3 women) on no medications, and placed a Cadwell Magnetic Stimulator in their primary motor
cortices. Using SPECT, they determined that after administration of rTMS, blood flow and
metabolism in the left orbitofrontal cortex and hypothalamus increased, while a decrease was
seen in the right prefrontal cortex, bilateral anterior cingulate and anterior temporal cortex.
Although the paper makes claims regarding the effects of rTMS on certain parts of the
brain as determined by neuroimaging, there is insufficient evidence to support Rationale 3 from
the Mayberg paper. First of all, the paper bears no mention of the subcallosal cingulate gyrus
specifically. While MS George et al. support the claim that blood flow in the brain may change
due to rTMS, particularly in the primary motor cortex region, targeting the SCG in relation to the
alleviation of depression is not at all mentioned or implied. Though the authors speculate that the
reduced activity in these areas of the brain may relate to mood-altering effects of tRMS, this
assumption is based off of other studies and is not established in this paper. Second, the main
point of this paper is how rTMS, coupled with brain imaging techniques, is a useful tool for
studying the brain and psychiatric illness, but does not provide direct support to the statements
made by the Mayberg paper. By focusing specifically on the usage of rTMS in tandem with
SPECT to elucidate brain changes and visualize neural circuits, this article is specific to this non-
surgical intervention, and cannot effectively claim that hyperactivity is significant in the
pathogenesis of depression. Really, this article only concludes that “rTMS...has both local and
remote effects” that may be visualized using SPECT technology.
The evidence that the third article listed provides is weak in supporting this rationale, and
may just as easily be considered no evidence at all.. Hamani et al. (2011) is a review article
entitled “The subcallosal cingulate gyrus in the context of major depression.” The portion of the
review that deals with the statement made by Lozano and colleagues is a brief section in which
Hamani et al. summarize literature on blood flow and metabolism in the SCG, defined by
Hamani et al. as “the portion of the cingulate gyrus lying ventral to the corpus callosum, from the
anterior boundary of the genu to the rostrum” (2011). The authors concluded that the local

changes to the target region of DBS were actually less likely to mediate the antidepressant
effects; rather, the modulations of the anatomical connections made by the SCG to other brain
areas and the subsequent transsynaptic changes in these areas (e.g. dorsolateral prefrontal cortex
and the insula) were more likely to facilitate this effect. However, many of these connections
were studied in nonhuman primates and the authors themselves caution the reliance on
nonhuman brains to study human connections. This area was implicated as functioning in
depression due to the increase in SCG activity in depressed patients, as shown by imaging
studies. However, several of the citations in support of the idea that the SCG should be targeted
for DBS in depression do not actually show changes in blood flow to the SCG in depression, but
rather in transient states of emotion (including sadness) (Pardo, 1993; George, 1995; Damasio,
2000; Talbot, 2006). In the Hamani review, figure 2 supposedly shows effects of various
depression treatments on SCG blood flow or glucose metabolism. One of these categories is
placebo, which seems here to have an effect comparable to treatments; the study cited showed
that the placebo effect can result in similar changes in glucose metabolism compared to
treatments (Mayberg, 2002). The decision to study the SCG region in response to DBS was
driven by a variety of studies, almost exclusively done on rats, that measured levels of
depression using the Forced Swim Test, a measurement the authors once again caution as
inapplicable to humans.
It should be noted that both Drs. Lozano and Mayberg (the last author in the 2012 study)
are authors contributing to the Hamani review- in fact, the three of them have contributed to
almost all of the deep brain stimulation and depression literature available to date. Therefore,
most of of the citations in the Hamani review include Drs. Lozano and Mayberg as authors as
well. Additionally, the review was submitted in April of 2010 while the Lozano 2012 study
manuscript submitted December of that same year, indicating that the review was not, in fact,
instrumental in the decision to choose the SCG as the target for the study (it seems likely that
much, if not all, of the data were already acquired before the review was written). Rather, the
inclusion of this particular citation serves to show that the authors wish to continue to study the
SCG based on previous perceived success with stimulation in this area (Mayberg, 2005; Lozano,
2008). While use of previous data from the same authors is often useful in the rationale for
current work, this method of doing so is obscuring at best.
The next evidence listed is also an example of an overreach by the authors of the Lozano
et al. paper to support their claim that the SCG can be implicated by reduced blood flow and
metabolic activity as the source of depressive symptoms. This evidence is a 2003 Mayberg
literature review article on what she identifies as depression’s dysfunctional limbic-cortical
circuits. In it, she recapitulates a number of experimental studies comparing changes from pre-
intervention metabolism (as measured by PET) and blood flow (as measured with fMRI)
between responders and non-responders to various depression interventions, including fluoxetine
and cognitive behavioral therapy, as well as structural approaches such as lesion-deficit. Time
and time again the subgenual cingulate appears as a region of interest, with abnormally high
activity in depressed patients compared with controls as well as in the responders compared with
non-responding patients. It is an impressive array of evidence, and there are many techniques and
research groups represented; however, a preponderance of these are either reviews or studies also
authored by Dr. Mayberg. This is a common occurrence with her: among the other evidence
appearing in this 2012 article for this specific SCG hypermetabolism claim are two papers also
cited within the 2003 review, both of which are papers of hers (both published in the American
Journal of Psychiatry, one in 1999 and the other in 2002). The 2003 review does feature a novel

(although “preliminary”) re-analysis of three cohorts’ worth of pre-existing data, a confirmatory
examination that once again identified subgenual cingulate as a region of difference and
hypermetabolism of the anterior cingulate as a feature of non-responders. With this style of
reporting, Mayberg walks a fine line between ‘double-dipping’ on citations and presenting
sufficiently distinct convergent results. Overall, the evidence is promising but perhaps oversold
with artificial citation inflation.
Again Dr. Mayberg cites her own work to support this claim which decreases the strength
of the evidence. “The Functional Neuroanatomy of the Placebo Effect” written by Mayberg et
al. (2002) is an article about PET scans measuring glucose metabolism in the brains of subjects
with unipolar depression. These patients were all hospitalized men who had been given a placebo
in a depression drug study and were reassessed after six weeks. A PET scan of the subject’s brain
was taken at the onset of the trial and again at the end. The results of the study showed that
metabolism increased for the placebo patients in the prefrontal cortex, anterior cingulate,
premotor, parietal, posterior insula, and posterior cingulate areas. This was accompanied by
metabolic decreases in the subgenual cingulate, parahippocampus, and thalamus. A noticeable
difference was that in non-placebo patients (those who received the drug fluoxetine), additional
decreases were seen in the subcortical and limbic metabolisms. This could be seen as an
additional advantage of the drug therapy as opposed to purely psychological therapeutic
treatments. This article directly corroborates the statement made in the article by Lozano et al
(2012) that ‘the hyperactivity [of the SCG area] is significant in the pathogenesis of depression
[because] various interventions that alleviate depression produce reductions in the blood flow or
metabolic activity in this area.’ The subjects who were given the placebo and those who were
given fluoxetine both showed decreased blood flow in the subgenual cingulate area associated
with alleviations of depression. However, there are some noticeable differences in the
experiments. The study conducted by Mayberg et al (2002) was only done on middle aged men
who were hospitalized, a very specific patient population instead of a random sampling. In
addition, the study only contained 17 subjects who were all taken from the same Veteran’s
Associations Hospital in Texas. This is not ideal for a study since these subjects are all taken
from similar backgrounds and situations, introducing the possibility of confounding variables.
The average HRSD score of these subjects was 22 with a standard deviation of 5, meaning that
the lowest subjects had a score of 17 or higher. In the trial conducted by Lozano et al (2012), the
cut off for HRSD scores of subjects was ≧20, making the data obtained from these patient
populations skewed since they were not measured on the same scale. The placebo effect study
was also only conducted over a period of 6 weeks during which the subjects were tested twice,
precluding any data about long term effects or significant changes. This is concerning when
compared to the study by Lozano et al (2012), which was conducted over a year since no long
term changes in PET scans are referenced as a basis for the paper.
The sixth citation is from the study, Mottaghy et al. (2002), and is attempts to support the
assertion using previous research that has shown a link between a decrease in depressive
symptomatology and reduced activity in the subcallosal cingulate gyrus area. An issue arises
here in that Mottaghy et al. (2002) conducted a pilot study (n=17) which examined the impact of
transcranial magnetic stimulation (rTMS) on activity within the left dorsolateral prefrontal
cortex. The objective of the study was to assess the effects of this using single photon emission
tomography and evaluate how predictive this brain SPECT technique was on how efficient rTMS
is in having an antidepressant effect. Using the Hamilton Depression Rating Scale (HDRS-28) to
score participants both before and after rTMS treatment, Mottaghy et al. found only five of the

17 patients to show a clinically significant response to rTMS treatment as demonstrated by an
equal to or greater than 50% decrease in their HDRS-28 scores. While the researchers attempted
to counterbalance their small sample size by using a hypothesis driven approach in analyzing
their data, it remains inappropriate to draw strong conclusions regarding the significance and
generalizability of their findings without more robust statistics. In fact, Mottaghy clearly states
that it cannot be concluded that the changes in rCBF are related to direct rTMS effects. Keeping
the limitations of their research paradigm in mind, Mottaghy et al. (2002) presented data that
illustrated a negative correlation between blood flow (rCBF) in allocortical structures--the
anterior cingulate being one-- and the suggested therapeutic effect of rTMS on depression. In
short, rTMS was found to have a higher therapeutic effect in patients with lower limbic rCBF
pretreatment. The first problem with this finding in the context of Lozano et al. (2012) is that it
supports the idea that there is variability in baseline rCBF of depressed individuals; it is not
enough to simply say that relatively less rCBF activity alleviates depressive symptomatology.
Furthermore, even if the results put forth in the Mottaghy et al. (2002) paper were more
statistically sound, whether or not their research could be considered applicable to the work of
Lozano et al. (2012) would at least require some knowledge of the baseline rCBF of the
participants included in the latter’s research paradigm. In addition, the Mottaghy et al paper was
written in 2002 and published in the Psychiatry Research Neuroimaging journal, ten years prior
to the publication of the Lozano study. Due to this reason, the findings can be considered as
weak support for a much more recent paper. Because of the above shortcomings, the Mottaghy et
al. (2002) citation is not sufficient evidence for the claim put forth in the Lozano et al. (2012)
article.
Dr. Mayberg also gives several citations to support the claim that rapid tryptophan
depletion is associated with hyperactivity in the subcallosal cingulate gyrus (SCG) and that this
hyperactivity is significant in the pathogenesis of depression and, while the area of the SCG is
implicated generally, studies find a wide range of areas showing decreased blood flow due to the
treatments.. One such study was conducted by Nobler et al. (2001) and examines blood flow  in
subjects before and after undergoing electroconvulsive therapy (ECT).    After evaluating this
reference, we find credibility in many respects to  the study. First, the source of the study seems
to be absent of outside   influences. A group of psychiatrists at Columbia University and the
New  York State Psychiatric Institute were provided with funding from the NIMH   to perform
this research in which they had 10 subjects imaged with PET   scanning before and after a 5-day
treatment of bilateral ECT. Statistical parametric mapping was then used to identify regions of
decreased metabolism. The study found that there was a widespread collection of regions with
decreased cerebral glucose metabolism after ECT, however specific emphasis is placed on areas
in the frontal and parietal cortex, anterior and posterior cingulate gyrus, and left temporal cortex.
The primary finding of the study is cited as having the most significant decrease in metabolic
activity in the frontal, prefrontal, and parietal cortex. The decrease in metabolic activity in the
cingulate gyrus is mentioned as a secondary finding. However, we do not believe this distinction
between primary and secondary outcomes plays a significant role in research outcomes at this
point due to the lack of power in these pilot studies. It is also important to recognize the
importance of the different areas of the brain playing a combined role in achieving normalcy in
brain functioning. This research was published in The American Journal of Psychiatry in 2001,
making this research 11 years old at the time it was used to support Lozano et al. (2012).
Nonetheless, due to the simplicity of the findings, we believe that the findings are still usable and
effective. Although this study utilized a very small sample size, the unified results in 100% of

patients   showing decreases in the metabolic rate of glucose across all subjects in   the
aforementioned areas does indeed add more weight to the publication.
Lastly, Dr. Mayberg and company use a meta analysis with significant limitations to
convince their audience of the importance of the SCG as a target for DBS to relieve depression.
This meta analysis looks at three studies across two institutions looking at metabolic changes in
specific regions of the brain when a subject is treated for depression, with a selective serotonin
reuptake inhibitor (SSRI) and with cognitive behavioral therapy (CBT). The meta analysis
combines the results of these studies by synthesizing the PET images and data of various brain
regions, including the subgenual cingulate, and comparing treatment responders and non-
responders, with healthy control groups, and to a group diagnosed with depression, but with no
treatment administered. The synthesis uses Structural Equation Modeling (SEM) to test a 7
structure model for depression. The model is found to be consistent in showing metabolic
differences between responders and non responders in the limbic↔subcortical pathway
(Orbitofrontal cortex↔subgenual cingulate) of the model. Mayberg finds in this meta analysis
that between responders and non-responders, there are differences in glucose metabolism of
these brain areas.
This meta analysis supports the statement made by Mayberg in her 2012 paper, that there
is reduced metabolic activity of the subcallosal cingulate gyrus in those who are not responding
to treatment of depression compared to those who are responding to treatment. The study is
strengthened by the fact that it is a meta analysis and has a much larger sample size than any one
study by itself, increasing its statistical power.
There are some limitations to this evidence, however. A major defect is that placebo
effect cannot be ruled out. For example, the data for paroxetine nonresponders shows a
significant decrease in depression rating as given by the Hamilton Depression Rating Scale (pre-
trial vs. post-trial), and is not accounted for by the authors. Another limitation of using a model
such as the one described is that it is difficult to separate a single region from the model and
implicate it as the structure or connection whose blood flow needs to be increased to reduce
depressive symptoms. The brain is a complexly interconnected organ and deep brain stimulation
does not have specific, local effects. Mayberg uses this evidence to say that she will increase
blood flow and metabolism in the subcallosal cingulate gyrus, but the perfusion and metabolic
effects will be widespread. Also, just as a note of caution, this study is an example of Mayberg
citing her own work. While these limitations reduce the efficacy of this study as evidence for her
claim, they do not necessarily override it. These limitations are not easily resolved, indeed it
may not be possible to resolve them. The possible benefits may outweigh the possible risks,
provided informed and comprehensive consent is obtained by those seeking to engage with this
experimental method, and that we are rigorous with the ethical considerations of such
procedures.
V. Conclusion

Dr. Helen Mayberg, Dr. Andres Lozano, and the other contributing authors of the paper
that is the focus of this criticism are impeccably credentialed and possess decades of practical
experience in psychobiology, neurology, and all related fields. Their expertise is not called into
question with this review of their paper, and should not be questioned based on the findings
presented here. We have reviewed the evidence presented to support the claim made by Drs.
Lozano and Mayberg and find, based on the wording of their claims, and due to their specificity,
that, overall, the evidence does not fully support their statements as is. The knowledge base is
not yet large enough to accommodate such certain statements. This is to be expected given that
modern neuroscience is still in its infancy. The very basic foundation of any science, especially
cutting edge science, is one of uncertainty. This is why we pursue scientific endeavors, to
mitigate this uncertainty and to answer questions. With untried and experimental procedures, it
is not generally expected that researchers know the outcomes of these procedures beforehand,
indeed, this is the point of such experiments, the point being that we do not already know.
Neuroscience, and science in general, would benefit were we to acknowledge this uncertainty.
Much of the argument presented here would be invalid had the claims by Dr. Mayberg been
tinged with the natural, inherent uncertainty that exists in this area of research. These
researchers have a certain amount of leeway to perform experimental tests, the evidence may
have been enough to warrant these studies even though the evidence was not, and could not be,
100 percent undisputed, and their credibility would have been strengthened. Learning from this
paper and the logical inconsistencies apparent therein, as a future researcher, I plan on keeping
the uncertain nature of science in mind if, and when, I publish results or make statements of fact.
Given the impact of experimental neuroscience on any number of lives at any number of
moments, it is important to not overstate the evidence or rationalization for performing our
experiments. We must be careful to apprise any interested party, especially those who may be
recruited as subject to the experiments but also other researchers of the field, of what we do not
know, as well as what we do know. In this age, where we are inundated with information at all
times, we must be more careful writers; the credibility of science is at stake.

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CHAPTER 2 – BIOMARKERS FOR NEUROPSYCHIATRIC ILLNESS: CRITERIA AND CHALLENGES
I. Introduction
The intersection of biology and psychology has been one fraught with controversy since
human beings began thinking in scientific terms and perhaps, since time immemorial. Before
there was a scientific method, there was no distinction between “science” and philosophy and
our questions were answered by philosophers. We are of another age, however, and it is time to
marry the science of biology with the largely philosophical nature of psychology. Evidence is
showing that there is a biological basis of behavior and, as such, psychopathologic disorders and
symptoms should be treated accordingly. The science of psychology already has given us a start
in this direction with the discovery of reward learning and conditioning and the gains of
neuroscience in understanding the most complex of all systems in the known universe, the
central nervous system and the human brain.
One such way that we can begin to explain the psychologic condition in biological terms
is with the search for biomarkers that may be able to predict and diagnose psychiatric illness and
other diseases affecting the brain and the mind. These biomarkers exist in many of the other
realms of medical science and the research is showing that they may exist in the field of
psychiatry as well.
This chapter will first report on the results of three studies that implicate a gene and its
epigenetics, in this case methylation and the induced change in functioning of the spindle and
kinetochore associated complex unit 2 (SKA2), which may play a regulatory role in
glucocorticoid receptor function and the stress pathway (HPA axis). The hypothesis is that by
measuring the methylation of this gene, we may find as a biomarker that would enhance our
assessment of suicide risk (Guintivano 2014). In order to provide the necessary background
information and to apply a logical critique to scientific reporting, this section of the chapter will
present the proposition of the authors of each study and outline the supporting reasons and
evidence for their claim.
Next, the near future of scientific research as it pertains to the fields of the neuroscience
of emotion and psychopathology will be examined with an in depth look at a current study and
how it relates to the mandate of the National Institute of Mental Health; to treat psychiatric
illness as any other medical illness, with the hopes of seeing the same remarkable progress that
denotes modern medical science, but leaves the field of psychiatry somewhat behind.
And third, some of the limitations to current research will be discussed and best practices
regarding psychiatric biomarker will be presented. This is an exciting time for science,
neuroscience especially.

II. Current Candidate for a Biomarker: Logical Analysis of Evidence and Line
of Reasoning
Three very recent studies provide strong evidence using credible and convincing logic to forward
the hypothesis that the SKA2 gene is a viable biomarker for psychopathological risk, especially
in the case of suicidal behavior and of other symptoms related to alterations in the HPA axis. By
presenting their results with a solid line of reasoning, these studies support further study of
SKA2 and its epigenetics.
A. First Study: Proposition: The first study to use SKA2 as a focal point in the search for a
biomarker for suicidality was conducted in 2014 out of Johns Hopkins University School
of Medicine and was conducted by Jerry Guintivano, Ph.D., Zachary Kaminsky, Ph.D.,
Holly Wilcox, Ph.D., William Eaton, Ph.D., Brion Maher, Ph.D., Jennifer Payne, M.D.,
and supporting contributors. Guintivano, et al., found that further study of SKA2
methylation as a genetic/epigenetic focus a biomarker for suicidality is warranted.
Supporting Reason 1: In this study, four genes
were found to be “significantly associated with
suicide,” but after analyzing differences in
methylation, only SKA2 showed statistical
significance across all samples (Guintivano, et al.
2014). The authors performed a Genome-Wide
Methylation Analysis on post mortem prefrontal
cortex samples of subjects who completed
suicide. Their cohort included 23 suicide
completers and 35 control, comparative subjects.
The figure to the right appears as Figure 1e in
their paper and summarizes their results and
provides evidence for this claim.
Supporting Reason 2: The researchers also
analyzed samples of peripheral blood from three
living cohorts who reported suicidal ideation
and/or an actual suicide attempt. They also found
levels of methylation of SKA2 to be greater
among this subpopulation of the living cohorts
compared to control.
Figure 1 SKA2 methylation across
postmortem and living samples (Suicide
completers, attempters, and those with
ideation. Reprinted from Guintivano et al
2014.

Supporting Reason 3: Aside from methylation, the gene itself
was found to have lower levels of expression among suicide
decedents (Guintivano 2014). This provides further support that
the SKA2 it’s expression levels differ in the prefontal cortex
between those who had completed suicide and those in the control
group. Figure 2 is the graphical representation provided as
evidence by Guintano, et al.
B. Second study: Proposition: The next study purporting SKA2 and its epigenetics as a
promising candidate for a biomarker for suicide risk was carried out, also at Johns
Hopkins, by, again, Zachary Kaminsky, Ph.D., Holly Wilcox, Ph.D., William Eaton,
Ph.D., and others. Kaminsky, et al. corroborate the earlier findings of Guintivano, et al.
and further the implication of SKA2 as a viable predictor of suicidality.
Supporting Reason 1: The authors created a suicide prediction model based on levels of
expression and epigenetics of SKA2 and were successful in showing retroactive
prediction of suicide attempt, but not suicide ideation (Kaminsky, et al. 2015). The
researchers tested the blood of N=421 individuals who were recruited for a larger study
on stressful life events and genetic and environmental factors (Kaminsky et al. 2015).
The authors consider this a moderate success, but go on to find that the model is
enhanced when paired with other diagnostic measures.
Supporting Reason 2: Kaminsky, et al. tested the Hamilton Anxiety Rating Scale
(HAM-A) with methylation of SKA2 and found no significant association. They did not
find a correlation between total anxiety reported and methylation of SKA2. However,
when they tested methylation levels with the Child Trauma Questionnaire (CTQ), the
researchers found a significant association and posit that trauma, which has been shown
to increase the risk of suicidal behavior* and ideation* (citations), is also correlated with
an increase in methylation of SKA2 (Kaminsky, et al. 2015). They, therefore,
incorporate CTQ into their suicide risk prediction model increasing its predictive power.
Supporting Reason 3: Further support for this biomarker involves the ease of obtaining
samples that can be tested. The researchers of this study also used saliva samples to
determine if the biomarker would be detectable in this less invasive manner. Kaminsky,
Figure 2 SKA2 Gene expression
levels in suicide completers
compared to control. Reprinted
from Guintivano, et al. 2014.

et al. report that the results obtained from saliva regarding methylation of SKA2 as a
predictor for suicidality were similar to results obtained from blood. This increases the
value of SKA2
methylation as a
biomarker. The figure to
the right provides
graphical evidence for
their claim.
C. Third study: Proposition: A third study was published this year that replicated the
findings of the previous two, and also expanded the power of the biomarker by showing
that levels can be used to predict specific suicide phenotypes (though only current
phenotype, not those that may have been present in the past), namely, suicide ideation vs.
suicidality with specific plan vs. actual suicide attempt performed as well as risk for
trauma related internalizing psychopathological problems (Sadeh, et al. 2016)
Supporting Reason 1: Sadeh, et al. used linear regression to analyze the association
between suicidal phenotypes as defined by the “major depressive episode module of the
Structured Clinical Interview for DSM-IV” (Sadeh, et al. 2016). The authors found that
current suicide phenotype is strongly correlated with SKA2 methylation. The beta value
demonstrates how strongly two variables are associated, with ‘0” denoting no association
and “1” indicating no statistically significant difference between the two variables.
According to the authors, the beta value for SKA2 methylation associated with current
suicide phenotype was .27 with a p-value of 0.014. They did not find any statistical
significance between SKA2 methylation and past suicide phenotypes (β=0.01 and p-
value=0.97), (Sadeh, et al. 2016).
Supporting Reason 2: Sadeh, et al. also tested SKA2 methylation as a predictor of
internalizing psychopathologies, finding that it does not predict PTSD, but that there is
significance when compared to other clinical diagnoses. Internalizing disorders, for
example, are those whereby symptoms are largely internal. For example, depressive
disorders, anxiety disorders, phobias; but not disorder with outwardly appearing
symptomology such as substance use disorders and antisocial personality disorder
(Sadeh, et al. 2016).
Figure 3 Determining methylation of
SKA2 via saliva compared to blood.
Reprinted from (Kaminsky, et al. 2015)

The significance of the Sadeh, et al. study, and the two previous studies, is best summarized in
their own words: “This study contributes to the rapidly expanding body of evidence implicating
epigenetic variation at SKA2 as a biomarker of susceptibility to stress-related pathology.
Findings advance prior work by demonstrating that methylation of this gene provides unique
information about suicide risk not captured by clinical symptom interviews and may index a
general susceptibility to experience internalizing psychopathology” (Sadeh, et al. 2016).
Analysis: The reporting of these three studies flows in a logical and consistent manner and is not
overstated. The authors provide strong statements supporting their findings and support their
statements with strong evidence presented clearly and accurately, and are intelligible to a wide
audience. The results show strong rationale for further study of SKA2 and the epigenetics of this
gene as a biomarker for suicidality and perhaps even other psychopathologic phenomena.

References
Guintivano, J., Brown, T., Newcomer, A., Jones, M., Cox, O., Maher, B. S., . . . Kaminsky, Z. A.
(2014). Identification and replication of a combined epigenetic and genetic biomarker
predicting suicide and suicidal behaviors. The American Journal of Psychiatry, 171(12),
1287-1296. doi:10.1176/appi.ajp.2014.14010008 Retrieved from
http://proxy.library.upenn.edu:2899/doi/abs/10.1176/appi.ajp.2014.14010008
Kaminsky, Z., Wilcox, H. C., Eaton, W. W., Van Eck, K., Kilaru, V., Jovanovic, T., . . . Smith,
K. (2015). Epigenetic and genetic variation at SKA2 predict suicidal behavior and post-
traumatic stress disorder. Translational Psychiatry, 5, e627.doi:10.1038/tp.2015.105
Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/26305478
Sadeh, N., Wolf, E.J., Logue, M.W., Hayes, J.P., Stone, A., Griffin, L.M., Schichman, S., and
Miller, M.W. (2016). Epigenetic variation at ska predicts suicide phenotypes and
internalizing psychopathology. Depression and Anxiety, 33(4), 308-315.
doi:10.1002/da.22480
Retrieved from http://proxy.library.upenn.edu:2154/doi/10.1002/da.22480/abstract

III. Inundation of Information: Research Reporting and Capitalizing on a New
Platform
Currently, there is a shift in the way research is expected to be performed in the field of
neuroscience as it pertains to psychopathology and the study of psychiatric illness, and this shift
enhances the search for biomarkers, such as the one for suicide risk. The focus of study in the
20th
century has been on a top down approach where researchers and clinicians alike begin with
an overarching diagnosis and seek to understand mental disorders under this umbrella of
generality which may or may not accurately describe the holistic condition of an individual. The
Diagnostic and Statistical Manual V forwards the idea of explaining mental health problems as a
collection of symptoms and characteristics, but basing research solely on this collection of signs
and symptoms is a rate-limiting step in the study of psychopathology and the search for effective
treatment. In order to more effectively study psychopathology, the National Institute of Mental
Health (NIMH) has proposed a novel system for research, the Research Domain Criteria
(RDoC). According to the former director of the NIMH, Thomas Insel, the RDoC does not seek
to replace the DSM, but create a new way to explore possibility and a new way to collect results
that will more easily spur further scientific study. In an NIMH introductory blog post regarding
RDoC, Insel writes,
The strength of each of the editions of DSM has been “reliability” – each edition has
ensured that clinicians use the same terms in the same ways. The weakness is its lack of
validity. Unlike our definitions of ischemic heart disease, lymphoma, or AIDS, the DSM
diagnoses are based on a consensus about clusters of clinical symptoms, not any objective
laboratory measure. In the rest of medicine, this would be equivalent to creating
diagnostic systems based on the nature of chest pain or the quality of fever. Indeed,
symptom-based diagnosis, once common in other areas of medicine, has been largely
replaced in the past half century as we have understood that symptoms alone rarely
indicate the best choice of treatment.
Patients with mental disorders deserve better. NIMH has launched the Research Domain
Criteria (RDoC) project to transform diagnosis by incorporating genetics, imaging,
cognitive science, and other levels of information to lay the foundation for a new
classification system.” (Insel 2013)
How does this relate to the search for an effective biomarker for determining risk for suicide?
The study of suicidality fits nicely into the RDoC framework. RDoC consists of a matrix of
Domains and Constructs that promise to enhance the search for the etiology and possible
treatments of psychiatric illness. This approach will more easily allow researchers to build upon
previous research using sound rationale and provide a more research-friendly results reporting
mechanism. To clarify, it will be helpful to give an example of RDoC Domains and Constructs
as they apply to suicidality.
The RDoC currently consists of 5 domains, Negative and Positive Valence Systems,
Cognitive Systems, Social Processes, and Arousal and Regulatory Systems. Each domain
encompasses a series of constructs and sub constructs which narrow down a particular area of

study and are cross referenced with, what the NIMH call, Units of analysis. These units of
analysis provide information on how a particular problem in pathophysiologic psychology has
previously been researched and which biological components may be implicated.
A very recently published paper studying patients hospitalized for acute suicide risk has
tested suicidality using RDoC, negative valence systems, specifically in the construct of potential
threat; positive valence systems, in the construct of reward attainment (anhedonia); and the
domain of social processes, in the construct of affiliation and attachment (Yaseen 2016). Using
linear regression to test for an association these researchers have determined that anhedonia,
entrapment (in the construct of frustrative nonreward), and anxiety were all significantly
correlated with suicidal ideation and may be used as a point of rationale for further study of a
biological cause of suicidality (Yaseen 2016). The value of the RDoC lies in the ability to link an
association for a particular area of interest and then cross reference what has been researched
previously in these domains and constructs and test new hypotheses with the previously studied
units of analysis. The authors of this particular study write, “Anhedonia and entrapment
represent distinct functional domain disturbances that correlate independently with severity of
suicidal ideation. These behavioral domains may be significant risk factors that should be
monitored when assessing suicide risk. Further studies should examine underlying biological
mechanisms involving reward and entrapment in relation to suicide” (Yaseen 2016). As
examples, Figures 4 shows the domains, constructs, and units of analysis for entrapment. For an
example of how the RDoC matrix may be applied to the Yaseen 2016 study see figure A1 of the
appendix.
Figure 4 Example RDoC matrix Reprinted from NIMH website 2016

References
Construct: Frustrative nonreward. (2016). Retrieved from
http://www.nimh.nih.gov/research-priorities/rdoc/constructs/frustrative-nonreward.shtml
Development and definitions of the RDoC domains and constructs. (2016). Retrieved from
http://www.nimh.nih.gov/research-priorities/rdoc/development-and-definitions-of-the-
rdoc-domains-and-constructs.shtml
Insel, T. (2013, April 29). Transforming diagnosis. Retrieved from
http://www.nimh.nih.gov/about/director/2013/transforming-diagnosis.shtml
RDoC matrix. (2016). Retrieved from
http://www.nimh.nih.gov/researchriorities/rdoc/constructs/rdoc-matrix.shtml
Yaseen, Z.S., Galynkera, I.I., Briggs, J., Freeda, R.D., Gabbaya, V. (2016). Functional domains
as correlates of suicidality among psychiatric inpatients Journal of affective
disorders, 203: 77-83. Retrieved from

IV. Current Limitations and Best Practices in the Search for a Biomarker
The limitations of the studies in this paper are not an absolute refutation of the reasons
and evidence presented by the researchers. They are necessary to scientific reporting and are
important to keep in mind, and perhaps rule out, in future study. We begin with a discussion of
the general limitations of current research that appear in all three studies from the beginning of
this chapter. All three papers report that their research was limited by inconsistency between
measurement metrics, limited, unrepresentative cohorts, and small sample size. The latter two
limitations are to be expected due to the difficulty in obtaining a large enough sample who may
meet the criteria for a specific test, on specific dates, at specific times. The former limitation, an
inconsistency between measurement metrics, can be remedied with current and general
acceptance of verified standard measurement tools. There are also some possible conflicts of
interest reported in these papers, specifically the first two, that are necessary additions to the
reporting of the research. Drs. Wilcox and Kaminsky, as of the time of the publishing of studies
one and two, has a patent application for a DNA methylation blood biomarker for suicide, among
other psychiatric symptoms. They, as well as other authors listed are funded by a variety of
financially interested parties (Guintivano, et al. 2014; Kaminsky, et al. 2015). We hope that our
researchers have the greater good in mind when conducting medical research, but it is always in
the best interest of the science to keep in mind that there are ways for results to be
misinterpreted, or overextended, and confirmation bias is always a peril in research. This bias
can be present unbeknownst to the researcher, but can affect the results nonetheless.
Other limitations that apply to all three studies, not discussed in any article, are the
presence or absence of medications, diet, and other environmental factors, such as air quality,
substance use. It is not out of the question that these confounding factors may have a large effect
on epigenetics and in tissue, blood, and other samples in general.
There are also limitations that are unique to each study. The Kaminsky, et al. (2015)
paper investigating SKA2 and its methylation as a biomarker for suicidality acknowledges the
following, additional limitations: the authors state that the psychological assessments themselves
may affect methylation levels, calling into question the validity of current gene methylation
studies, generally (Kaminsky, et al. 2015). Hopefully, further studies can find a way to rule out
this confound.
Sadeh, et al. (2016) mention that age and the effects of the passage of time also could
have an effect on methylation levels and cannot be ruled out with the current results (Sadeh, et
al. 2016).
As stated in the beginning of this section, there is no limitation listed that negate the
results obtained from these studies. Future studies can be improved with the acknowledgement
of such weaknesses, and the case for biomarkers in determining suicide risk, and also for risk
related to other psychiatric symptoms, remains a strong one and the current state of the field is
exciting and promising.

References
Guintivano, J., Brown, T., Newcomer, A., Jones, M., Cox, O., Maher, B. S., . . . Kaminsky, Z. A.
(2014). Identification and replication of a combined epigenetic and genetic biomarker
predicting suicide and suicidal behaviors. The American Journal of Psychiatry, 171(12),
1287-1296. doi:10.1176/appi.ajp.2014.14010008 Retrieved from
http://proxy.library.upenn.edu:2899/doi/abs/10.1176/appi.ajp.2014.14010008
Kaminsky, Z., Wilcox, H. C., Eaton, W. W., Van Eck, K., Kilaru, V., Jovanovic, T., . . . Smith,
K. (2015). Epigenetic and genetic variation at SKA2 predict suicidal behavior and post-
traumatic stress disorder. Translational Psychiatry, 5, e627.doi:10.1038/tp.2015.105
Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/26305478
Sadeh, N., Wolf, E.J., Logue, M.W., Hayes, J.P., Stone, A., Griffin, L.M., Schichman, S., and
Miller, M.W. (2016). Epigenetic variation at ska predicts suicide phenotypes and
internalizing psychopathology. Depression and Anxiety, 33(4), 308-315.
doi:10.1002/da.22480
Retrieved from http://proxy.library.upenn.edu:2154/doi/10.1002/da.22480/abstract

CONCLUSION
It is impossible for any one researcher to have in mind all of the information that even
their field of expertise encompasses, especially in the field of neurobiology as it pertains to
psychology. The DSM is a useful tool for classifying patients and identifying patterns across a
wide variety of populations and a wide variety of categories, but it has not provided the research
community the necessary tools to further study psychological illness at the same high level of
other medical problems. The RDoC seeks to rectify this discrepancy and hopefully bring more
effective treatments to more people. With this new initiative, and with a rigorous, rational, and
logical approach to informing the other members of the research community, the search for
scientific explanations that lead to evidence-based treatments will be enhanced and we will be
ready to continue into the 21st
century. As we all continue in this process of growth, learning,
and training as scientists and academics, there are a couple of things that we can do to apply this
rigorous, rational, and logical approach to scientific literature and discussion. In reviewing,
discussing, and reporting out information, we can look for the logic and line of reasoning in that
which we are examining; we can keep in mind the audience to whom we write and/or speak; we
can highlight possible limitations and confounding variables to the work at hand; and we can
seek to verify the results that we, or others, have obtained. The science that we do deserves this
treatment and further study is easier and made more accurate with proper reporting.

ACKNOWLEDGEMENTS
This work, especially Chapter One, was a collaboration with many authors. I would like
to thank my co-authors, the Summer Session I class of BIBB 480 (Biological Basis of
Psychiatric Disorders) at the University of Pennsylvania. Chapter One could not have been
written as timely, and with such perspective, alone. Credit is also due to Dr. Nedra Lexow as
guiding expert and facilitator.

APPENDIX
FIGURE A1
This is a visual representation of the Negative Valence Systems Domain and its associated
Constructs, with the particular elements of the Units of Analysis for the construct of Frustrative
Nonreward. Suicidality could be inserted into many places in the RDoC; based on the Yaseen, et
al. 2016 paper, I added, as an example of how the RDoC may be used, as a unit of analysis for
“Behavior.” The various self-report measures related to suicidality could, perhaps, be added to
the RDoC in this construct under the self-report unit of analysis. All information from this visual
representation was obtained from the NIMH website (NIMH 2016).

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