Biomarkers outperform symptoms in parsing psychosis subgroups 12/8/15 via NIH

[*GG*]

Multiple biological pathways lead to similar symptoms – NIH-funded study.

http://www.nih.gov/news-events/news...tperform-symptoms-parsing-psychosis-subgroups

GG

Figured this might be of interest to people who keep up on Psychosomatic issues in our illness, that it is not all in our heads, a Biomarker for us would be really good!

 

[alex3619]

In time it will all be biomarker driven. The days of symptom driven psychiatric diagnoses are limited ... but we are still a long long way for doing that for most psych disorders, if not nearly all of them. Thanks for this article.

 

[Marco]

Fascinating - thanks.

We NEED research like this but do we really need to fret about 'strict' criteria of ME/CFS?

"The results lend support to the institute’s Research Diagnostic Criteria (RDoC) initiative, which frees scientists from designing research based on traditional diagnostic categories, encouraging them to explore groupings based on genomics, behavioral dimensions, physiological traits, or brain imaging findings. More precise diagnosis is expected to lead to improved treatments."

 

[Simon]

Three biomarker-based categories, called biotypes, outperformed traditional diagnoses, such as schizophrenia and bipolar disorder with psychosis, in sorting psychosis cases into distinct subgroups on the basis of brain biology...

“The biotypes were more biologically homogeneous than categories based on observable symptoms,” explained Bruce Cuthbert, Ph.D., acting director of the NIH’s National Institute of Mental Health (NIMH), which funded the study. “Just as fever or infection can have many different causes, multiple psychosis-causing disease processes – operating via different biological pathways – can lead to similar symptoms, confounding the search for better care.”

Fascinating. Couldn't find the underlying study, though

 

[A.B.]

So this confirms what many have been thinking right? That criteria based on description of symptoms are really inadequate in some diseases.

 

[alex3619]

@A.B, this is already well known, but the problem has always been what to do about it.

 

[Woolie]

@Simon, here is the original article.

Identification of Distinct Psychosis Biotypes Using Brain-Based Biomarkers
Brett A. Clementz, Ph.D., John A. Sweeney, Ph.D., Jordan P. Hamm, Ph.D., Elena I. Ivleva, M.D., Ph.D., Lauren E. Ethridge, Ph.D., Godfrey D. Pearlson, M.D., Matcheri S. Keshavan, M.D., Carol A. Tamminga, M.D.

Objective: Clinical phenomenology remains the primary means for classifying psychoses despite considerable evidence that this method incompletely captures biologically mean- ingful differentiations. Rather than relying on clinical diagnoses as the gold standard, this project drew on neurobiological heterogeneity among psychosis cases to delineate subgroups independent of their phenomenological manifestations.

Method: A large biomarker panel (neuropsychological, stop signal, saccadic control, and auditory stimulation paradigms) characterizing diverse aspects of brain function was collected on individuals with schizophrenia, schizoaffective disorder, and bipolar disorder with psychosis (N=711), their first-degree relatives (N=883), and demographically comparable healthy subjects (N=278). Biomarker variance across paradigms was exploited to create nine integrated variables that were used to capture neurobiological variance among the psychosis cases. Data on external validating measures (social functioning, structural magnetic resonance imaging, family biomarkers, and clinical information) were collected.

Results: Multivariate taxometric analyses identified three neurobiologically distinct psychosis biotypes that did not respect clinical diagnosis boundaries. The same analysis procedure using clinical DSM diagnoses as the criteria was best described by a single severity continuum (schizo- phrenia worse than schizoaffective disorder worse than bipolar psychosis); this was not the case for biotypes. The external validating measures supported the distinctiveness of these subgroups compared with clinical diagnosis, highlighting a possible advantage of neurobiological versus clinical categorization schemes for differentiating psychotic disorders.

Conclusions: These data illustrate how multiple pathways may lead to clinically similar psychosis manifestations, and they provide explanations for the marked heterogeneity observed across laboratories on the same biomarker vari- ables when DSM diagnoses are used as the gold standard.[/quotes]

 

[Sean]

Biomarkers more reliable than subjectively assessed symptoms.

Surprise!

Not.

 

[Woolie]

I have mixed feelings about this paper. I really like the idea behind the approach - of cutting across the traditional diagnostic boundaries and looking for other, better ways of differentiating people with psychiatric disorders. And its an impressive sample, of more than 700 patients - wow!

But what I find odd is that they didn't justify why they chose the measures they did. And the measures were actually behavioural, not biological ones - even though they keep using the word "biological" everywhere. Its like they just gathered together a lot of tasks that people with psychosis have previously been found to perform poorly on.

It turns out some people are impaired on one group of tasks/measures and not the other, and others show the opposite pattern (there's a third group, but they're just less impaired on everything, so they don't seem to count as a qualitatively different group)

The MRI scans don't offer much at all. The two main groups have more widespread grey matter loss than the other (the one that is less impaired on everything), but the patterns for these two main groups do not appear to be qualitatively different.

I didn't come away from the paper convinced that this method of discriminating amongst patients is better than the traditional method. What you'd need in order to be convincing here is some sort of theoretical framework which was consistent with the patterns, or some evidence that they're more useful in some practical way - like predicting responsiveness to treatment or prognosis or something.

However, it's definitely interesting data, and a step in the right direction.