Whenever I read the DSM, I always thought I had EVERYTHING.  Russ Poldrack provides a glimpse into what the future of diagnosing mental illness might look like using slightly more objective and quantifiable measures of the brain’s biological processes.

Does this mean that mental suffering will no longer be commodified in the mental health “biz” ?  Um, I doubt it, but hopefully the turn away from the DSM toward the RDoC will open some new pathways to treatment.

Studies on adopted children raised by parents in hostile marriages: show (obviously) that frustration and anger begets frustration and anger … irrespective of genes.

“Although there was no direct association between birth mother anger/frustration and toddler anger/frustration, as noted above, birth mother anger/frustration significantly moderated the relation between adoptive parent marital hostility and later toddler anger/frustration. This genetic moderation is consistent with the premise that children whose birth mothers report higher levels of anger/frustration inherit an emotional lability, making them more susceptible to the negative impact of marital hostility.”

But, for an unfortunate few … the doubly unfortunate experience of having an “inherited emotional lability” while being raised in an emotionally harsh environment, can mean a lifetime of emotional anguish, stress-related-physical suffering and falling through the cracks of society.

Learning to read emotions and faces is important for our well-being.  For some of us, the act of gazing into another person’s eyes is innately rewarding … especially if they are smiling.  New mothers and their infants can be found locked in each others smiling countenance … thus strengthening the developing neural pathways upon which the infant’s future social skills will grow.

One component of these neural pathways is the CNR1 gene expressed in the striatum and other brain regions that process rewarding and positively-reinforcing stimuli.  For most of us, a happy smiling face is positively rewarding … moreso with certain CNR1 genotypes.

From Drs. Baron-Cohen and Chakrabarti:

“A comparison of these results with those from our earlier fMRI study reveals that for the SNP rs806377, the allelic group (CC) associated with the highest striatal response is also associated with the longest gaze duration for happy faces. For rs806380, the allelic group associated with the highest striatal response (GG) is also associated with the longest gaze duration for happy faces.”

My 23andMe profile shows both the long-gaze CC and GG genotypes for rs806377 and rs806380.  Mmmmkay … I guess this would be a good time to apologize to all the girls I inappropriately stared at in the cafeteria back in college … even though you weren’t usually smiling back at me.  I guess my CNR1 and striatum were pretty overactive.

The above images are eigenfaces … which are statistically distilled basic components of human faces … from which ANY human face can be reconstructed as a combination of the above basic components.  It’s a great mathematical trick – particularly if you’re into the whole mass surveillance and electronic police state thing.

If you are more into the whole, helping people and medical care thing, check out the global consortia at ENIGMA who have been carrying out massive genetic and brain scanning studies - like this one involving 437,607 SNPs in 31,622 voxels in 731 subjects using their new method, vGeneWAS, to study Alzheimer’s Disease:

“We hypothesized that vGeneWAS would, in some situations, have greater power to detect associations than existing SNP-based methods. One such situation might be when a gene contains many loci with weak individual effects. In addition, we expected that vGeneWAS would have greater overall power than mass SNP-based methods, like vGWAS, because of the drastic reduction in the effective number of statistical tests performed.”

The vGeneWAS method relies on the calculation of “eigenSNPs” which are eigenvectors that describe a matrix of n subjects by m SNPs in an individual gene (an n-x-m matrix of 1′s,0′s,-1′s for aa, aA, AA genotypes).  EigenSNPs are sort of like eigenfaces insofar as eigenSNPs (which are not actual SNPs) capture the majority of variance, or the basic essence of an individual gene … but seriously, you should read the original article ’cause every stats test I ever took totally punched me in the face.

In any case, the eigenSNP-by-voxel method pulled out some legit results such as rs2373115 (where the G-allele confers risk) in the GAB2 gene  which has repeatedly been implicated in the risk of age-related late-onset Alzheimer’s Disease (in folks who carry ApoE4  rs429358(C) alleles).  The authors found that the genetic risk of AD conferred by GAB2 may arise by way of GAB2′s effect on brain structure in the periventricular areas, which have been known to be among the first brain regions to show AD-related changes (time-lapse movie of AD tissue loss in the brain).

Genes that confer risk for illness are ideal targets for prevention and treatment.  So, also, are genes associated with natural or treatment-based RECOVERY from illness.  In a search for “recovery genes”, association studies in women who have recovered from eating disorders (ED) vs. those who are still struggling to recover reveals that the C-allele of rs17536211 is associated with recovery.

From Bloss et al.:  ”Given the substantial genetic component in the etiology of EDs in general, it follows that there may be genetic variants that contribute to the likelihood of recovery.”

“These were women who were over age 25 years, carried a lifetime diagnosis of either AN, BN, or ED-NOS (ie, subthreshold AN or BN), and for whom data were available regarding the presence (n=361 endorsed ongoing ED symptoms in the past year and considered ‘ill’) or absence (n=115 no ED symptoms in the past year and considered ‘recovered’) of ED symptoms.”

“rs17536211, an intronic SNP in GABRG1 on chromosome 4, showed the strongest statistical evidence of association with a GC-corrected p-value of 4.63 × 10⁻⁶, which corresponds to an FDR of 0.021 (Figure 1). The odds ratio (OR) observed for this SNP is 0.46, suggesting that possession of copies of the minor allele [C] is protective from long-term chronic illness (ie, it is associated with recovery).”

How might this SNP confer a protective effect?  The authors review data on the role of GABRG1 subunits in the un-learning of conditioned fear responses ["GABRG1 subunits are found in the lateral inputs, a region that arises from the intercalated cells masses, and is thought to be responsible for mediating inhibition of amygdala output during extinction of conditioned fear (Likhtik et al, 2008)"] and suggest that individuals with the protective C-alleles may be slightly more able to uncouple eating from a very real and debilitating fear response.

*photo credit

This chart from John Hawks shows how brain volume (y-axis) has increased gradually during the past 2 million years of human evolution.   rs31480 is an interesting SNP because individuals homozygous for the ancestral “C” allele have slightly smaller cranial volumes than TT individuals (well, at least the individuals in this particular study do).  The SNP is located in the IL3 gene which regulates proliferation in a variety of cell types including neural progenitor cells – thus possibly influencing the development of overall brain size.

Personal sidenote – I have a kind of a big head – literally – but 23andMe does not cover rs31480.  So, yeah, that whole mystery remains. 

Let’s be honest.  We are all great liars … to ourselves, and others.  The big blatant lies (I swear I never had sex with Monica Lewinsky) and the little well-meaning lies (No honey, that dress does not make your butt look big) and especially the lies that contain just enough truth as to seem believable on a global scale (Lowering taxes on the rich will spur economic growth) … are what make our lives, and daytime TV, so interesting.

Pity the poor human brain … for some people think that IT cannot tell a lie. Scientists in collaboration with law enforcement have been measuring the  P300 brain wave  as a sort of lie detector (here, here, here) more specifically  ”an accurate, and countermeasure (CM)-resistant P300-based Guilty Knowledge Test.”

Interestingly, the properties of the P300 neural biomarker are highly heritable and associated with a variety of genetic polymorphisms - including rs521674 located in the noradrenergic receptor ADRA2A gene (functions in the alerting and stress response elicited when lying/trying not to lie).

I’m an AT heterozygote at rs521674 and proud of my pro-deceitful suppressed P300 … and I don’t give a crap if my subconscious brain knows it or not.  As a balding overweight married stay-at-home father of two rambunctious children, lying to myself is really all I have going for me.

We all have social networks.  Your friends and family are a network of relationships.  The neural networks in your brain that carry out computations involved in social interactions are another type of “social network”.  These two networks are obviously related – in so far as your ability to self-reference and understand your own internal thoughts and feelings predicts how well you can understand and predict the internal thoughts and feelings of others – and thus how extensive your network of friends and family is likely to be.  The structure of your brain networks may even be related to how many friends you have on facebook.

According to Lencz and colleagues, there is a genetic association between the T-allele of rs1344706 and the structure and connectivity of the neural networks that carry out self-referential processing in the brain … in the so-called “default mode network” that is associated with “stimulus independent” mental activity and with social cognition such as when you are attributing mental states to others.

Interestingly, the T-allele of this SNP – residing in the zinc finger protein 804A gene - has been previously associated with schizophrenia (SZ).

From Lencz and colleagues:

“To our knowledge, this is also the first study to identify a genetic correlate of multiple brain regional GM volumes comprising the default mode network.”

The default mode network comprises regions that show synchronized activity at ‘resting’ baseline, in the absence of specific stimulation (Raichle et al, 2001). Ongoing work has implicated this network in the development of self-referential thought (Spreng and Grady, 2010), which has been specifically implicated in the developmental psychopathology of SZ (Nelson et al, 2009).

[link to research article on loss-of-function variants in the human genome]

Never … except when it’s about male pattern baldness.