Virginia Hughes has a nice piece out on generational transmission of……experiences. In this case she focuses on a paper by Dias and Ressler (2014) showing that if you do fear conditioning to a novel odor in mice, the next two generations of offspring of these mice retain sensitivity to that odor.

This led me to mention that there is a story in substance abuse that has been presented at meetings in the past couple of years that is fascinating. Poking around I found out that the group of Yasmin Hurd (this Yasmin Hurd, yes) has a new paper out. I’ve been eagerly awaiting this story, to say the least.

Szutorisz H, Dinieri JA, Sweet E, Egervari G, Michaelides M, Carter JM, Ren Y, Miller ML, Blitzer RD, Hurd YL. Parental THC Exposure Leads to Compulsive Heroin-Seeking and Altered Striatal Synaptic Plasticity in the Subsequent Generation.Neuropsychopharmacology. 2014 Jan 2. doi: 10.1038/npp.2013.352. [Epub ahead of print] [PubMed, Neuropsychopharmacology]

This study was conducted with Long-Evans rats. The first step was to expose both male and female rats, during adolescence, to Δ9tetrahydrocannabinol (THC) at a dose of 1.5 mg/kg, i.p. every third day from Post Natal Day 28-49. No detectable THC was still present in the animals 16 (and 28) days later. The animals were bred at PND 64-68. Parallel Vehicle exposed rats were the comparison.

The resulting pups were fostered out to surrogate mothers in new “litters” consisting of approximately equal male/female pubs and an equal number from the THC-exposed and Vehicle-exposed parents. So this rules out any effects the adolescent THC might have on parenting behavior (that would affect the pups) and mutes any effect of littermates who are offspring of the experimental or control parents.

TransGenerationalTHCheroinThe paper shows a number of phenotypes expressed by the offspring of parents exposed to THC in adolescence. I’ve picked the one that is of greatest interest to me to show. Figure 1d from the paper depicts behavioral data for a heroin intravenous self-administration study conducted when the offspring had reached adulthood. As you can see, under Fixed-Ratio 5 (5 presses per drug infusion) the animals with parents who were exposed to THC pressed more for heroin than did the control group. They were equal in presses directed at the inactive lever and exhibited equal locomotor activity during the self-administration session. This latter shows that the drug-lever pressing was not likely due to a generalized activation or other nonspecific effect.

The paper contains some additional work- electrophysiology showing altered Long Term Depression in the dorsal striatum, differential behavior during heroin withdrawal and alterations in glutamate and dopamine-related gene expression. I’ll let you read the details for yourself.

But the implications here are stunning and much more work needs to be completed post-haste.

We’ve known for some time (centuries?) that substance abuse runs in families. The best studied case is perhaps alcoholism. The heritability of alcoholism has been established using human twin studies, family studies in which degree of relatedness is used and adoption studies. Establishing that alcoholism has a heritable component led to attempts to identify genetic variations that might confer increased risk.

The findings of Szutorisz and colleagues throws a new wrinkle into the usual human study designs. It may be possible to identify another factor- parental drug exposure- which explains additional variability in family outcomes. This would probably help to narrow the focus on the genetic variants that are important and also help to identify epigenetic mechanism that change in response to actual drug use.

On the pre-clinical research side… Is it via the male or female…or is it both? Does the specific developmental window of exposure (this was adolescent) matter? Does the specific drug matter? Is the downstream effect limited to some substances but not others? Is there a general liability for affective disorder being wrought? Does the effect continue off into subsequent generations? Can it be amped up in magnitude for the F2 generation (and onward) if the F0 and F1 generations are both exposed?

I think if this finding holds up it will help to substantially advance understanding of how An Old Family Tradition can become established. As I posted before:

In his classic song the great philosopher and student of addictive disorders, Hank Williams, Jr., blames a traditional source for increasing the probability of developing substance abuse:

….Hank why do you drink?
(Hank) why do you roll smoke?
Why must you live out the songs you wrote?
Stop and think it over
Try and put yourself in my unique position
If I get stoned and sing all night long
It’s a family tradition!

A communication to the blog raised an issue that is worth exploring in a little more depth. The questioner wanted to know if I knew why a NIH Program Announcement had disappeared.

The Program Announcement (PA) is the most general of the NIH Funding Opportunity Announcements (FOAs). It is described with these key features:

  • Identifies areas of increased priority and/or emphasis on particular funding mechanisms for a specific area of science
  • Usually accepted on standard receipt (postmarked) dates on an on-going basis
  • Remains active for three years from date of release unless the announcement indicates a specific expiration date or the NIH Institute/Center (I/C) inactivates sooner

In my parlance, the PA means “Hey, we’re interested in seeing some applications on topic X“….and that’s about it. Admittedly, the study section reviewers are supposed to conduct review in accordance with the interests of the PA. Each application has to be submitted under one of the FOAs that are active. Sometimes, this can be as general as the omnibus R01 solicitation. That’s pretty general. It could apply to any R01 submitted to any of the NIH Institutes or Centers (ICs). The PAs can offer a greater degree of topic specificity, of course. I recommend you go to the NIH Guide page and browse around. You should bookmark the current-week page and sign up for email alerts if you haven’t already. (Yes, even grad students should do this.) Sometimes you will find a PA that seems to fit your work exceptionally well and, of course, you should use it. Just don’t expect it to be a whole lot of help.

This brings us to the specific query that was sent to the blog, i.e., why did the PA DA-14-106 go missing, only a week or so after being posted?

Sometimes a PA expires and is either not replaced or you have happened across it in between expiration and re-issue of the next 3-year version. Those are the more-common reasons. I’d never seen one be pulled immediately after posting, however. But the NOT-DA-14-006 tells the tale:

This Notice is to inform the community that NIDA’s “Synthetic Psychoactive Drugs and Strategic Approaches to Counteract Their Deleterious Effects” Funding Opportunity Announcements (FOAs) (PA-14-104, PA-14-105, PA-14-106) have been reposted as PARs, to allow a Special Emphasis Panel to provide peer review of the applications. To make this change, NIDA has withdrawn PA-14-104, PA-14-105, PA-14-106, and has reposted these announcements as PAR-14-106, PAR-14-105, and PAR-14-104.

This brings us to the key difference between the PA and a PAR (or a PAS):

  • Special Types
    • PAR: A PA with special receipt, referral and/or review considerations, as described in the PAR announcement
    • PAS: A PA that includes specific set-aside funds as described in the PAS announcement

Applications submitted under a PA are going to be assigned to the usual Center for Scientific Review (CSR) panels and thrown in with all the other applications. This can mean that the special concerns of the PA do not really influence review. How so? Well, the NIDA has a generic-ish and long-running PA on the “Neuroscience Research on Drug Abuse“. This is really general. So general that several entire study sections of the CSR fit within it. Why bother reviewing in accordance with the PA when basically everything assigned to the section is, vaguely, in this sphere? And even on the more-specific ones (say, Sex-Differences in Drug Abuse or HIV/AIDS in Drug Abuse, that sort of thing) the general interest of the IC fades into the background. The panel is already more-or-less focused on those being important issues.  So the Significance evaluation on the part of the reviewers barely budges in response to a PA. I bet many reviewers don’t even bother to check the PA at all.

The PAR means, however, that the IC convenes their own Special Emphasis Panel specifically for that particular funding opportunity. So the review panel can be tailored to the announcement’s goals much in the way that a panel is tailored for a Request for Applications ( RFA) FOA. The panel can have very specific expertise for both the PAR and for the applications that are received and,  presumably, have reviewers with a more than average appreciation for the topic of the PAR. There is no existing empaneled population of reviewers to limit choices. There is no distraction from the need to get reviewers who can handle applications that are on topics different from the PAR in question. An SEP brings focus. The mere fact of a SEP also tends to keep the reviewer’s mind on the announcement’s goals. They don’t have to juggle the goals of PA vs PA vs PA as they would in  a general CSR panel.

As you know, Dear Reader, I have blogged about both synthetic cannabinoid drugs and the “bath salts” here on this blog now and again. So I can speculate a little bit about what happened here. These classes of recreational drugs hit the attention of regulatory authorities and scientists in the US around about 2009, and certainly by 2010. There have been a modest but growing number of papers published. I have attended several conference symposia themed around these drugs. And yet if you do some judicious searching on RePORTER you will find precious few grants dedicated to these compounds. It it no great leap of faith to figure that various PIs have been submitting grants on these topics and are not getting fundable scores. There are, of course, many possible reasons for this and some may have influenced NIDA’s thinking on this PA/PAR.

It may be the case that NIDA felt that reviewers simply did not know that they wanted to see some applications funded and were consequently not prioritizing the Significance of such applications. Or it may be that NIDA felt that their good PIs who would write competitive grants were not interested in the topics. Either way, a PA would appear to be sufficient encouragement.

The replacement of a PA with a PAR, however, suggests that NIDA has concluded that the problem lies with study section reviewers and  that a mere PA was not going to be sufficient* to focus minds.

As one general conclusion from this vignette, the PAR is substantially better than the PA when it comes to enhancing the chances for applications submitted to it. This holds in a case in which there is some doubt that the usual CSR study sections will find the goals to be Significant. The caveat is that when there is no such doubt, the PAR is worse because the applications on the topic will all be in direct competition with each other. The PAR essentially guarantees that some grants on the topic will be funded, but the PA potentially allows more of them to be funded.

It is only “essentially” because the PAR does not come with set-aside funds as does the RFA or the PAS. And I say “potentially” because this depends on their being many highly competitive applications which are distributed across several CSR sections for a PA.


*This is a direct validation of my position that the PA is a rather weak stimulus, btw.

As always when it comes to NIDA specifics, see Disclaimer.

Pot kills?

February 25, 2014

Apparently pot CAN kill.


Hartung and colleagues conclude from two Cases:

After exclusion of other causes of death we assume that the young men died from cardiovascular complications evoked by smoking cannabis….The assumption of fatal heart failure in both cases is corroborated by the acute effects of marijuana, including a marked increase in heart rate that may result in cardiac ischemia in susceptible individuals, lesser increases in cardiac output, supine blood pressure and postural hypotension….We assume the deaths of these two young men occurred due to arrhythmias evoked by smoking cannabis; however this assumption does not rule out the presence of predisposing cardiovascular factors.


The Legislative Mandates have been issued for FY 2014.

The intent of this Notice is to provide information on the following statutory provisions that limit the use of funds on NIH grant, cooperative agreement, and contract awards for FY2014.

It contains the usual familiar stuff, of pointed interest is the prohibition against using grant funds to promote the legalization of Schedule I drugs and the one that prohibits any lobbing of the government. With respect to the Schedule I drugs issue, for a certain segment of my audience, I remind you of the critical exception:

(8) Limitation on Use of Funds for Promotion of Legalization of Controlled Substances (Section 509)
“(a) None of the funds made available in this Act may be used for any activity that promotes the legalization of any drug or other substance included in schedule I of the schedules of controlled substances established under section 202 of the Controlled Substances Act except for normal and recognized executive-congressional communications. (b)The limitation in subsection (a) shall not apply when there is significant medical evidence of a therapeutic advantage to the use of such drug or other substance or that federally sponsored clinical trials are being conducted to determine therapeutic advantage.”

I wouldn’t like to find out the hard way but I would presume this means that research into the medical benefits of marijuana, THC and/or other cannabinoid compounds are just fine. I seem to recall reading more than one paper listing NIH support that might be viewed in this light.

What I found more fascinating was a little clause that I had not previously noticed in the anti-lobbying section.

(3) Anti-Lobbying (Section 503)

(c) The prohibitions in subsections (a) and (b) shall include any activity to advocate or promote any proposed, pending or future Federal, State or local tax increase, or any proposed, pending, or future requirement or restriction on any legal consumer product, including its sale or marketing, including but not limited to the advocacy or promotion of gun control.”

there is also another stand-alone section in case you didn’t get the point:

(2) Gun Control (Section 217)
“None of the funds made available in this title may be used, in whole or in part, to advocate or promote gun control.”

I was sufficiently curious to go back through the years and found out that this language did not appear in the Notice for FY 2011 and was inserted for FY 2012. This was part of the “FY 2012 the Consolidated Appropriations Act, 2012 (Public Law 112-74) signed into law on December 23, 2011“. I didn’t bother to go back through the legislative history and try to figure out when the gun control part was added but it looks like something similar that affected the CDC appropriation was put into place in 1996.

So I guess we should have expected the anti-gun-control forces to get around to it eventually?

A reasonably provocative paper which suggests that automobile drivers are impaired at a blood alcohol concentration (BAC) as low as 0.01% has recently appeared.

Phillips DP, Sousa AL, Moshfegh RT. Official blame for drivers with very low blood alcohol content: there is no safe combination of drinking and driving.Inj Prev. 2014 Jan 7. doi: 10.1136/injuryprev-2013-040925. [Epub ahead of print][Pubmed][Publisher]

When I was first told of this finding, my initial curiosity was not so much about the findings but more about the design. It is incredibly difficult to come up with ways to compare drinking driver versus non-drinking driver stats in field studies or data mining retrospectives.

The authors drew data from US traffic fatalities1 recorded in the National Center for Health Statistics database and the Fatality Analysis Reporting System database. The study sought to test the hypothesis that driver BAC would be related to the driver being determined to be solely and officially at blame for the crash. There are numerous factors that were coded for drivers including “under the influence of alcohol, drugs or medication” and “driving on wrong side of the road”. The “under the influence…” factor was dropped from all analyses for the obvious reasons that it would contaminate their test of hypothesis.

This is important for the reader to grapple with his or her most obvious complaint about this design. If the police officer is determining the responsibility and can smell (or otherwise detect) alcohol on one driver, this puts a bias in the outcome measure (responsibility for the crash) that would tend to correlate with the thing being tested (BAC). So the authors focused on the factors that were seemingly unambiguous. Such as “running off road” or “driving wrong way on one-way” versus “unsafe speed for conditions” and other ambiguous factors that depend on a police judgement.

The authors calculated the Sole Official Blame (SOB) as the number of drivers officially and solely blamed for the crash divided by the number of drivers officially assigned no blame for the crash. They also calculated the percentage of drivers blamed solely and officially for the crash divided by the total number of drivers involved. Phillips14-traffic-F1Figure 1 from the paper presents the SOB by the BAC for both male and female drivers. The solid line is the “All Blame Factors” and the dotted line is for the unambiguous factors- the far better measure2, IMO. These data do make a case that fatal crash risk is an essentially linear function of BAC. Importantly, there is no inflection of the curve at either 0.08 or 0.1 BAC which have been the US legal limits during my driving lifetime. The error bars are 95% confidence intervals and they are using lack of overlap of the 95% CI as their inferential statistic indicating a significant difference (they also include a chi-square statistic for the 0.1 BAC vs sober bin). So far, so good. BAC is linearly correlated with the risk of being the sole and officially blamed driver for a fatal accident. [UPDATE: I didn’t originally catch a bit of a dodge the authors are pulling here. The inferential analyses are conducted on the “all blame factors. Then they state “these patterns hold when one considered all blame factors or unambiguous factors”. This “pattern” language is sometimes used to skip over the fact that the inferential analysis didn’t hold up on the other variable(s). This is a big problem, given my questions about the contamination of the blame issue if the officer knows one driver had been drinking alcohol.]

An interesting side-analysis looked at the problem that BAC is not always measured which could introduce a bias. I’m assuming that the first analysis used only verified negative BAC “sober” drivers but it is hard to find this directly stated. Anyway, they looked at the correlation on a state-by-state basis between the SOB “buzzed”, aka 0.1 BAC and SOB sober (which was 2.09 for the overall dataset), and the percent of unmeasured BACs in the fatal crash listing. The correlation was negative, showing that the lower the proportion of unmeasured BACs in a state, the larger the difference between sober and 0.1% BAC drivers in fatal crash responsibility. So if anything, I guess we have to assume that a lower percentage of blood testing results in an underestimate of the crash risk.

The authors next moved on to take a crack at the question of circumstances. In essence it addressed the question of whether people driving at 0.1% BAC are doing so under risky circumstances. At night, for example.
Phillips14-traffic-F3The third Figure from the paper depicts SOB ratio and the Percent Blamed for a subset of two-car crash pairings in which one driver was sober and the other was at a positive BAC. The beauty here is that nondriver circumstances are as identical as you can get for the sober and intoxicated drivers. The authors performed 16 chi-square tests but a quick multiple-comparisons adjustment to the listed p values shows they still survive as all of them being different, BAC vs sober, for SOB and P measures. Odds of being at fault are 60/40 for 0.1% BAC versus sober and about 80/20 by the time you reach two car crashes in which one driver was at 0.08% BAC. Interestingly this is the analysis that appears to show some categorical difference between BAC of 0.1-0.3% and BAC of 0.6-0.8%. They also did a cute little comparison of paired-crashes where one driver was at 0.08 and the other was 0.5-0.7 BAC. The SOB did not differ (95% CI overlap) in this analysis.

As a final note, a bunch of supplementary analyses were provided to try to rule in or out additional driver (sex, race), vehicle (speed and model year) and circumstantial (raining, time, location) factors. The relationship of SOB with BAC persisted.

Probably my largest question about traffic risks conferred by low levels of alcohol consumption is captured by the report of the relative effect size of the “most common driver factors” in Table 1. The “Driving too fast for conditions or in excess of the posted speed limit” factor is a large contributor to SOB ratio in the 0.1-0.7%BAC drivers as well as one of the larger differences from the sober drivers. This underlines a suspicion that those who are willing to drive after a low amount of alcohol consumed are perhaps innately different from those who are not. They might be somewhat more of a risk taker. Here, we’d really want to get at the population that is willing to drive after a drink or two and look at their driving crash risk when they are sober. Methodologically, this is asking for a lot, I realize.

This is only one study, of course. There may be other data out there that show a less continuous function of fatal crash risk to BAC in this range below the current US legal limit. But this is for sure an important study.

1authors say that there is no sufficiently detailed database for nonfatal crashes, sady.

2Still trying to wrap my head around whether these “unambiguous” factors are in fact uncontaminated by the police officer’s knowledge that one of the drivers had been drinking. Presumably they write up their reports somewhat after they have investigated. Maybe I’m searching for rigor where none is needed but it still bugs me.

I last did this poll in 2009 on the old Sb version of the blog. My readership has changed, medical marijuana has marched on and, most importantly, two US states have finally legalized recreational use of marijuana. A comment on a recent post reminded me of this.

Grumble asked:

I’m not sure why the “how much did usage change” question would be interesting at all. Can’t we just say “of course usage will go up, duh?”

and I replied:

there is a species of denialist cannabis fan (we get them around here now and again) that insists that full legalization will do nothing to use rates. Their rationale is that pot is so easy to get that anyone who wants to smoke pot already does. I counter with the idea that they are biased by their subculture and proffer the counter example of *my* subcultures of interest in which there are tons of people for whom the only reason they do *not* smoke weed, on the odd occasion, is the legal status.

Well, what do you think?

Have at it peeps!

The ONDCP twitter account just posted a very interesting graph on past-month marijuana use rates in the 12-17 year old adolescent population.

This dovetails very nicely with a factoid being twittered today in the #MTF2013 hashtag which is covering the release of the mid-term data from the Monitoring the Future project.

this actually surprised me. That it was so low.

Of course, one’s first suspicion is that states which are liberal enough to pass medical marijuana laws might have adolescent populations that are more likely to smoke marijuana anyway, i.e., regardless of the medical legalization. Be nice to see a workup on teen marijuana use in these states before and after they legalized medical marijuana.