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OT128: Opentos Thread

This is the bi-weekly visible open thread (there are also hidden open threads twice a week you can reach through the Open Thread tab on the top of the page). Post about anything you want, but please try to avoid hot-button political and social topics. You can also talk at the SSC subreddit or the SSC Discord server – and also check out the SSC Podcast. Also:

1. Comments of the week: scchm presents an apparently original theory that buspirone works on D4 receptors (but see the whole thread, including my comments). And Murphy gives some pointers for determining when to believe claims of large effects from single genes.

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APA Meetup This Saturday

I’d like to meet any SSC readers who will be at the American Psychiatric Association meeting this weekend in San Francisco.

I propose lunch on Saturday 5/18, 12 PM. We can meet at Room 312 (randomly chosen as a room that doesn’t seem to be occupied at the time; if I’m wrong and it’s in use we’ll congregate awkwardly by the door) then go to a nearby restaurant. I’ll be wearing a dark blue shirt (if I remember), the silver spiral necklace I use as my avatar in the comments, and a nametag with my real name (Scott S_____). Please watch this post for potential emergency changes in time/location.

If you’re thinking of coming, send me an email at scott@slatestarcodex.com with your phone number so I know how many people to expect/wait for and can contact you if needed. If you don’t send me an email on time, don’t worry, you can still show up.

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A Critical Period For Lactation Fetishes

Enquist et al on lactation fetishes is one of my favorite papers.

They wonder – as we’ve all wondered at one point or another – how people develop fetishes. One plausible hypothesis is “sexual imprinting”. During childhood, you have a critical period (maybe ages 1 to 5) where you figure out what sex is. If you see some weird stuff during that time, you could end up with a fetish. For example, a child who sees latex used in a sexualized way (for example, they catch a glimpse of a sexy movie where someone is wearing latex) might grow up with a latex fetish.

Enquist et al realize lactation fetishes offer a natural test of this hypothesis. Children with younger siblings will see a lot of breastfeeding going on during their critical window; children without younger siblings will see less. Since it’s easy to ask people how many siblings they have, you can see if younger siblings correlate with lactation fetishes.

They survey some online lactation fetishist communities and ask everyone how many older and younger siblings they have. Although by chance we would expect an equal number of both, in fact the fetishists have many more younger than older siblings:

They interpret this as support for their critical window theory.

But their graph looks a lot like this graph of SSC readers:

I use the opposite order they do, but both graphs show the same thing: more older than younger siblings.

I interpret the SSC data as showing a birth order effect on intellectual curiosity. But if this is true, it casts Enquist et al’s results into doubt. The trait I’m calling “intellectual curiosity” is linked to openness to experience. Could it also cause people to be more curious and open about fetishes, or more likely to join online communities about those fetishes?

I decided to test these hypotheses using the SSC 2019 Survey, which contained data on participants’ fetishes. I looked into lactation to replicate the Enquist results, but also into diaper fetishes, since that seemed like another fetish where exposure to the relevant stimulus would depend a lot on having a baby in the house. I also looked at latex, foot, bondage, masochism, and furry fetishes as control groups. Here are the results:

All fetishes had more older than younger siblings. But the difference was only significant in lactation fetish (p = 0.01). The difference between significant and nonsignificant results is not always itself significant, and I’m not sure how I would properly analyze this given the many different comparisons (some of which I made after seeing the data). i lean towards not being very impressed with the critical window theory on this metric.

But here’s another potential test: compare people with younger siblings to people with no siblings.

In Enquist et al’s model, the presence of a younger sibling causes the lactation fetish. In my model, the presence of an older sibling suppresses openness to experience and prevents fetish formation. So if only children behaved more like older siblings, that would support my model; if they behaved more like younger children, it would support Enquist et al.

I compared participants with no siblings to participants with a younger sibling in the critical window of less than five years age gap. Here are the results:

No difference. This suggests that having a younger sibling does not make you more likely to develop a baby-related fetish, which suggests it’s just that having an older sibling makes you less likely to develop it. This casts doubt on any simple critical window theory of fetishes, and makes it more likely that Enquist et al were just detecting the same birth order effects on openness to experience that can be found in many unusual communities.

These data are thanks to people who graciously revealed their deepest secrets for the cause of science; please be kind and don’t make fun of them or call them gross in the comments. Although I’ve made every other part of the survey publicly available, given the sensitivity of fetishes I’m keeping these particular answers private. If you are a professional researcher (or an amateur researcher with a good track record of professionalism and data integrity), and you want to test these results, please email me at scott[at]slatestarcodex[dot]com and we can discuss how to make that happen.

Age Gaps And Birth Order Effects

Psychologists are split on the existence of “birth order effects”, where oldest siblings will have different personality traits and outcomes than middle or youngest siblings. Although some studies detect effects, they tend to be weak and inconsistent.

Last year, I posted Birth Order Effects Exist And Are Very Strong, finding a robust 70-30 imbalance in favor of older siblings among SSC readers. I speculated that taking a pre-selected population and counting the firstborn-to-laterborn ratio was better at revealing these effects than taking an unselected population and trying to measure their personality traits. Since then, other independent researchers have confirmed similar effects in historical mathematicians and Nobel-winning physicists. Although birth order effects do not seem to consistently affect IQ, some studies suggest that they do affect something like “intellectual curiosity”, which would explain firstborns’ over-representation in intellectual communities.

Why would firstborns be more intellectually curious? If we knew that, could we do something different to make laterborns more intellectually curious? A growing body of research highlights the importance of genetics on children’s personalities and outcomes, and casts doubt on the ability of parents and teachers to significantly affect their trajectories. But here’s a non-genetic factor that’s a really big deal on one of the personality traits closest to our hearts. How does it work?

People looking into birth order effects have come up with a couple of possible explanations:

1. Intra-family competition. The oldest child choose some interest or life path. Then younger children don’t want to live in their older sibling’s shadow all the time, so they do something else.

2. Decreased parental investment. Parents can devote 100% of their child-rearing time to the oldest child, but only 50% or less to subsequent children.

3. Changed parenting strategies. Parents may take extra care with their firstborn, since they are new to parenting and don’t know what small oversights they can get away with vs. what will end in disaster. Afterwards, they are more relaxed and willing to let the child “take care of themselves”. Or they become less interested in parenting because it is no longer novel.

4. Maternal antibodies. Studies show that younger sons with older biological brothers (but not sisters!) are more likely to be homosexual. This holds true even if someone is adopted and never met their older brother. The most commonly-cited theory is that during a first pregnancy, the mother’s immune system may develop antibodies to some unexpected part of the male fetus (maybe androgen receptors?) and damages these receptors during subsequent pregnancies. A similar process could be responsible for other birth order effects.

5. Maternal vitamin deficiencies. An alert reader sent me Does Birth Spacing Affect Maternal Or Child Nutritional Status? It points out that people maintain “stockpiles” of various nutrients in their bodies. During pregnancy, a woman may deplete her nutrient stockpiles in the difficult task of creating a baby, and the stockpiles may take years to recover. If the woman gets pregnant again before she recovers, she might not have enough nutrients for the fetus, and that may affect its development.

How can we distinguish among these possibilities? One starting point might be to see how age gaps affect birth order effects. How close together do two siblings have to be for the older to affect the younger? If a couple has a child, waits ten years, and then has a second child, does the second child still show the classic laterborn pattern? If so, we might be more concerned about maternal antibodies or changes in parenting style. If not, we might be more concerned about vitamin deficiencies or distracted parental attention.

Methods And Results

I used the 2019 Slate Star Codex survey, in which 8,171 readers of this blog answered a few hundred questions about their lives and opinions.

Of those respondents, I took the subset who had exactly one sibling, who reported an age gap of one year or more, and who reported their age gap with an integer result (I rounded non-integers to integers if they were not .5, and threw out .5 answers). 2,835 respondents met these criteria.

Of these 2,835, 71% were the older sibling and 29% were the younger sibling. This replicates the results from last year’s survey, which also found that 71% of one-sibling readers were older.

Here are the results by age gap:

Birth order effects are strong from one-year to seven-year age gaps, and don’t differ much within that space. After seven years, birth order effects decrease dramatically and are no longer significantly different from zero.

I also investigated people who had more than one sibling, but were either the oldest or the youngest in their families.

More siblings = more problems more of a birth order effect, but the overall pattern was similar. There is a possible small decline in strength from one to seven years, followed by a very large decline between seven and eight years.

Here’s the previous two graphs considered as a single very-large-n sample:

The pattern remains pretty clear: vague hints of a decline from age 1 to 7, followed by a very large decline afterwards.

(Tumblr user athenaegalea kindly double-checked my calculations; you can see her slightly-differently-presented results here).

Weirdly, among people who reported a zero-year age gap, 70% are older siblings. This wouldn’t make much sense for twins, since here older vs. younger just means who made it out of the uterus first. I don’t know if this means there’s some kind of reporting error that discredits this entire project, whether people who were born about 9 months apart reported this as a zero year age gap, or whether it’s just an unfortunate coincidence.

These results suggest that age gaps do affect the strength of birth order effects. People with siblings seven or fewer years older than them will behave as laterborns; people separated from their older siblings by more than seven years will act like firstborn children.

Discussion

This study found an ambiguous and gradual decline from one to seven years, but also a much bigger cliff from seven to eight years. Is this a coincidence, or is there something important that happens at seven?

Most of the sample was American; in the US, children start school at about age five. Although it might make sense for older siblings stop mattering once they are in school, this would predict a cliff at five years rather than seven years.

Developmental psychologists sometimes distinguish between early childhood (before 6-8 years) and middle childhood (after that point). This is supposed to be a real qualitative transition, just like eg puberty. We might take this very seriously, and posit that having a sibling in early childhood causes birth order effects, but one in middle childhood doesn’t. But why should this be? Overall I’m still pretty confused about this.

These results may be consistent with an intra-family competition hypothesis. Children try to avoid living in the shadow of their older siblings, perhaps by avoiding intellectual pursuits those children find interesting. But if there is too much of an age gap, then siblings are at such different places that competition no longer feels relevant.

These results may be partly consistent with a parental investment hypothesis. Parents might have to split their attention between first and laterborn children, so that laterborns never get the period of sustained parental attention that firstborns do. But since an age gap as small as one year produces this effect, this would suggest that only the first year of childrearing matters; after the first year, even the firstborn children in this group are getting split attention. This is hard to explain if we are talking about as complicated a trait as “intellectual curiosity” – surely there are things parents do when a child is two or three to make them more curious?

These results don’t seem consistent with hypotheses based on changing parenting strategies or maternal antibodies, unless parenting strategies or the immune system “reset” to their naive values after a certain number of years.

They also don’t seem too consistent with vitamin-based hypotheses. I don’t know how long it takes to replenish vitamin stockpiles, and it’s probably different for every vitamin. But I would be surprised if giving people one vs. five years for this had basically no effect, but giving them eight instead of seven years had a very large effect. Overall I would expect the first year of vitamin replenishment to be the most important, with diminishing returns thereafter, which doesn’t fit the birth order effect pattern.

Overall these results make me lean slightly more towards intra-family competition or parental investment as the major cause of birth order effects. I can’t immediately think of a way to distinguish between these two hypotheses, but I’m interested in hearing people’s ideas.

I welcome people trying to replicate or expand on these results. All of the data used in this post are freely available and can be downloaded here.

Is There A Case For Skepticism Of Psychedelic Therapy?

There’s been an explosion of interest in the use of psychedelics in psychiatry. Like everyone else, I hope this works out. But recent discussion has been so overwhelmingly positive that it’s worth reviewing whether there’s a case for skepticism. I think it would look something like this:

1. Psychedelics have mostly been investigated in small studies run by true believers. These are the conditions that produce a field made of unreplicable results, like the effects of 5-HTTLPR. Some of the most exciting psychedelic findings have already failed to replicate; for example, a study two years ago found that psilocybin did not permanently increase the Openness personality trait. This was one of the most exciting studies and had shaped a lot of my thinking around the issue. Now it’s gone.

2. Some of the most impressive stories involve psychedelic-assisted psychotherapy, where people who talk with a therapist, while on a substance, obtain true insight and get real closure. But every psychotherapy has amazing success stories floating out there. Back when psychoanalysis was new, the whole world was full of people telling their amazing success stories about how Dr. Freud helped them obtain true insight and get real closure. I think of psychotherapy as a domain where people can get as many amazing success stories as they want whether or not they’re really doing anything right, for unclear reasons.

3. Ketamine is the best comparison for psychedelics. Like psychedelics, it’s often used as a recreational drug, and produces profound experiences. Like psychedelics, it got hyped as an exciting new innovation that was going to revolutionize everything in psychiatry (in this case, depression treatment). But it’s been in pretty common (albeit non-formulary) use for five years now, and nothing has been revolutionized; my (very anecdotal) impression is that most patients who seek ketamine treatment find it only about as helpful as anything else. The gold-standard FDA studies are abysmal, worse than most other antidepressant medications. I’m sure ketamine works great for some people, just as SSRIs, therapy, and diet/exercise work well for some people. But at least so far it hasn’t been revolutionary.

4. Another good comparison is NSI-189. Again, a totally revolutionary new drug with a totally revolutionary new mechanism, with so many anecdotes of amazing success that depressed people started getting it on the black market before the FDA trials were even underway. People were posting testimonials that NSI-189 changed their life and that it was going to destroy the market for every other antidepressant. When the FDA trials finally finished, it was discovered to be ineffective. Seriously, the graveyards are littered with revolutionary new treatments for treatment-resistant depression that have great success in anecdotes and preliminary studies.

5. Between 10% and 50% of Americans have tried psychedelics. If psychedelics did something shocking, we would already know about it. I occasionally hear stories like “I did LSD and my depression went away”, but I also occasionally hear stories like “I did LSD and then my depression got worse”, so whatever. I know plenty of people who use heroic amounts of LSD all the time, and are still nervous wrecks. It’s possible there’s some set and setting that will improve this, but see part 7 below.

(one exception to this might be microdosing, which is a pretty new idea and might work differently from regular trips.)

6. In my model of psychedelics, they artificially stimulate your insight system the same way heroin artificially stimulates your happiness system. This leads to all those stories where people feel like they discovered the secret of the universe, but when they recover their faculties, they find it was only some inane triviality. This sounds very likely to produce people who think their psychedelic experience has changed everything and solved all their problems, which means we should discount these impressions as evidence that psychedelics really do change everything and solve all your problems. Granted, feeling like you truly understand the universe may itself help with depression, but I worry this is not a very lasting effect. See my posts on PIHKal and Universal Love, Said The Cactus Person.

7. Even if all of the above are wrong and psychedelics work very well, the FDA could kill them with a thousand paper cuts. Again, look at ketamine: the new FDA approval ensures people will be getting the slightly different esketamine, through a weird route of administration, while paying $600 a pop, in specialized clinics that will probably be hard to find. Given the price and inconvenience, insurance companies will probably restrict it to the most treatment-resistant patients, and it probably won’t help them (treatment-resistant patients tend to stay that way). Given the panic around psychedelics, I expect it to be similarly difficult to get them even if they are legal and technically FDA-approved. Depressed people will never be able to walk into a psychiatrist’s office and get LSD. They’ll walk into a psychiatrist’s office, try Prozac for three months, try Wellbutrin for three months, argue with their insurance for a while, eventually get permission to drive to a city an hour away that has a government-licensed LSD clinic, and get some weird form of LSD that might or might not work, using a procedure optimized to minimize hallucinations. I don’t know what the optimal set and setting for LSD is, but if it’s anything other than “the inside of a government-licensed LSD clinic, having a government-licensed LSD therapist ask you standard questions”, you won’t get it.

I hope I am wrong about this, I really do. And I think there’s a good chance that I might be. I really want psychedelic research to succeed and I support it wholeheartedly. But there’s been so much hype around so many things before that I want to avoid getting burned again, so I ‘ll stay skeptical for now.

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5-HTTLPR: A Pointed Review

In 1996, some researchers discovered that depressed people often had an unusual version of the serotonin transporter gene 5-HTTLPR. The study became a psychiatric sensation, getting thousands of citations and sparking dozens of replication attempts (page 3 here lists 46).

Soon scientists moved beyond replicating the finding to trying to elucidate the mechanism. Seven studies (see here for list) found that 5-HTTLPR affected activation of the amygdala, a part of the brain involved in processing negative stimuli. In one especially interesting study, it was found to bias how the amygdala processed ambiguous facial expression; in another, it modulated how the emotional systems of the amygdala connected to the attentional systems of the anterior cingulate cortex. In addition, 5-HTTLPR was found to directly affect the reactivity of the HPA axis, the stress processing circuit leading from the adrenal glands to the brain.

As interest increased, studies began pointing to 5-HTTLPR in other psychiatric conditions as well. One study found a role in seasonal affective disorder, another in insomnia. A meta-analysis of twelve studies found a role (p = 0.001) in PTSD. A meta-analysis of twenty-three studies found a role (p = 0.000016) in anxiety-related personality traits. Even psychosis and Alzheimer’s disease, not traditionally considered serotonergic conditions, were affected. But my favorite study along these lines has to be 5-HTTLPR Polymorphism Is Associated With Nostalgia-Proneness.

Some people in bad life situations become depressed, and others seem unaffected; researchers began to suspect that genes like 5-HTTLPR might be involved not just in causing depression directly, but in modulating how we respond to life events. A meta-analysis looked at 54 studies of the interaction and found “strong evidence that 5-HTTLPR moderates the relationship between stress and depression, with the s allele associated with an increased risk of developing depression under stress (P = .00002)”. This relationship was then independently re-confirmed for every conceivable population and form of stress. Depressed children undergoing childhood adversity. Depressed children with depressed mothers. Depressed youth. Depressed adolescent girls undergoing peer victimization. They all developed different amounts of depression based on their 5-HTTLPR genotype. The mainstream media caught on and dubbed 5-HTTLPR and a few similar variants “orchid genes”, because orchids are sensitive to stress but will bloom beautifully under the right conditions. Stories about “orchid genes” made it into The Atlantic, Wired, and The New York Times.

If finding an interaction between two things is exciting, finding an interaction between even more things must be even better! Enter studies on how the interaction between 5-HTTLPR and stress in depressed youth itself interacted with MAO-A levels and gender. What about parenting style? Evidence That 5-HTTLPR x Positive Parenting Is Associated With Positive Affect “For Better And Worse” What about decision-making? Gender Moderates The Association Between 5-HTTLPR And Decision-Making Under Uncertainty, But Not Under Risk. What about single motherhood? The influence of family structure, the TPH2 G-703T and the 5-HTTLPR serotonergic genes upon affective problems in children aged 10–14 years. What if we just throw all the interesting genes together and see what happens? Three-Way Interaction Effect Of 5-HTTLPR, BDNF Val66Met, And Childhood Adversity On Depression.

If 5-HTTLPR plays such an important role in depression, might it also have relevance for antidepressant treatment? A few studies of specific antidepressants started suggesting the answer was yes – see eg 5-HTTLPR Predicts Non-Remission In Major Depression Patients Treated With Citalopram and Influence Of 5-HTTLPR On The Antidepressant Response To Fluvoxamine In Japanese Depressed Patients. A meta-analysis of 15 studies found that 5-HTTLPR genotype really did affect SSRI efficacy (p = 0.0001). Does this mean psychiatrists should be testing for 5-HTTLPR before treating patients? A cost-effectiveness analysis says it does. There’s only one problem.

ALL.

OF.

THIS.

IS.

LIES.

Or at least this is the conclusion I draw from Border et al’s No Support For Historical Candidate Gene Or Candidate Gene-by-Interaction Hypotheses For Major Depression Across Multiple Large Samples, in last month’s American Journal Of Psychiatry.

They don’t ignore the evidence I mention above. In fact, they count just how much evidence there is, and find 450 studies on 5-HTTLPR before theirs, most of which were positive. But they point out that this doesn’t make sense given our modern understanding of genetics. Outside a few cases like cystic fibrosis, most important traits are massively polygenic or even omnigenic; no one gene should be able to have measurable effects. So maybe this deserves a second look.

While psychiatrists have been playing around with samples of a few hundred people (the initial study “discovering” 5-HTTLPR used n = 1024), geneticists have been building up the infrastructure to analyze samples of hundreds of thousands of people using standardized techniques. Border et al focus this infrastructure on 5-HTTLPR and its fellow depression genes, scanning a sample of 600,000+ people and using techniques twenty years more advanced than most of the studies above had access to. They claim to be able to simultaneously test almost every hypothesis ever made about 5-HTTLPR, including “main effects of polymorphisms and genes, interaction effects on both the additive and multiplicative scales and, in G3E analyses, considering multiple indices of environmental exposure (e.g., traumatic events in childhood or adulthood)”. What they find is…nothing. Neither 5-HTTLPR nor any of seventeen other comparable “depression genes” had any effect on depression.

I love this paper because it is ruthless. The authors know exactly what they are doing, and they are clearly enjoying every second of it. They explain that given what we now know about polygenicity, the highest-effect-size depression genes require samples of about 34,000 people to detect, and so any study with fewer than 34,000 people that says anything about specific genes is almost definitely a false positive; they go on to show that the median sample size for previous studies in this area was 345. They show off the power of their methodology by demonstrating that negative life events cause depression at p = 0.000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000001, because it’s pretty easy to get a low p-value in a sample of 600,000 people if an effect is real. In contrast, the gene-interaction effect of 5-HTTLPR has a p-value of .919, and the main effect from the gene itself doesn’t even consistently point in the right direction. Using what they call “exceedingly liberal significance thresholds” which are 10,000 times easier to meet than the usual standards in genetics, they are unable to find any effect. This isn’t a research paper. This is a massacre.

Let me back off a second and try to be as fair as possible to the psychiatric research community.

First, over the past fifteen years, many people within the psychiatric community have been sounding warnings about 5-HTTLPR. The first study showing failure to replicate came out in 2005. A meta-analysis by Risch et al from 2009 found no effect and prompted commentary saying that 5-HTTLPR was an embarrassment to the field. After 2010, even the positive meta-analyses (of which there were many) became guarded, saying only that they seemed to detect an effect but weren’t sure it was real. This meta-analysis on depression says there is “a small but statistically significant effect” but that “we caution it is possible the effect has an artifactual basis”. This meta-analysis of 5-HTTLPR amygdala studies says there is a link, but that “most studies to date are nevertheless lacking in statistical power”.

Counter: there were also a lot of meta-analyses that found the opposite. The Slate article on the “orchid gene” came out after Risch’s work, mentioned it, but then quoted a scientist calling it “bullshit”. I don’t think the warnings did anything more than convince people that this was a controversial field with lots of evidence on both sides. For that matter, I don’t know if this new paper will do anything more than convince people of that. Maybe I trust geneticists saying “no, listen to me, it’s definitely like this” more than the average psychiatrist does. Maybe we’re still far from hearing the last of 5-HTTLPR and its friends.

Second, this paper doesn’t directly prove that every single study on 5-HTTLPR was wrong. It doesn’t prove that it doesn’t cause depression in children with depressed mothers in particular. It doesn’t prove that it doesn’t cause insomnia, or PTSD, or nostalgia-proneness. It doesn’t prove that it doesn’t affect amygdala function.

Counter: it doesn’t directly prove this, but it casts doubt upon them. The authors of this paper are geneticists who are politely trying to explain how genetics works to psychiatrists. They are arguing that single genes usually matter less than people think. They do an analysis of depression to demonstrate that they know what they’re talking about, but the points they are making apply to insomnia, nostalgia, and everything else. So all the studies above are at least questionable.

Third, most of these studies were done between 2000 – 2010, when we understood less about genetics. Surely you can’t blame people for trying?

Counter: The problem isn’t that people studied this. The problem is that the studies came out positive when they shouldn’t have. This was a perfectly fine thing to study before we understood genetics well, but the whole point of studying is that, once you have done 450 studies on something, you should end up with more knowledge than you started with. In this case we ended up with less.

(if you’re wondering how you can do 450 studies on something and get it wrong, you may be new here – read eg here and here)

Also, the studies keep coming. Association Between 5-HTTLPR Polymorphism, Suicide Attempts, And Comorbidity In Mexican Adolescents With Major Depressive Disorder is from this January. Examining The Effect Of 5-HTTLPR ON Depressive Symptoms In Postmenopausal Women 1 Year After Initial Breast Cancer Treatment is from this February. Association Of DRD2, 5-HTTLPR, And 5-HTTVNTR With PTSD In Tibetan Adolescents was published after the Border et al paper! Come on!

Having presented the case for taking it easy, I also want to present the opposite case: the one for being as concerned as possible.

First, what bothers me isn’t just that people said 5-HTTLPR mattered and it didn’t. It’s that we built whole imaginary edifices, whole castles in the air on top of this idea of 5-HTTLPR mattering. We “figured out” how 5-HTTLPR exerted its effects, what parts of the brain it was active in, what sorts of things it interacted with, how its effects were enhanced or suppressed by the effects of other imaginary depression genes. This isn’t just an explorer coming back from the Orient and claiming there are unicorns there. It’s the explorer describing the life cycle of unicorns, what unicorns eat, all the different subspecies of unicorn, which cuts of unicorn meat are tastiest, and a blow-by-blow account of a wrestling match between unicorns and Bigfoot.

This is why I start worrying when people talk about how maybe the replication crisis is overblown because sometimes experiments will go differently in different contexts. The problem isn’t just that sometimes an effect exists in a cold room but not in a hot room. The problem is more like “you can get an entire field with hundreds of studies analyzing the behavior of something that doesn’t exist”. There is no amount of context-sensitivity that can help this.

Second, most studies about 5-HTTLPR served to reinforce all of our earlier preconceptions. Start with the elephant in the room: 5-HTTLPR is a serotonin transporter gene. SSRIs act on the serotonin transporter. If 5-HTTLPR played an important role in depression, we were right to focus on serotonin and extra-right to prescribe SSRIs; in fact, you could think of SSRIs as directly countering a genetic deficiency in depressed people. I don’t have any evidence that the pharmaceutical industry funded 5-HTTLPR studies or pushed 5-HTTLPR. As far as I can tell, they just created a general buzz of excitement around the serotonin transporter, scientists looked there, and then – since crappy science will find whatever it’s looking for – it was appropriately discovered that yes, changes in the serotonin transporter gene caused depression.

But this was just the worst example of a general tendency. Lots of people were already investigating the role of the HPA axis in depression – so lo and behold, it was discovered that 5-HTTLPR affected the HPA axis. Other groups were already investigating the role of BDNF in depression – so lo and behold, it was discovered that 5-HTTLPR affected BDNF. Lots of people already thought bad parenting caused depression – so lo and behold, it was discovered that 5-HTTLPR modulated the effects of bad parenting. Once 5-HTTLPR became a buzzword, everyone who thought anything at all went off and did a study showing that 5-HTTLPR played a role in whatever they had been studying before.

From the outside, this looked like people confirming they had been on the right track. If you previously doubted that bad parenting played a role in depression, now you could open up a journal and discover that the gene for depression interacts with bad parenting! If you’d previously doubted there was a role for the amygdala, you could open up a journal and find that the gene for depression affects amygdala function. Everything people wanted to believe anyway got a new veneer of scientific credibility, and it was all fake.

Third, antidepressant pharmacogenomic testing.

This is the thing where your psychiatrist orders a genetic test that tells her which antidepressant is right for you. Everyone keeps talking these up as the future of psychiatry, saying how it’s so cool how now we have true personalized medicine, how it’s an outrage that insurance companies won’t cover them, etc, etc, etc. The tests have made their way into hospitals, into psychiatry residency programs, and various high-priced concierge medical systems. A company that makes them recently sold for $410 million, and the industry as a whole may be valued in the billions of dollars; the tests themselves cost as much as $2000 per person, most of which depressed patients have to pay out of pocket. I keep trying to tell people these tests don’t work, but this hasn’t affected their popularity.

A lot of these tests rely on 5-HTTLPR. GeneSight, one of the most popular, uses seven genes. One is SLC6A4, the gene containing 5-HTTLPR as a subregion. Another is HTR2A, which Border et al debunked in the same study as 5-HTTLPR. The studies above do not directly prove that these genes don’t affect antidepressant response. But since the only reason we thought that they might was because of evidence they affected depression, and now it seems they don’t affect depression, it’s less likely that they affect antidepressant response too.

The other five are liver enzymes. I am not an expert on the liver and I can’t say for sure that you can’t use a few genes to test liver enzymes’ metabolism of antidepressants. But people who are experts in the liver tell me you can’t. And given that GeneSight has already used two genes that we know don’t work, why should we trust that they did any better a job with the liver than they did with the brain?

Remember, GeneSight and their competitors refuse to release the proprietary algorithms they use to make predictions. They refuse to let any independent researchers study whether their technique works. They dismiss all the independent scientists saying that their claims are impossible by arguing that they’re light-years ahead of mainstream science and can do things that nobody else can. If you believed them before, you should be more cautious now. They are not light-years ahead of mainstream science. They took some genes that mainstream science had made a fuss over and claimed they could use them to predict depression. Now we think they were wrong about those. What are the chances they’re right about the others?

Yes, GeneSight has ten or twenty studies proving that their methods work. Those were all done by scientists working for GeneSight. Remember, if you have bad science you can prove whatever you want. What does GeneSight want? Is it possible they want their product to work and make them $410 million? This sounds like the kind of thing that companies sometimes want, I dunno.

I’m really worried I don’t see anyone updating on this. From where I’m sitting, the Border et al study passed unremarked upon. Maybe I’m not plugged in to the right discussion networks, I don’t know.

But I think we should take a second to remember that yes, this is really bad. That this is a rare case where methodological improvements allowed a conclusive test of a popular hypothesis, and it failed badly. How many other cases like this are there, where there’s no geneticist with a 600,000 person sample size to check if it’s true or not? How many of our scientific edifices are built on air? How many useless products are out there under the guise of good science? We still don’t know.

OT127: Openinsula Thread

This is the bi-weekly visible open thread (there are also hidden open threads twice a week you can reach through the Open Thread tab on the top of the page). Post about anything you want, but please try to avoid hot-button political and social topics. You can also talk at the SSC subreddit or the SSC Discord server – and also check out the SSC Podcast.

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Little Known Types Of Eclipse

A lunar eclipse occurs when the Earth gets between the Moon and the Sun.

A solar eclipse occurs when the Moon gets between the Earth and the Sun.

A terrestrial eclipse occurs when the Earth gets between you and the Sun. Happens once per 24 hours.

An atmospheric eclipse occurs when an asteroid gets between you and the sky. Generally fatal.

A reverse solar eclipse occurs when the Sun gets between the Moon and the Earth. Extremely fatal.

A motivational eclipse occurs when the Moon gets between you and your goals. You can’t let it stop you! Destroy it! Destroy the Moon!

A marital eclipse occurs when the Moon gets between you and your spouse. You’re going to need to practice good communication about the new celestial body in your life if you want your relationship to survive.

A capillary eclipse occurs when your hair gets between your eyes and the Sun. Get a haircut.

A lexicographic eclipse occurs when “Moon” gets between “Earth” and “Sun” in the dictionary. All Anglophone countries are in perpetual lexicographic eclipse.

A filioque eclipse occurs when the Holy Spirit gets between the Father and the Son.

An apoc eclipse occurs when the Great Beast 666, with seven heads and ten horns, and upon the horns ten crowns, and upon its heads the name of blasphemy, gets between the Earth and the Sun. Extremely fatal.

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Update To Partial Retraction Of Animal Value And Neuron Number

A few weeks ago I published results of a small (n = 50) survey showing that people’s moral valuation of different kinds of animals scaled pretty nicely with the animals’ number of cortical neurons (see here for more on why we might expect that to be true).

A commenter, Tibbar, did a larger survey on Mechanical Turk and got very different results, so I retracted the claim. I wasn’t sure why we got such different results, but I chalked it down to chance, or perhaps to my having surveyed an animal-rights-conscious crowd who thinks a lot about this kinds of things vs. Tibbar surveying random MTurkers.

Now David Moss, from effective altruist organization Rethink Priorities, has looked into this more deeply and resolved some of the discrepancies.

The problem is that I did a terrible job explaining my procedure (I linked to the form I used, but the link was broken when Tibbar did his survey). In particular, I included the line:

If you believe [animals have moral value] in general, but think some specific animal I ask about doesn’t work this way, feel free to leave the question blank or put in “99999”, which I will interpret as “basically infinity”

About 5 – 10% of respondents took me up on this. Tibbar didn’t make this suggestion, and none of his participants did this.

Moss surveyed 490 people on Mechanical Turk, and did not offer people a “basically infinity” option. However, many (20% – 40%) of his participants said the question didn’t apply to specific animals.

He found that when he ignored these, he got the same (low) numbers as Tibbar; when he counted an N/A answer as a vote for “basically infinity”, he got the same (high) numbers that I did.

This graph measures people’s perceptions of how many of each animal is morally equivalent to one human. “Priorities (inclusive)” is Rethink Priorities’ survey, with refusal to vote counted as “basically infinity”. “Priorities (exclusive)” is Rethink Priorities’ survey, with refusals to vote thrown out. I think this demonstrates pretty well that you can get either mine or Tibbar’s numbers depending on which choice you make.

But Moss also points out that all of this is just a fragile balance between people who say every life is worth the same regardless of species, versus people who just spam the box with as many nines as they can.

So it’s not clear how much we should be drawing from this in any case. Whatever. I still think it’s neat.

The moral of the story is to always explain your procedures really well before you try to replicate something. Also to make sure the link to your procedures actually goes to your procedures, although maybe no one other than me has ever made that specific mistake before.

Buspirone Shortage In Healthcaristan SSR

(Epistemic status: Unsure on details. Some post-publication edits 5/1 to make this less strident.)

I.

There is a national shortage of buspirone.

Buspirone is a 5HT-1 agonist used to control anxiety. Unlike most psychiatric drugs, it’s in a class of its own – there are no other sole 5HT-1 agonists on the market. It’s not a very strong medication, but it’s safe, it’s non-addictive, it’s off-patent, and it works well for a subset of patients. Some of them have been on it for years.

Now there’s a national shortage. My patients can’t get it, or have to go hunting from pharmacy to pharmacy until they find one that has it. I’ve told people find a source to stockpile a supply so they don’t run out. It feels like we’re living in the Soviet Union.

How did this happen? The New York Times writes:

The main reason for the buspirone shortage appears to be interrupted production at a Mylan Pharmaceuticals plant in Morgantown, W.Va., which produced about a third of the country’s supply of the drug. The Food and Drug Administration had said the facility was dirty and that the company failed to follow quality control procedures.

So the FDA shut down a major buspirone factory. But government agencies – ones that are a lot less nice than the FDA – shut down methamphetamine factories all the time without creating methamphetamine shortages. Why is the buspirone market so vulnerable? The Times again:

Rock bottom prices for some generic drugs are also contributing to the crisis. Consolidation among wholesalers has led to the creation of three buying consortium behemoths that purchase 90 percent of the generic pharmaceutical products in the United States, said Adam Fein, a consultant and chief executive of Drug Channels Institute. These “monster” buyers have squeezed manufacturers on prices, and “some of those generic manufacturers are deciding the profit is so low they can’t make money, and they’re exiting the category,” Dr. Fein said.

Is this really how economics works? There’s a medicine that millions of people desperately need? But nobody will produce it because they can’t make a profit? Huh? Isn’t the usual solution to just raise the price? And people will buy it at the higher price, because they need it so badly? And then you will make more profit, and can keep on making the medication? Isn’t “nobody will supply this product, it’s too cheap” just the economics version of “nobody goes there anymore, it’s too crowded”?

Sure, generic drug manufacturing is pretty consolidated. Most individual generic drugs are now manufactured only by one or two companies. If one of those few companies gets greedy (like Martin Shkreli did with Daraprim), they can increase prices by orders of magnitude without a lot of competitors to push back. And if one of those few companies suffers a shock (like the FDA closing the buspirone factory), it makes sense that there might not be enough competitors to pick up the slack.

But how come this is only happening in pharmaceuticals? How come (in capitalist countries) there are almost never meat shortages, bread shortages, laptop shortages, or chair shortages? Is there something unusual about the pharmaceutical landscape that predisposes it to this sort of thing?

I am not an expert in this area and may be getting some of it wrong. But from Berndt, Conti, and Murphy (2017) and a Berndt, Conti, and Murphy (2018), I gather that a big part of the story is the Generic Drug User Fee Amendments (GDUFA) of 2012 and 2017.

The story goes something like this. The FDA demanded that generic drug manufacturers pass FDA inspection before setting up shop. But the FDA didn’t have enough inspectors to review manufacturers in a timely manner. So companies kept asking the FDA for permission to enter the generics market, and the FDA kept telling them there was a several year waiting period. In 2012, Congress recognized the problem. Politicians, FDA officials, and industry leaders agreed on a new policy where generic drug manufacturing companies would pay the FDA lots of money (about $300 million last time anyone checked), and the FDA would use that money to hire inspectors so they could clear their backlog of applications.

The good news is, the FDA hired lots more inspectors and they are now pretty good at responding to generic drug applications in a timely way. The bad news is that the fees to the companies were designed in a way that subtly encouraged monopolies in generic drug markets. I don’t understand all the specifics, but there seem to be two main problems.

First, if you manufacture a drug, the FDA will charge you a fee, but the fee doesn’t scale linearly with how much of the drug you produce. So suppose Martin Shkreli owns a very big Daraprim factory. The FDA might charge him $1 million per year to fund their inspectors. Suppose you are a small businessman who is angry at Martin Shkreli’s fee hike, and you want to open a competing Daraprim factory in your small town, using your small amount of personal savings. Probably your factory will be much smaller than Martin Shkreli’s. But the FDA will still charge you the same $1 million per year. At worst this means you make no profit; even at best, Shkreli’s economy of scale gives him a big advantage over you. So you may decide not to enter the market at all. From the second paper:

President of the Pharma & Biopharma Outsourcing Association, Gil Roth, remarked, ‘We have a single generic client that we do a short run of production for. Why are we charged the same as a Teva facility that pumps out a billion tablets?’ Another commented, ‘At least a flat tax is based on a percentage, either of revenue or profit. This is a flat fee, which makes it a regressive tax on smaller businesses, both contract manufacturers and small generics companies’

I think the fee might even be per factory, which encourages companies to concentrate all their manufacturing at a single site – like the Mylan one that just got shut down, thus affecting the whole country’s buspirone supply.

Second, traditional economics suggests that if some company has a monopoly on a product that people really need (like a medication), they will charge very high prices. But many generic drugs are produced by only one company each – and Shkrelis aside, most of them charge affordable prices. Why? Berndt et al argue it is because of the possibility of competition: if Shkreli raises his prices too high, some other company can move in and undercut him. But FDA licensing procedures make this undercutting harder than it could be: it will take months to years, and thousands to millions of dollars, for the other company to move in (at which point Shkreli can just say “Haha, no” and lower his prices again, meaning the undercutter would lose all the money they put in).

Historically, the system has worked anyway – because lots of companies are sitting on pre-existing FDA approval to make certain drugs. If a company had ever made a drug in the past, they had FDA permission to make it again whenever they wanted. So if Shkreli raises prices on Daraprim, some other company that made Daraprim ten years ago can set up a new factory tomorrow and undercut him. This helped prevent would-be Shkrelis in most markets, and provided a safety valve for shocks like the one creating the buspirone shortage today.

But GDUFA weakened this system by mandating that any company with FDA approval to manufacture a drug pay yearly inspection fees to the FDA, whether or not they were actively manufacturing it. That turned FDA approval for drugs you weren’t actively manufacturing into a liability; you were paying fees, but not making a profit. Companies started voluntarily cancelling their FDA approvals for older drugs so they wouldn’t have to pay the fees. That meant monopolists lost a lot of their potential competition. And that cleared the way for people like Shkreli to hike prices.

You get more of what you subsidize and less of what you tax. Unfortunately, the FDA is inadvertently taxing companies for being in the generic drug business. And it’s taxing them more if they’re not a monopolist with economies of scale. That means we get fewer companies in the generics industry, and more monopolists.

So my very tentative guess as to why buspirone is more plagued by shortages than bread or chairs is because number one, the need for FDA approval makes it hard for new companies to enter the buspirone industry, and number two, the FDA’s fee structure favors large-scale monopolies over small-scale competitors.

II.

The price of insulin is much too high. Vox argues that this is because of the “lax regulatory environment” and the “free market approach”, and that if we could just become socialist like all of the cool countries, everything would be fine.

Insulin is off-patent. It was discovered almost a hundred years ago. But somehow, all the insulin sold in the US is brand-name. This is shocking and obviously the root of the problem. What’s going on? Vox links NEJM’s Why Is There No Generic Insulin?, but summarizes it by saying it’s “because companies have made those incremental improvements to insulin products, which has allowed them to keep their formulations under patent” and because “older insulin formulations have fallen out of fashion.”

I am not diabetic. But if I were, I don’t think I would worry that much which kinds of insulin were vs. weren’t fashionable. What’s really going on?

Here my source is partly the NEJM paper above, but also Health Affairs’ Biologics Are Natural Monopolies. Both agree that the key point is insulin’s nature as a “biologic”. It’s not a simple molecule you can make with a chemistry set. It’s a complex peptide hormone of about seven hundred atoms, arranged in a series of helices and threads and tentacles. The only way to manufacture it is to genetically engineer some microorganism to make it for you.

The FDA usually requires generic manufacturers to prove that their drug is identical to the brand name drug they’re copying. But genetic engineering is hard, microorganisms are uncooperative, and insulin is too complicated to say with certainty that any one insulin molecule is “identical” to any other. So the FDA has lowered their standards for biologics to require proof that a generic biological is “similar”.

But even proving biosimilarity is orders of magnitude tougher than anything that small molecules have to go through. From the Health Affairs article, slightly transposed for readability:

The typical [small molecule] generic drug takes firms 1-3 years, $1-$5 million, and no human clinical trials to introduce. [In contrast], the entire biosimilar development process has been projected to span 8-10 years and cost upwards of $100 million. Human clinical trials involving hundreds of patients can cost $20-40 million to simply confirm that the candidate biosimilar generally replicates the reference product’s short-term positive and negative clinical effects.

Brand-name insulin companies make a bad situation worse by patenting their manufacturing techniques, using different patents than the drug patent, which may still be in effect when a generics manufacturer is trying to copy their drug. For example, Sanofi has somehow managed to get 74 different patents on their Insulin Lantus, which this I-MAK report describes as a “patent thicket”. Many of these patents seem to be totally illegal, and exist only so that it would cost a generics company time and money to challenge them in court. Most generics companies look at the process of trying to prove their hideously complex molecule is “biosimilar” to Sanofi’s hideously complex molecule, without using any of the 74 different manufacturing processes Sanofi uses to make it, and decide against entering the market.

Then the FDA mandates that biosimilars have a different name than the product they are replacing (ordinary generic drugs may not use the trade name, but can use the same chemical name). This makes it harder to have prescriptions for one cover the other, and doctors may have too much inertia to switch to a new drug with a new name. This limits potential sales for these products.

So the reason companies aren’t making generic insulin is that the FDA approval process for generic insulin is very onerous, brand name companies have excessive and illegal patents that make the approval process even worse, and companies’ ability to sell what comes out the other end is limited.

I realize my political slant makes me blame poor regulatory choices for these sorts of things pretty often. And the Health Affairs article I’m drawing from makes a different argument than I do, arguing that their biological properties make insulins “natural monopolies” and that policy choices are only secondary to this. You should consider my biases before you necessarily take my words at face value.

But the NEJM article mentions that plenty of poorer countries do have biosimilar generic insulins, including such gleaming-high-tech bastions of cutting-edge pharmaceutical excellence as Peru. Which of the following do you think is true?:

1. Peru has better technology than the US, and so is able to make cheap biosimilar insulin using processes that our own scientists and engineers can’t manage.

2. Peru has a bigger market than the US, so there’s more money in creating generic insulin to sell to Peruvians than there is selling it to Americans.

3. Peru has a better regulatory environment than the US, and this is enough to make producing biosimilar insulins cheap and easy.

Extreme fringe libertarians have a certain way with words. For example, they call taxes “the government stealing money from you at gunpoint”. This is a little melodramatic, but words like “patent loopholes” and “onerous review processes” sound a little bloodless for something that probably kills thousands of diabetics each year. So I would like to take a page from the extreme libertarian lexicon and speculate that the problem with insulin costs is that the government will shoot anyone who tries to make cheap insulin.

And then Vox writes an article saying that the problem is “the free market” and we need more government intervention. Fine, whatever. I have despaired of anyone ever analyzing this topic in any greater depth than that. The drug situation is going to keep getting worse – for small molecules, for biosimilars, for whatever. People are going to keep blaming “the free market” and implementing more poorly-thought-out regulation. And so the cycle will keep going, ad infinitum. Vox will keep writing this article once a year or so, and I’ll keep telling them they are bad and wrong, and we’ll both get some clicks out of it. The system works!

I want to clarify that I’m not criticizing the current FDA administration. The FDA has recently done a great job trying to shift their processes marginally in the direction of approving more medications, approving more companies entering the generic market, promoting more competition, and generally doing everything right. Even the GDUFA was a step in the right direction, in that it was necessary in order to get generics approved at all. This is probably part of why drug prices are starting to drop (note that there’s a complicated debate over how true this is and what statistics to use, but I think even the skeptics agree the trend is positive, and they are rising less quickly than they have in the past). There are probably some small steps they could still make to improve things – I get the impression that having the government pay for FDA inspections using tax dollars instead of having the distortionary GDUFA system would help. And patent reform would be great. But a lot of this is concessions to political reality that are probably outside the FDA’s control.

The current trends are good, and further small fixes could be better, but they probably aren’t enough to make drugs affordable and consistently available to patients. If this is even possible, it’s going to require more dramatic changes – not just having good regulators who try to make the best of the current system, but reforming the system entirely. This is a tough order (and I’ll try to blog later about what might be involved). But it’s the only thing that I can imagine allowing us to eventually catch up to Peru.