Aaron Besterman (@besterman_a) profile picture

Child psychiatry. Psychiatric genetics. Rare neurodevelopmental disease research. Tweets my own. He/His.🇺🇸🇨🇦🇨🇴

San Diego, CA
Joined July 2017
Photo by Aaron Besterman (@besterman_a)Photo by Aaron Besterman (@besterman_a)Photo by Aaron Besterman (@besterman_a)Photo by Aaron Besterman (@besterman_a)Photo by Aaron Besterman (@besterman_a)Photo by Aaron Besterman (@besterman_a)Photo by Aaron Besterman (@besterman_a)Photo by Aaron Besterman (@besterman_a)Photo by Aaron Besterman (@besterman_a)Photo by Aaron Besterman (@besterman_a)
Aaron Besterman retweeted
📄 New preprint from ENCAP, the European Network for Clinical Application in Psychiatric Genomics: Recalculated CNV penetrance: what it does and does not change for counselling 🔗 doi.org/10.64898/2026.10.06.… 🧵 1/6
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A subset of people diagnosed with severe psychiatric illnesses may actually have immune-mediated brain diseases. Properly diagnosing and effectively treating these patients is an important area of discovery in the mental health space. I had a deeply interesting and informative time visiting researchers at the National Institute of Mental Health yesterday, who are working on cutting-edge approaches to that issue and many more.
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Aaron Besterman retweeted
An exciting new exome-wide association study (ExWAS) of schizophrenia from the SCHEMA consortium, based on ~88k cases and ~150k controls. The previous analysis, published in 2022, had ~24k cases and ~97k controls and found 10 genes at exome-wide significance. The current analysis maps 16 genes, 8 of them new: SCAF1, FYN, PPP3CA, HDAC9, JARID2, ATP9A, PTK2 and SCN2A. Another 24 pass the FDR 5% threshold (40 in total). A few interesting findings to highlight: 1. Some genes, like GRIN2A, GRIA3 and CACNA1G, dropped below FDR 5% in the new analysis. These are also developmental delay (DD) / intellectual disability (ID) genes, and the older cohorts carry more damaging variants in DD/ID genes than the new ones. That suggests a shift in ascertainment: the new samples have milder cases, or fewer cases with comorbid DD/ID. 2. Aggregating missense variants with a newer composite predictor increased power, raising the number of exome-wide genes from 13 to 16. 3. Looking at variant classes separately matters. A good example is SCN2A, where the schizophrenia signal is driven mainly by missense variants and the DD/ID signal mainly by loss-of-function variants. 4. Common and rare variants mostly don't converge on the same genes. Only 6 of the 40 sit near a GWAS locus, no more than chance. That is a feature rather than a bug for a disease like schizophrenia, which is under strong natural selection: selection keeps large-effect variants rare, so burden tests and GWAS end up ranking different genes. 5. A rare-variant schizophrenia gene now points to an FDA-approved schizophrenia medicine. Xanomeline (a component of Cobenfy) is an M1/M4 muscarinic receptor agonist, approved for schizophrenia in 2024. Rare damaging variants in CHRM4, the gene encoding M4, increase schizophrenia risk (30 cases vs 5 controls, OR ~8; FDR 5%, just short of exome-wide significance). That aligns with the therapeutic hypothesis of activating M4 to treat schizophrenia. Sealock et al. bioRxiv 2026
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Aaron Besterman retweeted
Excited to share our latest preprint, led by RachelSmith & @YundanLiao: "Autism genes converge on three functional programs organized by neuronal subclass, developmental timing, and cortical patterning" #ASD #genomics #singlecell #GeneRegulatoryNetwork biorxiv.org/content/10.64898…
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Aaron Besterman retweeted
If it's isn't obvious already, it is the end of papers as a measure of productivity, expertise or accomplishment. The odds of publishing in "glam" conferences & journals also very quickly approaches random & the time for gate keeping review increasing exponentially. 1/
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Aaron Besterman retweeted
Major release! =--=--=--=--= I have compiled the worlds largest database of pediatric suicide information, consisting of 137 countries, from 1952-2025. In total, 27.64 BILLION person-years of data are represented. /1
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Aaron Besterman retweeted
Congratulations to 2026 #LaskerAward winners Emmanuel Mignot of @StanfordMed and Masashi Yanagisawa of the @UNIV_TSUKUBA_EN! For identification of orexin, a brain peptide that maintains wakefulness, and the discovery that orexin deficiency causes uncontrolled sleep in #narcolepsy — revealing a key insight into the nature of sleep. #Lasker2026 #LaskerLaureate
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Aaron Besterman retweeted
Our genetic association study of the Big Five personality traits (extraversion, agreeableness, conscientiousness, neuroticism and openness to experience) came out in @Nature today, check it out here (open access): nature.com/articles/s41586-0…
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Aaron Besterman retweeted
My testimony today at the Texas State capital I’m the co-founder of CostPlusDrugs.com. We started Cost Plus Drugs because the prescription drug market is too complicated, too opaque and too expensive. Our model is simple: we show what we pay for a drug, add a transparent markup and pharmacy fee, and show the customer the price. No games. No hidden spread. And a large percentage of our customers already have insurance. They come to us because our cash price is often lower than what their insurance plan asks them to pay. That tells you something is wrong. Here are five things Texas can do about it. 1. Let patients shop for cheaper drugs If someone's insurance says a prescription costs $500, but they can buy the exact same drug for $100 cash, let them buy it for $100. Then credit that $100 toward their deductible and out-of-pocket maximum wherever Texas has authority to do so. Patients should be rewarded for saving themselves and their health plan money. They shouldn't be punished for it. That's how you create something healthcare desperately needs: Price competition. 2. Standardize PBM and TPA contracts Texas should require the state, cities, counties and school districts to use standardized model contracts and mandatory terms for PBMs and TPAs. I've reviewed these contracts. They routinely run hundreds of pages. I've seen contracting packages longer than a thousand pages. There is no human being—or group of human beings—on this planet who can stay awake and understand every provision in contracts that complicated. I don't care how much coffee they drink. I call it contractual terrorism. The vendor only has to sneak a couple of tricks through hundreds of pages. The employer has to find every one. It can't. I've developed a model PBM contract designed to eliminate the major tricks and hidden economics we've identified. Texas can have it for free. Use mine. Improve it. Open source it. I don't care. Just stop making every government entity negotiate these contracts from scratch. 3. Make the economics public If taxpayers are paying the bill, taxpayers should know the price. Pricing. Fees. Rebates. Guarantees. Pharmacy reimbursement. Affiliate compensation. Audit rights. Make them public. I'm not talking about patient information or legitimate security information. I'm talking about the money. You cannot have an efficient market without price discovery. Without price discovery, you get information asymmetry. And when one side knows dramatically more than the other, guess who wins? Not taxpayers. Not employers. Not patients. Open the contracts up and let competitors see what they have to beat. That giant sucking sound you hear will be money moving away from healthcare conglomerates that are too big to care and back toward taxpayers, employers and patients. In the immortal words of Charles Barkley: I guarantee it. 4. Kill the gag clauses PBM contracts are like Fight Club. The number one rule of Fight Club is that you can't talk about Fight Club. The number one rule of many PBM contracts seems to be that you can't talk about your PBM contract. That's insane. Let employers compare pricing, rebates, fees, guarantees and reimbursement terms. Markets work better when buyers know what other buyers are paying. 5. Make enforcement hurt If a healthcare company commits a serious violation, give them one mulligan. But after a second material federal or Texas enforcement action within a defined period, make them ineligible for new Texas government contracts for a period of time. Two strikes. You're out. Today, some of these companies can make billions, get caught, pay a fine and write it off more easily than I wrote off an NBA fine. That's not deterrence. That's a cost of doing business. And Texas should spend more on enforcement. If Texas spends $10 million auditing contracts and analyzing claims and prevents $100 million in unnecessary spending, that's not overhead. That's a 10x return on investmen
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Aaron Besterman retweeted
You've heard of the Bush-Francis Catatonia Rating Scale. You may not have heard that there is now a Catatonia Quick Screen, which uses only 4 questions. It is actually performing really well, including - this paper(!) - with the original Bush-Francis data. doi.org/10.1111/acps.70135
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Aaron Besterman retweeted
Incredibly excited to share the first major paper from my lab @carnevale_lab led by postdoc Qi Liu @GladstoneInst @UCSF executing the first ever genome-wide in vivo screens for genetic modifications to enhance human T cell therapies for solid tumors. Now in @Nature: nature.com/articles/s41586-0…
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Aaron Besterman retweeted
Excited to share our latest work from the Gandal Lab: "Beyond the gene: isoform diversity as a key contributor to human brain disorders" sciencedirect.com/science/ar… Congrats to @Gene_Yunlong_Ma @connorjops
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Aaron Besterman retweeted
1/5 Cell identity is written in the proteome, not in the DNA, and not always in the RNA. Out on bioRxiv today: The first cell type-resolved, MS-based proteomic atlas of the human body. biorxiv.org/content/10.64898…
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Aaron Besterman retweeted
How does TMS — a treatment for depression — reshape dysfunctional brain circuits? In our new Cell paper, we identify a cell type-specific prefrontal mechanism linking accelerated iTBS to antidepressant-like behavioral effects and circuit plasticity. cell.com/cell/fulltext/S0092…
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Aaron Besterman retweeted
Embryo selection using polygenic risk scoring has been a hot topic recently, with startups investing millions into the idea. Previous studies on embryo screening have reported relative risk reductions of up to 50%. The high risk reduction estimates are, however, based on the assumption that each IVF cycle produces 2 to 5 viable embryos, all having a similar chance of a successful live birth. Sadly, that’s not the reality. In a new preprint, the authors analyzed data from 6,944 real IVF cycles from 4,452 infertility patients. The reality of the IVF pipeline: on average, each cycle produced just 0.88 euploid embryos and 0.17 live births. You cannot select the lowest-risk embryo when most cycles don’t give you a choice. Next, the authors simulated how disease risk reduction fares in this realistic scenario. The relative risk reduction ranged from under 0.5% across all cycles to just 1–3% in cycles that resulted in a live birth, far below the previously predicted 50%. It’s worth noting there is one setting where risk reduction reached a reasonable level of ~20%: egg donor cycles, where viable embryos tend to be many due to young donors. Even here, the estimate is a fraction of prior predictions. The findings raise an important question: who is polygenic embryo screening actually for? It’s designed for patients with multiple viable embryos, all birth-ready, in a single cycle. Those patients don’t exist in most clinics. The reality is that this technology is being built for healthy, fertile individuals with plenty of financial resources, doing IVF electively to have designer babies. Klausner et al. medRxiv 2026 medrxiv.org/content/10.64898…
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Very excited to share our pediatric catatonia clinical pathway in acute medical care settings consensus study is out in the Journal of the Academy of Consultation-Liaison Psychiatry. There’s a link good til the end of May for the pdf here: authors.elsevier.com/a/1mvN4… 1/
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Aaron Besterman retweeted
Happy to see our work on repeat expansions led by my colleagues--Sahar Gelfman & Vijay Kumar--at RGC published in @Nature. Below is a thread highlighting what we learned from systematically studying repeat mutations at population-scale in ~1 million individuals
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