Research Spotlights: July 2021

Response to chronic stress passed down from fathers’ sperm in mice

Stress in future fathers has been shown to induce long-lasting changes in sperm cells that can change genetic factors and behavior in later generations. However, it is unknown whether transmission patterns differed depending on fathers’ responses to chronic stress. In a study in mice funded by the NIMH, researchers tested whether fathers’ resiliency or susceptibility to chronic stress impacted behavioral responses in offspring. The study identified that male mice that have a heightened stress response produce offspring that are similarly vulnerable to stressful situations due to epigenetic alterations in their sperm.

To investigate how fathers’ susceptibility to stress results in behavioral changes in their offspring, researchers exposed adult male mice to chronic stress by placing them in contact with an aggressive mouse and then tested whether this impacted their future exploratory behavior in the presence of the aggressor. Mice were deemed susceptible or resilient to stress based on their subsequent exploratory behavior. Next, sperm was used to artificially inseminate females, and the offspring were tested for their stress responsivity using tasks such as exploratory behavior in an open, naturally fear-inducing space. Indeed, mice born from fathers that were vulnerable to stress had the same heighted stress response.

Additionally, researchers examined the RNA transcripts of mouse sperm before and after applying stress and found that 1,400 genes were altered in vulnerable mice, while only 62 genes were altered in resilient mice. This study developed a further understanding of intergenerational epigenetic transmission of behavioral experience. This research indicates that other factors may contribute to mental health disorders and may help lead to identifying molecular targets for drugs to improve treatment.

Cunningham AM, et al. 2021. Sperm transcriptional state associated with paternal transmission of stress phenotypes, Journal of Neuroscience. JN-RM-3192-20; DOI:

Barriers to opioid treatment for reproductive-age women decrease access to life-saving medications

How easy is it to get treatment for opioid addiction/opioid use disorder (OUD) if you are female and pregnant? To add to the question, how difficult is it to get treatment if you are pregnant and on public insurance? A study funded by the NIDA sought to answer these questions.

Trained female callers placed telephone calls to a sample of publicly listed opioid treatment clinics and buprenorphine providers in Florida, Kentucky, Massachusetts, Michigan, Missouri, North Carolina, Tennessee, Virginia, Washington, and West Virginia to obtain appointments to receive medication for OUD. Callers were randomly assigned to be pregnant or non-pregnant and have private or Medicaid-based insurance. The callers placed 28,651 uniquely randomized calls—10,117 to buprenorphine-waivered prescribers and 754 to opioid treatment programs. Open-ended, qualitative data were obtained about their ability to access treatment and were analyzed using a qualitative, iterative inductive-deductive approach on 17,970 unique free-text comments.

The results revealed challenges in scheduling a first-time appointment to receive treatment for OUD, including finding a provider who takes insurance, long on-hold times, and difficult interactions with clinic receptionists. Many callers felt stigmatized during the calls and felt extreme emotions due to responses from those answer the phone, despite that they were actors. Access to treatment was even more difficult for women who are pregnant and have OUD, with pregnant women about 20 percent less likely to be accepted for treatment than nonpregnant women. Those on Medicaid also documented more barriers to obtaining an appointment than those with private insurance.

As the U.S. opioid crisis continues to grow, women are increasingly affected with the rate of drug-related deaths among women jumping from 3.9 to 13.4 per thousand from 1999 to 2016. Medications for opioid use disorder reduce overdose death, improve quality of life, and improve pregnancy outcomes. Still, barriers to OUD treatment remain for reproductive-age women.

Phillippi JC, Schulte R, Bonnet K, Schlundt DD, Cooper WO, Martin PR, Kozhimannil KB, Patrick SW, 2021. Reproductive-Age Women's Experience of Accessing Treatment for Opioid Use Disorder: “We Don't Do That Here”, Women's Health Issues, ISSN 1049-3867,

Computational modeling—a potential tool to guide individually tailored language rehabilitation plans for bilingual stroke patients with aphasia

In recently published results from a study supported by the NIDCD, scientists demonstrate the utility of using computer simulations to predict language recovery in bilingual patients with aphasia. Following stroke or other similar brain injuries, aphasia is the most common speech and language disorder that affects bilingual adults. Bilingual individuals with aphasia often have varying degrees and patterns of impairment and recovery in their two languages.

Previous research indicates that treatment in either language can induce recovery with most individuals showing therapy effects in the treated language, while other research shows varying degrees of improvement in the untreated language. One question that remains unanswered is how to identify the language for treatment that results in the greatest therapy gains across both languages for bilingual patients with aphasia. Using computational modeling, the researchers aimed to predict the optimal language for treatment by simulating therapy outcomes in both languages, while accounting for both individual history of bilingualism and impairment in each language.

In this study, the researchers built upon their prior research which developed BiLex31, a neural network model to simulate pre-stroke naming ability in Spanish-English patients with aphasia. Using this model, researchers simulated the brain of a bilingual person that is language impaired and measured their brain’s response to therapy in English and Spanish in order to identify the optimal language to target during treatment and predict outcomes following therapy including how well a person will recover their language skills. They found that BiLex31 accurately predicted treatment effects in the treated language and importantly, captured different degrees of cross-language generalization in the language that the treatment was not given. Additionally, they found that this model could predict language recovery in an independent population of bilingual patients (those not used to train BiLex31). These findings indicate that these computational tools may be useful for guiding healthcare providers in choosing the optimal rehabilitation plan for bilingual aphasia patients. Clinical trials using this technology are currently underway, which will further elucidate how these computational neural models could potentially be implemented in hospital and clinical settings.

Grasemann U., Peñaloza, C., Dekhtyar, M. et al. 2021. Predicting language treatment response in bilingual aphasia using neural network-based patient models. Sci Rep 11, 10497.