Vidar Martin Steen

Background: Genetic testing has become an integrated part of health care for patients with breast or ovarian cancer, and the increasing demand for genetic testing is accompanied by an increasing need for easy access to reliable genetic information for patients. Therefore, we developed a chatbot app (Rosa) that is able to perform humanlike digital conversations about genetic BRCA testing. Objective: Before implementing this new information service in daily clinical practice, we wanted to explore 2 aspects of chatbot use: the perceived utility and trust in chatbot technology among healthy patients at risk of hereditary cancer and how interaction with a chatbot regarding sensitive information about hereditary cancer influences patients. Methods: Overall, 175 healthy individuals at risk of hereditary breast and ovarian cancer were invited to test the chatbot, Rosa, before and after genetic counseling. To secure a varied sample, participants were recruited from all cancer genetic clinics in Norway, and the selection was based on age, gender, and risk of having a BRCA pathogenic variant. Among the 34.9% (61/175) of participants who consented for individual interview, a selected subgroup (16/61, 26%) shared their experience through in-depth interviews via video. The semistructured interviews covered the following topics: usability, perceived usefulness, trust in the information received via the chatbot, how Rosa influenced the user, and thoughts about future use of digital tools in health care. The transcripts were analyzed using the stepwise-deductive inductive approach. Results: The overall finding was that the chatbot was very welcomed by the participants. They appreciated the 24/7 availability wherever they were and the possibility to use it to prepare for genetic counseling and to repeat and ask questions about what had been said afterward. As Rosa was created by health care professionals, they also valued the information they received as being medically correct. Rosa was referred to as being better than Google because it provided specific and reliable answers to their questions. The findings were summed up in 3 concepts: “Anytime, anywhere”; “In addition, not instead”; and “Trustworthy and true.” All participants (16/16) denied increased worry after reading about genetic testing and hereditary breast and ovarian cancer in Rosa. Conclusions: Our results indicate that a genetic information chatbot has the potential to contribute to easy access to uniform information for patients at risk of hereditary breast and ovarian cancer, regardless of geographical location. The 24/7 availability of quality-assured information, tailored to the specific situation, had a reassuring effect on our participants. It was consistent across concepts that Rosa was a tool for preparation and repetition; however, none of the participants (0/16) supported that Rosa could replace genetic counseling if hereditary cancer was confirmed. This indicates that a chatbot can be a well-suited digital companion to genetic counseling.

BACKGROUND Genetic testing has become an integrated part of health care for patients with breast or ovarian cancer, and the increasing demand for genetic testing is accompanied by an increasing need for easy access to reliable genetic information for patients. Therefore, we developed a chatbot app (Rosa) that is able to perform humanlike digital conversations about genetic BRCA testing. OBJECTIVE Before implementing this new information service in daily clinical practice, we wanted to explore 2 aspects of chatbot use: the perceived utility and trust in chatbot technology among healthy patients at risk of hereditary cancer and how interaction with a chatbot regarding sensitive information about hereditary cancer influences patients. METHODS Overall, 175 healthy individuals at risk of hereditary breast and ovarian cancer were invited to test the chatbot, Rosa, before and after genetic counseling. To secure a varied sample, participants were recruited from all cancer genetic clinics in Norway, and the selection was based on age, gender, and risk of having a BRCA pathogenic variant. Among the 34.9% (61/175) of participants who consented for individual interview, a selected subgroup (16/61, 26%) shared their experience through in-depth interviews via video. The semistructured interviews covered the following topics: usability, perceived usefulness, trust in the information received via the chatbot, how Rosa influenced the user, and thoughts about future use of digital tools in health care. The transcripts were analyzed using the stepwise-deductive inductive approach. RESULTS The overall finding was that the chatbot was very welcomed by the participants. They appreciated the 24/7 availability wherever they were and the possibility to use it to prepare for genetic counseling and to repeat and ask questions about what had been said afterward. As Rosa was created by health care professionals, they also valued the information they received as being medically correct. Rosa was referred to as being better than Google because it provided specific and reliable answers to their questions. The findings were summed up in 3 concepts: “Anytime, anywhere”; “In addition, not instead”; and “Trustworthy and true.” All participants (16/16) denied increased worry after reading about genetic testing and hereditary breast and ovarian cancer in Rosa. CONCLUSIONS Our results indicate that a genetic information chatbot has the potential to contribute to easy access to uniform information for patients at risk of hereditary breast and ovarian cancer, regardless of geographical location. The 24/7 availability of quality-assured information, tailored to the specific situation, had a reassuring effect on our participants. It was consistent across concepts that Rosa was a tool for preparation and repetition; however, none of the participants (0/16) supported that Rosa could replace genetic counseling if hereditary cancer was confirmed. This indicates that a chatbot can be a well-suited digital companion to genetic counseling.

20.10.2021: Rettelse - Tidsskr Nor Legeforen 2021; 141: 1338–40.

07.10.2021: Kronikk - Høyteknologisk fosterdiagnostikk med non-invasiv prenatal test, ofte omtalt som NIPT, er ikke lenger forbeholdt en selektert høyrisikogruppe eller gravide som på egenhånd oppsøker slike tjenester utenlands.

09.11.2020: Debatt - Det er i dag fullt mulig å avgi eksamensbesvarelser med kliniske vurderinger som åpenbart ville ført til alvorlig helseskade hos pasienten, og likevel bestå.

INTRODUCTION: The cerebral cortex underlies our complex cognitive capabilities. Variations in human cortical surface area and thickness are associated with neurological, psychological, and behavioral traits and can be measured in vivo by magnetic resonance imaging (MRI). Studies in model organisms have identified genes that influence cortical structure, but little is known about common genetic variants that affect human cortical structure. RATIONALE: To identify genetic variants associated with human cortical structure at both global and regional levels, we conducted a genome-wide association meta-analysis of brain MRI data from 51,665 individuals across 60 cohorts. We analyzed the surface area and average thickness of the whole cortex and 34 cortical regions with known functional specializations. RESULTS: We identified 369 nominally genome-wide significant loci ( P < 5 × 10 ⁻⁸ ) associated with cortical structure in a discovery sample of 33,992 participants of European ancestry. Of the 360 loci for which replication data were available, 241 loci influencing surface area and 66 influencing thickness remained significant after replication, with 237 loci passing multiple testing correction ( P < 8.3 × 10 ⁻¹⁰ ; 187 influencing surface area and 50 influencing thickness). Common genetic variants explained 34% (SE = 3%) of the variation in total surface area and 26% (SE = 2%) in average thickness; surface area and thickness showed a negative genetic correlation ( r _G = −0.32, SE = 0.05, P = 6.5 × 10 ⁻¹² ), which suggests that genetic influences have opposing effects on surface area and thickness. Bioinformatic analyses showed that total surface area is influenced by genetic variants that alter gene regulatory activity in neural progenitor cells during fetal development. By contrast, average thickness is influenced by active regulatory elements in adult brain samples, which may reflect processes that occur after mid-fetal development, such as myelination, branching, or pruning. When considered together, these results support the radial unit hypothesis that different developmental mechanisms promote surface area expansion and increases in thickness. To identify specific genetic influences on individual cortical regions, we controlled for global measures (total surface area or average thickness) in the regional analyses. After multiple testing correction, we identified 175 loci that influence regional surface area and 46 that influence regional thickness. Loci that affect regional surface area cluster near genes involved in the Wnt signaling pathway, which is known to influence areal identity. We observed significant positive genetic correlations and evidence of bidirectional causation of total surface area with both general cognitive functioning and educational attainment. We found additional positive genetic correlations between total surface area and Parkinson’s disease but did not find evidence of causation. Negative genetic correlations were evident between total surface area and insomnia, attention deficit hyperactivity disorder, depressive symptoms, major depressive disorder, and neuroticism. CONCLUSION: This large-scale collaborative work enhances our understanding of the genetic architecture of the human cerebral cortex and its regional patterning. The highly polygenic architecture of the cortex suggests that distinct genes are involved in the development of specific cortical areas. Moreover, we find evidence that brain structure is a key phenotype along the causal pathway that leads from genetic variation to differences in general cognitive function. Identifying genetic influences on human cortical structure.: ( A ) Measurement of cortical surface area and thickness from MRI. ( B ) Genomic locations of common genetic variants that influence global and regional cortical structure. ( C ) Our results support the radial unit hypothesis that the expansion of cortical surface area is driven by proliferating neural progenitor cells. ( D ) Cortical surface area shows genetic correlation with psychiatric and cognitive traits. Error bars indicate SE. IMAGE CREDITS: (A) K. COURTNEY; (C) M. R. GLASS

To investigate whether changes in serum lipids are associated with cognitive performance in first episode psychosis (FEP) patients during their first year of antipsychotic drug treatment. One hundred and thirty-two antipsychotic-treated FEP patients were included through the TOP study along with 83 age- and gender-matched healthy controls (HC). Information regarding cognitive performance, psychotic symptoms, lifestyle, body mass index, serum lipids [total cholesterol, high-density lipoprotein (HDL) cholesterol, low-density lipoprotein cholesterol, and triglycerides] and antipsychotic treatment was obtained at baseline and after 1 year. The cognitive test battery is comprised of assessments for verbal learning, processing speed, working memory, verbal fluency, and inhibition. Mixed-effects models were used to study the relationship between changes over time in serum lipids and cognitive domains, controlling for potential confounders. There was a significant group by HDL interaction effect for verbal learning (F = 11.12, p = 0.001), where an increase in HDL levels was associated with improvement in verbal learning in FEP patients but not in HC. Practice effects, lifestyle, and psychotic symptoms did not significantly affect this relationship. Antipsychotic-treated FEP patients who increased in HDL levels during the first year of follow-up exhibited better verbal learning capacity. Further investigations are needed to clarify the underlying mechanisms.

Antipsychotic drugs can negatively affect the metabolic status of patients, with olanzapine as one of the most potent drugs. While patients are often medicated for long time periods, experiments in rats typically run for 1 to 12 weeks, showing olanzapine-related weight gain and increased plasma lipid levels, with transcriptional upregulation of lipogenic genes in liver and adipose tissue. It remains unknown whether metabolic status will deteriorate with time. To examine long-term metabolic effects, we administered intramuscular long-acting injections of olanzapine (100 mg/kg BW) or control substance to female rats for up to 13 months. Exposure to olanzapine long-acting injections led to rapid weight gain, which was sustained throughout the experiment. At 1, 6, and 13 months, plasma lipid levels were measured in separate cohorts of rats, displaying no increase. Hepatic transcription of lipid-related genes was transiently upregulated at 1 month. Glucose and insulin tolerance tests indicated insulin resistance in olanzapine-treated rats after 12 months. Our data show that the continuous increase in body weight in response to long-term olanzapine exposure was accompanied by surprisingly few concomitant changes in plasma lipids and lipogenic gene expression, suggesting that adaptive mechanisms are involved to reduce long-term metabolic adverse effects of this antipsychotic agent in rats.

Background: Recent studies have implicated variations in DNA methylation in the aetiology of schizophrenia. Genome-wide scans in both brain and blood report differential methylated regions (DMRs) and positions (DMPs) between patients with schizophrenia and healthy controls. Previously, we reported that DMRs where human specific methylation (hDMR) has occurred over evolutionary time are enriched for schizophrenia-associated markers (SCZ_hDMR). However, it is unknown whether these human specific DMRs show variable methylation in patients with schizophrenia.Methods: Using publicly available data, we investigate if human specific DMRs that harbour genetic variants associated with schizophrenia are differentially methylated between cases and controls.Results: We find statistically significant (p < 1e-4) methylation difference in schizophrenia associated human specific DMRs (SCZ hDMR) between brain samples of cases and controls. However, we fail to find evidence of similar differences in methylation in blood samples.Conclusion: Regions that are evolutionarily important for human species and that are associated with schizophrenia, also show difference in methylation variation in the brain in patients with schizophrenia.