Multi-omic molecular profiling and network biology for precision anaesthesiology: a narrative review.

Technological advancement, data democratisation, and decreasing costs have led to a revolution in molecular biology in which the entire set of DNA, RNA, proteins, and various other molecules - the 'multi-omic' profile - can be measured in humans. Sequencing 1 million bases of human DNA now costs US$0.01, and emerging technologies soon promise to reduce the cost of sequencing the whole genome to US$100. These trends have made it feasible to sample the multi-omic profile of millions of people, much of which is publicly available for medical research. Can anaesthesiologists use these data to improve patient care? This narrative review brings together a rapidly growing literature in multi-omic profiling across numerous fields that points to the future of precision anaesthesiology. Here, we discuss how DNA, RNA, proteins, and other molecules interact in molecular networks that can be used for preoperative risk stratification, intraoperative optimisation, and postoperative monitoring. This literature provides evidence for four fundamental insights: (1) Clinically similar patients have different molecular profiles and, as a consequence, different outcomes. (2) Vast, publicly available, and rapidly growing molecular datasets have been generated in chronic disease patients and can be repurposed to estimate perioperative risk. (3) Multi-omic networks are altered in the perioperative period and influence postoperative outcomes. (4) Multi-omic networks can serve as empirical, molecular measurements of a successful postoperative course. With this burgeoning universe of molecular data, the anaesthesiologist-of-the-future will tailor their clinical management to an individual's multi-omic profile to optimise postoperative outcomes and long-term health.

Improving liver transplant outcomes with transplant-omics and network biology.

PURPOSE OF REVIEW: Molecular omics data is increasingly ubiquitous throughout medicine. In organ transplantation, recent large-scale research efforts are generating the 'transplant-ome' - the entire set of molecular omics data, including the genome, transcriptome, proteome, and metabolome. Importantly, early studies in anesthesiology have demonstrated how perioperative interventions alter molecular profiles in various patient populations. The next step for anesthesiologists and intensivists will be to tailor perioperative care to the transplant-ome of individual liver transplant patients. RECENT FINDINGS: In liver transplant patients, elements of the transplant-ome predict complications and point to novel interventions. Importantly, molecular profiles of both the donor organ and recipient contribute to this risk, and interventions like normothermic machine perfusion influence these profiles. As we can now measure various omics molecules simultaneously, we can begin to understand how these molecules interact to form molecular networks and emerging technologies offer noninvasive and continuous ways to measure these networks throughout the perioperative period. Molecules that regulate these networks are likely mediators of complications and actionable clinical targets throughout the perioperative period. SUMMARY: The transplant-ome can be used to tailor perioperative care to the individual liver transplant patient. Monitoring molecular networks continuously and noninvasively would provide new opportunities to optimize perioperative management.

Intraoperative opioids are associated with decreased recurrence rates in colon adenocarcinoma: a retrospective observational cohort study.

BACKGROUND: Opioid-induced immunomodulation may be important in colon adenocarcinoma, where tumour DNA mismatch repair (MMR) can determine the level of immune activation with consequences for therapeutic response and prognosis. We evaluated the relationship between intraoperative opioid exposure, MMR subtype, and oncological outcomes after surgery for colon adenocarcinoma. METHODS: Intraoperative opioid use (standardised by calculating morphine milligram equivalents) during stage I-III colon adenocarcinoma resection was reviewed retrospectively. Tumours were classified as DNA mismatch repair deficient (dMMR) or proficient (pMMR) by immunohistochemistry. The primary outcome was local tumour recurrence, distant tumour recurrence, or both (multivariable analysis). The exposures of interest were intraoperative analgesia and tumour subtype. Opioid-related gene expression was analysed using The Cancer Genome Atlas Colon Adenocarcinoma transcriptomic data. RESULTS: Clinical and pathological data were analysed from 1157 subjects (median age, 60 [51-70] yr; 49% female) who underwent curative resection for stage I-III colon adenocarcinoma. Higher intraoperative opioid doses were associated with reduced risk of tumour recurrence (hazard ratio=0.92 per 10 morphine milligram equivalents; 95% confidence interval [95% CI], 0.87-0.98; P=0.007), but not with overall survival. In tumours deficient in DNA MMR, tumour recurrence was less likely (HR=0.38; 95% CI, 0.21-0.68; P=0.001), with higher opioid dose associated with eightfold lower recurrence rates. Gene expression related to opioid signalling was different between dMMR and pMMR tumours. CONCLUSIONS: Higher intraoperative opioid dose was associated with a lower risk of tumour recurrence after surgery for stage I-III colon adenocarcinoma, but particularly so in tumours in which DNA MMR was deficient.

Intraoperative opioids are associated with improved recurrence-free survival in triple-negative breast cancer.

BACKGROUND: Opioid-induced immunomodulation may be of particular importance in triple-negative breast cancer (TNBC) where an immune response is associated with improved outcome and response to immunotherapy. We evaluated the association between intraoperative opioids and oncological outcomes and explored patterns of opioid receptor expression in TNBC. METHODS: Consecutive patients with stage I-III primary TNBC were identified from a prospectively maintained database. Opioid receptor expression patterns in the tumour microenvironment were analysed using publicly available bulk and single-cell RNA-seq data. RESULTS: A total of 1143 TNBC cases were retrospectively analysed. In multivariable analysis, higher intraoperative opioid dose was associated with favourable recurrence-free survival, hazard ratio 0.93 (95% confidence interval 0.88-0.99) per 10 oral morphine milligram equivalents increase (P=0.028), but was not significantly associated with overall survival, hazard ratio 0.96 (95% confidence interval 0.89-1.02) per 10 morphine milligram equivalents increase (P=0.2). Bulk RNA-seq analysis of opioid receptors showed that OPRM1 was nearly non-expressed. Compared with normal breast tissue OGFR, OPRK1, and OPRD1 were upregulated, while TLR4 was downregulated. At a single-cell level, OPRM1 and OPRD1 were not detectable; OPRK1 was expressed mainly on tumour cells, whereas OGFR and TLR4 were more highly expressed on immune cells. CONCLUSIONS: We found a protective effect of intraoperative opioids on recurrence-free survival in TNBC. Opioid receptor expression was consistent with a net protective effect of opioid agonism, with protumour receptors either not expressed or downregulated, and antitumour receptors upregulated. In this era of personalised medicine, efforts to differentiate the effects of opioids across breast cancer subtypes (and ultimately individual patients) should continue.

Intraoperative opioid exposure, tumour genomic alterations, and survival differences in people with lung adenocarcinoma.

BACKGROUND: Opioids have been linked to worse oncologic outcomes in surgical patients. Studies in certain cancer types have identified associations between survival and intra-tumoural opioid receptor gene alterations, but no study has investigated whether the tumour genome interacts with opioid exposure to affect survival. We sought to determine whether intraoperative opioid exposure is associated with recurrence-specific survival and overall survival in early-stage lung adenocarcinoma, and whether selected tumour genomics are associated with this relationship. Associations between ketamine and dexmedetomidine and outcomes were also studied. METHODS: Surgical patients (N=740) with pathological stage I-III lung adenocarcinoma and next-generation sequencing data were retrospectively reviewed from a prospectively maintained database. RESULTS: On multivariable analysis, ketamine administration was protective for recurrence-specific survival (hazard ratio = 0.44, 95% confidence interval 0.24-0.80; P=0.007), compared with no adjunct. Higher intraoperative oral morphine milligram equivalents were significantly associated with worse overall survival (hazard ratio=1.09/10 morphine milligram equivalents, 95% confidence interval 1.02-1.17; P=0.010). Significant interaction effects were found between morphine milligram equivalents and fraction genome altered and morphine milligram equivalents and CDKN2A, such that higher fraction genome altered or CDKN2A alterations were associated with worse overall survival at higher morphine milligram equivalents (P=0.044 and P=0.052, respectively). In contrast, alterations in the Wnt (P=0.029) and Hippo (P=0.040) oncogenic pathways were associated with improved recurrence-specific survival at higher morphine milligram equivalents, compared with unaltered pathways. CONCLUSIONS: Intraoperative opioid exposure is associated with worse overall survival, whereas ketamine exposure is associated with improved recurrence-specific survival in patients with early-stage lung adenocarcinoma. This is the first study to investigate tumour-specific genomic interactions with intraoperative opioid administration to modify survival associations.

Huntington's disease in the United States: Variation by demographic and socioeconomic factors.

BACKGROUND: Despite extensive research regarding the etiology of Huntington's disease, relatively little is known about the epidemiology of this rare disorder, particularly in the United States where there are no national-scale estimates of the disease. OBJECTIVES: To provide national-scale estimates of Huntington's disease in a U.S. population and to test whether disease rates are increasing, and whether frequency varies by race, ethnicity, or other factors. METHODS: Using an insurance database of over 67 million enrollees, we retrospectively identified a cohort of 3,707 individuals diagnosed with Huntington's disease between 2003 and 2016. We estimated annual incidence, annual diagnostic frequency, and tested for trends over time and differences in diagnostic frequency by sociodemographic characteristics. RESULTS: During the observation period, the age-adjusted cumulative incidence rate was1.22 per 100,000 persons (95% confidence interval: 1.53, 1.65), and age-adjusted diagnostic frequency was 6.52 per 100,000 persons (95% confidence interval: 5.31, 5.66); both rates remained relatively stable over the 14-year period. We identified several previously unreported differences in Huntington's disease frequency by self-reported sex, income, and race/ethnicity. However, racial/ethnic differences were of lower magnitude than have previously been reported in other country-level studies. CONCLUSIONS: In these large-scale estimates of U.S. Huntington's disease epidemiology, we found stable disease frequency rates that varied by several sociodemographic factors. These findings suggest that disease patterns may be more driven by social or environmental factors than has previously been appreciated. Results further demonstrate the potential utility of administrative Big Data in rare disease epidemiology when other data sources are unavailable. © 2019 International Parkinson and Movement Disorder Society.

Systems Genetic Analyses Highlight a TGFß-FOXO3 Dependent Striatal Astrocyte Network Conserved across Species and Associated with Stress, Sleep, and Huntington's Disease.

Recent systems-based analyses have demonstrated that sleep and stress traits emerge from shared genetic and transcriptional networks, and clinical work has elucidated the emergence of sleep dysfunction and stress susceptibility as early symptoms of Huntington's disease. Understanding the biological bases of these early non-motor symptoms may reveal therapeutic targets that prevent disease onset or slow disease progression, but the molecular mechanisms underlying this complex clinical presentation remain largely unknown. In the present work, we specifically examine the relationship between these psychiatric traits and Huntington's disease (HD) by identifying striatal transcriptional networks shared by HD, stress, and sleep phenotypes. First, we utilize a systems-based approach to examine a large publicly available human transcriptomic dataset for HD (GSE3790 from GEO) in a novel way. We use weighted gene coexpression network analysis and differential connectivity analyses to identify transcriptional networks dysregulated in HD, and we use an unbiased ranking scheme that leverages both gene- and network-level information to identify a novel astrocyte-specific network as most relevant to HD caudate. We validate this result in an independent HD cohort. Next, we computationally predict FOXO3 as a regulator of this network, and use multiple publicly available in vitro and in vivo experimental datasets to validate that this astrocyte HD network is downstream of a signaling pathway important in adult neurogenesis (TGFß-FOXO3). We also map this HD-relevant caudate subnetwork to striatal transcriptional networks in a large (n = 100) chronically stressed (B6xA/J)F2 mouse population that has been extensively phenotyped (328 stress- and sleep-related measurements), and we show that this striatal astrocyte network is correlated to sleep and stress traits, many of which are known to be altered in HD cohorts. We identify causal regulators of this network through Bayesian network analysis, and we highlight their relevance to motor, mood, and sleep traits through multiple in silico approaches, including an examination of their protein binding partners. Finally, we show that these causal regulators may be therapeutically viable for HD because their downstream network was partially modulated by deep brain stimulation of the subthalamic nucleus, a medical intervention thought to confer some therapeutic benefit to HD patients. In conclusion, we show that an astrocyte transcriptional network is primarily associated to HD in the caudate and provide evidence for its relationship to molecular mechanisms of neural stem cell homeostasis. Furthermore, we present a unified systems-based framework for identifying gene networks that are associated with complex non-motor traits that manifest in the earliest phases of HD. By analyzing and integrating multiple independent datasets, we identify a point of molecular convergence between sleep, stress, and HD that reflects their phenotypic comorbidity and reveals a molecular pathway involved in HD progression.

Pharmacological risk factors associated with hospital readmission rates in a psychiatric cohort identified using prescriptome data mining.

BACKGROUND: Worldwide, over 14% of individuals hospitalized for psychiatric reasons have readmissions to hospitals within 30 days after discharge. Predicting patients at risk and leveraging accelerated interventions can reduce the rates of early readmission, a negative clinical outcome (i.e., a treatment failure) that affects the quality of life of patient. To implement individualized interventions, it is necessary to predict those individuals at highest risk for 30-day readmission. In this study, our aim was to conduct a data-driven investigation to find the pharmacological factors influencing 30-day all-cause, intra- and interdepartmental readmissions after an index psychiatric admission, using the compendium of prescription data (prescriptome) from electronic medical records (EMR). METHODS: The data scientists in the project received a deidentified database from the Mount Sinai Data Warehouse, which was used to perform all analyses. Data was stored in a secured MySQL database, normalized and indexed using a unique hexadecimal identifier associated with the data for psychiatric illness visits. We used Bayesian logistic regression models to evaluate the association of prescription data with 30-day readmission risk. We constructed individual models and compiled results after adjusting for covariates, including drug exposure, age, and gender. We also performed digital comorbidity survey using EMR data combined with the estimation of shared genetic architecture using genomic annotations to disease phenotypes. RESULTS: Using an automated, data-driven approach, we identified prescription medications, side effects (primary side effects), and drug-drug interaction-induced side effects (secondary side effects) associated with readmission risk in a cohort of 1275 patients using prescriptome analytics. In our study, we identified 28 drugs associated with risk for readmission among psychiatric patients. Based on prescription data, Pravastatin had the highest risk of readmission (OR = 13.10; 95% CI (2.82, 60.8)). We also identified enrichment of primary side effects (n = 4006) and secondary side effects (n = 36) induced by prescription drugs in the subset of readmitted patients (n = 89) compared to the non-readmitted subgroup (n = 1186). Digital comorbidity analyses and shared genetic analyses further reveals that cardiovascular disease and psychiatric conditions are comorbid and share functional gene modules (cardiomyopathy and anxiety disorder: shared genes (n = 37; P = 1.06815E-06)). CONCLUSIONS: Large scale prescriptome data is now available from EMRs and accessible for analytics that could improve healthcare outcomes. Such analyses could also drive hypothesis and data-driven research. In this study, we explored the utility of prescriptome data to identify factors driving readmission in a psychiatric cohort. Converging digital health data from EMRs and systems biology investigations reveal a subset of patient populations that have significant comorbidities with cardiovascular diseases are more likely to be readmitted. Further, the genetic architecture of psychiatric illness also suggests overlap with cardiovascular diseases. In summary, assessment of medications, side effects, and drug-drug interactions in a clinical setting as well as genomic information using a data mining approach could help to find factors that could help to lower readmission rates in patients with mental illness.

Silencing the α2 subunit of γ-aminobutyric acid type A receptors in rat dorsal root ganglia reveals its major role in antinociception posttraumatic nerve injury.

BACKGROUND: Neuropathic pain (NPP) is likely the result of repetitive high-frequency bursts of peripheral afferent activity leading to long-lasting changes in synaptic plasticity in the spinal dorsal horn. Drugs that promote γ-aminobutyric acid (GABA) activity in the dorsal horn provide partial relief of neuropathic symptoms. The authors examined how in vivo silencing of the GABA receptor type A (GABAA) α2 gene in dorsal root ganglia (DRG) controls NPP. METHODS: After crush injury to the right sciatic nerve of female rats, the α2 GABAA antisense and mismatch oligodeoxynucleotides or NO-711 (a GABA uptake inhibitor) were applied to the L5 DRG. In vivo behavioral assessment of nociception was conducted before the injury and ensuing 10 days (n = 4 to 10). In vitro quantification of α2 GABAA protein and electrophysiological studies of GABAA currents were performed on acutely dissociated L5 DRG neurons at relevant time points (n = 6 to 14). RESULTS: NPP postcrush injury of a sciatic nerve in adult female rats coincides with significant down-regulation of the α2 subunit expression in the ipsilateral DRG (approximately 30%). Selective down-regulation of α2 expression in DRGs significantly worsens mechanical (2.55 ± 0.75 to 5.16 ± 1.16) and thermal (7.97 ± 0.96 to 5.51 ± 0.75) hypersensitivity in crush-injured animals and causes development of significant mechanical (2.33 ± 0.40 to 5.00 ± 0.33) and thermal (10.80 ± 0.29 to 7.34 ± 0.81) hypersensitivity in sham animals (data shown as mean ± SD). Conversely, up-regulation of endogenous GABA via blockade of its uptake in DRG alleviates NPP. CONCLUSION: The GABAA receptor in the DRG plays an important role in pathophysiology of NPP caused by sciatic nerve injury and represents promising target for novel pain therapies.

N-cadherin regulates molecular organization of excitatory and inhibitory synaptic circuits in adult hippocampus in vivo.

N-Cadherin and ß-catenin form a transsynaptic adhesion complex required for spine and synapse development. In adulthood, N-cadherin mediates persistent synaptic plasticity, but whether the role of N-cadherin at mature synapses is similar to that at developing synapses is unclear. To address this, we conditionally ablated N-cadherin from excitatory forebrain synapses in mice starting in late postnatal life and examined hippocampal structure and function in adulthood. In the absence of N-cadherin, ß-catenin levels were reduced, but numbers of excitatory synapses were unchanged, and there was no impact on number or shape of dendrites or spines. However, the composition of synaptic molecules was altered. Levels of GluA1 and its scaffolding protein PSD95 were diminished and the density of immunolabeled puncta was decreased, without effects on other glutamate receptors and their scaffolding proteins. Additionally, loss of N-cadherin at excitatory synapses triggered increases in the density of markers for inhibitory synapses and decreased severity of hippocampal seizures. Finally, adult mutant mice were profoundly impaired in hippocampal-dependent memory for spatial episodes. These results demonstrate a novel function for the N-cadherin/ß-catenin complex in regulating ionotropic receptor composition of excitatory synapses, an appropriate balance of excitatory and inhibitory synaptic proteins and the maintenance of neural circuitry necessary to generate flexible yet persistent cognitive and synaptic function.

Divergent landscapes of A-to-I editing in postmortem and living human brain.

Adenosine-to-inosine (A-to-I) editing is a prevalent post-transcriptional RNA modification within the brain. Yet, most research has relied on postmortem samples, assuming it is an accurate representation of RNA biology in the living brain. We challenge this assumption by comparing A-to-I editing between postmortem and living prefrontal cortical tissues. Major differences were found, with over 70,000 A-to-I sites showing higher editing levels in postmortem tissues. Increased A-to-I editing in postmortem tissues is linked to higher ADAR and ADARB1 expression, is more pronounced in non-neuronal cells, and indicative of postmortem activation of inflammation and hypoxia. Higher A-to-I editing in living tissues marks sites that are evolutionarily preserved, synaptic, developmentally timed, and disrupted in neurological conditions. Common genetic variants were also found to differentially affect A-to-I editing levels in living versus postmortem tissues. Collectively, these discoveries offer more nuanced and accurate insights into the regulatory mechanisms of RNA editing in the human brain.

Divergent landscapes of A-to-I editing in postmortem and living human brain.

Adenosine-to-inosine (A-to-I) editing is a prevalent post-transcriptional RNA modification within the brain. Yet, most research has relied on postmortem samples, assuming it is an accurate representation of RNA biology in the living brain. We challenge this assumption by comparing A-to-I editing between postmortem and living prefrontal cortical tissues. Major differences were found, with over 70,000 A-to-I sites showing higher editing levels in postmortem tissues. Increased A-to-I editing in postmortem tissues is linked to higher ADAR1 and ADARB1 expression, is more pronounced in non-neuronal cells, and indicative of postmortem activation of inflammation and hypoxia. Higher A-to-I editing in living tissues marks sites that are evolutionarily preserved, synaptic, developmentally timed, and disrupted in neurological conditions. Common genetic variants were also found to differentially affect A-to-I editing levels in living versus postmortem tissues. Collectively, these discoveries illuminate the nuanced functions and intricate regulatory mechanisms of RNA editing within the human brain.

Multiomic foundations of human prefrontal cortex tissue function.

The prefrontal cortex (PFC) is a region of the brain that in humans is involved in the production of higher-order functions such as cognition, emotion, perception, and behavior. Neurotransmission in the PFC produces higher-order functions by integrating information from other areas of the brain. At the foundation of neurotransmission, and by extension at the foundation of higher-order brain functions, are an untold number of coordinated molecular processes involving the DNA sequence variants in the genome, RNA transcripts in the transcriptome, and proteins in the proteome. These "multiomic" foundations are poorly understood in humans, perhaps in part because most modern studies that characterize the molecular state of the human PFC use tissue obtained when neurotransmission and higher-order brain functions have ceased (i.e., the postmortem state). Here, analyses are presented on data generated for the Living Brain Project (LBP) to investigate whether PFC tissue from individuals with intact higher-order brain function has characteristic multiomic foundations. Two complementary strategies were employed towards this end. The first strategy was to identify in PFC samples obtained from living study participants a signature of RNA transcript expression associated with neurotransmission measured intracranially at the time of PFC sampling, in some cases while participants performed a task engaging higher-order brain functions. The second strategy was to perform multiomic comparisons between PFC samples obtained from individuals with intact higher-order brain function at the time of sampling (i.e., living study participants) and PFC samples obtained in the postmortem state. RNA transcript expression within multiple PFC cell types was associated with fluctuations of dopaminergic, serotonergic, and/or noradrenergic neurotransmission in the substantia nigra measured while participants played a computer game that engaged higher-order brain functions. A subset of these associations - termed the "transcriptional program associated with neurotransmission" (TPAWN) - were reproduced in analyses of brain RNA transcript expression and intracranial neurotransmission data obtained from a second LBP cohort and from a cohort in an independent study. RNA transcripts involved in TPAWN were found to be (1) enriched for RNA transcripts associated with measures of neurotransmission in rodent and cell models, (2) enriched for RNA transcripts encoded by evolutionarily constrained genes, (3) depleted of RNA transcripts regulated by common DNA sequence variants, and (4) enriched for RNA transcripts implicated in higher-order brain functions by human population genetic studies. In PFC excitatory neurons of living study participants, higher expression of the genes in TPAWN tracked with higher expression of RNA transcripts that in rodent PFC samples are markers of a class of excitatory neurons that connect the PFC to deep brain structures. TPAWN was further reproduced by RNA transcript expression patterns differentiating living PFC samples from postmortem PFC samples, and significant differences between living and postmortem PFC samples were additionally observed with respect to (1) the expression of most primary RNA transcripts, mature RNA transcripts, and proteins, (2) the splicing of most primary RNA transcripts into mature RNA transcripts, (3) the patterns of co-expression between RNA transcripts and proteins, and (4) the effects of some DNA sequence variants on RNA transcript and protein expression. Taken together, this report highlights that studies of brain tissue obtained in a safe and ethical manner from large cohorts of living individuals can help advance understanding of the multiomic foundations of brain function.

Opioids and immune checkpoint inhibitors differentially regulate a common immune network in triple-negative breast cancer.

Background: Opioids are the primary analgesics for cancer pain. Recent clinical evidence suggests opioids may counteract the effect of immune checkpoint inhibition (ICI) immunotherapy, but the mechanism for this interaction is unknown. The following experiments study how opioids and immunotherapy modulate a common RNA expression pathway in triple negative breast cancer (TNBC), a cancer subtype in which immunotherapy is increasingly used. This study identifies a mechanism by which opioids may decrease ICI efficacy, and compares ketamine, a non-opioid analgesic with emerging use in cancer pain, for potential ICI interaction. Methods: Tumor RNA expression and clinicopathologic data from a large cohort with TNBC (N=286) was used to identify RNA expression signatures of disease. Various drug-induced RNA expression profiles were extracted from multimodal RNA expression datasets and analyzed to estimate the RNA expression effects of ICI, opioids, and ketamine on TNBC. Results: We identified a RNA expression network in CD8+ T-cells that was relevant to TNBC pathogenesis and prognosis. Both opioids and anti-PD-L1 ICI regulated RNA expression in this network, suggesting a nexus for opioid-ICI interaction. Morphine and anti-PD-L1 therapy regulated RNA expression in opposing directions. By contrast, there was little overlap between the effect of ketamine and anti-PD-L1 therapy on RNA expression. Conclusions: Opioids and ICI may target a common immune network in TNBC and regulate gene expression in opposing fashion. No available evidence supports a similar interaction between ketamine and ICI.

Convergent abnormalities in striatal gene networks in human cocaine use disorder and mouse cocaine administration models.

Cocaine use disorder (CUD) is an intractable syndrome, and rising overdose death rates represent a substantial public health crisis that exacts tremendous personal and financial costs on patients and society. Sharp increases in cocaine use drive the urgent need for better mechanistic insight into this chronic relapsing brain disorder that currently lacks effective treatment options. To investigate the transcriptomic changes involved, we conducted RNA sequencing on two striatal brain regions that are heavily implicated in CUD, the nucleus accumbens and caudate nucleus, from men suffering from CUD and matched controls. Weighted gene coexpression analyses identified CUD-specific gene networks enriched in ionotropic receptors and linked to lowered neuroinflammation, contrasting the proinflammatory responses found in opioid use disorder. Integration of comprehensive transcriptomic datasets from mouse cocaine self-administration models revealed evolutionarily conserved gene networks in CUD that implicate especially D1 medium spiny neurons as drivers of cocaine-induced plasticity.

A study of gene expression in the living human brain.

A goal of medical research is to determine the molecular basis of human brain health and illness. One way to achieve this goal is through observational studies of gene expression in human brain tissue. Due to the unavailability of brain tissue from living people, most such studies are performed using tissue from postmortem brain donors. An assumption underlying this practice is that gene expression in the postmortem human brain is an accurate representation of gene expression in the living human brain. Here, this assumption - which, until now, had not been adequately tested - is tested by comparing human prefrontal cortex gene expression between 275 living samples and 243 postmortem samples. Expression levels differed significantly for nearly 80% of genes, and a systematic examination of alternative explanations for this observation determined that these differences are not a consequence of cell type composition, RNA quality, postmortem interval, age, medication, morbidity, symptom severity, tissue pathology, sample handling, batch effects, or computational methods utilized. Analyses integrating the data generated for this study with data from earlier landmark studies that used tissue from postmortem brain donors showed that postmortem brain gene expression signatures of neurological and mental illnesses, as well as of normal traits such as aging, may not be accurate representations of these gene expression signatures in the living brain. By using tissue from large cohorts living people, future observational studies of human brain biology have the potential to (1) determine the medical research questions that can be addressed using postmortem tissue as a proxy for living tissue and (2) expand the scope of medical research to include questions about the molecular basis of human brain health and illness that can only be addressed in living people (e.g., "What happens at the molecular level in the brain as a person experiences an emotion?").

Identifying Mobile Sensing Indicators of Stress-Resilience.

Resident physicians (residents) experiencing prolonged workplace stress are at risk of developing mental health symptoms. Creating novel, unobtrusive measures of resilience would provide an accessible approach to evaluate symptom susceptibility without the perceived stigma of formal mental health assessments. In this work, we created a system to find indicators of resilience using passive wearable sensors and smartphone-delivered ecological momentary assessment (EMA). This system identified indicators of resilience during a medical internship, the high stress first-year of a residency program. We then created density estimation approaches to predict these indicators before mental health changes occurred, and validated whether the predicted indicators were also associated with resilience. Our system identified resilience indicators associated with physical activity (step count), sleeping behavior, reduced heart rate, increased mood, and reduced mood variability. Density estimation models were able to replicate a subset of the associations between sleeping behavior, heart rate, and resilience. To the best of our knowledge, this work provides the first methodology to identify and predict indicators of resilience using passive sensing and EMA. Researchers studying resident mental health can apply this approach to design resilience-building interventions and prevent mental health symptom development.