Anxiety disorders are increasingly prevalent, affect people's ability to do things, and decrease quality of life. Due to lack of objective tests, they are underdiagnosed and sub-optimally treated, ...resulting in adverse life events and/or addictions. We endeavored to discover blood biomarkers for anxiety, using a four-step approach. First, we used a longitudinal within-subject design in individuals with psychiatric disorders to discover blood gene expression changes between self-reported low anxiety and high anxiety states. Second, we prioritized the list of candidate biomarkers with a Convergent Functional Genomics approach using other evidence in the field. Third, we validated our top biomarkers from discovery and prioritization in an independent cohort of psychiatric subjects with clinically severe anxiety. Fourth, we tested these candidate biomarkers for clinical utility, i.e. ability to predict anxiety severity state, and future clinical worsening (hospitalizations with anxiety as a contributory cause), in another independent cohort of psychiatric subjects. We showed increased accuracy of individual biomarkers with a personalized approach, by gender and diagnosis, particularly in women. The biomarkers with the best overall evidence were GAD1, NTRK3, ADRA2A, FZD10, GRK4, and SLC6A4. Finally, we identified which of our biomarkers are targets of existing drugs (such as a valproate, omega-3 fatty acids, fluoxetine, lithium, sertraline, benzodiazepines, and ketamine), and thus can be used to match patients to medications and measure response to treatment. We also used our biomarker gene expression signature to identify drugs that could be repurposed for treating anxiety, such as estradiol, pirenperone, loperamide, and disopyramide. Given the detrimental impact of untreated anxiety, the current lack of objective measures to guide treatment, and the addiction potential of existing benzodiazepines-based anxiety medications, there is a urgent need for more precise and personalized approaches like the one we developed.
Abstract
The time delay between flux variations in different wavelength bands can be used to probe the inner regions of active galactic nuclei (AGNs). Here, we present the first measurements of the ...time delay between optical and near-infrared (NIR) flux variations in H0507+164, a nearby Seyfert 1.5 galaxy at z = 0.018. The observations in the optical V-band and NIR J, H, and Ks bands carried over 35 epochs during the period 2016 October to 2017 April
were used to estimate the inner radius of the dusty torus. From a careful reduction and analysis of the data using cross-correlation techniques, we found delayed responses of the J, H, and Ks light curves to the V-band light curve. In the rest frame of the source, the lags between optical and NIR bands are found to be $27.1^{+13.5}_{-12.0}\,\mathrm{d}$ (V versus J), $30.4^{+13.9}_{-12.0}\,\mathrm{d}$ (V versus H) and $34.6^{+12.1}_{-9.6}\,\mathrm{d}$ (V versus Ks). The lags between the optical and different NIR bands are thus consistent with each other. The measured lags indicate that the inner edge of dust torus is located at a distance of 0.029 pc from the central ultraviolet/optical AGN continuum. This is larger than the radius of the broad line region of this object determined from spectroscopic monitoring observations thereby supporting the unification model of AGN. The location of H0507+164 in the τ–MV plane indicates that our results are in excellent agreement with the now known lag-luminosity scaling relationship for dust in AGN.
Psychosis occurs inside the brain, but may have external manifestations (peripheral molecular biomarkers, behaviors) that can be objectively and quantitatively measured. Blood biomarkers that track ...core psychotic manifestations such as hallucinations and delusions could provide a window into the biology of psychosis, as well as help with diagnosis and treatment. We endeavored to identify objective blood gene expression biomarkers for hallucinations and delusions, using a stepwise discovery, prioritization, validation, and testing in independent cohorts design. We were successful in identifying biomarkers that were predictive of high hallucinations and of high delusions states, and of future psychiatric hospitalizations related to them, more so when personalized by gender and diagnosis. Top biomarkers for hallucinations that survived discovery, prioritization, validation and testing include PPP3CB, DLG1, ENPP2, ZEB2, and RTN4. Top biomarkers for delusions include AUTS2, MACROD2, NR4A2, PDE4D, PDP1, and RORA. The top biological pathways uncovered by our work are glutamatergic synapse for hallucinations, as well as Rap1 signaling for delusions. Some of the biomarkers are targets of existing drugs, of potential utility in pharmacogenomics approaches (matching patients to medications, monitoring response to treatment). The top biomarkers gene expression signatures through bioinformatic analyses suggested a prioritization of existing medications such as clozapine and risperidone, as well as of lithium, fluoxetine, valproate, and the nutraceuticals omega-3 fatty acids and magnesium. Finally, we provide an example of how a personalized laboratory report for doctors would look. Overall, our work provides advances for the improved diagnosis and treatment for schizophrenia and other psychotic disorders.
There are to date no objective clinical laboratory blood tests for psychotic disease states. We provide proof of principle for a convergent functional genomics (CFG) approach to help identify and ...prioritize blood biomarkers for two key psychotic symptoms, one sensory (hallucinations) and one cognitive (delusions). We used gene expression profiling in whole blood samples from patients with schizophrenia and related disorders, with phenotypic information collected at the time of blood draw, then cross-matched the data with other human and animal model lines of evidence. Topping our list of candidate blood biomarkers for hallucinations, we have four genes decreased in expression in high hallucinations states (Fn1, Rhobtb3, Aldh1l1, Mpp3), and three genes increased in high hallucinations states (Arhgef9, Phlda1, S100a6). All of these genes have prior evidence of differential expression in schizophrenia patients. At the top of our list of candidate blood biomarkers for delusions, we have 15 genes decreased in expression in high delusions states (such as Drd2, Apoe, Scamp1, Fn1, Idh1, Aldh1l1), and 16 genes increased in high delusions states (such as Nrg1, Egr1, Pvalb, Dctn1, Nmt1, Tob2). Twenty-five of these genes have prior evidence of differential expression in schizophrenia patients. Predictive scores, based on panels of top candidate biomarkers, show good sensitivity and negative predictive value for detecting high psychosis states in the original cohort as well as in three additional cohorts. These results have implications for the development of objective laboratory tests to measure illness severity and response to treatment in devastating disorders such as schizophrenia.
Short- and mid-term data on Roux-en-Y gastric bypass (RYGB) indicate sustained weight loss and improvement in co-morbidities. Few long-term studies exist, some of which are outdated, based on open ...procedures or different techniques.
To investigate long-term weight loss, co-morbidity remission, nutritional status, and complication rates among patients undergoing RYGB.
An academic, university hospital in the United States.
Between October 2000 and January 2004, patients who underwent RYGB≥10 years before study onset were eligible for chart review, office visits, and telephone interviews. Revisional surgery was an endpoint, ceasing eligibility for study follow-up. Outcomes included weight loss measures and rates of co-morbidity remission, complications, and nutritional deficiencies.
RYGB was performed in 328 patients with a mean preoperative body mass index of 47.5 kg/m(2). Of 294 eligible patients, 134 (46%) were contacted for follow-up at ≥ 10 years (10+Year follow-up). Mean percentage excess weight loss (%EWL) was 58.9% at 10+Year. Higher %EWL was achieved by non-super-obese versus super-obese (61.3% versus 52.9%, P = .034). Blood pressure, lipid panel, and hemoglobin A1c improved significantly. At 10 years, remission of co-morbidities was 46% for hypertension and hyperlipidemia and 58% for diabetes mellitus. Thirty patients (9%) had revisional surgery for weight regain. Sixty-four patients (19.5%) had long-term complications requiring surgery. All-cause mortality was 2.7%. Nutritional deficiencies were seen in 87% of patients.
Weight loss after RYGB appears to be significant and sustainable, especially in the non-super-obese. Co-morbidities are improved, with a substantial number in remission a decade later. Nutritional deficiencies are almost universal.
Our aim was to determine outcomes with transplanting kidneys from deceased donors with acute kidney injury, defined as a donor with terminal serum creatinine ≥2.0 mg/dL, or a donor requiring acute ...renal replacement therapy. We included all patients who received deceased donor kidney transplant from June 2004 to October 2013. There were 162 AKI donor transplant recipients (21% of deceased donor transplants): 139 in the standard criteria donor (SCD) and 23 in the expanded criteria donor (ECD) cohort. 71% of the AKI donors had stage 3 (severe AKI), based on acute kidney injury network (AKIN) staging. Protocol biopsies were done at 1, 4, and 12 months posttransplant. One and four month formalin‐fixed paraffin embedded (FFPE) biopsies from 48 patients (24 AKI donors, 24 non‐AKI) underwent global gene expression profiling using DNA microarrays (96 arrays). DGF was more common in the AKI group but eGFR, graft survival at 1 year and proportion with IF/TA>2 at 1 year were similar for the two groups. At 1 month, there were 898 differentially expressed genes in the AKI group (p‐value <0.005; FDR <10%), but by 4 months there were no differences. Transplanting selected kidneys from deceased donors with AKI is safe and has excellent outcomes.
The authors show that transplanting select kidneys from deceased donors with severe acute injury results in excellent outcomes, including graft survival, and resolution of early differences in allograft gene expression for tissue damage, cell death, and inflammation.
Short-term memory dysfunction is a key early feature of Alzheimer's disease (AD). Psychiatric patients may be at higher risk for memory dysfunction and subsequent AD due to the negative effects of ...stress and depression on the brain. We carried out longitudinal within-subject studies in male and female psychiatric patients to discover blood gene expression biomarkers that track short term memory as measured by the retention measure in the Hopkins Verbal Learning Test. These biomarkers were subsequently prioritized with a convergent functional genomics approach using previous evidence in the field implicating them in AD. The top candidate biomarkers were then tested in an independent cohort for ability to predict state short-term memory, and trait future positive neuropsychological testing for cognitive impairment. The best overall evidence was for a series of new, as well as some previously known genes, which are now newly shown to have functional evidence in humans as blood biomarkers: RAB7A, NPC2, TGFB1, GAP43, ARSB, PER1, GUSB, and MAPT. Additional top blood biomarkers include GSK3B, PTGS2, APOE, BACE1, PSEN1, and TREM2, well known genes implicated in AD by previous brain and genetic studies, in humans and animal models, which serve as reassuring de facto positive controls for our whole-genome gene expression discovery approach. Biological pathway analyses implicate LXR/RXR activation, neuroinflammation, atherosclerosis signaling, and amyloid processing. Co-directionality of expression data provide new mechanistic insights that are consistent with a compensatory/scarring scenario for brain pathological changes. A majority of top biomarkers also have evidence for involvement in other psychiatric disorders, particularly stress, providing a molecular basis for clinical co-morbidity and for stress as an early precipitant/risk factor. Some of them are modulated by existing drugs, such as antidepressants, lithium and omega-3 fatty acids. Other drug and nutraceutical leads were identified through bioinformatic drug repurposing analyses (such as pioglitazone, levonorgestrel, salsolidine, ginkgolide A, and icariin). Our work contributes to the overall pathophysiological understanding of memory disorders and AD. It also opens new avenues for precision medicine- diagnostics (assement of risk) as well as early treatment (pharmacogenomically informed, personalized, and preventive).
We endeavored to identify objective blood biomarkers for pain, a subjective sensation with a biological basis, using a stepwise discovery, prioritization, validation, and testing in independent ...cohorts design. We studied psychiatric patients, a high risk group for co-morbid pain disorders and increased perception of pain. For discovery, we used a powerful within-subject longitudinal design. We were successful in identifying blood gene expression biomarkers that were predictive of pain state, and of future emergency department (ED) visits for pain, more so when personalized by gender and diagnosis. MFAP3, which had no prior evidence in the literature for involvement in pain, had the most robust empirical evidence from our discovery and validation steps, and was a strong predictor for pain in the independent cohorts, particularly in females and males with PTSD. Other biomarkers with best overall convergent functional evidence for involvement in pain were GNG7, CNTN1, LY9, CCDC144B, and GBP1. Some of the individual biomarkers identified are targets of existing drugs. Moreover, the biomarker gene expression signatures were used for bioinformatic drug repurposing analyses, yielding leads for possible new drug candidates such as SC-560 (an NSAID), and amoxapine (an antidepressant), as well as natural compounds such as pyridoxine (vitamin B6), cyanocobalamin (vitamin B12), and apigenin (a plant flavonoid). Our work may help mitigate the diagnostic and treatment dilemmas that have contributed to the current opioid epidemic.
There are no minimally invasive diagnostic metrics for acute kidney transplant rejection (AR), especially in the setting of the common confounding diagnosis, acute dysfunction with no rejection ...(ADNR). Thus, though kidney transplant biopsies remain the gold standard, they are invasive, have substantial risks, sampling error issues and significant costs and are not suitable for serial monitoring. Global gene expression profiles of 148 peripheral blood samples from transplant patients with excellent function and normal histology (TX; n = 46), AR (n = 63) and ADNR (n = 39), from two independent cohorts were analyzed with DNA microarrays. We applied a new normalization tool, frozen robust multi‐array analysis, particularly suitable for clinical diagnostics, multiple prediction tools to discover, refine and validate robust molecular classifiers and we tested a novel one‐by‐one analysis strategy to model the real clinical application of this test. Multiple three‐way classifier tools identified 200 highest value probesets with sensitivity, specificity, positive predictive value, negative predictive value and area under the curve for the validation cohort ranging from 82% to 100%, 76% to 95%, 76% to 95%, 79% to 100%, 84% to 100% and 0.817 to 0.968, respectively. We conclude that peripheral blood gene expression profiling can be used as a minimally invasive tool to accurately reveal TX, AR and ADNR in the setting of acute kidney transplant dysfunction.
This study of kidney transplantation describes a three‐way classifier based on global gene expression profiling of peripheral blood and the blood signatures of patients with excellent functioning grafts that can be used in the setting of acute kidney transplant dysfunction to accurately distinguish between biopsy‐proven acute rejection and acute dysfunction with no rejection.
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