Treatment Response Phenotypes Research Articles

Abstract 3565: The Cox proportional hazards mixed model enables accurate estimation of the total effect somatic SNVs have on treatment outcomes

Abstract Heritability is the variation in disease susceptibility attributed to genetic variation and is a fundamental parameter for interpreting disease architecture and making predictions. In the context of germline genetics, variance component models are commonly used to estimate heritability for continuous or case-control phenotypes (under the liability threshold model, LTM). However, models for time-to-event (TTE) outcomes have been largely unstudied. This has limited the characterization of age-of-onset and treatment response phenotypes, the latter particularly relevant for clinical studies. Here, we propose and evaluate a Cox proportional hazard Mixed Model (COXMM) to enable accurate estimation for TTE phenotypes with censoring. We apply these methods to Real World data from the Profile cohort from Dana-Farber Cancer Institute, a large prospectively collected tumor sequencing cohort with detailed clinical annotation. We implemented an efficient COXMM with a random effect modeled by the genetic relatedness across individuals, and benchmarked its performance in extensive simulations. We simulated phenotypes according to generative models reflecting either LTM or TTE models. For TTE phenotypes, data followed various Weibull distributions with independent censoring. Across TTE simulations, COXMM produced unbiased estimates while the classic case-control heritability estimator showed significant downward bias. Likewise, restricting only to cases and estimating the heritability of age-of-onset as a normalized continuous phenotype produced biased estimates, due to the artificial exclusion of controls. For example, for an age-of-onset with heritability of 0.8 and 40% of individuals in the study being cases, COXMM correctly inferred the heritability to be 0.80 +/- 0.007, compared to 0.32 +/- 0.004 for a conventional case-control model, and 0.09 +/- 0.02 for a conventional case-only age-of-onset model. In the Profile cohort, we analyzed the impact of somatic SNVs on progression free survival (PFS) and overall survival (OS) in patients with non-small cell lung cancer (N=954 and N=1796, respectively). We restricted to somatic SNVs present in at least 5% of patients. For OS, we observed that the COXMM heritability estimate was significantly larger than those computed by case-control status and using a normalized case-only age/duration (COXMM: 0.19 +/- 0.003; Case-Control: 0.07 +/- 0.2; Duration: 0.04 +/- 0.01). We observed a similar phenomenon for PFS as well (COXMM: 0.11 +/- 0.01; Case-Control: 0.03 +/- 0.4; Duration: 0.03 +/- 0.02). These results demonstrate that somatic features are most strongly associated with TTE and can be accurately estimated with COXMM. COXMM enables the efficient quantification of TTE heritability for diverse clinical phenotypes and outperforms existing methods. Citation Format: Kodi Taraszka, Alexander Gusev. The Cox proportional hazards mixed model enables accurate estimation of the total effect somatic SNVs have on treatment outcomes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3565.

Connectomic insight into unique stroke patient recovery after rTMS treatment.

An improved understanding of the neuroplastic potential of the brain has allowed advancements in neuromodulatory treatments for acute stroke patients. However, there remains a poor understanding of individual differences in treatment-induced recovery. Individualized information on connectivity disturbances may help predict differences in treatment response and recovery phenotypes. We studied the medical data of 22 ischemic stroke patients who received MRI scans and started repetitive transcranial magnetic stimulation (rTMS) treatment on the same day. The functional and motor outcomes were assessed at admission day, 1 day after treatment, 30 days after treatment, and 90 days after treatment using four validated standardized stroke outcome scales. Each patient underwent detailed baseline connectivity analyses to identify structural and functional connectivity disturbances. An unsupervised machine learning (ML) agglomerative hierarchical clustering method was utilized to group patients according to outcomes at four-time points to identify individual phenotypes in recovery trajectory. Differences in connectivity features were examined between individual clusters. Patients were a median age of 64, 50% female, and had a median hospital length of stay of 9.5 days. A significant improvement between all time points was demonstrated post treatment in three of four validated stroke scales utilized. ML-based analyses identified distinct clusters representing unique patient trajectories for each scale. Quantitative differences were found to exist in structural and functional connectivity analyses of the motor network and subcortical structures between individual clusters which could explain these unique trajectories on the Barthel Index (BI) scale but not on other stroke scales. This study demonstrates for the first time the feasibility of using individualized connectivity analyses in differentiating unique phenotypes in rTMS treatment responses and recovery. This personalized connectomic approach may be utilized in the future to better understand patient recovery trajectories with neuromodulatory treatment.

The Impact of BDNF, NTRK2, NGFR, CREB1, GSK3B, AKT, MAPK1, MTOR, PTEN, ARC, and SYN1 Genetic Polymorphisms in Antidepressant Treatment Response Phenotypes

This study aimed to investigate the influence of genetic variants in neuroplasticity-related genes on antidepressant treatment phenotypes. The BDNF-TrkB signaling pathway, as well as the downstream kinases Akt and ERK and the mTOR pathway, have been implicated in depression and neuroplasticity. However, clinicians still struggle with the unpredictability of antidepressant responses in depressed patients. We genotyped 26 polymorphisms in BDNF, NTRK2, NGFR, CREB1, GSK3B, AKT, MAPK1, MTOR, PTEN, ARC, and SYN1 in 80 patients with major depressive disorder treated according to the Texas Medical Algorithm for 27 months at Hospital Magalhães Lemos, Porto, Portugal. Our results showed that BDNF rs6265, PTEN rs12569998, and SYN1 rs1142636 SNP were associated with treatment-resistant depression (TRD). Additionally, MAPK1 rs6928 and GSK3B rs6438552 gene polymorphisms were associated with relapse. Moreover, we found a link between the rs6928 MAPK1 polymorphism and time to relapse. These findings suggest that the BDNF, PTEN, and SYN1 genes may play a role in the development of TRD, while MAPK1 and GSK3B may be associated with relapse. GO analysis revealed enrichment in synaptic and trans-synaptic transmission pathways and glutamate receptor activity with TRD-associated genes. Genetic variants in these genes could potentially be incorporated into predictive models of antidepressant response.

Rituximab versus tocilizumab in rheumatoid arthritis: synovial biopsy-based biomarker analysis of the phase 4 R4RA randomized trial

Patients with rheumatoid arthritis (RA) receive highly targeted biologic therapies without previous knowledge of target expression levels in the diseased tissue. Approximately 40% of patients do not respond to individual biologic therapies and 5–20% are refractory to all. In a biopsy-based, precision-medicine, randomized clinical trial in RA (R4RA; n = 164), patients with low/absent synovial B cell molecular signature had a lower response to rituximab (anti-CD20 monoclonal antibody) compared with that to tocilizumab (anti-IL6R monoclonal antibody) although the exact mechanisms of response/nonresponse remain to be established. Here, in-depth histological/molecular analyses of R4RA synovial biopsies identify humoral immune response gene signatures associated with response to rituximab and tocilizumab, and a stromal/fibroblast signature in patients refractory to all medications. Post-treatment changes in synovial gene expression and cell infiltration highlighted divergent effects of rituximab and tocilizumab relating to differing response/nonresponse mechanisms. Using ten-by-tenfold nested cross-validation, we developed machine learning algorithms predictive of response to rituximab (area under the curve (AUC) = 0.74), tocilizumab (AUC = 0.68) and, notably, multidrug resistance (AUC = 0.69). This study supports the notion that disease endotypes, driven by diverse molecular pathology pathways in the diseased tissue, determine diverse clinical and treatment–response phenotypes. It also highlights the importance of integration of molecular pathology signatures into clinical algorithms to optimize the future use of existing medications and inform the development of new drugs for refractory patients.

Genetic variants associated with acamprosate treatment response in alcohol use disorder patients: A multiple omics study.

Background and PurposeAcamprosate is an anti‐craving drug used for the pharmacotherapy of alcohol use disorder (AUD). However, only some patients achieve optimal therapeutic outcomes. This study was designed to explore differences in metabolomic profiles between patients who maintained sobriety and those who relapsed, to determine whether those differences provide insight into variation in acamprosate treatment response phenotypes.Experimental ApproachWe previously conducted an acamprosate trial involving 442 AUD patients, and 267 of these subjects presented themselves for a 3‐month follow‐up. The primary outcome was abstinence. Clinical information, genomic data and metabolomics data were collected. Baseline plasma samples were assayed using targeted metabolomics.Key ResultsBaseline plasma arginine, threonine, α‐aminoadipic acid and ethanolamine concentrations were associated with acamprosate treatment outcomes and baseline craving intensity, a measure that has been associated with acamprosate treatment response. We next applied a pharmacometabolomics‐informed genome‐wide association study (GWAS) strategy to identify genetic variants that might contribute to variations in plasma metabolomic profiles that were associated with craving and/or acamprosate treatment outcome. Gene expression data for induced pluripotent stem cell‐derived forebrain astrocytes showed that a series of genes identified during the metabolomics‐informed GWAS were ethanol responsive. Furthermore, a large number of those genes could be regulated by acamprosate. Finally, we identified a series of single nucleotide polymorphisms that were associated with acamprosate treatment outcomes.Conclusion and ImplicationsThese results serve as an important step towards advancing our understanding of disease pathophysiology and drug action responsible for variation in acamprosate response and alcohol craving in AUD patients.

Lack of association of FKBP5 SNPs and haplotypes with susceptibility and treatment response phenotypes in Han Chinese with major depressive disorder: A pilot case-control study (STROBE).

The identification of single-nucleotide polymorphisms (SNPs) in genes putatively related to pathophysiological processes in major depressive disorder (MDD) might improve both diagnosis and personalized treatment strategies eventually leading to more effective interventions. Considering the important role of the glucocorticoid receptor and the related FK506 binding protein 51 (FKBP51) in the pathophysiology of MDD, we aimed to investigate putative associations between variants of FKBP5, the coding gene of FKBP51, with antidepressant treatment resistance and MDD susceptibility.Nine common SNPs of the FKBP5 gene prioritized based on location and, putative or known functions were genotyped in Han Chinese population, including MDD patients with or without antidepressant-treatment resistance and healthy controls. Associations of FKBP5 SNPs with MDD susceptibility and treatment response were examined in the whole group of MDD patients, as well as in subgroups stratified by antidepressant treatment resistance, compared with healthy controls.In total, 181 Han Chinese patients with MDD and 80 healthy controls were recruited. No significant SNP or haplotype associations were observed in the whole patient group. There were nominal significant differences both for the haplotype block with SNPs in strong LD (r2 > 0.8, P = .040) and haplotype block with SNPs in moderate LD (r2 > 0.1, P = .017) between the haplotype distributions of patients with antidepressant treatment resistance (n = 81) and healthy controls, but both significances did not survive multiple testing correction. Furthermore, no specific haplotype could be observed causing a significant difference in any combination between all comparisons.No associations were observed of FKBP5 variants with MDD or antidepressant treatment response. The lack of associations might be due to the relatively small sample size of this study (power ranged from 0.100 to 0.752). A follow-up study will need larger, better phenotyped, and more homogeneous samples to draw a definitive conclusion regarding the involvement of this gene in MDD.

The associations of CNR1 SNPs and haplotypes with vulnerability and treatment response phenotypes in Han Chinese with major depressive disorder: A case-control association study.

BackgroundUnderstanding how genetic polymorphisms are associated with the pathophysiology of major depressive disorder (MDD) may aid in diagnosis and the development of personalized treatment strategies. CNR1 is the gene coding Cannabinoid type 1 receptor which is highly involved in emotional processing and in regulating neurotransmitter releases. We aimed to investigate the associations of CNR1 single‐nucleotide polymorphisms (SNPs) with MDD susceptibility and treatment response.MethodsThe study reported data on 181 Han Chinese with MDD and 80 healthy controls. The associations of CNR1 genetic polymorphisms with MDD susceptibility and treatment response were examined, wherein the MDD patients were subgrouped further by responding to antidepressant treatment, compared with healthy controls separately.ResultsThe CNR1 SNPs rs806367 and rs6454674 and haplotype C‐T‐T‐C of rs806366, rs806367, rs806368, and rs806370 were associated with increased susceptibility for MDD and antidepressant treatment resistance, but the association was not detected in other SNPs or the haplotype block of rs806368 and rs806370.ConclusionThe CNR1 is a promising candidate for the genetic association study of MDD. Larger and well‐characterized samples are required to confirm the genetic association of CNR1 with MDD because of the limitations such as relatively small sample size and lack of information for correcting confounding factors.

449 The Effects of Positional and Sleep Stage Dependency on Mandibular Advancement Device Treatment Outcome in Obstructive Sleep Apnea

Abstract Introduction Mandibular advancement device (MAD) responder phenotype are not well understood in patients with obstructive sleep apnea (OSA). Recent studies have reported the association between MAD treatment response and polysomnographic phenotypes using positional and sleep stage dependency, but with inconsistent findings. Thus, the study aims to investigate the relationship between the two phenotypes and MAD response. Methods This retrospective study recruited patients with OSA (apnea-hypopnea index [AHI] >10/h), who were 20 to 80 years old, treatment naïve, and received MAD treatment for more than three months from 2009 to 2017. AHIsupine/AHInon-supine ≥2 and <2 meant supine predominant (supine-p) and non-positional OSA, respectively. REM-AHI/NREM-AHI ≥2, ≤0.5, and between 0.5 to 2 indicated REM-predominant (REM-p), NREM-predominant (NREM-p), and stage-independent (SI) OSA, respectively. Three criteria defined successful MAD treatment (i.e., criterion 1: residual AHI <5/h with >50% reduction; criterion 2: residual AHI 50% reduction; criterion 3: reduction >50%). The association between the two phenotypes and the three treatment criteria was identified using multivariable logistic regression. Results A total of 218 patients with a median age of 52.5 years, body mass index (BMI) of 25.4 kg/m2, and AHI of 28.2/h were recruited. Supine-p OSA had lower waist circumferences than non-positional OSA. The REM-p group had lower AHI and more female than the NREM-p and SI group. Supine-p OSA had better response than non-positional OSA (criterion 1: 43.2% vs 34.1%; criterion 2: 63.6% vs 34.1%; criterion 3: 77.3% vs 51.2%). NREM-p OSA had lower response across all three criteria (REM-p vs NREM-p vs SI: criterion 1: 57.6% vs 0% vs 42.0%; criterion 2: 75.8% vs 16.7% vs 56.5%; criterion 3: 75.8% vs 33.3% vs 77.1%). The odds of MAD response for supine-p OSA was 3.78 (95% CI = 1.44–9.93) to 3.98 (95% CI = 1.58–9.99)-fold than non-positional OSA while the odds for NREM-p OSA were 0.06 (95% CI = 0.01–0.58) to 0.15 (95% CI = 0.03–0.67)-fold than SI OSA after adjusting demographics and clinical features affecting MAD response. Conclusion Positional and sleep stage dependency were associated with MAD response and could be indicators for personal-tailored OSA treatment. Support (if any) The Ministry of Science and Technology, Taiwan (MOST 109-2314-B-002-252)

Acamprosate—an Anti-Craving Drug for Alcohol Use Disorder (AUD) Pharmacotherapy: Plasma Metabolomics Signatures are Associated With Alcohol Craving Intensity and Acamprosate Treatment Response

Acamprosate is an anti-craving drug used for the pharmacotherapy of alcohol use disorder (AUD). However, acamprosate’s mechanism(s) of action during the treatment of AUD remains unclear, and only some patients achieve optimal therapeutic outcomes. The present study was designed to explore the differences in metabolomic profiles between patients who maintained sobriety and those who relapsed. It also sought to determine whether those differences might provide insight into the mechanisms involved in the variations in acamprosate treatment response phenotypes.

Genetics of Schizophrenia and Bipolar Disorder: Potential Clinical Applications

Schizophrenia and bipolar disorder were the first psychiatric illnesses to demonstrate familial aggregation in systematic studies. Twin studies demonstrate high (up to 80%) heritability. Several decades of research using linkage, candidate gene, genome-wide association studies (GWASs), and next-generation sequencing studies ensued in the effort to identify etiologically relevant genetic variants. Over the last decade, GWASs using consortium-based datasets of tens of thousands of participants led to the confirmation of polygenic architectures in both illnesses, which overlapped with each other, as well as the identification of hundreds of mostly non-coding variants. Large, recurrent copy number variants (CNVs) and a higher CNV burden have been robustly identified in schizophrenia, but not bipolar disorder. Polygenic risk scores have emerged as promising signatures of underlying illness risk, which might be useful in predicting treatment response and other outcome phenotypes. Pharmacogenetic studies show promise to identify variants that predict drug response and adverse effects. However, they are currently underpowered because of the expense of conducting trials with sample sizes adequate to detect genetic variants of small effect. Large-scale precision medicine efforts such as All of Us and the Million Veteran Program are in process and might yet yield such information. [ Psychiatr Ann . 2021;51(4):158–164.]

A pilot study of cystic fibrosis exacerbation response phenotypes reveals contrasting serum and sputum iron trends

The cystic fibrosis (CF) community seeks to explain heterogeneous outcomes of pulmonary exacerbation (PEX) treatment. Serum and sputum inflammatory mediators may identify people with CF (PwCF) at risk for suboptimal responses. However, lack of an established association between response phenotypes and these mediators limits clinical application. In this pilot study, we prospectively characterized treatment response phenotypes by assessing health-related quality-of-life (HRQoL) during PEX. We also measured lung function and iron-related biochemical parameters in serum and sputum. We classified subjects as sustained symptom-responders (SRs) or non-sustained symptom-responders (NSRs) based on the absence or presence, respectively, of worsened symptom scores after initial improvement. We used linear mixed models (LMMs) to determine whether trends in lung function, hematologic, serum, and sputum indices of inflammation differed between response cohorts. In 20 PwCF, we identified 10 SRs and 10 NSRs with no significant differences in lung function at PEX onset and treatment durations. SRs had better model-predicted trends in lung function than NSRs during PEX. Non-linear trends in serum and sputum iron levels significantly differed between SRs and NSRs. In adults with cystic fibrosis, PEX treatment response phenotypes may be correlated with distinctive trends in serum and sputum iron concentrations.

Transforming clinical trials in rheumatology: towards patient-centric precision medicine.

Despite the success of targeted therapies in the treatment of inflammatory arthritides, the lack of predictive biomarkers drives a 'trial and error' approach to treatment allocation, leading to variable and/or unsatisfactory responses. In-depth characterization of the synovial tissue in rheumatoid arthritis, as well as psoriatic arthritis and spondyloarthritis, is bringing new insights into the diverse cellular and molecular features of these diseases and their potential links with different clinical and treatment-response phenotypes. Such progress raises the tantalizing prospect of improving response rates by matching the use of specific agents to the cognate target pathways that might drive particular disease subtypes in specific patient groups. Innovative patient-centric, molecular pathology-driven clinical trial approaches are needed to achieve this goal. Whilst progress is clearly being made, it is important to emphasize that this field is still in its infancy and there are a number of potential barriers to realizing the premise of patient-centric clinical trials.

Molecular Portraits of Early Rheumatoid Arthritis Identify Clinical and Treatment Response Phenotypes

SummaryThere is a current imperative to unravel the hierarchy of molecular pathways that drive the transition of early to established disease in rheumatoid arthritis (RA). Herein, we report a comprehensive RNA sequencing analysis of the molecular pathways that drive early RA progression in the disease tissue (synovium), comparing matched peripheral blood RNA-seq in a large cohort of early treatment-naive patients, namely, the Pathobiology of Early Arthritis Cohort (PEAC). We developed a data exploration website (https://peac.hpc.qmul.ac.uk/) to dissect gene signatures across synovial and blood compartments, integrated with deep phenotypic profiling. We identified transcriptional subgroups in synovium linked to three distinct pathotypes: fibroblastic pauci-immune pathotype, macrophage-rich diffuse-myeloid pathotype, and a lympho-myeloid pathotype characterized by infiltration of lymphocytes and myeloid cells. This is suggestive of divergent pathogenic pathways or activation disease states. Pro-myeloid inflammatory synovial gene signatures correlated with clinical response to initial drug therapy, whereas plasma cell genes identified a poor prognosis subgroup with progressive structural damage.

Orexin in the anxiety spectrum: association of a HCRTR1 polymorphism with panic disorder/agoraphobia, CBT treatment response and fear-related intermediate phenotypes

Preclinical studies point to a pivotal role of the orexin 1 (OX1) receptor in arousal and fear learning and therefore suggest the HCRTR1 gene as a prime candidate in panic disorder (PD) with/without agoraphobia (AG), PD/AG treatment response, and PD/AG-related intermediate phenotypes. Here, a multilevel approach was applied to test the non-synonymous HCRTR1 C/T Ile408Val gene variant (rs2271933) for association with PD/AG in two independent case-control samples (total n = 613 cases, 1839 healthy subjects), as an outcome predictor of a six-weeks exposure-based cognitive behavioral therapy (CBT) in PD/AG patients (n = 189), as well as with respect to agoraphobic cognitions (ACQ) (n = 483 patients, n = 2382 healthy subjects), fMRI alerting network activation in healthy subjects (n = 94), and a behavioral avoidance task in PD/AG pre- and post-CBT (n = 271). The HCRTR1 rs2271933 T allele was associated with PD/AG in both samples independently, and in their meta-analysis (p = 4.2 × 10−7), particularly in the female subsample (p = 9.8 × 10−9). T allele carriers displayed a significantly poorer CBT outcome (e.g., Hamilton anxiety rating scale: p = 7.5 × 10−4). The T allele count was linked to higher ACQ sores in PD/AG and healthy subjects, decreased inferior frontal gyrus and increased locus coeruleus activation in the alerting network. Finally, the T allele count was associated with increased pre-CBT exposure avoidance and autonomic arousal as well as decreased post-CBT improvement. In sum, the present results provide converging evidence for an involvement of HCRTR1 gene variation in the etiology of PD/AG and PD/AG-related traits as well as treatment response to CBT, supporting future therapeutic approaches targeting the orexin-related arousal system.

A sputum 6-gene signature predicts future exacerbations of poorly controlled asthma

Improved diagnostic tools for predicting future exacerbation frequency in asthmatic patients are required. Asputum gene expression signature of 6 biomarkers (6-gene signature [6GS], including Charcot-Leyden crystal galectin [CLC]; carboxypeptidase 3 [CPA3]; deoxyribonuclease 1-like 3 [DNASE1L3]; alkaline phosphatase, liver/bone/kidney [ALPL]; CXCR2; and IL1B) predicts inflammatory and treatment response phenotypes in patients with stable asthma. Recently, we demonstrated that azithromycin (AZM) add-on treatment in patients with uncontrolled moderate-to-severe asthma significantly reduced asthma exacerbations (AMAZES clinical trial). We sought to test whether the 6GS predicts future exacerbation and inflammatory phenotypes in a subpopulation of AMAZES and to test the effect of AZM therapy on 6GS expression and prognostic capacity. One hundred forty-two patients (73 placebo-treated and 69 AZM-treated patients) had sputum stored for quantitative PCR of 6GS markers at baseline and after 48weeks of treatment. Logistic regression and receiver operating characteristic and area under the curve (AUC) determination were performed on baseline measures, and in an exploratory analysis the predictive value of the 6GS was compared with conventional biomarkers for exacerbation and inflammatory phenotypes. The 6GS significantly predicted all future exacerbation phenotypes tested. Calculated AUCs for the 6GS were significantly greater than AUCs for peripheral blood eosinophil counts, sputum neutrophil counts, and combined sputum eosinophil and neutrophil counts. 6GS AUCs were also numerically but not significantly greater than those for fractional exhaled nitric oxide values and sputum eosinophil counts. AZM treatment altered neither 6GS expression nor the predictive capacity of the 6GS for future exacerbation phenotypes. The 6GS was a significant predictor of airway inflammatory phenotype in this population. We demonstrate that a sputum gene signature can predict future exacerbation phenotypes of asthma, with the greatest biomarker performance in identifying those who would experience frequent severe exacerbations. AZM therapy did not modify 6GS expression or biomarker performance, suggesting the therapeutic action of AZM is independent of 6GS-related inflammatory pathways.

The Impact of BDNF Polymorphisms on Suicidality in Treatment-Resistant Major Depressive Disorder: A European Multicenter Study.

BackgroundNumerous studies have reported associations between the brain-derived neurotrophic factor (BDNF) gene and psychiatric disorders, including suicidal behavior, although with conflicting results.MethodsA total of 250 major depressive disorder patients were collected in the context of a European multicenter resistant depression study and treated with antidepressants at adequate doses for at least 4 weeks. Suicidality was assessed using the Mini International Neuropsychiatric Interview and Hamilton Rating Scale for Depression, and treatment response using the HAM-D. Genotyping was performed for the functional Val66Met polymorphism (rs6265) and 7 additional tagging single nucleotide polymorphisms within the BDNF gene.ResultsNeither BDNF single markers nor haplotypes were found to be associated with suicide risk and lifetime history of suicide attempts. Gender-specific analyses revealed nonsignificant single marker (rs908867) and haplotypic association with suicide risk in males after multiple testing correction. Analyzing treatment response phenotypes, the functional Val66Met polymorphism as well as rs10501087 showed significant genotypic and haplotypic association with suicide risk in remitters (n=34, 13.6%).ConclusionsConsidering the sample size, the present findings need to be replicated in larger samples to confirm or refute a role of BDNF in the investigated suicidal behavior phenotypes.

Comprehensive analysis of treatment response phenotypes in rheumatoid arthritis for pharmacogenetic studies

BackgroundAn individual patient’s response to a particular drug is influenced by multiple factors, which may include genetic predisposition. Pharmacogenetic studies attempt to discover and estimate the contributions of genetic variants to the variability in response to a drug treatment. The task of identifying the genetic contribution is often complicated by response phenotypes that are based on imprecise or subjective clinical observations. Because the success of a pharmacogenetic study depends on the analysis of a heritable phenotype, it is important to identify phenotypes with a significant heritable component to ensure reliable and reproducible results in subsequent genetic association studies.MethodsWe retrospectively analyzed data collected from 436 rheumatoid arthritis patients treated with golimumab during the phase III GO-FURTHER study. We investigated the reliability of several potential response outcomes after golimumab treatment. Using whole-genome sequencing of the clinical trial cohort, we estimated the heritability of each potential outcome measure. We further performed a longitudinal analysis of the clinical data to estimate variability of outcome measures over time and the degree to which each response metric could be confounded by placebo response.ResultsWe determined that the high degree of within-patient variation over time makes a single follow-up visit insufficient to assess an individual patient’s response to golimumab treatment. We found that different potential response outcomes had varying degrees of heritability and that averaging across multiple follow-up visits yielded higher heritability estimates than single follow-up estimates. Importantly, we found that the change in swollen and tender joint counts were the most heritable outcome metrics we tested; however, we showed that they are also more likely to be confounded by a placebo response than objective phenotypes like the change in C-reactive protein levels.ConclusionsOur rigorous approach to finding robust and heritable response phenotypes could be beneficial to all pharmacogenetic studies and may lead to more reliable and reproducible results.Trial RegistrationClinicaltrials.gov NCT00973479. Registered 4 September 2009.

Oral Appliance Treatment Response and Polysomnographic Phenotypes of Obstructive Sleep Apnea.

Mandibular advancement splints (MAS) are an effective treatment for obstructive sleep apnea (OSA); however, therapeutic response is variable. Younger age, female gender, less obesity, and milder and supine-dependent OSA have variably been associated with treatment success in relatively small samples. Our objective was to utilize a large cohort of MAS treated patients (1) to compare efficacy across patients with different phenotypes of OSA and (2) to assess demographic, anthropometric, and polysomnography variables as treatment response predictors. Retrospective analysis of MAS-treated patients participating in clinical trials in sleep centers in Sydney, Australia between years 2000-2013. All studies used equivalent customized two-piece MAS devices and treatment protocols. Treatment response was defined as (1) apnea-hypopnea index (AHI) < 5/h, (2) AHI < 10/h and ≥ 50% reduction, and (3) ≥ 50% AHI reduction. A total of 425 patients (109 female) were included (age 51.2 ± 10.9 years, BMI 29.2 ± 5.0 kg/m2). MAS reduced AHI by 50.3% ± 50.7% across the group. Supine-predominant OSA patients had lower treatment response rates than non-positional OSA (e.g., 36% vs. 59% for AHI < 10/h). REM-predominant OSA showed a lower response rate than either NREM or non-stage dependent OSA. In prediction modelling, age, baseline AHI, and anthropometric variables were predictive of MAS treatment outcome but not OSA phenotype. Gender was not associated with treatment outcome. Lower MAS treatment response rates were observed in supine and REM sleep. In a large sample, we confirm that demographic, anthropometric, and polysomnographic data only weakly inform about MAS efficacy, supporting the need for alternative objective prediction methods to reliably select patients for MAS treatment.

FAS -670A>G genetic polymorphism Is associated with Treatment Resistant Depression

BackgroundHippocampal neurogenesis has been suggested as a downstream event of antidepressants (AD) mechanism of action and might explain the lag time between AD administration and the therapeutic effect. Despite the widespread use of AD in the context of Major Depressive Disorder (MDD) there are no reliable biomarkers of treatment response phenotypes, and a significant proportion of patients display Treatment Resistant Depression (TRD). Fas/FasL system is one of the best-known death-receptor mediated cell signaling systems and is recognized to regulate cell proliferation and tumor cell growth. Recently this pathway has been described to be involved in neurogenesis and neuroplasticity. MethodsSince FAS -670A>G and FASL -844T>C functional polymorphisms never been evaluated in the context of depression and antidepressant therapy, we genotyped FAS -670A>G and FASL -844T>C in a subset of 80 MDD patients to evaluate their role in antidepressant treatment response phenotypes. ResultsWe found that the presence of FAS -670G allele was associated with antidepressant bad prognosis (relapse or TRD: OR=6.200; 95% CI: [1.875–20.499]; p=0.001), and we observed that patients carrying this allele have a higher risk to develop TRD (OR=10.895; 95% CI: [1.362–87.135]; p=0.008). Moreover, multivariate analysis adjusted to potentials confounders showed that patients carrying G allele have higher risk of early relapse (HR=3.827; 95% CI: [1.072–13.659]; p=0.039). FAS mRNA levels were down-regulated among G carriers, whose genotypes were more common in TRD patients. No association was found between FASL-844T>C genetic polymorphism and any treatment phenotypes. LimitationsSmall sample size. Patients used antidepressants with different mechanisms of action. ConclusionTo the best of our knowledge this is the first study to evaluate the role of FAS functional polymorphism in the outcome of antidepressant therapy. This preliminary report associates FAS -670A>G genetic polymorphism with Treatment Resistant Depression and with time to relapse. The current results may possibly be given to the recent recognized role of Fas in neurogenesis and/or neuroplasticity.

Vanin-1 expression and methylation discriminate pediatric asthma corticosteroid treatment response

There is considerable heterogeneity in asthma treatment response. We sought to identify biomarkers of corticosteroid treatment response in children with asthma and evaluate the utility and mechanistic basis of these biomarkers. Children (5-18 years) presenting to the emergency department with an acute asthma exacerbation were recruited and followed during hospitalization. Nasal epithelial cells were collected on presentation to the emergency department (T0) and 18 to 24 hours later (T1), and T1/T0 gene expression ratios were analyzed to identify genes associated with good and poor corticosteroid treatment response phenotypes. The utility of these genes in discriminating between systemic corticosteroid treatment response groups was then tested prospectively in a new cohort of patients. A gene candidate (vanin-1 [VNN1]) that consistently distinguished good versus poor response phenotypes was further studied in an experimental asthma model, and VNN1 promoter methylation was measured by means of bisulfite pyrosequencing in patients. VNN1 mRNA expression changes were associated with systemic corticosteroid treatment response in children with acute asthma, and VNN1 was required for optimal response to corticosteroid treatment in an experimental asthma model. A CpG site within the VNN1 promoter was differentially methylated between good versus poor treatment response groups, and methylation at this site correlated with VNN1 mRNA expression. We have identified a biological basis for poor corticosteroid treatment response that can be used to distinguish a subgroup of asthmatic children who respond poorly to systemic corticosteroid treatment. VNN1 contributes to corticosteroid responsiveness, and changes in VNN1 nasal epithelial mRNA expression and VNN1 promoter methylation might be clinically useful biomarkers of treatment response in asthmatic children.