Clinical outcomes and genome-wide association for a brain methylation site in an antidepressant pharmacogenetics study in Mexican Americans

Impulsive and Omission Errors: Potential Temporal Processing Endophenotypes in ADHD

Temporal processing (TP) is associated with functions such as perception, verbal skills, temporal perspective, and future planning, and is intercorrelated with working memory, attention, and inhibitory control, which are highly impaired in individuals with attention deficit hyperactivity disorder (ADHD). Here we evaluate TP measures as potential endophenotypes in Caribbean families ascertained from probands affected by ADHD. A total of 232 individuals were recruited and clinically evaluated using an extensive battery of neuropsychological tasks and reaction time (RT)-based task paradigms. Further, the heritability (genetic variance underpinning phenotype) was estimated as a measure of the genetics apportionment. A predictive framework for ADHD diagnosis was derived using these tasks. We found that individuals with ADHD differed from controls in neuropsychological tasks assessing mental control, visual-verbal memory, verbal fluency, verbal, and semantic fluency. In addition, TP measures such as RT, errors, and variability were also affected in individuals with ADHD. Moreover, we determined that only omission and commission errors had significant heritability. In conclusion, we have disentangled omission and commission errors as possible TP endophenotypes in ADHD, which can be suitable to assess the neurobiological and genetic basis of ADHD. A predictive model using these endophenotypes led to remarkable sensitivity, specificity, precision and classification rate for ADHD diagnosis, and may be a useful tool for patients' diagnosis, follow-up, and longitudinal assessment in the clinical setting.

Rare Functional Variants Associated with Antidepressant Remission in Mexican-Americans: Short title: Antidepressant remission and pharmacogenetics in Mexican-Americans

INTRODUCTION

Rare genetic functional variants can contribute to 30-40% of functional variability in genes relevant to drug action. Therefore, we investigated the role of rare functional variants in antidepressant response.

METHOD

Mexican-American individuals meeting the Diagnostic and Statistical Manual-IV criteria for major depressive disorder (MDD) participated in a prospective randomized, double-blind study with desipramine or fluoxetine. The rare variant analysis was performed using whole-exome genotyping data. Network and pathway analyses were carried out with the list of significant genes.

RESULTS

The Kernel-Based Adaptive Cluster method identified functional rare variants in 35 genes significantly associated with treatment remission (False discovery rate, FDR <0.01). Pathway analysis of these genes supports the involvement of the following gene ontology processes: olfactory/sensory transduction, regulation of response to cytokine stimulus, and meiotic cell cycleprocess.

LIMITATIONS

Our study did not have a placebo arm. We were not able to use antidepressant blood level as a covariate. Our study is based on a small sample size of only 65 Mexican-American individuals. Further studies using larger cohorts are warranted.

CONCLUSION

Our data identified several rare functional variants in antidepressant drug response in MDD patients. These have the potential to serve as genetic markers for predicting drug response.

TRIAL REGISTRATION

ClinicalTrials.gov NCT00265291.

Genetic Markers for Later Remission in Response to Early Improvement of Antidepressants

Planning subsequent treatment strategies based on early responses rather than waiting for delayed antidepressant action can be helpful. We identified genetic markers for later non-remission in patients exhibiting poor early improvement using whole-exome sequencing data of depressive patients treated in a naturalistic manner. Among 1000 patients, early improvement at 2 weeks (reduction in Hamilton Depression Rating Scale [HAM-D] score ≥ 20%) and remission at 12 weeks (HAM-D score ≤ 7) were evaluated. Gene- and variant-level analyses were conducted to compare patients who did not exhibit early improvement and did not eventually achieve remission (n = 126) with those who exhibited early improvement and achieved remission (n = 385). Genes predicting final non-remission in patients who exhibited poor early improvement (COMT, PRNP, BRPF3, SLC25A40, and CGREF1 in males; PPFIBPI, LZTS3, MEPCE, MAP1A, and PFAS in females; ST3GAL5 in the total population) were determined. Among the significant genes, variants in the PRNP (rs1800014), COMT (rs6267), BRPF3 (rs200565609), and SLC25A40 genes (rs3213633) were identified. However, interpretations should be made cautiously, as complex pharmacotherapy involves various genes and pathways. Early detection of poor early improvement and final non-remission based on genetic risk would be helpful for decision-making in a clinical setting.

Targeted exome sequencing identifies five novel loci at genome-wide significance for modulating antidepressant response in patients with major depressive disorder

In order to determine the role of single nucleotide variants (SNVs) in modulating antidepressant response, we conducted a study, consisting of 929 major depressive disorder (MDD) patients, who were treated with antidepressant drugs (drug-only) or in combination with a repetitive transcranial magnetic stimulation (plus-rTMS), followed by targeted exome sequencing analysis. We found that the "plus-rTMS" patients presented a more effective response to the treatment when compared to the 'drug-only' group. Our data firstly demonstrated that the SNV burden had a significant impact on the antidepressant response presented in the "drug-only" group, but was limited in the "plus-rTMS" group. Further, after controlling for overall SNV burden, seven single nucleotide polymorphisms (SNPs) at five loci, IL1A, GNA15, PPP2CB, PLA2G4C, and GBA, were identified as affecting the antidepressant response at genome-wide significance (P < 5 × 10^-08). Additional multiple variants achieved a level of correction for multiple testing, including GNA11, also shown as a strong signal for MDD risk. Our study showed some promising evidence on genetic variants that could be used as individualized therapeutic guides for MDD patients.

A Review of Mental Health and Mental Health Care Disparities Research: 2011-2014

Racial/ethnic minorities in the United States are more likely than Whites to have severe and persistent mental disorders and less likely to access mental health care. This comprehensive review evaluates studies of mental health and mental health care disparities funded by the National Institute of Mental Health (NIMH) to provide a benchmark for the 2015 NIMH revised strategic plan. A total of 615 articles were categorized into five pathways underlying mental health care and three pathways underlying mental health disparities. Identified studies demonstrate that socioeconomic mechanisms and demographic moderators of disparities in mental health status and treatment are well described, as are treatment options that support diverse patient needs. In contrast, there is a need for studies that focus on community- and policy-level predictors of mental health care disparities, link discrimination- and trauma-induced neurobiological pathways to disparities in mental illness, assess the cost effectiveness of disparities reduction programs, and scale up culturally adapted interventions.

Pharmacogenetics and Depression: A Critical Perspective

Depression leads the higher personal and socio-economical burden within psychiatric disorders. Despite the fact that over 40 antidepressants (ADs) are available, suboptimal response still poses a major challenge and is thought to be partially a result of genetic variation. Pharmacogenetics studies the effects of genetic variants on treatment outcomes with the aim of providing tailored treatments, thereby maximizing efficacy and tolerability. After two decades of pharmacogenetic research, variants in genes coding for the cytochromes involved in ADs metabolism (CYP2D6 and CYP2C19) are now considered biomarkers with sufficient scientific support for clinical application, despite the lack of conclusive cost/effectiveness evidence. The effect of variants in genes modulating ADs mechanisms of action (pharmacodynamics) is still controversial, because of the much higher complexity of ADs pharmacodynamics compared to ADs metabolism. Considerable progress has been made since the era of candidate gene studies: the genomic revolution has made possible to assess genetic variance on an unprecedented scale, throughout the whole genome, and to analyze the cumulative effect of different variants. The results have revealed key information on the biological mechanisms mediating ADs effect and identified hypothetical new pharmacological targets. They also paved the way for future availability of polygenic pharmacogenetic panels to predict treatment outcome, which are expected to explain much higher variance in ADs response compared to CYP2D6 and CYP2C19 only. As the demand and availability of AD pharmacogenetic testing is projected to increase, it is important for clinicians to keep abreast of this evolving area to facilitate informed discussions with their patients.

GSK-3β and BDNF genes may not be associated with venlafaxine treatment response in Chinese of Han ethnicity

PURPOSE

Venlafaxine is one of the commonly prescribed antidepressants for major depressive disorder (MDD). Accumulated evidence revealed the involvement of glutamatergic system in the pathophysiology of MDD and antidepressant treatment.

METHODS

We recruited 193 MDD patients who have been taking venlafaxine for 6 weeks, and investigated whether single nucleotide polymorphisms (SNPs) in GSK-3β and BDNF were associated with treatment response. Nine SNPs were selected randomly depending on association studies. Efficacy of treatment was determined by 17-item Hamilton Rating Scale. Allele and genotype frequencies were compared between responders and nonresponders.

RESULTS

After adjusting the false discovery rate, no significant difference was observed between response and nonresponse groups in allele or genotype distributions after venlafaxine treatment for 6 weeks.

CONCLUSION

Our results indicated that genetic variants in the GSK-3β and BDNF may not be associated with treatment response in MDD patients treated with venlafaxine.

Genetic variants in major depressive disorder: From pathophysiology to therapy

In spite of promising preclinical results there is a decreasing number of new registered medications in major depression. The main reason behind this fact is the lack of confirmation in clinical studies for the assumed, and in animals confirmed, therapeutic results. This suggests low predictive value of animal studies for central nervous system disorders. One solution for identifying new possible targets is the application of genetics and genomics, which may pinpoint new targets based on the effect of genetic variants in humans. The present review summarizes such research focusing on depression and its therapy. The inconsistency between most genetic studies in depression suggests, first of all, a significant role of environmental stress. Furthermore, effect of individual genes and polymorphisms is weak, therefore gene x gene interactions or complete biochemical pathways should be analyzed. Even genes encoding target proteins of currently used antidepressants remain non-significant in genome-wide case control investigations suggesting no main effect in depression, but rather an interaction with stress. The few significant genes in GWASs are related to neurogenesis, neuronal synapse, cell contact and DNA transcription and as being nonspecific for depression are difficult to harvest pharmacologically. Most candidate genes in replicable gene x environment interactions, on the other hand, are connected to the regulation of stress and the HPA axis and thus could serve as drug targets for depression subgroups characterized by stress-sensitivity and anxiety while other risk polymorphisms such as those related to prominent cognitive symptoms in depression may help to identify additional subgroups and their distinct treatment. Until these new targets find their way into therapy, the optimization of current medications can be approached by pharmacogenomics, where metabolizing enzyme polymorphisms remain prominent determinants of therapeutic success.

Low-frequency and rare variants may contribute to elucidate the genetics of major depressive disorder

Major depressive disorder (MDD) is a common but serious psychiatric disorder with significant levels of morbidity and mortality. Recent genome-wide association studies (GWAS) on common variants increase our understanding of MDD; however, the underlying genetic basis remains largely unknown. Many studies have been proposed to explore the genetics of complex diseases from a viewpoint of the "missing heritability" by considering low-frequency and rare variants, copy-number variations, and other types of genetic variants. Here we developed a novel computational and statistical strategy to investigate the "missing heritability" of MDD. We applied Hamming distance on common, low-frequency, and rare single-nucleotide polymorphism (SNP) sets to measure genetic distance between two individuals, and then built the multi-dimensional scaling (MDS) pictures. Whole-exome genotyping data from a Los Angeles Mexican-American cohort (203 MDD and 196 controls) and a European-ancestry cohort (473 MDD and 497 controls) were examined using our proposed methodology. MDS plots showed very significant separations between MDD cases and healthy controls for low-frequency SNP set (P value < 2.2e-16) and rare SNP set (P value = 7.681e-12). Our results suggested that low-frequency and rare variants may play more significant roles in the genetics of MDD.

The antidepressant fluoxetine acts on energy balance and leptin sensitivity via BDNF

Leptin and Brain Derived Neurotrophic Factor (BDNF) pathways are critical players in body weight homeostasis. Noninvasive treatments like environmental stimulation are able to increase response to leptin and induce BDNF expression in the brain. Emerging evidences point to the antidepressant selective serotonin reuptake inhibitor Fluoxetine (FLX) as a drug with effects similar to environmental stimulation. FLX is known to impact on body weight, with mechanisms yet to be elucidated. We herein asked whether FLX affects energy balance, the leptin system and BDNF function. Adult lean male mice chronically treated with FLX showed reduced weight gain, higher energy expenditure, increased sensitivity to acute leptin, increased hypothalamic BDNF expression, associated to changes in white adipose tissue expression typical of “brownization”. In the Ntrk2^tm1Ddg/J model, carrying a mutation in the BDNF receptor Tyrosine kinase B (TrkB), these effects are partially or totally reversed. Wild type obese mice treated with FLX showed reduced weight gain, increased energy output, and differently from untreated obese mice, a preserved acute response to leptin in terms of activation of the intracellular leptin transducer STAT3. In conclusion, FLX impacts on energy balance and induces leptin sensitivity and an intact TrkB function is required for these effects to take place.

Investigation of copy number variation in subjects with major depression based on whole-genome sequencing data

BACKGROUND

Despite recent intensive research using genome-wide association studies, the underlying biological basis of major depressive disorder (MDD) still remains unknown. In contrast to genotyping platforms which identify specific variations, whole-genome sequencing (WGS) allows us to detect all private genetic variations within an individual. So far there have been no studies investigating copy number variations (CNVs) in subjects with MDD using WGS data.

METHODS

We obtained complete WGS paired-end reads data of 15 MDD patients and 10 ethnically matched healthy controls. We performed alignments for the sequencing reads and used GASV package to call CNVs including deletion, inversion, translocation and divergence for those subjects.

RESULTS

Our results show that, in the Mexican-American sample, deletion CNVs were significantly richer in MDD cases than healthy controls on each of 23 chromosomes. However, other types of CNVs failed to reach any significance. In the Australian sample, there was no statistically significant difference of CNVs between MDD cases and controls. Furthermore, we found that the Australian group had significantly more deletion CNVs than the Mexican-American group.

LIMITATIONS

High quality WGS costs limited obtaining larger datasets. The GASV package does not currently support duplication or insertion CNVs.

CONCLUSIONS

To our knowledge this is the first time that CNVs detected by WGS data are used to study major depression. The conclusion that deletion CNVs are significantly richer in MDD cases than healthy controls is consistent with the previous finding about recurrent depressive disorder by genome-wide association analysis of CNVs on a large genotyping microarray data.

Personalized prescribing: a new medical model for clinical implementation of psychotropic drugs

The use of pharmacogenetic tests was already being proposed in psychiatry in the early 2000s because genetic factors were known to influence drug pharmacokinetics and pharmacodynamics. However, sufficient levels of evidence to justify routine use have been achieved for only a few tests (eg, major histocompatibility complex, class I, B, allele 1502 [HLA-B*1502] for carbamazepine in epilepsy and bipolar disorders); many findings are too preliminary or, when replicated, of low clinical relevance because of a small effect size. Although drug selection and dose adaptation according to cytochrome P450 genotypes are sound, a large number of patients need to be genotyped in order to prevent one case of severe side effect and/or nonresponse. The decrease in cost for genetic analysis shifts the cost: benefit ratio toward increasing use of pharmacogenetic tests. However, they have to be combined with careful clinical evaluations and other tools (eg, therapeutic drug monitoring and phenotyping) to contribute to the general aim of providing the best care for psychiatric patients.

The PHF21B gene is associated with major depression and modulates the stress response

Major depressive disorder (MDD) affects around 350 million people worldwide; however, the underlying genetic basis remains largely unknown. In this study, we took into account that MDD is a gene-environment disorder, in which stress is a critical component, and used whole-genome screening of functional variants to investigate the 'missing heritability' in MDD. Genome-wide association studies (GWAS) using single- and multi-locus linear mixed-effect models were performed in a Los Angeles Mexican-American cohort (196 controls, 203 MDD) and in a replication European-ancestry cohort (499 controls, 473 MDD). Our analyses took into consideration the stress levels in the control populations. The Mexican-American controls, comprised primarily of recent immigrants, had high levels of stress due to acculturation issues and the European-ancestry controls with high stress levels were given higher weights in our analysis. We identified 44 common and rare functional variants associated with mild to moderate MDD in the Mexican-American cohort (genome-wide false discovery rate, FDR, <0.05), and their pathway analysis revealed that the three top overrepresented Gene Ontology (GO) processes were innate immune response, glutamate receptor signaling and detection of chemical stimulus in smell sensory perception. Rare variant analysis replicated the association of the PHF21B gene in the ethnically unrelated European-ancestry cohort. The TRPM2 gene, previously implicated in mood disorders, may also be considered replicated by our analyses. Whole-genome sequencing analyses of a subset of the cohorts revealed that European-ancestry individuals have a significantly reduced (50%) number of single nucleotide variants compared with Mexican-American individuals, and for this reason the role of rare variants may vary across populations. PHF21b variants contribute significantly to differences in the levels of expression of this gene in several brain areas, including the hippocampus. Furthermore, using an animal model of stress, we found that Phf21b hippocampal gene expression is significantly decreased in animals resilient to chronic restraint stress when compared with non-chronically stressed animals. Together, our results reveal that including stress level data enables the identification of novel rare functional variants associated with MDD.

Whole-genome single nucleotide variant distribution on genomic regions and its relationship to major depression

Recent advances in DNA technologies have provided unprecedented opportunities for biological and medical research. In contrast to current popular genotyping platforms which identify specific variations, whole-genome sequencing (WGS) allows for the detection of all private mutations within an individual. Major depressive disorder (MDD) is a chronic condition with enormous medical, social and economic impacts. Genetic analysis, by identifying risk variants and thereby increasing our understanding of how MDD arises, could lead to improved prevention and the development of new and more effective treatments. Here we investigated the distributions of whole-genome single nucleotide variants (SNVs) on 12 different genomic regions for 25 human subjects using the symmetrised Kullback-Leibler divergence to measure the similarity between their SNV distributions. We performed cluster analysis for MDD patients and ethnically matched healthy controls. The results showed that Mexican-American controls grouped closer; in contrast depressed Mexican-American participants grouped away from their ethnically matched controls. This implies that whole-genome SNV distribution on the genomic regions may be related to major depression.

A latent genetic subtype of major depression identified by whole-exome genotyping data in a Mexican-American cohort

Identifying data-driven subtypes of major depressive disorder (MDD) is an important topic of psychiatric research. Currently, MDD subtypes are based on clinically defined depression symptom patterns. Although a few data-driven attempts have been made to identify more homogenous subgroups within MDD, other studies have not focused on using human genetic data for MDD subtyping. Here we used a computational strategy to identify MDD subtypes based on single-nucleotide polymorphism genotyping data from MDD cases and controls using Hamming distance and cluster analysis. We examined a cohort of Mexican-American participants from Los Angeles, including MDD patients (n=203) and healthy controls (n=196). The results in cluster trees indicate that a significant latent subtype exists in the Mexican-American MDD group. The individuals in this hidden subtype have increased common genetic substrates related to major depression and they also have more anxiety and less middle insomnia, depersonalization and derealisation, and paranoid symptoms. Advances in this line of research to validate this strategy in other patient groups of different ethnicities will have the potential to eventually be translated to clinical practice, with the tantalising possibility that in the future it may be possible to refine MDD diagnosis based on genetic data.

A novel strategy for clustering major depression individuals using whole-genome sequencing variant data

Major depressive disorder (MDD) is highly prevalent, resulting in an exceedingly high disease burden. The identification of generic risk factors could lead to advance prevention and therapeutics. Current approaches examine genotyping data to identify specific variations between cases and controls. Compared to genotyping, whole-genome sequencing (WGS) allows for the detection of private mutations. In this proof-of-concept study, we establish a conceptually novel computational approach that clusters subjects based on the entirety of their WGS. Those clusters predicted MDD diagnosis. This strategy yielded encouraging results, showing that depressed Mexican-American participants were grouped closer; in contrast ethnically-matched controls grouped away from MDD patients. This implies that within the same ancestry, the WGS data of an individual can be used to check whether this individual is within or closer to MDD subjects or to controls. We propose a novel strategy to apply WGS data to clinical medicine by facilitating diagnosis through genetic clustering. Further studies utilising our method should examine larger WGS datasets on other ethnical groups.

Single-nucleotide variant proportion in genes: a new concept to explore major depression based on DNA sequencing data

Major depressive disorder (MDD) is a common psychiatric illness with significant medical and socioeconomic impact. Genetic factors are likely to play important roles in the development of this condition. DNA sequencing technology has the ability to identify all private genetic mutations and provides new channels for studying the biology of MDD. In this proof-of-concept study we proposed a novel concept, single-nucleotide variant proportion (SNVP), to investigate MDD based on whole-genome sequencing (WGS) data. Our SNVP-based approach can be used to test newly found candidate genes as a complement to genome-wide genotyping analysis. Furthermore, we performed cluster analysis for MDD patients and ethnically matched healthy controls, and found that clusters based on SNVP may predict MDD diagnosis. Our results suggest that SNVP may be used as a potential biomarker associated with major depression. Our methodology could be a valuable predictive/diagnostic tool as one can test whether a new subject falls within or close to an existing MDD cluster. Advances in this study design have the potential to personalized treatments and could include the ability to diagnose patients based on their full or part DNA sequencing data.

Linkage and association analysis of ADHD endophenotypes in extended and multigenerational pedigrees from a genetic isolate

Attention-deficit/hyperactivity disorder (ADHD) is a heritable, chronic, neurodevelopmental disorder with serious long-term repercussions. Despite being one of the most common cognitive disorders, the clinical diagnosis of ADHD is based on subjective assessments of perceived behaviors. Endophenotypes (neurobiological markers that cosegregate and are associated with an illness) are thought to provide a more powerful and objective framework for revealing the underlying neurobiology than syndromic psychiatric classification. Here, we present the results of applying genetic linkage and association analyses to neuropsychological endophenotypes using microsatellite and single nucleotide polymorphisms. We found several new genetic regions linked and/or associated with these endophenotypes, and others previously associated to ADHD, for example, loci harbored in the LPHN3, FGF1, POLR2A, CHRNA4 and ANKFY1 genes. These findings, when compared with those linked and/or associated to ADHD, suggest that these endophenotypes lie on shared pathways. The genetic information provided by this study offers a novel and complementary method of assessing the genetic causes underpinning the susceptibility to behavioral conditions and may offer new insights on the neurobiology of the disorder.

APOE*E2 allele delays age of onset in PSEN1 E280A Alzheimer's disease

Alzheimer's disease (AD) age of onset (ADAOO) varies greatly between individuals, with unique causal mutations suggesting the role of modifying genetic and environmental interactions. We analyzed ~50 000 common and rare functional genomic variants from 71 individuals of the 'Paisa' pedigree, the world's largest pedigree segregating a severe form of early-onset AD, who were affected carriers of the fully penetrant E280A mutation in the presenilin-1 (PSEN1) gene. Affected carriers with ages at the extremes of the ADAOO distribution (30s-70s age range), and linear mixed-effects models were used to build single-locus regression models outlining the ADAOO. We identified the rs7412 (APOE*E2 allele) as a whole exome-wide ADAOO modifier that delays ADAOO by ~12 years (β=11.74, 95% confidence interval (CI): 8.07-15.41, P=6.31 × 10(-8), PFDR=2.48 × 10(-3)). Subsequently, to evaluate comprehensively the APOE (apolipoprotein E) haplotype variants (E1/E2/E3/E4), the markers rs7412 and rs429358 were genotyped in 93 AD affected carriers of the E280A mutation. We found that the APOE*E2 allele, and not APOE*E4, modifies ADAOO in carriers of the E280A mutation (β=8.24, 95% CI: 4.45-12.01, P=3.84 × 10(-5)). Exploratory linear mixed-effects multilocus analysis suggested that other functional variants harbored in genes involved in cell proliferation, protein degradation, apoptotic and immune dysregulation processes (i.e., GPR20, TRIM22, FCRL5, AOAH, PINLYP, IFI16, RC3H1 and DFNA5) might interact with the APOE*E2 allele. Interestingly, suggestive evidence as an ADAOO modifier was found for one of these variants (GPR20) in a set of patients with sporadic AD from the Paisa genetic isolate. This is the first study demonstrating that the APOE*E2 allele modifies the natural history of AD typified by the age of onset in E280A mutation carriers. To the best of our knowledge, this is the largest analyzed sample of patients with a unique mutation sharing uniform environment. Formal replication of our results in other populations and in other forms of AD will be crucial for prediction, follow-up and presumably developing new therapeutic strategies for patients either at risk or affected by AD.

BDNF/TRKB/P75NTR polymorphisms and their consequences on antidepressant efficacy in depressed patients

We propose an extensive review of the literature about BDNF/TRKB/P75NTR polymorphisms and their consequences on antidepressant efficacy in depressed patients. Five genome-wide association studies and 30 association studies were included. Twenty seven studies focused on the Val66Met polymorphism (rs6265), the Met allele being associated with a higher antidepressant efficacy only in Asian patients. Other BDNF/TRKB/P75NTR polymorphisms (BDNF: rs7103411, rs7124442, rs908867, rs2049046, rs61888800, rs10501087, rs1491850; TRKB: rs10868223, rs11140778, rs1565445, rs1659412; P75NTR: rs2072446) were reported to be associated with antidepressant efficacy but these results were not replicated. Finally, there are 15 positive studies among 30 studies regarding BDNF/TRKB/P75NTR polymorphisms. The only SNP which benefits of at least three positive studies is the BDNF Val66Met polymorphism (rs6265). Consequently, with a lack of good and consistent studies, the clinical utility of BDNF in treatment selection is far from clear. We propose several recommendations for further studies.