GxE interaction effects of HCRTR2 single nucleotide polymorphism and adverse childhood experiences on methamphetamine use disorder.

Background: Methamphetamine use disorder (MUD) is a worldwide health concern. The hypothalamic orexin system regulates stress response and addictive behaviors. The genetic variation in the hypocretin receptor 2 (HCRTR2), rs2653349, is associated with substance use disorder.Objectives: We explored the gene-environment (GxE) interaction of rs2653349 and adverse childhood experiences (ACEs) associated with MUD susceptibility.Methods: Four hundred and one individuals (336 males, 65 females) with MUD and 348 healthy controls (288 males, 60 females) completed a self-report questionnaire evaluating ACEs, encompassing childhood abuse and household dysfunction categories, and were genotyped for SNP rs2653349. Methamphetamine use variables were collected using the Diagnostic Interview for Genetic Studies. We used regression analyses to assess the GxE effect on MUD risk.Results: The MUD group had a comparable genotypic distribution for rs2653349 to the control group, albeit with a higher prevalence and number of types of ACEs, correlating with an increased MUD risk (p < .05). No significant genetic impact of rs2653349 on MUD risk was found. However, we observed a GxE interaction effect between the minor allele of rs2653349 and the number of childhood abuse or household dysfunction types, correlating with a reduced MUD risk (OR = -0.71, p = .04, Benjamini-Hochberg adjusted p = .08 and OR = -0.59, p = .045, Benjamini-Hochberg adjusted p = .09, respectively).Conclusion: HCRTR2 SNP rs2653349 has no significant impact on MUD risk, but ACEs may increase this risk. GxE results suggest that rs2653349 could offer protection against developing MUD in individuals experiencing multiple types of ACEs.

Treatment response to low-dose ketamine infusion for treatment-resistant depression: A gene-based genome-wide association study.

BACKGROUNDS: Evidence suggested the crucial roles of brain-derived neurotrophic factor (BDNF) and glutamate system functioning in the antidepressant mechanisms of low-dose ketamine infusion in treatment-resistant depression (TRD). METHODS: 65 patients with TRD were genotyped for 684,616 single nucleotide polymorphisms (SNPs). Twelve ketamine-related genes were selected for the gene-based genome-wide association study on the antidepressant effect of ketamine infusion and the resulting serum ketamine and norketamine levels. RESULTS: Specific SNPs and whole genes involved in BDNF-TrkB signaling (i.e., rs2049048 in BDNF and rs10217777 in NTRK2) and the glutamatergic and GABAergic systems (i.e., rs16966731 in GRIN2A) were associated with the rapid (within 240 min) and persistent (up to 2 weeks) antidepressant effect of low-dose ketamine infusion and with serum ketamine and norketamine levels. DISCUSSION: Our findings confirmed the predictive roles of BDNF-TrkB signaling and glutamatergic and GABAergic systems in the underlying mechanisms of low-dose ketamine infusion for TRD treatment.

Orexin-A Levels in Relation to the Risk of Metabolic Syndrome in Patients with Schizophrenia Taking Antipsychotics.

Background: The role of orexin-A in regulating metabolic homeostasis has been recognized, but its association with antipsychotic-induced metabolic abnormalities remains unclear. We investigated the association between orexin-A levels and metabolic syndrome in patients with schizophrenia treated with clozapine or less obesogenic antipsychotics compared with nonpsychiatric controls. Methods: Plasma orexin-A levels and metabolic parameters were determined in 159 patients with schizophrenia: 109 taking clozapine; 50 taking aripiprazole, amisulpride, ziprasidone, or haloperidol; and 60 nonpsychiatric controls. Results: Orexin-A levels were significantly higher in the group taking less obesogenic antipsychotics, followed by the clozapine group and the controls (F=104.6, P<.01). Higher orexin-A levels were correlated with better metabolic profiles in the patient groups but not in the controls. Regression analyses revealed that the patients with higher orexin-A levels had significantly lower risk of metabolic syndrome (adjusted odds ratio [OR]=0.04, 95% CI: 0.01-0.38 for the 2nd tertile; OR=0.04, 95% CI: 0.01-0.36 for the 3rd tertile, compared with the first tertile), after adjustment for age, sex, smoking history, types of antipsychotics (clozapine vs less obesogenic antipsychotics), duration of antipsychotic treatment, and disease severity. Conclusions: Our results revealed that the orexin-A level was upregulated in patients with schizophrenia treated with antipsychotics, especially for the group taking less obesogenic antipsychotics. Furthermore, higher orexin-A levels were independently associated with better metabolic profiles. These observations suggest that an upregulation of orexin-A has a protective effect against the development of metabolic abnormalities in patients with schizophrenia receiving antipsychotic treatment.

No association of CYP2E1 genetic polymorphisms with alcohol dependence in Han Taiwanese population.

Cytochrome P450 2E1 (CYP2E1) gene is one of the candidate genes for alcohol dependence (AD). Four single nucleotide polymorphisms (SNPs) of CYP2E1 gene (CYP2E1*1D, *5B, *6 and *1B) have been associated with AD previously in other ethnic populations. To date, only CYP2E1*5B and *6 SNPs have been investigated in relation to AD in our population. The objective of the study was to examine the genetic associations of CYP2E1 covering the four above-noted SNPs conjointly with AD in Han Taiwanese population based on single SNP analysis and haplotype-based approach. We enrolled a total of 340 patients fulfilling DSM-IV-TR diagnostic criteria of AD and 319 healthy controls and genotyped them for the above four SNPs of CYP2E1 gene. By comparing the differences of genotype, allele, and pertinent haplotype frequencies, we did not support a genetic association between CYP2E1 and AD in Han Taiwanese either by single allele tests or haplotype-based analyses.

The rs1277306 Variant of the REST Gene Confers Susceptibility to Cognitive Aging in an Elderly Taiwanese Population.

BACKGROUND/AIMS: There is growing evidence that the RE1-silencing transcription factor (REST) gene may contribute to cognitive aging and Alzheimer diseases. In this replication study, we reassessed whether single nucleotide polymorphisms (SNPs) within the REST gene are linked with cognitive aging independently and/or through complex interactions in an older Taiwanese population. METHODS: A total of 634 Taiwanese subjects aged over 60 years from the Taiwan Biobank were analyzed. Mini-Mental State Examination (MMSE) scores were performed for all subjects to weigh cognitive functions. RESULTS: Our data showed that the REST rs1277306 SNP was significantly associated with cognitive aging among all subjects (p = 0.0052). Furthermore, the association remained significant for individuals without APOE ε4 allele (p = 0.0092), but not for individuals with at least 1 APOE ε4 allele. This association remained significant after Bonferroni correction. Additionally, we found the interactions between the rs1713985 and rs1277306 SNPs on cognitive aging (p = 0.016). However, the 3-marker haplotype derived from the rs1713985, rs3796529, and rs7680734 SNPs in the REST gene demonstrated no association with cognitive aging. CONCLUSION: Our study indicates that the REST gene may contribute to susceptibility to cognitive aging independently as well as through SNP-SNP and APOE-REST interactions.

Identification of Susceptible Loci and Enriched Pathways for Bipolar II Disorder Using Genome-Wide Association Studies.

BACKGROUND: This study aimed to identify susceptible loci and enriched pathways for bipolar disorder subtype II. METHODS: We conducted a genome-wide association scan in discovery samples with 189 bipolar disorder subtype II patients and 1773 controls, and replication samples with 283 bipolar disorder subtype II patients and 500 controls in a Taiwanese Han population using Affymetrix Axiom Genome-Wide CHB1 Array. We performed single-marker and gene-based association analyses, as well as calculated polygeneic risk scores for bipolar disorder subtype II. Pathway enrichment analyses were employed to reveal significant biological pathways. RESULTS: Seven markers were found to be associated with bipolar disorder subtype II in meta-analysis combining both discovery and replication samples (P<5.0×10-6), including markers in or close to MYO16, HSP90AB3P, noncoding gene LOC100507632, and markers in chromosomes 4 and 10. A novel locus, ETF1, was associated with bipolar disorder subtype II (P<6.0×10-3) in gene-based association tests. Results of risk evaluation demonstrated that higher genetic risk scores were able to distinguish bipolar disorder subtype II patients from healthy controls in both discovery (P=3.9×10-4~1.0×10-3) and replication samples (2.8×10-4~1.7×10-3). Genetic variance explained by chip markers for bipolar disorder subtype II was substantial in the discovery (55.1%) and replication (60.5%) samples. Moreover, pathways related to neurodevelopmental function, signal transduction, neuronal system, and cell adhesion molecules were significantly associated with bipolar disorder subtype II. CONCLUSION: We reported novel susceptible loci for pure bipolar subtype II disorder that is less addressed in the literature. Future studies are needed to confirm the roles of these loci for bipolar disorder subtype II.

The Relationships of Obesity-Related Genetic Variants With Metabolic Profiles and Response to Metformin in Clozapine-Treated Patients With Schizophrenia.

Obesity-related genetic variants, including TMEM18 (rs6548238), SH2B1 (rs7498665), and GNPDA2 (rs10938397), have been shown to be associated with obesity in the general population. Our study aimed to test whether these genetic variants are associated with metabolic profiles and metformin treatment response in clozapine-treated schizophrenic patients. We recruited 107 clozapine-treated patients who were genotyped and measured their metabolic profiles. Fifty-five subjects, who had at least 1 metabolic abnormality in a range of measures, were subsequently randomized to a 24-week trial of metformin (n = 28) or placebo (n = 27). We examined the associations between TMEM18, SH2B1, GNPDA2 genetic variants and metabolic profiles at baseline in all patients and metabolic changes in the trial groups. We found a significant association between SH2B1 and blood pressure at baseline in all patients. In the metformin group, TMEM18 minor allele carriers had a greater reduction in insulin levels (P = 0.04). A significantly higher proportion of TMEM18 and GNPDA2 minor allele carriers (60% and 40%) lost more than 7% of their body weight after metformin treatment as compared with their homozygous counterparts (21.7% and 15.4%, P = 0.02 and 0.004, respectively).There were trends toward favorable metabolic changes in minor allele carrier groups. In the placebo group, no association between genetic variants and changes in metabolic profiles was found. In conclusion, the study results suggest that these genes might be associated with metabolic abnormalities and response to metformin in clozapine-treated patients with schizophrenia.

Risk and information evaluation of prioritized genes for complex traits: application to bipolar disorder.

Many susceptibility genes for complex traits were identified without conclusive findings. There is a strong need to integrate rapidly accumulated genomic data from multi-dimensional platforms, and to conduct risk evaluation for potential therapeutic and diagnostic usages. We set up an algorithm to computationally search for optimal weight-vector for various data sources, while minimized potential noises. Through gene-prioritization framework, combined scores for the resulting prioritized gene-set were calculated using a genome-wide association (GWA) dataset, following with evaluation using weighted genetic risk score and risk-attributed information using an independent GWA dataset. The significance of association of GWA data was corrected for gene length. Enriched functional pathways were identified for the prioritized gene-set using the Gene Ontology analysis. We illustrated our framework with bipolar disorder. 233 prioritized genes were identified from 10,830 candidates that curated from six platforms. The prioritized genes were significantly enriched (P(adjusted) < 1 × 10(-5)) in 18 biological functions and molecular mechanisms including membrane, synaptic transmission, transmission of nerve impulse, integral to membrane, and plasma membrane. Our risk evaluation demonstrated higher weighted genetic risk score in bipolar patients than controls (P-values ranged from 0.002 to 3.8 × 10(-6)). Substantial risk-information (71%) was extracted from prioritized genes for bipolar illness than other candidate-gene sets. Our evidence-based prioritized gene-set provides opportunity to explore the complex network and to conduct follow-up basic and clinical studies for complex traits.

Integrative pathway and network analysis provide insights on flooding-tolerance genes in soybean.

Soybean is highly sensitive to flooding and extreme rainfall. The phenotypic variation of flooding tolerance is a complex quantitative trait controlled by many genes and their interaction with environmental factors. We previously constructed a gene-pool relevant to soybean flooding-tolerant responses from integrated multiple omics and non-omics databases, and selected 144 prioritized flooding tolerance genes (FTgenes). In this study, we proposed a comprehensive framework at the systems level, using competitive (hypergeometric test) and self-contained (sum-statistic, sum-square-statistic) pathway-based approaches to identify biologically enriched pathways through evaluating the joint effects of the FTgenes within annotated pathways. These FTgenes were significantly enriched in 36 pathways in the Gene Ontology database. These pathways were related to plant hormones, defense-related, primary metabolic process, and system development pathways, which plays key roles in soybean flooding-induced responses. We further identified nine key FTgenes from important subnetworks extracted from several gene networks of enriched pathways. The nine key FTgenes were significantly expressed in soybean root under flooding stress in a qRT-PCR analysis. We demonstrated that this systems biology framework is promising to uncover important key genes underlying the molecular mechanisms of flooding-tolerant responses in soybean. This result supplied a good foundation for gene function analysis in further work.

Cytokine- and Vascular Endothelial Growth Factor-Related Gene-Based Genome-Wide Association Study of Low-Dose Ketamine Infusion in Patients with Treatment-Resistant Depression.

BACKGROUND AND OBJECTIVE: Ketamine may work as an anti-inflammatory agent, and it increases the levels of vascular endothelial growth factor (VEGF) in patients with treatment-resistant depression. However, whether genes related to pro-inflammatory and anti-inflammatory cytokines and VEGF may predict the treatment response to ketamine remains unknown.Therefore the aim of this study was to analyze whether specific genes related to inflammatory processes and VEGF were associated with treatment response to low-dose ketamine in patients with treatment-resistant depression. METHODS: Based on the genome data from our clinical trial, this study was a secondary analysis of candidate genes correlated with different timepoints of depressive symptoms. In total, 65 patients with treatment-resistant depression (n = 21 for ketamine 0.5 mg/kg, 20 for ketamine 0.2 mg/kg, and 24 for normal saline) were genotyped for 684,616 single nucleotide polymorphisms. Genes associated with 80 cytokines (i.e., interleukin [IL]-1, IL-6, tumor necrosis factor-α, and adiponectin) and VEGF (i.e., VEGF and VEGF receptors) were selected for the gene-based genome-wide association study on the antidepressant effect of a ketamine infusion. RESULTS: Specific single nucleotide polymorphisms, including rs2540315 and rs75746675 in IL1R1 and rs79568085 in VEGFC, were related to the rapid (within 240 min) antidepressant effect of a ketamine infusion; specific single nucleotide polymorphisms, such as Affx-20131665 in PIGF and rs8179353, rs8179353, and rs8179353 in TNFRSF8, were associated with the sustained (up to 2 weeks) antidepressant effect of low-dose (combined 0.5 mg/kg and 0.2 mg/kg) ketamine. CONCLUSIONS: Our findings further revealed that genes related to both anti-inflammatory and pro-inflammatory cytokines (i.e., IL-1, IL-2, IL-6, tumor necrosis factor-α, C-reactive protein, and adiponectin) and VEGF-FLK signaling predicted the treatment response to a ketamine infusion in patients with treatment-resistant depression. The synergic modulation of inflammatory and VEGF systems may contribute to the antidepressant effect of ketamine. CLINICAL TRIAL REGISTRATION: University Hospital Medical Information Network Clinical Trials Registry (UMIN-CTR) number: UMIN000016985.

Enriched pathways for major depressive disorder identified from a genome-wide association study.

Major depressive disorder (MDD) has caused a substantial burden of disease worldwide with moderate heritability. Despite efforts through conducting numerous association studies and now, genome-wide association (GWA) studies, the success of identifying susceptibility loci for MDD has been limited, which is partially attributed to the complex nature of depression pathogenesis. A pathway-based analytic strategy to investigate the joint effects of various genes within specific biological pathways has emerged as a powerful tool for complex traits. The present study aimed to identify enriched pathways for depression using a GWA dataset for MDD. For each gene, we estimated its gene-wise p value using combined and minimum p value, separately. Canonical pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG) and BioCarta were used. We employed four pathway-based analytic approaches (gene set enrichment analysis, hypergeometric test, sum-square statistic, sum-statistic). We adjusted for multiple testing using Benjamini & Hochberg's method to report significant pathways. We found 17 significantly enriched pathways for depression, which presented low-to-intermediate crosstalk. The top four pathways were long-term depression (p⩽1×10-5), calcium signalling (p⩽6×10-5), arrhythmogenic right ventricular cardiomyopathy (p⩽1.6×10-4) and cell adhesion molecules (p⩽2.2×10-4). In conclusion, our comprehensive pathway analyses identified promising pathways for depression that are related to neurotransmitter and neuronal systems, immune system and inflammatory response, which may be involved in the pathophysiological mechanisms underlying depression. We demonstrated that pathway enrichment analysis is promising to facilitate our understanding of complex traits through a deeper interpretation of GWA data. Application of this comprehensive analytic strategy in upcoming GWA data for depression could validate the findings reported in this study.

An advanced systems biology framework of feature engineering for cold tolerance genes discovery from integrated omics and non-omics data in soybean.

Soybean is sensitive to low temperatures during the crop growing season. An urgent demand for breeding cold-tolerant cultivars to alleviate the production loss is apparent to cope with this scenario. Cold-tolerant trait is a complex and quantitative trait controlled by multiple genes, environmental factors, and their interaction. In this study, we proposed an advanced systems biology framework of feature engineering for the discovery of cold tolerance genes (CTgenes) from integrated omics and non-omics (OnO) data in soybean. An integrative pipeline was introduced for feature selection and feature extraction from different layers in the integrated OnO data using data ensemble methods and the non-parameter random forest prioritization to minimize uncertainties and false positives for accuracy improvement of results. In total, 44, 143, and 45 CTgenes were identified in short-, mid-, and long-term cold treatment, respectively, from the corresponding gene-pool. These CTgenes outperformed the remaining genes, the random genes, and the other candidate genes identified by other approaches in an independent RNA-seq database. Furthermore, we applied pathway enrichment and crosstalk network analyses to uncover relevant physiological pathways with the discovery of underlying cold tolerance in hormone- and defense-related modules. Our CTgenes were validated by using 55 SNP genotype data of 56 soybean samples in cold tolerance experiments. This suggests that the CTgenes identified from our proposed systematic framework can effectively distinguish cold-resistant and cold-sensitive lines. It is an important advancement in the soybean cold-stress response. The proposed pipelines provide an alternative solution to biomarker discovery, module discovery, and sample classification underlying a particular trait in plants in a robust and efficient way.

A multiple phenotype imputation method for genetic diversity and core collection in Taiwanese vegetable soybean.

Establishment of vegetable soybean (edamame) [Glycine max (L.) Merr.] germplasms has been highly valued in Asia and the United States owing to the increasing market demand for edamame. The idea of core collection (CC) is to shorten the breeding program so as to improve the availability of germplasm resources. However, multidimensional phenotypes typically are highly correlated and have different levels of missing rate, often failing to capture the underlying pattern of germplasms and select CC precisely. These are commonly observed on correlated samples. To overcome such scenario, we introduced the "multiple imputation" (MI) method to iteratively impute missing phenotypes for 46 morphological traits and jointly analyzed high-dimensional imputed missing phenotypes (EC impu ) to explore population structure and relatedness among 200 Taiwanese vegetable soybean accessions. An advanced maximization strategy with a heuristic algorithm and PowerCore was used to evaluate the morphological diversity among the EC impu . In total, 36 accessions (denoted as CC impu ) were efficiently selected representing high diversity and the entire coverage of the EC impu . Only 4 (8.7%) traits showed slightly significant differences between the CC impu and EC impu . Compared to the EC impu , 96% traits retained all characteristics or had a slight diversity loss in the CC impu . The CC impu exhibited a small percentage of significant mean difference (4.51%), and large coincidence rate (98.1%), variable rate (138.76%), and coverage (close to 100%), indicating the representativeness of the EC impu . We noted that the CC impu outperformed the CC raw in evaluation properties, suggesting that the multiple phenotype imputation method has the potential to deal with missing phenotypes in correlated samples efficiently and reliably without re-phenotyping accessions. Our results illustrated a significant role of imputed missing phenotypes in support of the MI-based framework for plant-breeding programs.

Polymorphisms of INSIG2, MC4R, and LEP are associated with obesity- and metabolic-related traits in schizophrenic patients.

BACKGROUND: Schizophrenic patients have a high prevalence of metabolic adversities. Previous studies have suggested some candidate genes for obesity- and metabolic-related traits, including the insulin-induced gene (INSIG2), melanocortin 4 receptor gene (MC4R), and leptin and leptin receptor genes (LEP and LEPR). We aimed to investigate the associations between these genes and metabolic disturbances in patients with schizophrenia in Taiwan. METHODS: Patients with a diagnosis of schizophrenia or schizoaffective disorder according to the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, were recruited from 36 community psychiatric rehabilitation centers or hospitals in Taipei. A total of 650 subjects were enrolled, and 577 were included in the genetic analyses. The anthropometric (body mass index, waist circumference [WC], and blood pressure) and biochemical measurements (fasting plasma glucose, insulin, triglyceride, high-density lipoprotein cholesterol, and Homeostasis Model of Assessment - Insulin Resistance index [HOMA-IR]) were assessed. Seven loci in the 4 genes were genotyped using standard TaqMan assays. Genetic association analyses were conducted for binary and quantitative measurements of the previously mentioned traits. Obese patients with schizophrenia exhibited more metabolic disturbances than nonobese patients. RESULTS AND CONCLUSIONS: Our data showed that INSIG2 was significantly associated with fasting plasma glucose (for rs17587100, P < 0.0001), MC4R was associated with WC (for rs2229616, P = 0.005), and LEP was associated with body mass index and WC (for rs7799039, P < 0.01). In addition, these loci showed suggestive associations with traits including high-density lipoprotein cholesterol and triglyceride, metabolic syndrome, insulin level, and HOMA-IR index (P = 0.05). In addition to the effect from antipsychotic medications and an unhealthy lifestyle, genetic factors also contribute to the high prevalence of obesity and metabolic disturbances in patients with schizophrenia, especially genes involved in metabolic-related pathways.

Differences in serum orexin-A levels between the acute and subacute withdrawal phases in individuals who use methamphetamine.

Orexin has been suggested to play a role in regulating the reward circuits and enhancing drug-seeking behaviors; however, its role in methamphetamine (METH) addiction remains unclear. We previously found that blood orexin-A levels are upregulated in individuals with recent METH exposure. Whether the levels would be altered following withdrawal is unknown. In this study, we compared the levels of serum orexin-A in individuals who use METH between the acute withdrawal (AW) phase and the subacute withdrawal (SAW) phase at baseline (T1) and examined the alterations in these levels after 2 weeks of abstinence (T2). In total, 60 participants (51 men and 9 women) were enrolled in the study; 20 participants with METH-positive urine test results were included in the AW group, and 40 participants with METH-negative urine test results who had self-reportedly last taken METH within the preceding 1-2 months were included in the SAW group. Serum orexin-A levels were measured using enzyme-linked immunosorbent assay. No significant differences in orexin-A levels were observed between the AW and SAW groups at baseline (p = .06). After 2 additional weeks of abstinence, the levels decreased significantly in the SAW group (0.58 ± 0.13 ng/mL) but not in the AW group (0.50 ± 0.14 ng/mL, p = .004). Our results demonstrated that orexin-A levels might decrease after a longer period of METH withdrawal, indicating that the orexin system is dysregulated in the addictive process of METH. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Genetic Pathways and Functional Subnetworks for the Complex Nature of Bipolar Disorder in Genome-Wide Association Study.

Bipolar disorder is a complex psychiatric trait that is also recognized as a high substantial heritability from a worldwide distribution. The success in identifying susceptibility loci for bipolar disorder (BPD) has been limited due to its complex genetic architecture. Growing evidence from association studies including genome-wide association (GWA) studies points to the need of improved analytic strategies to pinpoint the missing heritability for BPD. More importantly, many studies indicate that BPD has a strong association with dementia. We conducted advanced pathway analytics strategies to investigate synergistic effects of multilocus within biologically functional pathways, and further demonstrated functional effects among proteins in subnetworks to examine mechanisms underlying the complex nature of bipolarity using a GWA dataset for BPD. We allowed bipolar susceptible loci to play a role that takes larger weights in pathway-based analytic approaches. Having significantly informative genes identified from enriched pathways, we further built function-specific subnetworks of protein interactions using MetaCore. The gene-wise scores (i.e., minimum p-value) were corrected for the gene-length, and the results were corrected for multiple tests using Benjamini and Hochberg's method. We found 87 enriched pathways that are significant for BPD; of which 36 pathways were reported. Most of them are involved with several metabolic processes, neural systems, immune system, molecular transport, cellular communication, and signal transduction. Three significant and function-related subnetworks with multiple hotspots were reported to link with several Gene Ontology processes for BPD. Our comprehensive pathway-network frameworks demonstrated that the use of prior knowledge is promising to facilitate our understanding between complex psychiatric disorders (e.g., BPD) and dementia for the access to the connection and clinical implications, along with the development and progression of dementia.

A Modified Roger's Distance Algorithm for Mixed Quantitative-Qualitative Phenotypes to Establish a Core Collection for Taiwanese Vegetable Soybeans.

Vegetable soybeans [Glycine max (L.) Merr.] have characteristics of larger seeds, less beany flavor, tender texture, and green-colored pods and seeds. Rich in nutrients, vegetable soybeans are conducive to preventing neurological disease. Due to the change of dietary habits and increasing health awareness, the demand for vegetable soybeans has increased. To conserve vegetable soybean germplasms in Taiwan, we built a core collection of vegetable soybeans, with minimum accessions, minimum redundancy, and maximum representation. Initially, a total of 213 vegetable soybean germplasms and 29 morphological traits were used to construct the core collection. After redundant accessions were removed, 200 accessions were retained as the entire collection, which was grouped into nine clusters. Here, we developed a modified Roger's distance for mixed quantitative-qualitative phenotypes to select 30 accessions (denoted as the core collection) that had a maximum pairwise genetic distance. No significant differences were observed in all phenotypic traits (p-values > 0.05) between the entire and the core collections, except plant height. Compared to the entire collection, we found that most traits retained diversities, but seven traits were slightly lost (ranged from 2 to 9%) in the core collection. The core collection demonstrated a small percentage of significant mean difference (3.45%) and a large coincidence rate (97.70%), indicating representativeness of the entire collection. Furthermore, large values in variable rate (149.80%) and coverage (92.5%) were in line with high diversity retained in the core collection. The results suggested that phenotype-based core collection can retain diversity and genetic variability of vegetable soybeans, providing a basis for further research and breeding programs.

Gene-Based Association Analysis Suggests Association of HTR2A With Antidepressant Treatment Response in Depressed Patients.

The serotonin [5-hydroxytryptamine (5-HT)] system has been implicated in the pathogenesis of major depressive disorder (MDD). Among the 5-HT receptor subtypes, 5-HT2 is one of the major pharmacological therapeutic targets for MDD. There have been inconsistent findings in previous pharmacogenetic studies investigating the antidepressant therapeutic response using one or several 5-HT2A (HTR2A) genetic polymorphisms. By using gene-based association analysis, we hope to identify genetic variants of HTR2A which are related to MDD susceptibility and its antidepressant therapeutic response. 288 HTR2A single nucleotide polymorphisms in MDD susceptibility have been investigated through a case-control (455 MDD patients and 2, 998 healthy controls) study, as well as in antidepressant efficacy (n = 455) in our current research. The 21-item Hamilton Rating Scale for Depression was used to evaluate measures of antidepressant therapeutic efficacy. From two MDD groups in the antidepressant therapeutic response, by using gene-based analyses, we have identified 14 polymorphisms as suggestive markers for therapeutic response (13 for remission and 1 for response) in both meta- and mega-analyses. All of these HTR2A reported polymorphisms did not reach statistical significance in the case-control association study. This current investigation supported the link between HTR2A variants and antidepressant therapeutic response in MDD but not with MDD susceptibility.

Prioritization and Evaluation of Flooding Tolerance Genes in Soybean [Glycine max (L.) Merr.].

Soybean [Glycine max (L.) Merr.] is one of the most important legume crops abundant in edible protein and oil in the world. In recent years there has been increasingly more drastic weather caused by climate change, with flooding, drought, and unevenly distributed rainfall gradually increasing in terms of the frequency and intensity worldwide. Severe flooding has caused extensive losses to soybean production and there is an urgent need to breed strong soybean seeds with high flooding tolerance. The present study demonstrates bioinformatics big data mining and integration, meta-analysis, gene mapping, gene prioritization, and systems biology for identifying prioritized genes of flooding tolerance in soybean. A total of 83 flooding tolerance genes (FTgenes), according to the appropriate cut-off point, were prioritized from 36,705 test genes collected from multidimensional genomic features linking to soybean flooding tolerance. Several validation results using independent samples from SoyNet, genome-wide association study, SoyBase, GO database, and transcriptome databases all exhibited excellent agreement, suggesting these 83 FTgenes were significantly superior to others. These results provide valuable information and contribution to research on the varieties selection of soybean.