GNN4DM: a graph neural network-based method to identify overlapping functional disease modules.

MOTIVATION: Identifying disease modules within molecular interaction networks is an essential exploratory step in computational biology, offering insights into disease mechanisms and potential therapeutic targets. Traditional methods often struggle with the inherent complexity and overlapping nature of biological networks, and they are limited in effectively leveraging the vast amount of available genomic data and biological knowledge. This limitation underscores the need for more effective, automated approaches to integrate these rich data sources. RESULTS: In this work, we propose GNN4DM, a novel graph neural network-based structured model that automates the discovery of overlapping functional disease modules. GNN4DM effectively integrates network topology with genomic data to learn the representations of the genes corresponding to functional modules and align these with known biological pathways for enhanced interpretability. Following the DREAM benchmark evaluation setting and extending with three independent data sources (GWAS Atlas, FinnGen, and DisGeNET), we show that GNN4DM performs better than several state-of-the-art methods in detecting biologically meaningful modules. Moreover, we demonstrate the method's applicability by discovering two novel multimorbidity modules significantly enriched across a diverse range of seemingly unrelated diseases. AVAILABILITY AND IMPLEMENTATION: Source code, all training data, and all identified disease modules are freely available for download at https://github.com/gezsi/gnn4dm. GNN4DM was implemented in Python.

Multicentric Assessment of a Multimorbidity-Adjusted Disability Score to Stratify Depression-Related Risks Using Temporal Disease Maps: Instrument Validation Study.

BACKGROUND: Comprehensive management of multimorbidity can significantly benefit from advanced health risk assessment tools that facilitate value-based interventions, allowing for the assessment and prediction of disease progression. Our study proposes a novel methodology, the Multimorbidity-Adjusted Disability Score (MADS), which integrates disease trajectory methodologies with advanced techniques for assessing interdependencies among concurrent diseases. This approach is designed to better assess the clinical burden of clusters of interrelated diseases and enhance our ability to anticipate disease progression, thereby potentially informing targeted preventive care interventions. OBJECTIVE: This study aims to evaluate the effectiveness of the MADS in stratifying patients into clinically relevant risk groups based on their multimorbidity profiles, which accurately reflect their clinical complexity and the probabilities of developing new associated disease conditions. METHODS: In a retrospective multicentric cohort study, we developed the MADS by analyzing disease trajectories and applying Bayesian statistics to determine disease-disease probabilities combined with well-established disability weights. We used major depressive disorder (MDD) as a primary case study for this evaluation. We stratified patients into different risk levels corresponding to different percentiles of MADS distribution. We statistically assessed the association of MADS risk strata with mortality, health care resource use, and disease progression across 1 million individuals from Spain, the United Kingdom, and Finland. RESULTS: The results revealed significantly different distributions of the assessed outcomes across the MADS risk tiers, including mortality rates; primary care visits; specialized care outpatient consultations; visits in mental health specialized centers; emergency room visits; hospitalizations; pharmacological and nonpharmacological expenditures; and dispensation of antipsychotics, anxiolytics, sedatives, and antidepressants (P<.001 in all cases). Moreover, the results of the pairwise comparisons between adjacent risk tiers illustrate a substantial and gradual pattern of increased mortality rate, heightened health care use, increased health care expenditures, and a raised pharmacological burden as individuals progress from lower MADS risk tiers to higher-risk tiers. The analysis also revealed an augmented risk of multimorbidity progression within the high-risk groups, aligned with a higher incidence of new onsets of MDD-related diseases. CONCLUSIONS: The MADS seems to be a promising approach for predicting health risks associated with multimorbidity. It might complement current risk assessment state-of-the-art tools by providing valuable insights for tailored epidemiological impact analyses of clusters of interrelated diseases and by accurately assessing multimorbidity progression risks. This study paves the way for innovative digital developments to support advanced health risk assessment strategies. Further validation is required to generalize its use beyond the initial case study of MDD.

MiR-128-3p as blood based liquid biopsy biomarker in childhood acute lymphoblastic leukemia.

BACKGROUND: Minimal residual disease (MRD) is one of the most valuable independent prognostic factors in acute lymphoblastic leukemia (ALL). Bone marrow (BM) aspiration, however, is an invasive process. Previous studies have shown that microRNAs (miR) and extracellular vesicle (EV)-related miRs show different expression profiles at the presence of malignant cells compared to healthy controls. In our previous project, we have reported that two miRs previously described to be overexpressed in blasts were significantly decreased over the first week of the therapy of patients with ALL in the platelet free plasma fraction (PFP) of peripheral blood samples (PB). The aim of the current study was to assess the relation between day 15 flow cytometry (FC) MRD and expression of miR-128-3p and miR-222-3p miRs in exosome-enriched fraction (EEF) of PFP to evaluate whether their expression in EEF correlates with day 15 FC MRD more precisely. METHODS: PB was collected from 13 patients diagnosed with pediatric pre-B ALL at 4 time points. Expression of miR-128-3p and miR-222-3p was measured by qPCR in PFP and EEF. RESULTS: Positive correlation was found between changes of miR-128-3p expression in EEF or PFP by day 8 of chemotherapy and day 15 FC MRD (rEEF = 0.99, pEEF = 1.13E-9 and rPFP = 0.99, pPFP = 4.75E-9, respectively). Furthermore, the decrease of miR-128-3p in EEF by day 15 of treatment also showed a positive correlation with day 15 FC MRD (rEEF = 0.96; pEEF = 4.89E-5). CONCLUSION: Our results show that circulating miRs are potential biomarkers of ALL MRD, asmiR-128-3p level both in PFP and EEF predicts day 15 FC MRD. In addition, the assessment of the EEF gave a more promising result.

A sound mind in a sound body: a novel concept unravelling heterogeneity of depression.

Depression is a highly prevalent and debilitating condition, yet we still lack both in-depth knowledge concerning its etiopathology and sufficiently efficacious treatment options. With approximately one third of patients resistant to currently available antidepressants there is a pressing need for a better understanding of depression, identifying subgroups within the highly heterogeneous illness category and to understand the divergent underlying biology of such subtypes, to help develop and personalise treatments. The TRAJECTOME project aims to address such challenges by (1) identifying depression-related multimorbidity subgroups and shared molecular pathways based on temporal disease profiles from healthcare systems and biobank data using machine learning approaches, and by (2) characterising these subgroups from multiple aspects including genetic variants, metabolic processes, lifestyle and environmental factors. Following the identification of multimorbidity trajectories, a disease burden score related to depression and adjusted for multimorbidity was established summarising the current state of the patient to weigh the molecular mechanisms associated with depression. In addition, the role of genetic and environmental factors, and also their interactions were identified for all subgroups. The project also attempted to identify potential metabolomic markers for the early diagnostics of these multimorbidity conditions. Finally, we prioritized molecular drug candidates matching the multimorbidity pathways indicated for the individual subgroups which would potentially offer personalised treatment simultaneously for the observable multimorbid conditions yet minimising polypharmacy and related side effects. The present paper overviews the TRAJECTOME project including its aims, tasks, procedures and accomplishments. (Neuropsychopharmacol Hung 2023; 25(4): 183-193)

Shared extracellular vesicle miRNA profiles of matched ductal pancreatic adenocarcinoma organoids and blood plasma samples show the power of organoid technology.

Extracellular vesicles (EV) are considered as a promising diagnostic tool for pancreatic ductal adenocarcinoma (PDAC), a disease with a poor 5-year survival that has not improved in the past years. PDAC patient-derived 3D organoids maintain the intratumoral cellular heterogeneity, characteristic for the tumor in vivo.Thus, they represent an ideal in vitro model system to study human cancers. Here we show that the miRNA cargo of EVs from PDAC organoids largely differs among patients. However, we detected a common set of EV miRNAs that were present in matched organoids and blood plasma samples of individual patients. Importantly, the levels of EV miR-21 and miR-195 were higher in PDAC blood EV preparations than in healthy controls, albeit we found no difference compared to chronic pancreatitis (CP) samples. In addition, here we report that the accumulation of collagen I, a characteristic change in the extracellular matrix (ECM) in both CP and PDAC, largely increases EV release from pancreatic ductal organoids. This provides a possible explanation why both CP and PDAC patient-derived plasma samples have an elevated amount of CD63 + EVs. Collectively, we show that PDAC patient-derived organoids represent a highly relevant model to analyze the cargo of tumor cell-derived EVs. Furthermore, we provide evidence that not only driver mutations, but also changes in the ECM may critically modify EV release from pancreatic ductal cells.

Genetic landscape of early-onset dementia in Hungary.

INTRODUCTION: Early-onset dementias (EOD) are predominantly genetically determined, but the underlying disease-causing alterations are often unknown. The most frequent forms of EODs are early-onset Alzheimer's disease (EOAD) and frontotemporal dementia (FTD). PATIENTS: This study included 120 Hungarian patients with EOD (48 familial and 72 sporadic) which had a diagnosis of EOAD (n = 49), FTD (n = 49), or atypical dementia (n = 22). RESULTS: Monogenic dementia was detected in 15.8% of the patients. A pathogenic hexanucleotide repeat expansion in the C9ORF72 gene was present in 6.7% of cases and disease-causing variants were detected in other known AD or FTD genes in 6.7% of cases (APP, PSEN1, PSEN2, GRN). A compound heterozygous alteration of the TREM2 gene was identified in one patient and heterozygous damaging variants in the CSF1R and PRNP genes were detected in two other cases. In two patients, the coexistence of several heterozygous damaging rare variants associated with neurodegeneration was detected (1.7%). The APOE genotype had a high odds ratio for both the APOE ɛ4/3 and the ɛ4/4 genotype (OR = 2.7 (95%CI = 1.3-5.9) and OR = 6.5 (95%CI = 1.4-29.2), respectively). In TREM2, SORL1, and ABCA7 genes, 5 different rare damaging variants were detected as genetic risk factors. These alterations were not present in the control group. CONCLUSION: Based on our observations, a comprehensive, targeted panel of next-generation sequencing (NGS) testing investigating several neurodegeneration-associated genes may accelerate the path to achieve the proper genetic diagnosis since phenotypes are present on a spectrum. This can also reveal hidden correlations and overlaps in neurodegenerative diseases that would remain concealed in separated genetic testing.

Two tagging single-nucleotide polymorphisms to capture HLA-DRB1*07:01-DQA1*02:01-DQB1*02:02 haplotype associated with asparaginase hypersensitivity.

AIMS: Asparaginase (ASP) hypersensitivity is a well-known challenge in the treatment of lymphoblastic malignancies. In terms of cost considerations, the cheap native Escherichia coli ASP, the most immunogenic form of this medication, is used in the first line in middle-income countries. Previously, the role of the HLA-DRB1*07:01-DQA1*02:01-DQB1*02:02 haplotype had been established to associate with E. coli ASP hypersensitivity. We investigated a possible cost-effective genetic testing method to identify patients harbouring the risk HLA haplotype in order to pave the way for safer ASP treatment. METHODS: In 241 patients with previously determined HLA-DRB1*07:01-DQA1*02:01-DQB1*02:02 haplotype and known ASP hypersensitivity status, 4 candidate HLA-tagging single-nucleotide polymorphisms (SNP)s were measured, and the performance of the different sets of these tag SNPs was evaluated. RESULTS: We identified a combination of 2 SNPs - rs28383172 and rs7775228 - as a tag for HLA-DRB1*07:01-DQA1*02:01-DQB1*02:02 haplotype with sensitivity and specificity values >95%. In line with previous findings, we found complete concordance between HLA-DRB1*07:01 and rs28383172. With bioinformatics methods, the results were also confirmed in the 1000 Genomes dataset in different ethnic groups. CONCLUSION: Rs28383172 and rs7775228 are suitable for identifying HLA-DRB1*07:01-DQA1*02:01-DQB1*02:02 carriers. Compared to the rest of the population, patients with hypersensitivity-prone genotype would benefit more from the administration of less immunogenic PEGylated ASP before the hypersensitivity evolves, incurring minimal extra cost.

Investigation of circulating lncRNAs as potential biomarkers in chronic respiratory diseases.

BACKGROUND: In the present study the blood expression level of inflammatory response and autoimmunity associated long non-coding RNAs (lncRNAs) were compared in patients with different chronic respiratory diseases and investigated whether they could be used as biomarkers in these diseases. METHODS: In the discovery cohort, the gene expression level of 84 lncRNAs were measured in the blood of 24 adult patients including healthy controls and patients with asthma and COPD. In the replication cohort the expression of 6 selected lncRNAs were measured in 163 subjects including healthy controls and adults with allergic rhinitis, asthma, COPD and children with asthma. It was evaluated whether these lncRNAs can be used as diagnostic biomarkers for any studied disease. With systems biology analysis the biological functions of the selected lncRNAs were predicted. RESULTS: In the discovery cohort, the mean expression of 27 lncRNAs showed nominally significant differences in at least one comparison. OIP5-AS1, HNRNPU, RP11-325K4.3, JPX, RP11-282O18.3, MZF1-AS1 were selected for measurement in the replication cohort. Three lncRNAs (HNRNPU, RP11-325K4.3, JPX) expressed significantly higher in healthy children than in adult controls. All the mean expression level of the 6 lncRNAs differed significantly between adult allergic rhinitis patients and controls. RP11-325K4.3, HNRNPU and OIP5-AS1 expressed higher in allergic asthma than in non-allergic asthma. COPD and asthma differed in the expression of RP11-325K4.3 from each other. In examining of the lncRNAs as biomarkers the weighted accuracy (WA) values were especially high in the comparison of healthy controls and patients with allergic rhinitis. OIP5-AS1 and JPX achieved 0.98 and 0.9 WA values, respectively, and the combination of the selected lncRNAs also resulted in a high performance (WA = 0.98). Altogether, OIP5-AS1 had the highest discriminative power in case of three out of six comparisons. CONCLUSION: Differences were detected in the expression of circulating lncRNAs in chronic respiratory diseases. Some of these differences might be utilized as biomarkers and also suggest a possible role of these lncRNAs in the pathomechanism of these diseases. The lncRNAs and the associated pathways are potential therapeutic targets in these diseases, but naturally additional studies are needed for the confirmation of these results.

MicroRNA-181a as novel liquid biopsy marker of central nervous system involvement in pediatric acute lymphoblastic leukemia.

BACKGROUND: Refractory central nervous system (CNS) involvement is among the major causes of therapy failure in childhood acute leukemia. Applying contemporary diagnostic methods, CNS disease is often underdiagnosed. To explore more sensitive and less invasive CNS status indicators, we examined microRNA (miR) expressions and extracellular vesicle (EV) characteristics. METHODS: In an acute lymphoblastic leukemia (ALL) discovery cohort, 47 miRs were screened using Custom TaqMan Advanced Low-Density Array gene expression cards. As a validation step, a candidate miR family was further scrutinized with TaqMan Advanced miRNA Assays on serial cerebrospinal fluid (CSF), bone marrow (BM) and peripheral blood samples with different acute leukemia subtypes. Furthermore, small EV-rich fractions were isolated from CSF and the samples were processed for immunoelectron microscopy with anti-CD63 and anti-CD81 antibodies, simultaneously. RESULTS: Regarding the discovery study, principal component analysis identified the role of miR-181-family (miR-181a-5p, miR-181b-5p, miR-181c-5p) in clustering CNS-positive (CNS+) and CNS-negative (CNS‒) CSF samples. We were able to validate miR-181a expression differences: it was about 52 times higher in CSF samples of CNS+ ALL patients compared to CNS‒ cases (n = 8 vs. n = 10, ΔFC = 52.30, p = 1.5E-4), and CNS+ precursor B cell subgroup also had ninefold higher miR-181a levels in their BM (p = 0.04). The sensitivity of CSF miR-181a measurement in ALL highly exceeded those of conventional cytospin in the initial diagnosis of CNS leukemia (90% vs. 54.5%). Pellet resulting from ultracentrifugation of CNS+ CSF samples of ALL patients showed atypical CD63-/CD81- small EVs in high density by immunoelectron microscopy. CONCLUSIONS: After validating in extensive cohorts, quantification of miR-181a or a specific EV subtype might provide novel tools to monitor CNS disease course and further adjust CNS-directed therapy in pediatric ALL.

Circulating microRNAs as minimal residual disease biomarkers in childhood acute lymphoblastic leukemia.

BACKGROUND: Treatment stratification based on bone marrow minimal residual disease (MRD) at set time points has resulted in considerably improved survival in pediatric acute lymphoblastic leukemia (ALL). Treatment response is assessed using bone marrow samples. MicroRNAs (miRs) easily traffic among fluid spaces and are more stable than most other RNA classes. We examined the role of circulating miRs as putative less invasive MRD biomarkers. METHODS: In an exploratory experiment, expression of 46 preselected miRs was studied in platelet-free blood plasma samples of 15 de novo, 5 relapsed ALL patients and 10 controls by Custom TaqMan Array Advanced MicroRNA Card. Based on their high expression in ALL compared to controls, and on the reduction observed along the induction therapy, four miRs were selected for further analyses: miR-128-3p, -181a-5p, -181b-5p and 222-3p. Their expression was measured by qPCR at 4 time points in 27 de novo ALL patients treated in the ALL IC-BFM 2009 study. RESULTS: The expression of all 4 miRs significantly decreased over the first week of therapy (miR-128-3p: log2 fold change - 2.86; adjusted p 3.6 × 10-7; miR-181b-5p: log2 fold change - 1.75; adjusted p 1.48 × 10-2; miR-181a-5p: log2 fold change -1.33; adjusted p 3.12 × 10-2; miR-222-3p: log2 fold change - 1.25; adjusted p 1.66 × 10-2). However, no significant further reduction in miR expression was found after the 8th day of therapy. Measured drop in expression of 2 miRs at day 8 strongly correlated with day 15 bone marrow flow cytometry MRD results (miR-128-3p: Pearson's r = 0.88, adjusted p = 2.71 × 10-4; miR-222-3p: r = 0.81, adjusted p = 2.99 × 10-3). CONCLUSION: In conclusion, these circulating miRs might act as biomarkers of residual leukemia. MiR-128-3p and miR-222-3p in blood predict day 15 flow cytometry MRD results 7 days earlier. Although, their sensitivity falls behind that of bone marrow flow cytometry MRD at day 15.

Possible roles of genetic variations in chemotherapy related cardiotoxicity in pediatric acute lymphoblastic leukemia and osteosarcoma.

BACKGROUND: The treatment of acute lymphoblastic leukemia (ALL) and osteosarcoma (OSC) is very effective: the vast majority of patients recover and survive for decades. However, they still need to face serious adverse effects of chemotherapy. One of these is cardiotoxicity which may lead to progressive heart failure in the long term. Cardiotoxicity is contributed mainly to the use of anthracyclines and might have genetic risk factors. Our goal was to test the association between left ventricular function and genetic variations of candidate genes. METHODS: Echocardiography data from medical records of 622 pediatric ALL and 39 OSC patients were collected from the period 1989-2015. Fractional shortening (FS) and ejection fraction (EF) were determined, 70 single nucleotide polymorphisms (SNPs) in 26 genes were genotyped. Multivariate logistic regression and multi-adjusted general linear model were performed to investigate the influence of genetic polymorphisms on the left ventricular parameters. Bayesian network based Bayesian multilevel analysis of relevance (BN-BMLA) method was applied to test for the potential interaction of the studied cofactors and SNPs. RESULTS: Our results indicate that variations in ABCC2, CYP3A5, NQO1, SLC22A6 and SLC28A3 genes might influence the left ventricular parameters. CYP3A5 rs4646450 TT was 17% among ALL cases with FS lower than 28, and 3% in ALL patients without pathological FS (p = 5.60E-03; OR = 6.94 (1.76-27.39)). SLC28A3 rs7853758 AA was 12% in ALL cases population, while only 1% among controls (p = 6.50E-03; OR = 11.56 (1.98-67.45)). Patients with ABCC2 rs3740066 GG genotype had lower FS during the acute phase of therapy and 5-10 years after treatment (p = 7.38E-03, p = 7.11E-04, respectively). NQO1 rs1043470 rare T allele was associated with lower left ventricular function in the acute phase and 5-10 years after the diagnosis (p = 4.28E-03 and 5.82E-03, respectively), and SLC22A6 gene rs6591722 AA genotype was associated with lower mean FS (p = 1.71E-03), 5-10 years after the diagnosis. CONCLUSIONS: Genetic variants in transporters and metabolic enzymes might modulate the individual risk to cardiac toxicity after chemotherapy.

Mitochondrial dysfunction and autism: comprehensive genetic analyses of children with autism and mtDNA deletion.

BACKGROUND: The etiology of autism spectrum disorders (ASD) is very heterogeneous. Mitochondrial dysfunction has been described in ASD; however, primary mitochondrial disease has been genetically proven in a small subset of patients. The main goal of the present study was to investigate correlations between mitochondrial DNA (mtDNA) changes and alterations of genes associated with mtDNA maintenance or ASD. METHODS: Sixty patients with ASD and sixty healthy individuals were screened for common mtDNA mutations. Next generation sequencing was performed on patients with major mtDNA deletions (mtdel-ASD) using two gene panels to investigate nuclear genes that are associated with ASD or are responsible for mtDNA maintenance. Cohorts of healthy controls, ASD patients without mtDNA alterations, and patients with mitochondrial disorders (non-ASD) harbouring mtDNA deletions served as comparison groups. RESULTS: MtDNA deletions were confirmed in 16.6% (10/60) of patients with ASD (mtdel-ASD). In 90% of this mtdel-ASD children we found rare SNVs in ASD-associated genes (one of those was pathogenic). In the intergenomic panel of this cohort one likely pathogenic variant was present. In patients with mitochondrial disease in genes responsible for mtDNA maintenance pathogenic mutations and variants of uncertain significance (VUS) were detected more frequently than those found in patients from the mtdel-ASD or other comparison groups. In healthy controls and in patients without a mtDNA deletion, only VUS were detected in both panel. CONCLUSIONS: MtDNA alterations are more common in patients with ASD than in control individuals. MtDNA deletions are not isolated genetic alterations found in ASD; they coexist either with other ASD-associated genetic risk factors or with alterations in genes responsible for intergenomic communication. These findings indicate that mitochondrial dysfunction is not rare in ASD. The occurring mtDNA deletions in ASD may be mostly a consequence of the alterations of the causative culprit genes for autism or genes responsible for mtDNA maintenance, or because of the harmful effect of environmental factors.

[Significance of whole exome sequencing in the diagnostics of rare neurological diseases - own experiences through a case presenting with ataxia]. / A teljesexom-szekvenálás jelentosége a ritka neurológiai betegségek diagnosztikájában ­ saját tapasztalatok egy ataxiás eset kapcsán.

Next generation sequencing (NGS) technologies reshape the diagnostics of rare neurological diseases. In the background of certain neurological symptoms, such as ataxia, many acquired and genetic causes may be present. Variations in a given gene can present with variable phenotypes, too. Because of this phenomenon, the conventional one gene sequencing approach often fails to identify the genetic background of a disease. Next generation sequencing panels allow to sequence 50-100 genes simultaneously, and if the disease stratification is not possible based on the clinical symptoms, whole exome sequencing can help in the diagnostic of genetic disorders with atypical presentation. This case study is about the exome sequencing of a patient with cerebellar ataxia. Genetic investigations identified rare variants in the SPG11 gene in association with the clinical phenotype, which gene was originally described in the background of hereditary spastic paraparesis. Our article highlights that in certain cases the variability of the leading presenting symptom makes it hard to select the correct gene panel. In our case the variants in the gene, formerly associated to hereditary spastic paraparesis, resulted in cerebellar ataxia initially, so even an ataxia NGS gene panel would not detect those. Orv Hetil. 2018; 159(28): 1163-1169.

HLA-DRB1*07:01-HLA-DQA1*02:01-HLA-DQB1*02:02 haplotype is associated with a high risk of asparaginase hypersensitivity in acute lymphoblastic leukemia.

Hypersensitivity reactions are the most frequent dose-limiting adverse reactions to Escherichia coli-derived asparaginase in pediatric acute lymphoblastic leukemia (ALL) patients. The aim of the present study was to identify associations between sequence-based Human Leukocyte Antigen Class II region alleles and asparaginase hypersensitivity in a Hungarian ALL population. Four-digit typing of HLA-DRB1 and HLA-DQB1 loci was performed in 359 pediatric ALL patients by using next-generation sequencing method. Based on genotypic data of the two loci, haplotype reconstruction was carried out. In order to investigate the possible role of the HLA-DQ complex, the HLA-DQA1 alleles were also inferred. Multivariate logistic regression analysis and a Bayesian network-based approach were applied to identify relevant genetic risk factors of asparaginase hypersensitivity. Patients with HLA-DRB1*07:01 and HLA-DQB1*02:02 alleles had significantly higher risk of developing asparaginase hypersensitivity compared to non-carriers [P=4.56×10-5; OR=2.86 (1.73-4.75) and P=1.85×10-4; OR=2.99 (1.68-5.31); n=359, respectively]. After haplotype reconstruction, the HLA-DRB1*07:01-HLA-DQB1*02:02 haplotype was associated with an increased risk. After inferring the HLA-DQA1 alleles the HLA-DRB1*07:01-HLA-DQA1*02:01-HLA-DQB1*02:02 haplotype was associated with the highest risk of asparaginase hypersensitivity [P=1.22×10-5; OR=5.00 (2.43-10.29); n=257]. Significantly fewer T-cell ALL patients carried the HLA-DQB1*02:02 allele and the associated haplotype than did pre-B-cell ALL patients (6.5%; vs. 19.2%, respectively; P=0.047). In conclusion, we identified a haplotype in the Human Leukocyte Antigen Class II region associated with a higher risk of asparaginase hypersensitivity. Our results confirm that variations in HLA-D region might influence the development of asparaginase hypersensitivity.

VariantMetaCaller: automated fusion of variant calling pipelines for quantitative, precision-based filtering.

BACKGROUND: The low concordance between different variant calling methods still poses a challenge for the wide-spread application of next-generation sequencing in research and clinical practice. A wide range of variant annotations can be used for filtering call sets in order to improve the precision of the variant calls, but the choice of the appropriate filtering thresholds is not straightforward. Variant quality score recalibration provides an alternative solution to hard filtering, but it requires large-scale, genomic data. RESULTS: We evaluated germline variant calling pipelines based on BWA and Bowtie 2 aligners in combination with GATK UnifiedGenotyper, GATK HaplotypeCaller, FreeBayes and SAMtools variant callers, using simulated and real benchmark sequencing data (NA12878 with Illumina Platinum Genomes). We argue that these pipelines are not merely discordant, but they extract complementary useful information. We introduce VariantMetaCaller to test the hypothesis that the automated fusion of measurement related information allows better performance than the recommended hard-filtering settings or recalibration and the fusion of the individual call sets without using annotations. VariantMetaCaller uses Support Vector Machines to combine multiple information sources generated by variant calling pipelines and estimates probabilities of variants. This novel method had significantly higher sensitivity and precision than the individual variant callers in all target region sizes, ranging from a few hundred kilobases to whole exomes. We also demonstrated that VariantMetaCaller supports a quantitative, precision based filtering of variants under wider conditions. Specifically, the computed probabilities of the variants can be used to order the variants, and for a given threshold, probabilities can be used to estimate precision. Precision then can be directly translated to the number of true called variants, or equivalently, to the number of false calls, which allows finding problem-specific balance between sensitivity and precision. CONCLUSIONS: VariantMetaCaller can be applied to small target regions and whole exomes as well, and it can be used in cases of organisms for which highly accurate variant call sets are not yet available, therefore it can be a viable alternative to hard filtering in cases where variant quality score recalibration cannot be used. VariantMetaCaller is freely available at http://bioinformatics.mit.bme.hu/VariantMetaCaller .

Impact of gene-by-trauma interaction in MDD-related multimorbidity clusters.

BACKGROUND: Major depressive disorder (MDD) is considerably heterogeneous in terms of comorbidities, which may hamper the disentanglement of its biological mechanism. In a previous study, we classified the lifetime trajectories of MDD-related multimorbidities into seven distinct clusters, each characterized by unique genetic and environmental risk-factor profiles. The current objective was to investigate genome-wide gene-by-environment (G × E) interactions with childhood trauma burden, within the context of these clusters. METHODS: We analyzed 77,519 participants and 6,266,189 single-nucleotide polymorphisms (SNPs) of the UK Biobank database. Childhood trauma burden was assessed using the Childhood Trauma Screener (CTS). For each cluster, Plink 2.0 was used to calculate SNP × CTS interaction effects on the participants' cluster membership probabilities. We especially focused on the effects of 31 candidate genes and associated SNPs selected from previous G × E studies for childhood maltreatment's association with depression. RESULTS: At SNP-level, only the high-multimorbidity Cluster 6 revealed a genome-wide significant SNP rs145772219. At gene-level, MPST and PRH2 were genome-wide significant for the low-multimorbidity Clusters 1 and 3, respectively. Regarding candidate SNPs for G × E interactions, individual SNP results could be replicated for specific clusters. The candidate genes CREB1, DBH, and MTHFR (Cluster 5) as well as TPH1 (Cluster 6) survived multiple testing correction. LIMITATIONS: CTS is a short retrospective self-reported measurement. Clusters could be influenced by genetics of individual disorders. CONCLUSIONS: The first G × E GWAS for MDD-related multimorbidity trajectories successfully replicated findings from previous G × E studies related to depression, and revealed risk clusters for the contribution of childhood trauma.

Unique genetic and risk-factor profiles in clusters of major depressive disorder-related multimorbidity trajectories.

The heterogeneity and complexity of symptom presentation, comorbidities and genetic factors pose challenges to the identification of biological mechanisms underlying complex diseases. Current approaches used to identify biological subtypes of major depressive disorder (MDD) mainly focus on clinical characteristics that cannot be linked to specific biological models. Here, we examined multimorbidities to identify MDD subtypes with distinct genetic and non-genetic factors. We leveraged dynamic Bayesian network approaches to determine a minimal set of multimorbidities relevant to MDD and identified seven clusters of disease-burden trajectories throughout the lifespan among 1.2 million participants from cohorts in the UK, Finland, and Spain. The clusters had clear protective- and risk-factor profiles as well as age-specific clinical courses mainly driven by inflammatory processes, and a comprehensive map of heritability and genetic correlations among these clusters was revealed. Our results can guide the development of personalized treatments for MDD based on the unique genetic, clinical and non-genetic risk-factor profiles of patients.

Multilevel evidence of MECP2-associated mitochondrial dysfunction and its therapeutic implications.

We present a male patient carrying a pathogenic MECP2 p. Arg179Trp variant with predominant negative psychiatric features and multilevel evidence of mitochondrial dysfunction who responded to the cariprazine treatment. He had delayed speech development and later experienced severe social anxiety, learning disabilities, cognitive slowing, and predominant negative psychiatric symptoms associated with rigidity. Clinical examinations showed multisystemic involvement. Together with elevated ergometric lactate levels, the clinical picture suggested mitochondrial disease, which was also supported by muscle histopathology. Exploratory transcriptome analysis also revealed the involvement of metabolic and oxidative phosphorylation pathways. Whole-exome sequencing identified a pathogenic MECP2 variant, which can explain both the dopamine imbalance and mitochondrial dysfunction in this patient. Mitochondrial dysfunction was previously suggested in classical Rett syndrome, and we detected related phenotype evidence on multiple consistent levels for the first time in a MECP2 variant carrier male. This study further supports the importance of the MECP2 gene in the mitochondrial pathways, which can open the gate for more personalized therapeutic interventions. Good cariprazine response highlights the role of dopamine dysfunction in the complex psychiatric symptoms of Rett syndrome. This can help identify the optimal treatment strategy from a transdiagnostic perspective instead of a classical diagnostic category.

Gene co-expression analyses of health(span) across multiple species.

Health(span)-related gene clusters/modules were recently identified based on knowledge about the cross-species genetic basis of health, to interpret transcriptomic datasets describing health-related interventions. However, the cross-species comparison of health-related observations reveals a lot of heterogeneity, not least due to widely varying health(span) definitions and study designs, posing a challenge for the exploration of conserved healthspan modules and, specifically, their transfer across species. To improve the identification and exploration of conserved/transferable healthspan modules, here we apply an established workflow based on gene co-expression network analyses employing GEO/ArrayExpress data for human and animal models, and perform a comprehensive meta-study of the resulting modules related to health(span), yielding a small set of literature backed health(span) candidate genes. For each experiment, WGCNA (weighted gene correlation network analysis) was used to infer modules of genes which correlate in their expression with a 'health phenotype score' and to determine the most-connected (hub) genes (and their interactions) for each such module. After mapping these hub genes to their human orthologs, 12 health(span) genes were identified in at least two species (ACTN3, ANK1, MRPL18, MYL1, PAXIP1, PPP1CA, SCN3B, SDCBP, SKIV2L, TUBG1, TYROBP, WIPF1), for which enrichment analysis by g:profiler found an association with actin filament-based movement and associated organelles, as well as muscular structures. We conclude that a meta-study of hub genes from co-expression network analyses for the complex phenotype health(span), across multiple species, can yield molecular-mechanistic insights and can direct experimentalists to further investigate the contribution of individual genes and their interactions to health(span).

Decreased Plasma Level of Cytokeratin 20 (KRT20) Is Indicative of the Emergence and Severity of Acute GvHD Irrespective to the Type of Organ Involvement.

Accurate risk prediction of acute graft versus host disease (aGvHD) is currently an unmet clinical need. This study sought to analyze whether three plasma proteins expressed in a largely skin- and gut-restricted manner would be affected by the development of acute cutaneous and gastrointestinal aGvHD. The diagnostic sensitivity, specificity, and prognostic value of plasma cytokeratin-15 (KRT15) cytokeratin-20 (KRT20), and occludin (OCLN) were evaluated in a discovery and a validation cohort using ELISA in comparison with elafin (PI3) and regenerating family member 3 alpha (REG3A), two established markers of skin- and gut aGvHD. The discovery cohort (n = 39) revealed that at the time of diagnosis, plasma KRT20 showed a progressive decrease from unaffected individuals to patients with single-, and patients with multi-organ aGvHD. KRT20 was affected by cutaneous (p = 0.0263) and gastrointestinal aGvHD (p = 0.0242) independently and in an additive manner. Sensitivity and specificity of KRT20 for aGvHD involving both target organs (AUC = 0.852) were comparable to that of PI3 for skin-aGvHD (AUC = 0.708) or that of REG3A for gut-aGvHD (AUC = 0.855). Patient follow-up in the validation cohort (n = 67) corroborated these observations (p < 0.001), and linked low KRT20 to grade 2+ disease (p < 0.001), but failed to confirm low KRT20 as an independent risk factor. These data established a link between low plasma KRT20 levels and moderate to severe aGvHD involving multiple target organs.