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Abstract Growing evidence suggests a potential link between the gut microbiome and schizophrenia. However, it is unclear whether the gut microbiome is causally associated with schizophrenia. We performed two-sample bidirectional Mendelian randomization to detect bidirectional causal relationships between gut microbiome and schizophrenia. Summary genome-wide association study (GWAS) datasets of the gut microbiome from the MiBioGen consortium (n = 18,340) and schizophrenia (n = 130,644) were utilized in our study. Then a cohort of sensitive analyses was followed to validate the robustness of MR results. We identified nine taxa that exerted positive causal effects on schizophrenia (OR: 1.08–1.16) and six taxa that conferred negative causal effects on schizophrenia (OR: 0.88–0.94). On the other hand, the reverse MR analysis showed that schizophrenia may increase the abundance of nine taxa (OR: 1.03–1.08) and reduce the abundance of two taxa (OR: 0.94). Our study unveiled mutual causal relationships between gut microbiome and schizophrenia. The findings may provide evidence for the treatment potential of gut microbiomes in schizophrenia.

Abstract Background Existing evidence suggests that alterations in the gut microbiome are closely associated with major depressive disorder (MDD). We aimed to reveal the causal relationships between MDD and various microbial taxa in the gut. Methods We used the two-sample Mendelian randomization (TSMR) to explore the bidirectional causal effects between gut microbiota and MDD. The genome-wide association studies summary results of gut microbiota were obtained from two large consortia, the MibioGen consortium and the Dutch Microbiome Project, which we analyzed separately. Results Our TSMR analysis identified 10 gut bacterial taxa that were protective against MDD, including phylum Actinobacteria, order Clostridiales, and family Bifidobacteriaceae (OR: 0.96 ∼ 0.98). Ten taxa were associated with an increased risk of MDD, including phyla Firmicutes and Proteobacteria, class Actinobacteria, and genus Alistipes (OR: 1.01 ∼ 1.09). On the other hand, MDD may decrease the abundance of 12 taxa, including phyla Actinobacteria and Firmicutes, families Bifidobacteriaceae and Defluviitaleaceae (OR: 0.63 ∼ 0.88). MDD may increase the abundance of 8 taxa, including phylum Bacteroidetes, genera Parabacteroides, and Bacteroides (OR: 1.12 ∼ 1.43). Conclusions Our study supports that there are mutual causal relationships between certain gut microbiota and the development of MDD suggesting that gut microbiota may be targeted in the treatment of MDD.

IntroductionThe gut microbiome (GM) has been implicated in cancer pathogenesis and treatment, including head and neck cancers (HNC). However, the specific microbial compositions influencing HNC and the underlying mechanisms remain largely unknown.MethodsThis study utilized published genome-wide association studies (GWAS) summary data-based two-sample Mendelian randomization (MR) to uncover the GM compositions that exert significant causal effects on HNC. Functional annotation and enrichment analysis were conducted to better understand the significant genetic variables and their connection with HNC. The HNC dataset included 2,281 cases and 314,193 controls. The GM GWAS data of 211 gut taxa (35 families, 20 orders, 16 classes, 9 phyla, and 131 genera) were obtained from the MibioGen consortium, involving 18,340 participants.ResultsMR analysis revealed four GM compositions exerting causal effects on HNC. Specifically, family Peptococcaceae.id.2024 was significantly associated with a 35% reduced risk of HNC (OR=0.65; 95%CI=0.48-0.90; P=0.0080). In contrast, genus DefluviitaleaceaeUCG-011.id.11287 (OR=1.54; 95%CI=1.13-2.09; P=0.0060), genus Gordonibacter.id.821 (OR=1.23; 95%CI=1.05-1.45; P=0.012), and genus Methanobrevibacter.id.123 (OR=1.28; 95%CI=1.01-1.62; P=0.040) showed a significant association with an increased risk of HNC. These GMs interact with genes and genetic variants involved in signaling pathways, such as GTPase regulation, influencing tumor progression and disease prognosis.ConclusionsOur study demonstrates, for the first time, the causal influence of specific gut microbiome compositions on HNC, offering significant insights for advancing clinical research and personalized treatments. The identified GMs may serve as potential biomarkers or therapeutic targets, paving the way for innovative approaches in HNC diagnosis, prevention, and therapy.

BackgroundSchizophrenia (SZ) is a severe mental disorder with complex origins. Observational studies suggested that inflammatory factors may play a role in the pathophysiology of SZ and we aim to investigate the potential genetic connection between them by examining the causal impact of circulating inflammatory proteins on SZ.MethodsWe utilized Mendelian randomization (MR) analysis to assess the causal relationship between circulating inflammatory proteins and SZ and the GWAS summary datasets were sourced from public databases. The SZ dataset comprised 74,776 cases and 101,023 controls, while the summary results for 91 plasma proteins in 14,824 participants were obtained through the Olink Target platform. Moreover, to identify and evaluate potential drug targets, we searched the Drug-Gene Interaction Database (DGIdb).ResultsThe results of the MR study confirmed that nine inflammatory proteins had a causal effect on SZ. Among these proteins, IL1A (OR: 0.93), TNFB (OR: 0.94), TNFSF14 (OR: 0.96), and CD40 (OR: 0.95) exhibited protective effects against SZ. Conversely, CCL23 (OR: 1.04), CCL19 (OR: 1.04), 4EBP1 (OR: 1.06), TWEAK (OR: 1.08), and DNER (OR: 1.10) were associated with an increased risk of SZ. The MR-Egger and weighted median methods also supported the direction of these effects. According to the Gene-Drug analysis, LTA, IL1A, CD40, and 4EBP1 can serve as drug targets.ConclusionsOur study established causal relationships between circulating inflammatory proteins and SZ. It may be beneficial to personalize the treatment of SZ by incorporating inflammation management into the treatment regimen.

IntroductionThe complex and unresolved pathogenesis of schizophrenia has posed significant challenges to its diagnosis and treatment. While recent research has established a clear association between immune function and schizophrenia, the causal relationship between the two remains elusive.MethodsWe employed a bidirectional two-sample Mendelian randomization approach to investigate the causal relationship between schizophrenia and 731 immune cell traits by utilizing public GWAS data. We further validated the causal relationship between schizophrenia and six types of white cell measures.ResultsWe found the overall causal effects of schizophrenia on immune cell traits were significantly higher than the reverse ones (0.011 ± 0.049 vs 0.001 ± 0.016, p < 0.001), implying that disease may lead to an increase in immune cells by itself. We also identified four immune cell traits that may increase the risk of schizophrenia: CD11c+ monocyte %monocyte (odds ratio (OR): 1.06, 95% confidence interval (CI): 1.03~1.09, FDR = 0.027), CD11c+ CD62L- monocyte %monocyte (OR:1.06, 95% CI: 1.03~1.09, FDR = 0.027), CD25 on IgD+ CD38- naive B cell (OR:1.03, 95% CI:1.01~1.06, FDR = 0.042), and CD86 on monocyte (OR = 1.04, 95% CI:1.01~1.06, FDR = 0.042). However, we did not detect any significant causal effects of schizophrenia on immune cell traits. Using the white blood cell traits data, we identified that schizophrenia increases the lymphocyte counts (OR:1.03, 95%CI: 1.01-1.04, FDR = 0.007), total white blood cell counts (OR:1.02, 95%CI: 1.01-1.04, FDR = 0.021) and monocyte counts (OR:1.02, 95%CI: 1.00-1.03, FDR = 0.034). The lymphocyte counts were nominally associated with the risk of schizophrenia (OR:1.08,95%CI:1.01-1.16, P=0.019).DiscussionOur study found that the causal relationship between schizophrenia and the immune system is complex, enhancing our understanding of the role of immune regulation in the development of this disorder. These findings offer new insights for exploring diagnostic and therapeutic options for schizophrenia.

IntroductionThe impact of the COVID-19 pandemic on head and neck cancer (HNC) has been suggested, but the causal relationship remains unclear.MethodsWe explore this connection by utilizing the Mendelian randomization (MR) approach applied to publicly available genome-wide association study (GWAS) summary datasets for COVID-19 and HNC. The datasets included critical COVID-19 (13,769 cases, 1,072,442 controls), hospitalized COVID-19 (32,519 cases, 2,062,805 controls), SARS-CoV-2 infection (122,616 cases, 2,475,240 controls), and HNC (2,131 cases, 287,137 controls). Mechanistic underpinnings of the causal relationships identified by MR analysis were explored through functional annotation augmented by AI-based literature data mining.ResultsSurprisingly, a genetic predisposition to contracting a milder form of COVID-19 substantially reduced the risks of developing HNC (OR: 0.52, 95% CI: 0.35–0.78, p = 1.42E-03), with no significant association between genetic liability to severe COVID-19 and the risk of HNC detected. Additionally, our findings highlighted 14 genes linked to SARS-CoV-2 infection, potentially playing a protective role in the context of HNC. These genes include OAS1, LOC107985887, BCL11A, DPP9, LOC107984685, LINC02326, MUC4, NXPE3, IFNAR2, LZTFL1, LOC105372437, NAPSA, LOC105376622, LOC107986082, and SLC6A20.ConclusionOur study emphasizes the protective role of the genetic liability to milder COVID-19 in reducing the risk of HNC while refuting a causal relationship between severe COVID-19 and HNC.

Abstract Previous studies have observed a significant comorbidity between Alzheimer’s disease (AD) and some other neuropsychiatric disorders. However, the mechanistic connections between neuropsychiatric disorders and AD are not well understood. We conducted a Mendelian randomization analysis to appraise the potential influences of 18 neurodegenerative and neuropsychiatric disorders on AD. We found that four disorders are causally associated with increased risk for AD, including bipolar disorder (BD) (OR: 1.09), migraine (OR: 1.09), schizophrenia (OR: 1.05), and Parkinson’s disease (PD) (OR: 1.07), while attention-deficit/hyperactivity disorder (ADHD) was associated with a decreased risk for AD (OR: 0.80). In case of amyotrophic lateral sclerosis (OR: 1.04) and Tourette’s syndrome (OR: 1.05), there was suggestive evidence of their causal effects of on AD. Our study shows that genetic components predisposing to BD, migraine, schizophrenia, and PD may promote the development of AD, while ADHD may be associated with a reduced risk of AD. The treatments aimed at alleviating neuropsychiatric diseases with earlier onset may also influence the risk of AD-related cognitive decline, which is typically observed later in life.

Background Mental disorders have a high comorbidity with cardiovascular disease (CVD), but the causality between them has not been fully appreciated.Objective This study aimed to systematically explore the bidirectional causality between the two broad categories of diseases.Methods We conducted Mendelian randomisation (MR) and multivariable MR (MVMR) analyses to evaluate potential causal links between 10 mental disorders, the use of antidepressants and 7 CVDs.Findings We discovered that major depressive disorder (MDD), attention-deficit/hyperactivity disorder (ADHD) and insomnia exhibit connections with elevated risks of two or more CVDs. Moreover, the use of antidepressants is linked to heightened risks of each CVD. Each distinct CVD is correlated with a greater probability of taking antidepressants. Our MVMR analysis demonstrated that the use of antidepressants is correlated with the elevation of respective risks across all cardiovascular conditions. This includes arrhythmias (OR: 1.28), atrial fibrillation (OR: 1.44), coronary artery disease (OR: 1.16), hypertension (OR: 1.16), heart failure (OR: 1.16), stroke (OR: 1.44) and entire CVD group (OR: 1.35). However, MDD itself was not linked to a heightened risk of any CVD.Conclusions The findings of our study indicate that MDD, insomnia and ADHD may increase the risk of CVD. Our findings highlight the utilisation of antidepressants as an independent risk factor for CVD, thus explaining the influence of MDD on CVD through the mediating effects of antidepressants.Clinical implications When treating patients with antidepressants, it is necessary to take into consideration the potential beneficial and detrimental effects of antidepressants.

Abstract Background The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can invade both the peripheral and central nervous systems and impact the function of the brain. Therefore, it is necessary to evaluate the mutual influences between COVID-19 outcomes and childhood mental disorders. Methods We examined genetic correlations and potential causalities between three childhood mental disorders and three COVID-19 phenotypes by genetically proxied analyses. The three mental disorders included attention-deficit/hyperactivity disorder (ADHD, N = 292,548), Tourette’s syndrome (TS, N = 14,307), and autism spectrum disorder (ASD, N = 46,350). The three COVID-19 traits included SARS-CoV-2 infection (N = 2,597,856), hospitalized COVID-19 (N = 2,095,324), and critical COVID-19 (N = 1,086,211). Literature-based analysis was used to build gene-based pathways connecting ADHD and COVID-19. Results ADHD was positively correlated with the three COVID-19 outcomes (Rg: 0.22 ~ 0.30). Our Mendelian randomization (MR) analyses found that ADHD confers a causal effect on hospitalized COVID-19 (odds ratio (OR): 1.36, 95% confidence interval (CI): 1.10–1.69). TS confers a causal effect on critical COVID-19 (OR: 1.14, 95% CI: 1.04–1.25). Genetic liability to the COVID-19 outcomes may not increase the risk for the childhood mental disorders. Pathway analysis identified several immunity-related genes that may link ADHD to COVID-19, including CRP, OXT, IL6, PON1, AR, TNFSF12, and IL10. Conclusions Our study suggests that both ADHD and TS may augment the severity of COVID-19 through immunity-related pathways. However, our results did not support a causal role of COVID-19 in the risk for the childhood mental disorders.

Background Previous studies have shown that educational attainment (EA), intelligence and income are key factors associated with mental disorders. However, the direct effects of each factor on major mental disorders are unclear.Aims We aimed to evaluate the overall and independent causal effects of the three psychosocial factors on common mental disorders.Methods Using genome-wide association study summary datasets, we performed Mendelian randomisation (MR) and multivariable MR (MVMR) analyses to assess potential associations between the 3 factors (EA, N=766 345; household income, N=392 422; intelligence, N=146 808) and 13 common mental disorders, with sample sizes ranging from 9907 to 807 553. Inverse-variance weighting was employed as the main method in the MR analysis.Results Our MR analysis showed that (1) higher EA was a protective factor for eight mental disorders but contributed to anorexia nervosa, obsessive-compulsive disorder (OCD), bipolar disorder (BD) and autism spectrum disorder (ASD); (2) higher intelligence was a protective factor for five mental disorders but a risk factor for OCD and ASD; (3) higher household income protected against 10 mental disorders but confers risk for anorexia nervosa. Our MVMR analysis showed that (1) higher EA was a direct protective factor for attention-deficit/hyperactivity disorder (ADHD) and insomnia but a direct risk factor for schizophrenia, BD and ASD; (2) higher intelligence was a direct protective factor for schizophrenia but a direct risk factor for major depressive disorder (MDD) and ASD; (3) higher income was a direct protective factor for seven mental disorders, including schizophrenia, BD, MDD, ASD, post-traumatic stress disorder, ADHD and anxiety disorder.Conclusions Our study reveals that education, intelligence and income intertwine with each other. For each factor, its independent effects on mental disorders present a more complex picture than its overall effects.

ObjectiveThe relationships between circulating inflammatory proteins and COVID-19 have been observed in previous cohorts. However, it is not unclear which circulating inflammatory proteins may boost the risk of or protect against COVID-19.MethodsWe performed Mendelian randomization (MR) analysis using GWAS summary result of 91 circulating inflammation-related proteins (N = 14,824) to assess their causal impact on severe COVID-19. The COVID-19 phenotypes encompassed both hospitalized (N = 2,095,324) and critical COVID-19 (N = 1,086,211). Moreover, sensitivity analyses were conducted to evaluate the robustness and reliability.ResultsWe found that seven circulating inflammatory proteins confer positive causal effects on severe COVID-19. Among them, serum levels of IL-10RB, FGF-19, and CCL-2 positively contributed to both hospitalized and critical COVID-19 conditions (OR: 1.10~1.16), while the other 4 proteins conferred risk on critical COVID-19 only (OR: 1.07~1.16), including EIF4EBP1, IL-7, NTF3, and LIF. Meanwhile, five proteins exert protective effects against hospitalization and progression to critical COVID-19 (OR: 0.85~0.95), including CXCL11, CDCP1, CCL4/MIP, IFNG, and LIFR. Sensitivity analyses did not support the presence of heterogeneity in the majority of MR analyses.ConclusionsOur study revealed risk and protective inflammatory proteins for severe COVID-19, which may have vital implications for the treatment of the disease.

Objective: We aimed to evaluate bidirectional genetic relationships between posttraumatic stress disorder (PTSD) and COVID-19. Methods: We investigated potential causal associations between PTSD and two COVID-19 conditions (COVID-19 hospitalization and SARS-CoV-2 infection) via Mendelian randomization (MR) analyses. Three genome-wide association study (GWAS) summary datasets were used in the study, including PTSD (N = 174,659), SARS-CoV-2 infection (N = 2,597,856), and COVID-19 hospitalization (N = 2,095,324). We performed a literature-based analysis to uncover molecular pathways connecting PTSD and COVID-19. Results: We found that PTSD exerts a causal effect on SARS-CoV-2 infection (odds ratio (OR): 1.10, 95% confidence interval (CI): 1.00–1.21, p = 0.048) and hospitalized COVID-19 (OR: 1.34, 95% CI: 1.07–1.67, p = 0.001). However, both SARS-CoV-2 infection and hospitalized COVID-19 were not associated with the risk of PTSD. Pathway analysis revealed that several immunity-related genes may link PTSD to COVID-19. Conclusions: Our study suggests that PTSD was associated with increased risks for COVID-19 susceptibility and severity. Early diagnosis and effective treatment of PTSD in individuals infected with the coronavirus may improve the management of the outcomes of COVID-19.

ObjectiveAlthough observational and genetic studies have indicated a correlation between OA and COVID-19, it remains uncertain whether osteoarthritis (OA) contributes to the severity of COVID-19. Here, we aimed to investigate the potential causal links between the two.MethodsIn this study, we conducted Mendelian randomization (MR) analysis to investigate whether there is a potential causal connection between OA and COVID-19 outcomes. The analysis utilized publicly available GWAS summary datasets, incorporating data on OA (N = 455,221), SARS-CoV-2 infection (N = 2,597,856), hospitalized COVID-19 (N = 2,095,324), and critical COVID-19 (N = 1,086,211). Additionally, we performed a literature analysis to establish a molecular network connecting OA and COVID-19.ResultsThe MR analysis showed causal effects of OA on hospitalized COVID-19 (OR: 1.21, 95% CI: 1.02–1.43, p = 0.026) and critical COVID-19 (OR: 1.35, 95% CI: 1.09–1.68, p = 0.006) but not on SARS-CoV-2 infection as such (OR: 1.00, 95% CI: 0.92–1.08, p = 0.969). Moreover, the literature-based pathway analysis uncovered a set of specific genes, such as CALCA, ACE, SIRT1, TNF, IL6, CCL2, and others, that were found to mediate the association between OA and COVID-19.ConclusionOur findings indicate that OA elevates the risk of severe COVID-19. Therefore, larger efforts should be made in the prevention of COVID-19 in OA patients.

Acute respiratory viral infections (ARVI) are the most common illnesses worldwide. In some instances, mild cases of ARVI progress to hyperinflammatory responses, which are damaging to pulmonary tissue and requiring intensive care. Here we summarize available information on preclinical and clinical effects of XC221GI (1-[2-(1-methyl imidazole-4-yl)-ethyl]perhydroazin-2,6-dione), an oral drug with a favorable safety profile that has been tested in animal models of influenza, respiratory syncytial virus, highly pathogenic coronavirus strains and other acute viral upper respiratory infections. XC221GI is capable of controlling IFN-gamma-driven inflammation as it is evident from the suppression of the production of soluble cytokines and chemokines, including IL-6, IL-8, CXCL10, CXCL9 and CXCL11 as well as a decrease in migration of neutrophils into the pulmonary tissue. An excellent safety profile of XC221GI, which is not metabolized by the liver, and its significant anti-inflammatory effects indicate utility of this compound in abating conversion of ambulatory cases of respiratory infections into the cases with aggravated presentation that require hospitalization. This drug is especially useful when rapid molecular assays determining viral species are impractical, or when direct antiviral drugs are not available. Moreover, XC221GI may be combined with direct antiviral drugs to enhance their therapeutic effects.

Abstract Background A fraction of patients referred for complex molecular profiling of biopsied tumors may harbor germline variants in genes associated with the development of hereditary cancer syndromes (HCS). Neither the bioinformatic analysis nor the reporting of such incidental germline findings are standardized. Methods Data from Next-Generation Sequencing (NGS) of biopsied tumor samples referred for complex molecular profiling were analyzed for germline variants in HCS-associated genes. Analysis of variant origin was performed employing bioinformatic algorithms followed by manual curation. When possible, the origin of the variant was validated by Sanger sequencing of the sample of normal tissue. The variants’ pathogenicity was assessed according to ACMG/AMP. Results Tumors were sampled from 183 patients (Males: 75 [41.0%]; Females: 108 [59.0%]; mean [SD] age, 57.7 [13.3] years) and analysed by targeted NGS. The most common tumor types were colorectal (19%), pancreatic (13%), and lung cancer (10%). A total of 56 sequence variants in genes associated with HCS were detected in 40 patients. Of them, 17 variants found in 14 patients were predicted to be of germline origin, with 6 variants interpreted as pathogenic (PV) or likely pathogenic (LPV), and 9 as variants of uncertain significance (VUS). For the 41 out of 42 (97%) missense variants in HCS-associated genes, the results of computational prediction of variant origin were concordant with that of experimental examination. We estimate that Sanger sequencing of a sample of normal tissue would be required for ~ 1–7% of the total assessed cases with PV or LPV, when necessity to follow with genetic counselling referral in ~ 2–15% of total assessed cases (PV, LPV or VUS found in HCS genes). Conclusion Incidental findings of pathogenic germline variants are common in data from cancer patients referred for complex molecular profiling. We propose an algorithm for the management of patients with newly detected variants in genes associated with HCS.

Aims: Deciphering the genetic relationships between major depressive disorder (MDD) and osteoarthritis (OA) may facilitate an understanding of their biological mechanisms, as well as inform more effective treatment regimens. We aim to investigate the mechanisms underlying relationships between MDD and OA in the context of common genetic variations. Methods: Linkage disequilibrium score regression was used to test the genetic correlation between MDD and OA. Polygenic analysis was performed to estimate shared genetic variations between the two diseases. Two-sample bidirectional Mendelian randomization analysis was used to investigate causal relationships between MDD and OA. Genomic loci shared between MDD and OA were identified using cross-trait meta-analysis. Fine-mapping of transcriptome-wide associations was used to prioritize putatively causal genes for the two diseases. Results: MDD has a significant genetic correlation with OA (rg = 0.29) and the two diseases share a considerable proportion of causal variants. Mendelian randomization analysis indicates that genetic liability to MDD has a causal effect on OA (bxy = 0.24) and genetic liability to OA conferred a causal effect on MDD (bxy = 0.20). Cross-trait meta-analyses identified 29 shared genomic loci between MDD and OA. Together with fine-mapping of transcriptome-wide association signals, our results suggest that Estrogen Receptor 1 (ESR1), SRY-Box Transcription Factor 5 (SOX5), and Glutathione Peroxidase 1 (GPX1) may have therapeutic implications for both MDD and OA. Conclusion: The study reveals substantial shared genetic liability between MDD and OA, which may confer risk for one another. Our findings provide a novel insight into phenotypic relationships between MDD and OA. Cite this article: Bone Joint Res 2022;11(1):12–22.

Abstract Objective LINC00461 is a highly conserved intergenic non-protein coding RNA that was implicated in schizophrenia at the genome-wide level. We aim to explore potential mechanisms underlying the involvement of LINC00461 in schizophrenia. Methods We performed a meta-analysis to investigate the association of LINC00461 rs410216 with schizophrenia, and evaluate the effects of the rs410216 on hippocampal volume and function using the functional magnetic resonance imaging (fMRI) analysis. We utilized the GTEx dataset to profile the expression distribution of LINC00461 across different brain regions, and to investigate the potential impact of the risk SNPs on the expression of LINC00461 and other nearby genes. We compared blood expression levels of LINC00461 between schizophrenia patients and controls. Results Here we show that single-nucleotide polymorphisms (SNPs) located in regulatory elements spanning the LINC00461 region are significantly associated with schizophrenia (index SNP rs410216, Pmeta = 1.43E-05); subjects carrying the risk allele of rs410216 showed decreased hippocampal volume. However, no significant association of the rs410216 variant with hippocampal activation was observed. Moreover, the expression level of LINC00461 mRNA was significantly lower in first-onset schizophrenia patients, and the risk allele also predicts a lower transcriptional level of LINC00461 in the hippocampus. Conclusion Together, these convergent lines of evidence implicate inadequate LINC00461 expression in the hippocampus in the development of schizophrenia, providing novel insight into the genetic architecture and biological etiology of schizophrenia.

Background Type 2 diabetes (T2D) is a chronic metabolic disorder with high comorbidity with mental disorders. The genetic links between attention-deficit/hyperactivity disorder (ADHD) and T2D have yet to be elucidated.Aims We aim to assess shared genetics and potential associations between ADHD and T2D.Methods We performed genetic correlation, two-sample Mendelian randomisation and polygenic overlap analyses between ADHD and T2D. The genome-wide association study (GWAS) summary results of T2D (80 154 cases and 853 816 controls), ADHD2019 (20 183 cases and 35 191 controls from the 2019 GWAS ADHD dataset) and ADHD2022 (38 691 cases and 275 986 controls from the 2022 GWAS ADHD dataset) were used for the analyses. The T2D dataset was obtained from the DIAGRAM Consortium. The ADHD datasets were obtained from the Psychiatric Genomics Consortium. We compared genome-wide association signals to reveal shared genetic variation between T2D and ADHD using the larger ADHD2022 dataset. Moreover, molecular pathways were constructed based on large-scale literature data to understand the connection between ADHD and T2D.Results T2D has positive genetic correlations with ADHD2019 (rg=0.33) and ADHD2022 (rg=0.31). Genetic liability to ADHD2019 was associated with an increased risk for T2D (odds ratio (OR): 1.30, p

Tea ingredients can effectively inhibit SARS-CoV-2 infection at adequate concentrations. It is not known whether tea intake could impact the susceptibility to COVID-19 or its severity. We aimed to evaluate the causal effects of tea intake on COVID-19 outcomes. We performed Mendelian randomization (MR) analyses to assess the causal associations between tea intake (N = 441,279) and three COVID-19 outcomes, including SARS-CoV-2 infection (122,616 cases and 2,475,240 controls), hospitalized COVID-19 (32,519 cases and 2,062,805 controls), and critical COVID-19 (13,769 cases and 1,072,442 controls). The MR analyses indicated that genetic propensity for tea consumption conferred a negative causal effect on the risk of SARS-CoV-2 infection (OR: 0.87, 95% confidence interval (CI): 0.78–0.97, P = 0.015). No causal effects on hospitalized COVID-19 (0.84, 0.64–1.10, P = 0.201) or critical COVID-19 (0.73, 0.51–1.03, P = 0.074) were detected. Our study revealed that tea intake could decrease the risk of SARS-CoV-2 infection, highlighting the potential preventive effect of tea consumption on COVID-19 transmission.

While worldwide efforts for improving COVID-19 vaccines are currently considered a top priority, the role of the genetic variants responsible for virus receptor protein stability is less studied. Angiotensin-converting enzyme-2 is the primary target of the SARS-CoV-1/SARS-CoV-2 spike (S) glycoprotein, enabling entry into the human body. Here, we applied computational saturation mutagenesis approaches to determine the folding energy caused by all possible mutations in ACE2 proteins within ACE2 - SARS-CoV-1-S/ACE2 - SARS-CoV-2-S complexes. We observed ACE2 mutations at residue D350 causing the most stabilizing effects on the protein. In addition, we identified ACE2 genetic variations in African Americans (rs73635825, rs766996587, and rs780574871), Latino Americans (rs924799658), and both groups (rs4646116 and rs138390800) affecting stability in the ACE2 - SARS-CoV-2-S complex. The findings in this study may aid in targeting the design of stable neutralizing peptides for treating minority patients.

Objectives: To explore the connection of hypertension and severe COVID-19 outcomes.Methods: A total of 68 observational studies recording mortality and/or general severity of COVID-19 were pooled for meta-analyses of the relationship of severe COVID-19 outcomes with hypertension as well as systolic and diastolic blood pressure. Genome-wide cross-trait meta-analysis (GWCTM) was performed to explore the genes linking between hypertension and COVID-19 severity.Results: The results of meta-analysis with the random effect model indicated that pooled risk ratios of hypertension on mortality and severity of COVID-19 were 1.80 [95% confidence interval (CI) 1.54–2.1] and 1.78 (95% confidence interval 1.56–2.04), respectively, although the apparent heterogeneity of the included studies was detected. In subgroup analysis, cohorts of severe and mild patients of COVID-19 assessed in Europe had a significant pooled weighted mean difference of 6.61 mmHg (95% CI 3.66–9.55) with no heterogeneity found (p = 0.26). The genes in the shared signature of hypertension and the COVID-19 severity were mostly expressed in lungs. Analysis of molecular networks commonly affected both by hypertension and by severe COVID-19 highlighted CCR1/CCR5 and IL10RB signaling, as well as Th1 and Th2 activation pathways, and also a potential for a shared regulation with multiple sclerosis.Conclusion: Hypertension is significantly associated with the severe course of COVID-19. Genetic variants within inflammation- and immunity-related genes may affect their expression in lungs and confer liability to both elevated blood pressure and to severe COVID-19.

Introduction: To evaluate Low-Molecular-Weight (LMW) DNA as a possible prognostic biomarker in acute ischemic and hemorrhagic stroke. Methods: LMW DNA samples were isolated from plasma and cerebrospinal fluid by phenol deproteinization, analyzed by gradient polyacrylamide electrophoresis and quantified by spectrophotometry. Results: Two common types of stroke, i.e. ischemic and hemorrhagic, differ by the temporal dynamics of cell-free DNA (cfDNA) accumulation. In hemorrhagic stroke, an initial increase in LMW DNA levels, most likely reflects an extent of the tissue damage, while in ischemic patients, the LMW DNA levels increase in parallel with the damage caused by hypoxia and subsequent compensatory reperfusion. Conclusion: These time-course data specify optimal assessment windows with maximum differentiating power for stroke outcomes: 24-48 hours post-event for ischemic stroke, and as close as possible to the moment of hospital admission for hemorrhagic stroke. These data also indicate the role of apoptosis in the formation of ischemic focus.

ObjectivesRecent studies suggest that asthma may have a protective effect on COVID-19.We aimed to investigate the causality between asthma and two COVID-19 outcomes and explore the mechanisms underlining this connection.MethodsSummary results of GWAS were used for the analyses, including asthma (88,486 cases and 447,859 controls), COVID-19 hospitalization (6,406 hospitalized COVID-19 cases and 902,088 controls), and COVID-19 infection (14,134 COVID-19 cases and 1,284,876 controls). The Mendelian randomization (MR) analysis was performed to evaluate the causal effects of asthma on the two COVID-19 outcomes. A cross-trait meta-analysis was conducted to analyze genetic variants within two loci shared by COVID-19 hospitalization and asthma.ResultsAsthma is associated with decreased risk both for COVID-19 hospitalization (odds ratio (OR): 0.70, 95% confidence interval (CI): 0.70-0.99) and for COVID-19 infection (OR: 0.83, 95%CI: 0.51-0.95). Asthma and COVID-19 share two genome-wide significant genes, including ABO at the 9q34.2 region and OAS2 at the 12q24.13 region. The meta-analysis revealed that ABO and ATXN2 contain variants with pleiotropic effects on both COVID-19 and asthma.ConclusionIn conclusion, our results suggest that genetic liability to asthma is associated with decreased susceptibility to SARS-CoV-2 and to severe COVID-19 disease, which may be due to the protective effects of ongoing inflammation and, possibly, related compensatory responses against COVID-19 in its early stage.

BACKGROUND Major depressive disorder (MDD) and posttraumatic stress disorder (PTSD) are highly comorbid and exhibit strong correlations with one another. We aimed to investigate mechanisms of underlying relationships between PTSD and 3 kinds of depressive phenotypes, namely, MDD, depressed affect (DAF), and depression (DEP, including both MDD and the broad definition of depression).METHODS Genetic correlations between PTSD and the depressive phenotypes were tested using linkage disequilibrium score regression. Polygenic overlap analysis was used to estimate shared and trait-specific causal variants across a pair of traits. Causal relationships between PTSD and the depressive phenotypes were investigated using Mendelian randomization. Shared genomic loci between PTSD and MDD were identified using cross-trait meta-analysis.RESULTS Genetic correlations of PTSD with the depressive phenotypes were in the range of 0.71–0.80. The estimated numbers of causal variants were 14,565, 12,965, 10,565, and 4,986 for MDD, DEP, DAF, and PTSD, respectively. In each case, causal variants contributing to PTSD were completely or largely covered by causal variants defining each of the depressive phenotypes. Mendelian randomization analysis indicated that the genetically determined depressive phenotypes confer a causal effect on PTSD (b = 0.21–0.31). Notably, genetically determined PTSD confers a causal effect on DEP (b = 0.14) and DAF (b = 0.15), but not MDD. Cross-trait meta-analysis of MDD and PTSD identified 47 genomic loci, including 29 loci shared between PTSD and MDD.CONCLUSION Evidence from shared genetics suggests that PTSD is a subtype of MDD. This study provides support to the efforts in reducing diagnostic heterogeneity in psychiatric nosology.FUNDING The National Key Research and Development Program of China and the National Natural Science Foundation of China.

Abstract The level of postvaccine protection depends on two factors: antibodies and T‐cell responses. While the first one is relatively easily measured, the measuring of the second one is a difficult problem. The recent studies indicate that the first one may be a good proxy for the protection, at least for SARS‐CoV‐2. The massive data currently gathered by both researcher and citizen scientists may be pivotal in confirming this observation, and the collective body of evidence is growing daily. This leads to an acceptance of IgG antibody levels as an accessible biomarker of individual's protection. With enormous and immediate need for assessing patient condition at the point of care, quantitative antibody analysis remains the most effective and efficient way to assess the protection against the disease. Let us not discount importance of reference points in the turmoil of current pandemics.

Major depressive disorder (MDD) is phenotypically associated with cardiovascular diseases (CVD). We aim to investigate mechanisms underlying relationships between MDD and CVD in the context of shared genetic variations. Polygenic overlap analysis was used to test genetic correlation and to analyze shared genetic variations between MDD and seven cardiovascular outcomes (coronary artery disease (CAD), heart failure, atrial fibrillation, stroke, systolic blood pressure, diastolic blood pressure, and pulse pressure measurement). Mendelian randomization analysis was used to uncover causal relationships between MDD and cardiovascular traits. By cross-trait meta-analysis, we identified a set of genomic loci shared between the traits of MDD and stroke. Putative causal genes for MDD and stroke were prioritized by fine-mapping of transcriptome-wide associations. Polygenic overlap analysis pointed toward substantial genetic variation overlap between MDD and CVD. Mendelian randomization analysis indicated that genetic liability to MDD has a causal effect on CAD and stroke. Comparison of genome-wide genes shared by MDD and CVD suggests 20q12 as a pleiotropic region conferring risk for both MDD and CVD. Cross-trait meta-analyses and fine-mapping of transcriptome-wide association signals identified novel risk genes for MDD and stroke, including RPL31P12, BORSC7, PNPT11, and PGF. Many genetic variations associated with MDD and CVD outcomes are shared, thus, pointing that genetic liability to MDD may also confer risk for stroke and CAD. Presented results shed light on mechanistic connections between MDD and CVD phenotypes.

Objectives: Uncovering the genetic basis of COVID-19 may shed insight into its pathogenesis and help to improve treatment measures. We aimed to investigate the host genetic variants associated with COVID-19.Methods: The summary result of a COVID-19 GWAS (9,373 hospitalized COVID-19 cases and 1,197,256 controls) was obtained from the COVID-19 Host Genetic Initiative GWAS meta-analyses. We tested colocalization of the GWAS signals of COVID-19 with expression and methylation quantitative traits loci (eQTL and mQTL, respectively) using the summary data-based Mendelian randomization (SMR) analysis. Four eQTL and two mQTL datasets were utilized in the SMR analysis, including CAGE blood eQTL data (n = 2,765), GTEx v7 blood (n = 338) and lung (n = 278) eQTL data, Geuvadis lymphoblastoid cells eQTL data, LBC-BSGS blood mQTL data (n = 1,980), and Hannon blood mQTL summary data (n = 1,175). We conducted a transcriptome-wide association study (TWAS) on COVID-19 with precomputed prediction models of GTEx v8 eQTL in lung and blood using S-PrediXcan.Results: Our SMR analyses identified seven protein-coding genes (TYK2, IFNAR2, OAS1, OAS3, XCR1, CCR5, and MAPT) associated with COVID-19, including two novel risk genes, CCR5 and tau-encoding MAPT. The TWAS revealed four genes for COVID-19 (CXCR6, CCR5, CCR9, and PIGN), including two novel risk genes, CCR5 and PIGN.Conclusion: Our study highlighted the functional relevance of some known genome-wide risk genes of COVID-19 and revealed novel genes contributing to differential outcomes of COVID-19 disease.

ObjectivesDeciphering the genetic relationships between major depressive disorder (MDD) and atopic diseases (asthma, hay fever, and eczema) may facilitate understanding of their biological mechanisms as well as the development of novel treatment regimens. Here we tested the genetic correlation between MDD and atopic diseases by linkage disequilibrium score regression.MethodsA polygenic overlap analysis was performed to estimate shared genetic variations between the two diseases. Causal relationships between MDD and atopic diseases were investigated using two-sample bidirectional Mendelian randomization analysis. Genomic loci shared between MDD and atopic diseases were identified using cross-trait meta-analysis. Putative functional genes were evaluated by fine-mapping of transcriptome-wide associations.ResultsThe polygenic analysis revealed approximately 15.8 thousand variants causally influencing MDD and 0.9 thousand variants influencing atopic diseases. Among these variants, approximately 0.8 thousand were shared between the two diseases. Mendelian randomization analysis indicates that genetic liability to MDD has a causal effect on atopic diseases (b = 0.22, p = 1.76 × 10-6), while genetic liability to atopic diseases confers a weak causal effect on MDD (b = 0.05, p = 7.57 × 10-3). Cross-trait meta-analyses of MDD and atopic diseases identified 18 shared genomic loci. Both fine-mapping of transcriptome-wide associations and analysis of existing literature suggest the estrogen receptor β-encoding gene ESR2 as one of the potential risk factors for both MDD and atopic diseases.ConclusionOur findings reveal shared genetic liability and causal links between MDD and atopic diseases, which shed light on the phenotypic relationship between MDD and atopic diseases.

The rapid rise and global consequences of the novel coronavirus disease 19 (COVID-19) have again brought the focus of the scientific community on the possible host factors involved in patient response and outcome to exposure to the virus. The disease severity remains highly unpredictable, and individuals with none of the aforementioned risk factors may still develop severe COVID-19. It was shown that genotype-related factors like an ABO Blood Group affect COVID-19 severity, and the risk of infection with SARS-CoV-2 was higher for patients with blood type A and lower for patients with blood type O. Currently it is not clear which specific genes are associated with COVID-19 severity. The comparative analysis of COVID-19 and other viral infections allows us to predict that the variants within the interferon pathway genes may serve as markers of the magnitude of immune response to specific pathogens. In particular, various members of Class III interferons (lambda) are reviewed in detail.

Food is the primary human source of choline, an essential precursor to the neurotransmitter acetylcholine, which has a central role in signaling pathways that govern sensorimotor functions. Most Americans do not consume their recommended amount of dietary choline, and populations with neurodevelopmental conditions like autism spectrum disorder (ASD) may be particularly vulnerable to consequences of choline deficiency. This study aimed to identify a relationship between ASD and cholinergic signaling through gene set enrichment analysis and interrogation of existing database evidence to produce a systems biology model. In gene set enrichment analysis, two gene ontologies were identified as overlapping for autism-related and for cholinergic pathways-related functions, both involving ion transport regulation. Subsequent modeling of ion transport intensive cholinergic signaling pathways highlighted the importance of two genes with autism-associated variants: GABBR1, which codes for the gamma aminobutyric acid receptor (GABAB1), and KCNN2, which codes for calcium-activated, potassium ion transporting SK2 channels responsible for membrane repolarization after cholinergic binding/signal transmission events. Cholinergic signal transmission pathways related to these proteins were examined in the Pathway Studio environment. The ion transport ontological associations indicated feasibility of a dietary choline support as a low-risk therapeutic intervention capable of modulating cholinergic sensory signaling in autism. Further research at the intersection of dietary status and sensory function in autism is warranted.

Background: Schizophrenia (SZ) is a severe chronic mental disorder with complex genetic mechanisms. Brain-derived neurotrophic factor (BDNF) is one of promising candidate genes for SZ, and rs6265 is a non-synonymous single nucleotide polymorphism (SNP) in BDNF.Methods: In this study, we performed a case-control association study of rs6265 in a cohort of Han Chinese population from eastern China, including 1,407 SZ patients and 1,136 healthy controls; and carried out a cis-mQTL (Methylation Quantitative Trait Loci) analysis for BDNF rs6265.Results: We found a positive association of rs6265 with SZ (P = 0.037), with the minor allele (A) of rs6265 conferring a protecting effect for SZ (OR = 0.89). Furthermore, cis-mQTL analysis indicates that rs6265 is associated with several methylation loci surrounding BDNF.Conclusions: Together, our findings provide further evidence to support the involvement of BDNF gene in the genesis of SZ.

Preeclampsia (PE) confers a significant risk for subsequent diagnosis with autism spectrum disorder (ASD), with the mechanisms underlying this observation being largely unknown. To identify molecular networks affected by both PE and ASD, we conducted a large-scale literature data mining and a gene set enrichment analysis (GSEA), followed by an expression mega-analysis in 13 independently profiled ASD datasets. Sets of genes implicated in ASD and in PE significantly overlap (156 common genes; p = 3.14E−67), with many biological pathways shared (94 pathways; p < 1.00E−21). A set of PE-driven molecular triggers possibly contributing to worsening the risk of subsequent ASD was identified, possibly representing a regulatory shift toward greater vulnerability to the development of ASD. Mega-analysis of expression highlighted RPS4Y1, an inhibitor of STAT3 that is expressed in a sexually dimorphic manner, as a contributor to both PE and ASD, which should be evaluated as a possible contributor to male predominance in ASD. A set of PE-driven molecular triggers may shift the developing brain toward a greater risk of ASD. One of these triggers, chromosome Y encoded gene RPS4Y1, an inhibitor of STAT3 signaling, warrants evaluation as a possible contributor to male predominance in ASD.

Pathogenesis of chronic obstructive pulmonary disease (COPD) is dependent on chronic inflammation and is hypothesized to represent organ-specific senescence phenotype. Identification of senescence-associated gene drivers for the development of COPD is warranted. By employing automated pipeline, we have compiled lists of the genes implicated in COPD (N = 918) and of the genes changing their activity along with cell senescence (N = 262), with a significant (p < 7.06e–60) overlap between these datasets (N = 89). A mega-analysis and a partial mega-analysis were conducted for gene sets linked to senescence but not yet to COPD, in nine independent mRNA expression datasets comprised of tissue samples of COPD cases (N = 171) and controls (N = 256). Mega-analysis of expression has identified CD38 and TNFRSF12A (p < 2.12e–8) as genes not yet explored in a context of senescence–COPD connection. Functional pathway enrichment analysis allowed to generate a model, which explains accelerated aging phenotypes previously observed in COPD patients. Presented results call for investigation of the role of TNFRSF12A/CD38 balance in establishing a vicious cycle of unresolvable tissue remodeling in COPD lungs.

BackgroundSchizophrenia risk genes are widely investigated, but a systemic analysis of miRNAs contributing to schizophrenia is lacking.MethodsSchizophrenia-associated genetic loci profiles were derived from a genome-wide association study (GWAS) from the Schizophrenia Working Group of the Psychiatric Genomics Consortium (PGC) dataset. Experimentally confirmed relationships between miRNAs and their target genes were retrieved from a miRTarBase. A competitive gene set association analysis for miRNA-target regulations was conducted by the Multi-marker Analysis of GenoMic Annotation (MAGMA) and further validated by literature-based functional pathway analysis using Pathway Studio. The association between the targets of three miRNAs and schizophrenia was further validated using a GWAS of antipsychotic treatment responses.ResultsThree novel schizophrenia-risk miRNAs, namely, miR-208b-3p, miR-208a-3p, and miR-494-5p, and their targetomes converged on calcium voltage-gated channel subunit alpha1 C (CACNA1C) and B-cell lymphoma 2 (BCL2), and these are well-known contributors to schizophrenia. Both miR-208a-3p and miR-208b-3p reduced the expression of the RNA-binding protein Quaking (QKI), whose suppression commonly contributes to demyelination of the neurons and to ischemia/reperfusion injury. On the other hand, both QKI and hsa-miR-494-5p were involved in gliomagenesis.ConclusionPresented results point at an orchestrating role of miRNAs in the pathophysiology of schizophrenia. The sharing of regulatory networks between schizophrenia and other pathologies may explain higher cardiovascular mortality and lower odds of glioma previously reported in psychiatric patients.

In contrast to traditional 2D cell cultures, both 3D models and organ-on-a-chip devices allow the study of the physiological responses of human cells. These models reconstruct human tissues in conditions closely resembling the body. Translation of these techniques into practice is hindered by associated labor costs, a need which may be remedied by automation. Impedance spectroscopy (IS) is a promising, automation-compatible label-free technology allowing to carry out a wide range of measurements both in real-time and as endpoints. IS has been applied to both the barrier cultures and the 3D constructs. Here we provide an overview of the impedance-based analysis in different setups and discuss its utility for organ-on-a-chip devices. Most attractive features of impedance-based assays are their compatibility with high-throughput format and supports for the measurements in real time with high temporal resolution, which allow tracing of the kinetics. As of now, IS-based techniques are not free of limitations, including imperfect understanding of the parameters that have their effects on the impedance, especially in 3D cell models, and relatively high cost of the consumables. Moreover, as the theory of IS stems from electromagnetic theory and is quite complex, work on popularization and explanation of the method for experimental biologists is required. It is expected that overcoming these limitations will lead to eventual establishing IS based systems as a standard for automated management of cell-based experiments in both academic and industry environments.

(1) Background: Brain-derived neurotrophic factor (BDNF) is one of the promising risk genes for schizophrenia (SZ), a disease with prominent dysregulation of miRNA networks. Here, we present a study of miRNA-BDNF co-expression changes in peripheral blood of SZ patients. (2) Methods: The expression levels of the BDNF mRNA and three validated binding miRNAs—miR-124-3p, miR-132-3p, and miR-206—were quantified in the blood of 48 healthy controls and 32 SZ patients before and after 12 weeks of treatment. The co-expression patterns were evaluated in the three groups. (3) Results: The expression levels of BDNF were significantly downregulated in SZ patients compared to the controls. After the treatment, the expression levels of BDNF were upregulated, while the expression levels of the three miRNAs were downregulated. Co-expression analyses showed positive correlations of this network in the SZ patients, while weak negative correlations were observed in the healthy controls. After the 12-week treatment, the overall correlation between BDNF and the three miRNAs reached the levels comparable to the healthy controls. (4) Conclusions: Our findings suggest the involvement of the miRNA-BDNF network in the onset and treatment of SZ.

Abstract Optogenetics has become widely recognized for its success in real-time control of brain neurons by utilizing non-mammalian photosensitive proteins to open or close membrane channels. Here we review a less well known type of optogenetic constructs that employs photosensitive proteins to transduce the signal to regulate gene transcription, and its possible use in medicine. One of the problems with existing gene therapies is that they could remain active indefinitely while not allowing regulated transgene production on demand. Optogenetic regulation of transcription (ORT) could potentially be used to regulate the production of a biological drug in situ, by repeatedly applying light to the tissue, and inducing expression of therapeutic transgenes when needed. Red and near infrared wavelengths, which are capable of penetration into tissues, have potential for therapeutic applications. Existing ORT systems are reviewed herein with these considerations in mind.

Abstract Background Cystic fibrosis (CF) is one of the most common life-threatening genetic disorders. Around 2000 variants in the CFTR gene have been identified, with some proportion known to be pathogenic and 300 disease-causing mutations have been characterized in detail by CFTR2 database, which complicates its analysis with conventional methods. Methods We conducted next-generation sequencing (NGS) in a cohort of 89 adult patients negative for p.Phe508del homozygosity. Complete clinical and demographic information were available for 84 patients. Results By combining MLPA with NGS, we identified disease-causing alleles in all the CF patients. Importantly, in 10% of cases, standard bioinformatics pipelines were inefficient in identifying causative mutations. Class IV-V mutations were observed in 38 (45%) cases, predominantly ones with pancreatic sufficient CF disease; rest of the patients had Class I-III mutations. Diabetes was seen only in patients homozygous for class I-III mutations. We found that 12% of the patients were heterozygous for more than two pathogenic CFTR mutations. Two patients were observed with p.[Arg1070Gln, Ser466*] complex allele which was associated with milder pulmonary obstructions (FVC 107 and 109% versus 67%, CI 95%: 63-72%; FEV 90 and 111% versus 47%, CI 95%: 37-48%). For the first time p.[Phe508del, Leu467Phe] complex allele was reported, observed in four patients (5%). Conclusion NGS can be a more information-gaining technology compared to standard methods. Combined with its equivalent diagnostic performance, it can therefore be implemented in the clinical practice, although careful validation is still required.

Alzheimer’s disease (AD) is marked by chronic neurodegeneration associated with the occurrence of plaques containing amyloid β (Aβ) proteins in various parts of the human brain. An increase in several Aβ fragments is well documented in patients with AD and anti-amyloid targeting is an emerging area of therapy. Soluble Aβ can bind to various cell surface and intracellular molecules with the pathogenic Aβ42 fragment leading to neurotoxicity. Here we examined the effect of Aβ42 on network adaptations in the proteome of nerve growth factor (NGF) differentiated PC12 cells using liquid-chromatography electrospray ionization mass spectrometry (LC-ESI MS/MS) proteomics. Whole-cell peptide mass fingerprinting was coupled to bioinformatic gene set enrichment analysis (GSEA) in order to identify differentially represented proteins and related gene ontology (GO) pathways within Aβ42 treated cells. Our results underscore a role for Aβ42 in disrupting proteome responses for signaling, bioenergetics, and morphology in mitochondria. These findings highlight the specific components of the mitochondrial response during Aβ42 neurotoxicity and suggest several new biomarkers for detection and surveillance of amyloid disease.

Abstract Background The history of human populations occupying the plains and mountain ridges separating Europe from Asia has been eventful, as these natural obstacles were crossed westward by multiple waves of Turkic and Uralic-speaking migrants as well as eastward by Europeans. Unfortunately, the material records of history of this region are not dense enough to reconstruct details of population history. These considerations stimulate growing interest to obtain a genetic picture of the demographic history of migrations and admixture in Northern Eurasia. Results We genotyped and analyzed 1076 individuals from 30 populations with geographical coverage spanning from Baltic Sea to Baikal Lake. Our dense sampling allowed us to describe in detail the population structure, provide insight into genomic history of numerous European and Asian populations, and significantly increase quantity of genetic data available for modern populations in region of North Eurasia. Our study doubles the amount of genome-wide profiles available for this region. We detected unusually high amount of shared identical-by-descent (IBD) genomic segments between several Siberian populations, such as Khanty and Ket, providing evidence of genetic relatedness across vast geographic distances and between speakers of different language families. Additionally, we observed excessive IBD sharing between Khanty and Bashkir, a group of Turkic speakers from Southern Urals region. While adding some weight to the “Finno-Ugric” origin of Bashkir, our studies highlighted that the Bashkir genepool lacks the main “core”, being a multi-layered amalgamation of Turkic, Ugric, Finnish and Indo-European contributions, which points at intricacy of genetic interface between Turkic and Uralic populations. Comparison of the genetic structure of Siberian ethnicities and the geography of the region they inhabit point at existence of the “Great Siberian Vortex” directing genetic exchanges in populations across the Siberian part of Asia. Slavic speakers of Eastern Europe are, in general, very similar in their genetic composition. Ukrainians, Belarusians and Russians have almost identical proportions of Caucasus and Northern European components and have virtually no Asian influence. We capitalized on wide geographic span of our sampling to address intriguing question about the place of origin of Russian Starovers, an enigmatic Eastern Orthodox Old Believers religious group relocated to Siberia in seventeenth century. A comparative reAdmix analysis, complemented by IBD sharing, placed their roots in the region of the Northern European Plain, occupied by North Russians and Finno-Ugric Komi and Karelian people. Russians from Novosibirsk and Russian Starover exhibit ancestral proportions close to that of European Eastern Slavs, however, they also include between five to 10 % of Central Siberian ancestry, not present at this level in their European counterparts. Conclusions Our project has patched the hole in the genetic map of Eurasia: we demonstrated complexity of genetic structure of Northern Eurasians, existence of East-West and North-South genetic gradients, and assessed different inputs of ancient populations into modern populations.

Abstract Background With 15,949 markers, the low-density Infinium QC Array-24 BeadChip enables linkage analysis, HLA haplotyping, fingerprinting, ethnicity determination, mitochondrial genome variations, blood groups and pharmacogenomics. It represents an attractive independent QC option for NGS-based diagnostic laboratories, and provides cost-efficient means for determining gender, ethnic ancestry, and sample kinships, that are important for data interpretation of NGS-based genetic tests. Methods We evaluated accuracy and reproducibility of Infinium QC genotyping calls by comparing them with genotyping data of the same samples from other genotyping platforms, whole genome/exome sequencing. Accuracy and robustness of determining gender, provenance, and kinships were assessed. Results Concordance of genotype calls between Infinium QC and other platforms was above 99%. Here we show that the chip’s ancestry informative markers are sufficient for ethnicity determination at continental and sometimes subcontinental levels, with assignment accuracy varying with the coverage for a particular region and ethnic groups. Mean accuracies of provenance prediction at a regional level were varied from 81% for Asia, to 89% for Americas, 86% for Africa, 97% for Oceania, 98% for Europe, and 100% for India. Mean accuracy of ethnicity assignment predictions was 63%. Pairwise concordances of AFR samples with the samples from any other super populations were the lowest (0.39–0.43), while the concordances within the same population were relatively high (0.55–0.61). For all populations except African, cross-population comparisons were similar in their concordance ranges to the range of within-population concordances (0.54–0.57). Gender determination was correct in all tested cases. Conclusions Our results indicate that the Infinium QC Array-24 chip is suitable for cost-efficient, independent QC assaying in the settings of an NGS-based molecular diagnostic laboratory; hence, we recommend its integration into the standard laboratory workflow. Low-density chips can provide sample-specific measures for variant call accuracy, prevent sample mix-ups, validate self-reported ethnicities, and detect consanguineous cases. Integration of low-density chips into QC procedures aids proper interpretation of candidate sequence variants. To enhance utility of this low-density chip, we recommend expansion of ADME and mitochondrial markers. Inexpensive Infinium-like low-density human chips have a potential to become a “Swiss army knife” among genotyping assays suitable for many applications requiring high-throughput assays.

Specificity of RNAi to selected target is challenged by off-target effects, both canonical and non-canonical. Notably, more than half of all human microRNAs are co-expressed with hosting them proteincoding genes. Here we dissect regulatory subnetwork centered on IGFBP6 gene, which is associated with low proliferative state and high migratory activity of basal-like breast cancer. We inhibited expression of IGFBP6 gene in a model cell line for basal-like breast carcinoma MDA-MB-231, then traced secondary and tertiary effects of this knockdown to LAMA4, a laminin encoding gene that contributes to the phenotype of triple-negative breast cancer. LAMA4-regulating miRNA miR-4274 and its host gene SORCS2 were highlighted as intermediate regulators of the expression levels of LAMA4, which correlated in a basal-like breast carcinoma sample subset of TCGA to the levels of SORCS2 negatively. Overall, our study points that the secondary and tertiary layers of regulatory interactions are certainly underappreciated. As these types of molecular event may significantly contribute to the formation of the cell phenotypes after RNA interference based knockdowns, further studies of multilayered molecular networks affected by RNAi are warranted.

MicroRNAs play a key role in the regulation of gene expression. A majority of microRNA–mRNA interactions remain unidentified. Despite extensive research, our ability to predict human microRNA-mRNA interactions using computational algorithms remains limited by a complexity of the models for non-canonical interactions, and an abundance of false-positive results. Here, we present the landscape of human microRNA–mRNA interactions derived from comprehensive analysis of HEK293 and Huh7.5 datasets, along with publicly available microRNA and mRNA expression data. We show that, while only 1–2% of human genes were the most regulated by microRNAs, few cell line–specific RNAs, including EEF1A1 and HSPA1B in HEK293 and AFP, APOB, and MALAT1 genes in Huh7.5, display substantial “sponge-like” properties. We revealed a group of microRNAs that are expressed at a very high level, while interacting with only a few mRNAs, which, indeed, serve as their specific expression regulators. In order to establish reliable microRNA-binding regions, we collected and systematically analyzed the data from 79 CLIP datasets of microRNA-binding sites. We report 46,805 experimentally confirmed mRNA–miRNA duplex regions. Resulting dataset is available at http://score.generesearch.ru/services/mirna/. Our study provides initial insight into the complexity of human microRNA–mRNA interactions.

Genotyping of cell-free DNA (cfDNA) in plasma samples has the potential to allow for a noninvasive assessment of tumor biology, avoiding the inherent shortcomings of tissue biopsy. Next generation sequencing (NGS), a leading technology for liquid biopsy analysis, continues to be hurdled with several major issues with cfDNA samples, including low cfDNA concentration and high fragmentation. In this study, by employing Ion Torrent PGM semiconductor technology, we performed a comparison between two multi-biomarker amplicon-based NGS panels characterized by a substantial difference in average amplicon length. In course of the analysis of the peripheral blood from 13 diagnostic non-small cell lung cancer patients, equivalence of two panels, in terms of overall diagnostic sensitivity and specificity was shown. A pairwise comparison of the allele frequencies for the same somatic variants obtained from the pairs of panel-specific amplicons, demonstrated an identical analytical sensitivity in range of 140 to 170 bp amplicons in size. Further regression analysis between amplicon length and its coverage, illustrated that NGS sequencing of plasma cfDNA equally tolerates amplicons with lengths in the range of 120 to 170 bp. To increase the sensitivity of mutation detection in cfDNA, we performed a computational analysis of the features associated with genome-wide nucleosome maps, evident from the data on the prevalence of cfDNA fragments of certain sizes and their fragmentation patterns. By leveraging the support vector machine-based machine learning approach, we showed that a combination of nucleosome map associated features with GC content, results in the increased accuracy of prediction of high inter-sample sequencing coverage variation (areas under the receiver operating curve: 0.75, 95% CI: 0.750–0.752 vs. 0.65, 95% CI: 0.63–0.67). Thus, nucleosome-guided fragmentation should be utilized as a guide to design amplicon-based NGS panels for the genotyping of cfDNA samples.

Gene set analysis (GSA) has become the common methodology for analyzing transcriptomics data. However, self-contained GSA techniques are rarely, if ever, used for proteomics data analysis. Here we present a self-contained proteome level GSA of four consensus molecular subtypes (CMSs) previously established by transcriptome dissection of colon carcinoma specimens. Despite notable difference in structure of proteomics and transcriptomics data, many pathway-wide characteristic features of CMSs found at the mRNA level were reproduced at the protein level. In particular, CMS1 features show heavy involvement of immune system as well as the pathways related to mismatch repair, DNA replication and functioning of proteasome, while CMS4 tumors upregulate complement pathway and proteins participating in epithelial-to-mesenchymal transition (EMT). In addition, protein level GSA yielded a set of novel observations visible at the proteome, but not at the transcriptome level, including possible involvement of major histocompatibility complex II (MHC-II) antigens in the known immunogenicity of CMS1 and a connection between cholesterol trafficking and the regulation of Integrin-linked kinase (ILK) in CMS3. Overall, this study proves utility of self-contained GSA approaches as a critical tool for analyzing proteomics data in general and dissecting protein-level molecular portraits of human tumors in particular.

Preventive treatments for dementia are warranted. Here we show that utilization of certain combinations of prescription medications and supplements correlates with reduced rates of cognitive decline. More than 1,900 FDA-approved agents and supplements were collapsed into 53 mechanism-based groups and traced in electronic medical records (EMRs) for >50,000 patients. These mechanistic groups were aligned with the data presented in more than 300 clinical trials, then regression model was built to fit the signals from EMRs to clinical trial performance. While EMR signals of each single agents correlated with clinical performance relatively weakly, the signals produced by combinations of active compounds were highly correlated with the clinical trial performance (R = 0.93, p = 3.8 x10^-8). Higher ranking pharmacological modalities were traced in patient profiles as their combinations, producing protective complexity estimates reflecting degrees of exposure to beneficial polypharmacy. For each age strata, the higher was the protective complexity score, the lower was the prevalence of dementia, with maximized life-long effects for the highest regression score /diversity compositions. The connection was less strong in individuals already diagnosed with cognitive impairment. Confounder analysis confirmed an independent effect of protective complexity in multivariate context. A sub-cohort with lifelong odds of dementia decreased > 5-folds was identified; this sub-cohort should be studied in further details, including controlled clinical trials. In short, our study systematically explored combinatorial preventive treatment regimens for age-associated multi-morbidity, with an emphasis on neurodegeneration, and provided extensive evidence for their feasibility.

Here we present a study of the thermal inactivation and the refolding of the proteins in Gram positive Bacillus subtilis. To enable use of bacterial luciferases as the models for protein thermal inactivation and refolding in B. subtilis cells, we developed a variety of bright luminescent B. subtilis strains which express luxAB genes encoding luciferases of differing thermolability. The kinetics of the thermal inactivation and the refolding of luciferases from Photorhabdus luminescens and Photobacterium leiognathi were compared in Gram negative and Gram positive bacteria. In B. subtilis cells, these luciferases are substantially more thermostable than in Escherichia coli. Thermal inactivation of the thermostable luciferase P. luminescens in B. subtilis at 48.5°С behaves as a first-order reaction. In E.coli, the first order rate constant (Kt) of the thermal inactivation of luciferase in E. coli exceeds that observed in B. subtilis cells 2.9 times. Incubation time dependence curves for the thermal inactivation of the thermolabile luciferase of P. leiognathi luciferase in the cells of E. coli and B. subtilis may be described by first and third order kinetics, respectively. Here we shown that the levels and the rates of refolding of thermally inactivated luciferases in B. subtilis cells are substantially lower that that observed in E. coli. In dnaK-negative strains of B. subtilis, both the rates of thermal inactivation and the efficiency of refolding are similar to that observed in wild-type strains. These experiments point that the role that DnaKJE plays in thermostability of luciferases may be limited to bacterial species resembling E. coli.

Non-alcoholic fatty liver disease (NAFLD) is the worldwide most common cause of chronic liver pathology, which prevalence strongly correlates with the increasing incidence of diabetes, obesity and metabolic syndrome in the general population. Simple steatosis, the earliest NAFLD stage, usually remains asymptomatic, and appropriate changes in the lifestyle, as well as the diet, can reverse the affected liver into the healthy state. The potential of simple steatosis to progress into severe fibrotic stages and to facilitate carcinogenesis necessitates timely NAFLD detection and risk stratification in community-based healthcare settings. Since their initial discovery a decade ago, extracellular circulating miRNAs have been found in all human biological fluids including blood and shown to hold great promises as non-invasive biomarkers. Normally, intracellular miRNAs participate in the regulation of gene expression, but once released by dying/dead cells they remain highly stable in the extracellular environment for prolonged periods. Therefore, circulating miRNA profiles can reflect the ongoing pathogenic processes in body’s tissues and organs, and enable highly sensitive non-invasive diagnosis of multiple disorders. A non-urgent character of the NAFLD-related decision-making justifies the use of chronic liver diseases as an excellent test case for examining the practical utility of circulating miRNAs as biomarkers for longitudinal monitoring of human health. In this review, we summarize the state-of-the-art in the field of early diagnosis of NAFLD using circulating blood miRNAs, and stress the necessity of additional experimental validation of their diagnostic potential. We further emphasize on the potential diagnostics promises of other cell-free RNA species found in human biological fluids.

Non-alcoholic fatty liver disease (NAFLD) is a hepatic manifestation of metabolic syndrome and major cause of chronic liver disease in developed countries. Its prevalence is increasing in parallel with the prevalence of obesity and other components of the metabolic syndrome. As the liver is central to the clearance and catabolism of circulating advanced glycosylation end-products (AGEs), AGEs and their cognate receptors-RAGE (receptor for AGEs) system might be involved in NAFLD in obese patients. To examine this, we investigated four common polymorphisms of RAGE gene: 1704G/T (rs184003), G82S (rs2070600), -374T/A (rs1800624) and -429T/C (rs1800625) in 340 obese patients with metabolic syndrome. and protein levels of AGE and RAGE. This is the first study to describe association of 4 common polymorphisms with non-alcoholic steatohepatitis (NASH) as well as to examine protein levels of RAGE and AGE. Univariate analysis showed patients carrying the rs1800624 heterozygote genotype (AT) exhibited 2.36-fold increased risk of NASH (odds ratio (OR) = 2.36; 95% confidence interval (95% CI): 1.35-4.19) after adjusting for confounders. The minor allele -374 A has been shown to suppress the expression of RAGE protein. The protein levels of esRAGE, total sRAGE and AGE protein levels did not correlate with each other in obese patients with no liver disease, indicative of RAGE signaling playing an independent role in liver injury. In obese patients with non-NASH NAFLD and NASH respectively, esRAGE protein showed strong positive correlation with total sRAGE protein. Further, haplotype analysis of the 4 SNPs, indicated that haplotype G-A-T-G was significantly associated with 2-fold increased risk for NASH (OR = 2.08; 95% CI: 1.21-3.5; P = 0.006) after adjusting for confounders. In conclusion, the presented data indicate that the G-A-T-G haplotype containing minor allele at position -374 A and major allele at position -429T, 1704G, and G82S G could be regarded as a marker for NASH.