Transcranial photobiomodulation and thermal stimulation induce distinct topographies of EEG alpha and beta power changes in healthy humans

Our recent study demonstrated that prefrontal transcranial photobiomodulation (tPBM) with 1064-nm laser enables significant changes in EEG rhythms, but these changes might result from the laser-induced heat rather than tPBM. This study hypothesized that tPBM-induced and heat-induced alterations in EEG power topography were significantly distinct. We performed two sets of measurements from two separate groups of healthy humans under tPBM (n = 46) and thermal stimulation (thermo_stim; n = 11) conditions. Each group participated in the study twice under true and respective sham stimulation with concurrent recordings of 64-channel EEG before, during, and after 8-min tPBM at 1064 nm or thermo_stim with temperature of 33–41 °C, respectively. After data preprocessing, EEG power spectral densities (PSD) per channel per subject were quantified and normalized by respective baseline PSD to remove the power-law effect. At the group level for each group, percent changes of EEG powers per channel were statistically compared between (1) tPBM vs light-stimulation sham, (2) thermo_stim vs heat-stimulation sham, and (3) tPBM vs thermo_stim after sham exclusion at five frequency bands using the non-parametric permutation tests. By performing the false discovery rate correction for multi-channel comparisons, we showed by EEG power change topographies that (1) tPBM significantly increased EEG alpha and beta powers, (2) the thermal stimulation created opposite effects on EEG power topographic patterns, and (3) tPBM and thermal stimulations induced significantly different topographies of changes in EEG alpha and beta power. Overall, this study provided evidence to support our hypothesis, showing that the laser-induced heat on the human forehead is not a mechanistic source causing increases in EEG power during and after tPBM.

Association between C-Maf-inducing protein gene rs2287112 polymorphism and schizophrenia

Background Schizophrenia is a severely multifactorial neuropsychiatric disorder, and the majority of cases are due to genetic variations. In this study, we evaluated the genetic association between the C-Maf-inducing protein (CMIP) gene and schizophrenia in the Han Chinese population. Methods In this case-control study, 761 schizophrenia patients and 775 healthy controls were recruited. Tag single-nucleotide polymorphisms (SNPs; rs12925980, rs2287112, rs3751859 and rs77700579) from the CMIP gene were genotyped via matrix-assisted laser desorption/ionization time of flight mass spectrometry. We used logistic regression to estimate the associations between the genotypes/alleles of each SNP and schizophrenia in males and females, respectively. The in-depth link between CMIP and schizophrenia was explored through linkage disequilibrium (LD) and further haplotype analyses. False discovery rate correction was utilized to control for Type I errors caused by multiple comparisons. Results There was a significant difference in rs287112 allele frequencies between female schizophrenia patients and healthy controls after adjusting for multiple comparisons (χ2 = 12.296, Padj = 0.008). Females carrying minor allele G had 4.445 times higher risk of schizophrenia compared with people who carried the T allele (OR = 4.445, 95% CI [1.788–11.046]). Linkage-disequilibrium was not observed in the subjects, and people with haplotype TTGT of rs12925980–rs2287112–rs3751859–rs77700579 had a lower risk of schizophrenia (OR = 0.42, 95% CI [0.19–0.94]) when compared with CTGA haplotypes. However, the association did not survive false discovery rate correction. Conclusion This study identified a potential CMIP variant that may confer schizophrenia risk in the female Han Chinese population.

Paired maternal and fetal metabolomics reveal a differential fingerprint in preeclampsia versus fetal growth restriction

Preeclampsia (PE) and fetal growth restriction (FGR) are both placenta-mediated disorders with unclear pathogenesis. Metabolomics of maternal and fetal pairs might help in understanding these disorders. We recruited prospectively pregnancies with normotensive FGR, PE without FGR, PE + FGR and uncomplicated pregnancies as controls. Nuclear magnetic resonance metabolomics were applied on plasma samples collected at delivery. Advanced lipoprotein, glycoprotein and choline profiling was performed using the Liposcale test. The software package Dolphin was used to quantify 24 low-molecular-weight metabolites. Statistical analysis comprised the comparison between each group of complicated pregnancies versus controls, considering 5% false discovery rate correction. Lipid profiles were altered in accordance with the clinical presentation of these disorders. Specifically, PE mothers and FGR fetuses (with or without FGR or PE, respectively) exhibited a pro-atherogenic and pro-inflammatory profile, with higher concentrations of triglycerides, remnant cholesterol (VLDL, IDL) and Glc/GalNAc-linked and lipid-associated glycoproteins compared to controls. Low-molecular-weight metabolites were extensively disturbed in preeclamptic mothers, with or without FGR. Growth restricted fetuses in the presence of PE showed changes in low-molecular-weight metabolites similar to their mothers (increased creatine and creatinine), while normotensive FGR fetuses presented scarce differences, consistent with undernutrition (lower isoleucine). Further research is warranted to clarify maternal and fetal adaptations to PE and FGR.

Regional variations in adverse event reporting rates and ACR responses in placebo/standard-of-care arms of rheumatoid arthritis trials

Objective Clinical trials are increasingly globalized, and adverse event (AE) rates and treatment responses may differ by geographical region. This study assessed regional differences in AE reporting rates and ACR response rates (ACR20/50) in patients with RA who received placebo/standard-of-care treatment in clinical trials. Methods Patients from the placebo arms of 7 RA trials in the TransCelerate Biopharma Inc database were grouped into 5 geographical regions (Asia, Latin America, Russian Federation and Eastern Europe [RFEE], USA, and Western Europe). Differences in demographics, AE reporting rates and ACR response were evaluated using descriptive statistics and omnibus tests for significance; pairwise comparisons were made between regions, with false discovery rate correction for multiple comparisons. Results Among 970 patients included, week 12 AE rates were significantly lower in the RFEE than in Asia, Latin America and the USA (22% vs 51%, 49% and 53%, respectively; P < 0.05 after false discovery rate correction). Similar differences in AE rates across geographical regions were seen at week 52. Among 747 patients with ACR data, the lowest response rates were observed in the USA (ACR20, 22%) and RFEE (ACR50, 3%); the highest response rates were seen in Western Europe (ACR20, 43%) and Latin America (ACR50, 15%). Only the differences in ACR50 response between the RFEE and Latin America remained significant after false discovery rate correction. Conclusion These placebo/standard-of-care arm data revealed significant regional differences in AE reporting rates and ACR50 response rates. Regional distribution of patients should be considered when conducting RA clinical trials, particularly during recruitment.

Metabolomic changes associated with frontotemporal lobar degeneration syndromes

ObjectiveWidespread metabolic changes are seen in neurodegenerative disease and could be used as biomarkers for diagnosis and disease monitoring. They may also reveal disease mechanisms that could be a target for therapy. In this study we looked for blood-based biomarkers in syndromes associated with frontotemporal lobar degeneration.MethodsPlasma metabolomic profiles were measured from 134 patients with frontotemporal lobar degeneration (behavioural variant frontotemporal dementia n=30, non fluent variant primary progressive aphasia n=26, progressive supranuclear palsy n=45, corticobasal syndrome n=33) and 32 healthy controls.ResultsForty-nine of 842 metabolites were significantly altered in frontotemporal lobar degeneration (after false-discovery rate correction for multiple comparisons). These were distributed across a wide range of metabolic pathways including amino acids, energy and carbohydrate, cofactor and vitamin, lipid and nucleotide pathways. The metabolomic profile supported classification between frontotemporal lobar degeneration and controls with high accuracy (88.1-96.6%) while classification accuracy was lower between the frontotemporal lobar degeneration syndromes (72.1-83.3%). One metabolic profile, comprising a range of different pathways, was consistently identified as a feature of each disease versus controls: the degree to which a patient expressed this metabolomic profile was associated with their subsequent survival (hazard ratio 0.74 [0.59-0.93], p = 0.0018).ConclusionsThe metabolic changes in FTLD are promising diagnostic and prognostic biomarkers. Further work is required to replicate these findings, examine longitudinal change, and test their utility in differentiating between FTLD syndromes that are pathologically distinct but phenotypically similar.

HotSpotAnnotations—a database for hotspot mutations and annotations in cancer

Hotspots, recurrently mutated DNA positions in cancer, are thought to be oncogenic drivers because random chance is unlikely and the knowledge of clear examples of oncogenic hotspots in genes like BRAF, IDH1, KRAS and NRAS among many other genes. Hotspots are attractive because provide opportunities for biomedical research and novel treatments. Nevertheless, recent evidence, such as DNA hairpins for APOBEC3A, suggests that a considerable fraction of hotspots seem to be passengers rather than drivers. To document hotspots, the database HotSpotsAnnotations is proposed. For this, a statistical model was implemented to detect putative hotspots, which was applied to TCGA cancer datasets covering 33 cancer types, 10 182 patients and 3 175 929 mutations. Then, genes and hotspots were annotated by two published methods (APOBEC3A hairpins and dN/dS ratio) that may inform and warn researchers about possible false functional hotspots. Moreover, manual annotation from users can be added and shared. From the 23 198 detected as possible hotspots, 4435 were selected after false discovery rate correction and minimum mutation count. From these, 305 were annotated as likely for APOBEC3A whereas 442 were annotated as unlikely. To date, this is the first database dedicated to annotating hotspots for possible false functional hotspots.