Searching for Imaging Biomarkers of Psychotic Dysconnectivity

Background: Progress in precision psychiatry is predicated on identifying reliable individual-level diagnostic biomarkers. For psychosis, measures of structural and functional connectivity could be promising biomarkers given consistent reports of dysconnectivity across psychotic disorders using magnetic resonance imaging. Methods: We leveraged data from four independent cohorts of patients with psychosis and control subjects with observations from approximately 800 individuals. We used group-level analyses and two supervised machine learning algorithms (support vector machines and ridge regression) to test within-, between-, and across-sample classification performance of white matter and resting-state connectivity metrics. Results: Although we replicated group-level differences in brain connectivity, individual-level classification was suboptimal. Classification performance within samples was variable across folds (highest area under the curve [AUC] range = 0.30) and across datasets (average support vector machine AUC range = 0.50; average ridge regression AUC range = 0.18). Classification performance between samples was similarly variable or resulted in AUC values of approximately 0.65, indicating a lack of model generalizability. Furthermore, collapsing across samples (resting-state functional magnetic resonance imaging, N = 888; diffusion tensor imaging, N = 860) did not improve model performance (maximal AUC = 0.67). Ridge regression models generally outperformed support vector machine models, although classification performance was still suboptimal in terms of clinical relevance. Adjusting for demographic covariates did not greatly affect results. Conclusions: Connectivity measures were not suitable as diagnostic biomarkers for psychosis as assessed in this study. Our results do not negate that other approaches may be more successful, although it is clear that a systematic approach to individual-level classification with large independent validation samples is necessary to properly vet neuroimaging features as diagnostic biomarkers

Family-based analyses reveal novel genetic overlap between cytokine interleukin-8 and risk for suicide attempt

Background: Suicide is major public health concern. It is imperative to find robust biomarkers so that at-risk individuals can be identified in a timely and reliable manner. Previous work suggests mechanistic links between increased cytokines and risk for suicide, but questions remain regarding the etiology of this association, as well as the roles of sex and BMI. Methods: Analyses were conducted using a randomly-ascertained extended-pedigree sample of 1882 Mexican-American individuals (60% female, mean age = 42.04, range = 18-97). Genetic correlations were calculated using a variance components approach between the cytokines TNF-α, IL-6 and IL-8, and Lifetime Suicide Attempt and Current Suicidal Ideation. The potentially confounding effects of sex and BMI were considered. Results: 159 individuals endorse a Lifetime Suicide Attempt. IL-8 and IL-6 shared significant genetic overlap with risk for suicide attempt (ρg = 0.49, pFDR = 7.67 × 10-03; ρg = 0.53, pFDR = 0.01), but for IL-6 this was attenuated when BMI was included as a covariate (ρg = 0.37, se = 0.23, pFDR = 0.12). Suicide attempts were significantly more common in females (pFDR = 0.01) and the genetic overlap between IL-8 and risk for suicide attempt was significant in females (ρg = 0.56, pFDR = 0.01), but not in males (ρg = 0.44, pFDR = 0.30). Discussion: These results demonstrate that: IL-8 shares genetic influences with risk for suicide attempt; females drove this effect; and BMI should be considered when assessing the association between IL-6 and suicide. This finding represents a significant advancement in knowledge by demonstrating that cytokine alterations are not simply a secondary manifestation of suicidal behavior, but rather, the pathophysiology of suicide attempts is, at least partly, underpinned by the same biological mechanisms responsible for regulating inflammatory response

Neurocognitive impairment in type 2 diabetes: evidence for shared genetic aetiology

Aims/hypothesis: Type 2 diabetes is associated with cognitive impairments, but it is unclear whether common genetic factors influence both type 2 diabetes risk and cognition. Methods: Using data from 1892 Mexican-American individuals from extended pedigrees, including 402 with type 2 diabetes, we examined possible pleiotropy between type 2 diabetes and cognitive functioning, as measured by a comprehensive neuropsychological test battery. Results: Negative phenotypic correlations (ρp) were observed between type 2 diabetes and measures of attention (Continuous Performance Test [CPT d\u27]: ρp = -0.143, p = 0.001), verbal memory (California Verbal Learning Test [CVLT] recall: ρp = -0.111, p = 0.004) and face memory (Penn Face Memory Test [PFMT]: ρp = -0.127, p = 0.002; PFMT Delayed: ρp = -0.148, p = 2 × 10-4), replicating findings of cognitive impairment in type 2 diabetes. Negative genetic correlations (ρg) were also observed between type 2 diabetes and measures of attention (CPT d\u27: ρg = -0.401, p = 0.001), working memory (digit span backward test: ρg = -0.380, p = 0.005), and face memory (PFMT: ρg = -0.476, p = 2 × 10-4; PFMT Delayed: ρg = -0.376, p = 0.005), suggesting that the same genetic factors underlying risk for type 2 diabetes also influence poor cognitive performance in these domains. Performance in these domains was also associated with type 2 diabetes risk using an endophenotype ranking value approach. Specifically, on measures of attention (CPT d\u27: β = -0.219, p = 0.005), working memory (digit span backward: β = -0.326, p = 0.035), and face memory (PFMT: β = -0.171, p = 0.023; PFMT Delayed: β = -0.215, p = 0.005), individuals with type 2 diabetes showed the lowest performance, while unaffected/unrelated individuals showed the highest performance, and those related to an individual with type 2 diabetes performed at an intermediate level. Conclusions/interpretation: These findings suggest that cognitive impairment may be a useful endophenotype of type 2 diabetes and, therefore, help to elucidate the pathophysiological underpinnings of this chronic disease. Data availability: The data analysed in this study is available in dbGaP: www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001215.v2.p2

The Genetic contribution to solving the cocktail-party problem

Communicating in everyday situations requires solving the cocktail-party problem, or segregating the acoustic mixture into its constituent sounds and attending to those of most interest. Humans show dramatic variation in this ability, leading some to experience real-world problems irrespective of whether they meet criteria for clinical hearing loss. Here, we estimated the genetic contribution to cocktail-party listening by measuring speech-reception thresholds (SRTs) in 425 people from large families and ranging in age from 18 to 91 years. Roughly half the variance of SRTs was explained by genes (h 2 = 0.567). The genetic correlation between SRTs and hearing thresholds (HTs) was medium (ρ G = 0.392), suggesting that the genetic factors influencing cocktail-party listening were partially distinct from those influencing sound sensitivity. Aging and socioeconomic status also strongly influenced SRTs. These findings may represent a first step toward identifying genes for hidden hearing loss, or hearing problems in people with normal HTs

Experimental determination of translational start sites resolves uncertainties in genomic open reading frame predictions – application to Mycobacterium tuberculosis

Correct identification of translational start sites is important for understanding protein function and transcriptional regulation. The annotated translational start sites contained in genome databases are often predicted using bioinformatics and are rarely verified experimentally, and so are not all accurate. Therefore, we devised a simple approach for determining translational start sites using a combination of epitope tagging and frameshift mutagenesis. This assay was used to determine the start sites of three Mycobacterium tuberculosis proteins: LexA, SigC and Rv1955. We were able to show that proteins may begin before or after the predicted site. We also found that a small, non-annotated open reading frame upstream of Rv1955 was expressed as a protein, which we have designated Rv1954A. This approach is readily applicable to any bacterial species for which plasmid transformation can be achieved

Association of Mitochondrial DNA Copy Number With Brain MRI Markers and Cognitive Function: A Meta-Analysis of Community-Based Cohorts

BACKGROUND AND OBJECTIVES: Previous studies suggest that lower mitochondrial DNA (mtDNA) copy number (CN) is associated with neurodegenerative diseases. However, whether mtDNA CN in whole blood is related to endophenotypes of Alzheimer disease (AD) and AD-related dementia (AD/ADRD) needs further investigation. We assessed the association of mtDNA CN with cognitive function and MRI measures in community-based samples of middle-aged to older adults. METHODS: We included dementia-free participants from 9 diverse community-based cohorts with whole-genome sequencing in the Trans-Omics for Precision Medicine (TOPMed) program. Circulating mtDNA CN was estimated as twice the ratio of the average coverage of mtDNA to nuclear DNA. Brain MRI markers included total brain, hippocampal, and white matter hyperintensity volumes. General cognitive function was derived from distinct cognitive domains. We performed cohort-specific association analyses of mtDNA CN with AD/ADRD endophenotypes assessed within ±5 years (i.e., cross-sectional analyses) or 5-20 years after blood draw (i.e., prospective analyses) adjusting for potential confounders. We further explored associations stratified by sex and age (≥60 years). Fixed-effects or sample size-weighted meta-analyses were performed to combine results. Finally, we performed mendelian randomization (MR) analyses to assess causality. RESULTS: We included up to 19,152 participants (mean age 59 years, 57% women). Higher mtDNA CN was cross-sectionally associated with better general cognitive function (β = 0.04; 95% CI 0.02-0.06) independent of age, sex, batch effects, race/ethnicity, time between blood draw and cognitive evaluation, cohort-specific variables, and education. Additional adjustment for blood cell counts or cardiometabolic traits led to slightly attenuated results. We observed similar significant associations with cognition in prospective analyses, although of reduced magnitude. We found no significant associations between mtDNA CN and brain MRI measures in meta-analyses. MR analyses did not reveal a causal relation between mtDNA CN in blood and cognition. DISCUSSION: Higher mtDNA CN in blood is associated with better current and future general cognitive function in large and diverse communities across the United States. Although MR analyses did not support a causal role, additional research is needed to assess causality. Circulating mtDNA CN could serve nevertheless as a biomarker of current and future cognitive function in the community

A Chemical Analog of Curcumin as an Improved Inhibitor of Amyloid Abeta Oligomerization

Amyloid-like plaques are characteristic lesions defining the neuropathology of Alzheimer's disease (AD). The size and density of these plaques are closely associated with cognitive decline. To combat this disease, the few therapies that are available rely on drugs that increase neurotransmission; however, this approach has had limited success as it has simply slowed an imminent decline and failed to target the root cause of AD. Amyloid-like deposits result from aggregation of the Aβ peptide, and thus, reducing amyloid burden by preventing Aβ aggregation represents an attractive approach to improve the therapeutic arsenal for AD. Recent studies have shown that the natural product curcumin is capable of crossing the blood-brain barrier in the CNS in sufficient quantities so as to reduce amyloid plaque burden. Based upon this bioactivity, we hypothesized that curcumin presents molecular features that make it an excellent lead compound for the development of more effective inhibitors of Aβ aggregation. To explore this hypothesis, we screened a library of curcumin analogs and identified structural features that contribute to the anti-oligomerization activity of curcumin and its analogs. First, at least one enone group in the spacer between aryl rings is necessary for measureable anti-Aβ aggregation activity. Second, an unsaturated carbon spacer between aryl rings is essential for inhibitory activity, as none of the saturated carbon spacers showed any margin of improvement over that of native curcumin. Third, methoxyl and hydroxyl substitutions in the meta- and para-positions on the aryl rings appear necessary for some measure of improved inhibitory activity. The best lead inhibitors have either their meta- and para-substituted methoxyl and hydroxyl groups reversed from that of curcumin or methoxyl or hydroxyl groups placed in both positions. The simple substitution of the para-hydroxy group on curcumin with a methoxy substitution improved inhibitor function by 6-7-fold over that measured for curcumin

Obesity and brain structure in schizophrenia - ENIGMA study in 3021 individuals

Schizophrenia is frequently associated with obesity, which is linked with neurostructural alterations. Yet, we do not understand how the brain correlates of obesity map onto the brain changes in schizophrenia. We obtained MRI-derived brain cortical and subcortical measures and body mass index (BMI) from 1260 individuals with schizophrenia and 1761 controls from 12 independent research sites within the ENIGMA-Schizophrenia Working Group. We jointly modeled the statistical effects of schizophrenia and BMI using mixed effects. BMI was additively associated with structure of many of the same brain regions as schizophrenia, but the cortical and subcortical alterations in schizophrenia were more widespread and pronounced. Both BMI and schizophrenia were primarily associated with changes in cortical thickness, with fewer correlates in surface area. While, BMI was negatively associated with cortical thickness, the significant associations between BMI and surface area or subcortical volumes were positive. Lastly, the brain correlates of obesity were replicated among large studies and closely resembled neurostructural changes in major depressive disorders. We confirmed widespread associations between BMI and brain structure in individuals with schizophrenia. People with both obesity and schizophrenia showed more pronounced brain alterations than people with only one of these conditions. Obesity appears to be a relevant factor which could account for heterogeneity of brain imaging findings and for differences in brain imaging outcomes among people with schizophrenia

Mitochondrial physiology

As the knowledge base and importance of mitochondrial physiology to evolution, health and disease expands, the necessity for harmonizing the terminology concerning mitochondrial respiratory states and rates has become increasingly apparent. The chemiosmotic theory establishes the mechanism of energy transformation and coupling in oxidative phosphorylation. The unifying concept of the protonmotive force provides the framework for developing a consistent theoretical foundation of mitochondrial physiology and bioenergetics. We follow the latest SI guidelines and those of the International Union of Pure and Applied Chemistry (IUPAC) on terminology in physical chemistry, extended by considerations of open systems and thermodynamics of irreversible processes. The concept-driven constructive terminology incorporates the meaning of each quantity and aligns concepts and symbols with the nomenclature of classical bioenergetics. We endeavour to provide a balanced view of mitochondrial respiratory control and a critical discussion on reporting data of mitochondrial respiration in terms of metabolic flows and fluxes. Uniform standards for evaluation of respiratory states and rates will ultimately contribute to reproducibility between laboratories and thus support the development of data repositories of mitochondrial respiratory function in species, tissues, and cells. Clarity of concept and consistency of nomenclature facilitate effective transdisciplinary communication, education, and ultimately further discovery