Workshop report - interdisciplinary metabolomic epidemiology: the pathway to clinical translation.

Metabolomic epidemiology studies are complex and require a broad array of domain expertise. Although many metabolite-phenotype associations have been identified; to date, few findings have been translated to the clinic. Bridging this gap requires understanding of both the underlying biology of these associations and their potential clinical implications, necessitating an interdisciplinary team approach. To address this need in metabolomic epidemiology, a workshop was held at Metabolomics 2023 in Niagara Falls, Ontario, Canada that highlighted the domain expertise needed to effectively conduct these studies -- biochemistry, clinical science, epidemiology, and assay development for biomarker validation -- and emphasized the role of interdisciplinary teams to move findings towards clinical translation.

Environmental neuroscience linking exposome to brain structure and function underlying cognition and behavior.

Individual differences in human brain structure, function, and behavior can be attributed to genetic variations, environmental exposures, and their interactions. Although genome-wide association studies have identified many genetic variants associated with brain imaging phenotypes, environmental exposures associated with these phenotypes remain largely unknown. Here, we propose that environmental neuroscience should pay more attention on exploring the associations between lifetime environmental exposures (exposome) and brain imaging phenotypes and identifying both cumulative environmental effects and their vulnerable age windows during the life course. Exposome-neuroimaging association studies face several challenges including the accurate measurement of the totality of environmental exposures varied in space and time, the highly correlated structure of the exposome, and the lack of standardized approaches for exposome-wide association studies. By agnostically scanning the effects of environmental exposures on brain imaging phenotypes and their interactions with genomic variations, exposome-neuroimaging association analyses will improve our understanding of causal factors associated with individual differences in brain structure and function as well as their relations with cognitive abilities and neuropsychiatric disorders.

Covariation of preadult environmental exposures, adult brain imaging phenotypes, and adult personality traits.

Exposure to preadult environmental exposures may have long-lasting effects on mental health by affecting the maturation of the brain and personality, two traits that interact throughout the developmental process. However, environment-brain-personality covariation patterns and their mediation relationships remain unclear. In 4297 healthy participants (aged 18-30 years), we combined sparse multiple canonical correlation analysis with independent component analysis to identify the three-way covariation patterns of 59 preadult environmental exposures, 760 adult brain imaging phenotypes, and five personality traits, and found two robust environment-brain-personality covariation models with sex specificity. One model linked greater stress and less support to weaker functional connectivity and activity in the default mode network, stronger activity in subcortical nuclei, greater thickness and volume in the occipital, parietal and temporal cortices, and lower agreeableness, consciousness and extraversion as well as higher neuroticism. The other model linked higher urbanicity and better socioeconomic status to stronger functional connectivity and activity in the sensorimotor network, smaller volume and surface area and weaker functional connectivity and activity in the medial prefrontal cortex, lower white matter integrity, and higher openness to experience. We also conducted mediation analyses to explore the potential bidirectional mediation relationships between adult brain imaging phenotypes and personality traits with the influence of preadult environmental exposures and found both environment-brain-personality and environment-personality-brain pathways. We finally performed moderated mediation analyses to test the potential interactions between macro- and microenvironmental exposures and found that one category of exposure moderated the mediation pathways of another category of exposure. These results improve our understanding of the effects of preadult environmental exposures on the adult brain and personality traits and may facilitate the design of targeted interventions to improve mental health by reducing the impact of adverse environmental exposures.

Metabolic biomarkers significantly enhance the prediction of HBV-related ACLF occurrence and outcomes.

BACKGROUND & AIMS: Acute-on-chronic liver failure (ACLF) is a clinical syndrome associated with high short-term mortality in patients with chronic liver disease. Chronic hepatitis B is the main cause of ACLF (HBV-ACLF) in China and other Asian countries. To improve disease management and survival for patients with ACLF, we aimed to discover novel biomarkers to enhance HBV-ACLF diagnosis and prognostication. METHODS: We performed a metabolomics profiling of 1,024 plasma samples collected from patients with HBV-related chronic liver disease with acute exacerbation at hospital admission in a multi-year and multi-center prospective study (367 ACLF and 657 non-ACLF). The samples were randomly separated into equal halves as a discovery set and a validation set. We identified metabolites associated with 90-day mortality in the ACLF group and the progression to ACLF within 28 days in the non-ACLF group (pre-ACLF) using statistical analysis and machine learning. We developed diagnostic algorithms in the discovery set and used these to assess the findings in the validation set. RESULTS: ACLF significantly altered the plasma metabolome, particularly in membrane lipid metabolism, steroid hormones, oxidative stress pathways, and energy metabolism. Numerous metabolites were significantly associated with 90-day mortality in the ACLF group and/or pre-ACLF in the non-ACLF group. We developed algorithms for the prediction of 90-day mortality in patients with ACLF (area under the curve 0.87 and 0.83 for the discovery set and validation set, respectively) and the diagnosis of pre-ACLF (area under the curve 0.94 and 0.88 for the discovery set and validation set, respectively). To translate our discoveries into practical clinical tests, we developed targeted assays using liquid chromatography-mass spectrometry. CONCLUSIONS: Based on novel metabolite biomarkers, we established tests for HBV-related ACLF with higher accuracy than existing methods. CLINICAL TRIAL NUMBER: NCT02457637 and NCT03641872. IMPACT AND IMPLICATIONS: Acute-on-chronic liver failure (ACLF) is a clinical syndrome associated with high short-term mortality affecting 25% of patients hospitalized with cirrhosis. Chronic hepatitis B is the main etiology of ACLF in China and other Asian counties. There is currently no effective therapy. Early diagnosis and accurate prognostication are critical for improving clinical outcomes in patients with ACLF. Based on novel metabolite biomarkers, we developed liquid chromatography-mass spectrometry tests with improved accuracy for the early diagnosis and prognostication of HBV-related ACLF. The liquid chromatography-mass spectrometry tests can be implemented in clinical labs and used by physicians to triage patients with HBV-related ACLF to ensure optimized clinical management.

Spontaneous brain activity abnormalities in migraine: A meta-analysis of functional neuroimaging.

Neuroimaging studies have demonstrated that migraine is accompanied by spontaneous brain activity alterations in specific regions. However, these findings are inconsistent, thus hindering our understanding of the potential neuropathology. Hence, we performed a quantitative whole-brain meta-analysis of relevant resting-state functional imaging studies to identify brain regions consistently involved in migraine. A systematic search of studies that investigated the differences in spontaneous brain activity patterns between migraineurs and healthy controls up to April 2022 was conducted. We then performed a whole-brain voxel-wise meta-analysis using the anisotropic effect size version of seed-based d mapping software. Complementary analyses including jackknife sensitivity analysis, heterogeneity test, publication bias test, subgroup analysis, and meta-regression analysis were conducted as well. In total, 24 studies that reported 31 datasets were finally eligible for our meta-analysis, including 748 patients and 690 controls. In contrast to healthy controls, migraineurs demonstrated consistent and robust decreased spontaneous brain activity in the angular gyrus, visual cortex, and cerebellum, while increased activity in the caudate, thalamus, pons, and prefrontal cortex. Results were robust and highly replicable in the following jackknife sensitivity analysis and subgroup analysis. Meta-regression analyses revealed that a higher visual analog scale score in the patient sample was associated with increased spontaneous brain activity in the left thalamus. These findings provided not only a comprehensive overview of spontaneous brain activity patterns impairments, but also useful insights into the pathophysiology of dysfunction in migraine.

CHIMGEN: a Chinese imaging genetics cohort to enhance cross-ethnic and cross-geographic brain research.

The Chinese Imaging Genetics (CHIMGEN) study establishes the largest Chinese neuroimaging genetics cohort and aims to identify genetic and environmental factors and their interactions that are associated with neuroimaging and behavioral phenotypes. This study prospectively collected genomic, neuroimaging, environmental, and behavioral data from more than 7000 healthy Chinese Han participants aged 18-30 years. As a pioneer of large-sample neuroimaging genetics cohorts of non-Caucasian populations, this cohort can provide new insights into ethnic differences in genetic-neuroimaging associations by being compared with Caucasian cohorts. In addition to micro-environmental measurements, this study also collects hundreds of quantitative macro-environmental measurements from remote sensing and national survey databases based on the locations of each participant from birth to present, which will facilitate discoveries of new environmental factors associated with neuroimaging phenotypes. With lifespan environmental measurements, this study can also provide insights on the macro-environmental exposures that affect the human brain as well as their timing and mechanisms of action.

Precision medicine screening using whole-genome sequencing and advanced imaging to identify disease risk in adults.

Reducing premature mortality associated with age-related chronic diseases, such as cancer and cardiovascular disease, is an urgent priority. We report early results using genomics in combination with advanced imaging and other clinical testing to proactively screen for age-related chronic disease risk among adults. We enrolled active, symptom-free adults in a study of screening for age-related chronic diseases associated with premature mortality. In addition to personal and family medical history and other clinical testing, we obtained whole-genome sequencing (WGS), noncontrast whole-body MRI, dual-energy X-ray absorptiometry (DXA), global metabolomics, a new blood test for prediabetes (Quantose IR), echocardiography (ECHO), ECG, and cardiac rhythm monitoring to identify age-related chronic disease risks. Precision medicine screening using WGS and advanced imaging along with other testing among active, symptom-free adults identified a broad set of complementary age-related chronic disease risks associated with premature mortality and strengthened WGS variant interpretation. This and other similarly designed screening approaches anchored by WGS and advanced imaging may have the potential to extend healthy life among active adults through improved prevention and early detection of age-related chronic diseases (and their risk factors) associated with premature mortality.

Plasma metabolomic profiles enhance precision medicine for volunteers of normal health.

Precision medicine, taking account of human individuality in genes, environment, and lifestyle for early disease diagnosis and individualized therapy, has shown great promise to transform medical care. Nontargeted metabolomics, with the ability to detect broad classes of biochemicals, can provide a comprehensive functional phenotype integrating clinical phenotypes with genetic and nongenetic factors. To test the application of metabolomics in individual diagnosis, we conducted a metabolomics analysis on plasma samples collected from 80 volunteers of normal health with complete medical records and three-generation pedigrees. Using a broad-spectrum metabolomics platform consisting of liquid chromatography and GC coupled with MS, we profiled nearly 600 metabolites covering 72 biochemical pathways in all major branches of biosynthesis, catabolism, gut microbiome activities, and xenobiotics. Statistical analysis revealed a considerable range of variation and potential metabolic abnormalities across the individuals in this cohort. Examination of the convergence of metabolomics profiles with whole-exon sequences (WESs) provided an effective approach to assess and interpret clinical significance of genetic mutations, as shown in a number of cases, including fructose intolerance, xanthinuria, and carnitine deficiency. Metabolic abnormalities consistent with early indications of diabetes, liver dysfunction, and disruption of gut microbiome homeostasis were identified in several volunteers. Additionally, diverse metabolic responses to medications among the volunteers may assist to identify therapeutic effects and sensitivity to toxicity. The results of this study demonstrate that metabolomics could be an effective approach to complement next generation sequencing (NGS) for disease risk analysis, disease monitoring, and drug management in our goal toward precision care.

Metabolic and co-expression network-based analyses associated with nitrate response in rice.

BACKGROUND: Understanding gene expression and metabolic re-programming that occur in response to limiting nitrogen (N) conditions in crop plants is crucial for the ongoing progress towards the development of varieties with improved nitrogen use efficiency (NUE). To unravel new details on the molecular and metabolic responses to N availability in a major food crop, we conducted analyses on a weighted gene co-expression network and metabolic profile data obtained from leaves and roots of rice plants adapted to sufficient and limiting N as well as after shifting them to limiting (reduction) and sufficient (induction) N conditions. RESULTS: A gene co-expression network representing clusters of rice genes with similar expression patterns across four nitrogen conditions and two tissue types was generated. The resulting 18 clusters were analyzed for enrichment of significant gene ontology (GO) terms. Four clusters exhibited significant correlation with limiting and reducing nitrate treatments. Among the identified enriched GO terms, those related to nucleoside/nucleotide, purine and ATP binding, defense response, sugar/carbohydrate binding, protein kinase activities, cell-death and cell wall enzymatic activity are enriched. Although a subset of functional categories are more broadly associated with the response of rice organs to limiting N and N reduction, our analyses suggest that N reduction elicits a response distinguishable from that to adaptation to limiting N, particularly in leaves. This observation is further supported by metabolic profiling which shows that several compounds in leaves change proportionally to the nitrate level (i.e. higher in sufficient N vs. limiting N) and respond with even higher levels when the nitrate level is reduced. Notably, these compounds are directly involved in N assimilation, transport, and storage (glutamine, asparagine, glutamate and allantoin) and extend to most amino acids. Based on these data, we hypothesize that plants respond by rapidly mobilizing stored vacuolar nitrate when N deficit is perceived, and that the response likely involves phosphorylation signal cascades and transcriptional regulation. CONCLUSIONS: The co-expression network analysis and metabolic profiling performed in rice pinpoint the relevance of signal transduction components and regulation of N mobilization in response to limiting N conditions and deepen our understanding of N responses and N use in crops.

A sister group contrast using untargeted global metabolomic analysis delineates the biochemical regulation underlying desiccation tolerance in Sporobolus stapfianus.

Understanding how plants tolerate dehydration is a prerequisite for developing novel strategies for improving drought tolerance. The desiccation-tolerant (DT) Sporobolus stapfianus and the desiccation-sensitive (DS) Sporobolus pyramidalis formed a sister group contrast to reveal adaptive metabolic responses to dehydration using untargeted global metabolomic analysis. Young leaves from both grasses at full hydration or at 60% relative water content (RWC) and from S. stapfianus at lower RWCs were analyzed using liquid and gas chromatography linked to mass spectrometry or tandem mass spectrometry. Comparison of the two species in the fully hydrated state revealed intrinsic differences between the two metabolomes. S. stapfianus had higher concentrations of osmolytes, lower concentrations of metabolites associated with energy metabolism, and higher concentrations of nitrogen metabolites, suggesting that it is primed metabolically for dehydration stress. Further reduction of the leaf RWC to 60% instigated a metabolic shift in S. stapfianus toward the production of protective compounds, whereas S. pyramidalis responded differently. The metabolomes of S. stapfianus leaves below 40% RWC were strongly directed toward antioxidant production, nitrogen remobilization, ammonia detoxification, and soluble sugar production. Collectively, the metabolic profiles obtained uncovered a cascade of biochemical regulation strategies critical to the survival of S. stapfianus under desiccation.

Metabolomic profiling reveals severe skeletal muscle group-specific perturbations of metabolism in aged FBN rats.

Mammalian skeletal muscles exhibit age-related adaptive and pathological remodeling. Several muscles in particular undergo progressive atrophy and degeneration beyond median lifespan. To better understand myocellular responses to aging, we used semi-quantitative global metabolomic profiling to characterize trends in metabolic changes between 15-month-old adult and 32-month-old aged Fischer 344 × Brown Norway (FBN) male rats. The FBN rat gastrocnemius muscle exhibits age-dependent atrophy, whereas the soleus muscle, up until 32 months, exhibits markedly fewer signs of atrophy. Both gastrocnemius and soleus muscles were analyzed, as well as plasma and urine. Compared to adult gastrocnemius, aged gastrocnemius showed evidence of reduced glycolytic metabolism, including accumulation of glycolytic, glycogenolytic, and pentose phosphate pathway intermediates. Pyruvate was elevated with age, yet levels of citrate and nicotinamide adenine dinucleotide were reduced, consistent with mitochondrial abnormalities. Indicative of muscle atrophy, 3-methylhistidine and free amino acids were elevated in aged gastrocnemius. The monounsaturated fatty acids oleate, cis-vaccenate, and palmitoleate also increased in aged gastrocnemius, suggesting altered lipid metabolism. Compared to gastrocnemius, aged soleus exhibited far fewer changes in carbohydrate metabolism, but did show reductions in several glycolytic intermediates, fumarate, malate, and flavin adenine dinucleotide. Plasma biochemicals showing the largest age-related increases included glycocholate, heme, 1,5-anhydroglucitol, 1-palmitoleoyl-glycerophosphocholine, palmitoleate, and creatine. These changes suggest reduced insulin sensitivity in aged FBN rats. Altogether, these data highlight skeletal muscle group-specific perturbations of glucose and lipid metabolism consistent with mitochondrial dysfunction in aged FBN rats.

[Long-term auditory monitoring in children with Alport syndrome based on different degrees of renal injury].

Objective:To investigate long-term auditory changes and characteristics of Alport syndrome（AS） patients with different degrees of renal injury. Methods:Retrospectively analyzing clinical data of patients diagnosed AS from January 2007 to September 2022, including renal pathology, genetic detection and hearing examination. A long-term follow-up focusing on hearing and renal function was conducted. Results:This study included 70 AS patients, of which 33（25 males, 8 females, aged 3.4-27.8 years） were followed up, resulting in a loss rate of 52.9%.The follow-up period ranged from 1.1to 15.8 years, with 16 patients followed-up for over 10 years. During the follow-up, 10 patients presenting with hearing abnormalities at the time of diagnosis of AS had progressive hearing loss, and 3 patients with new hearing abnormalities were followed up, which appeared at 5-6 years of disease course. All of which were sensorineural deafness. While only 3 patients with hearing abnormalities among 13 patients received hearing aid intervention. Of these patients,7 developed end-stage renal disease（ESRD）, predominantly males （6/7）. The rate of long-term hearing loss was significantly different between ESRD group and non-ESRD group（P=0.013）. There was no correlation between the progression of renal disease and long-term hearing level（P>0.05）. kidney biopsies from 28 patients revealed varying degrees of podocyte lesion and uneven thickness of basement membrane. The severity of podocyte lesion was correlated with the rate of long-term hearing loss（P=0.048）, and there was no correlation with the severity of hearing loss（P>0.05）. Among 11 cases, theCOL4A5mutationwas most common （8 out of 11）, but there was no significant correlation between the mutation type and hearing phenotype（P>0.05）. Conclusion:AS patients exhibit progressive hearing loss with significant heterogeneity over the long-term.. THearing loss is more likely to occur 5-6 years into the disease course. Hearing abnormalities are closely related to renal disease status, kidney tissue pathology, and gene mutations, emphasizing the need for vigilant long-term hearing follow-up and early intervention.

Schizophrenia mediating the effect of smoking phenotypes on antisocial behavior: A Mendelian randomization analysis.

AIMS: Previous studies have indicated that smoking is linked to an increased risk of developing schizophrenia, and that individuals with schizophrenia are more prone to engaging in antisocial behavior. However, the causal effects of smoking behaviors on antisocial behavior and the potential mediating role of schizophrenia remains largely unclear. METHODS: In the present study, using the summary data from genome wide association studies of smoking phenotypes (N = 323,386-805,431), schizophrenia (Ncases = 53,386, Ncontrols = 77,258), and antisocial behavior (N = 85,359), we assessed bidirectional causality between smoking phenotypes and schizophrenia by the Mendelian randomization (MR) approach. Using a two-step MR approach, we further examined whether causal effects of smoking phenotypes/schizophrenia on antisocial behavior were mediated by schizophrenia/smoking phenotypes. RESULTS: The results showed that smoking initiation (SmkInit) and age of smoking initiation (AgeSmk) causally increase the risk of schizophrenia (SmkInit: OR = 2.06, 95% CI = 1.77-2.39, p = 4.36 × 10-21 ; AgeSmk: OR = 0.32, 95% CI = 0.16-0.62, p = 8.11 × 10-4 , Bonferroni corrected). However, there was no causal effect that liability to schizophrenia leads to smoking phenotypes. MR evidence also revealed causal influences of SmkInit and the amount smoked (CigDay) on antisocial behavior (SmkInit: OR = 1.28, 95% CI = 1.17-1.41, p = 2.53 × 10-7 ; CigDay: OR = 1.16, 95% CI = 1.06-1.27, p = 1.60 × 10-3 , Bonferroni corrected). Furthermore, the mediation analysis indicated that the relationship between SmkInit and antisocial behavior was partly mediated by schizophrenia (mediated proportion = 6.92%, 95% CI = 0.004-0.03, p = 9.66 × 10-3 ). CONCLUSIONS: These results provide compelling evidence for taking smoking interventions as a prevention strategy for schizophrenia and its related antisocial behavior.

Comparative metabolic profiling between desiccation-sensitive and desiccation-tolerant species of Selaginella reveals insights into the resurrection trait.

Spike mosses (Selaginellaceae) represent an ancient lineage of vascular plants in which some species have evolved desiccation tolerance (DT). A sister-group contrast to reveal the metabolic basis of DT was conducted between a desiccation-tolerant species, Selaginella lepidophylla, and a desiccation-sensitive species, Selaginella moellendorffii, at 100% relative water content (RWC) and 50% RWC using non-biased, global metabolomics profiling technology, based on GC/MS and UHLC/MS/MS(2) platforms. A total of 301 metabolites, including 170 named (56.5%) and 131 (43.5%) unnamed compounds, were characterized across both species. S. lepidophylla retained significantly higher abundances of sucrose, mono- and polysaccharides, and sugar alcohols than did S. moellendorffii. Aromatic amino acids, the well-known osmoprotectant betaine and flavonoids were also more abundant in S. lepidophylla. Notably, levels of γ-glutamyl amino acid, linked with glutathione metabolism in the detoxification of reactive oxygen species, and with possible nitrogen remobilization following rehydration, were markedly higher in S. lepidophylla. Markers for lipoxygenase activity were also greater in S. lepidophylla, especially at 50% RWC. S. moellendorffii contained more than twice the number of unnamed compounds, with only a slightly greater abundance than in S. lepidophylla. In contrast, S. lepidophylla contained 14 unnamed compounds of fivefold or greater abundance than in S. moellendorffii, suggesting that these compounds might play critical roles in DT. Overall, S. lepidophylla appears poised to tolerate desiccation in a constitutive manner using a wide range of metabolites with some inducible components, whereas S. moellendorffii mounts only limited metabolic responses to dehydration stress.

The chloroplast triggers developmental reprogramming when mutS HOMOLOG1 is suppressed in plants.

Multicellular eukaryotes demonstrate nongenetic, heritable phenotypic versatility in their adaptation to environmental changes. This inclusive inheritance is composed of interacting epigenetic, maternal, and environmental factors. Yet-unidentified maternal effects can have a pronounced influence on plant phenotypic adaptation to changing environmental conditions. To explore the control of phenotypy in higher plants, we examined the effect of a single plant nuclear gene on the expression and transmission of phenotypic variability in Arabidopsis (Arabidopsis thaliana). MutS HOMOLOG1 (MSH1) is a plant-specific nuclear gene product that functions in both mitochondria and plastids to maintain genome stability. RNA interference suppression of the gene elicits strikingly similar programmed changes in plant growth pattern in six different plant species, changes subsequently heritable independent of the RNA interference transgene. The altered phenotypes reflect multiple pathways that are known to participate in adaptation, including altered phytohormone effects for dwarfed growth and reduced internode elongation, enhanced branching, reduced stomatal density, altered leaf morphology, delayed flowering, and extended juvenility, with conversion to perennial growth pattern in short days. Some of these effects are partially reversed with the application of gibberellic acid. Genetic hemicomplementation experiments show that this phenotypic plasticity derives from changes in chloroplast state. Our results suggest that suppression of MSH1, which occurs under several forms of abiotic stress, triggers a plastidial response process that involves nongenetic inheritance.

Perturbation of bile acid homeostasis is an early pathogenesis event of drug induced liver injury in rats.

Drug-induced liver injury (DILI) is a significant consideration for drug development. Current preclinical DILI assessment relying on histopathology and clinical chemistry has limitations in sensitivity and discordance with human. To gain insights on DILI pathogenesis and identify potential biomarkers for improved DILI detection, we performed untargeted metabolomic analyses on rats treated with thirteen known hepatotoxins causing various types of DILI: necrosis (acetaminophen, bendazac, cyclosporine A, carbon tetrachloride, ethionine), cholestasis (methapyrilene and naphthylisothiocyanate), steatosis (tetracycline and ticlopidine), and idiosyncratic (carbamazepine, chlorzoxasone, flutamide, and nimesulide) at two doses and two time points. Statistical analysis and pathway mapping of the nearly 1900 metabolites profiled in the plasma, urine, and liver revealed diverse time and dose dependent metabolic cascades leading to DILI by the hepatotoxins. The most consistent change induced by the hepatotoxins, detectable even at the early time point/low dose, was the significant elevations of a panel of bile acids in the plasma and urine, suggesting that DILI impaired hepatic bile acid uptake from the circulation. Furthermore, bile acid amidation in the hepatocytes was altered depending on the severity of the hepatotoxin-induced oxidative stress. The alteration of the bile acids was most evident by the necrosis and cholestasis hepatotoxins, with more subtle effects by the steatosis and idiosyncratic hepatotoxins. Taking together, our data suggest that the perturbation of bile acid homeostasis is an early event of DILI. Upon further validation, selected bile acids in the circulation could be potentially used as sensitive and early DILI preclinical biomarkers.

3-hydroxykynurenine and other Parkinson's disease biomarkers discovered by metabolomic analysis.

Parkinson's disease (PD) biomarkers are needed to enhance therapeutics research and to understand PD pathogenesis. Methods that simultaneously measure hundreds of small molecular-weight compounds-metabolomic analysis-"fingerprint" disease-specific alterations in individual compounds or metabolic pathways. Beyond a nontargeted search for PD biomarkers, we hypothesized that PD cerebrospinal fluid would show increased formation of the excitotoxin 3-hydroxykynurenine and diminished concentration of the antioxidant glutathione. Cerebrospinal fluid was collected at <4 hours postmortem from 48 pathologically-verified PD subjects and 57 comparably-aged controls. Assays involved ultra-high-performance liquid and gas chromatography linked to mass spectrometry. We used univariate techniques to determine fold-changes in concentrations of biochemicals; false-discovery rates were calculated to exclude spurious findings. Data was modeled using a Support Vector Machine for analyzing compounds selected by Welch's t test. Classification accuracy was determined by cross-validation. Of 243 structurally-identified biochemicals,19 compounds differentiated PD from controls at a 20% false-discovery level. In PD, mean 3-hydroxykynurenine concentration was increased by one-third, and mean oxidized glutathione was decreased by 40% (for each, P < .01). Four of the 19 compounds differentiating PD from controls were N-acetylated amino acids, suggesting a generalized alteration in N-acetylation activity. The Support Vector Machine classification model distinguished between groups at 83% sensitivity and 91% specificity for the learning data, and at 65% and 79% from cross-validation. In this study, the first for metabolomic profiling of PD cerebrospinal fluid, we found several novel biomarkers and offer new directions for recognizing disease-specific biochemical indicators. The findings support involvement of excitotoxicity and oxidative stress in the pathogenesis of PD.

Transcriptional signatures of the cortical morphometric similarity network gradient in first-episode, treatment-naive major depressive disorder.

Recent studies have shown that major depressive disorder (MDD) is accompanied by alterations in functional and structural network gradients. However, whether changes are present in the cortical morphometric similarity (MS) network gradient, and the relationship between alterations of the gradient and gene expression remains largely unknown. In this study, the MS network was constructed, and its gradient was calculated in 71 patients with first-episode, treatment-naive MDD, and 69 demographically matched healthy controls. Between-group comparisons were performed to investigate abnormalities in the MS network gradient, and partial least squares regression analysis was conducted to explore the association between gene expression profiles and MS network gradient-based alternations in MDD. We found that the gradient was primarily significantly decreased in sensorimotor regions in patients with MDD compared with healthy controls, and increased in visual-related regions. In addition, the altered principal MS network gradient in the left postcentral cortex and right lingual cortex exhibited significant correlations with symptom severity. The abnormal gradient pattern was spatially correlated with the brain-wide expression of genes enriched for neurobiologically relevant pathways, downregulated in the MDD postmortem brain, and preferentially expressed in different cell types and cortical layers. These results demonstrated alterations of the principal MS network gradient in MDD and suggested the molecular mechanisms for structural alternations underlying MDD.

Association between gray matter atrophy, cerebral hypoperfusion, and cognitive impairment in Alzheimer's disease.

Background: Alzheimer's disease (AD) is one of the most severe neurodegenerative diseases leading to dementia in the elderly. Cerebral atrophy and hypoperfusion are two important pathophysiological characteristics. However, it is still unknown about the area-specific causal pathways between regional gray matter atrophy, cerebral hypoperfusion, and cognitive impairment in AD patients. Method: Forty-two qualified AD patients and 49 healthy controls (HC) were recruited in this study. First, we explored voxel-wise inter-group differences in gray matter volume (GMV) and arterial spin labeling (ASL) -derived cerebral blood flow (CBF). Then we explored the voxel-wise associations between GMV and Mini-Mental State Examination (MMSE) score, GMV and CBF, and CBF and MMSE to identify brain targets contributing to cognitive impairment in AD patients. Finally, a mediation analysis was applied to test the causal pathways among atrophied GMV, hypoperfusion, and cognitive impairment in AD. Results: Voxel-wise permutation test identified that the left middle temporal gyrus (MTG) had both decreased GMV and CBF in the AD. Moreover, the GMV of this region was positively correlated with MMSE and its CBF, and CBF of this region was also positively correlated with MMSE in AD (p < 0.05, corrected). Finally, mediation analysis revealed that gray matter atrophy of left MTG drives cognitive impairment of AD via the mediation of CBF (proportion of mediation = 55.82%, ß = 0.242, 95% confidence interval by bias-corrected and accelerated bootstrap: 0.082 to 0.530). Conclusion: Our findings indicated suggested that left MTG is an important hub linking gray matter atrophy, hypoperfusion, and cognitive impairment for AD, and might be a potential treatment target for AD.

The identification and cognitive correlation of perfusion patterns measured with arterial spin labeling MRI in Alzheimer's disease.

BACKGROUND: Vascular dysfunction, including cerebral hypoperfusion, plays an important role in the pathogenesis and progression of Alzheimer's disease (AD), independent of amyloid and tau pathology. We established an AD-related perfusion pattern (ADRP) measured with arterial spin labeling (ASL) MRI using multivariate spatial covariance analysis. METHODS: We obtained multimodal MRI including pseudo-continuous ASL and neurocognitive testing in a total of 55 patients with a diagnosis of mild to moderate AD supported by amyloid PET and 46 normal controls (NCs). An ADRP was established from an identification cohort of 32 patients with AD and 32 NCs using a multivariate analysis method based on scaled subprofile model/principal component analysis, and pattern expression in individual subjects was quantified for both the identification cohort and a validation cohort (23 patients with AD and 14 NCs). Subject expression score of the ADRP was then used to assess diagnostic accuracy and cognitive correlations in AD patients and compared with global and regional cerebral blood flow (CBF) in specific areas identified from voxel-based univariate analysis. RESULTS: The ADRP featured negative loading in the bilateral middle and posterior cingulate and precuneus, inferior parietal lobule, and frontal areas, and positive loading in the right cerebellum and bilateral basal areas. Subject expression score of the ADRP was significantly elevated in AD patients compared with NCs (P < 0.001) and showed good diagnostic accuracy for AD with area under receiver-operator curve of 0.87 [95% CI (0.78-0.96)] in the identification cohort and 0.85 in the validation cohort. Moreover, there were negative correlations between subject expression score and global cognitive function and performance in various cognitive domains in patients with AD. The characteristics of the ADRP topography and subject expression scores were supported by analogous findings obtained with regional CBF. CONCLUSIONS: We have reported a characteristic perfusion pattern associated with AD using ASL MRI. Subject expression score of this spatial covariance pattern is a promising MRI biomarker for the identification and monitoring of AD.