Metabolomics Signatures of serotonin reuptake inhibitor (Escitalopram), serotonin norepinephrine reuptake inhibitor (Duloxetine) and Cognitive Behavior Therapy on Key Neurotransmitter Pathways in Major Depressive Disorder.

Metabolomics provides powerful tools that can inform about heterogeneity in disease and response to treatments. In this study, we employed an electrochemistry-based targeted metabolomics platform to assess the metabolic effects of three randomly-assigned treatments: escitalopram, duloxetine, and Cognitive Behavior Therapy (CBT) in 163 treatment-naïve outpatients with major depressive disorder. Serum samples from baseline and 12 weeks post-treatment were analyzed using targeted liquid chromatography-electrochemistry for metabolites related to tryptophan, tyrosine metabolism and related pathways. Changes in metabolite concentrations related to each treatment arm were identified and compared to define metabolic signatures of exposure. In addition, association between metabolites and depressive symptom severity (assessed with the 17-item Hamilton Rating Scale for Depression [HRSD17]) and anxiety symptom severity (assessed with the 14-item Hamilton Rating Scale for Anxiety [HRSA14]) were evaluated, both at baseline and after 12 weeks of treatment. Significant reductions in serum serotonin level and increases in tryptophan-derived indoles that are gut bacterially derived were observed with escitalopram and duloxetine arms but not in CBT arm. These include indole-3-propionic acid (I3PA), indole-3-lactic acid (I3LA) and Indoxyl sulfate (IS), a uremic toxin. Purine-related metabolites were decreased across all arms. Different metabolites correlated with improved symptoms in the different treatment arms revealing potentially different mechanisms between response to antidepressant medications and to CBT.

The DIRAC framework: Geometric structure underlies roles of diversity and accuracy in combining classifiers.

Combining classification systems potentially improves predictive accuracy, but outcomes have proven impossible to predict. Similar to improving binary classification with fusion, fusing ranking systems most commonly increases Pearson or Spearman correlations with a target when the input classifiers are "sufficiently good" (generalized as "accuracy") and "sufficiently different" (generalized as "diversity"), but the individual and joint quantitative influence of these factors on the final outcome remains unknown. We resolve these issues. Building on our previous empirical work establishing the DIRAC (DIversity of Ranks and ACcuracy) framework, which accurately predicts the outcome of fusing binary classifiers, we demonstrate that the DIRAC framework similarly explains the outcome of fusing ranking systems. Specifically, precise geometric representation of diversity and accuracy as angle-based distances within rank-based combinatorial structures (permutahedra) fully captures their synergistic roles in rank approximation, uncouples them from the specific metrics of a given problem, and represents them as generally as possible.

Serum Bile Acids Improve Prediction of Alzheimer's Progression in a Sex-Dependent Manner.

Sex disparities in serum bile acid (BA) levels and Alzheimer's disease (AD) prevalence have been established. However, the precise link between changes in serum BAs and AD development remains elusive. Here, authors quantitatively determined 33 serum BAs and 58 BA features in 4 219 samples collected from 1 180 participants from the Alzheimer's Disease Neuroimaging Initiative. The findings revealed that these BA features exhibited significant correlations with clinical stages, encompassing cognitively normal (CN), early and late mild cognitive impairment, and AD, as well as cognitive performance. Importantly, these associations are more pronounced in men than women. Among participants with progressive disease stages (n = 660), BAs underwent early changes in men, occurring before AD. By incorporating BA features into diagnostic and predictive models, positive enhancements are achieved for all models. The area under the receiver operating characteristic curve improved from 0.78 to 0.91 for men and from 0.76 to 0.83 for women for the differentiation of CN and AD. Additionally, the key findings are validated in a subset of participants (n = 578) with cerebrospinal fluid amyloid-beta and tau levels. These findings underscore the role of BAs in AD progression, offering potential improvements in the accuracy of AD prediction.

The MT1 receptor as the target of ramelteon neuroprotection in ischemic stroke.

Stroke is the leading cause of death and disability worldwide. Novel and effective therapies for ischemic stroke are urgently needed. Here, we report that melatonin receptor 1A (MT1) agonist ramelteon is a neuroprotective drug candidate as demonstrated by comprehensive experimental models of ischemic stroke, including a middle cerebral artery occlusion (MCAO) mouse model of cerebral ischemia in vivo, organotypic hippocampal slice cultures ex vivo, and cultured neurons in vitro; the neuroprotective effects of ramelteon are diminished in MT1-knockout (KO) mice and MT1-KO cultured neurons. For the first time, we report that the MT1 receptor is significantly depleted in the brain of MCAO mice, and ramelteon treatment significantly recovers the brain MT1 losses in MCAO mice, which is further explained by the Connectivity Map L1000 bioinformatic analysis that shows gene-expression signatures of MCAO mice are negatively connected to melatonin receptor agonist like Ramelteon. We demonstrate that ramelteon improves the cerebral blood flow signals in ischemic stroke that is potentially mediated, at least, partly by mechanisms of activating endothelial nitric oxide synthase. Our results also show that the neuroprotection of ramelteon counteracts reactive oxygen species-induced oxidative stress and activates the nuclear factor erythroid 2-related factor 2/heme oxygenase-1 pathway. Ramelteon inhibits the mitochondrial and autophagic death pathways in MCAO mice and cultured neurons, consistent with gene set enrichment analysis from a bioinformatics perspective angle. Our data suggest that Ramelteon is a potential neuroprotective drug candidate, and MT1 is the neuroprotective target for ischemic stroke, which provides new insights into stroke therapy. MT1-KO mice and cultured neurons may provide animal and cellular models of accelerated ischemic damage and neuronal cell death.

Circulating lipid profiles are associated with cross-sectional and longitudinal changes of central biomarkers for Alzheimer's disease.

Investigating the association of lipidome profiles with central Alzheimer's disease (AD) biomarkers, including amyloid/tau/neurodegeneration (A/T/N), can provide a holistic view between the lipidome and AD. We performed cross-sectional and longitudinal association analysis of serum lipidome profiles with AD biomarkers in the Alzheimer's Disease Neuroimaging Initiative cohort (N=1,395). We identified lipid species, classes, and network modules that were significantly associated with cross-sectional and longitudinal changes of A/T/N biomarkers for AD. Notably, we identified the lysoalkylphosphatidylcholine (LPC(O)) as associated with "A/N" biomarkers at baseline at lipid species, class, and module levels. Also, GM3 ganglioside showed significant association with baseline levels and longitudinal changes of the "N" biomarkers at species and class levels. Our study of circulating lipids and central AD biomarkers enabled identification of lipids that play potential roles in the cascade of AD pathogenesis. Our results suggest dysregulation of lipid metabolic pathways as precursors to AD development and progression.

Age-related changes in circadian regulation of the human plasma lipidome.

Aging alters the amplitude and phase of centrally regulated circadian rhythms. Here we evaluate whether peripheral circadian rhythmicity in the plasma lipidome is altered by aging through retrospective lipidomics analysis on plasma samples collected in 24 healthy individuals (9 females; mean ± SD age: 40.9 ± 18.2 years) including 12 younger (4 females, 23.5 ± 3.9 years) and 12 middle-aged older, (5 females, 58.3 ± 4.2 years) individuals every 3 h throughout a 27-h constant routine (CR) protocol, which allows separating evoked changes from endogenously generated oscillations in physiology. Cosinor regression shows circadian rhythmicity in 25% of lipids in both groups. On average, the older group has a ~14% lower amplitude and a ~2.1 h earlier acrophase of the lipid circadian rhythms (both, p ≤ 0.001). Additionally, more rhythmic circadian lipids have a significant linear component in addition to the sinusoidal across the 27-h CR in the older group (44/56) compared to the younger group (18/58, p < 0.0001). Results from individual-level data are consistent with group-average results. Results indicate that prevalence of endogenous circadian rhythms of the human plasma lipidome is preserved with healthy aging into middle-age, but significant changes in rhythmicity include a reduction in amplitude, earlier acrophase, and an altered temporal relationship between central and lipid rhythms.

Risk Factors for Type 2 Diabetes in the Multiethnic Cohort.

OBJECTIVES: In this report, we investigated the association between established risk factors and type 2 diabetes (T2D) across 5 distinct ethnic groups and explored differences according to T2D definition within the Multiethnic Cohort (MEC) Study. METHODS: Using the full MEC, with participants in Hawaii and Los Angeles (N=172,230), we applied Cox regression to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). All participants completed questionnaires asking about demographics, anthropometrics, lifestyle factors, and regular diet. T2D status was determined from self-reported diagnosis/medication and Medicare claims. We assessed the associations between well-established risk factors and T2D in the full cohort, after stratification by ethnic group, according to the T2D definition, and in a biorepository subset. Effect modification by ethnicity was evaluated using Wald's tests. RESULTS: Overall, 46,500 (27%) participants had an incident T2D diagnosis after a mean follow-up of 17.1±6.9 years. All predictors were significantly associated with T2D: overweight (HR=1.74), obesity (HR=2.90), red meat intake (HR=1.15), short (HR=1.04) and long (HR=1.08) sleep duration, and smoking (HR=1.26) predicted a significantly higher T2D incidence, whereas coffee (HR=0.90) and alcohol (HR=0.78) consumption, physical activity (HR=0.89), and diet quality (HR=0.96) were associated with lower T2D incidence. The strength of these associations was similar across ethnic groups with noteworthy disparities for overweight/obesity, physical activity, alcohol intake, coffee consumption, and diet quality. CONCLUSIONS: These findings confirm the importance of known risk factors for T2D across ethnic groups, but small differences were detected that may contribute to disparate incidence rates in some ethnic groups, especially for obesity and physical activity.

Genetic loci of beta-aminoisobutyric acid are associated with aging-related mild cognitive impairment.

We studied the genetic associations of a previously developed Metabolomic Risk Score (MRS) for Mild Cognitive Impairment (MCI) and beta-aminoisobutyric acid metabolite (BAIBA)-the metabolite highlighted by results from a genome-wide association study (GWAS) of the MCI-MRS, and assessed their association with MCI in datasets of diverse race/ethnicities. We first performed a GWAS for the MCI-MRS and BAIBA, in Hispanic/Latino adults (n = 3890) from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). We identified ten independent genome-wide significant (p value <5 × 10-8) variants associated with MCI-MRS or BAIBA. Variants associated with the MCI-MRS are located in the Alanine-Glyoxylate Aminotransferase 2 (AGXT2 gene), which is known to be associated with BAIBA metabolism. Variants associated with BAIBA are located in the AGXT2 gene and in the SLC6A13 gene. Next, we tested the variants' association with MCI in independent datasets of n = 3178 HCHS/SOL older individuals, n = 3775 European Americans, and n = 1032 African Americans from the Atherosclerosis Risk In Communities (ARIC) study. Variants were considered associated with MCI if their p value <0.05 in the meta-analysis of the three datasets and their direction of association was consistent with expectation. Rs16899972 and rs37369 from the AGXT2 region were associated with MCI. Mediation analysis supported the mediation effect of BAIBA between the two genetic variants and MCI (p value = 0.004 for causal mediated effect). In summary, genetic variants in the AGXT2 region are associated with MCI in Hispanic/Latino, African, and European American populations in the USA, and their effect is likely mediated by changes in BAIBA levels.

Plasma metabolites associated with cognitive function across race/ethnicities affirming the importance of healthy nutrition.

INTRODUCTION: We studied the replication and generalization of previously identified metabolites potentially associated with global cognitive function in multiple race/ethnicities and assessed the contribution of diet to these associations. METHODS: We tested metabolite-cognitive function associations in U.S.A. Hispanic/Latino adults (n = 2222) from the Community Health Study/ Study of Latinos (HCHS/SOL) and in European (n = 1365) and African (n = 478) Americans from the Atherosclerosis Risk In Communities (ARIC) Study. We applied Mendelian Randomization (MR) analyses to assess causal associations between the metabolites and cognitive function and between Mediterranean diet and cognitive function. RESULTS: Six metabolites were consistently associated with lower global cognitive function across all studies. Of these, four were sugar-related (e.g., ribitol). MR analyses provided weak evidence for a potential causal effect of ribitol on cognitive function and bi-directional effects of cognitive performance on diet. DISCUSSION: Several diet-related metabolites were associated with global cognitive function across studies with different race/ethnicities. HIGHLIGHTS: Metabolites associated with cognitive function in Puerto Rican adults were recently identified. We demonstrate the generalizability of these associations across diverse race/ethnicities. Most identified metabolites are related to sugars. Mendelian Randomization (MR) provides weak evidence for a causal effect of ribitol on cognitive function. Beta-cryptoxanthin and other metabolites highlight the importance of a healthy diet.

Development and validation of a metabolite index for obstructive sleep apnea across race/ethnicities.

Obstructive sleep apnea (OSA) is a common disorder characterized by recurrent episodes of upper airway obstruction during sleep resulting in oxygen desaturation and sleep fragmentation, and associated with increased risk of adverse health outcomes. Metabolites are being increasingly used for biomarker discovery and evaluation of disease processes and progression. Studying metabolomic associations with OSA in a diverse community-based cohort may provide insights into the pathophysiology of OSA. We aimed to develop and replicate a metabolite index for OSA and identify individual metabolites associated with OSA. We studied 219 metabolites and their associations with the apnea hypopnea index (AHI) and with moderate-severe OSA (AHI ≥ 15) in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) (n = 3507) using two methods: (1) association analysis of individual metabolites, and (2) least absolute shrinkage and selection operator (LASSO) regression to identify a subset of metabolites jointly associated with OSA, which was used to develop a metabolite index for OSA. Results were validated in the Multi-Ethnic Study of Atherosclerosis (MESA) (n = 475). When assessing the associations with individual metabolites, we identified seven metabolites significantly positively associated with OSA in HCHS/SOL (FDR p < 0.05), of which four associations-glutamate, oleoyl-linoleoyl-glycerol (18:1/18:2), linoleoyl-linoleoyl-glycerol (18:2/18:2) and phenylalanine, were replicated in MESA (one sided-p < 0.05). The OSA metabolite index, composed of 14 metabolites, was associated with a 50% increased risk for moderate-severe OSA (OR = 1.50 [95% CI 1.21-1.85] per 1 SD of OSA metabolite index, p < 0.001) in HCHS/SOL and 55% increased risk (OR = 1.55 [95% CI 1.10-2.20] per 1 SD of OSA metabolite index, p = 0.013) in MESA, both adjusted for demographics, lifestyle, and comorbidities. Similar albeit less significant associations were observed for AHI. Replication of the metabolite index in an independent multi-ethnic dataset demonstrates the robustness of metabolomic-based OSA index to population heterogeneity. Replicated metabolite associations may provide insights into OSA-related molecular and metabolic mechanisms.

Predicting drug toxicity at the intersection of informatics and biology: DTox builds a foundation.

Hao et al. (2022) present DTox (deep learning for toxicology), a neural network designed to predict and probe the sites and potential mechanisms underlying chemical toxicity; results provide a map to facilitate modular testing and improvements across multiple disparate applications.

Blood metabolites predicting mild cognitive impairment in the study of Latinos-investigation of neurocognitive aging (HCHS/SOL).

INTRODUCTION: Blood metabolomics-based biomarkers may be useful to predict measures of neurocognitive aging. METHODS: We tested the association between 707 blood metabolites measured in 1451 participants from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), with mild cognitive impairment (MCI) and global cognitive change assessed 7 years later. We further used Lasso penalized regression to construct a metabolomics risk score (MRS) that predicts MCI, potentially identifying a different set of metabolites than those discovered in individual-metabolite analysis. RESULTS: We identified 20 metabolites predicting prevalent MCI and/or global cognitive change. Six of them were novel and 14 were previously reported as associated with neurocognitive aging outcomes. The MCI MRS comprised 61 metabolites and improved prediction accuracy from 84% (minimally adjusted model) to 89% in the entire dataset and from 75% to 87% among apolipoprotein E ε4 carriers. DISCUSSION: Blood metabolites may serve as biomarkers identifying individuals at risk for MCI among US Hispanics/Latinos.

Ranks underlie outcome of combining classifiers: Quantitative roles for diversity and accuracy.

Combining classifier systems potentially improves predictive accuracy, but outcomes have proven impossible to predict. Classification most commonly improves when the classifiers are "sufficiently good" (generalized as " accuracy ") and "sufficiently different" (generalized as " diversity "), but the individual and joint quantitative influence of these factors on the final outcome remains unknown. We resolve these issues. Beginning with simulated data, we develop the DIRAC framework (DIversity of Ranks and ACcuracy), which accurately predicts outcome of both score-based fusions originating from exponentially modified Gaussian distributions and rank-based fusions, which are inherently distribution independent. DIRAC was validated using biological dual-energy X-ray absorption and magnetic resonance imaging data. The DIRAC framework is domain independent and has expected utility in far-ranging areas such as clinical biomarker development/personalized medicine, clinical trial enrollment, insurance pricing, portfolio management, and sensor optimization.

Metabolomic and inflammatory signatures of symptom dimensions in major depression.

BACKGROUND: Major depressive disorder (MDD) is a highly heterogenous disease, both in terms of clinical profiles and pathobiological alterations. Recently, immunometabolic dysregulations were shown to be correlated with atypical, energy-related symptoms but less so with the Melancholic or Anxious distress symptom dimensions of depression in The Netherlands Study of Depression and Anxiety (NESDA) study. In this study, we aimed to replicate these immunometabolic associations and to characterize the metabolomic correlates of each of the three MDD dimensions. METHODS: Using three clinical rating scales, Melancholic, and Anxious distress, and Immunometabolic (IMD) dimensions were characterized in 158 patients who participated in the Predictors of Remission to Individual and Combined Treatments (PReDICT) study and from whom plasma and serum samples were available. The NESDA-defined inflammatory index, a composite measure of interleukin-6 and C-reactive protein, was measured from pre-treatment plasma samples and a metabolomic profile was defined using serum samples analyzed on three metabolomics platforms targeting fatty acids and complex lipids, amino acids, acylcarnitines, and gut microbiome-derived metabolites among other metabolites of central metabolism. RESULTS: The IMD clinical dimension and the inflammatory index were positively correlated (r = 0.19, p = 0.019) after controlling for age, sex, and body mass index, whereas the Melancholic and Anxious distress dimensions were not, replicating the previous NESDA findings. The three symptom dimensions had distinct metabolomic signatures using both univariate and set enrichment statistics. IMD severity correlated mainly with gut-derived metabolites and a few acylcarnitines and long chain saturated free fatty acids. Melancholia severity was significantly correlated with several phosphatidylcholines, primarily the ether-linked variety, lysophosphatidylcholines, as well as several amino acids. Anxious distress severity correlated with several medium and long chain free fatty acids, both saturated and polyunsaturated ones, sphingomyelins, as well as several amino acids and bile acids. CONCLUSION: The IMD dimension of depression appears reliably associated with markers of inflammation. Metabolomics provides powerful tools to inform about depression heterogeneity and molecular mechanisms related to clinical dimensions in MDD, which include a link to gut microbiome and lipids implicated in membrane structure and function.

Body Fat Distribution, Glucose Metabolism, and Diabetes Status Among Older Adults: The Multiethnic Cohort Adiposity Phenotype Study.

BACKGROUND: As the proportion of visceral (VAT) to subcutaneous adipose tissue (SAT) may contribute to type 2 diabetes (T2D) development, we examined this relation in a cross-sectional design within the Multiethnic Cohort that includes Japanese Americans known to have high VAT. The aim was to understand how ectopic fat accumulation differs by glycemic status across ethnic groups with disparate rates of obesity, T2D, and propensity to accumulate VAT. METHODS: In 2013-2016, 1,746 participants aged 69.2 (standard deviation, 2.7) years from five ethnic groups completed questionnaires, blood collections, and whole-body dual X-ray absorptiometry and abdominal magnetic resonance imaging scans. Participants with self-reported T2D and/or medication were classified as T2D, those with fasting glucose >125 and 100-125 mg/dL as undiagnosed cases (UT2D) and prediabetes (PT2D), respectively. Using linear regression, we estimated adjusted means of adiposity measures by T2D status. RESULTS: Overall, 315 (18%) participants were classified as T2D, 158 (9%) as UT2D, 518 (30%) as PT2D, and 755 (43%) as normoglycemic (NG), with significant ethnic differences (P < 0.0001). In fully adjusted models, VAT, VAT/SAT, and percent liver fat increased significantly from NG, PT2D, UT2D, to T2D (P < 0.001). Across ethnic groups, the VAT/SAT ratio was lowest for NG participants and highest for T2D cases. Positive trends were observed in all groups except African Americans, with highest VAT/SAT in Japanese Americans. CONCLUSION: These findings indicate that VAT plays an important role in T2D etiology, in particular among Japanese Americans with high levels of ectopic adipose tissue, which drives the development of T2D to a greater degree than in other ethnic groups.

Type 2 Diabetes Among Filipino American Adults in the Multiethnic Cohort.

INTRODUCTION: Several Asian racial and ethnic groups, including individuals of Filipino ancestry, are at higher risk of developing type 2 diabetes than White individuals, despite their lower body mass index (BMI). This study examined determinants of type 2 diabetes among Filipino American adults in the Multiethnic Cohort Study. METHODS: Participants in Hawaii and Los Angeles completed questionnaires on demographics, diet, and anthropometrics. Generational status was determined according to birthplace of participants and their parents. Based on self-reported data and data on medications, type 2 diabetes status was classified as no, prevalent, or incident. We used polytomous logistic regression, while adjusting for confounders, to obtain odds ratios. RESULTS: Among 10,681 Multiethnic Cohort Study participants reporting any Filipino ancestry, 57% were 1st-, 17% were 2nd-, and 25% were 3rd-generation Filipino Americans. Overall, 13% and 17% of participants had a prevalent or incident type 2 diabetes diagnosis. Overweight and obesity and the presence of other risk factors increased from the 1st to subsequent generations. First-generation immigrants were less likely to report type 2 diabetes at cohort entry than immigrants of subsequent generations who were born in the US or whose parents were born in the US; only the prevalence of type 2 diabetes was significantly elevated in the 2nd generation compared with the 1st generation. CONCLUSION: The results support the hypothesis that Filipino migrants adopt lifestyle factors of the host country and subsequent generations experience higher type 2 diabetes rates due to changes in risk factor patterns.

Associations of the gut microbiome with hepatic adiposity in the Multiethnic Cohort Adiposity Phenotype Study.

Nonalcoholic fatty liver disease (NAFLD) is a risk factor for liver cancer and prevalence varies by ethnicity. Along with genetic and lifestyle factors, the gut microbiome (GM) may contribute to NAFLD and its progression to advanced liver disease. Our cross-sectional analysis assessed the association of the GM with hepatic adiposity among African American, Japanese American, White, Latino, and Native Hawaiian participants in the Multiethnic Cohort. We used MRI to measure liver fat and determine nonalcoholic fatty liver disease (NAFLD) status (n = 511 cases) in 1,544 participants, aged 60-77 years, with 12-53% overall adiposity (BMI of 17.8-46.2 kg/m2). The GM was measured by 16S rRNA gene sequencing and, on a subset, by metagenomic sequencing. Alpha diversity was lower overall with NAFLD and in certain ethnicities (African Americans, Whites, and Latinos). In models regressing genus on NAFLD status, 62 of 149 genera (40%) exhibited a significant interaction between NAFLD and ethnicity stratified analysis found 69 genera significantly associated with NAFLD in at least one ethnic group. No single genus was significantly associated with NAFLD across all ethnicities. In contrast, the same bacterial metabolic pathways were over-represented in participants with NAFLD regardless of ethnicity. Imputed secondary bile acid and carbohydrate pathways were associated with NAFLD, the latter of which was corroborated by metagenomics, although different genera in different ethnicities were associated with these pathways. Overall, we found that NAFLD was associated with altered bacterial composition and metabolism, and that bacterial endotoxin, assessed by plasma lipopolysaccharide binding protein (LBP), may mediate liver fat-associated systemic inflammation in a manner that seems to vary by ethnicity.

Qualitative Characterization of the Rat Liver Mitochondrial Lipidome Using All Ion Fragmentation on an Exactive Benchtop Orbitrap MS.

Untargeted lipidomics profiling by liquid chromatography -mass spectrometry (LC-MS) allows researchers to observe the occurrences of lipids in a biological sample without showing intentional bias to any specific class of lipids and allows retrospective reanalysis of data collected. Typically, and in the specific method described, a general extraction method followed by LC separation is used to achieve nonspecific class coverage of the lipidome prior to high resolution accurate mass (HRAM) MS detection . Here we describe a workflow including the isolation of mitochondria from liver tissue, followed by mitochondrial lipid extraction and the LC-MS conditions used for data acquisition. We also highlight how, in this method, all ion fragmentation can be used to identify species of lower abundances, often missed by data dependent fragmentation techniques. Here we describe the isolation of mitochondria from liver tissue, followed by mitochondrial lipid extraction and the LC-MS conditions used for data acquisition.

The gut microbiome and type 2 diabetes status in the Multiethnic Cohort.

BACKGROUND: The gut microbiome may play a role in inflammation associated with type 2 diabetes (T2D) development. This cross-sectional study examined its relation with glycemic status within a subset of the Multiethnic Cohort (MEC) and estimated the association of circulating bacterial endotoxin (measured as plasma lipopolysaccharide-binding protein (LBP)) with T2D, which may be mediated by C-reactive protein (CRP). METHODS: In 2013-16, cohort members from five ethnic groups completed clinic visits, questionnaires, and stool and blood collections. Participants with self-reported T2D and/or taking medication were considered T2D cases. Those with fasting glucose >125 and 100-125 mg/dL were classified as undiagnosed (UT2D) and pre-diabetes (PT2D) cases, respectively. We characterized the gut microbiome through 16S rRNA gene sequencing and measured plasma LBP and CRP by standard assays. Linear regression was applied to estimate associations of the gut microbiome community structure and LBP with T2D status adjusting for relevant confounders. RESULTS: Among 1,702 participants (59.9-77.4 years), 735 (43%) were normoglycemic (NG), 506 (30%) PT2D, 154 (9%) UT2D, and 307 (18%) T2D. The Shannon diversity index decreased (ptrend = 0.05), while endotoxin, measured as LBP, increased (ptrend = 0.0003) from NG to T2D. Of 10 phyla, Actinobacteria (ptrend = 0.007), Firmicutes (ptrend = 0.003), and Synergistetes (ptrend = 0.02) were inversely associated and Lentisphaerae (ptrend = 0.01) was positively associated with T2D status. Clostridium sensu stricto 1, Lachnospira, and Peptostreptococcaceae were less, while Escherichia-Shigella and Lachnospiraceae were more abundant among T2D patients, but the associations with Actinobacteria, Clostridium sensu stricto 1, and Escherichia-Shigella may be due metformin use. PT2D/UT2D values were closer to NG than T2D. No indication was detected that CRP mediated the association of LBP with T2D. CONCLUSIONS: T2D but not PT2D/UT2D status was associated with lower abundance of SCFA-producing genera and a higher abundance of gram-negative endotoxin-producing bacteria suggesting that the gut microbiome may contribute to chronic systemic inflammation and T2D through bacterial translocation.

Genome-Wide Association Study of Liver Fat: The Multiethnic Cohort Adiposity Phenotype Study.

The global rise in fatty liver is a major public health problem. Thus, it is critical to identify both global and population-specific genetic variants associated with liver fat. We conducted a genome-wide association study (GWAS) of percent liver fat and nonalcoholic fatty liver disease (NAFLD) assessed by magnetic resonance imaging in 1,709 participants from the population-based Multiethnic Cohort Adiposity Phenotype Study. Our participants comprised older adults of five U.S. racial/ethnic groups: African Americans (n = 277), Japanese Americans (n = 424), Latinos (n = 348), Native Hawaiians (n = 274), and European Americans (n = 386). The established missense risk variant rs738409 located in patatin-like phospholipase domain containing 3 (PNPLA3) at 22q13 was confirmed to be associated with percent liver fat (P = 3.52 × 10-15) but more strongly in women than men (P heterogeneity = 0.002). Its frequency correlated with the prevalence of NAFLD across the five ethnic/racial groups. Rs738409 was also associated with homeostasis model assessment of insulin resistance (HOMA-IR) (beta = 0.028; P = 0.009) and circulating levels of insulin (beta = 0.022; P = 0.020) and alanine aminotransferase (beta = 0.016; P = 0.030). A novel association of percent liver fat with rs77249491 (located at 6q13 between limb region 1 domain containing 1 [LMBRD1] and collagen type XIX alpha 1 chain [COL19A1] (P = 1.42 × 10-8) was also observed. Rs7724941 was associated with HOMA-IR (beta = 0.12; P = 0.0005), insulin (beta = 0.11; P = 0.0003), triglycerides (beta = 0.059; P = 0.01), high-density lipoprotein (beta = -0.046; P = 0.04), and sex hormone binding globulin (beta = -0.084; P = 0.0012). This variant was present in Japanese Americans (minor allele frequency [MAF], 8%) and Native Hawaiians (MAF, 2%). Conclusion: We replicated the PNPLA3 rs738409 association in a multiethnic population and identified a novel liver fat risk variant in Japanese Americans and Native Hawaiians. GWASes of percent liver fat in East Asian and Oceanic populations are needed to replicate the rs77249491 association.