Protein Biomarkers for Insulin Resistance and Type 2 Diabetes Risk in Two Large Community Cohorts

Multivariable Mendelian randomization with incomplete measurements on the exposure variables in the Hispanic Community Health Study/Study of Latinos

Multivariable Mendelian randomization allows simultaneous estimation of direct causal effects of multiple exposure variables on an outcome. When the exposure variables of interest are quantitative omic features, obtaining complete data can be economically and technically challenging: the measurement cost is high, and the measurement devices may have inherent detection limits. In this paper, we propose a valid and efficient method to handle unmeasured and undetectable values of the exposure variables in a one-sample multivariable Mendelian randomization analysis with individual-level data. We estimate the direct causal effects with maximum likelihood estimation and develop an expectation-maximization algorithm to compute the estimators. We show the advantages of the proposed method through simulation studies and provide an application to the Hispanic Community Health Study/Study of Latinos, which has a large amount of unmeasured exposure data.

Molecular mechanisms linking type 2 diabetes mellitus and late-onset Alzheimer's disease: A systematic review and qualitative meta-analysis

Research evidence indicating common metabolic mechanisms through which type 2 diabetes mellitus (T2DM) increases risk of late-onset Alzheimer's dementia (LOAD) has accumulated over recent decades. The aim of this systematic review is to provide a comprehensive review of common mechanisms, which have hitherto been discussed in separate perspectives, and to assemble and evaluate candidate loci and epigenetic modifications contributing to polygenic risk linkages between T2DM and LOAD. For the systematic review on pathophysiological mechanisms, both human and animal studies up to December 2023 are included. For the qualitative meta-analysis of genomic bases, human association studies were examined; for epigenetic mechanisms, data from human studies and animal models were accepted. Papers describing pathophysiological studies were identified in databases, and further literature gathered from cited work. For genomic and epigenomic studies, literature mining was conducted by formalised search codes using Boolean operators in search engines, and augmented by GeneRif citations in Entrez Gene, and other sources (WikiGenes, etc.). For the systematic review of pathophysiological mechanisms, 923 publications were evaluated, and 138 gene loci extracted for testing candidate risk linkages. 3 57 publications were evaluated for genomic association and descriptions of epigenomic modifications. Overall accumulated results highlight insulin signalling, inflammation and inflammasome pathways, proteolysis, gluconeogenesis and glycolysis, glycosylation, lipoprotein metabolism and oxidation, cell cycle regulation or survival, autophagic-lysosomal pathways, and energy. Documented findings suggest interplay between brain insulin resistance, neuroinflammation, insult compensatory mechanisms, and peripheral metabolic dysregulation in T2DM and LOAD linkage. The results allow for more streamlined longitudinal studies of T2DM-LOAD risk linkages.

β-Thalassemia and Diabetes Mellitus: Current State and Future Directions

β-Thalassemia major is a congenital hemoglobin disorder that requires regular blood transfusion. The disease is often associated with iron overload and diabetes mellitus, among other complications. Pancreatic iron overload in β-thalassemia patients disrupts β-cell function and insulin secretion and induces insulin resistance. Several risk factors, including family history of diabetes, sedentary lifestyle, obesity, gender, and advanced age increase the risk of diabetes in β-thalassemia patients. Precautionary measures such as blood glucose monitoring, anti-diabetic medications, and healthy living in β-thalassemia patients notwithstanding, the prevalence of diabetes in β-thalassemia patients continues to rise. This review aims to address the relationship between β-thalassemia and diabetes in an attempt to understand how the pathology and management of β-thalassemia precipitate diabetes mellitus. The possible employment of surrogate biomarkers for early prediction and intervention is discussed. More work is still needed to better understand the molecular mechanism(s) underlying the link between β-thalassemia and diabetes and to identify novel prognostic and therapeutic targets.

Monocytes Release Pro-Cathepsin D to Drive Blood-to-Brain Transcytosis in Diabetes

BACKGROUND

Microvascular complications are the major outcome of type 2 diabetes progression, and the underlying mechanism remains to be determined.

METHODS

High-throughput RNA sequencing was performed using human monocyte samples from controls and diabetes. The transgenic mice expressing human CTSD (cathepsin D) in the monocytes was constructed using CD68 promoter. In vivo 2-photon imaging, behavioral tests, immunofluorescence, transmission electron microscopy, Western blot analysis, vascular leakage assay, and single-cell RNA sequencing were performed to clarify the phenotype and elucidate the molecular mechanism.

RESULTS

Monocytes expressed high-level CTSD in patients with type 2 diabetes. The transgenic mice expressing human CTSD in the monocytes showed increased brain microvascular permeability resembling the diabetic microvascular phenotype, accompanied by cognitive deficit. Mechanistically, the monocytes release nonenzymatic pro-CTSD to upregulate caveolin expression in brain endothelium triggering caveolae-mediated transcytosis, without affecting the paracellular route of brain microvasculature. The circulating pro-CTSD activated the caveolae-mediated transcytosis in brain endothelial cells via its binding with low-density LRP1 (lipoprotein receptor-related protein 1). Importantly, genetic ablation of CTSD in the monocytes exhibited a protective effect against the diabetes-enhanced brain microvascular transcytosis and the diabetes-induced cognitive impairment.

CONCLUSIONS

These findings uncover the novel role of circulatory pro-CTSD from monocytes in the pathogenesis of cerebral microvascular lesions in diabetes. The circulatory pro-CTSD is a potential target for the intervention of microvascular complications in diabetes.

Cardiometabolic profiles and proteomics associated with obesity phenotypes in a longitudinal cohort of young adults

To assess cardiometabolic profiles and proteomics to identify biomarkers associated with the metabolically healthy and unhealthy obesity. Young adults (N = 156) enrolled were classified as not having obesity, metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUHO) based on NCEP ATP-III criteria. Plasma proteomics at study entry were measured using Olink Cardiometabolic Explore panel. Linear regression was used to assess associations between proteomics and obesity groups as well as cardiometabolic traits of glucose, insulin, and lipid profiles at baseline and follow-up visits. Enriched biological pathways were further identified based on the significant proteomic features. Among the baseline 95 (61%) and 61 (39%) participants classified as not having obesity and having obesity (8 MHO and 53 MUHO), respectively. Eighty of the participants were followed-up with an average 4.6 years. Forty-one proteins were associated with obesity (FDR < 0.05), 29 of which had strong associations with insulin-related traits and lipid profiles (FDR < 0.05). Inflammation, immunomodulation, extracellular matrix remodeling and endoplasmic reticulum lumen functions were enriched by 40 proteins. In this study population, obesity and MHO were associated with insulin resistance and dysregulated lipid profiles. The underlying mechanism included elevated inflammation and deteriorated extracellular matrix remodeling function.

Lessons and Applications of Omics Research in Diabetes Epidemiology

PURPOSE OF REVIEW

Recent advances in genomic technology and molecular techniques have greatly facilitated the identification of disease biomarkers, advanced understanding of pathogenesis of different common diseases, and heralded the dawn of precision medicine. Much of these advances in the area of diabetes have been made possible through deep phenotyping of epidemiological cohorts, and analysis of the different omics data in relation to detailed clinical information. In this review, we aim to provide an overview on how omics research could be incorporated into the design of current and future epidemiological studies.

RECENT FINDINGS

We provide an up-to-date review of the current understanding in the area of genetic, epigenetic, proteomic and metabolomic markers for diabetes and related outcomes, including polygenic risk scores. We have drawn on key examples from the literature, as well as our own experience of conducting omics research using the Hong Kong Diabetes Register and Hong Kong Diabetes Biobank, as well as other cohorts, to illustrate the potential of omics research in diabetes. Recent studies highlight the opportunity, as well as potential benefit, to incorporate molecular profiling in the design and set-up of diabetes epidemiology studies, which can also advance understanding on the heterogeneity of diabetes. Learnings from these examples should facilitate other researchers to consider incorporating research on omics technologies into their work to advance the field and our understanding of diabetes and its related co-morbidities. Insights from these studies would be important for future development of precision medicine in diabetes.

Genetic overlap and causal inferences between diet-derived antioxidants and small-cell lung cancer

Several studies have reported that antioxidants exert both preventive and inhibitory effects against tumors. However, their causal effects on small-cell lung cancer (SCLC) remain controversial. Herein, we explored the causal effects of 6 antioxidants on SCLC by combining a genome-wide association study database and the Mendelian randomization (MR) approach. We obtained antioxidant genetic variance data for 6 exposure factors: carotene, vitamin A (retinol), selenium, zinc, vitamin C, and vitamin E, from the genome-wide association study database. The instrumental variables for exposure factors and SCLC outcomes were integrated by screening instrumental variables and merging data. Two-sample MR was used to analyze the causal relationship between exposure and outcomes. Finally, we examined the heterogeneity and horizontal pleiotropy of the MR analysis by performing multiple sensitivity analyses. We found a causal relationship between carotene and SCLC using two-sample MR analysis and sensitivity analysis (P = .02; odds ratio = 0.73; 95% confidence interval: 0.55-0.95). In contrast, there was no causal relationship between other examined antioxidants and SCLC. We found that diet-derived circulating antioxidants could afford protection against SCLC, and carotene is the causal protective factor against SCLC.

Targeted Proteomics Reveals Functional Targets for Early Diabetes Susceptibility in Young Adults

BACKGROUND

The circulating proteome may encode early pathways of diabetes susceptibility in young adults for surveillance and intervention. Here, we define proteomic correlates of tissue phenotypes and diabetes in young adults.

METHODS

We used penalized models and principal components analysis to generate parsimonious proteomic signatures of diabetes susceptibility based on phenotypes and on diabetes diagnosis across 184 proteins in >2000 young adults in the CARDIA (Coronary Artery Risk Development in Young Adults study; mean age, 32 years; 44% women; 43% Black; mean body mass index, 25.6±4.9 kg/m2), with validation against diabetes in >1800 individuals in the FHS (Framingham Heart Study) and WHI (Women's Health Initiative).

RESULTS

In 184 proteins in >2000 young adults in CARDIA, we identified 2 proteotypes of diabetes susceptibility-a proinflammatory fat proteotype (visceral fat, liver fat, inflammatory biomarkers) and a muscularity proteotype (muscle mass), linked to diabetes in CARDIA and WHI/FHS. These proteotypes specified broad mechanisms of early diabetes pathogenesis, including transorgan communication, hepatic and skeletal muscle stress responses, vascular inflammation and hemostasis, fibrosis, and renal injury. Using human adipose tissue single cell/nuclear RNA-seq, we demonstrate expression at transcriptional level for implicated proteins across adipocytes and nonadipocyte cell types (eg, fibroadipogenic precursors, immune and vascular cells). Using functional assays in human adipose tissue, we demonstrate the association of expression of genes encoding these implicated proteins with adipose tissue metabolism, inflammation, and insulin resistance.

CONCLUSIONS

A multifaceted discovery effort uniting proteomics, underlying clinical susceptibility phenotypes, and tissue expression patterns may uncover potentially novel functional biomarkers of early diabetes susceptibility in young adults for future mechanistic evaluation.

Mendelian randomization with incomplete measurements on the exposure in the Hispanic Community Health Study/Study of Latinos

Mendelian randomization has been widely used to assess the causal effect of a heritable exposure variable on an outcome of interest, using genetic variants as instrumental variables. In practice, data on the exposure variable can be incomplete due to high cost of measurement and technical limits of detection. In this paper, we propose a valid and efficient method to handle both unmeasured and undetectable values of the exposure variable in one-sample Mendelian randomization analysis with individual-level data. We estimate the causal effect of the exposure variable on the outcome using maximum likelihood estimation and develop an expectation maximization algorithm for the computation of the estimator. Simulation studies show that the proposed method performs well in making inference on the causal effect. We apply our method to the Hispanic Community Health Study/Study of Latinos, a community-based prospective cohort study, and estimate the causal effect of several metabolites on phenotypes of interest.

p21-activated kinase 4 counteracts PKA-dependent lipolysis by phosphorylating FABP4 and HSL

Adipose tissue lipolysis is mediated by cAMP-protein kinase A (PKA)-dependent intracellular signalling. Here, we show that PKA targets p21-activated kinase 4 (PAK4), leading to its protein degradation. Adipose tissue-specific overexpression of PAK4 in mice attenuates lipolysis and exacerbates diet-induced obesity. Conversely, adipose tissue-specific knockout of Pak4 or the administration of a PAK4 inhibitor in mice ameliorates diet-induced obesity and insulin resistance while enhancing lipolysis. Pak4 knockout also increases energy expenditure and adipose tissue browning activity. Mechanistically, PAK4 directly phosphorylates fatty acid-binding protein 4 (FABP4) at T126 and hormone-sensitive lipase (HSL) at S565, impairing their interaction and thereby inhibiting lipolysis. Levels of PAK4 and the phosphorylation of FABP4-T126 and HSL-S565 are enhanced in the visceral fat of individuals with obesity compared to their lean counterparts. In summary, we have uncovered an important role for FABP4 phosphorylation in regulating adipose tissue lipolysis, and PAK4 inhibition may offer a therapeutic strategy for the treatment of obesity.

Inter-organ crosstalk during development and progression of type 2 diabetes mellitus

Type 2 diabetes mellitus (T2DM) is characterized by tissue-specific insulin resistance and pancreatic β-cell dysfunction, which result from the interplay of local abnormalities within different tissues and systemic dysregulation of tissue crosstalk. The main local mechanisms comprise metabolic (lipid) signalling, altered mitochondrial metabolism with oxidative stress, endoplasmic reticulum stress and local inflammation. While the role of endocrine dysregulation in T2DM pathogenesis is well established, other forms of inter-organ crosstalk deserve closer investigation to better understand the multifactorial transition from normoglycaemia to hyperglycaemia. This narrative Review addresses the impact of certain tissue-specific messenger systems, such as metabolites, peptides and proteins and microRNAs, their secretion patterns and possible alternative transport mechanisms, such as extracellular vesicles (exosomes). The focus is on the effects of these messengers on distant organs during the development of T2DM and progression to its complications. Starting from the adipose tissue as a major organ relevant to T2DM pathophysiology, the discussion is expanded to other key tissues, such as skeletal muscle, liver, the endocrine pancreas and the intestine. Subsequently, this Review also sheds light on the potential of multimarker panels derived from these biomarkers and related multi-omics for the prediction of risk and progression of T2DM, novel diabetes mellitus subtypes and/or endotypes and T2DM-related complications.

Hallmarks of the metabolic secretome

The identification of novel secreted factors is advancing at an unprecedented pace. However, there is a critical need to consolidate and integrate this knowledge to provide a framework of their diverse mechanisms, functional significance, and inter-relationships. Complicating this effort are challenges related to nonstandardized methods, discrepancies in sample handling, and inconsistencies in the annotation of unknown molecules. This Review aims to synthesize the rapidly expanding field of the metabolic secretome, encompassing the five major types of secreted factors: proteins, peptides, metabolites, lipids, and extracellular vesicles. By systematically defining the functions and detection of the components within the metabolic secretome, this Review provides a primer into the advances of the field, and how integration of the techniques discussed can provide a deeper understanding of the mechanisms underlying metabolic homeostasis and its disorders.

Assessing the causal relationship between COVID-19 and post-COVID-19 syndrome: A Mendelian randomisation study

Background

In the aftermath of the coronavirus disease 2019 (COVID-19) pandemic, we sought to explore the causal association between COVID-19 and 17 prevalent post-COVID-19 syndrome (PCS) symptoms using Mendelian randomisation (MR) methodology.

Methods

We used 22 extensive genome-wide association study (GWAS) data sets, incorporating genetic variants as instrumental variables. Univariate Mendelian randomisation (UVMR) analyses involved 15 single nucleotide polymorphisms (SNPs) for COVID-19 patients, 33 for hospitalised COVID-19 patients, and 29 for patients with severe respiratory symptoms due to COVID-19. Furthermore, we further used multivariable Mendelian randomisation (MVMR) analyses based on 93 SNPs for COVID-19 patients, 105 for hospitalised COVID-19 patients, and 99 for patients with severe respiratory symptoms due to COVID-19. With these analyses, we aimed to assess the causal associations between varying levels of COVID-19 infection and 17 prevalent PCS symptoms while accounting for the influence of educational and income levels.

Results

UVMR analysis identified potential causal effects of COVID-19 genetic susceptibility on myalgia and pain in various regions. Hospitalised COVID-19 was potentially linked to erectile dysfunction and alopecia areata. Very severe respiratory confirmed patients exhibited increased pain and tobacco use. Meanwhile, the MVMR analysis demonstrated a potential causal link between hospitalised COVID-19 and heart arrhythmia, and a protective effect of COVID-19 on tobacco use after adjusting for educational and income levels.

Conclusions

Our MR analysis provides compelling evidence of causal associations between genetic susceptibility to COVID-19 and specific PCS symptoms, in which educational and income levels play a mediating role. These findings shed light on PCS pathogenesis and underscore the importance of considering social factors in its management. Tailored interventions and policies are crucial for PCS-affected individuals' well-being. Further research is needed to explore the impact of social determinants on COVID-19 patients and the wider population.

Mendelian randomization analyses suggest a causal role for circulating GIP and IL-1RA levels in homeostatic model assessment-derived measures of β-cell function and insulin sensitivity in Africans without type 2 diabetes

BACKGROUND

In vitro and in vivo studies have shown that certain cytokines and hormones may play a role in the development and progression of type 2 diabetes (T2D). However, studies on their role in T2D in humans are scarce. We evaluated associations between 11 circulating cytokines and hormones with T2D among a population of sub-Saharan Africans and tested for causal relationships using Mendelian randomization (MR) analyses.

METHODS

We used logistic regression analysis adjusted for age, sex, body mass index, and recruitment country to regress levels of 11 cytokines and hormones (adipsin, leptin, visfatin, PAI-1, GIP, GLP-1, ghrelin, resistin, IL-6, IL-10, IL-1RA) on T2D among Ghanaians, Nigerians, and Kenyans from the Africa America Diabetes Mellitus study including 2276 individuals with T2D and 2790 non-T2D individuals. Similar linear regression models were fitted with homeostatic modelling assessments of insulin sensitivity (HOMA-S) and β-cell function (HOMA-B) as dependent variables among non-T2D individuals (n = 2790). We used 35 genetic variants previously associated with at least one of these 11 cytokines and hormones among non-T2D individuals as instrumental variables in univariable and multivariable MR analyses. Statistical significance was set at 0.0045 (0.05/11 cytokines and hormones).

RESULTS

Circulating GIP and IL-1RA levels were associated with T2D. Nine of the 11 cytokines and hormones (exceptions GLP-1 and IL-6) were associated with HOMA-S, HOMA-B, or both among non-T2D individuals. Two-stage least squares MR analysis provided evidence for a causal effect of GIP and IL-RA on HOMA-S and HOMA-B in multivariable analyses (GIP ~ HOMA-S β =  - 0.67, P-value = 1.88 × 10-6 and HOMA-B β = 0.59, P-value = 1.88 × 10-5; IL-1RA ~ HOMA-S β =  - 0.51, P-value = 8.49 × 10-5 and HOMA-B β = 0.48, P-value = 5.71 × 10-4). IL-RA was partly mediated via BMI (30-34%), but GIP was not. Inverse variance weighted MR analysis provided evidence for a causal effect of adipsin on T2D (multivariable OR = 1.83, P-value = 9.79 × 10-6), though these associations were not consistent in all sensitivity analyses.

CONCLUSIONS

The findings of this comprehensive MR analysis indicate that circulating GIP and IL-1RA levels are causal for reduced insulin sensitivity and increased β-cell function. GIP's effect being independent of BMI suggests that circulating levels of GIP could be a promising early biomarker for T2D risk. Our MR analyses do not provide conclusive evidence for a causal role of other circulating cytokines in T2D among sub-Saharan Africans.

Label-free quantitative proteomics analysis for type 2 diabetes mellitus early diagnostic marker discovery using data-independent acquisition mass spectrometry (DIA-MS)

Type-2 diabetes mellitus (T2DM) therapy requires early diagnosis and complication avoidance. Unfortunately, current diagnostic markers do not meet these needs. Data-independent acquisition mass spectrometry (DIA-MS) offers a solution for clinical diagnosis, providing reliable and precise sample quantification. This study utilized DIA-MS to investigate proteomic differential expression in the serum of recently diagnosed T2DM patients. The study conducted a comparative protein expression analysis between healthy and recently diagnosed T2DM groups (discovery cohort). A candidate protein was then validated using enzyme-linked immune assay (ELISA) on serum samples collected from T2DM patients (n = 87) and healthy control (n = 60) (validation cohort). A total of 1074 proteins were identified, and 90 were significantly dysregulated between the two groups, including 32 newly associated with T2DM. Among these proteins, the expression of S100 calcium-binding protein A6 (S100A6) was validated by ELISA. It showed a significant increase in T2DM samples compared to the control group. It was evaluated as a biomarker using the receiver operating characteristic (ROC) curve, consistent with the DIA-MS results. Novel proteins are reported to be involved in the development and progression of T2DM. Further studies are required to investigate the differential expression of candidate marker proteins in a larger population of T2DM patients.

Multi-tissue epigenetic analysis identifies distinct associations underlying insulin resistance and Alzheimer's disease at CPT1A locus

BACKGROUND

Insulin resistance (IR) is a major risk factor for Alzheimer's disease (AD) dementia. The mechanisms by which IR predisposes to AD are not well-understood. Epigenetic studies may help identify molecular signatures of IR associated with AD, thus improving our understanding of the biological and regulatory mechanisms linking IR and AD.

METHODS

We conducted an epigenome-wide association study of IR, quantified using the homeostatic model assessment of IR (HOMA-IR) and adjusted for body mass index, in 3,167 participants from the Framingham Heart Study (FHS) without type 2 diabetes at the time of blood draw used for methylation measurement. We identified DNA methylation markers associated with IR at the genome-wide level accounting for multiple testing (P < 1.1 × 10-7) and evaluated their association with neurological traits in participants from the FHS (N = 3040) and the Religious Orders Study/Memory and Aging Project (ROSMAP, N = 707). DNA methylation profiles were measured in blood (FHS) or dorsolateral prefrontal cortex (ROSMAP) using the Illumina HumanMethylation450 BeadChip. Linear regressions (ROSMAP) or mixed-effects models accounting for familial relatedness (FHS) adjusted for age, sex, cohort, self-reported race, batch, and cell type proportions were used to assess associations between DNA methylation and neurological traits accounting for multiple testing.

RESULTS

We confirmed the strong association of blood DNA methylation with IR at three loci (cg17901584-DHCR24, cg17058475-CPT1A, cg00574958-CPT1A, and cg06500161-ABCG1). In FHS, higher levels of blood DNA methylation at cg00574958 and cg17058475 were both associated with lower IR (P = 2.4 × 10-11 and P = 9.0 × 10-8), larger total brain volumes (P = 0.03 and P = 9.7 × 10-4), and smaller log lateral ventricular volumes (P = 0.07 and P = 0.03). In ROSMAP, higher levels of brain DNA methylation at the same two CPT1A markers were associated with greater risk of cognitive impairment (P = 0.005 and P = 0.02) and higher AD-related indices (CERAD score: P = 5 × 10-4 and 0.001; Braak stage: P = 0.004 and P = 0.01).

CONCLUSIONS

Our results suggest potentially distinct epigenetic regulatory mechanisms between peripheral blood and dorsolateral prefrontal cortex tissues underlying IR and AD at CPT1A locus.

Associations of plasma proteomics with type 2 diabetes and related traits: results from the longitudinal KORA S4/F4/FF4 Study

AIMS/HYPOTHESIS

This study aimed to elucidate the aetiological role of plasma proteins in glucose metabolism and type 2 diabetes development.

METHODS

We measured 233 proteins at baseline in 1653 participants from the Cooperative Health Research in the Region of Augsburg (KORA) S4 cohort study (median follow-up time: 13.5 years). We used logistic regression in the cross-sectional analysis (n=1300), and Cox regression accounting for interval-censored data in the longitudinal analysis (n=1143). We further applied two-level growth models to investigate associations with repeatedly measured traits (fasting glucose, 2 h glucose, fasting insulin, HOMA-B, HOMA-IR, HbA1c), and two-sample Mendelian randomisation analysis to investigate causal associations. Moreover, we built prediction models using priority-Lasso on top of Framingham-Offspring Risk Score components and evaluated the prediction accuracy through AUC.

RESULTS

We identified 14, 24 and four proteins associated with prevalent prediabetes (i.e. impaired glucose tolerance and/or impaired fasting glucose), prevalent newly diagnosed type 2 diabetes and incident type 2 diabetes, respectively (28 overlapping proteins). Of these, IL-17D, IL-18 receptor 1, carbonic anhydrase-5A, IL-1 receptor type 2 (IL-1RT2) and matrix extracellular phosphoglycoprotein were novel candidates. IGF binding protein 2 (IGFBP2), lipoprotein lipase (LPL) and paraoxonase 3 (PON3) were inversely associated while fibroblast growth factor 21 was positively associated with incident type 2 diabetes. LPL was longitudinally linked with change in glucose-related traits, while IGFBP2 and PON3 were linked with changes in both insulin- and glucose-related traits. Mendelian randomisation analysis suggested causal effects of LPL on type 2 diabetes and fasting insulin. The simultaneous addition of 12 priority-Lasso-selected biomarkers (IGFBP2, IL-18, IL-17D, complement component C1q receptor, V-set and immunoglobulin domain-containing protein 2, IL-1RT2, LPL, CUB domain-containing protein 1, vascular endothelial growth factor D, PON3, C-C motif chemokine 4 and tartrate-resistant acid phosphatase type 5) significantly improved the predictive performance (ΔAUC 0.0219; 95% CI 0.0052, 0.0624).

CONCLUSIONS/INTERPRETATION

We identified new candidates involved in the development of derangements in glucose metabolism and type 2 diabetes and confirmed previously reported proteins. Our findings underscore the importance of proteins in the pathogenesis of type 2 diabetes and the identified putative proteins can function as potential pharmacological targets for diabetes treatment and prevention.

Proteomic Predictors of Incident Diabetes: Results From the Atherosclerosis Risk in Communities (ARIC) Study

OBJECTIVE

The plasma proteome preceding diabetes can improve our understanding of diabetes pathogenesis.

RESEARCH DESIGN AND METHODS

In 8,923 Atherosclerosis Risk in Communities (ARIC) Study participants (aged 47-70 years, 57% women, 19% Black), we conducted discovery and internal validation for associations of 4,955 plasma proteins with incident diabetes. We externally validated results in the Singapore Multi-Ethnic Cohort (MEC) nested case-control (624 case subjects, 1,214 control subjects). We used Cox regression to discover and validate protein associations and risk-prediction models (elastic net regression with cardiometabolic risk factors and proteins) for incident diabetes. We conducted a pathway analysis and examined causality using genetic instruments.

RESULTS

There were 2,147 new diabetes cases over a median of 19 years. In the discovery sample (n = 6,010), 140 proteins were associated with incident diabetes after adjustment for 11 risk factors (P < 10-5). Internal validation (n = 2,913) showed 64 of the 140 proteins remained significant (P < 0.05/140). Of the 63 available proteins, 47 (75%) were validated in MEC. Novel associations with diabetes were found for 22 the 47 proteins. Prediction models (27 proteins selected by elastic net) developed in discovery had a C statistic of 0.731 in internal validation, with ΔC statistic of 0.011 (P = 0.04) beyond 13 risk factors, including fasting glucose and HbA1c. Inflammation and lipid metabolism pathways were overrepresented among the diabetes-associated proteins. Genetic instrument analyses suggested plasma SHBG, ATP1B2, and GSTA1 play causal roles in diabetes risk.

CONCLUSIONS

We identified 47 plasma proteins predictive of incident diabetes, established causal effects for 3 proteins, and identified diabetes-associated inflammation and lipid pathways with potential implications for diagnosis and therapy.

Associations between circadian disruption and cardiometabolic disease risk: A review

The human circadian system plays a vital role in many physiological processes, and circadian rhythms are found in virtually all tissues and organs. The disruption of circadian rhythms may lead to adverse health outcomes. Evidence from recent population-based studies was reviewed because they represent real-world behavior and can be useful in developing future studies to reduce the risk of adverse health conditions, including cardiovascular diseases, obesity, and diabetes mellitus, which may occur because of circadian disruption. An electronic search in PubMed and Web of Science (2012-2022) was performed. Selected articles were based on specific inclusion and exclusion criteria. Five factors that may disrupt circadian rhythm alignment are discussed: shift work, late chronotype, late sleep timing, sleep irregularity, and late meal timing. Evidence from observational studies of these circadian disruptors suggests potential detrimental effects on cardiometabolic health, including higher BMI/obesity, higher blood pressure, greater dyslipidemia, greater inflammation, and diabetes. Future research should identify the specific underlying pathways in order to mitigate the health consequences of shift work. Furthermore, optimal sleep and mealtimes for metabolic health can be explored in intervention studies. Lastly, it is important that the timing of external environmental cues (such as light) and behaviors that influence circadian rhythms are managed.

Targeted proteomics identifies potential biomarkers of dysglycaemia, beta cell function and insulin sensitivity in Black African men and women

AIMS/HYPOTHESIS

Using a targeted proteomics approach, we aimed to identify and validate circulating proteins associated with impaired glucose metabolism (IGM) and type 2 diabetes in a Black South African cohort. In addition, we assessed sex-specific associations between the validated proteins and pathophysiological pathways of type 2 diabetes.

METHODS

This cross-sectional study included Black South African men (n=380) and women (n=375) who were part of the Middle-Aged Soweto Cohort (MASC). Dual-energy x-ray absorptiometry was used to determine fat mass and visceral adipose tissue, and fasting venous blood samples were collected for analysis of glucose, insulin and C-peptide and for targeted proteomics, measuring a total of 184 pre-selected protein biomarkers. An OGTT was performed on participants without diabetes, and peripheral insulin sensitivity (Matsuda index), HOMA-IR, basal insulin clearance, insulin secretion (C-peptide index) and beta cell function (disposition index) were estimated. Participants were classified as having normal glucose tolerance (NGT; n=546), IGM (n=116) or type 2 diabetes (n=93). Proteins associated with dysglycaemia (IGM or type 2 diabetes) in the MASC were validated in the Swedish EpiHealth cohort (NGT, n=1706; impaired fasting glucose, n=550; type 2 diabetes, n=210).

RESULTS

We identified 73 proteins associated with dysglycaemia in the MASC, of which 34 were validated in the EpiHealth cohort. Among these validated proteins, 11 were associated with various measures of insulin dynamics, with the largest number of proteins being associated with HOMA-IR. In sex-specific analyses, IGF-binding protein 2 (IGFBP2) was associated with lower HOMA-IR in women (coefficient -0.35; 95% CI -0.44, -0.25) and men (coefficient -0.09; 95% CI -0.15, -0.03). Metalloproteinase inhibitor 4 (TIMP4) was associated with higher insulin secretion (coefficient 0.05; 95% CI 0.001, 0.11; p for interaction=0.025) and beta cell function (coefficient 0.06; 95% CI 0.02, 0.09; p for interaction=0.013) in women only. In contrast, a stronger positive association between IGFBP2 and insulin sensitivity determined using an OGTT (coefficient 0.38; 95% CI 0.27, 0.49) was observed in men (p for interaction=0.004). A posteriori analysis showed that the associations between TIMP4 and insulin dynamics were not mediated by adiposity. In contrast, most of the associations between IGFBP2 and insulin dynamics, except for insulin secretion, were mediated by either fat mass index or visceral adipose tissue in men and women. Fat mass index was the strongest mediator between IGFBP2 and insulin sensitivity (total effect mediated 40.7%; 95% CI 37.0, 43.6) and IGFBP2 and HOMA-IR (total effect mediated 39.1%; 95% CI 31.1, 43.5) in men.

CONCLUSIONS/INTERPRETATION

We validated 34 proteins that were associated with type 2 diabetes, of which 11 were associated with measures of type 2 diabetes pathophysiology such as peripheral insulin sensitivity and beta cell function. This study highlights biomarkers that are similar between cohorts of different ancestry, with different lifestyles and sociodemographic profiles. The African-specific biomarkers identified require validation in African cohorts to identify risk markers and increase our understanding of the pathophysiology of type 2 diabetes in African populations.

Advances in multi-omics study of biomarkers of glycolipid metabolism disorder

Glycolipid metabolism disorder are major threats to human health and life. Genetic, environmental, psychological, cellular, and molecular factors contribute to their pathogenesis. Several studies demonstrated that neuroendocrine axis dysfunction, insulin resistance, oxidative stress, chronic inflammatory response, and gut microbiota dysbiosis are core pathological links associated with it. However, the underlying molecular mechanisms and therapeutic targets of glycolipid metabolism disorder remain to be elucidated. Progress in high-throughput technologies has helped clarify the pathophysiology of glycolipid metabolism disorder. In the present review, we explored the ways and means by which genomics, transcriptomics, proteomics, metabolomics, and gut microbiomics could help identify novel candidate biomarkers for the clinical management of glycolipid metabolism disorder. We also discuss the limitations and recommended future research directions of multi-omics studies on these diseases.

Apolipoprotein D and transthyretin are reduced in female adolescent offspring of women with type 1 diabetes: The EPICOM study

AIMS

Adolescent offspring exposed to maternal diabetes during intrauterine life show a less favourable metabolic profile than the background population. Here, we hypothesize that offspring of women with type 1 diabetes (T1D), possess sex-specific alterations in the serum profile of proteins involved in lipid, metabolic and transport processes and that these alterations are associated with lipid profile and indices of insulin sensitivity and secretion.

METHODS

A prospective nationwide follow-up study (EPICOM) in a Danish population. Blood samples were assessed from offspring of women with T1D (index offspring, n = 267, 13-20 years), and matched control offspring (n = 290). Serum proteins were analysed using a 25-plex cardio-metabolic targeted proteomics assay, which includes 12 apolipoproteins and 13 transport and inflammatory proteins.

RESULTS

Apolipoprotein D (ApoD) and transthyretin (TTR) were reduced in index females as compared to female controls (-8.1%, p < 0.001 and -6.1%, p = 0.006 respectively), but not in index males (2.2%, p = 0.476 and -2.4%, p = 0.731 respectively). Sex-dependent inverse associations between exposure to maternal T1D in utero and ApoD and TTR were significant after adjusting for age, BMI-SDS and Tanner stage (OR = 0.252 [95% CI 0.085, 0.745], p = 0.013 and OR = 0.149 [95% CI 0.040, 0.553], p = 0.004). ApoD correlated to indices of insulin sensitivity and secretion in a similar sex-specific pattern in crude and adjusted analyses.

CONCLUSIONS

Low ApoD may be regarded as an early risk marker of metabolic syndrome. A possible link between ApoD and cardiovascular disease needs further investigation.

Circulating Proteome and Progression of Type 2 Diabetes

CONTEXT

Circulating proteomes may provide intervention targets for type 2 diabetes (T2D).

OBJECTIVE

We aimed to identify proteomic biomarkers associated with incident T2D and assess its joint effect with dietary or lifestyle factors on the T2D risk.

METHODS

We established 2 nested case-control studies for incident T2D: discovery cohort (median 6.5 years of follow-up, 285 case-control pairs) and validation cohort (median 2.8 years of follow-up, 38 case-control pairs). We integrated untargeted mass spectrometry-based proteomics and interpretable machine learning to identify T2D-related proteomic biomarkers. We constructed a protein risk score (PRS) with the identified proteomic biomarkers and used a generalized estimating equation to evaluate PRS-T2D relationship with repeated profiled proteome. We evaluated association of PRS with trajectory of glycemic traits in another non-T2D cohort (n = 376). Multiplicative interactions of dietary or lifestyle factors with PRS were evaluated using logistic regression.

RESULTS

Seven proteins (SHBG, CAND1, APOF, SELL, MIA3, CFH, IGHV1-2) were retained as the proteomic biomarkers for incident T2D. PRS (per SD change) was positively associated with incident T2D across 2 cohorts, with an odds ratio 1.29 (95% CI, 1.08-1.54) and 1.84 (1.19-2.84), respectively. Participants with a higher PRS had a higher probability showing unfavored glycemic trait trajectory in the non-T2D cohort. Red meat intake and PRS showed a multiplicative interaction on T2D risk in the discovery (P = 0.003) and validation cohort (P = 0.017).

CONCLUSION

This study identified proteomic biomarkers for incident T2D among the Chinese populations. The higher intake of red meat may synergistically interact with the proteomic biomarkers to exaggerate the T2D risk.

Diagnostic and Prognostic Protein Biomarkers of β-Cell Function in Type 2 Diabetes and Their Modulation with Glucose Normalization

Development of type-2 diabetes(T2D) is preceded by β-cell dysfunction and loss. However, accurate measurement of β-cell function remains elusive. Biomarkers have been reported to predict β-cell functional decline but require validation. Therefore, we determined whether reported protein biomarkers could distinguish patients with T2D (onset < 10-years) from controls. A prospective, parallel study in T2D (n = 23) and controls (n = 23) was undertaken. In T2D subjects, insulin-induced blood glucose normalization from baseline 7.6 ± 0.4 mmol/L (136.8 ± 7.2 mg/dL) to 4.5 ± 0.07 mmol/L (81 ± 1.2 mg/dL) was maintained for 1-h. Controls were maintained at 4.9 ± 0.1 mmol/L (88.2 ± 1.8 mg/dL). Slow Off-rate Modified Aptamer (SOMA) -scan plasma protein measurement determined a 43-protein panel reported as diagnostic and/or prognostic for T2D. At baseline, 9 proteins were altered in T2D. Three of 13 prognostic/diagnostic proteins were lower in T2D: Adiponectin (p < 0.0001), Endocan (p < 0.05) and Mast/stem cell growth factor receptor-Kit (KIT) (p < 0.01). Two of 14 prognostic proteins [Cathepsin-D (p < 0.05) and Cadherin-E (p < 0.005)], and four of 16 diagnostic proteins [Kallikrein-4 (p = 0.001), Aminoacylase-1 (p = 0.001), Insulin-like growth factor-binding protein-4 (IGFBP4) (p < 0.05) and Reticulon-4 receptor (RTN4R) (p < 0.001)] were higher in T2D. Protein levels were unchanged following glucose normalization in T2D. Our results suggest that a focused biomarker panel may be useful for assessing β-cell dysfunction and may complement clinical decision-making on insulin therapy. Unchanged post-glucose normalization levels indicate these are not acute-phase proteins or affected by glucose variability.

Proteins associated with incident metabolic syndrome in population-based cohorts

BACKGROUND

The metabolic syndrome (MetS) identifies persons with clustering of multiple cardiometabolic risk factors. The underlying pathology inducing this clustering is not fully known. We used a targeted proteomics assay to identify associations of circulating proteins with MetS and its components, cross-sectionally and longitudinally.

METHODS

We explored and validated associations of 86 cardiovascular proteins, assessed using a proximity extension assay, with the MetS in two independent cohorts; the Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS, n = 996) and Uppsala Longitudinal Study of Adult Men (ULSAM, n = 785). The analyses were adjusted for smoking, exercise habits, education, and energy and alcohol intake.

RESULTS

Nine proteins were associated with all five components of the MetS in PIVUS using FDR < 0.05 in a cross-sectional analysis. Of those nine proteins, only Interleukin-1 receptor antagonist protein (IL-1RA) was associated with all five components of the MetS in ULSAM using p < 0.05. IL-1RA levels were associated with incident MetS (n = 109) in PIVUS during a 5-year follow-up (HR 1.76 for a 1 SD change (95% CI 1.38, 2.24), p = 4.3*10^-6). IL-1RA was however not causally related to MetS in a two-sample Mendelian randomization analysis using published data.

CONCLUSION

Circulating IL-1RA was related to all five components of the MetS in a cross-sectional analysis in two independent samples, as well as to incident MetS in a longitudinal analysis. However, Mendelian randomization analyses did not provide support for a causal role for IL-1RA in the development of MetS.

Evening chronotype is associated with elevated biomarkers of cardiometabolic risk in the EpiHealth cohort: a cross-sectional study

STUDY OBJECTIVES

Individuals with evening chronotype have a higher risk of cardiovascular and metabolic disorders, although the underlying mechanisms are not well understood. In a population-based cohort, we aimed to investigate the association between chronotype and 242 circulating proteins from three panels of established or candidate biomarkers of cardiometabolic processes.

METHODS

In 2,471 participants (49.7% men, mean age 61.2±8.4 SD years) from the EpiHealth cohort, circulating proteins were analyzed with a multiplex proximity extension technique. Participants self-reported their chronotype on a five-level scale from extreme morning to extreme evening chronotype. With the intermediate chronotype set as the reference, each protein was added as the dependent variable in a series of linear regression models adjusted for confounders. Next, the chronotype coefficients were jointly tested and the resulting p-values adjusted for multiple testing using false discovery rate (5%). For the associations identified, we then analyzed the marginal effect of each chronotype category.

RESULTS

We identified 17 proteins associated with chronotype. Evening chronotype was positively associated with proteins previously linked to insulin resistance and cardiovascular risk, namely retinoic acid receptor protein 2, fatty acid-binding protein adipocyte, tissue-type plasminogen activator, and plasminogen activator inhibitor 1 (PAI-1). Additionally, PAI-1 was inversely associated with the extreme morning chronotype.

CONCLUSIONS

In this population-based study, proteins previously related with cardiometabolic risk were elevated in the evening chronotypes. These results may guide future research in the relation between chronotype and cardiometabolic disorders.

Molecular Aspects of Lifestyle and Environmental Effects in Patients With Diabetes: JACC Focus Seminar

Diabetes is characterized as an integrated condition of dysregulated metabolism across multiple tissues, with well-established consequences on the cardiovascular system. Recent advances in precision phenotyping in biofluids and tissues in large human observational and interventional studies have afforded a unique opportunity to translate seminal findings in models and cellular systems to patients at risk for diabetes and its complications. Specifically, techniques to assay metabolites, proteins, and transcripts, alongside more recent assessment of the gut microbiome, underscore the complexity of diabetes in patients, suggesting avenues for precision phenotyping of risk, response to intervention, and potentially novel therapies. In addition, the influence of external factors and inputs (eg, activity, diet, medical therapies) on each domain of molecular characterization has gained prominence toward better understanding their role in prevention. Here, the authors provide a broad overview of the role of several of these molecular domains in human translational investigation in diabetes.

Insulin resistance is linked to a specific profile of immune activation in human subjects

We tested the hypothesis that a particular immune activation profile might be correlated with insulin resistance in a general population. By measuring 43 markers of immune, endothelial, and coagulation activation, we have previously shown that five different immune activation profiles may be distinguished in 150 volunteers. One of these profiles, Profile 2, characterized by CD4+ T cell senescence, inflammation, monocyte, B cell, and endothelial activation, presented elevated insulinemia, glycemia, triglyceridemia, and γ-glutamyl transferase, a marker of liver injury, in comparison with other profiles. Our data are compatible with a model in which a particular immune activation profile might favor the development of insulin resistance and metabolic syndrome. In this hypothesis, identification of this profile, that is feasible with only 3 markers with an error rate of 5%, might allow to personalize the screening and prevention of metabolic syndrome-driven morbidities as liver steatosis.

A Panel of 6 Biomarkers Significantly Improves the Prediction of Type 2 Diabetes in the MONICA/KORA Study Population

CONTEXT

Improved strategies to identify persons at high risk of type 2 diabetes are important to target costly preventive efforts to those who will benefit most.

OBJECTIVE

This work aimed to assess whether novel biomarkers improve the prediction of type 2 diabetes beyond noninvasive standard clinical risk factors alone or in combination with glycated hemoglobin A1c (HbA1c).

METHODS

We used a population-based case-cohort study for discovery (689 incident cases and 1850 noncases) and an independent cohort study (262 incident cases, 2549 noncases) for validation. An L1-penalized (lasso) Cox model was used to select the most predictive set among 47 serum biomarkers from multiple etiological pathways. All variables available from the noninvasive German Diabetes Risk Score (GDRSadapted) were forced into the models. The C index and the category-free net reclassification index (cfNRI) were used to evaluate the predictive performance of the selected biomarkers beyond the GDRSadapted model (plus HbA1c).

RESULTS

Interleukin-1 receptor antagonist, insulin-like growth factor binding protein 2, soluble E-selectin, decorin, adiponectin, and high-density lipoprotein cholesterol were selected as the most relevant biomarkers. The simultaneous addition of these 6 biomarkers significantly improved the predictive performance both in the discovery (C index [95% CI], 0.053 [0.039-0.066]; cfNRI [95% CI], 67.4% [57.3%-79.5%]) and the validation study (0.034 [0.019-0.053]; 48.4% [35.6%-60.8%]). Significant improvements by these biomarkers were also seen on top of the GDRSadapted model plus HbA1c in both studies.

CONCLUSION

The addition of 6 biomarkers significantly improved the prediction of type 2 diabetes when added to a noninvasive clinical model or to a clinical model plus HbA1c.

Mesenchymal Stem Cell-Based Therapy for Diabetes Mellitus: Enhancement Strategies and Future Perspectives

Diabetes mellitus (DM), a chronic disorder of carbohydrate metabolism, is characterized by the unbridled hyperglycemia resulted from the impaired ability of the body to either produce or respond to insulin. As a cell-based regenerative therapy, mesenchymal stem cells (MSCs) hold immense potency for curing DM duo to their easy isolation, multi-differentiation potential, and immunomodulatory property. However, despite the promising efficacy in pre-clinical animal models, naive MSC administration fails to exhibit clinically satisfactory therapeutic outcomes, which varies greatly among individuals with DM. Recently, numbers of innovative strategies have been applied to improve MSC-based therapy. Preconditioning, genetic modification, combination therapy and exosome application are representative strategies to maximize the therapeutic benefits of MSCs. Therefore, in this review, we summarize recent advancements in mechanistic studies of MSCs-based treatment for DM, and mainly focus on the novel approaches aiming to improve the anti-diabetic potentials of naive MSCs. Additionally, the potential directions of MSCs-based therapy for DM are also proposed at a glance.

Association of FADS2 rs174575 gene polymorphism and insulin resistance in type 2 diabetes mellitus

Background

Many risk factors contribute to the pathogenesis of diabetes. Gene and lifestyle factors are considered to be the major contributors. A dietary pattern is attributed to be one of the lifestyle risk factors favoring diabetes. The present study aims to find an association between fatty acid desaturase (FADS) gene polymorphism and glycemic profile in type 2 diabetes mellitus (T2DM).

Methodology

A total of 429 subjects were included in the study on the basis of inclusion and exclusion criteria, of which 213 and 216 subjects were diabetic and control, respectively. Body mass index was calculated. Fasting plasma glucose, glycated hemoglobin (HbA1c) and insulin were measured using commercially available kits. rs174575 of FADS2 was selected based on previous publications and identified using the dbSNP database. To compare the biochemical parameters with the genotype, the following three models were used: additive model (CC vs CG vs GG), dominant model (CC + CG vs GG), and recessive model (CC vs CG + GG).

Results and Discussion

FBS, HbA1c, insulin, HOMA-IR, and HOMA-B exhibited a high and statistically significant difference between subjects and controls. The three models exhibited a statistically significant difference between FBS, HOMA-IR, and HOMA- B (p<0.05).

Conclusion

The distribution of rs174575 genotype differed significantly between the subjects and controls in the present study. The study revealed that genetic variation in FADS2 is an additional facet to consider while studying the risk factors of T2DM.

Deciphering the Plasma Proteome of Type 2 Diabetes

With an estimated prevalence of 463 million affected, type 2 diabetes represents a major challenge to health care systems worldwide. Analyzing the plasma proteomes of individuals with type 2 diabetes may illuminate hitherto unknown functional mechanisms underlying disease pathology. We assessed the associations between type 2 diabetes and >1,000 plasma proteins in the Cooperative Health Research in the Region of Augsburg (KORA) F4 cohort (n = 993, 110 cases), with subsequent replication in the third wave of the Nord-Trøndelag Health Study (HUNT3) cohort (n = 940, 149 cases). We computed logistic regression models adjusted for age, sex, BMI, smoking status, and hypertension. Additionally, we investigated associations with incident type 2 diabetes and performed two-sample bidirectional Mendelian randomization (MR) analysis to prioritize our results. Association analysis of prevalent type 2 diabetes revealed 24 replicated proteins, of which 8 are novel. Proteins showing association with incident type 2 diabetes were aminoacylase-1, growth hormone receptor, and insulin-like growth factor-binding protein 2. Aminoacylase-1 was associated with both prevalent and incident type 2 diabetes. MR analysis yielded nominally significant causal effects of type 2 diabetes on cathepsin Z and rennin, both known to have roles in the pathophysiological pathways of cardiovascular disease, and of sex hormone-binding globulin on type 2 diabetes. In conclusion, our high-throughput proteomics study replicated previously reported type 2 diabetes-protein associations and identified new candidate proteins possibly involved in the pathogenesis of type 2 diabetes.

Whole blood co-expression modules associate with metabolic traits and type 2 diabetes: an IMI-DIRECT study

Background

The rising prevalence of type 2 diabetes (T2D) poses a major global challenge. It remains unresolved to what extent transcriptomic signatures of metabolic dysregulation and T2D can be observed in easily accessible tissues such as blood. Additionally, large-scale human studies are required to further our understanding of the putative inflammatory component of insulin resistance and T2D. Here we used transcriptomics data from individuals with (n = 789) and without (n = 2127) T2D from the IMI-DIRECT cohorts to describe the co-expression structure of whole blood that mainly reflects processes and cell types of the immune system, and how it relates to metabolically relevant clinical traits and T2D.

Methods

Clusters of co-expressed genes were identified in the non-diabetic IMI-DIRECT cohort and evaluated with regard to stability, as well as preservation and rewiring in the cohort of individuals with T2D. We performed functional and immune cell signature enrichment analyses, and a genome-wide association study to describe the genetic regulation of the modules. Phenotypic and trans-omics associations of the transcriptomic modules were investigated across both IMI-DIRECT cohorts.

Results

We identified 55 whole blood co-expression modules, some of which clustered in larger super-modules. We identified a large number of associations between these transcriptomic modules and measures of insulin action and glucose tolerance. Some of the metabolically linked modules reflect neutrophil-lymphocyte ratio in blood while others are independent of white blood cell estimates, including a module of genes encoding neutrophil granule proteins with antibacterial properties for which the strongest associations with clinical traits and T2D status were observed. Through the integration of genetic and multi-omics data, we provide a holistic view of the regulation and molecular context of whole blood transcriptomic modules. We furthermore identified an overlap between genetic signals for T2D and co-expression modules involved in type II interferon signaling.

Conclusions

Our results offer a large-scale map of whole blood transcriptomic modules in the context of metabolic disease and point to novel biological candidates for future studies related to T2D.

Data-Driven Modeling of Knowledge Assemblies in Understanding Comorbidity Between Type 2 Diabetes Mellitus and Alzheimer's Disease

Background:

Recent studies have suggested comorbid association between Alzheimer’s disease (AD) and type 2 diabetes mellitus (T2DM) through identification of shared molecular mechanisms. However, the inference is pre-dominantly literature-based and lacks interpretation of pre-disposed genomic variants and transcriptomic measurables.

Objective:

In this study, we aim to identify shared genetic variants and dysregulated genes in AD and T2DM and explore their functional roles in the comorbidity between the diseases.

Methods:

The genetic variants for AD and T2DM were retrieved from GWAS catalog, GWAS central, dbSNP, and DisGeNet and subjected to linkage disequilibrium analysis. Next, shared variants were prioritized using RegulomeDB and Polyphen-2. Afterwards, a knowledge assembly embedding prioritized variants and their corresponding genes was created by mining relevant literature using Biological Expression Language. Finally, coherently perturbed genes from gene expression meta-analysis were mapped to the knowledge assembly to pinpoint biological entities and processes and depict a mechanistic link between AD and T2DM.

Results:

Our analysis identified four genes (i.e., ABCG1, COMT, MMP9, and SOD2) that could have dual roles in both AD and T2DM. Using cartoon representation, we have illustrated a set of causal events surrounding these genes which are associated to biological processes such as oxidative stress, insulin resistance, apoptosis and cognition.

Conclusion:

Our approach of using data as the driving force for unraveling disease etiologies eliminates literature bias and enables identification of novel entities that serve as the bridge between comorbid conditions.

Integrating Genetics and the Plasma Proteome to Predict the Risk of Type 2 Diabetes

PURPOSE OF THE REVIEW

Proteins are the central layer of information transfer from genome to phenome and represent the largest class of drug targets. We review recent advances in high-throughput technologies that provide comprehensive, scalable profiling of the plasma proteome with the potential to improve prediction and mechanistic understanding of type 2 diabetes (T2D).

RECENT FINDINGS

Technological and analytical advancements have enabled identification of novel protein biomarkers and signatures that help to address challenges of existing approaches to predict and screen for T2D. Genetic studies have so far revealed putative causal roles for only few of the proteins that have been linked to T2D, but ongoing large-scale genetic studies of the plasma proteome will help to address this and increase our understanding of aetiological pathways and mechanisms leading to diabetes. Studies of the human plasma proteome have started to elucidate its potential for T2D prediction and biomarker discovery. Future studies integrating genomic and proteomic data will provide opportunities to prioritise drug targets and identify pathways linking genetic predisposition to T2D development.

Alzheimer's disease and type 2 diabetes mellitus: A systematic review of proteomic studies

Similar to dementia, the risk for developing type 2 diabetes mellitus (T2DM) increases with age, and T2DM also increases the risk for dementia, particularly Alzheimer's disease (AD). Although T2DM is primarily a peripheral disorder and AD is a central nervous system disease, both share some common features as they are chronic and complex diseases, and both show involvement of oxidative stress and inflammation in their progression. These characteristics suggest that T2DM may be associated with AD, which gave rise to a new term, type 3 diabetes (T3DM). In this study, we searched for matching peripheral proteomic biomarkers of AD and T2DM based in a systematic review of the available literature. We identified 17 common biomarkers that were differentially expressed in both patients with AD or T2DM when compared with healthy controls. These biomarkers could provide a useful workflow for screening T2DM patients at risk to develop AD.

Plasma Cathepsin D Activity Rather Than Levels Correlates With Metabolic Parameters of Type 2 Diabetes in Male Individuals

Objective

Type 2 diabetes mellitus is a metabolic disorder characterized by insulin resistance. Previous studies in patients demonstrated that plasma levels of cathepsin D (CTSD), which is optimally active in the acidic environment of lysosomes, correlate with insulin resistance. As plasma pH is slightly reduced in type 2 diabetic patients and we have previously shown that plasma CTSD activity is causally linked to insulin levels in vivo, it is likely that the activity of CTSD in plasma will be increased in type 2 diabetes compared to healthy individuals. However, so far the interaction between CTSD activity and levels to postprandial metabolic derangements in type 2 diabetes is not known.

Methods

Eighteen type 2 diabetes and 16 age-matched healthy males were given 2 consecutive standardized mixed meals, after which blood samples were collected. Plasma metabolic parameters as well as CTSD levels and activity were measured, and changes in plasma pH was assessed.

Results

In line with the elevation of plasma free fatty acids (FFA) levels in male type 2 diabetics patients, plasma pH in type 2 diabetic individuals was decreased compared to male healthy individuals. While plasma CTSD levels were similar, plasma CTSD activity was increased in male type 2 diabetic compared to male healthy individuals. Besides, plasma CTSD activity rather than levels significantly correlated with indicators of type 2 diabetes (HbA1c, HOMA-IR and glucose). Furthermore, FFA was also independently associated with plasma CTSD activity (standardized β = 0.493, p = 0.007).

Conclusions

Despite similar plasma CTSD levels, type 2 diabetic male individuals showed increased plasma CTSD activity compared to healthy males, which was independently linked to plasma FFA levels. Our data therefore point toward plasma CTSD as a metabolic regulator in male type 2 diabetes.

An Exploratory Association Analysis of the Insulin Gene Region With Diabetes Mellitus in Two Dog Breeds

Samoyeds and Australian Terriers are the 2 dog breeds at highest risk (>10-fold) for diabetes mellitus in the United States. It is unknown if the insulin (INS) gene is involved in the pathophysiology of diabetes in Samoyeds and Australian Terriers. It was hypothesized that the INS gene region provides a common genetic causality for diabetes in Samoyeds and Australian Terriers. We conducted a 2-stage genetic association study involving both breeds. In the discovery stage (Stage 1), Samoyeds with and without diabetes were compared in the frequencies of 447 tagging single-nucleotide polymorphisms (SNPs) within 2.5 megabases (Mb) up- and downstream of the INS gene on the Illumina CanineHD BeadChip. SNPs yielding a P-value < 0.005 were selected for further follow-up. In the validation stage (Stage 2), Australian Terriers with and without diabetes were compared in the SNPs genotyped by the Affymetrix GeneChip Canine Genome 2.0 Array and within 1 Mb up- and downstream of the selected SNPs from Stage 1. Two SNPs that were in high linkage disequilibrium (LD, r2 = 0.7) were selected from Stage 1. In Stage 2, among the 76 SNPs examined, 5 were significantly associated with diabetes after Bonferroni's correction for multiple comparisons. Three of these 5 SNPs were in complete LD (r2 = 1 for all associations) and the 2 remaining SNPs were in moderate LD (r2 = 0.4). In conclusion, an association between the INS gene region and diabetes was suggested in 2 dog breeds of different clades. This region could have importance in diabetes in other breeds or in canine diabetes at large.

Circulating Protein Signatures and Causal Candidates for Type 2 Diabetes

The increasing prevalence of type 2 diabetes poses a major challenge to societies worldwide. Blood-based factors like serum proteins are in contact with every organ in the body to mediate global homeostasis and may thus directly regulate complex processes such as aging and the development of common chronic diseases. We applied a data-driven proteomics approach, measuring serum levels of 4,137 proteins in 5,438 elderly Icelanders, and identified 536 proteins associated with prevalent and/or incident type 2 diabetes. We validated a subset of the observed associations in an independent case-control study of type 2 diabetes. These protein associations provide novel biological insights into the molecular mechanisms that are dysregulated prior to and following the onset of type 2 diabetes and can be detected in serum. A bidirectional two-sample Mendelian randomization analysis indicated that serum changes of at least 23 proteins are downstream of the disease or its genetic liability, while 15 proteins were supported as having a causal role in type 2 diabetes.

Metabolomics and Proteomics in Type 2 Diabetes

The persistent increase in the worldwide burden of type 2 diabetes mellitus (T2D) and the accompanying rise of its complications, including cardiovascular disease, necessitates our understanding of the metabolic disturbances that cause diabetes mellitus. Metabolomics and proteomics, facilitated by recent advances in high-throughput technologies, have given us unprecedented insight into circulating biomarkers of T2D even over a decade before overt disease. These markers may be effective tools for diabetes mellitus screening, diagnosis, and prognosis. As participants of metabolic pathways, metabolite and protein markers may also highlight pathways involved in T2D development. The integration of metabolomics and proteomics with genomics in multiomics strategies provides an analytical method that can begin to decipher causal associations. These methods are not without their limitations; however, with careful study design and sample handling, these methods represent powerful scientific tools that can be leveraged for the study of T2D. In this article, we aim to give a timely overview of circulating metabolomics and proteomics findings with T2D observed in large human population studies to provide the reader with a snapshot into these emerging fields of research.

Neurology-related protein biomarkers are associated with cognitive ability and brain volume in older age

Identifying biological correlates of late life cognitive function is important if we are to ascertain biomarkers for, and develop treatments to help reduce, age-related cognitive decline. Here, we investigated the associations between plasma levels of 90 neurology-related proteins (Olink® Proteomics) and general fluid cognitive ability in the Lothian Birth Cohort 1936 (LBC1936, N = 798), Lothian Birth Cohort 1921 (LBC1921, N = 165), and the INTERVAL BioResource (N = 4451). In the LBC1936, 22 of the proteins were significantly associated with general fluid cognitive ability (β between -0.11 and -0.17). MRI-assessed total brain volume partially mediated the association between 10 of these proteins and general fluid cognitive ability. In an age-matched subsample of INTERVAL, effect sizes for the 22 proteins, although smaller, were all in the same direction as in LBC1936. Plasma levels of a number of neurology-related proteins are associated with general fluid cognitive ability in later life, mediated by brain volume in some cases.

Plasma cathepsin D activity is negatively associated with hepatic insulin sensitivity in overweight and obese humans

AIMS/HYPOTHESIS

Insulin resistance in skeletal muscle and liver plays a major role in the pathophysiology of type 2 diabetes. The hyperinsulinaemic-euglycaemic clamp is considered the gold standard for assessing peripheral and hepatic insulin sensitivity, yet it is a costly and labour-intensive procedure. Therefore, easy-to-measure, cost-effective approaches to determine insulin sensitivity are needed to enable organ-specific interventions. Recently, evidence emerged that plasma cathepsin D (CTSD) is associated with insulin sensitivity and hepatic inflammation. Here, we aimed to investigate whether plasma CTSD is associated with hepatic and/or peripheral insulin sensitivity in humans.

METHODS

As part of two large clinical trials (one designed to investigate the effects of antibiotics, and the other to investigate polyphenol supplementation, on insulin sensitivity), 94 overweight and obese adults (BMI 25-35 kg/m²) previously underwent a two-step hyperinsulinaemic-euglycaemic clamp (using [6,6-²H₂]glucose) to assess hepatic and peripheral insulin sensitivity (per cent suppression of endogenous glucose output during the low-insulin-infusion step, and the rate of glucose disappearance during high-insulin infusion [40 mU/(m² × min)], respectively). In this secondary analysis, plasma CTSD levels, CTSD activity and plasma inflammatory cytokines were measured.

RESULTS

Plasma CTSD levels were positively associated with the proinflammatory cytokines IL-8 and TNF-α (IL-8: standardised β = 0.495, p < 0.001; TNF-α: standardised β = 0.264, p = 0.012). Plasma CTSD activity was negatively associated with hepatic insulin sensitivity (standardised β = -0.206, p = 0.043), independent of age, sex, BMI and waist circumference, but it was not associated with peripheral insulin sensitivity. However, plasma IL-8 and TNF-α were not significantly correlated with hepatic insulin sensitivity.

CONCLUSIONS/INTERPRETATION

We demonstrate that plasma CTSD activity, but not systemic inflammation, is inversely related to hepatic insulin sensitivity, suggesting that plasma CTSD activity may be used as a non-invasive marker for hepatic insulin sensitivity in humans.

Increased Release of Proinflammatory Proteins in Primary Human Adipocytes and Activation of the Inflammatory NFĸB, p38, and ERK Pathways upon Omentin Treatment

OBJECTIVES

To investigate the impact of omentin on the release of inflammation-related biomarkers and inflammatory pathways in primary human adipocytes.

METHODS

Adipocytes were treated with or without omentin (500 and 2,000 ng/mL), and the supernatants were analyzed for inflammation-related biomarkers using proximity extension assay technology. Potential upstream regulators of the omentin-stimulated proteins were identified using Ingenuity Pathway Analysis. Protein levels of components of inflammatory pathways were measured using Western blotting.

RESULTS

2,000 ng/mL omentin induced the release of 30 biomarkers 97.1 ± 31.1-fold in the supernatants (all p < 0.05). Most biomarkers were proin-flammatory chemokines and cytokines. We identified the transcription factor nuclear factor "kappa-light-chain-enhancer" of activated B cells (NFĸB) and the kinases p38 and extracellular signal-regulated kinase (ERK)1/2 as potential upstream regulators in silico. On the cellular level, treatment with 2,000 ng/mL omentin for 24 h enhanced the phosphorylation levels of NFĸB 2.1 ± 0.3-fold (p < 0.05), of p38 2.6 ± 0.4-fold (p < 0.05), and of ERK1/2 1.8 ± 0.2-fold (p < 0.05).

CONCLUSIONS

These data argue that omentin exerts proinflammatory effects through the activation of the inflammatory NFĸB, p38, and ERK1/2 pathways in cultured primary adipocytes.

Changes in Proteomic Profiles are Related to Changes in BMI and Fat Distribution During 10 Years of Aging

OBJECTIVE

This study investigated how changes in 84 proteins over a 10-year period of aging were related to changes in measures of body fat and distribution over the same period.

METHODS

Cardiovascular candidate proteins were measured using the proximal extension assay technique, along with BMI and waist-hip ratio (WHR), at ages 70, 75, and 80 in 1,016 participants of the Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) cohort. Associations of changes in plasma protein levels, BMI, and WHR over time were analyzed using linear mixed models.

RESULTS

Changes in 19 and 16 proteins were significantly associated with changes in BMI and WHR, respectively (P < 0.00059), over the investigated 10-year period. Leptin and fatty acid-binding protein 4 were among the proteins most strongly associated with changes in both BMI and WHR. Four of the proteins significantly tracked with change in BMI (P < 0.00059) but not WHR (P > 0.05): endothelial cell-specific molecule 1, pentraxin-related protein PTX3, ST2 protein (also known as interleukin-1 receptor-like 1), and spondin-1. Five proteins tracked with change in WHR (P < 0.00059) but not BMI (P > 0.05): caspase-8, cathepsin L1, oxidized low-density lipoprotein receptor 1, interleukin-6 receptor subunit alpha, and C-C motif chemokine 20.

CONCLUSIONS

This is the first large longitudinal study of how changes in plasma protein signatures are associated with changes in measures of body fat and distribution over 10 years of aging.

New Insights into Adipokines as Potential Biomarkers for Type-2 Diabetes Mellitus

A large number of studies have been focused on investigating serum biomarkers associated with risk or diagnosis of type-2 diabetes mellitus. In the last decade, promising studies have shown that circulating levels of adipokines could be used as a relevant biomarker for diabetes mellitus progression as well as therapeutic future targets. Here, we discuss the possible use of recently described adipokines, including apelin, omentin-1, resistin, FGF-21, neuregulin-4 and visfatin, as early biomarkers for diabetes. In addition, we also include recent findings of other well known adipokines such as leptin and adiponectin. In conclusion, further studies are needed to clarify the pathophysiological significance and clinical value of these biological factors as potential biomarkers in type-2 diabetes and related dysfunctions.

In search of causal pathways in diabetes: a study using proteomics and genotyping data from a cross-sectional study

AIMS/HYPOTHESIS

The pathogenesis of type 2 diabetes is not fully understood. We investigated whether circulating levels of preselected proteins were associated with the outcome 'diabetes' and whether these associations were causal.

METHODS

In 2467 individuals of the population-based, cross-sectional EpiHealth study (45-75 years, 50% women), 249 plasma proteins were analysed by the proximity extension assay technique. DNA was genotyped using the Illumina HumanCoreExome-12 v1.0 BeadChip. Diabetes was defined as taking glucose-lowering treatment or having a fasting plasma glucose of ≥7.0 mmol/l. The associations between proteins and diabetes were assessed using logistic regression. To investigate causal relationships between proteins and diabetes, a bidirectional two-sample Mendelian randomisation was performed based on large, genome-wide association studies belonging to the DIAGRAM and MAGIC consortia, and a genome-wide association study in the EpiHealth study.

RESULTS

Twenty-six proteins were positively associated with diabetes, including cathepsin D, retinal dehydrogenase 1, α-L-iduronidase, hydroxyacid oxidase 1 and galectin-4 (top five findings). Three proteins, lipoprotein lipase, IGF-binding protein 2 and paraoxonase 3 (PON-3), were inversely associated with diabetes. Fourteen of the proteins are novel discoveries. The Mendelian randomisation study did not disclose any significant causal effects between the proteins and diabetes in either direction that were consistent with the relationships found between the protein levels and diabetes.

CONCLUSIONS/INTERPRETATION

The 29 proteins associated with diabetes are involved in several physiological pathways, but given the power of the study no causal link was identified for those proteins tested in Mendelian randomisation. Therefore, the identified proteins are likely to be biomarkers for type 2 diabetes, rather than representing causal pathways.

Proteomic Analysis of Longitudinal Changes in Blood Pressure

Hypertension is the leading risk factor for premature death worldwide. The identification of modifiable causes of hypertension remains an imperative task. We aimed to investigate associations between 79 proteins implicated in cardiovascular disease and longitudinal blood pressure (BP) changes in three Swedish prospective cohorts. In a discovery phase, we investigated associations between baseline circulating protein levels assessed with a proximity extension assay and BP stage progression at follow-up 5 years later among persons without BP-lowering drugs at baseline in two independent community-based cohorts from the Prospective Investigation of the Vasculature in Uppsala Seniors study (PIVUS) and the Uppsala Longitudinal Study of Adult Men (ULSAM). We used an independent cohort, the Malmö Diet and Cancer Study (MDC), for replication. The primary outcome of BP stage progression was defined as per the 2017 AHA/ACC (American Heart Association/ American College of Cardiology) Guideline BP categories. We also investigated associations of protein levels with changes in BP on a continuous scale, and meta-analyzed all three cohorts. Levels of renin were associated with BP stage progression with a 5% false discovery rate (FDR) in the ULSAM (n = 238) and PIVUS (n = 566) cohorts, but we could not replicate this association in the MDC cohort (n = 2659). The association in the discovery cohorts was modest, with an odds ratio for BP stage progression over 5 years of 1.33 (95% confidence interval 1.14 to 1.56) per standard deviation of baseline renin. In conclusion, we could not find any novel robust associations with longitudinal BP increase in a proximity extension assay-based proteomics investigation in three cohorts.

Diet-Induced Obese Mice and Leptin-Deficient Lepob/ob Mice Exhibit Increased Circulating GIP Levels Produced by Different Mechanisms

As glucose-dependent insulinotropic polypeptide (GIP) possesses pro-adipogenic action, the suppression of the GIP hypersecretion seen in obesity might represent a novel therapeutic approach to the treatment of obesity. However, the mechanism of GIP hypersecretion remains largely unknown. In the present study, we investigated GIP secretion in two mouse models of obesity: High-fat diet-induced obese (DIO) mice and leptin-deficient Lep^ob/ob mice. In DIO mice, plasma GIP was increased along with an increase in GIP mRNA expression in the lower small intestine. Despite the robust alteration in the gut microbiome in DIO mice, co-administration of maltose and the α-glucosidase inhibitor (α-GI) miglitol induced the microbiome-mediated suppression of GIP secretion. The plasma GIP levels of Lep^ob/ob mice were also elevated and were suppressed by fat transplantation. The GIP mRNA expression in fat tissue was not increased in Lep^ob/ob mice, while the expression of an interleukin-1 receptor antagonist (IL-1Ra) was increased. Fat transplantation suppressed the expression of IL-1Ra. The plasma IL-1Ra levels were positively correlated with the plasma GIP levels. Accordingly, although circulating GIP levels are increased in both DIO and Lep^ob/ob mice, the underlying mechanisms differ, and the anti-obesity actions of α-GIs and leptin sensitizers may be mediated partly by the suppression of GIP secretion.

Association between Biomarkers of Low-grade Inflammation and Sex Hormones in Women with Polycystic Ovary Syndrome

Objective Women with polycystic ovary syndrome (PCOS) have higher circulating levels of C-reactive protein, but the relationship between inflammation and endocrine function in PCOS remains poorly understood. Thus, this study aimed to investigate the association between low-grade inflammation and sex hormones in women with PCOS.

Design and Patients A comprehensive panel of biomarkers of inflammation was measured in serum of 63 women with PCOS using proximity extension assay technology. Associations of 65 biomarkers with sex hormones were assessed without and with adjustment for age and body mass index (BMI).

Results In the unadjusted analysis, 20 biomarkers were positively correlated with 17-OH-progesterone (17-OH-P), 14 with prolactin and 6 with free testosterone, whereas inverse associations were found for 16 biomarkers with sex hormone-binding globulin (SHBG), 6 with luteinizing hormone (LH) and 6 with estrogen (all p<0.05). Among the positive associations, correlations were mainly found for five chemokines (CXCL11, CCL4, MCP-4/CCL13, CXCL5, CXCL6) and for VEGF-A, LAP-TGFβ1, TNFSF14 and MMP-1. Inverse associations with sex hormones were mainly present for two chemokines (CXCL1, MCP-2/CCL8), CDCP1, CST5 and CSF-1. Adjustment for age and BMI reduced the number of biomarker associations for SHBG and estrogen, but had hardly any impact on associations with 17-OH-P, prolactin, free testosterone and LH.

Conclusion Women with PCOS feature BMI-independent associations between biomarkers of inflammation and certain sex steroid and hypophyseal hormones. Most of these inflammation-related biomarkers were chemokines, which may be relevant as potential mediators of the increased cardiometabolic risk of women with PCOS.

Associations of Circulating Protein Levels With Lipid Fractions in the General Population

Objective- Revealing patterns of associations between circulating protein and lipid levels could improve biological understanding of cardiovascular disease (CVD). In this study, we investigated the associations between proteins related to CVD and triglyceride (TG), total cholesterol, LDL (low-density lipoprotein), and HDL (high-density lipoprotein) cholesterol levels in individuals from the general population. Approach and Results- We measured plasma protein levels using the Olink ProSeek CVD I or II+III arrays and analyzed 57 proteins available in 3 population-based cohorts: EpiHealth (n=2029; 52% women; median age, 61 years), PIVUS (Prospective Study of the Vasculature in Uppsala Seniors; n=790; 51% women; all aged 70 years), and ULSAM (Uppsala Longitudinal Study of Adult Men; n=551; all men aged 77 years). A discovery analysis was performed in EpiHealth in a regression framework (adjusted for sex, age, body mass index, smoking, glucose levels, systolic blood pressure, blood pressure medication, diabetes mellitus medication, and CVD history), and associations with false discovery rate <0.05 were further tested in PIVUS and ULSAM, where a P value of 0.05 was considered a successful replication (validation false discovery rate of 0.1%). We used summary statistics from a genome-wide association study on each protein biomarker (meta-analysis of EpiHealth, PIVUS, ULSAM, and IMPROVE [Carotid Intima-Media Thickness and IMT-Progression as Predictors of Vascular Events in a High-Risk European Population]) and publicly available data from Global Lipids Genetics Consortium to perform Mendelian randomization analyses to address possible causality of protein levels. Of 57 tested proteins, 42 demonstrated an association with at least 1 lipid fraction; 35 were associated with TG, 15 with total cholesterol, 9 with LDL cholesterol, and 24 with HDL cholesterol. Among these associations, we found KIM-1 (kidney injury molecule-1), TNFR (TNF [tumor necrosis factor] receptor) 1 and 2, TRAIL-R2 (TRAIL [TNF-related apoptosis-inducing ligand] receptor 2), and RETN (resistin) to be associated with all 4 lipid fractions. Further, 15 proteins were related to both TG and HDL cholesterol in a consistent and biologically expected manner, that is, higher TG and lower HDL cholesterol or vice versa. Another common pattern of associations was concomitantly higher TG, total cholesterol, and LDL cholesterol, which is associated with higher CVD risk. We did not find evidence of causal links for protein levels. Conclusions- Our comprehensive analysis of plasma proteins and lipid fractions of 3370 individuals from the general population provides new information about lipid metabolism.