Revealing the role of the human blood plasma proteome in obesity using genetic drivers

Cord Blood Proteomic Profiles, Birth Weight, and Early Life Growth Trajectories

Importance

The cord blood proteome, a repository of proteins derived from both mother and fetus, might offer valuable insights into the physiological and pathological state of the fetus. However, its association with birth weight and growth trajectories early in life remains unexplored.

Objective

To identify cord blood proteins associated with birth weight and the birth weight ratio (BWR) and to evaluate the associations of these cord blood proteins with early growth trajectories.

Design, Setting, and Participants

This cohort study included 288 mother-child pairs from the ongoing prospective Environmental Influence on Early Aging birth cohort study. Newborns were recruited from East-Limburg Hospital in Genk, Belgium, between February 2010 and November 2017 and followed up until ages 4 to 6 years. Data were analyzed from February 2022 to September 2023.

Main Outcomes and Measures

The outcome of interest was the associations of 368 inflammatory-related cord blood proteins with birth weight or BWR and with early life growth trajectories (ie, rapid growth at age 12 months and weight, body mass index [BMI] z score, waist circumference, and overweight at age 4-6 years) using multiple linear regression models. The BWR was calculated by dividing the birth weight by the median birth weight of the population-specific reference growth curve, considering parity, sex, and gestational age. Results are presented as estimates or odds ratios (ORs) for each doubling in proteins.

Results

The sample included 288 infants (125 [43.4%] male; mean [SD] gestation age, 277.2 [11.6] days). The mean (SD) age of the child at the follow-up examination was 4.6 (0.4) years old. After multiple testing correction, there were significant associations of birth weight and BWR with 7 proteins: 2 positive associations: afamin (birth weight: coefficient, 341.16 [95% CI, 192.76 to 489.50]) and secreted frizzled-related protein 4 (SFRP4; birth weight: coefficient, 242.60 [95% CI, 142.77 to 342.43]; BWR: coefficient, 0.07 [95% CI, 0.04 to 0.10]) and 5 negative associations: cadherin EGF LAG 7-pass G-type receptor 2 (CELSR2; birth weight: coefficient, -237.52 [95% CI, -343.15 to -131.89]), ephrin type-A receptor 4 (EPHA4; birth weight: coefficient, -342.78 [95% CI, -463.10 to -222.47]; BWR: coefficient, -0.11 [95% CI, -0.14 to -0.07]), SLIT and NTRK-like protein 1 (SLITRK1; birth weight: coefficient, -366.32 [95% CI, -476.66 to -255.97]; BWR: coefficient, -0.11 [95% CI, -0.15 to -0.08]), transcobalamin-1 (TCN1; birth weight: coefficient, -208.75 [95% CI, -305.23 to -112.26]), and unc-5 netrin receptor D (UNC5D; birth weight: coefficient, -209.27 [95% CI, -295.14 to -123.40]; BWR: coefficient, -0.07 [95% CI, -0.09 to -0.04]). Further evaluation showed that 2 proteins were still associated with rapid growth at age 12 months (afamin: OR, 0.32 [95% CI, 0.11-0.88]; TCN1: OR, 2.44 [95% CI, 1.26-4.80]). At age 4 to 6 years, CELSR2, EPHA4, SLITRK1, and UNC5D were negatively associated with weight (coefficients, -1.33 to -0.68 kg) and body mass index z score (coefficients, -0.41 to -0.23), and EPHA4, SLITRK1, and UNC5D were negatively associated with waist circumference (coefficients, -1.98 to -0.87 cm). At ages 4 to 6 years, afamin (OR, 0.19 [95% CI, 0.05-0.70]) and SLITRK1 (OR, 0.32 [95% CI, 0.10-0.99]) were associated with lower odds for overweight.

Conclusions and Relevance

This cohort study found 7 cord blood proteins associated with birth weight and growth trajectories early in life. Overall, these findings suggest that stressors that could affect the cord blood proteome during pregnancy might have long-lasting associations with weight and body anthropometrics.

Plasma proteomic profile of abdominal obesity in older adults

OBJECTIVE

This study examines the plasma proteomic profile of abdominal obesity in older adults.

METHODS

The association of abdominal obesity (waist circumference [WC]) with 4265 plasma proteins identified using the SomaScan Assay was examined in 969 Ashkenazi Jewish participants (LonGenity cohort), aged 65 years and older (mean [SD] age 75.7 [6.7] years, 55.4% women), using regression models. Pathway analysis, as well as weighted correlation network analysis, was performed. WC was determined from the proteome using elastic net regression.

RESULTS

A total of 480 out of 4265 proteins were associated with WC in the linear regression model. Leptin (β [SE] = 12.363 [0.490]), inhibin β C chain (INHBC; β [SE] = 24.324 [1.448]), insulin-like growth factor-binding protein 2 (IGFBP-2; β [SE] = -12.782 [0.841]), heparan-sulfate 6-O-sulfotransferase 3 (H6ST3; β [SE] = -39.995 [2.729]), and matrix-remodeling-associated protein 8 (MXRA8; β [SE] = -27.101 [1.850]) were the top proteins associated with WC. Cell adhesion, extracellular matrix remodeling, and IGF transport pathways were the top enriched pathways associated with WC. WC signature determined from plasma proteins was highly correlated with measured WC (r = 0.80) and was associated with various metabolic and physical traits.

CONCLUSIONS

The study unveiled a multifaceted plasma proteomic profile of abdominal obesity in older adults, offering insights into its wide-ranging impact on the proteome. It also elucidated novel proteins, clusters of correlated proteins, and pathways that are intricately associated with abdominal obesity.

Multiplex proteomics identifies inflammation-related plasma biomarkers for aging and cardio-metabolic disorders

BACKGROUND

Cardio-metabolic disorders (CMDs) are common in aging people and are pivotal risk factors for cardiovascular diseases (CVDs). Inflammation is involved in the pathogenesis of CVDs and aging, but the underlying inflammatory molecular phenotypes in CMDs and aging are still unknown.

METHOD

We utilized multiple proteomics to detect 368 inflammatory proteins in the plasma of 30 subjects, including healthy young individuals, healthy elderly individuals, and elderly individuals with CMDs, by Proximity Extension Assay technology (PEA, O-link). Protein-protein interaction (PPI) network and functional modules were constructed to explore hub proteins in differentially expressed proteins (DEPs). The correlation between proteins and clinical traits of CMDs was analyzed and diagnostic value for CMDs of proteins was evaluated by ROC curve analysis.

RESULT

Our results revealed that there were 161 DEPs (adjusted p < 0.05) in normal aging and EGF was the most differentially expressed hub protein in normal aging. Twenty-eight DEPs were found in elderly individuals with CMDs and MMP1 was the most differentially expressed hub protein in CMDs. After the intersection of DEPs in aging and CMDs, there were 10 overlapping proteins: SHMT1, MVK, EGLN1, SLC39A5, NCF2, CXCL6, IRAK4, REG4, PTPN6, and PRDX5. These proteins were significantly correlated with the level of HDL-C, TG, or FPG in plasma. They were verified to have good diagnostic value for CMDs in aging with an AUC > 0.7. Among these, EGLN1, NCF2, REG4, and SLC39A2 were prominently increased both in normal aging and aging with CMDs.

CONCLUSION

Our results could reveal molecular markers for normal aging and CMDs, which need to be further expanded the sample size and to be further investigated to predict their significance for CVDs.

Clinically relevant plasma proteome for adiposity depots: evidence from systematic mendelian randomization and colocalization analyses

BACKGROUND

The accumulation of visceral and ectopic fat comprise a major cause of cardiometabolic diseases. However, novel drug targets for reducing unnecessary visceral and ectopic fat are still limited. Our study aims to provide a comprehensive investigation of the causal effects of the plasma proteome on visceral and ectopic fat using Mendelian randomization (MR) approach.

METHODS

We performed two-sample MR analyses based on five large genome-wide association study (GWAS) summary statistics of 2656 plasma proteins, to screen for causal associations of these proteins with traits of visceral and ectopic fat in over 30,000 participants of European ancestry, as well as to assess mediation effects by risk factors of outcomes. The colocalization analysis was conducted to examine whether the identified proteins and outcomes shared casual variants.

RESULTS

Genetically predicted levels of 14 circulating proteins were associated with visceral and ectopic fat (P < 4.99 × 10- 5, at a Bonferroni-corrected threshold). Colocalization analysis prioritized ten protein targets that showed effect on outcomes, including FST, SIRT2, DNAJB9, IL6R, CTSA, RGMB, PNLIPRP1, FLT4, PPY and IL6ST. MR analyses revealed seven risk factors for visceral and ectopic fat (P < 0.0024). Furthermore, the associations of CTSA, DNAJB9 and IGFBP1 with primary outcomes were mediated by HDL-C and SHBG. Sensitivity analyses showed little evidence of pleiotropy.

CONCLUSIONS

Our study identified candidate proteins showing putative causal effects as potential therapeutic targets for visceral and ectopic fat accumulation and outlined causal pathways for further prevention of downstream cardiometabolic diseases.

Human cord plasma proteomic analysis reveals sexually dimorphic proteins associated with intrauterine growth restriction

Intrauterine growth restriction (IUGR) is associated with increased risk of cardiometabolic disease later in life and has been shown to affect female and male offspring differently, but the mechanisms remain unclear. The purpose of this study was to identify proteomic differences and metabolic risk markers in IUGR male and female neonates when compared to appropriate for gestational age (AGA) babies that will provide a better understanding of IUGR pathogenesis and its associated risks. Our results revealed alterations in IUGR cord plasma proteomes with most of the differentially abundant proteins implicated in peroxisome pathways. This effect was evident in females but not in males. Furthermore, we observed that catalase activity, a peroxisomal enzyme, was significantly increased in females (p < 0.05) but unchanged in males. Finally, we identified risk proteins associated with obesity, type-2 diabetes, and glucose intolerance such as EGF containing fibulin extracellular matrix protein 1 (EFEMP1), proprotein convertase subtilisin/kexin type 9 (PCSK9) and transforming growth factor beta receptor 3 (TGFBR3) proteins unique to females while coagulation factor IX (C9) and retinol binding protein 4 (RBP4) are unique in males. In conclusion, IUGR may display sexual dimorphism which may be associated with differences in lifelong risk for cardiometabolic disease between males and females.

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.

Adiposity and cancer: meta-analysis, mechanisms, and future perspectives

Obesity is a recognised risk factor for many cancers and with rising global prevalence, has become a leading cause of cancer. Here we summarise the current evidence from both population-based epidemiologic investigations and experimental studies on the role of obesity in cancer development. This review presents a new meta-analysis using data from 40 million individuals and reports positive associations with 19 cancer types. Utilising major new data from East Asia, the meta-analysis also shows that the strength of obesity and cancer associations varies regionally, with stronger relative risks for several cancers in East Asia. This review also presents current evidence on the mechanisms linking obesity and cancer and identifies promising future research directions. These include the use of new imaging data to circumvent the methodological issues involved with body mass index and the use of omics technologies to resolve biologic mechanisms with greater precision and clarity.

Impact of weight loss on cancer-related proteins in serum: results from a cluster randomised controlled trial of individuals with type 2 diabetes

BACKGROUND

Type 2 diabetes is associated with higher risk of several cancer types. However, the biological intermediates driving this relationship are not fully understood. As novel interventions for treating and managing type 2 diabetes become increasingly available, whether they also disrupt the pathways leading to increased cancer risk is currently unknown. We investigated the effect of a type 2 diabetes intervention, in the form of intentional weight loss, on circulating proteins associated with cancer risk to gain insight into potential mechanisms linking type 2 diabetes and adiposity with cancer development.

METHODS

Fasting serum samples from participants with diabetes enrolled in the Diabetes Remission Clinical Trial (DiRECT) receiving the Counterweight-Plus weight-loss programme (intervention, N = 117, mean weight-loss 10 kg, 46% diabetes remission) or best-practice care by guidelines (control, N = 143, mean weight-loss 1 kg, 4% diabetes remission) were subject to proteomic analysis using the Olink Oncology-II platform (48% of participants were female; 52% male). To identify proteins which may be altered by the weight-loss intervention, the difference in protein levels between groups at baseline and 1 year was examined using linear regression. Mendelian randomization (MR) was performed to extend these results to evaluate cancer risk and elucidate possible biological mechanisms linking type 2 diabetes and cancer development. MR analyses were conducted using independent datasets, including large cancer meta-analyses, UK Biobank, and FinnGen, to estimate potential causal relationships between proteins modified during intentional weight loss and the risk of colorectal, breast, endometrial, gallbladder, liver, and pancreatic cancers.

FINDINGS

Nine proteins were modified by the intervention: glycoprotein Nmb; furin; Wnt inhibitory factor 1; toll-like receptor 3; pancreatic prohormone; erb-b2 receptor tyrosine kinase 2; hepatocyte growth factor; endothelial cell specific molecule 1 and Ret proto-oncogene (Holm corrected P-value <0.05). Mendelian randomization analyses indicated a causal relationship between predicted circulating furin and glycoprotein Nmb on breast cancer risk (odds ratio (OR) = 0.81, 95% confidence interval (CI) = 0.67-0.99, P-value = 0.03; and OR = 0.88, 95% CI = 0.78-0.99, P-value = 0.04 respectively), though these results were not supported in sensitivity analyses examining violations of MR assumptions.

INTERPRETATION

Intentional weight loss among individuals with recently diagnosed diabetes may modify levels of cancer-related proteins in serum. Further evaluation of the proteins identified in this analysis could reveal molecular pathways that mediate the effect of adiposity and type 2 diabetes on cancer risk.

FUNDING

The main sources of funding for this work were Diabetes UK, Cancer Research UK, World Cancer Research Fund, and Wellcome.

Longitudinal multi-omics study reveals common etiology underlying association between plasma proteome and BMI trajectories in adolescent and young adult twins

BACKGROUND

The influence of genetics and environment on the association of the plasma proteome with body mass index (BMI) and changes in BMI remains underexplored, and the links to other omics in these associations remain to be investigated. We characterized protein-BMI trajectory associations in adolescents and adults and how these connect to other omics layers.

METHODS

Our study included two cohorts of longitudinally followed twins: FinnTwin12 (N = 651) and the Netherlands Twin Register (NTR) (N = 665). Follow-up comprised 4 BMI measurements over approximately 6 (NTR: 23-27 years old) to 10 years (FinnTwin12: 12-22 years old), with omics data collected at the last BMI measurement. BMI changes were calculated in latent growth curve models. Mixed-effects models were used to quantify the associations between the abundance of 439 plasma proteins with BMI at blood sampling and changes in BMI. In FinnTwin12, the sources of genetic and environmental variation underlying the protein abundances were quantified by twin models, as were the associations of proteins with BMI and BMI changes. In NTR, we investigated the association of gene expression of genes encoding proteins identified in FinnTwin12 with BMI and changes in BMI. We linked identified proteins and their coding genes to plasma metabolites and polygenic risk scores (PRS) applying mixed-effects models and correlation networks.

RESULTS

We identified 66 and 14 proteins associated with BMI at blood sampling and changes in BMI, respectively. The average heritability of these proteins was 35%. Of the 66 BMI-protein associations, 43 and 12 showed genetic and environmental correlations, respectively, including 8 proteins showing both. Similarly, we observed 7 and 3 genetic and environmental correlations between changes in BMI and protein abundance, respectively. S100A8 gene expression was associated with BMI at blood sampling, and the PRG4 and CFI genes were associated with BMI changes. Proteins showed strong connections with metabolites and PRSs, but we observed no multi-omics connections among gene expression and other omics layers.

CONCLUSIONS

Associations between the proteome and BMI trajectories are characterized by shared genetic, environmental, and metabolic etiologies. We observed few gene-protein pairs associated with BMI or changes in BMI at the proteome and transcriptome levels.

Using trials of caloric restriction and bariatric surgery to explore the effects of body mass index on the circulating proteome

Thousands of proteins circulate in the bloodstream; identifying those which associate with weight and intervention-induced weight loss may help explain mechanisms of diseases associated with adiposity. We aimed to identify consistent protein signatures of weight loss across independent studies capturing changes in body mass index (BMI). We analysed proteomic data from studies implementing caloric restriction (Diabetes Remission Clinical trial) and bariatric surgery (By-Band-Sleeve), using SomaLogic and Olink Explore1536 technologies, respectively. Linear mixed models were used to estimate the effect of the interventions on circulating proteins. Twenty-three proteins were altered in a consistent direction after both bariatric surgery and caloric restriction, suggesting that these proteins are modulated by weight change, independent of intervention type. We also integrated Mendelian randomisation (MR) estimates of the effect of BMI on proteins measured by SomaLogic from a UK blood donor cohort as a third line of causal evidence. These MR estimates provided further corroborative evidence for a role of BMI in regulating the levels of six proteins including alcohol dehydrogenase-4, nogo receptor and interleukin-1 receptor antagonist protein. These results indicate the importance of triangulation in interrogating causal relationships; further study into the role of proteins modulated by weight in disease is now warranted.

A phenome-wide approach to identify causal risk factors for deep vein thrombosis

Deep vein thrombosis (DVT) is the formation of a blood clot in a deep vein. DVT can lead to a venous thromboembolism (VTE), the combined term for DVT and pulmonary embolism, a leading cause of death and disability worldwide. Despite the prevalence and associated morbidity of DVT, the underlying causes are not well understood. Our aim was to leverage publicly available genetic summary association statistics to identify causal risk factors for DVT. We conducted a Mendelian randomization phenome-wide association study (MR-PheWAS) using genetic summary association statistics for 973 exposures and DVT (6,767 cases and 330,392 controls in UK Biobank). There was evidence for a causal effect of 57 exposures on DVT risk, including previously reported risk factors (e.g. body mass index-BMI and height) and novel risk factors (e.g. hyperthyroidism and varicose veins). As the majority of identified risk factors were adiposity-related, we explored the molecular link with DVT by undertaking a two-sample MR mediation analysis of BMI-associated circulating proteins on DVT risk. Our results indicate that circulating neurogenic locus notch homolog protein 1 (NOTCH1), inhibin beta C chain (INHBC) and plasminogen activator inhibitor 1 (PAI-1) influence DVT risk, with PAI-1 mediating the BMI-DVT relationship. Using a phenome-wide approach, we provide putative causal evidence that hyperthyroidism, varicose veins and BMI enhance the risk of DVT. Furthermore, the circulating protein PAI-1 has a causal role in DVT aetiology and is involved in mediating the BMI-DVT relationship.

Comprehensive analyses of circulating cardiometabolic proteins and objective measures of fat mass

BACKGROUND

The underlying molecular pathways for the effect of excess fat mass on cardiometabolic diseases is not well understood. Since body mass index is a suboptimal measure of body fat content, we investigated the relationship of fat mass measured by dual-energy X-ray absorptiometry with circulating cardiometabolic proteins.

METHODS

We used data from a population-based cohort of 4950 Swedish women (55-85 years), divided into discovery and replication samples; 276 proteins were assessed with three Olink Proseek Multiplex panels. We used random forest to identify the most relevant biomarker candidates related to fat mass index (FMI), multivariable linear regression to further investigate the associations between FMI characteristics and circulating proteins adjusted for potential confounders, and principal component analysis (PCA) for the detection of common covariance patterns among the proteins.

RESULTS

Total FMI was associated with 66 proteins following adjustment for multiple testing in discovery and replication multivariable analyses. Five proteins not previously associated with body size were associated with either lower FMI (calsyntenin-2 (CLSTN2), kallikrein-10 (KLK10)), or higher FMI (scavenger receptor cysteine-rich domain-containing group B protein (SSC4D), trem-like transcript 2 protein (TLT-2), and interleukin-6 receptor subunit alpha (IL-6RA)). PCA provided an efficient summary of the main variation in FMI-related circulating proteins involved in glucose and lipid metabolism, appetite regulation, adipocyte differentiation, immune response and inflammation. Similar patterns were observed for regional fat mass measures.

CONCLUSIONS

This is the first large study showing associations between fat mass and circulating cardiometabolic proteins. Proteins not previously linked to body size are implicated in modulation of postsynaptic signals, inflammation, and carcinogenesis.

Healthy lifestyle linked to innate immunity and lipoprotein metabolism: a cross-sectional comparison using untargeted proteomics

This study used untargeted proteomics to compare blood proteomic profiles in two groups of adults that differed widely in lifestyle habits. A total of 52 subjects in the lifestyle group (LIFE) (28 males, 24 females) and 52 in the control group (CON) (27 males, 25 females) participated in this cross-sectional study. Age, education level, marital status, and height did not differ significantly between LIFE and CON groups. The LIFE and CON groups differed markedly in body composition, physical activity patterns, dietary intake patterns, disease risk factor prevalence, blood measures of inflammation, triglycerides, HDL-cholesterol, glucose, and insulin, weight-adjusted leg/back and handgrip strength, and mood states. The proteomics analysis showed strong group differences for 39 of 725 proteins identified in dried blood spot samples. Of these, 18 were downregulated in the LIFE group and collectively indicated a lower innate immune activation signature. A total of 21 proteins were upregulated in the LIFE group and supported greater lipoprotein metabolism and HDL remodeling. Lifestyle-related habits and biomarkers were probed and the variance (> 50%) in proteomic profiles was best explained by group contrasts in indicators of adiposity. This cross-sectional study established that a relatively small number of proteins are associated with good lifestyle habits.

Conventional and genetic associations of adiposity with 1463 proteins in relatively lean Chinese adults

Adiposity is associated with multiple diseases and traits, but little is known about the causal relevance and mechanisms underlying these associations. Large-scale proteomic profiling, especially when integrated with genetic data, can clarify mechanisms linking adiposity with disease outcomes. We examined the associations of adiposity with plasma levels of 1463 proteins in 3977 Chinese adults, using measured and genetically-instrumented BMI. We further used two-sample bi-directional MR analyses to assess if certain proteins influenced adiposity, along with other (e.g. enrichment) analyses to clarify possible mechanisms underlying the observed associations. Overall, the mean (SD) baseline BMI was 23.9 (3.3) kg/m2, with only 6% being obese (i.e. BMI ≥ 30 kg/m2). Measured and genetically-instrumented BMI was significantly associated at FDR < 0.05 with levels of 1096 (positive/inverse: 826/270) and 307 (positive/inverse: 270/37) proteins, respectively, with FABP4, LEP, IL1RN, LSP1, GOLM2, TNFRSF6B, and ADAMTS15 showing the strongest positive and PON3, NCAN, LEPR, IGFBP2 and MOG showing the strongest inverse genetic associations. These associations were largely linear, in adiposity-to-protein direction, and replicated (> 90%) in Europeans of UKB (mean BMI 27.4 kg/m2). Enrichment analyses of the top > 50 BMI-associated proteins demonstrated their involvement in atherosclerosis, lipid metabolism, tumour progression and inflammation. Two-sample bi-directional MR analyses using cis-pQTLs identified in CKB GWAS found eight proteins (ITIH3, LRP11, SCAMP3, NUDT5, OGN, EFEMP1, TXNDC15, PRDX6) significantly affect levels of BMI, with NUDT5 also showing bi-directional association. The findings among relatively lean Chinese adults identified novel pathways by which adiposity may increase disease risks and novel potential targets for treatment of obesity and obesity-related diseases.

Associations of three thermogenic adipokines with metabolic syndrome in obese and non-obese populations from the China plateau: the China Multi-Ethnic Cohort

OBJECTIVES

High altitude exposure decreases the incidence of obesity and metabolic syndrome, but increases the expression of the thermogenic adipokines (leptin, fat cell fatty acid-binding protein (A-FABP) and visfatin). This study investigated the correlation of these adipokines with obesity and metabolic syndrome (MetS) in populations residing in a plateau-specific environment.

DESIGN

Case-control study.

SETTING

We cross-sectionally analysed data from the China Multi-Ethnic Cohort.

PARTICIPANTS

A total of 475 obese (OB, body mass index (BMI)≥28.0 kg/m²) plateau Han people and 475 age, sex and region-matched non-obese (NO, 18.5≤BMI<24.0 kg/m²) subjects were recruited. MetS was defined according to the National Cholesterol Education Program Adult Treatment Panel III guidelines.

PRIMARY AND SECONDARY OUTCOME MEASURES

Data with normal distributions were expressed as the mean (Stanard Deviation, SD), and data with skewed distributions were expressed as the median (Interquartile Range, IQR). The participants were grouped and the rank-sum test, χ² test or t-tests was used for comparing groups. Spearman correlation coefficients were estimated to assess the relationships among leptin, A-FABP, visfatin and the components of MetS in each group.

RESULTS

A-FABP was an independent predictor of OB (OR, 1.207; 95% CI, 1.170 to 1.245; p<0.05), ABSI (OR, 1.035; 95%CI, 1.019 to 1.052; p<0.05) and MetS (OR, 1.035; 95% CI, 1.013 to 1.057; p<0.05). Leptin was an independent predictor of MetS in the NO group. Visfatin was an independent predictor of increased ABSI, but not for OB or MetS.

CONCLUSION

An abnormally elevated plasma A-FABP level, but not leptin or visfatin is a potential risk factor for MetS in high-altitude populations.

Longitudinal multi-omics study reveals common etiology underlying association between plasma proteome and BMI trajectories in adolescent and young adult twins

Background

The influence of genetics and environment on the association of the plasma proteome with body mass index (BMI) and changes in BMI remain underexplored, and the links to other omics in these associations remain to be investigated. We characterized protein-BMI trajectory associations in adolescents and adults and how these connect to other omics layers.

Methods

Our study included two cohorts of longitudinally followed twins: FinnTwin12 (N=651) and the Netherlands Twin Register (NTR) (N=665). Follow-up comprised four BMI measurements over approximately 6 (NTR: 23-27 years old) to 10 years (FinnTwin12: 12-22 years old), with omics data collected at the last BMI measurement. BMI changes were calculated using latent growth curve models. Mixed-effects models were used to quantify the associations between the abundance of 439 plasma proteins with BMI at blood sampling and changes in BMI. The sources of genetic and environmental variation underlying the protein abundances were quantified using twin models, as were the associations of proteins with BMI and BMI changes. In NTR, we investigated the association of gene expression of genes encoding proteins identified in FinnTwin12 with BMI and changes in BMI. We linked identified proteins and their coding genes to plasma metabolites and polygenic risk scores (PRS) using mixed-effect models and correlation networks.

Results

We identified 66 and 14 proteins associated with BMI at blood sampling and changes in BMI, respectively. The average heritability of these proteins was 35%. Of the 66 BMI-protein associations, 43 and 12 showed genetic and environmental correlations, respectively, including 8 proteins showing both. Similarly, we observed 6 and 4 genetic and environmental correlations between changes in BMI and protein abundance, respectively. S100A8 gene expression was associated with BMI at blood sampling, and the PRG4 and CFI genes were associated with BMI changes. Proteins showed strong connections with many metabolites and PRSs, but we observed no multi-omics connections among gene expression and other omics layers.

Conclusions

Associations between the proteome and BMI trajectories are characterized by shared genetic, environmental, and metabolic etiologies. We observed few gene-protein pairs associated with BMI or changes in BMI at the proteome and transcriptome levels.

Reversion of breast epithelial polarity alterations caused by obesity

Molecular links between breast cancer risk factors and pro-oncogenic tissue alterations are poorly understood. The goal of this study was to characterize the impact of overweight and obesity on tissue markers of risk, using normal breast biopsies, a mouse model of diet-induced obesity, and cultured breast acini. Proliferation and alteration of epithelial polarity, both necessary for tumor initiation, were quantified by immunostaining. High BMI (>30) and elevated leptin were associated with compromised epithelial polarity whereas overweight was associated with a modest increase in proliferation in human and mice mammary glands. Human serum with unfavorable adipokine levels altered epithelial polarization of cultured acini, recapitulating the effect of leptin. Weight loss in mice led to metabolic improvements and restored epithelial polarity. In acini cultures, alteration of epithelial polarity was prevented by antioxidants and could be reverted by normalizing culture conditions. This study shows that obesity and/or dietary factors modulate tissue markers of risk. It provides a framework to set target values for metabolic improvements and to assess the efficacy of interventional studies aimed at reducing breast cancer risk.

Canonical correlation analysis for multi-omics: Application to cross-cohort analysis

Integrative approaches that simultaneously model multi-omics data have gained increasing popularity because they provide holistic system biology views of multiple or all components in a biological system of interest. Canonical correlation analysis (CCA) is a correlation-based integrative method designed to extract latent features shared between multiple assays by finding the linear combinations of features-referred to as canonical variables (CVs)-within each assay that achieve maximal across-assay correlation. Although widely acknowledged as a powerful approach for multi-omics data, CCA has not been systematically applied to multi-omics data in large cohort studies, which has only recently become available. Here, we adapted sparse multiple CCA (SMCCA), a widely-used derivative of CCA, to proteomics and methylomics data from the Multi-Ethnic Study of Atherosclerosis (MESA) and Jackson Heart Study (JHS). To tackle challenges encountered when applying SMCCA to MESA and JHS, our adaptations include the incorporation of the Gram-Schmidt (GS) algorithm with SMCCA to improve orthogonality among CVs, and the development of Sparse Supervised Multiple CCA (SSMCCA) to allow supervised integration analysis for more than two assays. Effective application of SMCCA to the two real datasets reveals important findings. Applying our SMCCA-GS to MESA and JHS, we identified strong associations between blood cell counts and protein abundance, suggesting that adjustment of blood cell composition should be considered in protein-based association studies. Importantly, CVs obtained from two independent cohorts also demonstrate transferability across the cohorts. For example, proteomic CVs learned from JHS, when transferred to MESA, explain similar amounts of blood cell count phenotypic variance in MESA, explaining 39.0% ~ 50.0% variation in JHS and 38.9% ~ 49.1% in MESA. Similar transferability was observed for other omics-CV-trait pairs. This suggests that biologically meaningful and cohort-agnostic variation is captured by CVs. We anticipate that applying our SMCCA-GS and SSMCCA on various cohorts would help identify cohort-agnostic biologically meaningful relationships between multi-omics data and phenotypic traits.

Liver-Expressed Antimicrobial Peptide 2 Is a Hepatokine That Predicts Weight Loss and Complete Remission of Type 2 Diabetes Mellitus after Vertical Sleeve Gastrectomy in Japanese Individuals

INTRODUCTION

Vertical sleeve gastrectomy (VSG) is considered one of the most effective treatments for sustained weight loss and complete remission of type 2 diabetes mellitus (CR-T2DM). Liver-expressed antimicrobial peptide 2 (LEAP2), a ghrelin receptor antagonist peptide, is a metabolic hormone regulated by VSG. However, it is unknown whether LEAP2 can be used to predict the outcomes of VSG. This study aimed to evaluate LEAP2 as a predictive factor for weight loss and CR-T2DM after VSG.

METHODS

This retrospective study included 39 Japanese participants with obesity who underwent VSG. Serum LEAP2, des-acyl ghrelin (DAG), and other metabolic and anthropometric parameters were studied before and at 12 months after VSG. Receiver operating characteristics (ROC) curve was generated to evaluate predictive score for weight loss with cut-off value of >50 percent excess weight loss. ROC curve was also generated to assess CR-T2DM.

RESULTS

Serum LEAP2 levels were significantly higher in participants with body mass index (BMI) 32-50 kg/m2 than in those with normal weight. Participants with BMI >50 kg/m2 had lower serum LEAP2 concentrations than those with BMI 32-50 kg/m2. VSG caused a significant reduction in serum DAG concentrations, but it did not affect serum LEAP2 concentrations in either male or female participants. Preoperative serum LEAP2 concentration of 2.88 pmol/mL was the optimal cutoff value for predicting weight loss after VSG, with sensitivity of 80.0% and specificity of 75.9%. Preoperative serum LEAP2 level higher than 4.67 pmol/mL predicted CR-T2DM after VSG with sensitivity of 100% and specificity of 58.8%.

CONCLUSION

Preoperative serum LEAP2 could predict weight loss and CR-T2DM as outcomes of VSG.

Proteome and genome integration analysis of obesity

ABSTRACT

The prevalence of obesity has increased worldwide in recent decades. Genetic factors are now known to play a substantial role in the predisposition to obesity and may contribute up to 70% of the risk for obesity. Technological advancements during the last decades have allowed the identification of many hundreds of genetic markers associated with obesity. However, the transformation of current genetic variant-obesity associations into biological knowledge has been proven challenging. Genomics and proteomics are complementary fields, as proteomics extends functional analyses. Integrating genomic and proteomic data can help to bridge a gap in knowledge regarding genetic variant-obesity associations and to identify new drug targets for the treatment of obesity. We provide an overview of the published papers on the integrated analysis of proteomic and genomic data in obesity and summarize four mainstream strategies: overlap, colocalization, Mendelian randomization, and proteome-wide association studies. The integrated analyses identified many obesity-associated proteins, such as leptin, follistatin, and adenylate cyclase 3. Despite great progress, integrative studies focusing on obesity are still limited. There is an increased demand for large prospective cohort studies to identify and validate findings, and further apply these findings to the prevention, intervention, and treatment of obesity. In addition, we also discuss several other potential integration methods.

Differences and commonalities in the genetic architecture of protein quantitative trait loci in European and Arab populations

Polygenic scores (PGS) can identify individuals at risk of adverse health events and guide genetics-based personalized medicine. However, it is not clear how well PGS translate between different populations, limiting their application to well-studied ethnicities. Proteins are intermediate traits linking genetic predisposition and environmental factors to disease, with numerous blood circulating protein levels representing functional readouts of disease-related processes. We hypothesized that studying the genetic architecture of a comprehensive set of blood-circulating proteins between a European and an Arab population could shed fresh light on the translatability of PGS to understudied populations. We therefore conducted a genome-wide association study with whole-genome sequencing data using 1301 proteins measured on the SOMAscan aptamer-based affinity proteomics platform in 2935 samples of Qatar Biobank and evaluated the replication of protein quantitative traits (pQTLs) from European studies in an Arab population. Then, we investigated the colocalization of shared pQTL signals between the two populations. Finally, we compared the performance of protein PGS derived from a Caucasian population in a European and an Arab cohort. We found that the majority of shared pQTL signals (81.8%) colocalized between both populations. About one-third of the genetic protein heritability was explained by protein PGS derived from a European cohort, with protein PGS performing ~20% better in Europeans when compared to Arabs. Our results are relevant for the translation of PGS to non-Caucasian populations, as well as for future efforts to extend genetic research to understudied populations.

Metabolically Healthy Obesity: Are Interventions Useful?

PURPOSE OF REVIEW

This review aims to detail the current global research state of metabolically healthy obesogenesis with regard to metabolic factors, disease prevalence, comparisons to unhealthy obesity, and targeted interventions to reverse or delay progression from metabolically healthy to unhealthy obesity.

RECENT FINDINGS

As a long-term condition with increased risk of cardiovascular, metabolic, and all-cause mortality risks, obesity threatens public health on a national level. The recent discovery of metabolically healthy obesity (MHO), a transitional condition during which obese persons carry comparatively lower health risks, has added to confusion about the true effect of visceral fat and subsequent long-term health risks. In this context, the evaluation of fat loss interventions, such as bariatric surgery, lifestyle changes (diet/exercise), and hormonal therapies require re-evaluation in light of evidence that progression to high-risk stages of obesity relies on metabolic status and that strategies to protect the metabolism may be useful in the prevention of metabolically unhealthy obesity. Typical calorie-based exercise and diet interventions have failed to reduce the prevalence of unhealthy obesity. Holistic lifestyle, psychological, hormonal, and pharmacological interventions for MHO, on the other hand, may at least prevent progression to metabolically unhealthy obesity.

Whole Transcriptome Analysis of Hypothalamus in Mice during Short-Term Starvation

Molecular profiling of the hypothalamus in response to metabolic shifts is a critical cue to better understand the principle of the central control of whole-body energy metabolism. The transcriptional responses of the rodent hypothalamus to short-term calorie restriction have been documented. However, studies on the identification of hypothalamic secretory factors that potentially contribute to the control of appetite are lacking. In this study, we analyzed the differential expression of hypothalamic genes and compared the selected secretory factors from the fasted mice with those of fed control mice using bulk RNA-sequencing. We verified seven secretory genes that were significantly altered in the hypothalamus of fasted mice. In addition, we determined the response of secretory genes in cultured hypothalamic cells to treatment with ghrelin and leptin. The current study provides further insights into the neuronal response to food restriction at the molecular level and may be useful for understanding the hypothalamic control of appetite.

Proteome-wide Mendelian randomization implicates nephronectin as an actionable mediator of the effect of obesity on COVID-19 severity

Obesity is a major risk factor for Coronavirus disease (COVID-19) severity; however, the mechanisms underlying this relationship are not fully understood. As obesity influences the plasma proteome, we sought to identify circulating proteins mediating the effects of obesity on COVID-19 severity in humans. Here, we screened 4,907 plasma proteins to identify proteins influenced by body mass index using Mendelian randomization. This yielded 1,216 proteins, whose effect on COVID-19 severity was assessed, again using Mendelian randomization. We found that an s.d. increase in nephronectin (NPNT) was associated with increased odds of critically ill COVID-19 (OR = 1.71, P = 1.63 × 10^-10). The effect was driven by an NPNT splice isoform. Mediation analyses supported NPNT as a mediator. In single-cell RNA-sequencing, NPNT was expressed in alveolar cells and fibroblasts of the lung in individuals who died of COVID-19. Finally, decreasing body fat mass and increasing fat-free mass were found to lower NPNT levels. These findings provide actionable insights into how obesity influences COVID-19 severity.

Association of epicardial adipose tissue with proteomics, coronary flow reserve, cardiac structure and function, and quality of life in heart failure with preserved ejection fraction: insights from the PROMIS-HFpEF study

AIM

Epicardial adipose tissue (EAT) may play a role in the pathophysiology of heart failure with preserved ejection fraction (HFpEF). We investigated associations of EAT with proteomics, coronary flow reserve (CFR), cardiac structure and function, and quality of life (QoL) in the prospective multinational PROMIS-HFpEF cohort.

METHODS AND RESULTS

Epicardial adipose tissue was measured by echocardiography in 182 patients and defined as increased if ≥9 mm. Proteins were measured using high-throughput proximity extension assays. Microvascular dysfunction was evaluated with Doppler-based CFR, cardiac structural and functional indices with echocardiography and QoL by Kansas City Cardiomyopathy Questionnaire (KCCQ). Patients with increased EAT (n = 54; 30%) had higher body mass index (32 [28-40] vs. 27 [23-30] kg/m² ; p < 0.001), lower N-terminal pro-B-type natriuretic peptide (466 [193-1133] vs. 1120 [494-1990] pg/ml; p < 0.001), smaller indexed left ventricular (LV) end-diastolic and left atrial (LA) volumes and tendency to lower KCCQ score. Non-indexed LV/LA volumes did not differ between groups. When adjusted for body mass index, EAT remained associated with LV septal wall thickness (coefficient 1.02, 95% confidence interval [CI] 1.00-1.04; p = 0.018) and mitral E wave deceleration time (coefficient 1.03, 95% CI 1.01-1.05; p = 0.005). Increased EAT was associated with proteomic markers of adipose biology and inflammation, insulin resistance, endothelial dysfunction, and dyslipidaemia but not significantly with CFR.

CONCLUSION

Increased EAT was associated with cardiac structural alterations and proteins expressing adiposity, inflammation, lower insulin sensitivity and endothelial dysfunction related to HFpEF pathology, probably driven by general obesity. Potential local mechanical or paracrine effects mediated by EAT remain to be elucidated.

Metabolic and proteomic signatures of type 2 diabetes subtypes in an Arab population

Type 2 diabetes (T2D) has a heterogeneous etiology influencing its progression, treatment, and complications. A data driven cluster analysis in European individuals with T2D previously identified four subtypes: severe insulin deficient (SIDD), severe insulin resistant (SIRD), mild obesity-related (MOD), and mild age-related (MARD) diabetes. Here, the clustering approach was applied to individuals with T2D from the Qatar Biobank and validated in an independent set. Cluster-specific signatures of circulating metabolites and proteins were established, revealing subtype-specific molecular mechanisms, including activation of the complement system with features of autoimmune diabetes and reduced 1,5-anhydroglucitol in SIDD, impaired insulin signaling in SIRD, and elevated leptin and fatty acid binding protein levels in MOD. The MARD cluster was the healthiest with metabolomic and proteomic profiles most similar to the controls. We have translated the T2D subtypes to an Arab population and identified distinct molecular signatures to further our understanding of the etiology of these subtypes.

Alterations in DNA methylation associate with fatty liver and metabolic abnormalities in a multi-ethnic cohort of pre-teenage children

Non-Alcoholic fatty liver disease (NAFLD) is the leading cause of chronic liver disease in children. Epigenetic alterations, such as through DNA methylation (DNAm), may link adverse childhood exposures and fatty liver and provide non-invasive methods for identifying children at high risk for NAFLD and associated metabolic dysfunction. We investigated the association between differential DNAm and liver fat content (LFC) and liver injury in pre-adolescent children. Leveraging data from the Newborn Epigenetics Study (NEST), we enrolled 90    mother-child dyads and used linear regression to identify CpG sites and differentially methylated regions (DMRs) in peripheral blood associated with LFC and alanine aminotransferase (ALT) levels in 7-12yo children. DNAm was measured using Infinium HumanMethylationEPIC BeadChips (Illumina). LFC and fibrosis were quantified by magnetic resonance imaging proton density fat fraction and elastography. Median LFC was 1.4% (range, 0.3-13.4%) and MRE was 2.5 kPa (range, 1.5-3.6kPa). Three children had LFC ≥ 5%, while six (7.6%) met our definition of NAFLD (LFC ≥ 3.7%). All children with NAFLD were obese and five were Black. LFC was associated with 88 DMRs and 106 CpGs (FDR<5%). The top two CpGs, cg25474373 and cg07264203, mapped to or near RFTN2 and PRICKLE2 genes. These two CpG sites were also significantly associated with a NAFLD diagnosis. As higher LFC associates with an adverse cardiometabolic profile already in childhood, altered DNAm may identify these children early in disease course for targeted intervention. Larger, longitudinal studies are needed to validate these findings and determine mechanistic relevance.

Holistic Integration of Omics Tools for Precision Nutrition in Health and Disease

The combination of multiple omics approaches has emerged as an innovative holistic scope to provide a more comprehensive view of the molecular and physiological events underlying human diseases (including obesity, dyslipidemias, fatty liver, insulin resistance, and inflammation), as well as for elucidating unique and specific metabolic phenotypes. These omics technologies include genomics (polymorphisms and other structural genetic variants), epigenomics (DNA methylation, histone modifications, long non-coding RNA, telomere length), metagenomics (gut microbiota composition, enterotypes), transcriptomics (RNA expression patterns), proteomics (protein quantities), and metabolomics (metabolite profiles), as well as interactions with dietary/nutritional factors. Although more evidence is still necessary, it is expected that the incorporation of integrative omics could be useful not only for risk prediction and early diagnosis but also for guiding tailored dietary treatments and prognosis schemes. Some challenges include ethical and regulatory issues, the lack of robust and reproducible results due to methodological aspects, the high cost of omics methodologies, and high-dimensional data analyses and interpretation. In this review, we provide examples of system biology studies using multi-omics methodologies to unravel novel insights into the mechanisms and pathways connecting the genotype to clinically relevant traits and therapy outcomes for precision nutrition applications in health and disease.

Uncovering the functions of plasma proteins in ulcerative colitis and identifying biomarkers for BPA-induced severe ulcerative colitis: A plasma proteome analysis

Ulcerative colitis (UC), a long-term inflammation of the colon, is a worldwide disease. Accumulating reports have suggested the contribution of environmental pollutants to UC development. As such, the identification of biomarkers to evaluate pollutant-induced UC could provide a better assessment on the world's pollution problem. In the present study, we applied the plasma proteome to profile the plasma protein changes in three models: dextran sulfate sodium (DSS)-induced colitis, bisphenol A (BPA), and BPA-severe colitis. We aimed to investigate the functional roles of plasma proteins related to colitis development and further understand the synergistic effect of BPA on colitis. In addition, we aimed to identify novel biomarkers for UC non-invasive diagnosis and assessment of BPA-induced colitis. Our results showed a significant dysregulation of plasma proteins in these three models. Bioinformatics analysis, including gene ontology, Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, and Ingenuity Pathway Analysis, highlighted the important effects of these dysregulated plasma proteins in immune and inflammatory responses through the regulation of CCR3 signaling in eosinophils, PI3K signaling in B lymphocytes, CD28 signaling in T helper cells, and leukocyte extravasation signaling in DSS-induced colitis model. Furthermore, our data suggested that BPA exposure altered the plasma proteins involved in lipid-related metabolic processes, leukocyte cell-cell adhesion and cytokine response. More importantly, we identified plasma proteins, ALB, APOA4, C3, CFB, DPEP1, HP, LTF, and Retnlg as biomarkers for assessing BPA-induced colitis.

Dietary carbohydrates: Pathogenesis and potential therapeutic targets to obesity-associated metabolic syndrome

Metabolic syndrome (MetS) is a common feature in obesity, comprising a cluster of abnormalities including abdominal fat accumulation, hyperglycemia, hyperinsulinemia, dyslipidemia, and hypertension, leading to diabetes and cardiovascular diseases (CVD). Intake of carbohydrates (CHO), particularly a sugary diet that rapidly increases blood glucose, triglycerides, and blood pressure levels is the predominant determining factor of MetS. Complex CHO, on the other hand, are a stable source of energy taking a longer time to digest. In particular, resistant starch (RS) or soluble fiber is an excellent source of prebiotics, which alter the gut microbial composition, which in turn improves metabolic control. Altering maternal CHO intake during pregnancy may result in the child developing MetS. Furthermore, lifestyle factors such as physical inactivity in combination with dietary habits may synergistically influence gene expression by modulating genetic and epigenetic regulators transforming childhood obesity into adolescent metabolic disorders. This review summarizes the common pathophysiology of MetS in connection with the nature of CHO, intrauterine nutrition, genetic predisposition, lifestyle factors, and advanced treatment approaches; it also emphasizes how dietary CHO may act as a key element in the pathogenesis and future therapeutic targets of obesity and MetS.

The heart-brain axis: A proteomics study of meditation on the cardiovascular system of Tibetan Monks

Background

There have been mixed reports on the beneficial effects of meditation in cardiovascular disease (CVD), which is widely considered the leading cause of death worldwide.

Methods

To clarify the role of meditation in modulating the heart-brain axis, we implemented an extreme phenotype strategy, i.e., Tibetan monks (BMI > 30) who practised 19.20 ± 7.82 years of meditation on average and their strictly matched non-meditative Tibetan controls. Hypothesis-free advanced proteomics strategies (Data Independent Acquisition and Targeted Parallel Reaction Monitoring) were jointly applied to systematically investigate and target the plasma proteome underlying meditation. Total cholesterol, low-density lipoprotein cholesterol  (LDL-C), apolipoprotein B (Apo B) and lipoprotein (a) [Lp(a)] as the potential cardiovascular risk factors were evaluated. Heart rate variability (HRV) was assessed by electrocardiogram.

Findings

Obesity, hypertension, and reduced HRV is offset by long-term meditation. Notably, meditative monks have blood pressure and HRV comparable to their matched Tibetan controls. Meditative monks have a protective plasma proteome, related to decreased atherosclerosis, enhanced glycolysis, and oxygen release, that confers resilience to the development of CVD. In addition, clinical risk factors in plasma were significantly decreased in monks compared with controls, including total cholesterol, LDL-C, Apo B, and Lp(a).

Interpretation

To our knowledge, this work is the first well-controlled proteomics investigation of long-term meditation, which opens up a window for individuals characterized by a sedentary lifestyle to improve their cardiovascular health with an accessible method practised for more than two millennia.

Funding

See the Acknowledgements section.

Repurposing drugs to treat cardiovascular disease in the era of precision medicine

Drug repurposing is the use of a given therapeutic agent for indications other than that for which it was originally designed or intended. The concept is appealing because of potentially lower development costs and shorter timelines than are needed to produce a new drug. To date, drug repurposing for cardiovascular indications has been opportunistic and driven by knowledge of disease mechanisms or serendipitous observation rather than by systematic endeavours to match an existing drug to a new indication. Innovations in two areas of personalized medicine — computational approaches to associate drug effects with disease signatures and predictive model systems to screen drugs for disease-modifying activities — support efforts that together create an efficient pipeline to systematically repurpose drugs to treat cardiovascular disease. Furthermore, new experimental strategies that guide the medicinal chemistry re-engineering of drugs could improve repurposing efforts by tailoring a medicine to its new indication. In this Review, we summarize the historical approach to repurposing and discuss the technological advances that have created a new landscape of opportunities.

Drugs can be repurposed for new therapeutic indications. In this Review, Mercola and colleagues summarize the latest techniques for systematic drug repurposing and re-engineering, which could increase the pace, efficiency and cost-effectiveness of drug discovery for the treatment of cardiovascular disease.

Contemporary technologies are expected to make drug repurposing large-scale, systematic and deliberate rather than opportunistic.

New experimental and computational tools harness patient genomics for drug repurposing.

Discovery of repurposed drugs on the basis of patient genomics has implications for precision prescribing of medicines to treat individual patients.

The treatment of rare, monogenic diseases, which often provide too little return on investment to incentivize conventional drug discovery, might benefit because the molecular aetiologies of these diseases are well suited to the discovery of drug repurposing candidates.

An approach for evaluating the effects of dietary fiber polysaccharides on the human gut microbiome and plasma proteome

Increases in snack consumption associated with Westernized lifestyles provide an opportunity to introduce nutritious foods into poor diets. We describe two 10-wk-long open label, single group assignment human studies that measured the effects of two snack prototypes containing fiber preparations from two sustainable and scalable sources; the byproducts remaining after isolation of protein from the endosperm of peas and the vesicular pulp remaining after processing oranges for the manufacture of juices. The normal diets of study participants were supplemented with either a pea- or orange fiber-containing snack. We focused our analysis on quantifying the abundances of genes encoding carbohydrate-active enzymes (CAZymes) (glycoside hydrolases and polysaccharide lyases) in the fecal microbiome, mass spectrometric measurements of glycan structures (glycosidic linkages) in feces, plus aptamer-based assessment of levels of 1,300 plasma proteins reflecting a broad range of physiological functions. Computational methods for feature selection identified treatment-discriminatory changes in CAZyme genes that correlated with alterations in levels of fiber-associated glycosidic linkages; these changes in turn correlated with levels of plasma proteins representing diverse biological functions, including transforming growth factor type β/bone morphogenetic protein-mediated fibrosis, vascular endothelial growth factor-related angiogenesis, P38/MAPK-associated immune cell signaling, and obesity-associated hormonal regulators. The approach used represents a way to connect changes in consumer microbiomes produced by specific fiber types with host responses in the context of varying background diets.

Mendelian Randomization Analysis Reveals Causal Effects of Plasma Proteome on Body Composition Traits

CONTEXT

Observational studies have demonstrated associations between plasma proteins and obesity, but evidence of causal relationship remains to be studied.

OBJECTIVE

We aimed to evaluate the causal relationship between plasma proteins and body composition.

METHODS

We conducted a 2-sample Mendelian randomization (MR) analysis based on the genome-wide association study (GWAS) summary statistics of 23 body composition traits and 2656 plasma proteins. We then performed hierarchical cluster analysis to evaluate the structure and pattern of the identified causal associations, and we performed gene ontology enrichment analysis to explore the functional relevance of the identified proteins.

RESULTS

We identified 430 putatively causal effects of 96 plasma proteins on 22 body composition traits (except obesity status) with strong MR evidence (P < 2.53 × 10 - 6, at a Bonferroni-corrected threshold). The top 3 causal associations are follistatin (FST) on trunk fat-free mass (Beta = -0.63, SE = 0.04, P = 2.00 × 10-63), insulin-like growth factor-binding protein 1 (IGFBP1) on trunk fat-free mass (Beta = -0.54, SE = 0.03, P = 1.79 × 10-57) and r-spondin-3 (RSPO3) on WHR (waist circumference/hip circumference) (Beta = 0.01, SE = 4.47 × 10-4, P = 5.45 × 10-60), respectively. Further clustering analysis and pathway analysis demonstrated that the pattern of causal effect to fat mass and fat-free mass may be different.

CONCLUSION

Our findings may provide evidence for causal relationships from plasma proteins to various body composition traits and provide basis for further targeted functional studies.

Insulin-Like Growth Factor Binding Proteins in Kidney Disease

The seven members of the insulin-like growth factor (IGF) binding protein family (IGFBPs) were initially considered to be the regulatory proteins of IGFs in the blood circulation, mainly as the subsequent reserve for bidirectional regulation of IGF function during environmental changes. However, in recent years, IGFBPs has been found to have many functions independent of IGFs. The role of IGFBPs in regulating transcription, inducing cell migration and apoptosis is closely related to the occurrence and development of kidney disease. IGFBP-1, IGFBP-3, IGFBP-4 are closely associated with diabetes and diabetic nephropathy. IGFBP-3, IGFBP-4, IGFBP-5, IGFBP-6 are involved in different kidney disease such as diabetes, FSGS and CKD physiological process as apoptosis proteins, IGFBP-7 has been used in clinical practice as a biomarker for early diagnosis and prognosis of AKI. This review focuses on the differential expression and pathogenesis of IGFBPs in kidney disease.

Proteome-wide associations with short- and long-term weight loss and regain after Roux-en-Y gastric bypass surgery

OBJECTIVE

Gastric bypass surgery results in long-term weight loss. Small studies have examined protein changes during rapid weight loss (up to 1 or 2 years post surgery). This study tested whether short-term changes were maintained after 12 years.

METHODS

A 12-year follow-up, protein-wide association study of 1,297 SomaLogic aptamer-based plasma proteins compared short- (2-year) and long-term (12-year) protein changes in 234 individuals who had gastric bypass surgery with 144 nonintervened individuals with severe obesity.

RESULTS

There were 51 replicated 12-year protein changes that differed between the surgery and nonsurgery groups. Adjusting for change in BMI, only 12 proteins remained significant, suggesting that BMI change was the primary reason for most protein changes and not non-BMI-related surgical effects. Protein changes were related to BMI changes during both weight-loss and weight-regain periods. The significant proteins were associated primarily with lipid, uric acid, or resting energy expenditure clinical variables and metabolic pathways. Eight protein changes were associated with 12-year diabetes remission, including apolipoprotein M, sex hormone binding globulin, and adiponectin (p < 3.5 × 10^-5 ).

CONCLUSIONS

This study showed that most short-term postsurgical changes in proteins were maintained at 12 years. Systemic protection pathways, including inflammation, complement, lipid, and adipocyte pathways, were related to the long-term benefits of gastric bypass surgery.

Effects of adiposity on the human plasma proteome: observational and Mendelian randomisation estimates

BACKGROUND

Variation in adiposity is associated with cardiometabolic disease outcomes, but mechanisms leading from this exposure to disease are unclear. This study aimed to estimate effects of body mass index (BMI) on an extensive set of circulating proteins.

METHODS

We used SomaLogic proteomic data from up to 2737 healthy participants from the INTERVAL study. Associations between self-reported BMI and 3622 unique plasma proteins were explored using linear regression. These were complemented by Mendelian randomisation (MR) analyses using a genetic risk score (GRS) comprised of 654 BMI-associated polymorphisms from a recent genome-wide association study (GWAS) of adult BMI. A disease enrichment analysis was performed using DAVID Bioinformatics 6.8 for proteins which were altered by BMI.

RESULTS

Observationally, BMI was associated with 1576 proteins (P < 1.4 × 10-5), with particularly strong evidence for a positive association with leptin and fatty acid-binding protein-4 (FABP4), and a negative association with sex hormone-binding globulin (SHBG). Observational estimates were likely confounded, but the GRS for BMI did not associate with measured confounders. MR analyses provided evidence for a causal relationship between BMI and eight proteins including leptin (0.63 standard deviation (SD) per SD BMI, 95% CI 0.48-0.79, P = 1.6 × 10-15), FABP4 (0.64 SD per SD BMI, 95% CI 0.46-0.83, P = 6.7 × 10-12) and SHBG (-0.45 SD per SD BMI, 95% CI -0.65 to -0.25, P = 1.4 × 10-5). There was agreement in the magnitude of observational and MR estimates (R2 = 0.33) and evidence that proteins most strongly altered by BMI were enriched for genes involved in cardiovascular disease.

CONCLUSIONS

This study provides evidence for a broad impact of adiposity on the human proteome. Proteins strongly altered by BMI include those involved in regulating appetite, sex hormones and inflammation; such proteins are also enriched for cardiovascular disease-related genes. Altogether, results help focus attention onto new proteomic signatures of obesity-related disease.

Towards Building a Quantitative Proteomics Toolbox in Precision Medicine: A Mini-Review

Precision medicine as a framework for disease diagnosis, treatment, and prevention at the molecular level has entered clinical practice. From the start, genetics has been an indispensable tool to understand and stratify the biology of chronic and complex diseases in precision medicine. However, with the advances in biomedical and omics technologies, quantitative proteomics is emerging as a powerful technology complementing genetics. Quantitative proteomics provide insight about the dynamic behaviour of proteins as they represent intermediate phenotypes. They provide direct biological insights into physiological patterns, while genetics accounting for baseline characteristics. Additionally, it opens a wide range of applications in clinical diagnostics, treatment stratification, and drug discovery. In this mini-review, we discuss the current status of quantitative proteomics in precision medicine including the available technologies and common methods to analyze quantitative proteomics data. Furthermore, we highlight the current challenges to put quantitative proteomics into clinical settings and provide a perspective to integrate proteomics data with genomics data for future applications in precision medicine.

Anti-Adipogenic Effect of Alchemilla monticola is Mediated Via PI3K/AKT Signaling Inhibition in Human Adipocytes

Obesity is a persistent and continuously expanding social health concern. Excessive fat mass accumulation is associated with increased risk of chronic diseases including diabetes, atherosclerosis, non-alcoholic steatohepatitis, reproductive dysfunctions and certain types of cancer. Alchemilla monticola Opiz. is a perennial plant of the Rosaceae family traditionally used to treat inflammatory conditions and as a component of weight loss herbal mixtures. In the search for bioactive leads with potential anti-adipogenic effect from A. monticola extract (ALM), we have employed nuclear magnetic resonance (NMR) based metabolomics to obtain data for the phytochemical profile of the extract. Further, molecular docking simulation was performed against key adipogenic targets for selected pure compounds, present in the ALM extract. Evaluation of the biological activity was done in human adipocytes exposed to ALM (5, 10 and 25 μg/ml), pure astragalin (AST) or quercitrin (QUE) both at the concentrations of 5, 10 and 25 μM. Investigation of the molecular pathways involved was performed through real-time quantitative PCR and Western blot analyses. According to the docking predictions strong putative affinity was revealed for both AST and QUE towards peroxisome proliferator-activated receptor gamma (PPARγ) and phosphoinositide 3-kinase (PI3K). Assessment of the intracellular lipid accumulation revealed anti-adipogenic activity of ALM. Correspondingly, the expression of the adipogenic genes CCAAT/enhancer-binding protein alpha (CEBPA) and PPARG was downregulated upon ALM and AST treatment. The Western blotting results exposed protein kinase B (AKT), PI3K and PPARγ as targets for the inhibitory effect of ALM and AST on adipogenesis. Collectively, we provide a broader insight of the phytochemical composition of A. monticola. Additionally, we demonstrate the anti-adipogenic effect of ALM and its active compound AST in human adipocytes. Furthermore, PI3K/AKT signaling pathway is identified to mediate the ALM anti-adipogenic action. Hence, the ALM extract and its secondary metabolite AST are worth further exploration as potentially active agents in obesity management.

Metabolic syndrome and the plasma proteome: from association to causation

Background

The metabolic syndrome (MetS), defined by the simultaneous clustering of cardio-metabolic risk factors, is a significant worldwide public health burden with an estimated 25% prevalence worldwide. The pathogenesis of MetS is not entirely clear and the use of molecular level data could help uncover common pathogenic pathways behind the observed clustering.

Methods

Using a highly multiplexed aptamer-based affinity proteomics platform, we examined associations between plasma proteins and prevalent and incident MetS in the KORA cohort (n = 998) and replicated our results for prevalent MetS in the HUNT3 study (n = 923). We applied logistic regression models adjusted for age, sex, smoking status, and physical activity.

We used the bootstrap ranking algorithm of least absolute shrinkage and selection operator (LASSO) to select a predictive model from the incident MetS associated proteins and used area under the curve (AUC) to assess its performance. Finally, we investigated the causal effect of the replicated proteins on MetS using two-sample Mendelian randomization.

Results

Prevalent MetS was associated with 116 proteins, of which 53 replicated in HUNT. These included previously reported proteins like leptin, and new proteins like NTR domain-containing protein 2 and endoplasmic reticulum protein 29. Incident MetS was associated with 14 proteins in KORA, of which 13 overlap the prevalent MetS associated proteins with soluble advanced glycosylation end product-specific receptor (sRAGE) being unique to incident MetS. The LASSO selected an eight-protein predictive model with an (AUC = 0.75; 95% CI = 0.71–0.79) in KORA.

Mendelian randomization suggested causal effects of three proteins on MetS, namely apolipoprotein E2 (APOE2) (Wald-Ratio = − 0.12, Wald-p = 3.63e−13), apolipoprotein B (APOB) (Wald-Ratio = − 0.09, Wald-p = 2.54e−04) and proto-oncogene tyrosine-protein kinase receptor (RET) (Wald-Ratio = 0.10, Wald-p = 5.40e−04).

Conclusions

Our findings offer new insights into the plasma proteome underlying MetS and identify new protein associations. We reveal possible casual effects of APOE2, APOB and RET on MetS. Our results highlight protein candidates that could potentially serve as targets for prevention and therapy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12933-021-01299-2.