Plasma protein expression profiles, cardiovascular disease, and religious struggles among South Asians in the MASALA study

Plasma proteome association with coronary heart disease and carotid intima media thickness: results from the KORA F4 study

BACKGROUND AND AIMS

Atherosclerosis is the main cause of stroke and coronary heart disease (CHD), both leading mortality causes worldwide. Proteomics, as a high-throughput method, could provide helpful insights into the pathological mechanisms underlying atherosclerosis. In this study, we characterized the associations of plasma protein levels with CHD and with carotid intima-media thickness (CIMT), as a surrogate measure of atherosclerosis.

METHODS

The discovery phase included 1000 participants from the KORA F4 study, whose plasma protein levels were quantified using the aptamer-based SOMAscan proteomics platform. We evaluated the associations of plasma protein levels with CHD using logistic regression, and with CIMT using linear regression. For both outcomes we applied two models: an age-sex adjusted model, and a model additionally adjusted for body mass index, smoking status, physical activity, diabetes status, hypertension status, low density lipoprotein, high density lipoprotein, and triglyceride levels (fully-adjusted model). The replication phase included a matched case-control sample from the independent KORA F3 study, using ELISA-based measurements of galectin-4. Pathway analysis was performed with nominally associated proteins (p-value < 0.05) from the fully-adjusted model.

RESULTS

In the KORA F4 sample, after Bonferroni correction, we found CHD to be associated with five proteins using the age-sex adjusted model: galectin-4 (LGALS4), renin (REN), cathepsin H (CTSH), and coagulation factors X and Xa (F10). The fully-adjusted model yielded only the positive association of galectin-4 (OR = 1.58, 95% CI = 1.30-1.93), which was successfully replicated in the KORA F3 sample (OR = 1.40, 95% CI = 1.09-1.88). For CIMT, we found four proteins to be associated using the age-sex adjusted model namely: cytoplasmic protein NCK1 (NCK1), insulin-like growth factor-binding protein 2 (IGFBP2), growth hormone receptor (GHR), and GDNF family receptor alpha-1 (GFRA1). After assessing the fully-adjusted model, only NCK1 remained significant (β = 0.017, p-value = 1.39e-06). Upstream regulators of galectin-4 and NCK1 identified from pathway analysis were predicted to be involved in inflammation pathways.

CONCLUSIONS

Our proteome-wide association study identified galectin-4 to be associated with CHD and NCK1 to be associated with CIMT. Inflammatory pathways underlying the identified associations highlight the importance of inflammation in the development and progression of CHD.

Lessons Learned from Immigrant Health Cohorts: A Review of the Evidence and Implications for Policy and Practice in Addressing Health Inequities among Asian Americans, Native Hawaiians, and Pacific Islanders

The health of Asian Americans, Native Hawaiians, and Pacific Islanders (AANHPI) is uniquely impacted by structural and social determinants of health (SSDH) shaped by immigration policies and colonization practices, patterns of settlement, and racism. These SSDH also create vast heterogeneity in disease risks across the AANHPI population, with some ethnic groups having high disease burden, often masked with aggregated data. Longitudinal cohort studies are an invaluable tool to identify risk factors of disease, and epidemiologic cohort studies among AANHPI populations have led to seminal discoveries of disease risk factors. This review summarizes the limited but growing literature, with a focus on SSDH factors, from seven longitudinal cohort studies with substantial AANHPI samples. We also discuss key information gaps and recommendations for the next generation of AANHPI cohorts, including oversampling AANHPI ethnic groups; measuring and innovating on measurements of SSDH; emphasizing the involvement of scholars from diverse disciplines; and, most critically, engaging community members to ensure relevancy for public health, policy, and clinical impact.

Bioinformatics and experimental analyses of glutamate receptor and its targets genes in myocardial and cerebral ischemia

BACKGROUND

There is a mutual hemodynamic and pathophysiological basis between the heart and brain. Glutamate (GLU) signaling plays an important role in the process of myocardial ischemia (MI) and ischemic stroke (IS). To further explore the common protective mechanism after cardiac and cerebral ischemic injuries, the relationship between GLU receptor-related genes and MI and IS were analyzed.

RESULTS

A total of 25 crosstalk genes were identified, which were mainly enriched in the Toll-like receptor signaling pathway, Th17 cell differentiation, and other signaling pathways. Protein-protein interaction analysis suggested that the top six genes with the most interactions with shared genes were IL6, TLR4, IL1B, SRC, TLR2, and CCL2. Immune infiltration analysis suggested that immune cells such as myeloid-derived suppressor cells and monocytes were highly expressed in the MI and IS data. Memory B cells and Th17 cells were expressed at low levels in the MI and IS data; molecular interaction network construction suggested that genes such as JUN, FOS, and PPARA were shared genes and transcription factors; FCGR2A was a shared gene of MI and IS as well as an immune gene. Least absolute shrinkage and selection operator logistic regression analysis identified nine hub genes: IL1B, FOS, JUN, FCGR2A, IL6, AKT1, DRD4, GLUD2, and SRC. Receiver operating characteristic analysis revealed that the area under the curve of these hub genes was > 65% in MI and IS for all seven genes except IL6 and DRD4. Furthermore, clinical blood samples and cellular models showed that the expression of relevant hub genes was consistent with the bioinformatics analysis.

CONCLUSIONS

In this study, we found that the GLU receptor-related genes IL1B, FOS, JUN, FCGR2A, and SRC were expressed in MI and IS with the same trend, which can be used to predict the occurrence of cardiac and cerebral ischemic diseases and provide reliable biomarkers to further explore the co-protective mechanism after cardiac and cerebral ischemic injury.

Analytical Considerations of Large-Scale Aptamer-Based Datasets for Translational Applications

The development and advancement of aptamer technology has opened a new realm of possibilities for unlocking the biocomplexity available within proteomics. With ultra-high-throughput and multiplexing, alongside remarkable specificity and sensitivity, aptamers could represent a powerful tool in disease-specific research, such as supporting the discovery and validation of clinically relevant biomarkers. One of the fundamental challenges underlying past and current proteomic technology has been the difficulty of translating proteomic datasets into standards of practice. Aptamers provide the capacity to generate single panels that span over 7000 different proteins from a singular sample. However, as a recent technology, they also present unique challenges, as the field of translational aptamer-based proteomics still lacks a standardizing methodology for analyzing these large datasets and the novel considerations that must be made in response to the differentiation amongst current proteomic platforms and aptamers. We address these analytical considerations with respect to surveying initial data, deploying proper statistical methodologies to identify differential protein expressions, and applying datasets to discover multimarker and pathway-level findings. Additionally, we present aptamer datasets within the multi-omics landscape by exploring the intersectionality of aptamer-based proteomics amongst genomics, transcriptomics, and metabolomics, alongside pre-existing proteomic platforms. Understanding the broader applications of aptamer datasets will substantially enhance current efforts to generate translatable findings for the clinic.

Precision Medicine Approach for Cardiometabolic Risk Factors in Therapeutic Apheresis

Lipoprotein apheresis (LA) is currently the most powerful intervention possible to reach a maximal reduction of lipids in patients with familial hypercholesterolemia and lipoprotein(a) hyperlipidemia. Although LA is an invasive method, it has few side effects and the best results in preventing further major cardiovascular events. It has been suggested that the highly significant reduction of cardiovascular complications in patients with severe lipid disorders achieved by LA is mediated not only by the potent reduction of lipid levels but also by the removal of other proinflammatory and proatherogenic factors. Here we performed a comprehensive proteomic analysis of patients on LA treatment using intra-individually a set of differently sized apheresis filters with the INUSpheresis system. This study revealed that proteomic analysis correlates well with routine clinical chemistry in these patients. The method is eminently suited to discover new biomarkers and risk factors for cardiovascular disease in these patients. Different filters achieve reduction and removal of proatherogenic proteins in different quantities. This includes not only apolipoproteins, C-reactive protein, fibrinogen, and plasminogen but also proteins like complement factor B (CFAB), protein AMBP, afamin, and the low affinity immunoglobulin gamma Fc region receptor III-A (FcγRIIIa) among others that have been described as atherosclerosis and metabolic vascular diseases promoting factors. We therefore conclude that future trials should be designed to develop an individualized therapy approach for patients on LA based on their metabolic and vascular risk profile. Furthermore, the power of such cascade filter treatment protocols may improve the prevention of cardiometabolic disease and its complications.

Identification of Hub Genes Associated with Abnormal Endothelial Function in Early Coronary Atherosclerosis

Abnormal coronary endothelial function is an important step in the development of atherosclerosis. Coronary atherosclerosis is one of the main causes of death worldwide. We constructed a co-expression network to identify hub genes associated with abnormal coronary endothelial function in early coronary atherosclerosis. In brief, we used the GSE132651 dataset from the gene expression omnibus database. The top 5000 genes with greatest variances were used for weighted gene co-expression network analysis, and the module most strongly correlated with abnormal coronary endothelial function was chosen as key module. Functional enrichment analysis was performed for genes in the key module, a protein-protein interaction network was constructed to find hub genes, and gene set enrichment analysis (GSEA) was also performed. Genes were classified into 7 modules, with the midnightblue module being the one that was most related to abnormal coronary endothelial function and containing genes enriched in DNA replication, cell cycle, nucleotide excision repair, and Human T-cell leukemia virus 1 infection. We identified nine hub genes (HOXC5, PRND, PADI3, RC3H1, DAPP1, SIT1, DRICH1, GPRIN2, and RHO), which differently expressed in abnormal and normal coronary endothelial function samples. GSEA suggested that samples associated with abnormal coronary endothelial function and highly expressed hub genes were linked with immune, coagulation, hypoxia, and angiogenesis processes. These hub genes, their expression pattern, and pathways may be involved in the development of abnormal coronary endothelial function and promotion of early coronary atherosclerosis.