Biomarkers and Disease Trajectories Influencing Women's Health: Results from the UK Biobank Cohort

Exploring beyond diagnoses in electronic health records to improve discovery: a review of the phenome-wide association study

Objective

The phenome-wide association study (PheWAS) systematically examines the phenotypic spectrum extracted from electronic health records (EHRs) to uncover correlations between phenotypes and exposures. This review explores methodologies, highlights challenges, and outlines future directions for EHR-driven PheWAS.

Materials and Methods

We searched the PubMed database for articles spanning from 2010 to 2023, and we collected data regarding exposures, phenotypes, cohorts, terminologies, replication, and ancestry.

Results

Our search yielded 690 articles. Following exclusion criteria, we identified 291 articles published between January 1, 2010, and December 31, 2023. A total number of 162 (55.6%) articles defined phenomes using phecodes, indicating that research is reliant on the organization of billing codes. Moreover, 72.8% of articles utilized exposures consisting of genetic data, and the majority (69.4%) of PheWAS lacked replication analyses.

Discussion

Existing literature underscores the need for deeper phenotyping, variability in PheWAS exposure variables, and absence of replication in PheWAS. Current applications of PheWAS mainly focus on cardiovascular, metabolic, and endocrine phenotypes; thus, applications of PheWAS in uncommon diseases, which may lack structured data, remain largely understudied.

Conclusions

With modern EHRs, future PheWAS should extend beyond diagnosis codes and consider additional data like clinical notes or medications to create comprehensive phenotype profiles that consider severity, temporality, risk, and ancestry. Furthermore, data interoperability initiatives may help mitigate the paucity of PheWAS replication analyses. With the growing availability of data in EHR, PheWAS will remain a powerful tool in precision medicine.

Associations of parity and cognitive decline, depression, and chronic comorbidity in West China: Results from WCHAT study

OBJECTIVE

To investigate the associations between parity (the number of offspring a female has borne) and cognitive function, depression, and chronic comorbidity in Western China.

METHODS

A total of 846 women aged 50-55 years were included in the current analysis. Cognitive status was measured using a 10-item short portable mental status questionnaire (SPMSQ). Depressive symptoms were assessed using the 15-item geriatric depression scale (GDS-15). Other characteristics were self-reported. The associations between parity and cognitive decline, depression, and chronic comorbidity were analyzed using univariable and multivariable models. Multivariable models were adjusted for age, ethnic group, occupation, marital status, educational level, lifestyle factors, and sleeping time.

RESULTS

Among the enrolled women, 26.71% were either childless or had one child, 47.40% had two children, 18.32% had three children, and 7.57% had ≥4 children. Compared to women with low parity, women with two or more children exhibited a higher risk of cognitive decline. Moreover, having four or more children was significantly associated with depression and chronic comorbidity. After adjusting covariates, women with three or more children exhibited a higher risk of cognitive decline than those with low parity. However, high parity was not significantly associated with depression or chronic comorbidity after adjustment for covariates.

CONCLUSION

Our study showed that ≥3 children was associated with cognitive decline in women. Longitudinal studies are needed to evaluate this conclusion and to investigate the mechanisms involved. More importantly, families and societies should pay more attention to women's long-term health outcomes related to fertility.

Proteogenomic Landscape of Breast Ductal Carcinoma Reveals Tumor Progression Characteristics and Therapeutic Targets

Multi-omics studies of breast ductal carcinoma (BRDC) have advanced the understanding of the disease's biology and accelerated targeted therapies. However, the temporal order of a series of biological events in the progression of BRDC is still poorly understood. A comprehensive proteogenomic analysis of 224 samples from 168 patients with malignant and benign breast diseases is carried out. Proteogenomic analysis reveals the characteristics of linear multi-step progression of BRDC, such as tumor protein P53 (TP53) mutation-associated estrogen receptor 1 (ESR1) overexpression is involved in the transition from ductal hyperplasia (DH) to ductal carcinoma in situ (DCIS). 6q21 amplification-associated nuclear receptor subfamily 3 group C member 1 (NR3C1) overexpression helps DCIS_Pure (pure DCIS, no histologic evidence of invasion) cells avoid immune destruction. The T-cell lymphoma invasion and metastasis 1, androgen receptor, and aldo-keto reductase family 1 member C1 (TIAM1-AR-AKR1C1) axis promotes cell invasion and migration in DCIS_adjIDC (DCIS regions of invasive cancers). In addition, AKR1C1 is identified as a potential therapeutic target and demonstrated the inhibitory effect of aspirin and dydrogesterone as its inhibitors on tumor cells. The integrative multi-omics analysis helps to understand the progression of BRDC and provides an opportunity to treat BRDC in different stages.

Investigating PPT2's role in ovarian cancer prognosis and immunotherapy outcomes

Ovarian cancer (OC) remains the primary cause of mortality among gynecological malignancies, and the identification of reliable molecular biomarkers to prognosticate OC outcomes is yet to be achieved. The gene palmitoyl protein thioesterase 2 (PPT2), which has been sparsely studied in OC, was closely associated with metabolism. This study aimed to determine the association between PPT2 expression, prognosis, immune infiltration, and potential molecular mechanisms in OC. We obtained the RNA-seq and clinical data from The Cancer Genome Atlas (TCGA), The Genotype-Tissue Expression (GTEx) and Gene Expression Omnibus (GEO) databases, then Kaplan-Meier analysis, univariate Cox regression, multivariate Cox regression, nomogram, and calibration were conducted to assess and verify the role of PPT2. Gene set enrichment analysis (GSEA) was used to figure out the closely correlated pathways with PPT2. Overexpression experiment was performed to explore the function of PPT2. Our findings showed that PPT2 mRNA expression was apparent down-regulation in OC tissue compared to normal ovarian tissues in TCGA, GTEx datasets, and GEO datasets. This differential expression was also confirmed in our in-house datasets at both the mRNA and protein levels. Decreased PPT2 expression correlated with lower survival rates in TCGA, several GEO datasets, and our in-house datasets. Multivariate analysis revealed that PPT2 was an independent factor in predicting better outcomes for OC patients in TCGA and GEO. A negative correlation was revealed between immune infiltration and PPT2 expression through Single-sample GSEA (ssGSEA). Additionally, PPT2 was negatively correlated with an up-regulated immune score, stromal score, and estimate score, suggesting that patients with low PPT2 expression might benefit more from immunotherapy. Numerous chemical agents showed lower IC50 in patients with high PPT2 expression. In single-cell RNA sequencing (scRNA-seq) analysis of several OC datasets, we found PPT2 was mainly expressed in endothelial cells. Furthermore, we found that PPT2 inhibited OC cell proliferation in vitro. Our results demonstrated that PPT2 was considered a favorable prognostic biomarker for OC and may be vital in predicting response to immunotherapy and chemotherapy. Further research was needed to fully understand the relationship between PPT2 and immunotherapy efficacy in OC patients.

Disease Trajectories from Healthcare Data: Methodologies, Key Results, and Future Perspectives

Disease trajectories, defined as sequential, directional disease associations, have become an intense research field driven by the availability of electronic population-wide healthcare data and sufficient computational power. Here, we provide an overview of disease trajectory studies with a focus on European work, including ontologies used as well as computational methodologies for the construction of disease trajectories. We also discuss different applications of disease trajectories from descriptive risk identification to disease progression, patient stratification, and personalized predictions using machine learning. We describe challenges and opportunities in the area that eventually will benefit from initiatives such as the European Health Data Space, which, with time, will make it possible to analyze data from cohorts comprising hundreds of millions of patients.

ECM1 and ANXA1 in urinary extracellular vesicles serve as biomarkers for breast cancer

Objective

Although urinary extracellular vesicles (uEVs) have been extensively studied in various cancers, their involvement in breast cancer (BC) remains largely unexplored. The non-invasive nature of urine as a biofluid and its abundant protein content offer considerable potential for the early detection of breast cancer.

Methods

This study analyzed the proteomic profiles of uEVs from BC patients and healthy controls (HC). The dysregulation of ECM1 and ANXA1 in the uEVs was validated in a larger cohort of 128 BC patients, 25 HC and 25 benign breast nodules (BBN) by chemiluminescence assay (CLIA). The expression levels of ECM1 and ANXA1 were also confirmed in the uEVs of MMTV-PyMT transgenic breast cancer mouse models.

Results

LC-MS/MS analysis identified 571 dysregulated proteins in the uEVs of BC patients. ECM1 and ANXA1 were selected for validation in 128 BC patients, 25 HC and 25 BBN using CLIA, as their fold change showed a significant difference of more than 10 with p-value<0.05. Protein levels of ECM1 and ANXA1 in uEVs were significantly increased in BC patients. In addition, the protein levels of ECM1 and ANXA1 in the uEVs of MMTV-PyMT transgenic mice were observed to increase progressively with the progression of breast cancer.

Conclusion

We developed a simple and purification-free assay platform to isolate uEVs and quantitatively detect ECM1 and ANXA1 in uEVs by WGA-coupled magnetic beads and CLIA. Our results suggest that ECM1 and ANXA1 in uEVs could potentially serve as diagnostic biomarkers for breast cancer.

The interaction of diet, alcohol, genetic predisposition, and the risk of breast cancer: a cohort study from the UK Biobank

BACKGROUND

Dietary factors have consistently been associated with breast cancer risk. However, there is limited evidence regarding their associations in women with different genetic susceptibility to breast cancer, and their interaction with alcohol consumption is also not well understood.

METHODS

We analyzed data from 261,853 female participants in the UK Biobank. Multivariable adjusted Cox proportional hazards models were used to estimate hazard ratios (HR) and 95% confidence intervals (CI) for associations between dietary factors and breast cancer risk. Additionally, we assessed the interaction of dietary factors with alcohol consumption and polygenic risk score (PRS) for breast cancer.

RESULTS

A moderately higher risk of breast cancer was associated with the consumption of processed meat (HR = 1.10, 95% CI 1.03, 1.18, p-trend = 0.016). Higher intake of raw vegetables and fresh fruits, and adherence to a healthy dietary pattern were inversely associated with breast cancer risk [HR (95% CI):0.93 (0.88-0.99), 0.87 (0.81, 0.93) and 0.93 (0.86-1.00), p for trend: 0.025, < 0.001, and 0.041, respectively]. Furthermore, a borderline significant interaction was found between alcohol consumption and the intake of processed meat with regard to breast cancer risk (P for interaction = 0.065). No multiplicative interaction was observed between dietary factors and PRS.

CONCLUSION

Processed meat was positively associated with breast cancer risk, and vegetables, fruits, and healthy dietary patterns were negatively associated with breast cancer risk. We found no strong interaction of dietary factors with alcohol consumption and genetic predisposition for risk of breast cancer.

MALAT1 expression in granulosa cells in PCOS patients with different phenotypes

Polycystic ovary syndrome (PCOS) is one of the most common reproductive endocrine metabolic disorders. The lncRNA metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) reportedly can regulate the reproductive system. Despite studies, the alteration of MALAT1 expression in granulosa cells (GCs) from PCOS patients was inconsistent. To evaluate MALAT1 expression in GCs in different PCOS subgroups and its association with PCOS phenotypes, we collected GCs from 110 PCOS cases and 71 controls, and examined MALAT1 expression by quantitative PCR. The results showed MALAT1 expression was upregulated in PCOS cases, especially in insulin resistant (IR) PCOS subgroup, obese PCOS subgroup and non-hyperandrogenic (NHA) PCOS subgroup. MALAT1 expression was positively correlated with BMI and several metabolic parameters in controls. Interestingly, MALAT1 expression was notably associated with some critical endocrine indexes for PCOS, including E2, FSH, LH and LH/FSH ratio. In different PCOS subgroups, we found significant positive correlations with LH/FSH ratio in IR-PCOS and PCOS with normal weight, and with serum T and LH level in NHA-PCOS subgroup. Integrated analysis with lncRNA target databases and PCOS-related databases revealed MALAT1 could participate in PCOS by influencing immune response and lipids metabolism in GCs. In conclusion, MALAT1 was differently expressed in GCs in PCOS, especially in IR, obese and NHA PCOS subgroups. MALAT1 was likely involved in metabolism and immune response in GCs in PCOS. However, more studies are necessary to establish this concept.

High-fat and high-sucrose diet impairs female reproduction by altering ovarian transcriptomic and metabolic signatures

BACKGROUND

Excessive energy intake in modern society has led to an epidemic surge in metabolic diseases, such as obesity and type 2 diabetes, posing profound threats to women's reproductive health. However, the precise impact and underlying pathogenesis of energy excess on female reproduction remain unclear.

METHODS

We established an obese and hyperglycemic female mouse model induced by a high-fat and high-sucrose (HFHS) diet, then reproductive phenotypes of these mice were evaluated by examing sexual hormones, estrous cycles, and ovarian morphologies. Transcriptomic and precise metabolomic analyses of the ovaries were performed to compare the molecular and metabolic changes in HFHS mice. Finally, orthogonal partial least squares discriminant analysis was performed to compare the similarities of traits between HFHS mice and women with polycystic ovary syndrome (PCOS).

RESULTS

The HFHS mice displayed marked reproductive dysfunctions, including elevated serum testosterone and luteinizing hormone levels, irregular estrous cycles, and impaired folliculogenesis, mimicking the clinical manifestations of women with PCOS. Precise metabolomic overview suggested that HFHS diet disrupted amino acid metabolism in the ovaries of female mice. Additionally, transcriptional profiling revealed pronounced disturbances in ovarian steroid hormone biosynthesis and glucolipid metabolism in HFHS mice. Further multi-omics analyses unveiled prominent aberration in ovarian arginine biosynthesis pathway. Notably, comparisons between HFHS mice and a cohort of PCOS patients identified analogous reproductive and metabolic signatures.

CONCLUSIONS

Our results provide direct in vivo evidence for the detrimental effects of overnutrition on female reproduction and offer insights into the metabolic underpinnings of PCOS.

Hematological and biochemical markers influencing breast cancer risk and mortality: Prospective cohort study in the UK Biobank by multi-state models

BACKGROUND

Breast cancer is the most common cancer and the leading cause of cancer-related death among women. However, evidence concerning hematological and biochemical markers influencing the natural history of breast cancer from in situ breast cancer to mortality is limited.

METHODS

In the UK Biobank cohort, 260,079 women were enrolled during 2006-2010 and were followed up until 2019 to test the 59 hematological and biochemical markers associated with breast cancer risk and mortality. The strengths of these associations were evaluated using the multivariable Cox regression models. To understand the natural history of breast cancer, multi-state survival models were further applied to examine the effects of biomarkers on transitions between different states of breast cancer.

RESULTS

Eleven biomarkers were found to be significantly associated with the risk of invasive breast cancer, including mainly inflammatory-related biomarkers and endogenous hormones, while serum testosterone was also associated with the risk of in-situ breast cancer. Among them, C-reactive protein (CRP) was more likely to be associated with invasive breast cancer and its transition to death from breast cancer (HR for the highest quartile = 1.46, 95 % CI = 1.07-1.97), while testosterone and insulin-like growth factor-1 (IGF-1) were more likely to impact the early state of breast cancer development (Testosterone: HR for the highest quartile = 1.31, 95 % CI = 1.12-1.53; IGF-1: HR for the highest quartile = 1.17, 95 % CI = 1.00-1.38).

CONCLUSION

Serum CRP, testosterone, and IGF-1 have different impacts on the transitions of different breast cancer states, confirming the role of chronic inflammation and endogenous hormones in breast cancer progression. This study further highlights the need of closer surveillance for these biomarkers during the breast cancer development course.

The interaction between systemic inflammatory markers and polygenic risk score in breast cancer risk: A cohort study in the UK Biobank

BACKGROUND

Systemic inflammatory markers have been widely used in cancer prognosis prediction recently. However, there is limited knowledge regarding their impact on breast cancer risk and their interaction with polygenic risk scores.

METHODS

A cohort study of 202,403 female participants from the UK Biobank were analyzed to estimate the hazard ratio (HR) for the incidence and mortality of breast cancer based on inflammatory markers using Cox regression models. Additionally, we stratified the analysis by polygenic risk scores (PRS) for breast cancer, and examined the interaction between these markers and PRS through likelihood ratio tests and relative excess risk due to interaction (RERI).

RESULTS

Women in the highest tertile of neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), and C-reactive protein (CRP) showed an increased risk of breast cancer [HR (95 %CI) = 1.10 (1.02-1.18), 1.09 (1.01-1.17) and 1.15 (1.05-1.25), respectively], as compared to those in the lowest tertile. Regarding breast cancer mortality, only NLR and CRP exhibited consistent results in the univariate model [HR (95 %CI) = 1.25 (0.99-1.58) and 1.39 (1.10-1.77), respectively]. When stratified by PRS, stronger associations between inflammatory markers and breast cancer risk were observed in the high PRS group. Furthermore, there was a significant additive interaction between CRP and PRS [RERI (95 % CI) = 0.30 (0.06-0.53)].

CONCLUSION

NLR and CRP are associated with breast cancer risk and mortality, and the effect of CRP is influenced by PRS. Systematic inflammatory markers, together with PRS, might be applied in combined screening for breast cancer.

Investigation of androgen receptor CAG repeats length in polycystic ovary syndrome diagnosed using the new international evidence-based guideline

BACKGROUND

To study whether CAG repeat polymorphism of androgen receptor (AR) contributes to the risk of polycystic ovarian morphology (PCOM) with antral follicle count (AFC) ≥ 20 in the context of new international guideline of polycystic ovary syndrome (PCOS).

METHODS

Blood of 109 PCOS cases and 61 controls were collected for the measurement of AR CAG repeats length by sequencing. The mean number and frequency distribution of CAG repeats length were observed. Detailed analysis was conducted by dividing PCOS cases into low AFC group (L-AFC, AFC < 20) and high AFC group (H-AFC, AFC ≥ 20) according to the new international evidence-based guideline.

RESULTS

The portion of individuals with lower CAG repeats length in H-AFC group was significantly larger than those with higher CAG repeats length. Logistic model revealed individuals with lower CAG length tended to develop H-AFC.

CONCLUSION

Lower CAG repeats length in the AR gene of PCOS cases increases risk of PCOM.

Phenomic Studies on Diseases: Potential and Challenges

The rapid development of such research field as multi-omics and artificial intelligence (AI) has made it possible to acquire and analyze the multi-dimensional big data of human phenomes. Increasing evidence has indicated that phenomics can provide a revolutionary strategy and approach for discovering new risk factors, diagnostic biomarkers and precision therapies of diseases, which holds profound advantages over conventional approaches for realizing precision medicine: first, the big data of patients' phenomes can provide remarkably richer information than that of the genomes; second, phenomic studies on diseases may expose the correlations among cross-scale and multi-dimensional phenomic parameters as well as the mechanisms underlying the correlations; and third, phenomics-based studies are big data-driven studies, which can significantly enhance the possibility and efficiency for generating novel discoveries. However, phenomic studies on human diseases are still in early developmental stage, which are facing multiple major challenges and tasks: first, there is significant deficiency in analytical and modeling approaches for analyzing the multi-dimensional data of human phenomes; second, it is crucial to establish universal standards for acquirement and management of phenomic data of patients; third, new methods and devices for acquirement of phenomic data of patients under clinical settings should be developed; fourth, it is of significance to establish the regulatory and ethical guidelines for phenomic studies on diseases; and fifth, it is important to develop effective international cooperation. It is expected that phenomic studies on diseases would profoundly and comprehensively enhance our capacity in prevention, diagnosis and treatment of diseases.

Comparison of Pairwise Venous and Fingertip Plasma Using Quantitative Proteomics Based on Data-Independent Acquisition

Blood contains a great deal of health-related information and can be used to monitor human health status. Clinically, venous or fingertip blood is usually used for blood tests. However, the clinical application settings of the two sources of blood are unclear. In this study, the proteomes of pairwise venous plasma (VP) and fingertip plasma (FP) were analyzed, and the levels of 3797 proteins were compared between VP and FP. The Spearman's correlation coefficient for the relationship between protein levels of VP and FP ranges from 0.64 to 0.78 (p < 0.0001). The common pathways of VP and FP are related to cell-cell adhesion, protein stabilization, innate immune response, and complement activation, the classical pathway. The VP-overrepresented pathway is related to actin filament organization, while the FP-overrepresented pathway is related to the hydrogen peroxide catabolic process. ADAMTSL4, ADIPOQ, HIBADH, and XPO5 both in VP and FP are potential gender-related proteins. Notably, the VP proteome has a higher interpretation on age than the FP proteome, and CD14 is a potential age-related protein in VP but not in FP. Our study mapped the different proteomes between VP and FP, which can provide value for the standardization of clinical blood tests.

Women at heart: Introducing gender cardio-oncology

As cardio-oncology imposed itself as the reference specialty for a comprehensive cardiovascular approach to all patients with cancer, a more specific and careful cardiac evaluation of women entering their journey into cancer care is needed. Gender medicine refers to the study of how sex-based biological and gender-based socioeconomic and cultural differences influence people's health. Gender-related aspects could account for differences in the development, progression, and clinical signs of diseases as well as in the treatment of adverse events. Gender also accounts for major differences in access to healthcare. As for medicine and healthcare in general, gender-related characteristics have gained significance in cardio-oncology and should no longer be neglected in both clinical practice and research. We aimed to review the most relevant cardiovascular issues in women related to the cardio-oncology approach to offer a specific gender-related point of view for clinicians involved in the care process for both cancer and cardiovascular disease.