1. Introduction

Lipidomics, the comprehensive profiling of molecular lipid species in biological systems, has rapidly transitioned from a niche analytical approach into an indispensable clinical tool. By elucidating intricate networks of lipid metabolism, signal transduction, and intercellular communication, it links discrete biochemical alterations to the underlying pathogenesis of complex human diseases. This review synthesizes recent advances in clinical lipidomics, focusing on state-of-the-art analytical technologies, including mass spectrometry-based workflows, and their application in biomarker discovery. We explore the translation of lipidomic profiling across diverse pathological conditions, encompassing cardiometabolic diseases, inflammatory skin and bowel disorders, metabolic and psychiatric conditions, as well as oncology and women’s health. Furthermore, we discuss the technological challenges of standardization, data processing, and the integration of lipidomics with other omics disciplines to accelerate the transition toward precision medicine in clinical practice.

Lipids are fundamental biological molecules that play essential roles in energy storage, membrane structure, and cellular signaling. The dysregulation of lipid metabolism is intrinsically linked to the pathophysiology of numerous diseases, making the comprehensive study of lipids (termed lipidomics) a rapidly expanding field in biomedical research ^[1][2]. Conventional clinical lipid panels remain largely restricted to macroscopic parameters, namely total triglycerides, total cholesterol, high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C). Although foundational for routine cardiovascular risk stratification, these standard biomarkers lack the molecular granularity required to capture the immense structural and functional diversity of the human lipidome ^[2].

Clinical lipidomics is an emerging subfield that focuses on the qualitative and quantitative analysis of individual lipid species in clinical samples to understand disease mechanisms, identify novel biomarkers, and develop targeted therapeutic strategies ^[3]. Advanced analytical platforms, particularly high-resolution mass spectrometry (HRMS) coupled with liquid chromatography (LC-MS), have enabled the identification of thousands of molecular lipid species from limited biological matrices ^[3][4]. However, the inherent structural diversity of lipids presents significant analytical challenges, particularly in method standardization and cross-study comparison ^[1]. This review aims to provide a comprehensive overview of recent methodological advancements in lipidomics and their translational applications across various clinical disciplines, highlighting the potential of clinical lipidomics to revolutionize diagnostic and therapeutic paradigms.

2. Analytical Techniques and Workflows

The successful implementation of clinical lipidomics relies on robust analytical workflows, encompassing sample collection, lipid extraction, mass spectrometry data acquisition, and sophisticated bioinformatics analysis ^[4]. The selection of an optimal analytical strategy remains pivotal, encompassing untargeted, targeted, and pseudo-targeted modalities ^[5].

Untargeted lipidomics, often utilizing HRMS systems such as quadrupole time-of-flight (Q-TOF) or Orbitrap analyzers, provides an unbiased global profile of lipids in a sample, making it ideal for biomarker discovery ^[5]. Conversely, targeted lipidomics employs low-resolution mass spectrometry (LRMS), typically using multiple reaction monitoring (MRM) on triple quadrupole instruments, to achieve high sensitivity and specificity for quantifying a predefined set of known lipids ^[6]. Pseudo-targeted lipidomics serves as an effective hybrid approach that integrates the strengths of both strategies, offering high coverage and accurate quantification of a wider array of lipid species ^[5].

Sample preparation and extraction constitute pivotal determinants of data fidelity. Although conventional liquid-liquid extraction strategies, such as the Folch and Bligh & Dyer protocols, remain benchmark methodologies, high-throughput research increasingly favors eco-friendly, automated alternatives – such as methyl tert-butyl ether (MTBE) or butanol/methanol (BUME) extractions – to mitigate solvent toxicity and streamline processing ^[7]. Furthermore, the integration of bioinformatics tools – including R and Python libraries, and databases like LIPID MAPS – is essential for processing complex datasets and extracting biologically meaningful information from large-scale studies ^[4]. Data normalization, transformation, and batch effect correction are particularly crucial in clinical settings to ensure reproducibility and reliability ^[4].

3. Lipidomics in Cardiometabolic Diseases

Cardiometabolic diseases, including atherosclerosis, type 2 diabetes, and metabolic syndrome, represent a major global health burden. Lipidomics has provided profound insights into the metabolic perturbations underlying these conditions. In atherosclerosis, detailed lipid profiling has revealed the critical role of specific lipid classes, such as ceramides and sphingolipids, in plaque development and instability ^[8]. For instance, ceramide and phospholipid-based risk scores have shown promise in predicting cardiovascular events beyond traditional risk factors ^[9].

Lipid homeostasis is closely governed by endocrine mechanisms. Specifically, thyroid hormones orchestrate lipid biosynthesis, mobilization, and catabolism, with overt hypothyroidism characteristically precipitating systemic elevations in total cholesterol, LDL-C, and circulating triglycerides ^[10]. Even subtle variations in thyroid-stimulating hormone (TSH) levels within the reference range have been associated with unfavorable lipid profiles ^[10]. Furthermore, circadian rhythms exert substantial control over lipid homeostasis. The molecular clocks regulate lipid digestion, absorption, and intracellular metabolism, with disruptions in circadian alignment linked to metabolic disorders and dyslipidemia ^[11]. In the context of drug discovery, understanding these metabolic shifts is critical. For example, PCSK9 inhibition, a major therapeutic strategy for lowering LDL-C, has been shown to significantly alter the plasma lipidome, notably reducing sphingolipids and ceramides, which may contribute to its atheroprotective effects ^[9].

4. Lipidomics in Inflammatory and Immune-Mediated Diseases

Lipidomics is transforming our understanding of chronic inflammatory conditions. In psoriasis, a systemic autoinflammatory disease, alterations in lipid metabolism contribute significantly to the disruption of the skin barrier and systemic inflammation. The disease is characterized by reduced total ceramide levels, altered ceramide profiles (e.g., decreased Cer[NP] and increased Cer[NS]), and changes in fatty acid composition, including elevated saturated and omega-6 fatty acids and reduced omega-3 fatty acids ^[12]. Additionally, pro-inflammatory lipid mediators such as leukotrienes and prostanoids play a crucial role in disease progression ^[12].

In inflammatory bowel disease (IBD) – comprising Crohn's disease and ulcerative colitis – lipidomic profiling has unraveled distinct metabolic signatures. Comprehensive lipid analyses reveal pronounced perturbations across glycerophospholipids (notably phosphatidylcholines and lysophosphatidylcholines), free fatty acids, and bioactive sphingolipids, highlighting their utility as candidate diagnostic and prognostic biomarkers ^[13]. Similarly, in celiac disease, metabolomic and lipidomic studies have revealed disturbances linked to gut microflora alterations, malabsorption, and increased intestinal permeability, providing a basis for novel diagnostic approaches ^[14].

5. Lipidomics in Oncology and Drug Discovery

Cancer cells exhibit profound metabolic reprogramming, with altered lipid metabolism being a hallmark of malignancy. In glioblastoma (GBM), these aggressive brain tumors depend heavily on de novo lipogenesis, fatty acid oxidation, and lipid droplet accumulation to support rapid growth and survival ^[15]. Lipidomics is crucial for identifying lipid-based biomarkers for early diagnosis and developing novel therapeutic strategies. The integration of lipidomics with drug discovery has led to the concept of multi-target directed ligands (MTDLs), which can simultaneously target multiple lipid metabolic pathways to overcome therapeutic resistance ^[15].

Across oncology, lipidomics offers a powerful tool for biomarker discovery, enabling the detection of disease-specific lipid signatures in biofluids ^[6]. Furthermore, its application extends to drug development, where it aids in understanding mechanisms of action, target engagement, and the metabolic impact of therapeutic interventions ^[6]. The integration of lipidomics with advanced drug delivery systems, such as lipid-based nanoparticles, holds promise for improving the specificity and efficacy of cancer therapies ^[15].

6. Lipidomics in Psychiatry and Mental Health

Emerging evidence highlights the critical role of lipid metabolism in mental health disorders, including major depressive disorder (MDD), bipolar disorder (BD), schizophrenia (SCZ), and obsessive-compulsive disorder (OCD) ^[16]. Shared genetic and lipidomic patterns suggest common pathophysiological pathways involving inflammation, lipid metabolism, and mitochondrial function. For example, alterations in polyunsaturated fatty acids (PUFAs), high-density lipoproteins, and arachidonic acid have been implicated in the underlying biology of these disorders ^[16].

Additionally, psychopharmacological regimens, most notably second-generation antipsychotics, frequently trigger profound metabolic dysregulation. Integrated metabolomic and lipidomic analyses of patient cohorts have systematically documented post-treatment shifts, characterized by marked enrichments in phosphatidylcholines juxtaposed with depletions in specific amino acids and acylcarnitine species ^[17]. These findings underscore the potential of lipidomics not only to elucidate disease mechanisms, but also to monitor treatment efficacy and predict adverse metabolic outcomes, facilitating a move toward precision psychiatry ^[16].

7. Lipidomics in Women's Health and Reproductive Medicine

Lipidomics has significant implications for women's health, offering new avenues for diagnosis and treatment in gynecological diseases ^[1]. In ovarian and cervical cancers, specific lipid alterations, including changes in phosphatidylcholines, lysophosphatidylcholines, and ceramides, have been identified as potential diagnostic biomarkers ^[3]. Endometriosis, a chronic inflammatory condition, is associated with characteristic disturbances in phospholipid and sphingolipid metabolism, which may contribute to lesion establishment and maintenance ^[1][3].

Lipid metabolism also plays an indispensable role in endometrial receptivity and embryo implantation. Key lipid-derived mediators, such as prostaglandins, endocannabinoids, and lysophosphatidic acid, are crucial for successful implantation and decidualization ^[18]. Cholesterol serves as a precursor for steroid hormones, and fluctuations in serum lipid profiles during the menstrual cycle reflect the metabolic demands of preparing the endometrium for pregnancy ^[18]. Additionally, lipidomics is instrumental in assessing the functional lipid composition of breast milk, which is vital for infant development. Functional lipids, including medium-chain triglycerides, phospholipids, and sphingolipids, confer significant health benefits and support the immune and neurological development of newborns ^[1].

8. Emerging Applications and Challenges

Beyond traditional human diseases, lipidomics is finding applications in diverse fields. In the meat industry, advanced lipidomic profiling is used for quality traceability, authentication, and nutritional assessment, ensuring food safety and public health ^[19]. In conditions like lipedema, an adipofascial disorder, lipidomic and metabolomic profiling suggest distinct pathological mechanisms compared to obesity and lymphedema, offering potential for new diagnostic biomarkers ^[20].

Despite its transformative potential, the clinical translation of lipidomics is fundamentally constrained by pre-analytical variability, a lack of standardized protocols for sample collection and data processing, and limited cross-platform comparability ^[1][21]. Establishing consensus guidelines and rigorous protocol standardization across the entire analytical workflow is therefore essential to ensure inter-study reproducibility and enable widespread clinical adoption ^[1][21]. Translating high-dimensional lipidomic datasets into actionable clinical knowledge demands robust bioinformatics pipelines alongside specialized computational expertise ^[4]. Crucially, before candidate lipid biomarkers can be integrated into routine diagnostics, their broad clinical utility must be rigorously validated through prospective, multi-center trials ^[3]. The integration of lipidomics with other omics disciplines, such as genomics, transcriptomics, and proteomics, will be essential to gain a holistic understanding of disease pathophysiology and advance precision medicine ^[3].

9. Conclusions

Clinical lipidomics has emerged as a transformative technology, offering unprecedented insights into the molecular basis of health and disease. By moving beyond traditional lipid measurements to comprehensive profiling, it has the potential to redefine diagnostic paradigms, identify novel therapeutic targets, and facilitate personalized medicine. The application of lipidomics across cardiometabolic, inflammatory, oncological, psychiatric, and gynecological diseases underscores its broad relevance. As analytical technologies continue to advance and standardization efforts mature, lipidomics holds immense promise for improving patient outcomes and reshaping clinical practice.

This entry is adapted from: https://doi.org/10.20944/preprints202608.0900.v1