Metabonomic analysis of seminal plasma in necrozoospermia patients based on liquid chromatography-mass spectrometry

Lipidomics random forest algorithm of seminal plasma is a promising method for enhancing the diagnosis of necrozoospermia

BACKGROUND

Despite the clear clinical diagnostic criteria for necrozoospermia in andrology, the fundamental mechanisms underlying it remain elusive. This study aims to profile the lipid composition in seminal plasma systematically and to ascertain the potential of lipid biomarkers in the accurate diagnosis of necrozoospermia. It also evaluates the efficacy of a lipidomics-based random forest algorithm model in identifying necrozoospermia.

METHODS

Seminal plasma samples were collected from patients diagnosed with necrozoospermia (n = 28) and normozoospermia (n = 28). Liquid chromatography-mass spectrometry (LC-MS) was used to perform lipidomic analysis and identify the underlying biomarkers. A lipid functional enrichment analysis was conducted using the LION lipid ontology database. The top 100 differentially significant lipids were subjected to lipid biomarker examination through random forest machine learning model.

RESULTS

Lipidomic analysis identified 46 lipid classes comprising 1267 lipid metabolites in seminal plasma. The top five enriched lipid functions as follows: fatty acid (FA) with ≤ 18 carbons, FA with 16-18 carbons, monounsaturated FA, FA with 18 carbons, and FA with 16 carbons. The top 100 differentially significant lipids were subjected to machine learning analysis and identified 20 feature lipids. The random forest model identified lipids with an area under the curve > 0.8, including LPE(20:4) and TG(4:0_14:1_16:0).

CONCLUSIONS

LPE(20:4) and TG(4:0_14:1_16:0), were identified as differential lipids for necrozoospermia. Seminal plasma lipidomic analysis could provide valuable biochemical information for the diagnosis of necrozoospermia, and its combination with conventional sperm analysis may improve the accuracy and reliability of the diagnosis.

Secondary infertility due to necrospermia in men with autosomal-dominant polycystic kidney disease: a report of two cases

Autosomal-dominant polycystic kidney disease (ADPKD) is the most common inherited kidney disease characterized by the formation of numerous cysts in organs other than the kidneys. Although female patients with ADPKD do not have direct fertility problems, infertility in male patients may arise following the formation of cystic lesions in the lower seminal tract, which impair the function of spermatozoa. Generally, the treatment strategy for necrospermia depends on the severity of sperm viability, and intracytoplasmic sperm injection may be offered to patients with necrospermia. We report two cases of secondary infertility in men with ADPKD. These men experienced an inability to reproduce naturally after the previous birth of a child, suggesting a progressive deterioration of semen quality. Semen analysis showed necrospermia in both patients, and transrectal ultrasound revealed marked dilatation of the seminal vesicles bilaterally. The main cause of secondary infertility in male patients with ADPKD is sperm death resulting from progressive dilatation of seminal vesicles. Further research is needed on the appropriate follow-up schedule for men with ADPKD who desire to reproduce naturally.

Critical Factors in Sample Collection and Preparation for Clinical Metabolomics of Underexplored Biological Specimens

This review article compiles critical pre-analytical factors for sample collection and extraction of eight uncommon or underexplored biological specimens (human breast milk, ocular fluids, sebum, seminal plasma, sweat, hair, saliva, and cerebrospinal fluid) under the perspective of clinical metabolomics. These samples are interesting for metabolomics studies as they reflect the status of living organisms and can be applied for diagnostic purposes and biomarker discovery. Pre-collection and collection procedures are critical, requiring protocols to be standardized to avoid contamination and bias. Such procedures must consider cleaning the collection area, sample stimulation, diet, and food and drug intake, among other factors that impact the lack of homogeneity of the sample group. Precipitation of proteins and removal of salts and cell debris are the most used sample preparation procedures. This review intends to provide a global view of the practical aspects that most impact results, serving as a starting point for the designing of metabolomic experiments.