Prediction and causal inference of cardiovascular and cerebrovascular diseases based on lifestyle questionnaires.

Cardiovascular and cerebrovascular diseases (CCVD) are prominent mortality causes in Japan, necessitating effective preventative measures, early diagnosis, and treatment to mitigate their impact. A diagnostic model was developed to identify patients with ischemic heart disease (IHD), stroke, or both, using specific health examination data. Lifestyle habits affecting CCVD development were analyzed using five causal inference methods. This study included 473,734 patients aged ≥ 40 years who underwent specific health examinations in Kanazawa, Japan between 2009 and 2018 to collect data on basic physical information, lifestyle habits, and laboratory parameters such as diabetes, lipid metabolism, renal function, and liver function. Four machine learning algorithms were used: Random Forest, Logistic regression, Light Gradient Boosting Machine, and eXtreme-Gradient-Boosting (XGBoost). The XGBoost model exhibited superior area under the curve (AUC), with mean values of 0.770 (± 0.003), 0.758 (± 0.003), and 0.845 (± 0.005) for stroke, IHD, and CCVD, respectively. The results of the five causal inference analyses were summarized, and lifestyle behavior changes were observed after the onset of CCVD. A causal relationship from 'reduced mastication' to 'weight gain' was found for all causal species theory methods. This prediction algorithm can screen for asymptomatic myocardial ischemia and stroke. By selecting high-risk patients suspected of having CCVD, resources can be used more efficiently for secondary testing.

Prediction and causal inference of hyperuricemia using gut microbiota.

Hyperuricemia (HUA) is a symptom of high blood uric acid (UA) levels, which causes disorders such as gout and renal urinary calculus. Prolonged HUA is often associated with hypertension, atherosclerosis, diabetes mellitus, and chronic kidney disease. Studies have shown that gut microbiota (GM) affect these chronic diseases. This study aimed to determine the relationship between HUA and GM. The microbiome of 224 men and 254 women aged 40 years was analyzed through next-generation sequencing and machine learning. We obtained GM data through 16S rRNA-based sequencing of the fecal samples, finding that alpha-diversity by Shannon index was significantly low in the HUA group. Linear discriminant effect size analysis detected a high abundance of the genera Collinsella and Faecalibacterium in the HUA and non-HUA groups. Based on light gradient boosting machine learning, we propose that HUA can be predicted with high AUC using four clinical characteristics and the relative abundance of nine bacterial genera, including Collinsella and Dorea. In addition, analysis of causal relationships using a direct linear non-Gaussian acyclic model indicated a positive effect of the relative abundance of the genus Collinsella on blood UA levels. Our results suggest abundant Collinsella in the gut can increase blood UA levels.

Effects of Switching from Degludec to Glargine U300 in Patients with Insulin-Dependent Type 1 Diabetes: A Retrospective Study.

Background and Objectives: Degludec (Deg) and glargine U300 (Gla-300) are insulin analogs with longer and smoother pharmacodynamic action than glargine U100 (Gla-100), a long-acting insulin that has been widely used for many years in type 1 and type 2 diabetes. Both improve glycemic variability (GV) and the frequency of hypoglycemia, unlike Gla-100. However, it is unclear which insulin analog affects GV and hypoglycemia better in patients with insulin-dependent type 1 diabetes. We evaluated the effects of switching from Deg to Gla-300 on the day-to-day GV and the frequency of hypoglycemia in patients with insulin-dependent type 1 diabetes treated with Deg-containing basal-bolus insulin therapy (BBT). Materials and Methods: We conducted a retrospective study on 24 patients with insulin-dependent type 1 diabetes whose treatment was switched from Deg-containing BBT to Gla-300-containing BBT. We evaluated the day-to-day GV measured as the standard deviation of fasting blood glucose levels (SD-FBG) calculated by the self-monitoring of blood glucose records, the frequency of hypoglycemia (total, severe, and nocturnal), and blood glucose levels measured as fasting plasma glucose (FPG) levels and hemoglobin A1c (HbA1c). Results: The characteristics of the patients included in the analysis with high SD-FBG had frequent hypoglycemic events, despite the use of Deg-containing BBT. For this population, SD-FBG and the frequency of nocturnal hypoglycemia decreased after the switch from Deg to Gla-300. Despite the decrease in the frequency of nocturnal hypoglycemia, the FPG and HbA1c did not worsen by the switch. The change in the SD-FBG had a negative correlation with the SD-FBG at baseline and a positive correlation with serum albumin levels. Conclusions: Switching from Deg to Gla-300 improved the SD-FBG and decreased the frequency of nocturnal hypoglycemia in insulin-dependent type 1 diabetes treated with Deg-containing BBT, especially in cases with low serum albumin levels and a high GV.

3D CNN-based Deep Learning Model-based Explanatory Prognostication in Patients with Multiple Myeloma using Whole-body MRI.

Although magnetic resonance imaging (MRI) data of patients with multiple myeloma (MM) are used to predict prognosis, few reports have applied artificial intelligence (AI) techniques for this purpose. We aimed to analyze whole-body diffusion-weighted MRI data using three-dimensional (3D) convolutional neural networks (CNNs) and Gradient-weighted Class Activation Mapping (Grad-CAM), an explainable AI, to predict prognosis and explore the factors involved in prediction. We retrospectively analyzed the MRI data of a total of 142 patients with MM obtained from two medical centers. We defined the occurrence of progressive disease after MRI evaluation within 12 months as a poor prognosis and constructed a 3D CNN-based deep learning model to predict prognosis. Images from 111 cases were used as the training and internal validation data; images from 31 cases were used as the external validation data. Internal validation of the AI model with stratified 5-fold cross-validation resulted in a significant difference in progression-free survival (PFS) between good and poor prognostic cases (2-year PFS, 91.2% versus [vs.] 61.1%, P = 0.0002). The AI model clearly stratified good and poor prognostic cases in the external validation cohort (2-year PFS, 92.9% vs. 55.6%, P = 0.004), with an area under the receiver operating characteristic curve of 0.804. According to Grad-CAM, the MRI signals of the spleen and bones of the vertebrae and pelvis contributed to prognosis prediction. This study is the first to show that image analysis of whole-body MRI using a 3D CNN without any other clinical data is effective in predicting the prognosis of patients with MM.

Thyrotoxicosis Misdiagnosed as Long Covid by Telemedicine - A Cautionary Tale.

Introduction: Individuals who have had severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection may develop post-coronavirus disease conditions, also known as long COVID. The symptoms of long COVID are nonspecific, and there are similarities between the symptoms of long COVID and those of Graves' disease (GD). Therefore, it is important to rule out GD in patients suspected of having long COVID. Telemedicine is widely used to avoid the risk of SARS-CoV-2 infection. However, owing to the lack of in-person examinations, diagnostic errors can occur. Case description: A 27-year-old Japanese woman presented complaining of persistent fatigue, dyspnea, and low-grade fever, and after in-person examination was finally diagnosed with GD. She had been diagnosed with SARS-CoV-2 infection four months earlier and her symptoms had resolved within 5 days but then recurred. Subsequently, she had 3 telemedicine visits and had been diagnosed with long COVID. Discussion: With telemedicine there may be delayed diagnosis of GD in patients with a recent history of SARS-CoV-2 infection. Some symptoms and abnormalities cannot be confirmed in telemedicine visits performed using a simple mobile phone. Therefore it is important to know which findings obtained in telemedicine visits with a simple mobile phone are suggestive of GD. Low-grade fever and tachycardia are often observed in patients with GD, but rarely occur in patients with long COVID. Conclusion: Tachycardia and persistent low-grade fever after SARS-CoV-2 infection, which can be confirmed by telemedicine, can be clues for the diagnosis of GD. Therefore, in-person examination should be added if these symptoms are confirmed by telemedicine. LEARNING POINTS: The symptoms of Graves 'disease (GD) and long COVID may overlap.With telemedicine there may be delayed diagnosis of GD, in patients with recent history of severe acute respiratory syndrome mediated by coronavirus 2 (SARS-CoV-2) infections.In telemedicine visits, tachycardia and persistent low-grade fever could be clues for the diagnosis of GD after SARS-CoV-2 infections on telemedicine.

Epigenetic alterations of 11beta-hydroxysteroid dehydrogenase 1 gene in the adipose tissue of patients with primary aldosteronism.

11Beta-hydroxysteroid dehydrogenase 1 (11ß-HSD1) is a key enzyme involved in metabolic syndrome. Transcript-specific epigenetic regulation of the gene encoding 11ß-HSD1 (HSD11B1) has been reported. We examined the mRNA level and methylation status of the HSD11B1 promoter region in the adipose tissue of patients with primary aldosteronism (PA). We compared 10 tissue specimens from patients with PA caused by aldosterone-producing adenoma (APA) with 8 adipose tissue specimens from patients with subclinical Cushing's syndrome (SCS) caused by cortisol-producing adenomas, 4 tissue specimens from patients with Cushing's adenoma (Cu), or 7 tissue specimens from patients with non-functioning adrenal adenoma (NFA). PA, SCS, and Cu were diagnosed according to the guideline of the Japan Endocrine Society. The mRNA level of HSD11B1 was quantified using real-time PCR. Isolated DNA was treated with bisulfite and amplified using primers specific to the human HSD11B1 promoter region. The glycohemoglobin level was significantly higher in patients with APA, SCS, or Cu than in those with NFA (p < 0.05). Blood pressure was significantly higher in patients with APA than in those with SCS, Cu, or NFA (p < 0.01). The HSD11B1 mRNA level was significantly increased in the adipose tissues of APA or SCS patients compared with Cu or NFA patients (p < 0.05). The methylation ratio was significantly lower in SCS patients than in APA, Cu, or NFA patients (p < 0.05). HSD11B1 expression is partly controlled by an epigenetic mechanism in human tissues. The pathophysiological role of epigenetic regulation of HSD11B1 expression in adipose tissue requires further study.

Analysis of Pharmaceutical Demand in the Region for Chronic Medicine Users Using National Health Insurance Data: Examination for Disaster Preparedness in Hakui City, Ishikawa Prefecture.

When large earthquakes occur over wide areas, in addition to damage to medical facilities, the disaster response capabilities of local governments are severely compromised. There is a very high possibility that the supply-demand balance of medicines will collapse within the disaster area, and that appropriate supplies of medicines will not be provided to disaster victims. Therefore, it is important to estimate in advance the quantity of pharmaceuticals that may be needed during disasters. In this study, the purpose is to clarify the quantity and quality of pharmaceuticals used by chronically ill patients by using Japanese National Health Insurance data regarding the issues mentioned above. The methodology used was to extract the status of pharmaceutical prescriptions based on receipt information from National Health Insurance data for Hakui, Ishikawa Prefecture, a small regional city in Japan, as the analysis target area. Through the analysis in this study, the quantity and quality of medicines supplied to chronically ill patients in Hakui, Ishikawa Prefecture, were clarified on a town-by-town basis.

A clinical assessment of portable point-of-care testing for quick cortisol assay during adrenal vein sampling.

This study assessed the clinical performance of point-of-care testing (POCT) for quick cortisol assay (QCA) during adrenal vein sampling (AVS) using a newly invented portable quantitative assay instrument. An observational study was conducted prospectively at two centres in Japan. Forty-eight patients with primary aldosteronism considered for adrenalectomy were enrolled in this study and underwent AVS. Three basal adrenal vein samples from each adrenal vein and two from the inferior vena cava were collected sequentially. The cortisol concentration of adrenal vein samples was measured by routine method and QCA. A total of 338 adrenal vein samples were analysed from 250 sites to determine AVS success or failure. The distribution of turnaround time of the QCA for AVS success or failure followed a normal distribution with an average of 20.5 min. A positive correlation between the routine method and QCA was observed regarding cortisol concentration or selectivity index. No significant difference between the two methods was observed regarding the success rate of AVS. Using the routine method as a reference, the sensitivity and specificity of AVS success or failure were 99.1% (210/212) and 81.6% (31/38), respectively. Easy, quick, portable, and precise POCT-QCA demonstrated its compatibility with routine methods regarding clinical performance.

Impact of gut microbiome on serum IgG4 levels in the general population: Shika-machi super preventive health examination results.

Introduction: Immunoglobulin G4 (IgG4) is a member of the human immunoglobulin G (IgG) subclass, a protein involved in immunity to pathogens and the body's resistance system. IgG4-related diseases (IgG4-RD) are intractable diseases in which IgG4 levels in the blood are elevated, causing inflammation in organs such as the liver, pancreas, and salivary glands. IgG4-RD are known to be more prevalent in males than in females, but the etiology remains to be elucidated. This study was conducted to investigate the relationship between gut microbiota (GM) and serum IgG4 levels in the general population. Methods: In this study, the relationship between IgG4 levels and GM evaluated in male and female groups of the general population using causal inference. The study included 191 men and 207 women aged 40 years or older from Shika-machi, Ishikawa. GM DNA was analyzed for the 16S rRNA gene sequence using next-generation sequencing. Participants were bifurcated into high and low IgG4 groups, depending on median serum IgG4 levels. Results: ANCOVA, Tukey's HSD, linear discriminant analysis effect size, least absolute shrinkage and selection operator logistic regression model, and correlation analysis revealed that Anaerostipes, Lachnospiraceae, Megasphaera, and [Eubacterium] hallii group were associated with IgG4 levels in women, while Megasphaera, [Eubacterium] hallii group, Faecalibacterium, Ruminococcus.1, and Romboutsia were associated with IgG4 levels in men. Linear non-Gaussian acyclic model indicated three genera, Megasphaera, [Eubacterium] hallii group, and Anaerostipes, and showed a presumed causal association with IgG4 levels in women. Discussion: This differential impact of the GM on IgG4 levels based on sex is a novel and intriguing finding.

In vivo relationship between bound and free insulin in patients with diabetes having anti-insulin antibodies.

Objective: The Scatchard plot of anti-insulin antibodies is curvilinear, indicating heterogeneity in binding sites. However, the relationship between bound insulin (B) and free insulin (F) in patients with anti-insulin antibodies has not yet been elucidated. This study aimed to determine this relationship. Methods: We studied two insulin-treated patients with diabetes who had high titers of anti-insulin antibodies. The B and F levels were measured using daily blood samples. Assuming that the law of mass action is applicable to the reactions between insulin and anti-insulin antibody forms, we plotted the bound-to-free ratio (B/F) vs. B using patient data. We also performed an equilibrium binding assay in vitro. Results: Some of the B/F vs. B plots of the daily variation showed an approximately linear relationship, while the Scatchard plots of in vitro data became curvilinear. Conclusion: Our study suggests that the one-site (high-affinity site) of anti-insulin antibodies accounts, for the most part, for insulin pharmacokinetics within physiological insulin concentrations. Supplementary Information: The online version contains supplementary material available at 10.1007/s13340-023-00641-1.

Using telemedicine to manage a patient with a hypertensive emergency due to pheochromocytoma.

Summary: The COVID-19 pandemic has led to the emergence of telemedicine on a global scale. In endocrinology, telemedicine has mainly been used in relation to chronic diseases, including diabetes. Herein, we report the case of an 18-year-old woman with a hypertensive emergency due to a pheochromocytoma who was quickly diagnosed and treated using telemedicine. The patient was referred to a cardiovascular hospital because of fatigue and sweating that did not improve with carvedilol. She had fluctuating blood pressure and tachycardia. Subsequently, since her thyroid function was normal, endocrine hypertension not due to thyroid dysfunction was suspected; a case consultation was made by phone to our clinic. Plain computed tomography (CT) was recommended owing to the high possibility of a pheochromocytoma; the CT scan showed an adrenal tumor with a 30 mm diameter. To assess her condition, endocrinologists, together with the attending doctor, interviewed her and her family directly using an online tool to obtain detailed information. We thus determined that she was at risk of a pheochromocytoma crisis. She was transferred to our hospital immediately for treatment, was diagnosed with pheochromocytoma, and underwent surgery. Telemedicine, especially involving doctor-to-patient with doctor consultations, can be effective in treating rare and emergent medical conditions such as pheochromocytoma crisis. Learning points: Telemedicine can be used for chronic diseases and emergency conditions. Online doctor-to-patient with doctor (D-to-P with D) consultations are useful when the expert opinion of a highly specialized physician present in a different geographical location is required. Telemedicine, especially D-to-P with D online consultations, can be effectively used for the diagnosis of rare and emergent medical conditions, such as pheochromocytoma crisis.

Impact of gut microbiome on the renin-aldosterone system: Shika-machi Super Preventive Health Examination results.

The renin-angiotensin-aldosterone system (RAAS) is a regulatory mechanism of the endocrine system and is associated with various diseases, including hypertension and renal and cardiovascular diseases. The gut microbiota (GM) have been associated with various diseases, mainly in animal models. However, to our knowledge, no studies have examined the relationship between the RAAS and GM in humans. The present study aimed to assess the association between the systemic RAAS and GM genera and their causal relationships. The study participants were 377 members of the general population aged 40 years or older in Shika-machi, Japan. Plasma renin activity (PRA), plasma aldosterone concentration (PAC), aldosterone-renin ratio (ARR), and GM composition were analyzed using the 16S rRNA method. The participants were divided into high and low groups according to the PRA, PAC, and ARR values. U-tests, one-way analysis of covariance, and linear discriminant analysis of effect size were used to identify the important bacterial genera between the two groups, and binary classification modeling using Random Forest was used to calculate the importance of the features. The results showed that Blautia, Bacteroides, Akkermansia, and Bifidobacterium were associated with the RAAS parameters. Causal inference analysis using the linear non-Gaussian acyclic model revealed a causal effect of Blautia on PAC via SBP. These results strengthen the association between the systemic RAAS and GM in humans, and interventions targeting the GM may provide new preventive measures and treatments for hypertension and renal disease.

Fulminant type 1 diabetes developed after influenza split vaccination.

Summary: Fulminant type 1 diabetes (FT1D) is a subtype of diabetes characterized by rapid progression of ß-cell destruction, hyperglycemia, and diabetic ketoacidosis (DKA). The pathogenesis of this disease remains unclear. However, viral infections, HLA genes, and immune checkpoint inhibitor use were reportedly involved in this disease. A 51-year-old Japanese man with no chronic medical condition was admitted to our hospital with complaints of nausea and vomiting. Cough, sore throat, nasal discharge, and diarrhea were not noted. He had a medical history of at least two influenza infections. His vaccination history was notable for receiving an inactive split influenza vaccine 12 days prior to developing these symptoms. He was diagnosed with DKA associated with FT1D. His HLA class II genotypes were nonsusceptible to FT1D, and he had a negative history of immune checkpoint inhibitor use. The destruction of the pancreas by cytotoxic T cells is reported to be involved in FT1D. Inactive split influenza vaccines do not directly activate cytotoxic T cells. However, these could activate the redifferentiation of memory CD8-positive T cells into cytotoxic T cells and induce FT1D, as this patient had a history of influenza infections. Learning points: Influenza split vaccination could cause fulminant type 1 diabetes (FT1D). The mechanism of influenza split vaccine-induced FT1D might be through the redifferentiation of CD8-positive memory T cells into cytotoxic T cells.

Molecular and Epigenetic Control of Aldosterone Synthase, CYP11B2 and 11-Hydroxylase, CYP11B1.

Aldosterone and cortisol serve important roles in the pathogenesis of cardiovascular diseases and metabolic disorders. Epigenetics is a mechanism to control enzyme expression by genes without changing the gene sequence. Steroid hormone synthase gene expression is regulated by transcription factors specific to each gene, and methylation has been reported to be involved in steroid hormone production and disease. Angiotensin II or potassium regulates the aldosterone synthase gene, CYP11B2. The adrenocorticotropic hormone controls the 11b-hydroxylase, CYP11B1. DNA methylation negatively controls the CYP11B2 and CYP11B1 expression and dynamically changes the expression responsive to continuous stimulation of the promoter gene. Hypomethylation status of the CYP11B2 promoter region is seen in aldosterone-producing adenomas. Methylation of recognition sites of transcription factors, including cyclic AMP responsive element binding protein 1 or nerve growth factor-induced clone B, diminish their DNA-binding activity. A methyl-CpG-binding protein 2 cooperates directly with the methylated CpG dinucleotides of CYP11B2. A low-salt diet, treatment with angiotensin II, and potassium increase the CYP11B2 mRNA levels and induce DNA hypomethylation in the adrenal gland. A close association between a low DNA methylation ratio and an increased CYP11B1 expression is seen in Cushing's adenoma and aldosterone-producing adenoma with autonomous cortisol secretion. Epigenetic control of CYP11B2 or CYP11B1 plays an important role in autonomic aldosterone or cortisol synthesis.

A hyperaldosteronism subtypes predictive model using ensemble learning.

This study aimed to develop a machine-learning algorithm to diagnose aldosterone-producing adenoma (APA) for predicting APA probabilities. A retrospective cross-sectional analysis of the Japan Rare/Intractable Adrenal Diseases Study dataset was performed using the nationwide PA registry in Japan comprised of 41 centers. Patients treated between January 2006 and December 2019 were included. Forty-six features at screening and 13 features at confirmatory test were used for model development to calculate APA probability. Seven machine-learning programs were combined to develop the ensemble-learning model (ELM), which was externally validated. The strongest predictive factors for APA were serum potassium (s-K) at first visit, s-K after medication, plasma aldosterone concentration, aldosterone-to-renin ratio, and potassium supplementation dose. The average performance of the screening model had an AUC of 0.899; the confirmatory test model had an AUC of 0.913. In the external validation, the AUC was 0.964 in the screening model using an APA probability of 0.17. The clinical findings at screening predicted the diagnosis of APA with high accuracy. This novel algorithm can support the PA practice in primary care settings and prevent potentially curable APA patients from falling outside the PA diagnostic flowchart.

Impact of Conducting Adrenal Venous Sampling in the Morning Versus Afternoon in Primary Aldosteronism.

Context: Adrenal venous sampling (AVS) is the gold standard technique for subtype differentiation of primary aldosteronism (PA) and to obtain aldosterone and cortisol measurements; however, their secretion patterns show fluctuations during the day. Objective: We aimed to examine the effects of AVS timing on AVS results. Methods: This multicenter, retrospective, observational study included a total of 753 patients who were diagnosed with PA and underwent AVS in 4 centers in Japan. Among them, 504 and 249 patients underwent AVS in the morning (AM-AVS) and in the afternoon (PM-AVS), respectively. The outcome measures were the impact of AVS timing and hormone fluctuations in a day on AVS results. Results: There were no differences in the success rate of AVS, diagnostic rate of disease type, or frequency of discrepancy in PA subtypes between the AM-AVS and PM-AVS groups. Regarding patients with unilateral PA, aldosterone concentrations in adrenal venous blood did not differ between the 2 groups on the dominant or nondominant side. Conversely, regarding patients with bilateral PA, aldosterone concentrations in adrenal venous blood were significantly higher in the AM-AVS than in the PM-AVS group. Conclusions: The timing of AVS did not seem to have a significant impact on subtype diagnosis. The aldosterone levels in adrenal venous blood were significantly higher in patients with bilateral PA in the AM-AVS group, but there was no such difference between patients with unilateral PA in the AM-AVS and PM-AVS groups. Each subtype may have a different hormone secretion pattern in a day.

Adrenal Hemorrhaging in a Patient with Severe Obstructive Sleep Apnea Syndrome with Elevated Plasma ACTH Levels.

Adrenal hemorrhaging (AH) is a rare condition characterized by bleeding into the suprarenal glands. A 62-year-old man with untreated obstructive sleep apnea syndrome (OSAS) was admitted to our hospital complaining of abdominal stiffness. He was diagnosed with left-sided AH and underwent adrenalectomy. Pre- and post-surgery, elevated plasma adrenocorticotropic hormone (ACTH) levels were observed. However, Cushing's syndrome and adrenal insufficiency were negative, and nasal continuous positive airway pressure (CPAP) normalized the plasma ACTH levels. Elevated ACTH levels are reportedly present in patients with OSAS. ACTH may be associated with the development of AH through the change in blood supply and other mechanisms.

Comprehensive Steroid Assay with Non-Targeted Analysis Using Liquid Chromatography Ion Mobility Mass Spectrometry.

Aldosterone-producing adenomas (APAs) have different steroid profiles in serum, depending on the causative genetic mutation. Ion mobility is a separation technique for gas-phase ions based on their m/z values, shapes, and sizes. Human serum (100 µL) was purified by liquid-liquid extraction using tert-butyl methyl ether/ethyl acetate at 1/1 (v/v) and mixed with deuterium-labeled steroids as the internal standard. The separated supernatant was dried, re-dissolved in water containing 20% methanol, and injected into a liquid chromatography-ion mobility-mass spectrometer (LC/IM/MS). We established a highly sensitive assay system by separating 20 steroids based on their retention time, m/z value, and drift time. Twenty steroids were measured in the serum of patients with primary aldosteronism, essential hypertension, and healthy subjects and were clearly classified using principal component analysis. This method was also able to detect phosphatidylcholine and phosphatidylethanolamine, which were not targeted. LC/IM/MS has a high selectivity for known compounds and has the potential to provide information on unknown compounds. This analytical method has the potential to elucidate the pathogenesis of APA and identify unknown steroids that could serve as biomarkers for APA with different genetic mutations.