Association Between Peripheral Blood Natural Killer Cells and Chromosomally Abnormal Spontaneous Abortion: A Retrospective Single-Center Study

Association Between Peripheral Blood Natural Killer Cells and Chromosomally Abnormal Spontaneous Abortion: A Retrospective Single-Center Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Association Between Peripheral Blood Natural Killer Cells and Chromosomally Abnormal Spontaneous Abortion: A Retrospective Single-Center Study Junmiao Xiang, Yundong Pan, Qianruo Pan, Weiya Zhuang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6504301/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Background Chromosomal abnormalities account for a significant proportion of spontaneous abortions (SA), yet the role of peripheral blood natural killer (pbNK) cells—especially across different karyotypes—remains unclear. Elucidating this relationship may reveal immune mechanisms underlying early pregnancy loss and identify actionable biomarkers. Methods This retrospective, single-center study included 1250 patients, comparing 294 early SA cases (classified as chromosomally normal or abnormal via CNV-seq) with 956 live births. Multivariable logistic regression and stratified analyses were used to assess the association between pbNK cell levels and chromosomally abnormal SA, as well as specific karyotypes. The diagnostic performance of pbNK cells was evaluated using receiver operating characteristic (ROC) curves. Results Multivariate analysis identified elevated pbNK cell levels as an independent risk factor for chromosomally abnormal SA (adjusted OR = 1.363, 95% CI: 1.033–1.797). Patients in the highest quartile of pbNK cells had a fourfold increased risk (OR = 4.123), with a linear dose-response relationship observed. Notably, SA cases associated with microdeletions showed the strongest association (OR = 10.807, 95% CI: 2.627–44.455), while trisomies demonstrated borderline significance. ROC analysis indicated moderate diagnostic utility (AUC = 65.1%, sensitivity = 52.1%, specificity = 74.8%). Conclusion These findings suggest that pbNK cell levels serve as a biomarker for chromosomally abnormal SA, particularly in microdeletion-related cases, and support a linear dose-response relationship between pbNK cell levels and SA risk. Peripheral blood natural killer cells Chromosomally abnormal spontaneous abortion Microdeletions Biomarker Immune dysregulation Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction Spontaneous abortion (SA) occurs in approximately 10% of clinically recognized pregnancies, with over 80% of cases in the first trimester [ 1 ]. SA can result from immunological factors, chromosomal abnormalities, anatomical anomalies, endocrine dysfunction, infections, and male factors [ 2 ]. Embryonic chromosomal abnormalities, occurring during gametogenesis or embryogenesis, are the leading cause of early SA, accounting for 50–60% of cases [ 3 ]. Chromosomal abnormalities encompass structural aberrations (e.g., deletions, duplications, translocations, and inversions) and numerical anomalies. Recent advancements in next-generation sequencing (NGS) technology have significantly enhanced the detection of aneuploidy and copy number variation sequencing (CNV-seq) in miscarriage tissues, offering improved sensitivity, specificity, and accuracy [ 4 , 5 ]. Chromosomal abnormalities are also recognized as a critical factor in recurrent spontaneous abortion (RSA) [ 6 ]. Early prediction of chromosomal abnormality-related miscarriages could prevent unnecessary interventions such as excessive tocolytic therapy. Therefore, identifying predictive biomarkers for embryonic chromosomal abnormalities holds significant clinical value in elucidating the etiology of early spontaneous abortion. The immune system plays a pivotal role in embryo implantation and pregnancy maintenance. Dysregulation of immune responses may lead to maternal immune rejection of the embryo by recognizing it as foreign [ 7 ]. Natural killer (NK) cells, a key component of the innate immune system, constitute 10–15% of circulating lymphocytes. These cells exhibit potent cytotoxic activity and are essential for establishing immune tolerance and maintaining a functional maternal-fetal interface [ 8 ]. Notably, decidual NK (dNK) cells, characterized by low cytotoxicity and high cytokine-secreting capacity, regulate extravillous trophoblast (EVT) invasion into the decidua and spiral arteries. Abnormal dNK cell distribution may impair EVT-mediated remodeling of uterine vasculature, ultimately compromising embryonic development [ 9 , 10 ]. Peripheral blood NK (pbNK) cells, characterized by the expression of CD56 (a neural cell adhesion molecule) and CD16 (FcγRIII), can be subdivided into two distinct subsets. Approximately 90% of peripheral blood NK cells exhibit relatively low CD56 expression levels and are positive for CD16, termed the "CD16 + CD56 + dim" subset. The remaining 10% display high CD56 expression with negative or low CD16 expression (CD16 − CD56 + bright) [ 11 ]. While endometrial sampling is impractical during normal pregnancy, pbNK cells serve as a noninvasive tool for monitoring immune dynamics. Activated pbNK cells are recruited to the endometrium during the mid-secretory phase of the menstrual cycle and early gestation [ 12 ]. These cells may trigger thrombosis, inflammatory responses, pro-inflammatory cytokine activation, or trophoblast apoptosis, potentially contributing to implantation failure or miscarriage [ 8 ]. Previous studies have demonstrated that RSA patients exhibit significantly elevated pbNK cell percentages and absolute counts compared to women with normal pregnancies [ 13 – 16 ]. This elevation may reflect maternal immune hyperactivation, leading to embryo rejection. For instance, Kim et al. [ 13 ] reported markedly higher pbNK cell percentages in RSA patients versus controls (P 18% demonstrating high specificity for distinguishing RSA cases, suggesting its utility as a diagnostic marker. While elevated pbNK cell levels have been linked to adverse pregnancy outcomes, their role in miscarriages caused by chromosomal abnormalities remains unclear. This study examines the relationship between the CD16 + CD56 + dim subset of pbNK cells and chromosomally abnormal spontaneous abortion, including different abnormal karyotypes. Additionally, it explores whether pbNK cell levels can serve as a predictor of pregnancy outcomes. 2. Material and Methods 2.1 Patient Population This retrospective study included 1250 patients with ultrasound-confirmed intrauterine pregnancies at The Third Affiliated Hospital of Wenzhou Medical University from January 2017 to September 2023. Among these, 294 patients who experienced early spontaneous abortion before 12 weeks and underwent uterine evacuation—with tissue collected for CNV-seq analysis—formed the SA group. Additionally, 956 patients with live births, defined as delivery at or after 28 weeks, served as controls. Exclusion criteria comprised incomplete clinical records, systemic comorbidities, insufficient follow-up data, severe infections, or reproductive system malformations. Spontaneous abortions were classified as chromosomally normal if CNV-seq results were normal and as chromosomally abnormal if the results were abnormal. The study was approved by the Research Ethics Committee of The Third Affiliated Hospital of Wenzhou Medical University, and all participants provided informed consent. 2.2 Clinical features record The study’s demographic and clinical data—including age, body mass index (BMI), reproductive history, and pregnancy follow-up—were collected from medical records and telephone follow-ups. 2.3 Coagulation and biochemical indicators measurements We used a TCA-6000 thromboelastometer (Shengyu Corporation, China) to measure thrombelastogram (TEG) parameters, including reaction time (R), clot formation time (K), maximum amplitude (MA), and clot formation rate (α-angle). Standard coagulation tests—international normalized ratio (INR), fibrinogen (FIB), thrombin time (TT), prothrombin time (PT), activated partial thromboplastin time (APTT), and D-dimer levels—were assessed using a STA-R MAX coagulation analyzer (France). In addition, levels of triiodothyronine (T3), thyroxine (T4), thyroid stimulating hormone (TSH), fasting blood glucose (FBG), 25-hydroxyvitamin D (25(OH)D), homocysteine (Hcy), total cholesterol (TC), triglycerides (TG), and uric acid (UA) were measured using a Siemens IM1600 chemiluminescence assay. 2.4 Immune biomarker measurements Lymphocyte subpopulations were analyzed using a BD FACSCanto II flow cytometer to measure CD16⁺CD56⁺ natural killer (pbNK) cells, CD19⁺ B lymphocytes, CD3⁺ T lymphocytes, CD4⁺ T lymphocytes, and CD8⁺ T lymphocytes. Complement components C3 and C4 were quantified by rate nephelometry using a Siemens CH930 automatic biochemical analyzer (Shanghai, China). Antinuclear antibody (ANA) titers were determined by indirect immunofluorescence on Hep-2 cells, with a positive result defined as a titer of 1:160 or greater. Additionally, IgG, IgA, and IgM isotypes of anticardiolipin (aCL) and anti-β2-glycoprotein I (aβ2GP1) antibodies were measured using iFlash CLIA kits (YHLO Biotech Co., Shenzhen, China), with cut-off values of 12 U/mL for aCL and 24 U/mL for aβ2GP1. All assays were performed by experienced technicians following the manufacturers’ protocols. Blood samples for these tests were collected from pregnant women between the 4th and 8th weeks of pregnancy. 2.5 Statistical analysis The Shapiro–Wilk test assessed data normality. Normally distributed continuous variables are presented as mean ± standard deviation (X ± SD), while non-normally distributed variables are presented as medians (Q1, Q3). Categorical data are reported as counts and proportions. For comparisons among three groups, the Kruskal–Wallis test was employed, followed by pairwise comparisons using the Mann–Whitney U test with Bonferroni correction to adjust for multiple testing. Proportions were compared using the χ² test. Multivariate-adjusted models evaluated the association between pbNK cells and chromosomally abnormal spontaneous abortion incidence. Variables for adjustment were selected based on a > 10% change in the effect estimate or a clinically significant association. The unadjusted model was followed by adjustments for age, BMI, pregnancy history, and previous miscarriage in Model 1; Model 1 was expanded to include C3, C4, T3, T4, FIB, and Hcy in Model 2; and Model 2 was further adjusted for CD19⁺ B cells, CD3⁺ T cells, and CD4⁺ T cells in Model 3. To compare the association between pbNK cells and all abnormal fetal tissue chromosome karyotypes, multivariate-adjusted models were used as unadjusted models and adjustments as in Model 3. Results are presented as odds ratios (OR) with 95% confidence intervals (CI). Receiver operating characteristic (ROC) curves assessed the diagnostic accuracy of pbNK cells, with the area under the curve (AUC) quantifying performance. Non-linearity was assessed using a likelihood ratio test to compare the model with only a linear term against the model including both linear and cubic spline terms. Subgroup analyses were also conducted. PbNK cells were treated as a categorical variable, while continuous variables were transformed into categorical variables based on clinically established cut-off points or median values. Interaction effects among subgroups were assessed using the likelihood ratio test. Statistical analyses were performed using R software (version 4.2.2; The R Foundation, http://www.R-project.org ), SPSS Statistics (version 22.0; IBM Corp., Armonk, NY), and Free Statistics (version 1.9; Beijing, China, http://www.clinicalscientists.cn/freestatistics ). All tests were two-tailed, with a P-value < 0.05 considered statistically significant. 3. Results 3.1. Clinical characteristics of the study participants The study included 1250 participants, categorized into three groups: 106 in the chromosomally normal spontaneous abortion group, 188 in the chromosomally abnormal spontaneous abortion group, and 956 in the live birth group. Significant differences were observed among the three groups in pregnancy history, previous miscarriage, Hcy, TC, FIB, C3 and C4, T3, T4, pbNK cells, CD19⁺ B cells, CD3⁺ T cells, and CD4⁺ T cells. Comparisons between the chromosomally abnormal spontaneous abortion group and the live birth group revealed significant differences in previous miscarriage, Hcy, FIB, C3, C4, T3, T4, pbNK cells, CD19⁺ B cells, CD3⁺ T cells, and CD4⁺ T cells. Notably, pbNK cells were the only parameter that differed significantly between the chromosomally abnormal spontaneous abortion group and both the chromosomally normal spontaneous abortion and live birth groups. However, no significant difference in pbNK cells was observed between the chromosomally normal spontaneous abortion group and the live birth group (Table 1 ). Table 1 Baseline demographic characteristics and laboratory indicators of the study population Variables Total (n = 1250) Chromosomally normal spontaneous abortion (n = 106) Chromosomally abnormal spontaneous abortion (n = 188) Live birth controls (n = 956) P -Value Age (years) 29.24 ± 8.64 30.82 ± 25.86 29.81 ± 4.78 28.96 ± 4.38 0.068 BMI (kg/m2) 21.47 ± 3.09 21.68 ± 2.62 21.21 ± 2.58 21.49 ± 3.23 0.395 Pregnancy history 0.003 Nulliparous 859 (68.72%) 88 (83.02%) a 132 (70.21%) b 639 (66.84%) b Multiparous 391 (31.28%) 18 (16.98%) 56 (29.79%) 317 (33.16%) Previous miscarriage < 0.001 0 479 (38.32%) 64 (60.38%) a 110 (58.51%) a 305 (31.9%) b 1 403 (32.24%) 19 (17.92%) a 45 (23.94%) a 339 (35.46%) b 2 213 (17.04%) 12 (11.32%) a, b 16 (8.51%) b 185 (19.35%) a ≥ 3 155 (12.40%) 11 (10.38%) a 17 (9.04%) a 127 (13.28%) a FBG (mmol/L) 4.75 ± 0.95 4.90 ± 1.66 4.74 ± 0.75 4.74 ± 0.87 0.266 UA (µmol/L) 248.68 ± 62.38 256.67 ± 50.83 253.65 ± 58.47 246.82 ± 64.19 0.151 25(OH)D (ng/mL) 20.02 ± 7.49 19.84 ± 9.08 19.80 ± 7.38 20.09 ± 7.33 0.856 Hcy (µmol/L) 6.28 ± 1.55 6.78 ± 1.91 a 6.56 ± 1.81 a 6.17 ± 1.43 b < 0.001 TC (mmol/L) 3.97 ± 0.74 4.12 ± 0.71 a 4.04 ± 0.67 a 3.95 ± 0.75 a 0.036 TG (mmol/L) 1.05 ± 0.57 1.08 ± 0.42 1.00 ± 0.37 1.06 ± 0.61 0.386 PT (s) 11.69 ± 0.72 11.75 ± 0.65 11.63 ± 0.68 11.69 ± 0.74 0.378 TT (s) 16.34 ± 1.33 16.54 ± 1.52 16.42 ± 1.07 16.31 ± 1.36 0.164 APTT (s) 28.20 ± 3.30 28.62 ± 3.03 28.50 ± 3.02 28.09 ± 3.38 0.121 INR 0.99 ± 0.06 0.99 ± 0.06 0.98 ± 0.06 0.99 ± 0.06 0.338 FIB (g/L) 2.95 ± 0.66 2.94 ± 0.58 a, b 2.84 ± 0.59 a 2.97 ± 0.68 b 0.036 D-dimer (ug/ml) 0.24 (0.16, 0.40) 0.22 (0.16, 0.35) 0.24 (0.16, 0.40) 0.25 (0.17, 0.40) 0.251 aPLs 0.526 Negative 1204 (96.3%) 102 (96.2%) 184 (97.9%) 918 (96%) Positive 46 (3.7%) 4 (3.8%) 4 (2.1%) 38 (4%) ANAs 0.452 Negative 1112 (88.96%) 95 (89.62%) 172 (91.49%) 845 (88.39%) Positive 138 (11.04%) 11 (10.38%) 16 (8.51%) 111 (11.61%) R (min) 5.62 ± 1.89 5.48 ± 1.48 5.69 ± 1.25 5.62 ± 2.03 0.666 K (min) 1.52 ± 0.63 1.53 ± 0.46 1.53 ± 0.59 1.52 ± 0.66 0.951 α-Angle (deg) 71.03 ± 5.12 71.06 ± 4.44 70.63 ± 4.04 71.10 ± 5.37 0.506 MA (mm) 66.01 ± 4.80 66.25 ± 4.60 65.70 ± 4.20 66.04 ± 4.93 0.57 C3 (mg/dL) 9.31 ± 2.01 9.35 ± 1.76 a, b 8.79 ± 1.74 a 9.41 ± 2.07 b < 0.001 C4 (mg/dL) 2.12 ± 0.71 2.14 ± 0.64 a, b 1.96 ± 0.53 a 2.15 ± 0.74 b 0.003 T3 (nmol/L) 1.75 ± 0.41 1.71 ± 0.40 a, b 1.63 ± 0.25 a 1.78 ± 0.44 b < 0.001 T4 (nmol/L) 120.89 ± 29.05 118.31 ± 31.53 a, b 110.42 ± 22.45 a 123.23 ± 29.46 b < 0.001 TSH (mIU/L) 1.65 (1.04, 2.39) 1.80 (1.19, 2.69) 1.73 (1.13, 2.44) 1.62 (1.02, 2.36) 0.089 CD16⁺CD56⁺ NK cells (%) 13.22 ± 7.38 13.78 ± 7.43 a 16.46 ± 8.00 b 12.53 ± 7.08 a < 0.001 CD19 + B cells (%) 13.29 ± 4.20 12.94 ± 4.03 a, b 11.90 ± 3.49 b 13.60 ± 4.29 a < 0.001 CD3 + T cells (%) 72.49 ± 7.17 72.24 ± 7.13 a, b 70.72 ± 7.42 a 72.86 ± 7.07 b < 0.001 CD4 + T cells (%) 38.58 ± 7.20 37.59 ± 7.06 a, b 35.98 ± 5.92 a 39.21 ± 7.32 b < 0.001 CD8 + T cells (%) 27.72 ± 6.02 28.65 ± 6.02 27.94 ± 5.92 27.58 ± 6.04 0.192 BMI: body mass index; FBG: fasting blood glucose; UA: uric acid; 25(OH)D: 25-hydroxyvitamin D; Hcy: homocysteine; TC: total cholesterol; TG: triglycerides; PT: prothrombin time; TT: thrombin time; APTT: activated partial thromboplastin time; INR: international normalized ratio; FIB: Fibrinogen; aPLs: antiphospholipid antibodies; ANAs: antinuclear antibodies; R: reaction time; K: clot formation time; MA: maximum amplitude; α-angle: clot formation rate; C3: complement C3; C4: complement C4; T3: triiodothyronine; T4: thyroxine; TSH: thyroid stimulating hormone; CD16⁺CD56⁺ NK cells: CD16⁺CD56⁺ natural killer cells; CD19 + B cells: CD19 + B lymphocytes; CD3 + T cells: T lymphocytes; CD4 + T cells: CD4 + T lymphocytes; CD8 + T cells: CD8 + T lymphocytes; Different letters(a, b) indicate significant differences between groups (p < 0.05); 3.2 Associated between pbNK cell levels and chromosomally abnormal spontaneous abortion Univariate logistic regression analysis indicated that age, Hcy, and pbNK cells were positively associated with an increased risk of chromosomally abnormal spontaneous abortion. In contrast, previous miscarriage, FIB, C3, C4, T3, T4, CD19⁺ B cells, CD3⁺ T cells, and CD4⁺ T cells were negatively associated with this risk (Table 2 ). Multivariate regression analysis (Table 3 ) further confirmed a significant positive association between pbNK cell levels and the risk of chromosomally abnormal spontaneous abortion across all four models. In the unadjusted model, an increase in pbNK cells was significantly associated with a higher risk of chromosomally abnormal spontaneous abortion (OR = 1.068; 95% CI: 1.047–1.089; P < 0.001). In the fully adjusted Model 3, the OR remained significant at 1.363 (95% CI: 1.033–1.797). For further analysis, pbNK cell levels were categorized into quartiles. Using the first quartile as the reference, the OR for the highest quartile in Model 3 was 4.123 (95% CI: 1.419–11.976), demonstrating a significant increasing trend (P < 0.05). Table 2 Univariable analysis of covariates associated with chromosomally abnormal spontaneous abortion compared to live birth controls Variables OR (95% CI) P -Value Age (years) 1.042 (1.007 ~ 1.079) 0.018 BMI 0.97 (0.921 ~ 1.022) 0.256 Pregnancy history Nulliparous 1(Ref.) Multiparous 0.855 (0.609 ~ 1.202) 0.3676 Previous miscarriage 0 1(Ref.) 1 0.368 (0.252 ~ 0.538) < 0.001 2 0.24 (0.138 ~ 0.418) < 0.001 ≥ 3 0.371 (0.214 ~ 0.644) < 0.001 T3 (nmol/L) 0.323 (0.199 ~ 0.525) < 0.001 T4 (nmol/L) 0.98 (0.973 ~ 0.987) < 0.001 FIB (g/L) 0.718 (0.556 ~ 0.927) 0.011 Hcy (µmol/L) 1.159 (1.056 ~ 1.273) 0.002 C3 (mg/dL) 0.188 (0.079 ~ 0.445) < 0.001 C4 (mg/dL) 0.015 (0.001 ~ 0.178) < 0.001 CD16⁺CD56⁺ NK cells (%) 1.068 (1.047 ~ 1.089) < 0.001 CD19 + B cells (%) 0.898 (0.861 ~ 0.937) < 0.001 CD3 + T cells (%) 0.961 (0.94 ~ 0.981) < 0.001 CD4 + T cells (%) 0.937 (0.916 ~ 0.959) < 0.001 BMI: body mass index; T3: triiodothyronine; T4: thyroxine; FIB: Fibrinogen; Hcy: homocysteine; C3: complement C3; C4: complement C4; CD16⁺CD56⁺ NK cells: CD16⁺CD56⁺ natural killer cells; CD19 + B cells: CD19 + B lymphocytes; CD3 + T cells: T lymphocytes; CD4 + T cells: CD4 + T lymphocytes; Table 3 Association of peripheral blood CD16⁺CD56⁺ NK cell levels with chromosomally abnormal spontaneous abortion across unadjusted and adjusted models compared with live birth controls Crude Model Model 1 Model 2 Model 3 Variable OR (95% CI) P -Value OR (95% CI) P -Value OR (95% CI) P -Value OR (95% CI) P -Value CD16⁺CD56⁺ NK cells 1.068 (1.047 ~ 1.089) < 0.001 1.064 (1.042 ~ 1.086) < 0.001 1.062 (1.039 ~ 1.085) < 0.001 1.363 (1.033 ~ 1.797) 0.029 CD16⁺CD56⁺ NK cells, per SD 1.621 (1.4 ~ 1.877) < 0.001 1.582 (1.358 ~ 1.844) < 0.001 1.557 (1.326 ~ 1.827) < 0.001 9.805 (1.269 ~ 75.739) 0.029 CD16⁺CD56⁺ NK cells (quartile) Q1 1(Ref.) 1(Ref.) 1(Ref.) 1(Ref.) Q2 1.512 (0.877 ~ 2.607) 0.137 1.496 (0.856 ~ 2.614) 0.157 1.33 (0.745 ~ 2.373) 0.3348 1.346 (0.724 ~ 2.504) 0.348 Q3 1.983 (1.173 ~ 3.355) 0.011 1.91 (1.115 ~ 3.272) 0.0185 1.838 (1.054 ~ 3.208) 0.032 1.879 (0.909 ~ 3.885) 0.089 Q4 4.34 (2.658 ~ 7.085) < 0.001 4.122 (2.491 ~ 6.821) < 0.001 3.849 (2.281 ~ 6.496) < 0.001 4.123 (1.419 ~ 11.976) 0.009 P for trend < 0.001 < 0.001 < 0.001 0.02 Crude model: adjusted for none. Model 1: Adjusted for Age, BMI, pregnancy history and previous miscarriage. Model 2: Adjusted for the variables in Model 1 plus C3, C4, T3, T4, FIB and Hcy. Model 3: Adjusted for the variables in Model 2 plus CD19 + B cells, CD3 + T cells and CD4 + T cells BMI: body mass index; T3: triiodothyronine; T4: thyroxine; FIB: Fibrinogen; Hcy: homocysteine; C3: complement C3; C4: complement C4; CD16⁺CD56⁺ NK cells: CD16⁺CD56⁺ natural killer cells; CD19 + B cells: CD19 + B lymphocytes; CD3 + T cells: T lymphocytes; CD4 + T cells: CD4 + T lymphocytes; 3.3 ROC diagnostic performance of pbNK cells ROC analysis was used to evaluate the diagnostic accuracy of pbNK cells in distinguishing live births from chromosomally abnormal spontaneous abortions. The AUC was 65.1, reflecting moderate diagnostic performance. At a cutoff value of 16.1, the sensitivity was 52.1% and the specificity was 74.8% (Fig. 2 ). 3.4 Nonlinear relationship between pbNK cells and chromosomally abnormal spontaneous abortion After adjusting for covariates, restricted cubic spline (RCS) analysis indicated a linear association between pbNK cell levels and the risk of chromosomally abnormal spontaneous abortion (P for non-linearity = 0.388) (Fig. 1 ). 3.5 Subgroup analyses Stratified analysis was conducted to examine the relationship between pbNK cell levels and chromosomally abnormal spontaneous abortion across various subgroups. No significant associations were observed when stratified by age, BMI, pregnancy history, previous miscarriage, Hcy, CD19⁺ B cells, CD3⁺ T cells, CD4⁺ T cells, ANAs, or aPLs (Fig. 3 ). 3.6 Associated between pbNK cell levels and all abnormal foetal tissue chromosome karyotypes Among the seven chromosome karyotypes, pbNK cell levels were significantly higher in cases of trisomy (16.88 ± 7.95), mosaicism (28.13 ± 7.32), and microdeletion (19.62 ± 7.44) compared to the live birth controls (13.22 ± 7.38) (Fig. 4 ). In the unadjusted model, significant associations were found for trisomy (OR = 1.073; 95% CI: 1.048–1.098; P < 0.001), mosaicism (OR = 1.196; 95% CI: 1.067–1.34; P = 0.002), and microdeletion (OR = 1.104; 95% CI: 1.04–1.172; P = 0.001) with pbNK cell levels. In the fully adjusted Model 3, only the OR for microdeletion with pbNK cell levels remained significant (OR = 10.807; 95% CI: 2.627–44.455), whereas trisomy did not reach significance (OR = 1.37; 95% CI: 0.977–1.922; P = 0.068) (Table 4 ). Table 4 Association of peripheral blood CD16⁺CD56⁺ NK cell levels with different abnormal spontaneous abortion chromosome karyotypes across unadjusted and fully adjusted models compared with live birth controls Crude Model Fully adjusted model Chromosome karyotypes Number OR (95% CI) P OR (95% CI) P Triploid 30 (3%) 1.037 (0.991 ~ 1.085) 0.120 1.516 (0.766 ~ 3.002) 0.232 Trisomy 115 (10.7%) 1.073 (1.048 ~ 1.098) < 0.001 1.37 (0.977 ~ 1.922) 0.068 Mosaicism 3 (0.3%) 1.196 (1.067 ~ 1.34) 0.002 1.579 (0.158 ~ 15.769) 0.697 45, X 19 (1.9%) 1.044 (0.988 ~ 1.103) 0.124 1.138 (0.449 ~ 2.884) 0.785 Microduplication 4 (0.4%) 1.017 (0.892 ~ 1.158) 0.805 0.39 (0.109 ~ 1.403) 0.150 Microdeletion 12 (1.2%) 1.104 (1.04 ~ 1.172) 0.001 10.807 (2.627 ~ 44.455) 0.001 Uniparental disomy 5 (0.5%) 0.973 (0.848 ~ 1.117) 0.699 0.661 (0.191 ~ 2.284) 0.513 Crude model: adjusted for none. Fully adjusted model: Adjusted for Age, BMI, pregnancy history, previous miscarriage, C3, C4, T3, T4, FIB, Hcy, CD19 + B cells, CD3 + T cells and CD4 + T cells 4. Discussion Our study indicates that a higher proportion of peripheral CD16⁺CD56⁺ natural killer cells among lymphocytes is correlated with an increased risk of chromosomally abnormal spontaneous abortion, with moderate diagnostic performance (AUC = 65.1). RCS and subgroup analyses further confirmed a stable, linear association between pbNK cell levels and chromosomally abnormal spontaneous abortion. Karyotype analysis revealed that both microdeletions and trisomies are associated with elevated pbNK cell levels. Notably, microdeletions were consistently associated with a higher risk of chromosomal abnormality-related miscarriage in both unadjusted and fully adjusted models. The stability of NK cells is crucial for a successful pregnancy. These cells constitute 10–15% of peripheral blood lymphocytes and 70–90% of uterine lymphocytes[ 17 ]. Their proportion, quantity, and activity are implicated in pregnancy complications such as fetal loss, preeclampsia, preterm birth, and congenital infections[ 18 ]. Unlike the resident decidual NK (dNK) cells, which are primarily CD16⁻CD56⁺bright, most peripheral blood NK cells exhibit a CD16⁺CD56⁺dim phenotype, characterized by higher cytotoxicity and lower cytokine secretion[ 11 ]. Studies suggest that peripheral CD16⁺CD56⁺bright NK cells and hematopoietic progenitors are recruited to the decidua during pregnancy and differentiate into dNK cells upon exposure to the local microenvironment[ 19 ]. These maternal immune cells interact with decidual stromal cells and extravillous trophoblasts (EVTs), shaping a highly complex immune microenvironment [ 7 ]. Early studies had limited sample sizes, making it difficult to determine whether elevated pbNK cell percentages or activity predicted miscarriage in women with RSA (n = 32, OR 17, 95% CI 0.82–350.6; activity: n = 92, OR 2.51, 95% CI 0.16–40.29) [ 20 ]. However, subsequent research has increasingly linked pbNK cells to pregnancy loss. Qiong Wang et al. [ 21 ] reported that women with lower pbNK levels during pregnancy had significantly higher live birth rates compared to those without such a reduction. A meta-analysis by Cavalcante et al. [ 22 ] found that pbNK cell levels were significantly higher in pregnant women with RSA than in pregnant controls (MD 8.21, 95% CI 6.08–10.34; p < 0.00001). Similarly, Kolanska et al. [ 23 ] conducted a meta-analysis demonstrating that pbNK cell proportions were higher in women with RSA (mean difference 3.47, 95% CI 2.94–4.00; p < 0.001) and recurrent implantation failure (RIF) (mean difference 1.64, 95% CI 0.82–2.45; p < 0.001) compared to controls. Adib Rad et al. [ 24 ] reported that pbNK cell levels were higher in women with recurrent miscarriage than in controls, with an AUC of 0.710 for peripheral NK cells CD56 + CD16 + (p = 0.001, 95%CI 0.596–0.824). In summary, our findings suggest that elevated CD16⁺CD56⁺ NK cell levels are an independent risk factor for pregnancy loss with chromosomal abnormalities. In karyotype analyses, 72.6% of chromosomal abnormalities were numerical, primarily non-diploid, while only 4.7% involved structural abnormalities [ 25 ]. CNVs are prevalent in the human genome, ranging in size from a few bases to several megabases [ 26 ]. CNVs are strongly linked to various diseases and contribute to prenatal ultrasound abnormalities, neurodevelopmental disorders, and intellectual disabilities, including epilepsy and autism [ 27 , 28 ]. Colley et al. reported that substructural chromosomal variations, such as small CNVs, along with gene mutations and methylation changes, may contribute to early embryonic miscarriage [ 29 ]. Our findings suggest that miscarriages linked to chromosomal microdeletions are significantly associated with pbNK cell levels. Microdeletions often cause haploinsufficiency of essential genes, disrupting key embryonic developmental pathways. For instance, the 22q11.2 microdeletion, which results in the loss of multiple genes, is associated with heart malformations, immune dysfunction, and neurodevelopmental defects, increasing miscarriage risk [ 30 , 31 ]. Our study further highlights a strong association between pbNK cells and chromosomally abnormal spontaneous abortions. This link may stem from chromosomal abnormalities, such as trisomies or microdeletions, that alter molecular signals (e.g., HLA molecules, heat shock proteins, or stress-related antigens) on embryonic cells. These signals may be identified as threats by the maternal immune system, triggering NK cell activation. The interaction between fetal genomic microdeletions and the maternal immune system remains poorly understood, warranting further investigation into its biological basis and underlying mechanisms. This study has several limitations. First, the small sample size—particularly for microdeletion cases—resulted in insufficient statistical power for subgroup analyses (e.g., across different karyotypes). Moreover, the single-center, retrospective design may limit the generalizability of our findings. Although confounding factors were rigorously adjusted, residual confounding (such as lifestyle and environmental exposures) may not have been fully captured, potentially affecting causal inference. Second, the CNV-seq technique has inherent limitations: it cannot detect balanced translocations or low-level mosaicism, which may lead to missed chromosomal abnormalities. Third, pbNK cell levels can fluctuate with gestational age and circadian rhythms. Although samples were collected between the 4th and 8th weeks of pregnancy, not controlling for these factors might have affected the stability of our results. Finally, the diagnostic performance of pbNK cell levels is modest (AUC = 65.1%, sensitivity = 52.1%), limiting their clinical utility when used alone. Combining pbNK cell levels with other biomarkers may improve predictive accuracy. Future prospective studies with larger and more diverse populations, as well as functional experiments (e.g., cytotoxicity assays, animal models), are essential to confirm these findings and elucidate how pbNK cells mediate embryonic rejection. 5. Conclusion In conclusion, our findings indicate that elevated pbNK cell levels are independent risk factors for chromosomally abnormal spontaneous abortion. Notably, spontaneous abortions resulting from microdeletions exhibit a strong association with increased pbNK cell levels. Additionally, trisomies may serve as potential risk factors for chromosomally abnormal spontaneous abortion. We identified a linear relationship between pbNK cell levels and the risk of chromosomally abnormal spontaneous abortion. However, further experimental studies are necessary to elucidate the mechanisms underlying this association. Abbreviations SA Spontaneous abortions pbNK Peripheral blood natural killer dNK Decidual natural killer CNV-seq Copy number variation sequencing RSA Recurrent spontaneous abortion Declarations Author contributions Junmiao Xiang: Conceptualization, Methodology, Software, Investigation, Formal Analysis, Funding Acquisition, Writing - Original Draft; Yundong Pan: Data Curation, Writing - Original Draft; Qianruo Pan: Visualization, Validation, Writing - Original Draft; Weiya Zhuang: Conceptualization, Resources, Supervision, Writing - Review & Editing. Funding This work was supported by Foundation of Wenzhou Municipal Health Commission (2020041) Data Availability Statement The data collected and analyzed during the current study are available from the corresponding author on reasonable request. Conflict of interest The authors declare that they have no competing interests. Consent for publication Informed consent for publication was obtained and signed by all participants involved in the study. All listed authors have reviewed this manuscript and have given their approval for its publication. Ethics approval The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of The Third Affiliated Hospital of Wenzhou Medical University. References ACOG Practice Bulletin No. 200: Early Pregnancy Loss. Obstet Gynecol. 2018, 132(5):e197-e207. García-Enguídanos A, Calle ME, Valero J, Luna S, Domínguez-Rojas V. Risk factors in miscarriage: a review. Eur J Obstet Gynecol Reprod Biol. 2002;102(2):111–9. Nikitina TV, Lebedev IN. Stem Cell-Based Trophoblast Models to Unravel the Genetic Causes of Human Miscarriages. Cells 2022, 11(12). Xie C, Tammi MT. CNV-seq, a new method to detect copy number variation using high-throughput sequencing. BMC Bioinformatics. 2009;10:80. Liu S, Song L, Cram DS, Xiong L, Wang K, Wu R, Liu J, Deng K, Jia B, Zhong M, et al. Traditional karyotyping vs copy number variation sequencing for detection of chromosomal abnormalities associated with spontaneous miscarriage. Ultrasound Obstet Gynecol. 2015;46(4):472–7. Park SJ, Min JY, Kang JS, Yang BG, Hwang SY, Han SH. Chromosomal abnormalities of 19,000 couples with recurrent spontaneous abortions: a multicenter study. Fertil Steril. 2022;117(5):1015–25. Ander SE, Diamond MS, Coyne CB. Immune responses at the maternal-fetal interface. Sci Immunol 2019, 4(31). Yougbaré I, Tai WS, Zdravic D, Oswald BE, Lang S, Zhu G, Leong-Poi H, Qu D, Yu L, Dunk C, et al. Activated NK cells cause placental dysfunction and miscarriages in fetal alloimmune thrombocytopenia. Nat Commun. 2017;8(1):224. Von Woon E, Greer O, Shah N, Nikolaou D, Johnson M, Male V. Number and function of uterine natural killer cells in recurrent miscarriage and implantation failure: a systematic review and meta-analysis. Hum Reprod Update. 2022;28(4):548–82. Tong X, Gao M, Du X, Lu F, Wu L, Wei H, Fu B. Analysis of uterine CD49a(+) NK cell subsets in menstrual blood reflects endometrial status and association with recurrent spontaneous abortion. Cell Mol Immunol. 2021;18(7):1838–40. Freud AG, Mundy-Bosse BL, Yu J, Caligiuri MA. The Broad Spectrum of Human Natural Killer Cell Diversity. Immunity. 2017;47(5):820–33. Bulmer JN, Lash GE. The Role of Uterine NK Cells in Normal Reproduction and Reproductive Disorders. Adv Exp Med Biol. 2015;868:95–126. King K, Smith S, Chapman M, Sacks G. Detailed analysis of peripheral blood natural killer (NK) cells in women with recurrent miscarriage. Hum Reprod. 2010;25(1):52–8. Aoki K, Kajiura S, Matsumoto Y, Ogasawara M, Okada S, Yagami Y, Gleicher N. Preconceptional natural-killer-cell activity as a predictor of miscarriage. Lancet. 1995;345(8961):1340–2. Kwak JY, Beaman KD, Gilman-Sachs A, Ruiz JE, Schewitz D, Beer AE. Up-regulated expression of CD56+, CD56+/CD16+, and CD19 + cells in peripheral blood lymphocytes in pregnant women with recurrent pregnancy losses. American journal of reproductive immunology (New York, NY : 1989) 1995, 34(2):93–99. Seshadri S, Sunkara SK. Natural killer cells in female infertility and recurrent miscarriage: a systematic review and meta-analysis. Hum Reprod Update. 2014;20(3):429–38. Zhang Y, Yang L, Yang D, Cai S, Wang Y, Wang L, Li Y, Li L, Yin T, Diao L. Understanding the heterogeneity of natural killer cells at the maternal-fetal interface: implications for pregnancy health and disease. Mol Hum Reprod 2024, 30(11). Erlebacher A. Immunology of the maternal-fetal interface. Annu Rev Immunol. 2013;31:387–411. Björkström NK, Ljunggren HG, Michaëlsson J. Emerging insights into natural killer cells in human peripheral tissues. Nat Rev Immunol. 2016;16(5):310–20. Tang AW, Alfirevic Z, Quenby S. Natural killer cells and pregnancy outcomes in women with recurrent miscarriage and infertility: a systematic review. Hum Reprod. 2011;26(8):1971–80. Ou M, Luo L, Yang Y, Yan N, Yan X, Zhong X, Cheong Y, Li T, Ouyang J, Wang Q. Decrease in peripheral natural killer cell level during early pregnancy predicts live birth among women with unexplained recurrent pregnancy loss: a prospective cohort study. American journal of obstetrics and gynecology 2024, 230(6):675.e671-675.e613. Cavalcante MB, da Silva PHA, Carvalho TR, Sampaio OGM, Câmara FEA, Cavalcante C, Barini R, Kwak-Kim J. Peripheral blood natural killer cell cytotoxicity in recurrent miscarriage: a systematic review and meta-analysis. J Reprod Immunol. 2023;158:103956. Kolanska K, Suner L, Cohen J, Ben Kraiem Y, Placais L, Fain O, Bornes M, Selleret L, Delhommeau F, Feger F, et al. Proportion of Cytotoxic Peripheral Blood Natural Killer Cells and T-Cell Large Granular Lymphocytes in Recurrent Miscarriage and Repeated Implantation Failure: Case-Control Study and Meta-analysis. Arch Immunol Ther Exp. 2019;67(4):225–36. Adib Rad H, Basirat Z, Mostafazadeh A, Faramarzi M, Bijani A, Nouri HR, Soleimani Amiri S. Evaluation of peripheral blood NK cell subsets and cytokines in unexplained recurrent miscarriage. J Chin Med Association: JCMA. 2018;81(12):1065–70. Eiben B, Bartels I, Bähr-Porsch S, Borgmann S, Gatz G, Gellert G, Goebel R, Hammans W, Hentemann M, Osmers R, et al. Cytogenetic analysis of 750 spontaneous abortions with the direct-preparation method of chorionic villi and its implications for studying genetic causes of pregnancy wastage. Am J Hum Genet. 1990;47(4):656–63. Lauer S, Gresham D. An evolving view of copy number variants. Curr Genet. 2019;65(6):1287–95. Wang H, Dong Z, Zhang R, Chau MHK, Yang Z, Tsang KYC, Wong HK, Gui B, Meng Z, Xiao K, et al. Low-pass genome sequencing versus chromosomal microarray analysis: implementation in prenatal diagnosis. Genet medicine: official J Am Coll Med Genet. 2020;22(3):500–10. Weiss LA, Shen Y, Korn JM, Arking DE, Miller DT, Fossdal R, Saemundsen E, Stefansson H, Ferreira MA, Green T, et al. Association between microdeletion and microduplication at 16p11.2 and autism. N Engl J Med. 2008;358(7):667–75. Colley E, Hamilton S, Smith P, Morgan NV, Coomarasamy A, Allen S. Potential genetic causes of miscarriage in euploid pregnancies: a systematic review. Hum Reprod Update. 2019;25(4):452–72. Chen CP, Huang JP, Chen YY, Chern SR, Wu PS, Su JW, Chen YT, Chen WL, Wang W. Chromosome 22q11.2 deletion syndrome: prenatal diagnosis, array comparative genomic hybridization characterization using uncultured amniocytes and literature review. Gene. 2013;527(1):405–9. Drozdov GV, Kashevarova AA, Lebedev IN. Copy number variations in spontaneous abortions: a meta-analysis. J Assist Reprod Genet 2025. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 15 May, 2025 Editor invited by journal 25 Apr, 2025 Editor assigned by journal 23 Apr, 2025 Submission checks completed at journal 23 Apr, 2025 First submitted to journal 22 Apr, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6504301","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":456919978,"identity":"14109136-50fe-4499-90ff-3041786e7d1e","order_by":0,"name":"Junmiao Xiang","email":"","orcid":"","institution":"The Third Affiliated Hospital of Wenzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Junmiao","middleName":"","lastName":"Xiang","suffix":""},{"id":456919979,"identity":"c042ef8d-da83-4ba1-b857-c32e94d36172","order_by":1,"name":"Yundong Pan","email":"","orcid":"","institution":"The Third Affiliated Hospital of Wenzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yundong","middleName":"","lastName":"Pan","suffix":""},{"id":456919980,"identity":"53868fd3-8522-478e-9a6f-3559e4f687d9","order_by":2,"name":"Qianruo Pan","email":"","orcid":"","institution":"The Third Affiliated Hospital of Wenzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Qianruo","middleName":"","lastName":"Pan","suffix":""},{"id":456919981,"identity":"69a9af51-6754-45f7-92c0-59c184e41908","order_by":3,"name":"Weiya Zhuang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAvklEQVRIiWNgGAWjYBACefb+jw8+VLAx8xOtxbDngLHhjDN87JINROu5kWAmzdkmx29wgFgdjD0HEqQZ2MykjY8nb2D4UbGNsBZ29oYDxgU8acZmZ54VMPacuU2MLQcbkmdIHEs2u5FjwMzYRoQWhhvJDId5DP7Xb55BvJY0xmaeBDZmAwlitRj2nGFmnHGAjVkC6JeDRPlFnr2H/cfHf8CobE/e+OBHBTEOQ4AE4qMGoYVUHaNgFIyCUTBCAABcPT26vCBYfQAAAABJRU5ErkJggg==","orcid":"","institution":"The Third Affiliated Hospital of Wenzhou Medical University","correspondingAuthor":true,"prefix":"","firstName":"Weiya","middleName":"","lastName":"Zhuang","suffix":""}],"badges":[],"createdAt":"2025-04-22 12:38:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6504301/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6504301/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":83142670,"identity":"56c5f2aa-fdbb-4f0e-a819-1443bc2e9d06","added_by":"auto","created_at":"2025-05-20 12:32:59","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":76988,"visible":true,"origin":"","legend":"\u003cp\u003eRestricted cubic spline shows the association between peripheral blood CD16⁺CD56⁺ NK cells and chromosomally abnormal spontaneous abortion. Data were fit by a logistic regression model based on restricted cubic splines. CD16⁺CD56⁺ NK cells was entered as continuous variable. Data were adjusted for all the factors of model 3 of Table 3. The curves line and shaded areas around depict the estimated values and their corresponding 95% confidence intervals.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6504301/v1/993597745fe99edec816cc89.png"},{"id":83143910,"identity":"eee3ee3a-c429-46b6-adff-414a52e588d7","added_by":"auto","created_at":"2025-05-20 12:40:59","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":149503,"visible":true,"origin":"","legend":"\u003cp\u003eThe area under the receiver operating characteristic (ROC) curve (AUC) for peripheral blood CD16⁺CD56⁺ NK cells in predicting chromosomally abnormal spontaneous abortion was 65.1%, indicating moderate diagnostic accuracy\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6504301/v1/0fd13a09ffc182ff03cd6a11.png"},{"id":83142675,"identity":"f5b8440e-3414-4bb0-9b5c-30a786cbc1e2","added_by":"auto","created_at":"2025-05-20 12:32:59","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":139578,"visible":true,"origin":"","legend":"\u003cp\u003eSubgroup analyses of the association between chromosomally abnormal spontaneous abortion and CD16⁺CD56⁺ NK cells.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6504301/v1/765f7d92402767265aafd552.png"},{"id":83142672,"identity":"62cabb63-5c7a-4a5e-bf52-70c62d24d697","added_by":"auto","created_at":"2025-05-20 12:32:59","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":51436,"visible":true,"origin":"","legend":"\u003cp\u003eBar-scatter plot illustrating the comparison of peripheral blood CD16⁺CD56⁺ natural killer cell levels across different chromosomal abnormalities associated with spontaneous abortion and live birth controls. The analysis revealed significantly higher CD16⁺CD56⁺ NK cell levels in the trisomy, mosaicism, and microdeletion groups than in the control group (P \u0026lt; 0.05).\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6504301/v1/9fd2eba11547516ccd8650bf.png"},{"id":83146206,"identity":"736dcad2-bd01-4385-887f-b955a1799bb5","added_by":"auto","created_at":"2025-05-20 13:05:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1689415,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6504301/v1/b5293a74-fc05-4032-8b3f-2597bf37071f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association Between Peripheral Blood Natural Killer Cells and Chromosomally Abnormal Spontaneous Abortion: A Retrospective Single-Center Study","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eSpontaneous abortion (SA) occurs in approximately 10% of clinically recognized pregnancies, with over 80% of cases in the first trimester [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. SA can result from immunological factors, chromosomal abnormalities, anatomical anomalies, endocrine dysfunction, infections, and male factors [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Embryonic chromosomal abnormalities, occurring during gametogenesis or embryogenesis, are the leading cause of early SA, accounting for 50\u0026ndash;60% of cases [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Chromosomal abnormalities encompass structural aberrations (e.g., deletions, duplications, translocations, and inversions) and numerical anomalies. Recent advancements in next-generation sequencing (NGS) technology have significantly enhanced the detection of aneuploidy and copy number variation sequencing (CNV-seq) in miscarriage tissues, offering improved sensitivity, specificity, and accuracy [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Chromosomal abnormalities are also recognized as a critical factor in recurrent spontaneous abortion (RSA) [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Early prediction of chromosomal abnormality-related miscarriages could prevent unnecessary interventions such as excessive tocolytic therapy. Therefore, identifying predictive biomarkers for embryonic chromosomal abnormalities holds significant clinical value in elucidating the etiology of early spontaneous abortion. The immune system plays a pivotal role in embryo implantation and pregnancy maintenance. Dysregulation of immune responses may lead to maternal immune rejection of the embryo by recognizing it as foreign [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Natural killer (NK) cells, a key component of the innate immune system, constitute 10\u0026ndash;15% of circulating lymphocytes. These cells exhibit potent cytotoxic activity and are essential for establishing immune tolerance and maintaining a functional maternal-fetal interface [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Notably, decidual NK (dNK) cells, characterized by low cytotoxicity and high cytokine-secreting capacity, regulate extravillous trophoblast (EVT) invasion into the decidua and spiral arteries. Abnormal dNK cell distribution may impair EVT-mediated remodeling of uterine vasculature, ultimately compromising embryonic development [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Peripheral blood NK (pbNK) cells, characterized by the expression of CD56 (a neural cell adhesion molecule) and CD16 (FcγRIII), can be subdivided into two distinct subsets. Approximately 90% of peripheral blood NK cells exhibit relatively low CD56 expression levels and are positive for CD16, termed the \"CD16\u003csup\u003e+\u003c/sup\u003eCD56\u003csup\u003e+\u003c/sup\u003edim\" subset. The remaining 10% display high CD56 expression with negative or low CD16 expression (CD16\u003csup\u003e\u0026minus;\u003c/sup\u003eCD56\u003csup\u003e+\u003c/sup\u003ebright) [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. While endometrial sampling is impractical during normal pregnancy, pbNK cells serve as a noninvasive tool for monitoring immune dynamics. Activated pbNK cells are recruited to the endometrium during the mid-secretory phase of the menstrual cycle and early gestation [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. These cells may trigger thrombosis, inflammatory responses, pro-inflammatory cytokine activation, or trophoblast apoptosis, potentially contributing to implantation failure or miscarriage [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Previous studies have demonstrated that RSA patients exhibit significantly elevated pbNK cell percentages and absolute counts compared to women with normal pregnancies [\u003cspan additionalcitationids=\"CR14 CR15\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. This elevation may reflect maternal immune hyperactivation, leading to embryo rejection. For instance, Kim et al. [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] reported markedly higher pbNK cell percentages in RSA patients versus controls (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with a pbNK cell threshold\u0026thinsp;\u0026gt;\u0026thinsp;18% demonstrating high specificity for distinguishing RSA cases, suggesting its utility as a diagnostic marker.\u003c/p\u003e \u003cp\u003eWhile elevated pbNK cell levels have been linked to adverse pregnancy outcomes, their role in miscarriages caused by chromosomal abnormalities remains unclear. This study examines the relationship between the CD16\u003csup\u003e+\u003c/sup\u003eCD56\u003csup\u003e+\u003c/sup\u003edim subset of pbNK cells and chromosomally abnormal spontaneous abortion, including different abnormal karyotypes. Additionally, it explores whether pbNK cell levels can serve as a predictor of pregnancy outcomes.\u003c/p\u003e"},{"header":"2. Material and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Patient Population\u003c/h2\u003e \u003cp\u003eThis retrospective study included 1250 patients with ultrasound-confirmed intrauterine pregnancies at The Third Affiliated Hospital of Wenzhou Medical University from January 2017 to September 2023. Among these, 294 patients who experienced early spontaneous abortion before 12 weeks and underwent uterine evacuation\u0026mdash;with tissue collected for CNV-seq analysis\u0026mdash;formed the SA group. Additionally, 956 patients with live births, defined as delivery at or after 28 weeks, served as controls. Exclusion criteria comprised incomplete clinical records, systemic comorbidities, insufficient follow-up data, severe infections, or reproductive system malformations. Spontaneous abortions were classified as chromosomally normal if CNV-seq results were normal and as chromosomally abnormal if the results were abnormal. The study was approved by the Research Ethics Committee of The Third Affiliated Hospital of Wenzhou Medical University, and all participants provided informed consent.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Clinical features record\u003c/h2\u003e \u003cp\u003eThe study\u0026rsquo;s demographic and clinical data\u0026mdash;including age, body mass index (BMI), reproductive history, and pregnancy follow-up\u0026mdash;were collected from medical records and telephone follow-ups.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Coagulation and biochemical indicators measurements\u003c/h2\u003e \u003cp\u003eWe used a TCA-6000 thromboelastometer (Shengyu Corporation, China) to measure thrombelastogram (TEG) parameters, including reaction time (R), clot formation time (K), maximum amplitude (MA), and clot formation rate (α-angle). Standard coagulation tests\u0026mdash;international normalized ratio (INR), fibrinogen (FIB), thrombin time (TT), prothrombin time (PT), activated partial thromboplastin time (APTT), and D-dimer levels\u0026mdash;were assessed using a STA-R MAX coagulation analyzer (France). In addition, levels of triiodothyronine (T3), thyroxine (T4), thyroid stimulating hormone (TSH), fasting blood glucose (FBG), 25-hydroxyvitamin D (25(OH)D), homocysteine (Hcy), total cholesterol (TC), triglycerides (TG), and uric acid (UA) were measured using a Siemens IM1600 chemiluminescence assay.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Immune biomarker measurements\u003c/h2\u003e \u003cp\u003eLymphocyte subpopulations were analyzed using a BD FACSCanto II flow cytometer to measure CD16⁺CD56⁺ natural killer (pbNK) cells, CD19⁺ B lymphocytes, CD3⁺ T lymphocytes, CD4⁺ T lymphocytes, and CD8⁺ T lymphocytes. Complement components C3 and C4 were quantified by rate nephelometry using a Siemens CH930 automatic biochemical analyzer (Shanghai, China). Antinuclear antibody (ANA) titers were determined by indirect immunofluorescence on Hep-2 cells, with a positive result defined as a titer of 1:160 or greater. Additionally, IgG, IgA, and IgM isotypes of anticardiolipin (aCL) and anti-β2-glycoprotein I (aβ2GP1) antibodies were measured using iFlash CLIA kits (YHLO Biotech Co., Shenzhen, China), with cut-off values of 12 U/mL for aCL and 24 U/mL for aβ2GP1. All assays were performed by experienced technicians following the manufacturers\u0026rsquo; protocols. Blood samples for these tests were collected from pregnant women between the 4th and 8th weeks of pregnancy.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Statistical analysis\u003c/h2\u003e \u003cp\u003eThe Shapiro\u0026ndash;Wilk test assessed data normality. Normally distributed continuous variables are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (X\u0026thinsp;\u0026plusmn;\u0026thinsp;SD), while non-normally distributed variables are presented as medians (Q1, Q3). Categorical data are reported as counts and proportions. For comparisons among three groups, the Kruskal\u0026ndash;Wallis test was employed, followed by pairwise comparisons using the Mann\u0026ndash;Whitney U test with Bonferroni correction to adjust for multiple testing. Proportions were compared using the χ\u0026sup2; test. Multivariate-adjusted models evaluated the association between pbNK cells and chromosomally abnormal spontaneous abortion incidence. Variables for adjustment were selected based on a\u0026thinsp;\u0026gt;\u0026thinsp;10% change in the effect estimate or a clinically significant association. The unadjusted model was followed by adjustments for age, BMI, pregnancy history, and previous miscarriage in Model 1; Model 1 was expanded to include C3, C4, T3, T4, FIB, and Hcy in Model 2; and Model 2 was further adjusted for CD19⁺ B cells, CD3⁺ T cells, and CD4⁺ T cells in Model 3. To compare the association between pbNK cells and all abnormal fetal tissue chromosome karyotypes, multivariate-adjusted models were used as unadjusted models and adjustments as in Model 3. Results are presented as odds ratios (OR) with 95% confidence intervals (CI). Receiver operating characteristic (ROC) curves assessed the diagnostic accuracy of pbNK cells, with the area under the curve (AUC) quantifying performance. Non-linearity was assessed using a likelihood ratio test to compare the model with only a linear term against the model including both linear and cubic spline terms. Subgroup analyses were also conducted. PbNK cells were treated as a categorical variable, while continuous variables were transformed into categorical variables based on clinically established cut-off points or median values. Interaction effects among subgroups were assessed using the likelihood ratio test. Statistical analyses were performed using R software (version 4.2.2; The R Foundation, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.R-project.org\u003c/span\u003e\u003cspan address=\"http://www.R-project.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), SPSS Statistics (version 22.0; IBM Corp., Armonk, NY), and Free Statistics (version 1.9; Beijing, China, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.clinicalscientists.cn/freestatistics\u003c/span\u003e\u003cspan address=\"http://www.clinicalscientists.cn/freestatistics\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). All tests were two-tailed, with a P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Clinical characteristics of the study participants\u003c/h2\u003e \u003cp\u003eThe study included 1250 participants, categorized into three groups: 106 in the chromosomally normal spontaneous abortion group, 188 in the chromosomally abnormal spontaneous abortion group, and 956 in the live birth group. Significant differences were observed among the three groups in pregnancy history, previous miscarriage, Hcy, TC, FIB, C3 and C4, T3, T4, pbNK cells, CD19⁺ B cells, CD3⁺ T cells, and CD4⁺ T cells. Comparisons between the chromosomally abnormal spontaneous abortion group and the live birth group revealed significant differences in previous miscarriage, Hcy, FIB, C3, C4, T3, T4, pbNK cells, CD19⁺ B cells, CD3⁺ T cells, and CD4⁺ T cells. Notably, pbNK cells were the only parameter that differed significantly between the chromosomally abnormal spontaneous abortion group and both the chromosomally normal spontaneous abortion and live birth groups. However, no significant difference in pbNK cells was observed between the chromosomally normal spontaneous abortion group and the live birth group (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline demographic characteristics and laboratory indicators of the study population\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal (n\u0026thinsp;=\u0026thinsp;1250)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChromosomally normal spontaneous abortion (n\u0026thinsp;=\u0026thinsp;106)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eChromosomally abnormal spontaneous abortion (n\u0026thinsp;=\u0026thinsp;188)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLive birth controls (n\u0026thinsp;=\u0026thinsp;956)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29.24\u0026thinsp;\u0026plusmn;\u0026thinsp;8.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.82\u0026thinsp;\u0026plusmn;\u0026thinsp;25.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29.81\u0026thinsp;\u0026plusmn;\u0026thinsp;4.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28.96\u0026thinsp;\u0026plusmn;\u0026thinsp;4.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.068\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21.47\u0026thinsp;\u0026plusmn;\u0026thinsp;3.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.68\u0026thinsp;\u0026plusmn;\u0026thinsp;2.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.21\u0026thinsp;\u0026plusmn;\u0026thinsp;2.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21.49\u0026thinsp;\u0026plusmn;\u0026thinsp;3.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.395\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePregnancy history\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNulliparous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e859 (68.72%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e88 (83.02%) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e132 (70.21%) \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e639 (66.84%) \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiparous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e391 (31.28%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (16.98%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56 (29.79%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e317 (33.16%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrevious miscarriage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e479 (38.32%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64 (60.38%) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e110 (58.51%) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e305 (31.9%) \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e403 (32.24%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (17.92%) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45 (23.94%) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e339 (35.46%) \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e213 (17.04%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (11.32%) \u003csup\u003ea, b\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16 (8.51%) \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e185 (19.35%) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge; 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e155 (12.40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (10.38%) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17 (9.04%) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e127 (13.28%) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFBG (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.90\u0026thinsp;\u0026plusmn;\u0026thinsp;1.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.74\u0026thinsp;\u0026plusmn;\u0026thinsp;0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.74\u0026thinsp;\u0026plusmn;\u0026thinsp;0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.266\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUA (\u0026micro;mol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e248.68\u0026thinsp;\u0026plusmn;\u0026thinsp;62.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e256.67\u0026thinsp;\u0026plusmn;\u0026thinsp;50.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e253.65\u0026thinsp;\u0026plusmn;\u0026thinsp;58.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e246.82\u0026thinsp;\u0026plusmn;\u0026thinsp;64.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.151\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25(OH)D (ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.02\u0026thinsp;\u0026plusmn;\u0026thinsp;7.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.84\u0026thinsp;\u0026plusmn;\u0026thinsp;9.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.80\u0026thinsp;\u0026plusmn;\u0026thinsp;7.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20.09\u0026thinsp;\u0026plusmn;\u0026thinsp;7.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.856\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHcy (\u0026micro;mol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.28\u0026thinsp;\u0026plusmn;\u0026thinsp;1.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.78\u0026thinsp;\u0026plusmn;\u0026thinsp;1.91\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.56\u0026thinsp;\u0026plusmn;\u0026thinsp;1.81\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.17\u0026thinsp;\u0026plusmn;\u0026thinsp;1.43\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTC (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.97\u0026thinsp;\u0026plusmn;\u0026thinsp;0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.67\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.75\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTG (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.386\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePT (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.69\u0026thinsp;\u0026plusmn;\u0026thinsp;0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.63\u0026thinsp;\u0026plusmn;\u0026thinsp;0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.69\u0026thinsp;\u0026plusmn;\u0026thinsp;0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.378\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTT (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.34\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.54\u0026thinsp;\u0026plusmn;\u0026thinsp;1.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.31\u0026thinsp;\u0026plusmn;\u0026thinsp;1.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.164\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAPTT (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28.20\u0026thinsp;\u0026plusmn;\u0026thinsp;3.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.62\u0026thinsp;\u0026plusmn;\u0026thinsp;3.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.50\u0026thinsp;\u0026plusmn;\u0026thinsp;3.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28.09\u0026thinsp;\u0026plusmn;\u0026thinsp;3.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.121\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eINR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.99\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.99\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.98\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.99\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.338\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFIB (g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.94\u0026thinsp;\u0026plusmn;\u0026thinsp;0.58\u003csup\u003ea, b\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.84\u0026thinsp;\u0026plusmn;\u0026thinsp;0.59\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.97\u0026thinsp;\u0026plusmn;\u0026thinsp;0.68\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD-dimer (ug/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.24 (0.16, 0.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.22 (0.16, 0.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.24 (0.16, 0.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.25 (0.17, 0.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.251\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eaPLs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.526\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1204 (96.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e102 (96.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e184 (97.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e918 (96%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46 (3.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (3.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (2.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e38 (4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eANAs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.452\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1112 (88.96%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95 (89.62%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e172 (91.49%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e845 (88.39%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e138 (11.04%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (10.38%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16 (8.51%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e111 (11.61%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR (min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.62\u0026thinsp;\u0026plusmn;\u0026thinsp;1.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.48\u0026thinsp;\u0026plusmn;\u0026thinsp;1.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.69\u0026thinsp;\u0026plusmn;\u0026thinsp;1.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.62\u0026thinsp;\u0026plusmn;\u0026thinsp;2.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.666\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eK (min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.951\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eα-Angle (deg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71.03\u0026thinsp;\u0026plusmn;\u0026thinsp;5.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71.06\u0026thinsp;\u0026plusmn;\u0026thinsp;4.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70.63\u0026thinsp;\u0026plusmn;\u0026thinsp;4.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e71.10\u0026thinsp;\u0026plusmn;\u0026thinsp;5.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.506\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMA (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66.01\u0026thinsp;\u0026plusmn;\u0026thinsp;4.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66.25\u0026thinsp;\u0026plusmn;\u0026thinsp;4.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65.70\u0026thinsp;\u0026plusmn;\u0026thinsp;4.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e66.04\u0026thinsp;\u0026plusmn;\u0026thinsp;4.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC3 (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.31\u0026thinsp;\u0026plusmn;\u0026thinsp;2.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.35\u0026thinsp;\u0026plusmn;\u0026thinsp;1.76\u003csup\u003ea, b\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.79\u0026thinsp;\u0026plusmn;\u0026thinsp;1.74\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.41\u0026thinsp;\u0026plusmn;\u0026thinsp;2.07\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC4 (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.64\u003csup\u003ea, b\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.96\u0026thinsp;\u0026plusmn;\u0026thinsp;0.53\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.74\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT3 (nmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.71\u0026thinsp;\u0026plusmn;\u0026thinsp;0.40\u003csup\u003ea, b\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.63\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.78\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT4 (nmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e120.89\u0026thinsp;\u0026plusmn;\u0026thinsp;29.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e118.31\u0026thinsp;\u0026plusmn;\u0026thinsp;31.53\u003csup\u003ea, b\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e110.42\u0026thinsp;\u0026plusmn;\u0026thinsp;22.45\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e123.23\u0026thinsp;\u0026plusmn;\u0026thinsp;29.46\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTSH (mIU/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.65 (1.04, 2.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.80 (1.19, 2.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.73 (1.13, 2.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.62 (1.02, 2.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.089\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD16⁺CD56⁺ NK cells (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.22\u0026thinsp;\u0026plusmn;\u0026thinsp;7.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.78\u0026thinsp;\u0026plusmn;\u0026thinsp;7.43\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.46\u0026thinsp;\u0026plusmn;\u0026thinsp;8.00\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.53\u0026thinsp;\u0026plusmn;\u0026thinsp;7.08\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD19\u003csup\u003e+\u003c/sup\u003e B cells (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.29\u0026thinsp;\u0026plusmn;\u0026thinsp;4.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.94\u0026thinsp;\u0026plusmn;\u0026thinsp;4.03\u003csup\u003ea, b\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.90\u0026thinsp;\u0026plusmn;\u0026thinsp;3.49\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.60\u0026thinsp;\u0026plusmn;\u0026thinsp;4.29\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD3\u003csup\u003e+\u003c/sup\u003e T cells (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72.49\u0026thinsp;\u0026plusmn;\u0026thinsp;7.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72.24\u0026thinsp;\u0026plusmn;\u0026thinsp;7.13\u003csup\u003ea, b\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70.72\u0026thinsp;\u0026plusmn;\u0026thinsp;7.42\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e72.86\u0026thinsp;\u0026plusmn;\u0026thinsp;7.07\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD4\u003csup\u003e+\u003c/sup\u003eT cells (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38.58\u0026thinsp;\u0026plusmn;\u0026thinsp;7.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37.59\u0026thinsp;\u0026plusmn;\u0026thinsp;7.06\u003csup\u003ea, b\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35.98\u0026thinsp;\u0026plusmn;\u0026thinsp;5.92\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e39.21\u0026thinsp;\u0026plusmn;\u0026thinsp;7.32\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD8\u003csup\u003e+\u003c/sup\u003e T cells (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27.72\u0026thinsp;\u0026plusmn;\u0026thinsp;6.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.65\u0026thinsp;\u0026plusmn;\u0026thinsp;6.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.94\u0026thinsp;\u0026plusmn;\u0026thinsp;5.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27.58\u0026thinsp;\u0026plusmn;\u0026thinsp;6.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.192\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eBMI: body mass index; FBG: fasting blood glucose; UA: uric acid; 25(OH)D: 25-hydroxyvitamin D; Hcy: homocysteine; TC: total cholesterol; TG: triglycerides; PT: prothrombin time; TT: thrombin time; APTT: activated partial thromboplastin time; INR: international normalized ratio; FIB: Fibrinogen; aPLs: antiphospholipid antibodies; ANAs: antinuclear antibodies; R: reaction time; K: clot formation time; MA: maximum amplitude; α-angle: clot formation rate; C3: complement C3; C4: complement C4; T3: triiodothyronine; T4: thyroxine; TSH: thyroid stimulating hormone; CD16⁺CD56⁺ NK cells: CD16⁺CD56⁺ natural killer cells; CD19\u003csup\u003e+\u003c/sup\u003e B cells: CD19\u003csup\u003e+\u003c/sup\u003e B lymphocytes; CD3\u003csup\u003e+\u003c/sup\u003e T cells: T lymphocytes; CD4\u003csup\u003e+\u003c/sup\u003e T cells: CD4\u003csup\u003e+\u003c/sup\u003e T lymphocytes; CD8\u003csup\u003e+\u003c/sup\u003e T cells: CD8\u003csup\u003e+\u003c/sup\u003e T lymphocytes; Different letters(a, b) indicate significant differences between groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05);\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Associated between pbNK cell levels and chromosomally abnormal spontaneous abortion\u003c/h2\u003e \u003cp\u003eUnivariate logistic regression analysis indicated that age, Hcy, and pbNK cells were positively associated with an increased risk of chromosomally abnormal spontaneous abortion. In contrast, previous miscarriage, FIB, C3, C4, T3, T4, CD19⁺ B cells, CD3⁺ T cells, and CD4⁺ T cells were negatively associated with this risk (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Multivariate regression analysis (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e3\u003c/span\u003e) further confirmed a significant positive association between pbNK cell levels and the risk of chromosomally abnormal spontaneous abortion across all four models. In the unadjusted model, an increase in pbNK cells was significantly associated with a higher risk of chromosomally abnormal spontaneous abortion (OR\u0026thinsp;=\u0026thinsp;1.068; 95% CI: 1.047\u0026ndash;1.089; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In the fully adjusted Model 3, the OR remained significant at 1.363 (95% CI: 1.033\u0026ndash;1.797). For further analysis, pbNK cell levels were categorized into quartiles. Using the first quartile as the reference, the OR for the highest quartile in Model 3 was 4.123 (95% CI: 1.419\u0026ndash;11.976), demonstrating a significant increasing trend (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariable analysis of covariates associated with chromosomally abnormal spontaneous abortion compared to live birth controls\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.042 (1.007\u0026thinsp;~\u0026thinsp;1.079)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.97 (0.921\u0026thinsp;~\u0026thinsp;1.022)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.256\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePregnancy history\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNulliparous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiparous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.855 (0.609\u0026thinsp;~\u0026thinsp;1.202)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.3676\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrevious miscarriage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.368 (0.252\u0026thinsp;~\u0026thinsp;0.538)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.24 (0.138\u0026thinsp;~\u0026thinsp;0.418)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge; 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.371 (0.214\u0026thinsp;~\u0026thinsp;0.644)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT3 (nmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.323 (0.199\u0026thinsp;~\u0026thinsp;0.525)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT4 (nmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.98 (0.973\u0026thinsp;~\u0026thinsp;0.987)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFIB (g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.718 (0.556\u0026thinsp;~\u0026thinsp;0.927)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHcy (\u0026micro;mol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.159 (1.056\u0026thinsp;~\u0026thinsp;1.273)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC3 (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.188 (0.079\u0026thinsp;~\u0026thinsp;0.445)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC4 (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.015 (0.001\u0026thinsp;~\u0026thinsp;0.178)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD16⁺CD56⁺ NK cells (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.068 (1.047\u0026thinsp;~\u0026thinsp;1.089)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD19\u003csup\u003e+\u003c/sup\u003e B cells (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.898 (0.861\u0026thinsp;~\u0026thinsp;0.937)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD3\u003csup\u003e+\u003c/sup\u003e T cells (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.961 (0.94\u0026thinsp;~\u0026thinsp;0.981)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD4\u003csup\u003e+\u003c/sup\u003e T cells (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.937 (0.916\u0026thinsp;~\u0026thinsp;0.959)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eBMI: body mass index; T3: triiodothyronine; T4: thyroxine; FIB: Fibrinogen; Hcy: homocysteine; C3: complement C3; C4: complement C4; CD16⁺CD56⁺ NK cells: CD16⁺CD56⁺ natural killer cells; CD19\u003csup\u003e+\u003c/sup\u003e B cells: CD19\u003csup\u003e+\u003c/sup\u003e B lymphocytes; CD3\u003csup\u003e+\u003c/sup\u003e T cells: T lymphocytes; CD4\u003csup\u003e+\u003c/sup\u003e T cells: CD4\u003csup\u003e+\u003c/sup\u003e T lymphocytes;\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation of peripheral blood CD16⁺CD56⁺ NK cell levels with chromosomally abnormal spontaneous abortion across unadjusted and adjusted models compared with live birth controls\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCrude Model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eModel 3\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-Value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-Value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-Value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-Value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD16⁺CD56⁺ NK cells\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.068 (1.047\u0026thinsp;~\u0026thinsp;1.089)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.064 (1.042\u0026thinsp;~\u0026thinsp;1.086)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.062 (1.039\u0026thinsp;~\u0026thinsp;1.085)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.363 (1.033\u0026thinsp;~\u0026thinsp;1.797)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.029\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD16⁺CD56⁺ NK cells, per SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.621 (1.4\u0026thinsp;~\u0026thinsp;1.877)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.582 (1.358\u0026thinsp;~\u0026thinsp;1.844)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.557 (1.326\u0026thinsp;~\u0026thinsp;1.827)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9.805 (1.269\u0026thinsp;~\u0026thinsp;75.739)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.029\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD16⁺CD56⁺ NK cells (quartile)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1(Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1(Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1(Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.512 (0.877\u0026thinsp;~\u0026thinsp;2.607)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.137\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.496 (0.856\u0026thinsp;~\u0026thinsp;2.614)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.33 (0.745\u0026thinsp;~\u0026thinsp;2.373)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.3348\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.346 (0.724\u0026thinsp;~\u0026thinsp;2.504)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.348\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.983 (1.173\u0026thinsp;~\u0026thinsp;3.355)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.91 (1.115\u0026thinsp;~\u0026thinsp;3.272)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0185\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.838 (1.054\u0026thinsp;~\u0026thinsp;3.208)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.879 (0.909\u0026thinsp;~\u0026thinsp;3.885)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.089\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.34 (2.658\u0026thinsp;~\u0026thinsp;7.085)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.122 (2.491\u0026thinsp;~\u0026thinsp;6.821)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.849 (2.281\u0026thinsp;~\u0026thinsp;6.496)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.123 (1.419\u0026thinsp;~\u0026thinsp;11.976)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP for trend\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eCrude model: adjusted for none.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eModel 1: Adjusted for Age, BMI, pregnancy history and previous miscarriage.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eModel 2: Adjusted for the variables in Model 1 plus C3, C4, T3, T4, FIB and Hcy.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eModel 3: Adjusted for the variables in Model 2 plus CD19\u003csup\u003e+\u003c/sup\u003e B cells, CD3\u003csup\u003e+\u003c/sup\u003e T cells and CD4\u003csup\u003e+\u003c/sup\u003e T cells\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eBMI: body mass index; T3: triiodothyronine; T4: thyroxine; FIB: Fibrinogen; Hcy: homocysteine; C3: complement C3; C4: complement C4; CD16⁺CD56⁺ NK cells: CD16⁺CD56⁺ natural killer cells; CD19\u003csup\u003e+\u003c/sup\u003e B cells: CD19\u003csup\u003e+\u003c/sup\u003e B lymphocytes; CD3\u003csup\u003e+\u003c/sup\u003e T cells: T lymphocytes; CD4\u003csup\u003e+\u003c/sup\u003e T cells: CD4\u003csup\u003e+\u003c/sup\u003e T lymphocytes;\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.3 ROC diagnostic performance of pbNK cells\u003c/h2\u003e \u003cp\u003eROC analysis was used to evaluate the diagnostic accuracy of pbNK cells in distinguishing live births from chromosomally abnormal spontaneous abortions. The AUC was 65.1, reflecting moderate diagnostic performance. At a cutoff value of 16.1, the sensitivity was 52.1% and the specificity was 74.8% (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Nonlinear relationship between pbNK cells and chromosomally abnormal spontaneous abortion\u003c/h2\u003e \u003cp\u003eAfter adjusting for covariates, restricted cubic spline (RCS) analysis indicated a linear association between pbNK cell levels and the risk of chromosomally abnormal spontaneous abortion (P for non-linearity\u0026thinsp;=\u0026thinsp;0.388) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Subgroup analyses\u003c/h2\u003e \u003cp\u003eStratified analysis was conducted to examine the relationship between pbNK cell levels and chromosomally abnormal spontaneous abortion across various subgroups. No significant associations were observed when stratified by age, BMI, pregnancy history, previous miscarriage, Hcy, CD19⁺ B cells, CD3⁺ T cells, CD4⁺ T cells, ANAs, or aPLs (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.6 Associated between pbNK cell levels and all abnormal foetal tissue chromosome karyotypes\u003c/h2\u003e \u003cp\u003eAmong the seven chromosome karyotypes, pbNK cell levels were significantly higher in cases of trisomy (16.88\u0026thinsp;\u0026plusmn;\u0026thinsp;7.95), mosaicism (28.13\u0026thinsp;\u0026plusmn;\u0026thinsp;7.32), and microdeletion (19.62\u0026thinsp;\u0026plusmn;\u0026thinsp;7.44) compared to the live birth controls (13.22\u0026thinsp;\u0026plusmn;\u0026thinsp;7.38) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). In the unadjusted model, significant associations were found for trisomy (OR\u0026thinsp;=\u0026thinsp;1.073; 95% CI: 1.048\u0026ndash;1.098; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), mosaicism (OR\u0026thinsp;=\u0026thinsp;1.196; 95% CI: 1.067\u0026ndash;1.34; P\u0026thinsp;=\u0026thinsp;0.002), and microdeletion (OR\u0026thinsp;=\u0026thinsp;1.104; 95% CI: 1.04\u0026ndash;1.172; P\u0026thinsp;=\u0026thinsp;0.001) with pbNK cell levels. In the fully adjusted Model 3, only the OR for microdeletion with pbNK cell levels remained significant (OR\u0026thinsp;=\u0026thinsp;10.807; 95% CI: 2.627\u0026ndash;44.455), whereas trisomy did not reach significance (OR\u0026thinsp;=\u0026thinsp;1.37; 95% CI: 0.977\u0026ndash;1.922; P\u0026thinsp;=\u0026thinsp;0.068) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation of peripheral blood CD16⁺CD56⁺ NK cell levels with different abnormal spontaneous abortion chromosome karyotypes across unadjusted and fully adjusted models compared with live birth controls\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eCrude Model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eFully adjusted model\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChromosome karyotypes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTriploid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30 (3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.037 (0.991\u0026thinsp;~\u0026thinsp;1.085)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.516 (0.766\u0026thinsp;~\u0026thinsp;3.002)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.232\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrisomy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e115 (10.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.073 (1.048\u0026thinsp;~\u0026thinsp;1.098)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.37 (0.977\u0026thinsp;~\u0026thinsp;1.922)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.068\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMosaicism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (0.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.196 (1.067\u0026thinsp;~\u0026thinsp;1.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.579 (0.158\u0026thinsp;~\u0026thinsp;15.769)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.697\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45, X\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (1.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.044 (0.988\u0026thinsp;~\u0026thinsp;1.103)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.138 (0.449\u0026thinsp;~\u0026thinsp;2.884)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.785\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMicroduplication\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.017 (0.892\u0026thinsp;~\u0026thinsp;1.158)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.805\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.39 (0.109\u0026thinsp;~\u0026thinsp;1.403)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.150\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMicrodeletion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (1.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.104 (1.04\u0026thinsp;~\u0026thinsp;1.172)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.807 (2.627\u0026thinsp;~\u0026thinsp;44.455)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUniparental disomy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (0.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.973 (0.848\u0026thinsp;~\u0026thinsp;1.117)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.699\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.661 (0.191\u0026thinsp;~\u0026thinsp;2.284)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.513\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eCrude model: adjusted for none.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eFully adjusted model: Adjusted for Age, BMI, pregnancy history, previous miscarriage, C3, C4, T3, T4, FIB, Hcy, CD19\u0026thinsp;+\u0026thinsp;B cells, CD3\u0026thinsp;+\u0026thinsp;T cells and CD4\u0026thinsp;+\u0026thinsp;T cells\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eOur study indicates that a higher proportion of peripheral CD16⁺CD56⁺ natural killer cells among lymphocytes is correlated with an increased risk of chromosomally abnormal spontaneous abortion, with moderate diagnostic performance (AUC\u0026thinsp;=\u0026thinsp;65.1). RCS and subgroup analyses further confirmed a stable, linear association between pbNK cell levels and chromosomally abnormal spontaneous abortion. Karyotype analysis revealed that both microdeletions and trisomies are associated with elevated pbNK cell levels. Notably, microdeletions were consistently associated with a higher risk of chromosomal abnormality-related miscarriage in both unadjusted and fully adjusted models.\u003c/p\u003e \u003cp\u003eThe stability of NK cells is crucial for a successful pregnancy. These cells constitute 10\u0026ndash;15% of peripheral blood lymphocytes and 70\u0026ndash;90% of uterine lymphocytes[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Their proportion, quantity, and activity are implicated in pregnancy complications such as fetal loss, preeclampsia, preterm birth, and congenital infections[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Unlike the resident decidual NK (dNK) cells, which are primarily CD16⁻CD56⁺bright, most peripheral blood NK cells exhibit a CD16⁺CD56⁺dim phenotype, characterized by higher cytotoxicity and lower cytokine secretion[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Studies suggest that peripheral CD16⁺CD56⁺bright NK cells and hematopoietic progenitors are recruited to the decidua during pregnancy and differentiate into dNK cells upon exposure to the local microenvironment[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. These maternal immune cells interact with decidual stromal cells and extravillous trophoblasts (EVTs), shaping a highly complex immune microenvironment [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eEarly studies had limited sample sizes, making it difficult to determine whether elevated pbNK cell percentages or activity predicted miscarriage in women with RSA (n\u0026thinsp;=\u0026thinsp;32, OR 17, 95% CI 0.82\u0026ndash;350.6; activity: n\u0026thinsp;=\u0026thinsp;92, OR 2.51, 95% CI 0.16\u0026ndash;40.29) [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. However, subsequent research has increasingly linked pbNK cells to pregnancy loss. Qiong Wang et al. [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] reported that women with lower pbNK levels during pregnancy had significantly higher live birth rates compared to those without such a reduction. A meta-analysis by Cavalcante et al. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] found that pbNK cell levels were significantly higher in pregnant women with RSA than in pregnant controls (MD 8.21, 95% CI 6.08\u0026ndash;10.34; p\u0026thinsp;\u0026lt;\u0026thinsp;0.00001). Similarly, Kolanska et al. [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] conducted a meta-analysis demonstrating that pbNK cell proportions were higher in women with RSA (mean difference 3.47, 95% CI 2.94\u0026ndash;4.00; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and recurrent implantation failure (RIF) (mean difference 1.64, 95% CI 0.82\u0026ndash;2.45; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) compared to controls. Adib Rad et al. [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] reported that pbNK cell levels were higher in women with recurrent miscarriage than in controls, with an AUC of 0.710 for peripheral NK cells CD56\u003csup\u003e+\u003c/sup\u003eCD16\u003csup\u003e+\u003c/sup\u003e (p\u0026thinsp;=\u0026thinsp;0.001, 95%CI 0.596\u0026ndash;0.824). In summary, our findings suggest that elevated CD16⁺CD56⁺ NK cell levels are an independent risk factor for pregnancy loss with chromosomal abnormalities.\u003c/p\u003e \u003cp\u003eIn karyotype analyses, 72.6% of chromosomal abnormalities were numerical, primarily non-diploid, while only 4.7% involved structural abnormalities [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. CNVs are prevalent in the human genome, ranging in size from a few bases to several megabases [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. CNVs are strongly linked to various diseases and contribute to prenatal ultrasound abnormalities, neurodevelopmental disorders, and intellectual disabilities, including epilepsy and autism [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Colley et al. reported that substructural chromosomal variations, such as small CNVs, along with gene mutations and methylation changes, may contribute to early embryonic miscarriage [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Our findings suggest that miscarriages linked to chromosomal microdeletions are significantly associated with pbNK cell levels. Microdeletions often cause haploinsufficiency of essential genes, disrupting key embryonic developmental pathways. For instance, the 22q11.2 microdeletion, which results in the loss of multiple genes, is associated with heart malformations, immune dysfunction, and neurodevelopmental defects, increasing miscarriage risk [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Our study further highlights a strong association between pbNK cells and chromosomally abnormal spontaneous abortions. This link may stem from chromosomal abnormalities, such as trisomies or microdeletions, that alter molecular signals (e.g., HLA molecules, heat shock proteins, or stress-related antigens) on embryonic cells. These signals may be identified as threats by the maternal immune system, triggering NK cell activation. The interaction between fetal genomic microdeletions and the maternal immune system remains poorly understood, warranting further investigation into its biological basis and underlying mechanisms.\u003c/p\u003e \u003cp\u003eThis study has several limitations. First, the small sample size\u0026mdash;particularly for microdeletion cases\u0026mdash;resulted in insufficient statistical power for subgroup analyses (e.g., across different karyotypes). Moreover, the single-center, retrospective design may limit the generalizability of our findings. Although confounding factors were rigorously adjusted, residual confounding (such as lifestyle and environmental exposures) may not have been fully captured, potentially affecting causal inference. Second, the CNV-seq technique has inherent limitations: it cannot detect balanced translocations or low-level mosaicism, which may lead to missed chromosomal abnormalities. Third, pbNK cell levels can fluctuate with gestational age and circadian rhythms. Although samples were collected between the 4th and 8th weeks of pregnancy, not controlling for these factors might have affected the stability of our results. Finally, the diagnostic performance of pbNK cell levels is modest (AUC\u0026thinsp;=\u0026thinsp;65.1%, sensitivity\u0026thinsp;=\u0026thinsp;52.1%), limiting their clinical utility when used alone. Combining pbNK cell levels with other biomarkers may improve predictive accuracy. Future prospective studies with larger and more diverse populations, as well as functional experiments (e.g., cytotoxicity assays, animal models), are essential to confirm these findings and elucidate how pbNK cells mediate embryonic rejection.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eIn conclusion, our findings indicate that elevated pbNK cell levels are independent risk factors for chromosomally abnormal spontaneous abortion. Notably, spontaneous abortions resulting from microdeletions exhibit a strong association with increased pbNK cell levels. Additionally, trisomies may serve as potential risk factors for chromosomally abnormal spontaneous abortion. We identified a linear relationship between pbNK cell levels and the risk of chromosomally abnormal spontaneous abortion. However, further experimental studies are necessary to elucidate the mechanisms underlying this association.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eSA Spontaneous abortions\u003c/p\u003e \u003cp\u003epbNK Peripheral blood natural killer\u003c/p\u003e \u003cp\u003edNK Decidual natural killer\u003c/p\u003e \u003cp\u003eCNV-seq Copy number variation sequencing\u003c/p\u003e \u003cp\u003eRSA Recurrent spontaneous abortion\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJunmiao Xiang: Conceptualization, Methodology, Software, Investigation, Formal Analysis, Funding Acquisition, Writing - Original Draft;\u0026nbsp;Yundong Pan: Data Curation, Writing - Original Draft; Qianruo Pan: Visualization, Validation, Writing - Original Draft; Weiya Zhuang: Conceptualization, Resources, Supervision, Writing - Review \u0026amp; Editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by Foundation of Wenzhou Municipal Health Commission (2020041)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data collected and analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent for publication was obtained and signed by all participants involved in the study. All listed authors have reviewed this manuscript and have given their approval for its publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of The Third Affiliated Hospital of Wenzhou Medical University.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eACOG Practice Bulletin No. 200: Early Pregnancy Loss. Obstet Gynecol. 2018, 132(5):e197-e207.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGarc\u0026iacute;a-Engu\u0026iacute;danos A, Calle ME, Valero J, Luna S, Dom\u0026iacute;nguez-Rojas V. Risk factors in miscarriage: a review. Eur J Obstet Gynecol Reprod Biol. 2002;102(2):111\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNikitina TV, Lebedev IN. Stem Cell-Based Trophoblast Models to Unravel the Genetic Causes of Human Miscarriages. Cells 2022, 11(12).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXie C, Tammi MT. CNV-seq, a new method to detect copy number variation using high-throughput sequencing. BMC Bioinformatics. 2009;10:80.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu S, Song L, Cram DS, Xiong L, Wang K, Wu R, Liu J, Deng K, Jia B, Zhong M, et al. Traditional karyotyping vs copy number variation sequencing for detection of chromosomal abnormalities associated with spontaneous miscarriage. Ultrasound Obstet Gynecol. 2015;46(4):472\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePark SJ, Min JY, Kang JS, Yang BG, Hwang SY, Han SH. Chromosomal abnormalities of 19,000 couples with recurrent spontaneous abortions: a multicenter study. Fertil Steril. 2022;117(5):1015\u0026ndash;25.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnder SE, Diamond MS, Coyne CB. Immune responses at the maternal-fetal interface. Sci Immunol 2019, 4(31).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYougbar\u0026eacute; I, Tai WS, Zdravic D, Oswald BE, Lang S, Zhu G, Leong-Poi H, Qu D, Yu L, Dunk C, et al. Activated NK cells cause placental dysfunction and miscarriages in fetal alloimmune thrombocytopenia. Nat Commun. 2017;8(1):224.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVon Woon E, Greer O, Shah N, Nikolaou D, Johnson M, Male V. Number and function of uterine natural killer cells in recurrent miscarriage and implantation failure: a systematic review and meta-analysis. Hum Reprod Update. 2022;28(4):548\u0026ndash;82.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTong X, Gao M, Du X, Lu F, Wu L, Wei H, Fu B. Analysis of uterine CD49a(+) NK cell subsets in menstrual blood reflects endometrial status and association with recurrent spontaneous abortion. Cell Mol Immunol. 2021;18(7):1838\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFreud AG, Mundy-Bosse BL, Yu J, Caligiuri MA. The Broad Spectrum of Human Natural Killer Cell Diversity. Immunity. 2017;47(5):820\u0026ndash;33.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBulmer JN, Lash GE. The Role of Uterine NK Cells in Normal Reproduction and Reproductive Disorders. Adv Exp Med Biol. 2015;868:95\u0026ndash;126.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKing K, Smith S, Chapman M, Sacks G. Detailed analysis of peripheral blood natural killer (NK) cells in women with recurrent miscarriage. Hum Reprod. 2010;25(1):52\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAoki K, Kajiura S, Matsumoto Y, Ogasawara M, Okada S, Yagami Y, Gleicher N. Preconceptional natural-killer-cell activity as a predictor of miscarriage. Lancet. 1995;345(8961):1340\u0026ndash;2.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKwak JY, Beaman KD, Gilman-Sachs A, Ruiz JE, Schewitz D, Beer AE. Up-regulated expression of CD56+, CD56+/CD16+, and CD19\u0026thinsp;+\u0026thinsp;cells in peripheral blood lymphocytes in pregnant women with recurrent pregnancy losses. \u003cem\u003eAmerican journal of reproductive immunology (New York, NY\u003c/em\u003e: 1989) 1995, 34(2):93\u0026ndash;99.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSeshadri S, Sunkara SK. Natural killer cells in female infertility and recurrent miscarriage: a systematic review and meta-analysis. Hum Reprod Update. 2014;20(3):429\u0026ndash;38.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang Y, Yang L, Yang D, Cai S, Wang Y, Wang L, Li Y, Li L, Yin T, Diao L. Understanding the heterogeneity of natural killer cells at the maternal-fetal interface: implications for pregnancy health and disease. Mol Hum Reprod 2024, 30(11).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eErlebacher A. Immunology of the maternal-fetal interface. Annu Rev Immunol. 2013;31:387\u0026ndash;411.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBj\u0026ouml;rkstr\u0026ouml;m NK, Ljunggren HG, Micha\u0026euml;lsson J. Emerging insights into natural killer cells in human peripheral tissues. Nat Rev Immunol. 2016;16(5):310\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTang AW, Alfirevic Z, Quenby S. Natural killer cells and pregnancy outcomes in women with recurrent miscarriage and infertility: a systematic review. Hum Reprod. 2011;26(8):1971\u0026ndash;80.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOu M, Luo L, Yang Y, Yan N, Yan X, Zhong X, Cheong Y, Li T, Ouyang J, Wang Q. Decrease in peripheral natural killer cell level during early pregnancy predicts live birth among women with unexplained recurrent pregnancy loss: a prospective cohort study. \u003cem\u003eAmerican journal of obstetrics and gynecology\u003c/em\u003e 2024, 230(6):675.e671-675.e613.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCavalcante MB, da Silva PHA, Carvalho TR, Sampaio OGM, C\u0026acirc;mara FEA, Cavalcante C, Barini R, Kwak-Kim J. Peripheral blood natural killer cell cytotoxicity in recurrent miscarriage: a systematic review and meta-analysis. J Reprod Immunol. 2023;158:103956.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKolanska K, Suner L, Cohen J, Ben Kraiem Y, Placais L, Fain O, Bornes M, Selleret L, Delhommeau F, Feger F, et al. Proportion of Cytotoxic Peripheral Blood Natural Killer Cells and T-Cell Large Granular Lymphocytes in Recurrent Miscarriage and Repeated Implantation Failure: Case-Control Study and Meta-analysis. Arch Immunol Ther Exp. 2019;67(4):225\u0026ndash;36.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAdib Rad H, Basirat Z, Mostafazadeh A, Faramarzi M, Bijani A, Nouri HR, Soleimani Amiri S. Evaluation of peripheral blood NK cell subsets and cytokines in unexplained recurrent miscarriage. J Chin Med Association: JCMA. 2018;81(12):1065\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEiben B, Bartels I, B\u0026auml;hr-Porsch S, Borgmann S, Gatz G, Gellert G, Goebel R, Hammans W, Hentemann M, Osmers R, et al. Cytogenetic analysis of 750 spontaneous abortions with the direct-preparation method of chorionic villi and its implications for studying genetic causes of pregnancy wastage. Am J Hum Genet. 1990;47(4):656\u0026ndash;63.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLauer S, Gresham D. An evolving view of copy number variants. Curr Genet. 2019;65(6):1287\u0026ndash;95.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang H, Dong Z, Zhang R, Chau MHK, Yang Z, Tsang KYC, Wong HK, Gui B, Meng Z, Xiao K, et al. Low-pass genome sequencing versus chromosomal microarray analysis: implementation in prenatal diagnosis. Genet medicine: official J Am Coll Med Genet. 2020;22(3):500\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWeiss LA, Shen Y, Korn JM, Arking DE, Miller DT, Fossdal R, Saemundsen E, Stefansson H, Ferreira MA, Green T, et al. Association between microdeletion and microduplication at 16p11.2 and autism. N Engl J Med. 2008;358(7):667\u0026ndash;75.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eColley E, Hamilton S, Smith P, Morgan NV, Coomarasamy A, Allen S. Potential genetic causes of miscarriage in euploid pregnancies: a systematic review. Hum Reprod Update. 2019;25(4):452\u0026ndash;72.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen CP, Huang JP, Chen YY, Chern SR, Wu PS, Su JW, Chen YT, Chen WL, Wang W. Chromosome 22q11.2 deletion syndrome: prenatal diagnosis, array comparative genomic hybridization characterization using uncultured amniocytes and literature review. Gene. 2013;527(1):405\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDrozdov GV, Kashevarova AA, Lebedev IN. Copy number variations in spontaneous abortions: a meta-analysis. J Assist Reprod Genet 2025.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-pregnancy-and-childbirth","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prch","sideBox":"Learn more about [BMC Pregnancy and Childbirth](http://bmcpregnancychildbirth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/prch/default.aspx","title":"BMC Pregnancy and Childbirth","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Peripheral blood natural killer cells, Chromosomally abnormal spontaneous abortion, Microdeletions, Biomarker, Immune dysregulation","lastPublishedDoi":"10.21203/rs.3.rs-6504301/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6504301/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eChromosomal abnormalities account for a significant proportion of spontaneous abortions (SA), yet the role of peripheral blood natural killer (pbNK) cells\u0026mdash;especially across different karyotypes\u0026mdash;remains unclear. Elucidating this relationship may reveal immune mechanisms underlying early pregnancy loss and identify actionable biomarkers.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis retrospective, single-center study included 1250 patients, comparing 294 early SA cases (classified as chromosomally normal or abnormal via CNV-seq) with 956 live births. Multivariable logistic regression and stratified analyses were used to assess the association between pbNK cell levels and chromosomally abnormal SA, as well as specific karyotypes. The diagnostic performance of pbNK cells was evaluated using receiver operating characteristic (ROC) curves.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eMultivariate analysis identified elevated pbNK cell levels as an independent risk factor for chromosomally abnormal SA (adjusted OR\u0026thinsp;=\u0026thinsp;1.363, 95% CI: 1.033\u0026ndash;1.797). Patients in the highest quartile of pbNK cells had a fourfold increased risk (OR\u0026thinsp;=\u0026thinsp;4.123), with a linear dose-response relationship observed. Notably, SA cases associated with microdeletions showed the strongest association (OR\u0026thinsp;=\u0026thinsp;10.807, 95% CI: 2.627\u0026ndash;44.455), while trisomies demonstrated borderline significance. ROC analysis indicated moderate diagnostic utility (AUC\u0026thinsp;=\u0026thinsp;65.1%, sensitivity\u0026thinsp;=\u0026thinsp;52.1%, specificity\u0026thinsp;=\u0026thinsp;74.8%).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThese findings suggest that pbNK cell levels serve as a biomarker for chromosomally abnormal SA, particularly in microdeletion-related cases, and support a linear dose-response relationship between pbNK cell levels and SA risk.\u003c/p\u003e","manuscriptTitle":"Association Between Peripheral Blood Natural Killer Cells and Chromosomally Abnormal Spontaneous Abortion: A Retrospective Single-Center Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-20 12:32:54","doi":"10.21203/rs.3.rs-6504301/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2025-05-15T07:26:23+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-04-25T05:22:20+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-24T00:36:34+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-24T00:34:02+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pregnancy and Childbirth","date":"2025-04-22T12:23:18+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pregnancy-and-childbirth","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prch","sideBox":"Learn more about [BMC Pregnancy and Childbirth](http://bmcpregnancychildbirth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/prch/default.aspx","title":"BMC Pregnancy and Childbirth","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f92ecbc4-c5f9-43fa-b139-07f125093cb9","owner":[],"postedDate":"May 20th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-05-20T12:32:55+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-20 12:32:54","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6504301","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6504301","identity":"rs-6504301","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}