Prolonged exposure to air pollution and risk of acute kidney injury and related mortality: a prospective cohort study based on hospitalized AKI cases and general population controls from the UK Biobank.

BACKGROUND: Previous investigations identified a connection between air pollution and kidney diseases. Nevertheless, there is a lack of comprehensive evidence on the long-term risks posed by air pollution with respect to acute kidney injury (AKI) and AKI-related death. METHODS: This prospective cohort analysis included 414,885 UK Biobank (UKB) participants who did not exhibit AKI at the study's outset. AKI was defined based on ICD-10 codes recorded for hospitalized patients. Cox proportional hazards models were used to assess the association between prolonged exposure to air pollutants (particulate matter with diameters of 2.5 micrometers or less (PM2.5), between 2.5 and 10 micrometers (PM2.5-10), and 10 micrometers or less (PM10), along with nitrogen dioxide (NO2) and nitrogen oxides (NOx)) and the risk of AKI and AKI-related death, adjusting for potential confounders including sex, age, ethnicity, education, income, lifestyle factors, and relevant clinical covariates. Restricted cubic splines were applied to evaluate non-linear dose-response relationships, and stratified analyses were performed to explore potential effect modification across subgroups. RESULTS: Over an average follow-up duration of 11.7 years, 14,983 cases of AKI and 326 cases of AKI-related death were diagnosed. Quartile analysis showed individuals exposed to higher levels of these air pollutants had a significantly higher risk of developing AKI and AKI-related death compared to those in the lowest quartile (all P < 0.05). The RCS curves depicting the relationship between PM2.5, PM2.5-10, PM10, NO2, NOx, and the risk of AKI showed a significant departure from linearity (P for non-linearity < 0.05), while the relationships between PM2.5, NO2, NOx, and the risk of AKI-related death did not exhibit a significant departure from linearity (P for non-linearity > 0.05). Sensitivity analyses confirmed the robustness of our findings. CONCLUSION: Our study reveals a direct association between prolonged air pollution exposure and elevated risks of both AKI and AKI-related death. These findings offer scientific validation for the adoption of environmental and public health measures directed towards the reduction of air pollution. Such initiatives could potentially ease the impact associated with AKI and AKI-related death.

Air pollutants, residential greenspace, and the risk of kidney stone disease: a large prospective cohort study from the UK Biobank.

BACKGROUND: The epidemiological evidence regarding the correlation between air pollution, residential greenspace, and the risk of kidney stone disease (KSD) is limited, with no large-scale prospective studies conducted on this relationship. OBJECTIVE: We conducted a large-scale prospective study from the UK Biobank to explore the correlation between air pollution, residential greenspace, and the risk of KSD. METHODS: This study included 419,835 UK Biobank participants who did not have KSD at baseline. An air pollution score was derived through the summation of concentrations for five air pollutants, including particulate matter (PM) with aerodynamic diameter ≤2.5 µm (PM2.5), ranging from 2.5 to 10 µm (PM2.5-10), ≤10 µm (PM10), nitrogen dioxide (NO2), and nitrogen oxides (NOx). Various covariates were adjusted for in Cox proportional hazard regression to evaluate the risk of KSD associated with air pollution score, single air pollutant, and residential greenspace. RESULTS: During a follow-up period of 12.7 years, 4503 cases of KSD were diagnosed. Significant associations were found between KSD risk and air pollution score (HR: 1.08, 95% CI: 1.03-1.13), PM2.5 (1.06, 1.02-1.11), PM10 (1.04, 1.01-1.07), NO2 (1.09, 1.02-1.16), NOx (1.08, 1.02-1.11), greenspace buffered at 300 m (0.95, 0.91-0.99), and greenspace buffered at 1000 m (0.92, 0.86-0.98) increase per interquartile range (IQR). PM2.5 and NO2 reductions may be a key mechanism for the protective impact of residential greenspace on KSD (P for indirect path < 0.05). IMPACT: Prolonged exposure to air pollution was correlated with a higher risk of KSD, while residential greenspace exhibits an inverse association with KSD risk, partially mediated by the reduction in air pollutants concentrations. These findings emphasize the significance of mitigating air pollution and maintaining substantial greenspace exposure as preventive measures against KSD.

Androgen deprivation therapy, neoadjuvant androgen deprivation therapy, and adjuvant androgen deprivation therapy in patients with locally advanced prostate cancer: a multi-center real-world retrospective study.

PURPOSE: Determining the potential benefit of neoadjuvant androgen deprivation therapy (ADT) and adjuvant ADT in patients with locally advanced prostate cancer (LAPC) undergoing complete resection. METHODS: 139 patients diagnosed with cT3-4, or cN+ LAPC in Xiangya Hospital and The First Affiliated Hospital of University of South China from 2010 to 2021 were collected. Cancer-specific survival (CSS) and overall survival (OS) of patients were assessed using Kaplan-Meier and Cox proportional risk analysis. We also analyzed the functional outcomes of two subgroups of patients who underwent radical prostatectomy (RP). RESULTS: Of the 182 patients with cT3-4, or cN+ LAPC, 139 patients (76.4%) were enrolled in the study with a 5-year survival rate of 82.3%. 45 patients (32.4%) received ADT alone, 46 patients (33.1%) received neoadjuvant ADT before surgery, and the remaining 48 patients (34.5%) received surgery with adjuvant ADT. Neoadjuvant ADT before surgery and surgery with adjuvant ADT were associated with significantly improved survival compared with ADT alone. Multivariate Cox models showed that neoadjuvant ADT before surgery (hazard ratio [HR], 0.29; 95% CI 0.13-0.92) or surgery with adjuvant ADT (HR, 0.26; 95% CI 0.16-0.78) was associated with improved CSS compared with ADT alone. Regional lymph node metastasis, positive lymphovascular invasion, and Gleason score 9 + were independent predictors of LAPC CSS and OS. More patients in the neoadjuvant ADT before surgery group achieved final continence status within 12 months after surgery (93.48% v 77.08%). CONCLUSION: CSS and OS were significantly prolonged in cT3-4, or cN+ LAPC patients who received neoadjuvant ADT before surgery and surgery with adjuvant ADT compared to ADT alone.

Oncogenic ACSM6 impairs CD8+ T cell-based immune response in bladder cancer.

Resistance to immunotherapy in bladder cancer has greatly limited its clinical application. Through single-cell sequencing, we determined that ACSM6, an oncogene that is highly expressed in bladder cancer, promotes the abilities of proliferation, cloning, migration, and invasion. The key point is that ACSM6 can also lead to a non-inflammatory immune microenvironment by inhibiting the chemotaxis and tumor killing ability of CD8+ T cells. Survival analysis revealed that high ACSM6 expression was associated with shorter overall survival in the immunotherapy cohort. In summary, ACSM6 is expected to become a novel biomarker for predict bladder cancer progression.

Hsa_circ_0000520 suppresses vasculogenic mimicry formation and metastasis in bladder cancer through Lin28a/PTEN/PI3K signaling.

BACKGROUND: Vasculogenic mimicry (VM) is a potential cause of resistance to antiangiogenic therapy and is closely related to the malignant progression of tumors. It has been shown that noncoding RNAs play an important role in the formation of VM in malignant tumors. However, the role of circRNAs in VM of bladder cancer and the regulatory mechanisms are unclear. METHODS: Firstly, hsa_circ_0000520 was identified to have circular character by Sanger sequencing and Rnase R assays. Secondly, the potential clinical value of hsa_circ_0000520 was explored by quantitative real-time polymerase chain reaction (qRT-PCR) and fluorescence in situ hybridization (FISH) of clinical specimens. Thirdly, the role of hsa_circ_0000520 in bladder cancer invasion, migration, and VM formation was examined by in vivo and in vitro experiments. Finally, the regulatory mechanisms of hsa_circ_0000520 in the malignant progression of bladder cancer were elucidated by RNA binding protein immunoprecipitation (RIP), RNA pulldown, co-immunoprecipitation (co-IP), qRT-PCR, Western blot (WB), and fluorescence co-localization. RESULTS: Hsa_circ_0000520 was characterized as a circular RNA and was lowly expressed in bladder cancer compared with the paracancer. Bladder cancer patients with high expression of hsa_circ_0000520 had better survival prognosis. Functionally, hsa_circ_0000520 inhibited bladder cancer invasion, migration, and VM formation. Mechanistically, hsa_circ_0000520 acted as a scaffold to promote binding of UBE2V1/UBC13 to Lin28a, further promoting the ubiquitous degradation of Lin28a, improving PTEN mRNA stability, and inhibiting the phosphorylation of the PI3K/AKT pathway. The formation of hsa_circ_0000520 in bladder cancer was regulated by RNA binding protein QKI. CONCLUSIONS: Hsa_circ_0000520 inhibits metastasis and VM formation in bladder cancer and is a potential target for bladder cancer diagnosis and treatment.

Osteogenic-Like Microenvironment of Renal Interstitium Induced by Osteomodulin Contributes to Randall's Plaque Formation.

Calcium oxalate (CaOx) kidney stones are common and recurrent, lacking pharmacological prevention. Randall's plaques (RPs), calcium deposits in renal papillae, serve as niduses for some CaOx stones. This study explores the role of osteogenic-like cells in RP formation resembling ossification. CaP crystals deposit around renal tubules, interstitium, and blood vessels in RP tissues. Human renal interstitial fibroblasts (hRIFs) exhibit the highest osteogenic-like differentiation potential compared to chloride voltage-gated channel Ka positive tubular epithelial cells, aquaporin 2 positive collecting duct cells, and vascular endothelial cells, echoing the upregulated osteogenic markers primarily in hRIFs within RP tissues. Utilizing RNA-seq, osteomodulin (OMD) is found to be upregulated in hRIFs within RP tissues and hRIFs following osteogenic induction. Furthermore, OMD colocalizes with CaP crystals and calcium vesicles within RP tissues. OMD can enhance osteogenic-like differentiation of hRIFs in vitro and in vivo. Additionally, crystal deposits are attenuated in mice with Omd deletion in renal interstitial fibroblasts following CaOx nephrocalcinosis induction. Mechanically, a positive feedback loop of OMD/BMP2/BMPR1A/RUNX2/OMD drives hRIFs to adopt osteogenic-like fates, by which OMD induces osteogenic-like microenvironment of renal interstitium to participate in RP formation. We identify OMD upregulation as a pathological feature of RP, paving the way for preventing CaOx stones.

Case report: Dupilumab: a promising treatment option for adult linear IgA bullous dermatosis with severe pruritus.

Linear IgA bullous dermatosis (LABD) is an acquired autoimmune subepidermal blistering disorder. Diagnosis always relies on skin pathology and direct immunofluorescence (DIF), with typical linear deposits of IgA along the basement membrane zone (BMZ). The typical clinical manifestation is tense bullae arranged like the "string of pearls" companied with severe pruritus. Dapsone is often considered first-line therapy for LABD, and it is necessary to test the HLA-B*1301 gene to prevent the occurrence of dapsone-induced hypersensitivity syndrome (DHS). Here we report a case of LABD resistant to corticosteroid and sulfasalazine, while waiting for HLA-B*1301 gene test results, dupilumab was used to control severe pruritus.

Case report: Managing pemphigus foliaceus using apremilast without systemic glucocorticosteroids or immunosuppressive agents.

Pemphigus foliaceus (PF) is a superficial form of pemphigus. Treatment options for PF resemble pemphigus vulgaris, including glucocorticosteroids, immunosuppressive agents and rituximab et al. These treatment approaches can effectively improve the condition but may also be accompanied by high risks of side effects. Therefore, it is crucial to find a safe and effective treatment options for patients with PF. It will not only benefit/be necessary for patients who refuse glucocorticosteroids or immunosuppressive agents treatments, but also for patients who cannot be treated with glucocorticosteroids or immunosuppressive agents. Herein, we reported a case of PF that was treated with apremilast without systemic glucocorticosteroids or immunosuppressive agents. A 54-year-old woman presented with itchy erythema and erosions on the trunk for more than 1 month. The patient applied mometasonefuroate cream without improvement for a duration of two weeks. The past history of diabetes mellitus and atrophic gastritis was reported. Physical examination revealed scattered erythematous macules and erosions on the trunk. No mucosal involvement was observed. The condition was assessed by the pemphigus disease area index and numerical rating scale, with baseline scores of 7 and 8, respectively. Histopathological examination showed acantholysis and intraepithelial blister. Direct immunofluorescence revealed the presence of IgG and Complement 3 deposition between the acanthocytes with the reticular distribution. Based on enzyme-linked immunosorbent assay results, the levels of Dsg1 and Dsg3 antibodies were 28.18 and 0.26 kU/L respectively. The diagnosis of PF was made. This patient was successfully treated with apremilast without systemic glucocorticosteroids or immunosuppressive agents. The patient has continued with apremilast 30mg once daily for maintenance and no adverse events related to apremilast such as gastrointestinal side effects were observed during the 9-month follow-up period. In conclusion, apremilast therapy without systemic glucocorticosteroids nor immunosuppressive agents might provide an effective alternative to management of mild PF without obvious side effect.

Social Determinants of Health Mediate Racial Disparities in Cardiovascular Disease in Men With Prostate Cancer.

Background: Cardiovascular disease (CVD) is a significant cause of morbidity and mortality in men with prostate cancer; however, data on racial disparities in CVD outcomes are limited. Objectives: We quantified the disparities in CVD according to self-identified race and the role of the structural social determinants of health in mediating disparities in prostate cancer patients. Methods: A retrospective cohort study of 3,543 prostate cancer patients treated with systemic androgen deprivation therapy (ADT) between 2008 and 2021 at a quaternary, multisite health care system was performed. The multivariable adjusted association between self-reported race (Black vs White) and incident major adverse cardiovascular events (MACE) after ADT initiation was evaluated using cause-specific proportional hazards. Mediation analysis determined the role of theme-specific and overall social vulnerability index (SVI) in explaining the racial disparities in CVD outcomes. Results: Black race was associated with an increased hazard of MACE (HR: 1.38; 95% CI: 1.16-1.65; P < 0.001). The association with Black race was strongest for incident heart failure (HR: 1.79; 95% CI: 1.32-2.43), cerebrovascular disease (HR: 1.98; 95% CI: 1.37-2.87), and peripheral artery disease (HR: 1.76; 95% CI: 1.26-2.45) (P < 0.001). SVI, specifically the socioeconomic status theme, mediated 98% of the disparity in MACE risk between Black and White patients. Conclusions: Black patients are significantly more likely to experience adverse CVD outcomes after systemic ADT compared with their White counterparts. These disparities are mediated by socioeconomic status and other structural determinants of health as captured by census tract SVI. Our findings motivate multilevel interventions focused on addressing socioeconomic vulnerability.

Spending Analysis of Machine Learning-Based Communication Nudges in Oncology.

BACKGROUND: Serious illness conversations (SICs) in the outpatient setting may improve mood and quality of life among patients with cancer and decrease aggressive end-of-life care. Interventions informed by behavioral economics may increase rates of SICs between oncology clinicians and patients, but the impact of these interventions on end-of-life spending is unknown. METHODS: This study is a secondary analysis of a stepped-wedge cluster randomized, controlled trial that involved nine medical oncology practices and their high-risk patients at a large academic institution between June 2019 and April 2020. The study included 1187 patients who were identified by a machine-learning algorithm as high risk of 180-day mortality and who died by December 2020. The patients were randomly assigned to standard of care (controls) or to a behavioral intervention designed to increase clinician-initiated SICs. We abstracted spending - defined as inflation-adjusted costs for acute care (inpatient plus emergency room), office/outpatient care, intravenous systemic therapy, other therapy (e.g., radiation), long-term care, and hospice - from the institution's accounting system, and we captured spending at inpatient, outpatient, and pharmacy settings. To evaluate intervention impacts on spending, we used a two-part model, first using logistic regression to model zero versus nonzero spending and second using generalized linear mixed models with gamma distribution and log-link function to model daily mean spending in the last 180days of life. Models were adjusted for clinic and wedge fixed effects, and they were clustered at the oncologist level. For all patients with at least one SIC within 6 months of death, we also calculated their mean daily spending before and after SIC. RESULTS: Median age at death was 68years (interquartile range, 15.5), 317 patients (27%) were Black or of ethnicities other than white, and 448 patients (38%) had an SIC. The intervention was associated with lower unadjusted mean daily spending in the last 6 months of life for the intervention group versus controls ($377.96 vs. $449.92; adjusted mean difference, -$75.33; 95% confidence interval, -$136.42 to -$14.23; P=0.02), translating to $13,747 total adjusted savings per decedent and $13 million in cumulative savings across all decedents in the intervention group. Compared with controls, patients in the intervention group incurred lower mean daily spending for systemic therapy (adjusted difference, -$44.59; P=0.001), office/outpatient care (-$9.62; P=0.001), and other therapy (-$8.65; P=0.04). The intervention was not associated with differences in end-of-life spending for acute care, long-term care, or hospice. Results were consistent for spending in the last 1 and 3 months of life and after adjusting for age, race, and ethnicity. For patients with SICs, mean daily spending decreased by $37.92 following the first SIC ($329.87 vs. $291.95). CONCLUSIONS: A machine learning-based, behaviorally informed intervention to prompt SICs led to end-of-life savings among patients with cancer, driven by decreased systemic therapy and outpatient spending. (Funded by the Penn Center for Precision Medicine and the National Institutes of Health; ClinicalTrials.gov number, NCT03984773.).

Effective alleviation of depressive and anxious symptoms and sleep disorders in benzodiazepine-dependent patients through repetitive transcranial magnetic stimulation.

Benzodiazepine (BZD) dependence poses a significant challenge in mental health, prompting the exploration of treatments like repetitive transcranial magnetic stimulation (rTMS). This research aims to assess the impact of rTMS on alleviating symptoms of BZD dependence. A randomized control trial was employed to study 40 BZD-dependent inpatients. Their symptoms were quantified using the Hamilton Anxiety Rating Scale (HAMA), Montgomery-Åsberg Depression Rating Scale (MADRS) and Pittsburgh Sleep Quality Index (PSQI). Participants were divided into a conventional treatment group (daily diazepam with gradual tapering) with supportive psychotherapy and another group receiving the same treatment supplemented with rTMS (five weekly sessions for 2 weeks). Significant improvements were observed in both groups over baseline in MADRS, HAMA and PSQI scores at the 2nd, 4th, 8th and 12th week assessments (p < 0.05). The group receiving rTMS in addition to conventional treatment exhibited superior improvements in all measures at the 8th and 12th weeks. The addition of rTMS to conventional treatment methods for BZD dependence significantly betters the recovery in terms of depression, anxiety and sleep quality, highlighting the role of rTMS as an effective adjunct therapy.

91 Circulating inflammatory proteins and the risk of age-related macular degeneration: A bidirectional Mendelian randomization study.

Previous observational studies have indicated a correlation between circulating inflammatory proteins and age-related macular degeneration (AMD), yet the causal nature of this relationship remains uncertain. This study aims to investigate the causal link between circulating inflammatory proteins and AMD utilizing a bidirectional two-sample Mendelian randomization approach. The findings indicated that elevated levels of four circulating inflammatory proteins, including C-C Motif Chemokine Ligand 11 (CCL11), Signaling Lymphocytic Activation Molecule Family Member 1 (SLAMF1), TNF Superfamily Member 11 (TRANCE) and Vascular Endothelial Growth Factor A (VEGF-A) lead to the increased risk of AMD, while increased levels of two circulating inflammatory proteins, including Fibroblast Growth Factor 19 (FGF-19) and Interleukin 10 Receptor Subunit Alpha (IL-10RA), resulted in the decreased risk of AMD. Conversely, the results from reverse Mendelian randomization suggested that the presence of AMD lead to the reduction in levels of 15 circulating inflammatory proteins. The findings of this study support the association between elevated levels of circulating inflammatory proteins and the risk of AMD, as well as the potential impact of AMD on reducing circulating inflammatory protein levels. CCL11, SLAMF1, TRANCE and VEGF-A are identified as potential molecular markers in the progression of AMD. These results offer a novel molecular therapeutic target for the prevention and treatment of AMD.

Feasibility of risk assessment for breast cancer molecular subtypes.

PURPOSE: Few breast cancer risk assessment models account for the risk profiles of different tumor subtypes. This study evaluated whether a subtype-specific approach improves discrimination. METHODS: Among 3389 women who had a screening mammogram and were later diagnosed with invasive breast cancer we performed multinomial logistic regression with tumor subtype as the outcome and known breast cancer risk factors as predictors. Tumor subtypes were defined by expression of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) based on immunohistochemistry. Discrimination was assessed with the area under the receiver operating curve (AUC). Absolute risk of each subtype was estimated by proportioning Gail absolute risk estimates by the predicted probabilities for each subtype. We then compared risk factor distributions for women in the highest deciles of risk for each subtype. RESULTS: There were 3,073 ER/PR+ HER2 - , 340 ER/PR +HER2 + , 126 ER/PR-ER2+, and 300 triple-negative breast cancers (TNBC). Discrimination differed by subtype; ER/PR-HER2+ (AUC: 0.64, 95% CI 0.59, 0.69) and TNBC (AUC: 0.64, 95% CI 0.61, 0.68) had better discrimination than ER/PR+HER2+ (AUC: 0.61, 95% CI 0.58, 0.64). Compared to other subtypes, patients at high absolute risk of TNBC were younger, mostly Black, had no family history of breast cancer, and higher BMI. Those at high absolute risk of HER2+ cancers were younger and had lower BMI. CONCLUSION: Our study provides proof of concept that stratifying risk prediction for breast cancer subtypes may enable identification of patients with unique profiles conferring increased risk for tumor subtypes.

Targeting gut and intratumoral microbiota: a novel strategy to improve therapy resistance in cancer with a focus on urologic tumors.

INTRODUCTION: Growing attention has been drawn to urologic tumors due to their rising incidence and suboptimal clinical treatment outcomes. Cancer therapy resistance poses a significant challenge in clinical oncology, limiting the efficacy of conventional treatments and contributing to disease progression. Recent research has unveiled a complex interplay between the host microbiota and cancer cells, highlighting the role of the microbiota in modulating therapeutic responses. AREAS COVERED: We used the PubMed and Web of Science search engines to identify key publications in the fields of tumor progression and urologic tumor treatment, specifically focusing on the role of the microbiota. In this review, we summarize the current literature on how microbiota influence the tumor microenvironment and anti-tumor immunity, as well as their impact on treatments for urinary system malignancies, highlighting promising future applications. EXPERT OPINION: We explore how the composition and function of the gut microbiota influence the tumor microenvironment and immune response, ultimately impacting treatment outcomes. Additionally, we discuss emerging strategies targeting the microbiota to enhance therapeutic efficacy and overcome resistance. The application of antibiotics, fecal microbiota transplantation, and oncolytic bacteria has improved tumor treatment outcomes, which provides a novel insight into developing therapeutic strategies for urologic cancer.

A constrained maximum likelihood approach to developing well-calibrated models for predicting binary outcomes.

The added value of candidate predictors for risk modeling is routinely evaluated by comparing the performance of models with or without including candidate predictors. Such comparison is most meaningful when the estimated risk by the two models are both unbiased in the target population. Very often data for candidate predictors are sourced from nonrepresentative convenience samples. Updating the base model using the study data without acknowledging the discrepancy between the underlying distribution of the study data and that in the target population can lead to biased risk estimates and therefore an unfair evaluation of candidate predictors. To address this issue assuming access to a well-calibrated base model, we propose a semiparametric method for model fitting that enforces good calibration. The central idea is to calibrate the fitted model against the base model by enforcing suitable constraints in maximizing the likelihood function. This approach enables unbiased assessment of model improvement offered by candidate predictors without requiring a representative sample from the target population, thus overcoming a significant practical challenge. We study theoretical properties for model parameter estimates, and demonstrate improvement in model calibration via extensive simulation studies. Finally, we apply the proposed method to data extracted from Penn Medicine Biobank to inform the added value of breast density for breast cancer risk assessment in the Caucasian woman population.

Efficient inference of parent-of-origin effect using case-control mother-child genotype data.

Parent-of-origin effect plays an important role in mammal development and disorder. Case-control mother-child pair genotype data can be used to detect parent-of-origin effect and is often convenient to collect in practice. Most existing methods for assessing parent-of-origin effect do not incorporate any covariates, which may be required to control for confounding factors. We propose to model the parent-of-origin effect through a logistic regression model, with predictors including maternal and child genotypes, parental origins, and covariates. The parental origins may not be fully inferred from genotypes of a target genetic marker, so we propose to use genotypes of markers tightly linked to the target marker to increase inference efficiency. A robust statistical inference procedure is developed based on a modified profile log-likelihood in a retrospective way. A computationally feasible expectation-maximization algorithm is devised to estimate all unknown parameters involved in the modified profile log-likelihood. This algorithm differs from the conventional expectation-maximization algorithm in the sense that it is based on a modified instead of the original profile log-likelihood function. The convergence of the algorithm is established under some mild regularity conditions. This expectation-maximization algorithm also allows convenient handling of missing child genotypes. Large sample properties, including weak consistency, asymptotic normality, and asymptotic efficiency, are established for the proposed estimator under some mild regularity conditions. Finite sample properties are evaluated through extensive simulation studies and the application to a real dataset.