Objective: To investigate the clinicopathological and genetic features of confined placental mosaicism (CPM) and its effect on fetal intrauterine growth. Methods: Fourteen CPM cases of Haidian Maternal and Children Health Hospital were collected from May 2018 to March 2022. Clinicopathological examination on placental specimens and molecular genetic analysis were performed. Results: The age of the parturient women ranged from 27 to 34 years, with an average age of (30.0±3.54) years. The gestational weeks ranged from 35+1 to 41+2 weeks. There were 4 premature births and 10 term births, among which 6 were female and 8 were male fetuses. Nine cases (9/14) had adverse pregnancy outcomes, including 7 cases of fetal growth restriction. The weight of CPM placenta decreased, with 6 cases below the 10th percentile of weight standards and 5 cases between the 10th and 25th percentile. All 14 CPM placental specimens showed morphological changes of perfusion dysfunction to varying degrees, with mainly placental-maternal vascular malperfusion followed by placental-fetal vascular malperfusion. The mosaic chromosomes in different CPM cases varied, with 16-trisomy/monosomy mosaicism being the most common followed by 7-trisomy and 21-trisomy/monosomy mosaicism. The mosaic proportion was unequal in different parts of the same CPM placenta, with the mosaic proportion of umbilical cord, fetal membranes, fetal surface, maternal surface, and edge ranging from 1% to 70%. Conclusions: The mosaic chromosomes in different CPM cases vary, and the mosaic proportion is unequal in different parts of the same CPM placenta. The pathological morphology is mainly manifested as perfusion dysfunction, which can lead to adverse pregnancy outcomes such as fetal growth restriction and preterm birth.
目的： 探讨限制性胎盘嵌合（confined placental mosaicism，CPM）的分子遗传与临床病理特征及其对胎儿宫内发育的影响。 方法： 收集北京市海淀区妇幼保健院2018年5月至2022年3月确诊的14例CPM，对胎盘标本进行分子遗传和病理学检查，并进行临床病理学分析。 结果： 产妇年龄27~34岁，平均年龄（30.0±3.54）岁，孕周35+1~41+2周。4例早产，10例足月产，其中女胎儿6例，男胎儿8例。9例（9/14）出现了不良妊娠结局，其中7例为胎儿生长受限。CPM胎盘重量减轻，其中6例重量小于第10百分位数，5例重量位于第10~25百分位数之间。14例CPM胎盘均出现不同程度的灌注功能障碍形态学变化，以胎盘-母体血管灌注功能障碍为主，其次为胎盘-胎儿血管灌注功能障碍。不同CPM病例嵌合染色体各异，以16-三体/单体嵌合常见，其次为7-三体和21-三体/单体嵌合。同一个CPM胎盘不同部位嵌合比例不等，脐带、胎膜、胎儿面、母体面和边缘嵌合比例波动范围为1%~70%。 结论： 不同CPM病例嵌合染色体各异，同一CPM胎盘不同部位嵌合比例不等，病理形态学以灌注功能障碍为主要表现，可导致胎儿生长受限、早产等不良妊娠结局发生。.

BACKGROUND: Predicted 1-year survival of children with trisomy 18 (T18) has increased to 59.3%. We aimed to systematically review the characteristics, management, and outcomes of children with T18 and hepatoblastoma.
METHODS: A systematic literature review of the PubMed, Embase, Scopus, Web of Science, and Cochrane Library databases was performed according to the PRISMA 2020 statement (end-of-search date: 03/03/2024).
RESULTS: Fifty studies reporting on 70 patients were included. The median age at diagnosis was 11.5 months, 85.9% were female (n = 55/64), and 15.0% had mosaic T18 (n = 6/40). Diagnosis was made during symptom evaluation (most commonly hepatomegaly or abdominal mass) in 45.5% (n = 15/33), incidentally in 24.2% (n = 8/33), during surveillance with abdominal ultrasound in 18.2% (n = 6/33), and at autopsy in 12.1% (n = 4/33). The median tumor size was 6.4 cm, 33.3% had multiple tumors (n = 14/42), and metastasis was present in one patient (3.8%; n = 1/26). Neoadjuvant chemotherapy was administered in 42.6% (n = 26/61) and adjuvant chemotherapy in 31.6% (n = 18/57). Surgical treatment was performed in 64.2% (n = 43/67). Of the patients not diagnosed on autopsy, overall mortality was 35.5% (n = 22/62) over a median follow-up of 11.0 months. Among the 26 deceased patients (including those diagnosed on autopsy), the most common causes of death were cardiopulmonary disease (38.5%, n = 10/26) and tumor progression (30.8%, n = 8/26).
CONCLUSIONS: T18 does not preclude resection with curative intent for hepatoblastoma. Combination of surgery and chemotherapy should be considered in children on an individualized basis depending on tumor characteristics and underlying cardiopulmonary comorbidities. Locoregional modalities may have a role in the setting of severe comorbidities.
METHODS: Level IV evidence.

Genomic mosaicism arising from mosaic variants is a phenomenon that describes the presence of a cell or cell populations with different genome compositions from the germline cells of an individual. It comprises all types of genetic variants. A large proportion of childhood genetic disorders are defined as being de novo, meaning that the disease-causing mutations are only detected in the proband, not in any of the parents. Population studies show that 80% of the de novo mutations arise from the paternal haplotype, that is, from paternal sperm mosaicism. This review provides a summary of the types and detection strategies of sperm mosaicism. In addition, it provides discussions on how recent studies demonstrated that genomic mosaic mutations in parents, especially those in the paternal sperms, could be inherited by the offspring and cause childhood disorders. According to the previous findings of the author\'s research team, sperm mosaicism derived from early embryogenesis and primordial germ cell stages can explain 5% to 20% of the de novo mutations related to clinical phenotypes and can serve as an important predictor of both rare and complex disorders. Sperm mosaicism shows great potential for clinical genetic diagnosis and consultations. Based on the published literature, the author suggests that, large-scale screening for de novo sperm mosaic mutations and population-based genetic screening should be conducted in future studies, which will greatly enhance the risk assessment in the offspring and effectively improve the genetic health at the population level. Implementation of direct sperm detection for de novo mutations will significantly increase the efficiency of the stratification of patient cohorts and improve recurrence risk assessment for future births. Future research in the field should be focused on the impact of environmental and lifestyle factors on the health of the offspring through sperms and their modeling of mutation signatures. In addition, targeted in vitro modeling of sperm mutations will also be a promising direction.

BACKGROUND: Mosaic chromosomal alterations (mCAs) are implicated in neuropsychiatric disorders, yet the contribution to schizophrenia (SCZ) risk for somatic copy number variations (sCNVs) emerging in early developmental stages is not fully established.
METHODS: We analyzed blood-derived genotype arrays from 9,715 SCZ patients and 28,822 controls of Chinese descent using a computational tool (MoChA) based on long-range chromosomal information to detect mCAs. We focused on probable early developmental sCNVs through stringent filtering. We assessed the sCNVs\' burden across varying cell fraction (CF) cutoffs, as well as the frequency with which genes were involved in sCNVs. We integrated this data with the Psychiatric Genomics Consortium (PGC) dataset, which comprises 12,834 SCZ cases and 11,648 controls of European descent, and complemented it with genotyping data from postmortem brain tissue of 936 subjects (449 cases and 487 controls).
RESULTS: Patients with SCZ had a significantly higher somatic losses detection rate than control subjects (1.00% vs 0.52%; odds ratio (OR) = 1.91; 95% CI, 1.47-2.49; two-sided Fisher\'s exact test, p=1.49×10-6). Further analysis indicated that the ORs escalated proportionately (from 1.91 to 2.78) with the increment in CF cutoffs. Recurrent sCNVs associated with SCZ (OR>8; Fisher\'s exact test, p<0.05) were identified, including notable regions at 10q21.1 (ZWINT), 3q26.1 (SLITRK3), 1q31.1 (BRINP3) and 12q21.31-21.32 (MGAT4C and NTS) in the Chinese cohort, some regions validated with PGC data. Cross-tissue validation pinpointed somatic losses at loci like 1p35.3-35.2 and 19p13.3-13.2.
CONCLUSIONS: The study highlights mCAs\' significant impact on SCZ, suggesting their pivotal role in the disorder\'s genetic etiology.

Mosaicism for autosomal trisomy is uncommon in clinical practice. However, despite its rarity among both prenatally and postnatally diagnoses, there are a large number of characterized and published cases. Surprisingly, in contrast to regular trisomies, no attempts at systematic analyses of mosaic carriers\' demographics were undertaken. This is the first study aimed to address this gap. For that, we have screened more than eight hundred publications on mosaic trisomies, reviewing data including gender and clinical status of mosaic carriers, maternal age and reproductive history. In total, 596 publications were eligible for analysis, containing data on 948 prenatal diagnoses, including true fetal mosaicism (TFM) and confined placental mosaicism (CPM), and on 318 cases of postnatally detected mosaicism (PNM). No difference was found in maternal age between normal pregnancy outcomes with appropriate birth weight and those with intrauterine growth restriction. Unexpectedly, a higher proportion of advanced maternal ages (AMA) was found in normal outcomes compared to abnormal ones (abnormal fetus or newborn) and fetal losses, 73% vs. 56% and 50%, p = 0.0015 and p = 0.0011, correspondingly. Another intriguing finding was a higher AMA proportion in mosaic carriers with concomitant uniparental disomy (UPD) for chromosomes 7, 14, 15, and 16 compared to carriers with biparental disomy (BPD) (72% vs. 58%, 92% vs. 55%, 87% vs. 78%, and 65% vs. 24%, correspondingly); overall figures were 78% vs. 48%, p = 0.0026. Analysis of reproductive histories showed a very poor reporting but almost two-fold higher rate of mothers reporting a previous fetal loss from PNM cohort (in which almost all patients were clinically abnormal) compared to mothers from the TFM and CPM cohorts (with a large proportion of normal outcomes), 30% vs. 16%, p = 0.0072. The occurrence of a previous pregnancy with a chromosome abnormality was 1 in 13 in the prenatal cohort and 1 in 16 in the postnatal cohort, which are five-fold higher compared to published studies on non-mosaic trisomies. We consider the data obtained in this study to be preliminary despite the magnitude of the literature reviewed since reporting of detailed data was mostly poor, and therefore, the studied cohorts do not represent \"big data\". Nevertheless, the information obtained is useful both for clinical genetic counseling and for modeling further studies.

Rubinstein-Taybi syndrome (RTS) is a rare genetic disorder characterized by intellectual disability, facial dysmorphisms, and enlarged thumbs and halluces. Approximately 55% of RTS cases result from pathogenic variants in the CREBBP gene, with an additional 8% linked to the EP300 gene. Given the close relationship between these two genes and their involvement in epigenomic modulation, RTS is grouped into chromatinopathies. The extensive clinical heterogeneity observed in RTS, coupled with the growing number of disorders involving the epigenetic machinery, poses a challenge to a phenotype-based diagnostic approach for these conditions. Here, we describe the first case of a patient clinically diagnosed with RTS with a CREBBP truncating variant in mosaic form. We also review previously described cases of mosaicism in CREBBP and apply clinical diagnostic guidelines to these patients, confirming the good specificity of the consensus. Nonetheless, these reports raise questions about the potential underdiagnosis of milder cases of RTS. The application of a targeted phenotype-based approach, coupled with high-depth NGS, may enhance the diagnostic yield of whole-exome sequencing (WES) in mild and mosaic conditions.

BACKGROUND: Mosaic Down syndrome is a triplication of chromosome 21 in some but not all cells. Little is known about the epidemiology of mosaic Down syndrome. We described prevalence of mosaic Down syndrome and the co-occurrence of common chronic conditions in 94,533 Medicaid enrolled adults with any Down syndrome enrolled from 2016 to 2019.
METHODS: We identified mosaic Down syndrome using the International Classification of Diseases and Related Health Problems, tenth edition code for mosaic Down syndrome and compared to those with nonmosaic Down syndrome codes. We identified chronic conditions using established algorithms and compared prevalence by mosaicism.
RESULTS: In total, 1966 (2.08%) had claims for mosaic Down syndrome. Mosaicism did not differ by sex or race/ethnicity with similar age distributions. Individuals with mosaicism were more likely to present with autism (13.9% vs. 9.6%) and attention deficit hyperactivity disorder (17.7% vs. 14.0%) compared to individuals without mosaicism. In total, 22.3% of those with mosaic Down syndrome and 21.5% of those without mosaicism had claims for Alzheimer\'s dementia (Prevalence difference: 0.8; 95% Confidence interval: -1.0, 2.8). The mosaic group had 1.19 times the hazard of Alzheimer\'s dementia compared to the nonmosaic group (95% CI: 1.0, 1.3).
CONCLUSIONS: Mosaicism may be associated with a higher susceptibility to certain neurodevelopmental and neurodegenerative conditions, including Alzheimer\'s dementia. Our findings challenge previous assumptions about its protective effects in Down syndrome. Further research is necessary to explore these associations in greater depth.

When an apparent de novo (new) genetic change has been identified as the cause of a serious genetic condition in a child, many couples would like to know the risk of this happening again in a future pregnancy. Current practice provides families with a population average risk of 1%-2%. However, this figure is not accurate for any specific couple, and yet, they are asked to make decisions about having another child and/or whether to have prenatal testing. The PREcision Genetic Counseling And REproduction (PREGCARE) study is a new personalized assessment strategy that refines a couple\'s recurrence risk prior to a new pregnancy, by analyzing several samples from the parent-child trio (blood, saliva, swabs, and father\'s sperm) using deep sequencing and haplotyping. Overall, this approach can reassure ~2/3 of couples who have a negligible (<0.1%) recurrence risk and focus support on those at higher risk (i.e. when mosaicism is identified in one of the parents). Here we present a qualitative interview study with UK clinical genetics professionals (n = 20), which investigate the potential implications of introducing such a strategy in genetics clinics. While thematic analysis of the interviews indicated perceived clinical utility, it also indicates a need to prepare couples for the psychosocial implications of parent-of-origin information and to support their understanding of the assessment being offered. When dealing with personalized reproductive risk, a traditional non-directive approach may not meet the needs of practitioner and client(s) and shared decision-making provides an additional framework that may relieve some patient burden. Further qualitative investigation with couples is planned.

Somatic chromosomal mosaicism, chromosome instability, and cancer are intimately linked together. Addressing the role of somatic genome variations (encompassing chromosomal mosaicism and instability) in cancer yields paradoxical results. Firstly, somatic mosaicism for specific chromosomal rearrangement causes cancer per se. Secondly, chromosomal mosaicism and instability are associated with a variety of diseases (chromosomal disorders demonstrating less severe phenotypes, complex diseases), which exhibit cancer predisposition. Chromosome instability syndromes may be considered the best examples of these diseases. Thirdly, chromosomal mosaicism and instability are able to result not only in cancerous diseases but also in non-cancerous disorders (brain diseases, autoimmune diseases, etc.). Currently, the molecular basis for these three outcomes of somatic chromosomal mosaicism and chromosome instability remains incompletely understood. Here, we address possible mechanisms for the aforementioned scenarios using a system analysis model. A number of theoretical models based on studies dedicated to chromosomal mosaicism and chromosome instability seem to be valuable for disentangling and understanding molecular pathways to cancer-causing genome chaos. In addition, technological aspects of uncovering causes and consequences of somatic chromosomal mosaicism and chromosome instability are discussed. In total, molecular cytogenetics, cytogenomics, and system analysis are likely to form a powerful technological alliance for successful research against cancer.

Overgrowth disorders comprise a group of entities with a variable phenotypic spectrum ranging from tall stature to isolated or lateralized overgrowth of body parts and or organs. Depending on the underlying physiological pathway affected by pathogenic genetic alterations, overgrowth syndromes are associated with a broad spectrum of neoplasia predisposition, (cardio) vascular and neurodevelopmental anomalies, and dysmorphisms. Pathologic overgrowth may be of prenatal or postnatal onset. It either results from an increased number of cells (intrinsic cellular hyperplasia), hypertrophy of the normal number of cells, an increase in interstitial spaces, or from a combination of all of these. The underlying molecular causes comprise a growing number of genetic alterations affecting skeletal growth and Growth-relevant signaling cascades as major effectors, and they can affect the whole body or parts of it (mosaicism). Furthermore, epigenetic modifications play a critical role in the manifestation of some overgrowth diseases. The diagnosis of overgrowth syndromes as the prerequisite of a personalized clinical management can be challenging, due to their clinical and molecular heterogeneity. Physicians should consider molecular genetic testing as a first diagnostic step in overgrowth syndromes. In particular, the urgent need for a precise diagnosis in tumor predisposition syndromes has to be taken into account as the basis for an early monitoring and therapy. With the (future) implementation of next-generation sequencing approaches and further omic technologies, clinical diagnoses can not only be verified, but they also confirm the clinical and molecular spectrum of overgrowth disorders, including unexpected findings and identification of atypical cases. However, the limitations of the applied assays have to be considered, for each of the disorders of interest, the spectrum of possible types of genomic variants has to be considered as they might require different methodological strategies. Additionally, the integration of artificial intelligence (AI) in diagnostic workflows significantly contribute to the phenotype-driven selection and interpretation of molecular and physiological data.