Nady El Hajj

Polycystic ovary syndrome (PCOS) is the most common reproductive and endocrine disorder affecting women in their reproductive age. PCOS is characterized by clustering of reproductive disturbances, including, but not limited to, hypothalamus-pituitary-ovarian axis dysfunction, chronic anovulation, excess androgen, and subfertility. PCOS extends beyond reproductive dysfunction to involve metabolic, endocrine, and cardiometabolic abnormalities. Therefore, it has recently been redefined as polyendocrine metabolic ovarian syndrome (PMOS). Despite the evolution of diagnostic criteria for PMOS in recent decades, there persists a knowledge gap regarding its origins and pathophysiology. Genetic studies have identified candidate genes associated with PMOS, but genetic factors alone cannot account for its varied phenotypes. The diverse phenotypes observed in PMOS instead point to a complex gene-environment interaction, thereby paving the way for epigenetic mechanisms to explain this heterogeneous trait. Emerging evidence suggests that epigenetic alterations during critical developmental periods, particularly in utero and during puberty, may contribute to the reproductive, metabolic, and endocrine manifestations of PMOS. These observations may re-frame PMOS as a developmental disorder that follows the developmental origin of health and disease (DOHaD) theory. In this review, we propose a comprehensive framework to address the complexity of PMOS pathogenesis and phenotypes. We investigated how environmental exposures during critical windows may shape the epigenome and contribute to PMOS development. The review also examines the biological rationale of the 2023 International Evidence-based Guideline for PCOS, including the use of anti-Müllerian hormone, postponing diagnosis until after puberty, and recommendations for healthy lifestyle behaviors.

Introduction: Gestational diabetes mellitus (GDM) is a condition characterized by glucose intolerance that is first identified during pregnancy and typically resolves after childbirth. This condition can lead to various complications, both prenatal and postnatal, including type 2 diabetes (T2D). However, not all women with GDM progress to T2D, and the molecular mechanisms underlying this heterogeneity remain poorly understood. Here, we hypothesized that GDM participants could be clustered into T2D-like subtypes. Methods: To derive T2D-like subtypes, we applied K-means clustering to GDM participants using the predefined T2D subtype cluster centers established in the QPHI cohort. Differential methylation analysis was performed, and the top-ranked sites were used for further analysis. Additionally, we estimated system-specific age acceleration and its association with subtype-specific complications. Results: Our study demonstrated the effectiveness of the novel clustering approach, originally developed for T2D, in GDM. Additionally, the exploratory analysis of the top-ranked CpG sites suggested potential subtype-related methylation patterns. The identified pathways also suggested overlapping molecular mechanisms underlying both GDM and T2D. Conclusion: These findings support the feasibility of classifying GDM into T2D-like clinical subtypes and suggest potential epigenetic differences that warrant validation in larger longitudinal cohorts.

Background: Goldenhar syndrome (oculo–auriculo–vertebral spectrum, OAVS) is a rare congenital disorder characterized by craniofacial malformations, systemic anomalies, and significant phenotypic variability. Although it is the second most common craniofacial malformation after a cleft palate, the genetic etiology of Goldenhar syndrome remains largely unexplored. This study aimed to identify genetic variants contributing to Goldenhar syndrome in a Lebanese family with three affected individuals, using whole-exome sequencing and complementary genomic approaches. Methods: Whole-exome sequencing was performed on the nuclear family to identify variants associated with the syndrome. Complementary DNA methylation and gene ontology analyses were conducted to explore epigenetic modifications. Results: A missense shared variant in the MID1 between the affected individuals [NP_000372.1): p. Ile593Phe] gene was observed in the family, while current ACMG evidence was insufficient to establish causality. Additional variants were identified, including a de novo mutation in FBXW11 and a rare frameshift alteration in NDUFAF8, with limited segregation, implicating these genes in associated phenotypes such as craniofacial anomalies and cardiac defects. DNA methylation analysis revealed hypomethylation at CpG sites within the ZC3H3 gene, suggesting an epigenetic contribution to disease variability. Conclusions: Our findings underscore the genetic and epigenetic complexity of Goldenhar syndrome, providing new insights into its molecular etiology and highlighting the challenges of variant interpretation in familial cases of rare congenital disorders.

Gestational diabetes mellitus (GDM) is a common metabolic disorder characterized by hyperglycemia that is first detected during pregnancy, which is not overt diabetes. GDM poses a substantial risk for prenatal and postnatal adverse outcomes affecting both the mother and the offspring. These complications include, but are not limited to, fetal macrosomia, shoulder dystocia, respiratory distress, neonatal hypoglycemia, type 2 diabetes (T2D), and cardiovascular diseases. Screening for GDM typically occurs between 24 and 28 weeks of gestation, a timing that is considered late and may increase the risk of all the adverse outcomes associated with GDM. Treatment and prevention strategies are not standardized globally, may be suboptimal, and are often initiated after a diagnosis has been made. Therefore, our primary goal was to identify DNA methylation signatures specific to GDM to understand its underlying mechanisms. We conducted genome-wide DNA methylation profiling for normal and GDM pregnant women across the three trimesters of pregnancy in the discovery cohort. DNA methylation levels were measured using the Infinium MethylationEPIC v2.0 BeadChip. Subsequently, our differentially methylated sites were validated in a second cohort. Furthermore, we performed downstream analyses, including KEGG pathway and Gene Ontology enrichment analysis, trait enrichment analysis, and gene expression regulation analysis for the validated differentially methylated sites identified in the second and third trimesters. In this study, we uncovered and validated new DNA methylation signatures that may significantly influence the expression of genes associated with GDM. Furthermore, we discovered new genes (RSL1D1, HOXD4, and MROH6) that may play a role in GDM and might be related to the risk of developing T2D and cardiovascular disease later in life. Trait analysis of the differentially methylated probes revealed that lifestyle and environmental factors are associated with the observed DNA methylation signatures in GDM. We conclude that DNA methylation changes during pregnancy might not fully explain GDM pathogenesis but can reflect population-specific environmental and behavioral factors before and during pregnancy. Some of these discovered CpG sites might regulate previously reported genes linked to GDM and diabetes, highlighting shared and distinct epigenetic mechanisms across populations.

Progeroid syndromes are rare genetic disorders that impact patients' health and lifespans and are characterized by symptoms that mimic the normal aging process. Telomere length is one of the aging hallmarks, a phenomenon linked to cellular aging. Telomere attrition was observed in different progeroid syndromes, such as Nijmegen breakage syndrome patients and Werner syndrome, indicating its contribution to the progeroid phenotype. However, whether it is a common feature in all progeroid syndromes is still unclear. Therefore, in this study, we aimed to estimate telomere length using the DNA methylation-based estimator of human telomere length in publicly available DNA methylation data from patients with Werner Syndrome, Hutchinson-Gilford Progeria Syndrome, Berardinelli-Seip Congenital Lipodystrophy type 2, and Dyskeratosis congenita, along with additional data provided by our laboratory from patients with Cerebroretinal Microangiopathy with Calcifications and Cysts and Wiedemann-Rautenstrauch Syndrome. Our findings revealed that certain progeroid syndromes, including classical Werner Syndrome, Berardinelli-Seip Congenital Lipodystrophy type 2, and Dyskeratosis congenita, have significant telomere attrition conversely to Hutchinson-Gilford Progeria Syndrome, Cerebroretinal Microangiopathy with Calcifications and Cysts, Wiedemann-Rautenstrauch Syndrome, and atypical Werner Syndrome. In conclusion, this study addresses a critical gap by providing new insights into the role of telomere attrition across different progeroid conditions. Further research is needed to elucidate the effect of telomere attrition on progeroid syndromes and its implications.

Gestational diabetes mellitus (GDM) is a common metabolic disorder characterized by hyperglycemia that is first detected during pregnancy, which is not overt diabetes. GDM poses a substantial risk for prenatal and postnatal adverse outcomes affecting both the mother and the offspring. These complications include, but are not limited to, fetal macrosomia, shoulder dystocia, respiratory distress, neonatal hypoglycemia, type 2 diabetes, and cardiovascular diseases. Screening for GDM typically occurs between 24 and 28 weeks of gestation, a timing that is considered late and may increase the risk of all the adverse outcomes associated with GDM. Treatment and prevention strategies are not standardized globally, may be suboptimal, and are often initiated after a diagnosis has been made. Therefore, our primary goal was to identify DNA methylation signatures specific to GDM to understand its underlying mechanisms. We conducted genome-wide DNA methylation profiling for normal and GDM pregnant women across the three trimesters of pregnancy in the discovery cohort. In addition, we validated our findings in a second cohort collected in Qatar. In this study, we uncovered and validated new DNA methylation signatures that may significantly influence the expression of genes associated with GDM. Furthermore, we discovered new genes ( RSL1D1 , HOXD4 , and MROH6 ) that may play a role in GDM and might be related to the risk of developing T2D and cardiovascular disease later in life. We conclude that DNA methylation changes during pregnancy might not fully explain GDM pathogenesis but can reflect population-specific environmental and behavioral factors before and during pregnancy. Some of these discovered CpG sites might regulate previously reported genes linked to GDM and diabetes, highlighting shared and distinct epigenetic mechanisms across populations.

Several progeroid syndromes’ causative mutations have been linked to epigenetic age acceleration as measured via several epigenetic clocks. At the same time, several protective variants have also been discovered that can reduce the risk of developing certain age-related disorders. However, the impact of these protective variants on epigenetic aging has not been well elucidated. Our research, which involved screening over 14,669 healthy individuals enrolled in the Qatar BioBank (QBB) and sequenced by the Qatar Genome Project (QGP), identified individuals carrying protective variants against age-related disorders, including Alzheimer’s disease (AD), type 2 diabetes (T2D), and atherosclerosis. In this study, we measured methylation levels in blood DNA using the EPIC v2 arrays. In addition, epigenetic age was calculated using various epigenetic clocks. Our analysis revealed that the APOE*E2 protective variant reduces the rate of GrimAge epigenetic aging when compared to individuals with the APOE4 AD risk allele. Furthermore, our differential DNA methylation analysis discovered the association of the PCSK9 protective variant with specific biological processes related to immune function and the cardiovascular system. In conclusion, APOE*E2 protective variants have a positive impact on epigenetic aging, while PCSK9 protective variants have a significant effect on DNA methylation signatures. Further studies are needed to better understand the underlying mechanisms by which protective variants influence epigenetic aging, particularly the role of APOE*E2 protective variants in biological aging. Furthermore, additional research is required to fully uncover the processes that might enable specific targeted therapies to mimic the effects of beneficial mutations, such as LOF variants in PCSK9, in reducing the risk of geriatric disorders.