Improving predictive accuracy in primary biliary cholangitis: A new genetic risk score.

BACKGROUND AND AIMS: Genetic variants influence primary biliary cholangitis (PBC) risk. We established and tested an accurate polygenic risk score (PRS) using these variants. METHODS: Data from two Italian cohorts (OldIT 444 cases, 901 controls; NewIT 255 cases, 579 controls) were analysed. The latest international genome-wide meta-analysis provided effect size estimates. The PRS, together with human leukocyte antigen (HLA) status and sex, was included in an integrated risk model. RESULTS: Starting from 46 non-HLA genes, 22 variants were selected. PBC patients in the OldIT cohort showed a higher risk score than controls: -.014 (interquartile range, IQR, -.023, .005) versus -.022 (IQR -.030, -.013) (p < 2.2 × 10-16). For genetic-based prediction, the area under the curve (AUC) was .72; adding sex increased the AUC to .82. Validation in the NewIT cohort confirmed the model's accuracy (.71 without sex, .81 with sex). Individuals in the top group, representing the highest 25%, had a PBC risk approximately 14 times higher than that of the reference group (lowest 25%; p < 10-6). CONCLUSION: The combination of sex and a novel PRS accurately discriminated between PBC cases and controls. The model identified a subset of individuals at increased risk of PBC who might benefit from tailored monitoring.

The Role of Epigenetics in Primary Biliary Cholangitis.

Primary Biliary Cholangitis (PBC) is a rare autoimmune disease of the liver, affecting mostly females. There is evidence that epigenetic changes have a pathogenic role in PBC. Epigenetic modifications are related to methylation of CpG DNA islands, post-translational modifications of histone proteins, and non-coding RNAs. In PBC, there are data showing a dysregulation of all these levels, especially in immune cells. In addition, epigenetics seems to be involved in complex phenomena such as X monosomy or abnormalities in the process of X chromosome inactivation, which have been reported in PBC and appear to influence its sex imbalance and pathogenesis. We review here historical data on epigenetic modifications in PBC, present new data, and discuss possible links among X-chromosome abnormalities at a genetic and epigenetic level, PBC pathogenesis, and PBC sex imbalance.

RUES2 hESCs exhibit MGE-biased neuronal differentiation and muHTT-dependent defective specification hinting at SP1.

RUES2 cell lines represent the first collection of isogenic human embryonic stem cells (hESCs) carrying different pathological CAG lengths in the HTT gene. However, their neuronal differentiation potential has yet to be thoroughly evaluated. Here, we report that RUES2 during ventral telencephalic differentiation is biased towards medial ganglionic eminence (MGE). We also show that HD-RUES2 cells exhibit an altered MGE transcriptional signature in addition to recapitulating known HD phenotypes, with reduced expression of the neurodevelopmental regulators NEUROD1 and BDNF and increased cleavage of synaptically enriched N-cadherin. Finally, we identified the transcription factor SP1 as a common potential detrimental co-partner of muHTT by de novo motif discovery analysis on the LGE, MGE, and cortical genes differentially expressed in HD human pluripotent stem cells in our and additional datasets. Taken together, these observations suggest a broad deleterious effect of muHTT in the early phases of neuronal development that may unfold through its altered interaction with SP1.

Genetic susceptibility to severe COVID-19.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the etiologic agent of the coronavirus disease 2019 (COVID-19) pandemic. Clinical manifestations of the disease range from an asymptomatic condition to life-threatening events and death, with more severe courses being associated with age, male sex, and comorbidities. Besides these risk factors, intrinsic characteristics of the virus as well as genetic factors of the host are expected to account for COVID-19 clinical heterogeneity. Genetic studies have long been recognized as fundamental to identify biological mechanisms underlying congenital diseases, to pinpoint genes/proteins responsible for the susceptibility to different inherited conditions, to highlight targets of therapeutic relevance, to suggest drug repurposing, and even to clarify causal relationships that make modifiable some environmental risk factors. Though these studies usually take long time to be concluded and, above all, to translate their discoveries to patients' bedside, the scientific community moved really fast to deliver genetic signals underlying different COVID-19 phenotypes. In this Review, besides a concise description of COVID-19 symptomatology and of SARS-CoV-2 mechanism of infection, we aimed to recapitulate the current literature in terms of host genetic factors that specifically associate with an increased severity of the disease.

X marks the spot in autoimmunity.

INTRODUCTION: Autoimmune diseases mostly affect females. Besides hormones, several factors related to chromosome X have been called in action to explain this sex predominance. AREAS COVERED: This paper provides an overview on the role of chromosome X (chrX) in explaining why females have higher susceptibility to autoimmunity. The work outlines some essential concepts regarding chrX inactivation, escape from chrX inactivation and the evolutionary history of chrX. In addition, we will discuss the concept of gene escape in immune cells, with examples related to specific X-linked genes and autoimmune diseases. EXPERT OPINION: There is growing evidence that many genes present on chrX escape inactivation, and some of them have significant immune-mediated functions. In immune cells of female individuals the escape of these genes is not constant, but the knowledge of the mechanisms controlling this plasticity are not completely understood. Future studies aimed at the characterization of these modifications at single-cell resolution, together with conformational 3D studies of the inactive X chromosome, will hopefully help to fill this gap of knowledge.

LLM-PBC: Logic Learning Machine-Based Explainable Rules Accurately Stratify the Genetic Risk of Primary Biliary Cholangitis.

BACKGROUND: The application of Machine Learning (ML) to genetic individual-level data represents a foreseeable advancement for the field, which is still in its infancy. Here, we aimed to evaluate the feasibility and accuracy of an ML-based model for disease risk prediction applied to Primary Biliary Cholangitis (PBC). METHODS: Genome-wide significant variants identified in subjects of European ancestry in the recently released second international meta-analysis of GWAS in PBC were used as input data. Quality-checked, individual genomic data from two Italian cohorts were used. The ML included the following steps: import of genotype and phenotype data, genetic variant selection, supervised classification of PBC by genotype, generation of "if-then" rules for disease prediction by logic learning machine (LLM), and model validation in a different cohort. RESULTS: The training cohort included 1345 individuals: 444 were PBC cases and 901 were healthy controls. After pre-processing, 41,899 variants entered the analysis. Several configurations of parameters related to feature selection were simulated. The best LLM model reached an Accuracy of 71.7%, a Matthews correlation coefficient of 0.29, a Youden's value of 0.21, a Sensitivity of 0.28, a Specificity of 0.93, a Positive Predictive Value of 0.66, and a Negative Predictive Value of 0.72. Thirty-eight rules were generated. The rule with the highest covering (19.14) included the following genes: RIN3, KANSL1, TIMMDC1, TNPO3. The validation cohort included 834 individuals: 255 cases and 579 controls. By applying the ruleset derived in the training cohort, the Area under the Curve of the model was 0.73. CONCLUSIONS: This study represents the first illustration of an ML model applied to common variants associated with PBC. Our approach is computationally feasible, leverages individual-level data to generate intelligible rules, and can be used for disease prediction in at-risk individuals.

The coding and long noncoding single-cell atlas of the developing human fetal striatum.

Deciphering how the human striatum develops is necessary for understanding the diseases that affect this region. To decode the transcriptional modules that regulate this structure during development, we compiled a catalog of 1116 long intergenic noncoding RNAs (lincRNAs) identified de novo and then profiled 96,789 single cells from the early human fetal striatum. We found that D1 and D2 medium spiny neurons (D1- and D2-MSNs) arise from a common progenitor and that lineage commitment is established during the postmitotic transition, across a pre-MSN phase that exhibits a continuous spectrum of fate determinants. We then uncovered cell type-specific gene regulatory networks that we validated through in silico perturbation. Finally, we identified human-specific lincRNAs that contribute to the phylogenetic divergence of this structure in humans. This work delineates the cellular hierarchies governing MSN lineage commitment.

MEDTEC Students against Coronavirus: Investigating the Role of Hemostatic Genes in the Predisposition to COVID-19 Severity.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the etiologic agent of the coronavirus disease 2019 (COVID-19) pandemic. Besides virus intrinsic characteristics, the host genetic makeup is predicted to account for the extreme clinical heterogeneity of the disease, which is characterized, among other manifestations, by a derangement of hemostasis associated with thromboembolic events. To date, large-scale studies confirmed that genetic predisposition plays a role in COVID-19 severity, pinpointing several susceptibility genes, often characterized by immunologic functions. With these premises, we performed an association study of common variants in 32 hemostatic genes with COVID-19 severity. We investigated 49,845 single-nucleotide polymorphism in a cohort of 332 Italian severe COVID-19 patients and 1668 controls from the general population. The study was conducted engaging a class of students attending the second year of the MEDTEC school (a six-year program, held in collaboration between Humanitas University and the Politecnico of Milan, allowing students to gain an MD in Medicine and a Bachelor's Degree in Biomedical Engineering). Thanks to their willingness to participate in the fight against the pandemic, we evidenced several suggestive hits (p < 0.001), involving the PROC, MTHFR, MTR, ADAMTS13, and THBS2 genes (top signal in PROC: chr2:127192625:G:A, OR = 2.23, 95%CI = 1.50-3.34, p = 8.77 × 10-5). The top signals in PROC, MTHFR, MTR, ADAMTS13 were instrumental for the construction of a polygenic risk score, whose distribution was significantly different between cases and controls (p = 1.62 × 10-8 for difference in median levels). Finally, a meta-analysis performed using data from the Regeneron database confirmed the contribution of the MTHFR variant chr1:11753033:G:A to the predisposition to severe COVID-19 (pooled OR = 1.21, 95%CI = 1.09-1.33, p = 4.34 × 10-14 in the weighted analysis).