Oral and non-oral lichen planus show genetic heterogeneity and differential risk for autoimmune disease and oral cancer

Lichen planus (LP) is a T-cell-mediated inflammatory disease affecting squamous epithelia in many parts of the body, most often the skin and oral mucosa. Cutaneous LP is usually transient and oral LP (OLP) is most often chronic, so we performed a large-scale genetic and epidemiological study of LP to address whether the oral and non-oral subgroups have shared or distinct underlying pathologies and their overlap with autoimmune disease. Using lifelong records covering diagnoses, procedures, and clinic identity from 473,580 individuals in the FinnGen study, genome-wide association analyses were conducted on carefully constructed subcategories of OLP (n = 3,323) and non-oral LP (n = 4,356) and on the combined group. We identified 15 genome-wide significant associations in FinnGen and an additional 12 when meta-analyzed with UKBB (27 independent associations at 25 distinct genomic locations), most of which are shared between oral and non-oral LP. Many associations coincide with known autoimmune disease loci, consistent with the epidemiologic enrichment of LP with hypothyroidism and other autoimmune diseases. Notably, a third of the FinnGen associations demonstrate significant differences between OLP and non-OLP. We also observed a 13.6-fold risk for tongue cancer and an elevated risk for other oral cancers in OLP, in agreement with earlier reports that connect LP with higher cancer incidence. In addition to a large-scale dissection of LP genetics and comorbidities, our study demonstrates the use of comprehensive, multidimensional health registry data to address outstanding clinical questions and reveal underlying biological mechanisms in common but understudied diseases.

GWAS of depression in 4,520 individuals from the Russian population highlights the role of MAGI2 (S-SCAM) in the gut-brain axis

We present the results of the depression Genome-wide association studies study performed on a cohort of Russian-descent individuals, which identified a novel association at chromosome 7q21 locus. Gene prioritization analysis based on already known depression risk genes indicated MAGI2 (S-SCAM) as the most probable gene from the locus and potential susceptibility gene for the disease. Brain and gut expression patterns were the main features highlighting functional relatedness of MAGI2 to the previously known depression risk genes. Local genetic covariance analysis, analysis of gene expression, provided initial suggestive evidence of hospital anxiety and depression scale and diagnostic and statistical manual of mental disorders scales having a different relationship with gut-brain axis disturbance. It should be noted, that while several independent methods successfully in silico validate the role of MAGI2, we were unable to replicate genetic association for the leading variant in the MAGI2 locus, therefore the role of rs521851 in depression should be interpreted with caution.

Case Report: Supernormal Vascular Aging in Leningrad Siege Survivors

Age-related changes in the vascular system play an important role in the biological age and lifespan of a person and maybe affected from an early age onward. One of the indicators of changes in the vascular system is arterial wall stiffness and its main measure, i.e., carotid-femoral pulse wave velocity (cfPWV). We examined arterial wall stiffness in a sample of 305 Leningrad Siege survivors to assess how hunger and stressful conditions during fetal development and early childhood affected the state of the cardiovascular system at a later age and what factors may neutralize the negative impact sustained in early childhood. Here, we presented an evaluation of two unique patients with supernormal vascular aging (SUPERNOVA) phenotype from this cohort and described the details of congruence between hereditary resistance and practiced lifestyle yielding slower biological aging rate.

Clinical and genetic markers of prehypertension in North-Western Russian population

Introduction

Prehypertension is a medical classification for patients with above normal blood pressure (BP) but insufficient for confirming hypertension diagnosis. Condition is often asymptomatic as it gradually develops over the years, yet recent meta-analyses suggest that prehypertension is a significant risk factor for stroke and other cardiovascular diseases.

Methods

We analyzed phenotypic data from 879 (age 25–64) individuals without hypertension from a population based-sampling cohort of St. Petersburg region in the North-West of Russia to identify clinical risk factors associated with prehypertension condition. All patients were divided in two groups – optimal BP (systolic BP <120 mmHg and diastolic BP <80; N=426) and prehypertension (systolic BP in range 120–140 mmHg and diastolic BP in range 80–90 and not on antihypertensive therapy; N=453).

Results

Phenotypic analysis with linear regression was corrected for age, sex, smoking status, BMI and levels of LDL and HDL cholesterol (Figure 1). Interestingly, blood level of insulin was significantly associated with prehypertension status along with insulin resistance index, however, presence of diabetes diagnosis in medical history was not significant. Phenotypes associated with prehypertension suggest that prehypertension is often developing along with hyperinsulinemia.

Finally, we estimated polygenic risk scores (PRS) for hypertension using UK biobank GWAS summary statistics and confirmed that prehypertension is more frequent at earlier age in patients with higher genetic susceptibility (Figure 1, Figure 2).

Conclusions

Hyperinsulinemia and genetic susceptibility to hypertension are strong risk factors for prehypertension.

Funding Acknowledgement

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): This work was financially supported by the Ministry of Science and Higher Education of the Russian Federation (Agreement No. 075-15-2020-901) to Al.K. Figure 1. Clinical markers of prehypertensionFigure 2. Genetic markers of prehypertension

Prioritization of disease genes from GWAS using ensemble-based positive-unlabeled learning

A primary challenge in understanding disease biology from genome-wide association studies (GWAS) arises from the inability to directly implicate causal genes from association data. Integration of multiple-omics data sources potentially provides important functional links between associated variants and candidate genes. Machine-learning is well-positioned to take advantage of a variety of such data and provide a solution for the prioritization of disease genes. Yet, classical positive-negative classifiers impose strong limitations on the gene prioritization procedure, such as a lack of reliable non-causal genes for training. Here, we developed a novel gene prioritization tool-Gene Prioritizer (GPrior). It is an ensemble of five positive-unlabeled bagging classifiers (Logistic Regression, Support Vector Machine, Random Forest, Decision Tree, Adaptive Boosting), that treats all genes of unknown relevance as an unlabeled set. GPrior selects an optimal composition of algorithms to tune the model for each specific phenotype. Altogether, GPrior fills an important niche of methods for GWAS data post-processing, significantly improving the ability to pinpoint disease genes compared to existing solutions.

Retroelement-Linked H3K4me1 Histone Tags Uncover Regulatory Evolution Trends of Gene Enhancers and Feature Quickly Evolving Molecular Processes in Human Physiology

Background: Retroelements (REs) are mobile genetic elements comprising ~40% of human DNA. They can reshape expression patterns of nearby genes by providing various regulatory sequences. The proportion of regulatory sequences held by REs can serve a measure of regulatory evolution rate of the respective genes and molecular pathways. Methods: We calculated RE-linked enrichment scores for individual genes and molecular pathways based on ENCODE project epigenome data for enhancer-specific histone modification H3K4me1 in five human cell lines. We identified consensus groups of molecular processes that are enriched and deficient in RE-linked H3K4me1 regulation. Results: We calculated H3K4me1 RE-linked enrichment scores for 24,070 human genes and 3095 molecular pathways. We ranked genes and pathways and identified those statistically significantly enriched and deficient in H3K4me1 RE-linked regulation. Conclusion: Non-coding RNA genes were statistically significantly enriched by RE-linked H3K4me1 regulatory modules, thus suggesting their high regulatory evolution rate. The processes of gene silencing by small RNAs, DNA metabolism/chromatin structure, sensory perception/neurotransmission and lipids metabolism showed signs of the fastest regulatory evolution, while the slowest processes were connected with immunity, protein ubiquitination/degradation, cell adhesion, migration and interaction, metals metabolism/ion transport, cell death, intracellular signaling pathways.