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.

BRAF V600E in a preclinical model of pleomorphic Xanthoastrocytoma: Analysis of the tumor microenvironment and immune cell infiltration dynamics in vivo.

Low-grade glioma (LGG) is the most common brain tumor affecting pediatric patients (pLGG) and BRAF mutations constitute the most frequent genetic alterations. Within the spectrum of pLGGs, approximately 70%-80% of pediatric patients diagnosed with transforming pleomorphic xanthoastrocytoma (PXA) harbor the BRAF V600E mutation. However, the impact of glioma BRAF V600E cell regulation of tumor-infiltrating immune cells and their contribution to tumor progression remains unclear. Moreover, the efficacy of BRAF inhibitors in treating pLGGs is limited compared with their impact on BRAF-mutated melanoma. Here we report a novel immunocompetent RCAS-BRAF V600E murine glioma model. Pathological assessment indicates this model seems to be consistent with diffuse gliomas and morphological features of PXA. Our investigations revealed distinct immune cell signatures associated with increased trafficking and activation within the tumor microenvironment (TME). Intriguingly, immune system activation within the TME also generated a pronounced inflammatory response associated with dysfunctional CD8+ T cells, increased presence of immunosuppressive myeloid cells and regulatory T cells. Further, our data suggests tumor-induced inflammatory processes, such as cytokine storm. These findings suggest a complex interplay between tumor progression and the robust inflammatory response within the TME in preclinical BRAF V600E LGGs, which may significantly influence animal survival.

Whole-exome sequencing reveals an association of rs112065068 in TGOLN2 gene with distant metastasis of non-small cell lung cancer.

Early prediction and prevention of recurring illness is critical for improving the survival rates of patients with non-small cell lung cancer (NSCLC). Previously, we demonstrated that the presence of premalignant epithelial changes in the small bronchi distant to the primary tumor is associated with NSCLC progression: isolated basal cell hyperplasia (iBCH) indicates a high risk of distant metastasis, BCH combined with squamous metaplasia (BCHSM) - a high risk of locoregional recurrence. Here, we aimed to identify germline single nucleotide variants (SNVs) and insertions and deletions (InDels) associated with distant metastasis and locoregional recurrence in cases with iBCH and BCHSM using whole-exome sequencing of 172 NSCLC patients. The rs112065068 of the TGOLN2 gene was identified only in iBCH patients and was associated with a high risk of distant metastasis (P < .001) and worse metastasis-free survival (HR = 4.19 (95 %CI 1.97-8.93); P < .001). This variant was validated in a group of 109 NSCLC patients using real-time PCR and Sanger sequencing analyses. To our knowledge, this study is the first to identify a germline variant associated with NSCLC distant metastasis.

Germline cancer susceptibility in individuals with melanoma.

BACKGROUND: Prior studies have estimated a small number of individuals with melanoma (2%-2.5%) have germline cancer predisposition, yet a recent twin study suggested melanoma has the highest hereditability among cancers. OBJECTIVE: To determine the incidence of hereditary melanoma and characterize the spectrum of cancer predisposition genes that may increase the risk of melanoma. METHODS: Four hundred individuals with melanoma and personal or family history of cancers underwent germline testing of >80 cancer predisposition genes. Comparative analysis of germline data was performed on 3 additional oncologic and dermatologic data sets. RESULTS: Germline pathogenic/likely pathogenic (P/LP) variants were identified in 15.3% (61) individuals with melanoma. Most variants (41, 67%) involved genes considered unrelated to melanoma (BLM, BRIP1, CHEK2, MLH1, MSH2, PMS2, RAD51C). A third (20, 33%) were in genes previously associated with familial melanoma (BAP1, BRCA2, CDKN2A, MITF, TP53). Nearly half (30, 46.9%) of P/LP variants were in homologous repair deficiency genes. Validation cohorts demonstrated P/LP rates of 10.6% from an unselected oncologic cohort, 15.8% from a selected commercial testing cohort, and 14.5% from a highly selected dermatologic study. LIMITATIONS: Cohorts with varying degrees of selection, some retrospective. CONCLUSION: Germline predisposition in individuals with melanoma is common, with clinically actionable findings diagnosed in 10.6% to 15.8%.

Homeostatic iron regulatory protein drives glioblastoma growth via tumor cell-intrinsic and sex-specific responses.

Background: Glioblastoma (GBM) displays alterations in iron that drive proliferation and tumor growth. Iron regulation is complex and involves many regulatory mechanisms, including the homeostatic iron regulator (HFE) gene, which encodes the homeostatic iron regulatory protein. While HFE is upregulated in GBM and correlates with poor survival outcomes, the function of HFE in GBM remains unclear. Methods: We interrogated the impact of cell-intrinsic Hfe expression on proliferation and survival of intracranially implanted animals through genetic gain- and loss-of-function approaches in syngeneic mouse glioma models, along with in vivo immune assessments. We also determined the expression of iron-associated genes and their relationship to survival in GBM using public data sets and used transcriptional profiling to identify differentially expressed pathways in control compared to Hfe-knockdown cells. Results: Overexpression of Hfe accelerated GBM proliferation and reduced animal survival, whereas suppression of Hfe induced apoptotic cell death and extended survival, which was more pronounced in females and associated with attenuation of natural killer cells and CD8+ T cell activity. Analysis of iron gene signatures in Hfe-knockdown cells revealed alterations in the expression of several iron-associated genes, suggesting global disruption of intracellular iron homeostasis. Further analysis of differentially expressed pathways revealed oxidative stress as the top pathway upregulated following Hfe loss. Hfe knockdown indeed resulted in enhanced 55Fe uptake and generation of reactive oxygen species. Conclusions: These findings reveal an essential function for HFE in GBM cell growth and survival, as well as a sex-specific interaction with the immune response.

Public platform with 39,472 exome control samples enables association studies without genotype sharing.

Acquiring a sufficiently powered cohort of control samples matched to a case sample can be time-consuming or, in some cases, impossible. Accordingly, an ability to leverage genetic data from control samples that were already collected elsewhere could dramatically improve power in genetic association studies. Sharing of control samples can pose significant challenges, since most human genetic data are subject to strict sharing regulations. Here, using the properties of singular value decomposition and subsampling algorithm, we developed a method allowing selection of the best-matching controls in an external pool of samples compliant with personal data protection and eliminating the need for genotype sharing. We provide access to a library of 39,472 exome sequencing controls at http://dnascore.net enabling association studies for case cohorts lacking control subjects. Using this approach, control sets can be selected from this online library with a prespecified matching accuracy, ensuring well-calibrated association analysis for both rare and common variants.

CR1 variants contribute to FSGS susceptibility across multiple populations.

Focal segmental glomerulosclerosis (FSGS) is a common cause of nephrotic syndrome with an annual incidence in the United States in African-Americans compared to European-Americans of 24 cases and 5 cases per million, respectively. Among glomerular diseases in Europe and Latin-America, FSGS was the second most frequent diagnosis, and in Asia the fifth. We expand previous efforts in understanding genetics of FSGS by performing a case-control study involving ethnically-diverse groups FSGS cases (726) and a pool of controls (13,994), using panel sequencing of approximately 2,500 podocyte-expressed genes. Through rare variant association tests, we replicated known risk genes - KANK1, COL4A4, and APOL1. A novel significant association was observed for the gene encoding complement receptor 1 (CR1). High-risk rare variants in CR1 in the European-American cohort were commonly observed in Latin- and African-Americans. Therefore, a combined rare and common variant analysis was used to replicate the CR1 association in non-European populations. The CR1 risk variant, rs17047661, gives rise to the Sl1/Sl2 (R1601G) allele that was previously associated with protection against cerebral malaria. Pleiotropic effects of rs17047661 may explain the difference in allele frequencies across continental ancestries and suggest a possible role for genetically-driven alterations of adaptive immunity in the pathogenesis of FSGS.

Mendelian Randomization Analysis reveals Inverse Genetic Risks between Skin Cancers and Vitiligo.

Several observational studies have demonstrated a consistent pattern of decreased melanoma risk among patients with vitiligo. More recently, this finding has been supported by a suggested genetic relationship between the two entities, with certain variants significantly associated with an increased risk of melanoma, basal cell carcinoma, and squamous cell carcinoma but a decreased risk of vitiligo. We compared 48 associated variants from a recently published GWAS and identified three variants-located in the TYR, MC1R-DEF8, and RALY-EIF2S2-ASIP-AHCY-ITCH loci- that correlated with an increased risk for melanoma, basal cell carcinoma, and squamous cell carcinoma and a decreased risk for vitiligo. We then used results of skin cancers and vitiligo GWAS to compare the shared genetic properties between these two traits through an unbiased Mendelian randomization analysis. Our results suggest that the inverse genetic relationship between common skin cancers and vitiligo is broader than previously reported owing to the influence of shared genome-wide significant associations.

Detecting biased validation of predictive models in the positive-unlabeled setting: disease gene prioritization case study.

Motivation: Positive-unlabeled data consists of points with either positive or unknown labels. It is widespread in medical, genetic, and biological settings, creating a high demand for predictive positive-unlabeled models. The performance of such models is usually estimated using validation sets, assumed to be selected completely at random (SCAR) from known positive examples. For certain metrics, this assumption enables unbiased performance estimation when treating positive-unlabeled data as positive/negative. However, the SCAR assumption is often adopted without proper justifications, simply for the sake of convenience. Results: We provide an algorithm that under the weak assumptions of a lower bound on the number of positive examples can test for the violation of the SCAR assumption. Applying it to the problem of gene prioritization for complex genetic traits, we illustrate that the SCAR assumption is often violated there, causing the inflation of performance estimates, which we refer to as validation bias. We estimate the potential impact of validation bias on performance estimation. Our analysis reveals that validation bias is widespread in gene prioritization data and can significantly overestimate the performance of models. This finding elucidates the discrepancy between the reported good performance of models and their limited practical applications. Availability and implementation: Python code with examples of application of the validation bias detection algorithm is available at github.com/ArtomovLab/ValidationBias.

Transgenerational and intergenerational effects of early childhood famine exposure in the cohort of offspring of Leningrad Siege survivors.

Famine exposure during early life development can affect disease risk in late-life period, yet, transmission of phenotypic features from famine-exposed individuals to the next generations has not been well characterized. The purpose of our case-control study was to investigate the association of parental starvation in the perinatal period and the period of early childhood with the phenotypic features observed in two generations of descendants of Leningrad siege survivors. We examined 54 children and 30 grandchildren of 58 besieged Leningrad residents who suffered from starvation in early childhood and prenatal age during the Second World War. Controls from the population-based national epidemiological ESSE-RF study (n = 175) were matched on sex, age and body mass index (BMI). Phenotypes of controls and descendants (both generations, children and grandchildren separately) were compared, taking into account multiple testing. Comparison of two generations descendants with corresponding control groups revealed significantly higher creatinine and lower glomerular filtration rate (GFR), both in meta-analysis and in independent analyses. The mean values of GFR for all groups were within the normal range (GFR less than 60 mL/min/1.73 m2 was recorded in 2 controls and no one in DLSS). Additionally, independent of the creatinine level, differences in the eating pattern were detected: insufficient fish and excessive red meat consumption were significantly more frequent in the children of the Leningrad siege survivors compared with controls. Blood pressure, blood lipids and glucose did not differ between the groups. Parental famine exposure in early childhood may contribute to a decrease in kidney filtration capacity and altered eating pattern in the offspring of famine-exposed individuals.

Discordant calls across genotype discovery approaches elucidate variants with systematic errors.

Large-scale high-throughput sequencing data sets have been transformative for informing clinical variant interpretation and for use as reference panels for statistical and population genetic efforts. Although such resources are often treated as ground truth, we find that in widely used reference data sets such as the Genome Aggregation Database (gnomAD), some variants pass gold-standard filters, yet are systematically different in their genotype calls across genotype discovery approaches. The inclusion of such discordant sites in study designs involving multiple genotype discovery strategies could bias results and lead to false-positive hits in association studies owing to technological artifacts rather than a true relationship to the phenotype. Here, we describe this phenomenon of discordant genotype calls across genotype discovery approaches, characterize the error mode of wrong calls, provide a list of discordant sites identified in gnomAD that should be treated with caution in analyses, and present a metric and machine learning classifier trained on gnomAD data to identify likely discordant variants in other data sets. We find that different genotype discovery approaches have different sets of variants at which this problem occurs, but there are characteristic variant features that can be used to predict discordant behavior. Discordant sites are largely shared across ancestry groups, although different populations are powered for the discovery of different variants. We find that the most common error mode is that of a variant being heterozygous for one approach and homozygous for the other, with heterozygous in the genomes and homozygous reference in the exomes making up the majority of miscalls.

Gene, cell type, and drug prioritization analysis suggest genetic basis for the utility of diuretics in treating Alzheimer disease.

We introduce a user-friendly tool for risk gene, cell type, and drug prioritization for complex traits: GCDPipe. It uses gene-level GWAS-derived data and gene expression data to train a model for the identification of disease risk genes and relevant cell types. Gene prioritization information is then coupled with known drug target data to search for applicable drug agents based on their estimated functional effects on the identified risk genes. We illustrate the utility of our approach in different settings: identification of the cell types, implicated in disease pathogenesis, was tested in inflammatory bowel disease (IBD) and Alzheimer disease (AD); gene target and drug prioritization was tested in IBD and schizophrenia. The analysis of phenotypes with known disease-affected cell types and/or existing drug candidates shows that GCDPipe is an effective tool to unify genetic risk factors with cellular context and known drug targets. Next, analysis of the AD data with GCDPipe suggested that gene targets of diuretics, as an Anatomical Therapeutic Chemical drug subgroup, are significantly enriched among the genes prioritized by GCDPipe, indicating their possible effect on the course of the disease.

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.

The 22q11.2 region regulates presynaptic gene-products linked to schizophrenia.

It is unclear how the 22q11.2 deletion predisposes to psychiatric disease. To study this, we generated induced pluripotent stem cells from deletion carriers and controls and utilized CRISPR/Cas9 to introduce the heterozygous deletion into a control cell line. Here, we show that upon differentiation into neural progenitor cells, the deletion acted in trans to alter the abundance of transcripts associated with risk for neurodevelopmental disorders including autism. In excitatory neurons, altered transcripts encoded presynaptic factors and were associated with genetic risk for schizophrenia, including common and rare variants. To understand how the deletion contributed to these changes, we defined the minimal protein-protein interaction network that best explains gene expression alterations. We found that many genes in 22q11.2 interact in presynaptic, proteasome, and JUN/FOS transcriptional pathways. Our findings suggest that the 22q11.2 deletion impacts genes that may converge with psychiatric risk loci to influence disease manifestation in each deletion carrier.

Genotype imputation and polygenic score estimation in northwestern Russian population.

Numerous studies demonstrated the lack of transferability of polygenic score (PGS) models across populations and the problem arising from unequal presentation of ancestries across genetic studies. However, even within European ancestry there are ethnic groups that are rarely presented in genetic studies. For instance, Russians, being one of the largest, diverse, and yet understudied group in Europe. In this study, we evaluated the reliability of genotype imputation for the Russian cohort by testing several commonly used imputation reference panels (e.g. HRC, 1000G, HGDP). HRC, in comparison with two other panels, showed the most accurate results based on both imputation accuracy and allele frequency concordance between masked and imputed genotypes. We built polygenic score models based on GWAS results from the UK biobank, measured the explained phenotypic variance in the Russian cohort attributed to polygenic scores for 11 phenotypes, collected in the clinic for each participant, and finally explored the role of allele frequency discordance between the UK biobank and the study cohort in the resulting PGS performance.

Case report: Somatic mutations in microtubule dynamics-associated genes in patients with WNT-medulloblastoma tumors.

Medulloblastoma (MB) is the most common pediatric brain tumor which accounts for about 20% of all pediatric brain tumors and 63% of intracranial embryonal tumors. MB is considered to arise from precursor cell populations present during an early brain development. Most cases (~70%) of MB occur at the age of 1-4 and 5-9, but are also infrequently found in adults. Total annual frequency of pediatric tumors is about 5 cases per 1 million children. WNT-subtype of MB is characterized by a high probability of remission, with a long-term survival rate of about 90%. However, in some rare cases there may be increased metastatic activity, which dramatically reduces the likelihood of a favorable outcome. Here we report two cases of MB with a histological pattern consistent with desmoplastic/nodular (DP) and classic MB, and genetically classified as WNT-MB. Both cases showed putative causal somatic protein truncating mutations identified in microtubule-associated genes: ARID2, TUBB4A, and ANK3.

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.

Enhanced epigenetic profiling of classical human monocytes reveals a specific signature of healthy aging in the DNA methylome.

The impact of healthy aging on molecular programming of immune cells is poorly understood. Here, we report comprehensive characterization of healthy aging in human classical monocytes, with a focus on epigenomic, transcriptomic, and proteomic alterations, as well as the corresponding proteomic and metabolomic data for plasma, using healthy cohorts of 20 young and 20 older males (~27 and ~64 years old on average). For each individual, we performed eRRBS-based DNA methylation profiling, which allowed us to identify a set of age-associated differentially methylated regions (DMRs) - a novel, cell-type specific signature of aging in DNA methylome. Hypermethylation events were associated with H3K27me3 in the CpG islands near promoters of lowly-expressed genes, while hypomethylated DMRs were enriched in H3K4me1 marked regions and associated with age-related increase of expression of the corresponding genes, providing a link between DNA methylation and age-associated transcriptional changes in primary human cells.

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.

Cancer risks associated with the germline MITF(E318K) variant.

The MITF(E318K) variant confers moderate risk for cutaneous melanoma. While there are small studies suggesting that this risk is associated with other malignancies (e.g. renal cell carcinoma), little is known about the role of this variant in specifying risk for other cancers. In this study, we perform a systematic review and meta-analysis of the published data as a backdrop to a whole-exome sequence(WES)-based characterization of MITF(E318K) risk for various cancers in sporadic samples from the TCGA and several genetically-enriched patient cohorts. We found minimal evidence of MITF(E318K)'s contribution to non-melanoma cancer risk among individuals with low inherited risks of melanoma (OR 1.168; 95% CI 0.78-1.74; p = 0.454), suggesting that earlier reports of an association between this variant and other malignancies may be related to shared environmental or polygenic risk factors rather than MITF(E318K). Interestingly, an association was observed with uterine carcinosarcoma, (OR 9.24; 95% CI 2.08-37.17; p = 0.024), which was not previously described. While more research needs to be completed, this study will help update cancer screening recommendations for patients with the MITF(E318K) variant.