BackgroundThyroid cancer and thyroid autoimmunity are considered opposite extremes of immune-responses. However, several studies have suggested that thyroid cancer coexists with autoimmune thyroid diseases like Hashimoto Thyroiditis (HT) and Graves disease (GD). We have shown that the risk of developing thyroid cancer is higher in patients with a silent form of autoimmune thyroid disease -Euthyroid Hashimoto Thyroiditis-(EHT).MethodsWe analyzed data from 2633 consecutive patients with GD, HT, EHT and non-Autoimmune Thyroid Disease (Non-AITD) for the presence of Differentiated Thyroid Cancer (DTC). We further investigated the microenvironment, and cellular mechanism of protection from DTC in GD/EHT by ex-vivo aspirating infiltrates from thyroid samples. We also re-constituted in vitro the in-vivo microenvironment to mimic an in-vivo context. We isolated NK cells and differentiated macrophages into M1 and M2 phenotype from healthy human peripheral blood monocytes.ResultsDTC was less frequent/aggressive in GD as compared to EHT or Non-AITD. Intra-thyroidal immune-cell profiling revealed differential Natural Killer (NK) cell activity and macrophage polarization in the settings of GD versus EHT. In GD, NK-cells were activated, and macrophages showed M1-like phenotype whereas, in EHT, NK-cells were less active and macrophages displayed M2-like phenotype. Furthermore, in vitro co-cultures of NK-cells with differentiated macrophage subsets revealed that the presence of activated NK (NA) cells favors M1 macrophages, boosts macrophage action and amplifies the innate defense mechanisms. Moreover, co-culture of M2 macrophages with NA, increases the cytotoxicity of NK-cells and favors a pro-inflammatory microenvironment that reverts the anti-inflammatory M2 towards pro-inflammatory M1.ConclusionSurveillance innate immune-cells like Natural Killer (NK) cells and macrophages are complementary to each other in their actions. We discovered here that activated NK-cells in the background of the thyroid autoimmune disease, GD, drive macrophage differentiation to the M1/killer phenotype which in turn is cytotoxic to cancer cells and down regulates the M2/repair phenotype. Understanding the molecular basis of macrophage-NK cell interface in Thyroid Cancer, ETH and GD will open new vistas for immunopathology and therapeutic intervention. Macrophages/innate immunity can be modulated from M2 to M1 phenotype to help treat thyroid cancer as naturally done by GD.Electronic supplementary materialThe online version of this article (10.1186/s40425-018-0483-y) contains supplementary material, which is available to authorized users.

We have developed a transgenic mouse model of Type 1 Diabetes (T1D) in which human GAD65 is expressed in pancreatic β-cells, and human MHC-II is expressed on antigen presenting cells. Induced GAD65 antigen presentation activates T-cells, which initiates the downstream events leading to diabetes. In our humanized mice, we have shown downregulation of eukaryotic translation initiation factor 5 A (elF5A), expressed only in actively dividing mammalian cells. In-vivo inhibition of elF5A hypusination by deoxyhypusine synthase (DHS) inhibitor “GC7” was studied; DHS inhibitor alters the pathophysiology in our mouse model by catalyzing the crucial hypusination and the rate-limiting step of elF5A activation. In our mouse model, we have shown that inhibition of eIF5A resets the pro-inflammatory bias in the pancreatic microenvironment. There was: (a) reduction of Th1/Th17 response, (b) an increase in Treg numbers, (c) debase in IL17 and IL21 cytokines levels in serum, (d) lowering of anti-GAD65 antibodies, and (e) ablation of the ER stress that improved functionality of the β-cells, but minimal effect on the cytotoxic CD8 T-cell (CTL) mediated response. Conclusively, immune modulation, in the case of T1D, may help to manipulate inflammatory responses, decreasing disease severity, and may help manage T1D in early stages of disease. Our study also demonstrates that without manipulating the CTLs mediated response extensively, it is difficult to treat T1D.

Nucleotide sequence differences on the whole-genome scale have been computed for 1,092 people from 14 populations publicly available by the 1000 Genomes Project. Total number of differences in genetic variants between 96,464 human pairs has been calculated. The distributions of these differences for individuals within European, Asian, or African origin were characterized by narrow unimodal peaks with mean values of 3.8, 3.5, and 5.1 million, respectively, and standard deviations of 0.1–0.03 million. The total numbers of genomic differences between pairs of all known relatives were found to be significantly lower than their respective population means and in reverse proportion to the distance of their consanguinity. By counting the total number of genomic differences it is possible to infer familial relations for people that share down to 6% of common loci identical-by-descent. Detection of familial relations can be radically improved when only very rare genetic variants are taken into account. Counting of total number of shared very rare single nucleotide polymorphisms (SNPs) from whole-genome sequences allows establishing distant familial relations for persons with eighth and ninth degrees of relationship. Using this analysis we predicted 271 distant familial pairwise relations among 1,092 individuals that have not been declared by 1000 Genomes Project. Particularly, among 89 British and 97 Chinese individuals we found three British–Chinese pairs with distant genetic relationships. Individuals from these pairs share identical-by-descent DNA fragments that represent 0.001%, 0.004%, and 0.01% of their genomes. With affordable whole-genome sequencing techniques, very rare SNPs should become important genetic markers for familial relationships and population stratification.

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Marker sets used in US dairy genomic predictions were previously expanded by including high-density (HD) or sequence markers with the largest effects for Holstein breed only. Other non-Holstein breeds lacked enough HD genotyped animals to be used as a reference population at that time, and thus were not included in the genomic prediction. Recently, numbers of non-Holstein breeds genotyped using HD panels reached an acceptable level for imputation and marker selection, allowing HD genomic prediction and HD marker selection for Holstein plus 4 other breeds. Genotypes for 351,461 Holsteins, 347,570 Jerseys, 42,346 Brown Swiss, 9,364 Ayrshires (including Red dairy cattle), and 4,599 Guernseys were imputed to the HD marker list that included 643,059 SNP. The separate HD reference populations included Illumina BovineHD (San Diego, CA) genotypes for 4,012 Holsteins, 407 Jerseys, 181 Brown Swiss, 527 Ayrshires, and 147 Guernseys. The 643,059 variants included the HD SNP and all 79,254 (80K) genetic markers and QTL used in routine national genomic evaluations. Before imputation, approximately 91 to 97% of genotypes were unknown for each breed; after imputation, 1.1% of Holstein, 3.2% of Jersey, 6.7% of Brown Swiss, 4.8% of Ayrshire, and 4.2% of Guernsey alleles remained unknown due to lower density haplotypes that had no matching HD haplotype. The higher remaining missing rates in non-Holstein breeds are mainly due to fewer HD genotyped animals in the imputation reference populations. Allele effects for up to 39 traits were estimated separately within each breed using phenotypic reference populations that included up to 6,157 Jersey males and 110,130 Jersey females. Correlations of HD with 80K genomic predictions for young animals averaged 0.986, 0.989, 0.985, 0.992, and 0.978 for Jersey, Ayrshire, Brown Swiss, Guernsey, and Holstein breeds, respectively. Correlations were highest for yield traits (about 0.991) and lowest for foot angle and rear legs-side view (0.981and 0.982, respectively). Some HD effects were more than twice as large as the largest 80K SNP effect, and HD markers had larger effects than nearby 80K markers for many breed-trait combinations. Previous studies selected and included markers with large effects for Holstein traits; the newly selected HD markers should also improve non-Holstein and crossbred genomic predictions and were added to official US genomic predictions in April 2020.

A new undesirable genetic factor, neuropathy with splayed forelimbs (JNS), has been identified recently in the Jersey breed. Calves affected with JNS are unable to stand on splayed forelimbs that exhibit significant extensor rigidity and excessive lateral abduction at birth. Affected calves generally are alert at birth but exhibit neurologic symptoms, including spasticity of head and neck and convulsive behavior. Other symptoms reported include dislocated shoulders, congenital craniofacial anomalies, and degenerative myelopathy. Inheritance of an undesirable genetic factor was determined from a study of 16 affected calves reported by Jersey breeders across the United States. All of their pedigrees traced back on both paternal and maternal sides to a common ancestor born in 1995. Genotypes revealed that JNS is attributable to a specific haplotype on Bos taurus autosome 6. Currently 8.2% of the genotyped US Jersey population are carriers of the haplotype. Sequencing of the region of shared homozygosity revealed missense variant rs1116058914 at base 60,158,901 of the ARS-UCD1.2 reference map as the most concordant with the genetic condition and the most likely cause. The single-base G to A substitution is in the coding region of the last exon of UCHL1, which is conserved across species. Mutations in humans and gene knockouts in mice cause similar recessive symptoms and muscular degeneration. Since December 2020, carrier status has been tracked using the identified haplotype and reported for all 459,784 genotyped Jersey animals. With random mating, about 2,200 affected calves per year with losses of about $250,000 would result from the 1.3 million US Jersey cows in the national population. Selection and mating programs can reduce numbers of JNS-affected births using either the haplotype status or a direct gene test in the future. Breeders should report calf abnormalities to their breed association to help discover new defects such as JNS.

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Background Checkpoint inhibitor, anti-Programmed cell death protein1/Ligand (PD1 / PDL1) immunotherapy achieved great success in modulating the immune system to reinvigorate targeted immune fight against several types of cancer. However, patients’ clinical response to this cancer immunotherapy varies widely. Biomarkers that can predict the greatest response to the anti-PD1 immunotherapy could help to personalize the maximum benefit for the right patient.Results This study explored transcriptomic biomarkers that were associated with the response (or no-response) to the anti-PD1/PDL1 immunotherapy in seven types of cancer [Malignant Pleural Mesothelioma (n=8), Head and Neck cancer (n=3), Lung Non-Squamous cancer (n=15), Squamous Lung cancer (n=8), Melanoma (n=23), Melanoma Skin Metastasis (n=10), and Renal Cell Carcinoma (n=11)]. The most common differentially expressed genes (105 genes) were between melanoma skin metastasis and renal cell carcinoma; followed by malignant pleural mesothelioma and renal cell carcinoma, which had 79 common differentially expressed genes; then malignant pleural mesothelioma and melanoma skin metastasis, which had 46 differentially expressed genes in common. Many similar (parallel) and dissimilar (anti-parallel) gene expression signatures were identified in this study. Parallel signature Differentially Expressed Genes (DEGs) are genes up-regulated together in either response or no-response group of different types of cancer, while the anti-parallel DEGs show up-regulation in the response group of one type of cancer while same genes are up-regulated in the no-response group of another different type of cancers. Target of Myb1 like 1 Membrane Trafficking Protein gene (TOM1L1) was found to be common among malignant pleural mesothelioma, melanoma skin metastasis, and renal cell carcinoma and was up-regulated in the cancer patients’ samples that did not respond to the anti-PD1/PDL1 immunotherapy. This study also found that differentially expressed Plasminogen Activator, Urokinase Receptor gene (PLAUR), was common among squamous lung cancer, melanoma and melanoma skin metastasis, and was up-regulated in the patients’ samples that responded to the anti-PD1/PDL1 immunotherapy.Conclusion In summary, this study identified DEGs biomarkers that can predict the response or no-response to the anti-PD1 immunotherapy across seven types of cancer. It also affirms the attention to important genes like TOM1L1 and PLAUR for their potential function in the cancer dissemination and metastasis.