X-chromosomal genetic variants are understudied but can yield valuable insights into sexually dimorphic human traits and diseases. We performed a sex-stratified cross-ancestry X-chromosome-wide association meta-analysis of seven kidney-related traits (n = 908,697), identifying 23 loci genome-wide significantly associated with two of the traits: 7 for uric acid and 16 for estimated glomerular filtration rate (eGFR), including four novel eGFR loci containing the functionally plausible prioritized genes ACSL4, CLDN2, TSPAN6 and the female-specific DRP2. Further, we identified five novel sex-interactions, comprising male-specific effects at FAM9B and AR/EDA2R, and three sex-differential findings with larger genetic effect sizes in males at DCAF12L1 and MST4 and larger effect sizes in females at HPRT1. All prioritized genes in loci showing significant sex-interactions were located next to androgen response elements (ARE). Five ARE genes showed sex-differential expressions. This study contributes new insights into sex-dimorphisms of kidney traits along with new prioritized gene targets for further molecular research.

• MeSH
• androgeny * genetika   MeSH
• celogenomová asociační studie * MeSH
• genetická predispozice k nemoci MeSH
• jednonukleotidový polymorfismus MeSH
• ledviny MeSH
• lidé MeSH
• lidské chromozomy X genetika   MeSH
• responzivní elementy MeSH
• tetraspaniny genetika   MeSH
• Check Tag
• lidé MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• metaanalýza MeSH

Pediatric steroid-sensitive nephrotic syndrome (pSSNS) is the most common childhood glomerular disease. Previous genome-wide association studies (GWAS) identified a risk locus in the HLA Class II region and three additional independent risk loci. But the genetic architecture of pSSNS, and its genetically driven pathobiology, is largely unknown. Here, we conduct a multi-population GWAS meta-analysis in 38,463 participants (2440 cases). We then conduct conditional analyses and population specific GWAS. We discover twelve significant associations-eight from the multi-population meta-analysis (four novel), two from the multi-population conditional analysis (one novel), and two additional novel loci from the European meta-analysis. Fine-mapping implicates specific amino acid haplotypes in HLA-DQA1 and HLA-DQB1 driving the HLA Class II risk locus. Non-HLA loci colocalize with eQTLs of monocytes and numerous T-cell subsets in independent datasets. Colocalization with kidney eQTLs is lacking but overlap with kidney cell open chromatin suggests an uncharacterized disease mechanism in kidney cells. A polygenic risk score (PRS) associates with earlier disease onset. Altogether, these discoveries expand our knowledge of pSSNS genetic architecture across populations and provide cell-specific insights into its molecular drivers. Evaluating these associations in additional cohorts will refine our understanding of population specificity, heterogeneity, and clinical and molecular associations.

• MeSH
• celogenomová asociační studie * MeSH
• dítě MeSH
• genetická predispozice k nemoci MeSH
• haplotypy MeSH
• jednonukleotidový polymorfismus MeSH
• lidé MeSH
• nefrotický syndrom * genetika   MeSH
• rizikové faktory MeSH
• Check Tag
• dítě MeSH
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• metaanalýza MeSH
• práce podpořená grantem MeSH
• Research Support, N.I.H., Extramural MeSH
• Research Support, U.S. Gov't, Non-P.H.S. MeSH

BACKGROUND: An early diagnosis together with an accurate disease progression monitoring of multiple sclerosis is an important component of successful disease management. Prior studies have established that multiple sclerosis is correlated with speech discrepancies. Early research using objective acoustic measurements has discovered measurable dysarthria. METHOD: The objective was to determine the potential clinical utility of machine learning and deep learning/AI approaches for the aiding of diagnosis, biomarker extraction and progression monitoring of multiple sclerosis using speech recordings. A corpus of 65 MS-positive and 66 healthy individuals reading the same text aloud was used for targeted acoustic feature extraction utilizing automatic phoneme segmentation. A series of binary classification models was trained, tuned, and evaluated regarding their Accuracy and area-under-the-curve. RESULTS: The Random Forest model performed best, achieving an Accuracy of 0.82 on the validation dataset and an area-under-the-curve of 0.76 across 5 k-fold cycles on the training dataset. 5 out of 7 acoustic features were statistically significant. CONCLUSION: Machine learning and artificial intelligence in automatic analyses of voice recordings for aiding multiple sclerosis diagnosis and progression tracking seems promising. Further clinical validation of these methods and their mapping onto multiple sclerosis progression is needed, as well as a validating utility for English-speaking populations.

• MeSH
• lidé MeSH
• pilotní projekty MeSH
• řeč * MeSH
• roztroušená skleróza * MeSH
• strojové učení MeSH
• umělá inteligence MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

Understanding cell types and mechanisms of dental growth is essential for reconstruction and engineering of teeth. Therefore, we investigated cellular composition of growing and non-growing mouse and human teeth. As a result, we report an unappreciated cellular complexity of the continuously-growing mouse incisor, which suggests a coherent model of cell dynamics enabling unarrested growth. This model relies on spatially-restricted stem, progenitor and differentiated populations in the epithelial and mesenchymal compartments underlying the coordinated expansion of two major branches of pulpal cells and diverse epithelial subtypes. Further comparisons of human and mouse teeth yield both parallelisms and differences in tissue heterogeneity and highlight the specifics behind growing and non-growing modes. Despite being similar at a coarse level, mouse and human teeth reveal molecular differences and species-specific cell subtypes suggesting possible evolutionary divergence. Overall, here we provide an atlas of human and mouse teeth with a focus on growth and differentiation.

• MeSH
• buněčná diferenciace * genetika   MeSH
• dospělí MeSH
• epitelové buňky MeSH
• genetická heterogenita MeSH
• kmenové buňky cytologie   MeSH
• lidé MeSH
• mezoderm cytologie   růst a vývoj   metabolismus   MeSH
• mladiství MeSH
• mladý dospělý MeSH
• modely u zvířat MeSH
• moláry cytologie   růst a vývoj   MeSH
• myši inbrední C57BL MeSH
• myši MeSH
• odontoblasty MeSH
• řezáky cytologie   růst a vývoj   MeSH
• vývojová regulace genové exprese MeSH
• zuby cytologie   růst a vývoj   MeSH
• zvířata MeSH
• Check Tag
• dospělí MeSH
• lidé MeSH
• mladiství MeSH
• mladý dospělý MeSH
• mužské pohlaví MeSH
• myši MeSH
• ženské pohlaví MeSH
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Research Support, N.I.H., Extramural MeSH

Asparaginase-associated pancreatitis is a life-threatening toxicity to childhood acute lymphoblastic leukemia treatment. To elucidate genetic predisposition and asparaginase-associated pancreatitis pathogenesis, ten trial groups contributed remission samples from patients aged 1.0-17.9 years treated for acute lymphoblastic leukemia between 2000 and 2016. Cases (n=244) were defined by the presence of at least two of the following criteria: (i) abdominal pain; (ii) levels of pancreatic enzymes ≥3 × upper normal limit; and (iii) imaging compatible with pancreatitis. Controls (n=1320) completed intended asparaginase therapy, with 78% receiving ≥8 injections of pegylated-asparaginase, without developing asparaginase-associated pancreatitis. rs62228256 on 20q13.2 showed the strongest association with the development of asparaginase-associated pancreatitis (odds ratio=3.75; P=5.2×10-8). Moreover, rs13228878 (OR=0.61; P=7.1×10-6) and rs10273639 (OR=0.62; P=1.1×10-5) on 7q34 showed significant association with the risk of asparaginase-associated pancreatitis. A Dana Farber Cancer Institute ALL Consortium cohort consisting of patients treated on protocols between 1987 and 2004 (controls=285, cases=33), and the Children's Oncology Group AALL0232 cohort (controls=2653, cases=76) were available as replication cohorts for the 20q13.2 and 7q34 variants, respectively. While rs62228256 was not validated as a risk factor (P=0.77), both rs13228878 (P=0.03) and rs10273639 (P=0.04) were. rs13228878 and rs10273639 are in high linkage disequilibrium (r2=0.94) and associated with elevated expression of the PRSS1 gene, which encodes for trypsinogen, and are known risk variants for alcohol-associated and sporadic pancreatitis in adults. Intra-pancreatic trypsinogen cleavage to proteolytic trypsin induces autodigestion and pancreatitis. In conclusion, this study finds a shared genetic predisposition between asparaginase-associated pancreatitis and non-asparaginase-associated pancreatitis, and targeting the trypsinogen activation pathway may enable identification of effective interventions for asparaginase-associated pancreatitis.

• MeSH
• akutní lymfatická leukemie komplikace   farmakoterapie   genetika   MeSH
• alely MeSH
• antitumorózní látky aplikace a dávkování   škodlivé účinky   MeSH
• asparaginasa aplikace a dávkování   škodlivé účinky   MeSH
• biologické modely MeSH
• dítě MeSH
• fenotyp MeSH
• genetická predispozice k nemoci MeSH
• genetická variace * MeSH
• genetické asociační studie MeSH
• genotyp MeSH
• jednonukleotidový polymorfismus MeSH
• kojenec MeSH
• lidé MeSH
• mladiství MeSH
• pankreatitida etiologie   MeSH
• polyethylenglykoly aplikace a dávkování   škodlivé účinky   MeSH
• předškolní dítě MeSH
• trypsin genetika   MeSH
• trypsinogen genetika   MeSH
• Check Tag
• dítě MeSH
• kojenec MeSH
• lidé MeSH
• mladiství MeSH
• mužské pohlaví MeSH
• předškolní dítě MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH