Publications

Abstract Background Evidence shows sex differences in cognitive performance in Alzheimer’s disease (AD). However, studies exploring whether genetic predisposition to AD differs in cognition among sex are scarce. We aimed to evaluate whether the influence of AD genetic liability in cognition differs among sex in cognitively unimpaired (CU) individuals in the AD continuum . Method We included 318 CU individuals from the ALFA+ cohort (Table 1). Cognitive change (∼3‐year follow‐up) was measured with a PACC and for individual cognitive domains. Polygenic scores estimating each participant’s genetic predisposition to AD were calculated with (PRS‐AD) and without (PRS‐ADnoAPOE) considering the APOE region (threshold = 5×10‐6). Amyloid positivity (Aβ+) was defined as cerebrospinal fluid (CSF) Aβ42/40<0.0071. Generalized linear models stratified by sex and amyloid status were performed to assess the association between cognitive change and genetic predisposition to AD. Models were corrected by age, years of education, and time between visits. Models were additionally corrected by baseline Jack’s cortical thickness AD signature as a marker of neurodegeneration. Result In Aβ+ women (n = 65), a higher genetic predisposition to AD was associated with steeper memory ( p PRS_AD = 0.04; p PRS_ADnoAPOE = 0.01) and executive function ( p PRS_ADnoAPOE = 0.001) decline after correcting by brain AD signature. In Aβ+ men (n = 44), a higher genetic predisposition to AD was associated with worse follow‐up performance on attention ( p PRS_AD = 0.05, p PRS_ADnoAPOE = 0.04), and results did not remain significant after correcting by brain AD signature (Figure 1). In Aβ‐, genetic predisposition to AD was also associated with executive function decline in women (n = 122) ( p PRS_AD = 0.16, p PRS_ADnoAPOE = 0.02), while Aβ‐ men (n = 87) showed worse follow‐up performance on visual processing ( p PRS_AD = 0.251, p PRS_ADnoAPOE = 0.001). Results remained significant after correcting by brain AD signature (Figure 2). Conclusion Our results showed that genetic predisposition to AD is associated with changes in different cognitive domains in men and women. These findings will contribute to developing precision medicine approaches in AD encompassing sex‐sensitive strategies for prevention.

Epigenetic changes through altered DNA methylation have been implicated in critical aspects of tumor progression, and have been extensively studied in a variety of cancer types. In contrast, our current knowledge of the aberrant genomic DNA methylation in tumor-associated fibroblasts (TAFs) or other stromal cells that act as critical coconspirators of tumor progression is very scarce. To address this gap of knowledge, we conducted genome-wide DNA methylation profiling on lung TAFs and paired control fibroblasts (CFs) from non-small cell lung cancer patients using the HumanMethylation450 microarray. We found widespread DNA hypomethylation concomitant with focal gain of DNA methylation in TAFs compared to CFs. The aberrant DNA methylation landscape of TAFs had a global impact on gene expression and a selective impact on the TGF-β pathway. The latter included promoter hypermethylation-associated SMAD3 silencing, which was associated with hyperresponsiveness to exogenous TGF-β1 in terms of contractility and extracellular matrix deposition. In turn, activation of CFs with exogenous TGF-β1 partially mimicked the epigenetic alterations observed in TAFs, suggesting that TGF-β1 may be necessary but not sufficient to elicit such alterations. Moreover, integrated pathway-enrichment analyses of the DNA methylation alterations revealed that a fraction of TAFs may be bone marrow-derived fibrocytes. Finally, survival analyses using DNA methylation and gene expression datasets identified aberrant DNA methylation on the EDARADD promoter sequence as a prognostic factor in non-small cell lung cancer patients. Our findings shed light on the unique origin and molecular alterations underlying the aberrant phenotype of lung TAFs, and identify a stromal biomarker with potential clinical relevance.

<p>Panel of antibodies used in flow cytometry experiments.</p>

Notch1 activation is essential for T-lineage specification of lymphomyeloid progenitors seeding the thymus. Progression along the T cell lineage further requires cooperative signaling provided by the interleukin 7 receptor (IL-7R), but the molecular mechanisms responsible for the dynamic and lineage-specific regulation of IL-7R during thymopoiesis are unknown. We show that active Notch1 binds to a conserved CSL-binding site in the human IL7R gene promoter and critically regulates IL7R transcription and IL-7R α chain (IL-7Rα) expression via the CSL–MAML complex. Defective Notch1 signaling selectively impaired IL-7Rα expression in T-lineage cells, but not B-lineage cells, and resulted in a compromised expansion of early human developing thymocytes, which was rescued upon ectopic IL-7Rα expression. The pathological implications of these findings are demonstrated by the regulation of IL-7Rα expression downstream of Notch1 in T cell leukemias. Thus, Notch1 controls early T cell development, in part by regulating the stage- and lineage-specific expression of IL-7Rα.

Abstract Objectives Triple-negative breast cancer (TNBC) is a highly aggressive breast cancer subtype with limited treatment options. Unlike other breast cancer subtypes, the scarcity of specific therapies and greater frequencies of distant metastases contribute to its aggressiveness. We aimed to find epigenetic changes that aid in the understanding of the dissemination process of these cancers. Data description Using CRISPR/Cas9, our experimental approach led us to identify and disrupt an insulator element, IE8, whose activity seemed relevant for cell invasion. The experiments were performed in two well-established TNBC cellular models, the MDA-MB-231 and the MDA-MB-436. To gain insights into the underlying molecular mechanisms of TNBC invasion ability, we generated and characterized high-resolution chromatin interaction (Hi-C) and chromatin accessibility (ATAC-seq) maps in both cell models and complemented these datasets with gene expression profiling (RNA-seq) in MDA-MB-231, the cell line that showed more significant changes in chromatin accessibility. Altogether, our data provide a comprehensive resource for understanding the spatial organization of the genome in TNBC cells, which may contribute to accelerating the discovery of TNBC-specific alterations triggering advances for this devastating disease.

<p>Panel of antibodies used in flow cytometry experiments.</p>

<p>DNA methylation array results with 6B4 antiCD137 mAb</p>

<p>Supplementary Figure 4. Effect of KAT6B shRNA-mediated depletion in the growth rate according to the XTT assay</p>

Additional file 2: Supplementary Table 1. Linear regression estimates for cognition outcomes in the entire sample. All models are adjusted for covariates: age, sex, education, and APOE status. Supplementary Table 2. Linear regression estimates for neuroimaging outcomes (i.e., Alzheimer’s disease and aging signatures) outcome in the entire sample. All models are adjusted for covariates: age, sex, education, and APOE status. Supplementary Table 3. Linear regression estimates for CSF biomarkers outcomes in the entire sample. All models are adjusted for covariates: age, sex, education, and APOE status. Supplementary Table 4. Linear regression estimates for cognition outcomes in APOE-ɛ4 carriers. All models are adjusted for covariates: age, sex, and education. Supplementary Table 5. Linear regression estimates for neuroimaging outcomes (i.e., Alzheimer’s disease and aging signatures) in APOE-ɛ4 carriers. All models are adjusted for covariates: age, sex, and education. Supplementary Table 6. Linear regression estimates for CSF biomarkers outcomes in APOE-ɛ4 carriers. All models are adjusted for covariates: age, sex, and education. Supplementary Table 7. Linear regression estimates for cognition outcomes in APOE-ɛ4 non-carriers. All models are adjusted for covariates: age, sex, and education. Supplementary Table 8. Linear regression estimates for neuroimaging outcomes (i.e., Alzheimer’s disease and aging signatures) in APOE-ɛ4 non-carriers. All models are adjusted for covariates: age, sex, and education. Supplementary Table 9. Linear regression estimates for CSF biomarkers outcomes in APOE-ɛ4 carriers. All models are adjusted for covariates: age, sex, and education. Supplementary Table 10. Linear regression estimates for cognition outcomes among individuals at high genetic predisposition to AD. All models are adjusted for covariates: age, sex, and education. Supplementary Table 11. Linear regression estimates for neuroimaging outcomes (i.e., Alzheimer’s disease and aging signatures) among individuals at high genetic predisposition to AD. All models are adjusted for covariates: age, sex, and education. Supplementary Table 12. Linear regression estimates for CSF biomarkers outcomes (i.e., Alzheimer’s disease and aging signatures) among individuals at high genetic predisposition to AD. All models are adjusted for covariates: age, sex, and education. Supplementary Table 13. Linear regression estimates for cognition outcomes among individuals at low genetic predisposition to AD. All models are adjusted for covariates: age, sex, and education. Supplementary Table 14. Linear regression estimates for neuroimaging outcomes (i.e., Alzheimer’s disease and aging signatures) among individuals at low genetic predisposition to AD. All models are adjusted for covariates: age, sex, and education. Supplementary Table 15. Linear regression estimates for CSF biomarkers outcomes among individuals at low genetic predisposition to AD. All models are adjusted for covariates: age, sex, and education.

Clinico-pathological features of the fourth CRC patient cohort. (XLSX 10 kb)