Background & Aims We evaluated differences in treatment of black vs white patients with colon cancer and assessed their effects on survival, based on cancer stage. Methods We collected data from the ...Surveillance, Epidemiology, and End Results–Medicare database and identified 6190 black and 61,951 white patients with colon cancer diagnosed from 1998 through 2009 and followed up through 2011. Three sets of 6190 white patients were matched sequentially, using a minimum distance strategy, to the same set of 6190 black patients based on demographic (age; sex; diagnosis year; and Surveillance, Epidemiology, and End Results registry), tumor presentation (demographic plus comorbidities, tumor stage, grade, and size), and treatment (presentation plus therapies) variables. We conducted sensitivity analyses to explore the effects of socioeconomic status in a subcohort that included 2000 randomly selected black patients. Racial differences in treatment were assessed using a logistic regression model; their effects on racial survival disparity were evaluated using the Kaplan–Meier method and the Cox proportional hazards model. Results After patients were matched for demographic variables, the absolute 5-year difference in survival between black and white patients was 8.3% (white, 59.2% 5-y survival; blacks, 50.9% 5-y survival) ( P < .0001); this value decreased significantly, to 5.0% ( P < .0001), after patients were matched for tumor presentation, and decreased to 4.9% ( P < .0001) when patients were matched for treatment. Differences in treatment therefore accounted for 0.1% of the 8.3% difference in survival between black and white patients. After patients were matched for tumor presentation, racial disparities were observed in almost all types of treatment; the disparities were most prominent for patients with advanced-stage cancer (stages III or IV, up to an 11.1% difference) vs early stage cancer (stages I or II, up to a 4.3% difference). After patients were matched for treatment, there was a greater reduction in disparity for black vs white patients with advanced-stage compared with early stage cancer. In sensitivity analyses, the 5-year racial survival disparity was 7.7% after demographic match, which was less than the 8.3% observed in the complete cohort. This reduction likely was owing to the differences between the subcohort and the complete cohort in those variables that were not included in the demographic match. This value was reduced to 6.5% ( P = .0001) after socioeconomic status was included in the demographic match. The difference decreased significantly to 2.8% ( P = .090) after tumor presentation match, but was not reduced further after treatment match. Conclusions We observed significant disparities in treatment and survival of black vs white patients with colon cancer. The disparity in survival appears to have been affected more strongly by tumor presentation at diagnosis than treatment. The effects of treatment differences on disparities in survival were greater for patients with advanced-stage vs early stage cancer.
Discovery of genotype-phenotype relationships remains a major challenge in clinical medicine. Here, we combined three sources of phenotypic data to uncover a new mechanism for rare and common ...diseases resulting from collagen secretion deficits. Using a zebrafish genetic screen, we identified the ric1 gene as being essential for skeletal biology. Using a gene-based phenome-wide association study (PheWAS) in the EHR-linked BioVU biobank, we show that reduced genetically determined expression of RIC1 is associated with musculoskeletal and dental conditions. Whole-exome sequencing identified individuals homozygous-by-descent for a rare variant in RIC1 and, through a guided clinical re-evaluation, it was discovered that they share signs with the BioVU-associated phenome. We named this new Mendelian syndrome CATIFA (cleft lip, cataract, tooth abnormality, intellectual disability, facial dysmorphism, attention-deficit hyperactivity disorder) and revealed further disease mechanisms. This gene-based, PheWAS-guided approach can accelerate the discovery of clinically relevant disease phenome and associated biological mechanisms.
There is strong evidence that rare variants are involved in complex disease etiology. The first step in implicating rare variants in disease etiology is their identification through sequencing in ...both randomly ascertained samples (e.g., the 1,000 Genomes Project) and samples ascertained according to disease status. We investigated to what extent rare variants will be observed across the genome and in candidate genes in randomly ascertained samples, the magnitude of variant enrichment in diseased individuals, and biases that can occur due to how variants are discovered. Although sequencing cases can enrich for casual variants, when a gene or genes are not involved in disease etiology, limiting variant discovery to cases can lead to association studies with dramatically inflated false positive rates.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Systemic lupus erythematosus is a heritable autoimmune disease that predominantly affects young women. To improve our understanding of genetic etiology, we conduct multi-ancestry and multi-trait ...meta-analysis of genome-wide association studies, encompassing 12 systemic lupus erythematosus cohorts from 3 different ancestries and 10 genetically correlated autoimmune diseases, and identify 16 novel loci. We also perform transcriptome-wide association studies, computational drug repurposing analysis, and cell type enrichment analysis. We discover putative drug classes, including a histone deacetylase inhibitor that could be repurposed to treat lupus. We also identify multiple cell types enriched with putative target genes, such as non-classical monocytes and B cells, which may be targeted for future therapeutics. Using this newly assembled result, we further construct polygenic risk score models and demonstrate that integrating polygenic risk score with clinical lab biomarkers improves the diagnostic accuracy of systemic lupus erythematosus using the Vanderbilt BioVU and Michigan Genomics Initiative biobanks.
Background:
Alzheimer’s disease (AD) is a debilitating neurodegenerative condition with few treatment options available. Drug repurposing studies have sought to identify existing drugs that could be ...repositioned to treat AD; however, the effectiveness of drug repurposing for AD remains unclear. This review systematically analyzes the progress made in drug repurposing for AD throughout the last decade, summarizing the suggested drug candidates and analyzing changes in the repurposing strategies used over time. We also examine the different types of data that have been leveraged to validate suggested drug repurposing candidates for AD, which to our knowledge has not been previous investigated, although this information may be especially useful in appraising the potential of suggested drug repurposing candidates. We ultimately hope to gain insight into the suggested drugs representing the most promising repurposing candidates for AD.
Methods:
We queried the PubMed database for AD drug repurposing studies published between 2012 and 2022. 124 articles were reviewed. We used RxNorm to standardize drug names across the reviewed studies, map drugs to their constituent ingredients, and identify prescribable drugs. We used the Anatomical Therapeutic Chemical (ATC) Classification System to group drugs.
Results:
573 unique drugs were proposed for repurposing in AD over the last 10 years. These suggested repurposing candidates included drugs acting on the nervous system (17%), antineoplastic and immunomodulating agents (16%), and drugs acting on the cardiovascular system (12%). Clozapine, a second-generation antipsychotic medication, was the most frequently suggested repurposing candidate (N = 6). 61% (76/124) of the reviewed studies performed a validation, yet only 4% (5/124) used real-world data for validation.
Conclusion:
A large number of potential drug repurposing candidates for AD has accumulated over the last decade. However, among these drugs, no single drug has emerged as the top candidate, making it difficult to establish research priorities. Validation of drug repurposing hypotheses is inconsistently performed, and real-world data has been critically underutilized for validation. Given the urgent need for new AD therapies, the utility of real-world data in accelerating identification of high-priority candidates for AD repurposing warrants further investigation.
The neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), and circulating tumor cells (CTCs) have been associated with survival in castration-resistant prostate cancer (CRPC). However, ...no study has examined the prognostic value of NLR and PLR in the context of CTCs.
Baseline CTCs from mCRPC patients were enumerated using the CellSearch System. Baseline NLR and PLR values were calculated using the data from routine complete blood counts. The associations of CTC, NLR, and PLR values, individually and jointly, with progression-free survival (PFS) and overall survival (OS), were evaluated using Kaplan-Meier analysis, as well as univariate and multivariate Cox models.
CTCs were detected in 37 (58.7%) of 63 mCRPC patients, and among them, 16 (25.4%) had ≥5 CTCs. The presence of CTCs was significantly associated with a 4.02-fold increased risk for progression and a 3.72-fold increased risk of death during a median follow-up of 17.6 months. OS was shorter among patients with high levels of NLR or PLR than those with low levels (log-rank P = 0.023 and 0.077). Neither NLR nor PLR was individually associated with PFS. Among the 37 patients with detectable CTCs, those with a high NLR had significantly shorter OS (log-rank P = 0.024); however, among the 26 patients without CTCs, the OS difference between high- and low-NLR groups was not statistically significant. Compared to the patients with CTCs and low NLR, those with CTCs and high levels of NLR had a 3.79-fold risk of death (P = 0.036). This association remained significant after adjusting for covariates (P = 0.031). Combination analyses of CTC and PLR did not yield significant results.
Among patients with detectable CTCs, the use of NLR could further classify patients into different risk groups, suggesting a complementary role for NLR in CTC-based prognostic stratification in mCRPC.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Purpose
Discordance between HER2 expression in tumor tissue (tHER2) and HER2 status on circulating tumor cells (cHER2) has been reported. It remains largely underexplored whether patients with tHER2
...−
/cHER2
+
can benefit from anti-HER2 targeted therapies.
Methods
cHER2 status was determined in 105 advanced-stage patients with tHER2
−
breast tumors. Association between cHER2 status and progression-free survival (PFS) was analyzed by univariate and multivariate Cox models and survival differences were compared by Kaplan–Meier method.
Results
Compared to the patients with low-risk cHER2 (cHER2
+
< 2), those with high-risk cHER2 (cHER2
+
≥ 2) had shorter survival time and an increased risk for disease progression (hazard ratio HR 2.16, 95% confidence interval CI 1.20–3.88,
P
= 0.010). Among the patients with high-risk cHER2, those who received anti-HER2 targeted therapies had improved PFS compared with those who did not (HR 0.30, 95% CI 0.10–0.92,
P
= 0.035). In comparison, anti-HER2 targeted therapy did not affect PFS among those with low-risk cHER2 (HR 0.70, 95% CI 0.36–1.38,
P
= 0.306). Similar results were obtained after adjusting covariates. A longitudinal analysis of 67 patients with cHER2 detected during follow-ups found that those whose cHER2 status changed from high-risk at baseline to low-risk at first follow-up exhibited a significantly improved survival compared to those whose cHER2 remained high-risk (median PFS: 11.7 weeks vs. 2.0 weeks, log-rank
P
= 0.001).
Conclusion
In advanced-stage breast cancer patients with tHER2
−
tumors, cHER2 status has the potential to guide the use of anti-HER2 targeted therapy in patients with high-risk cHER2.
Genome-wide association studies (GWAS) have identified numerous susceptibility loci for Alzheimer's disease (AD). However, utilizing GWAS and multi-omics data to identify high-confidence AD risk ...genes (ARGs) and druggable targets that can guide development of new therapeutics for patients suffering from AD has heretofore not been successful.
To address this critical problem in the field, we have developed a network-based artificial intelligence framework that is capable of integrating multi-omics data along with human protein-protein interactome networks to accurately infer accurate drug targets impacted by GWAS-identified variants to identify new therapeutics. When applied to AD, this approach integrates GWAS findings, multi-omics data from brain samples of AD patients and AD transgenic animal models, drug-target networks, and the human protein-protein interactome, along with large-scale patient database validation and in vitro mechanistic observations in human microglia cells.
Through this approach, we identified 103 ARGs validated by various levels of pathobiological evidence in AD. Via network-based prediction and population-based validation, we then showed that three drugs (pioglitazone, febuxostat, and atenolol) are significantly associated with decreased risk of AD compared with matched control populations. Pioglitazone usage is significantly associated with decreased risk of AD (hazard ratio (HR) = 0.916, 95% confidence interval CI 0.861-0.974, P = 0.005) in a retrospective case-control validation. Pioglitazone is a peroxisome proliferator-activated receptor (PPAR) agonist used to treat type 2 diabetes, and propensity score matching cohort studies confirmed its association with reduced risk of AD in comparison to glipizide (HR = 0.921, 95% CI 0.862-0.984, P = 0.0159), an insulin secretagogue that is also used to treat type 2 diabetes. In vitro experiments showed that pioglitazone downregulated glycogen synthase kinase 3 beta (GSK3β) and cyclin-dependent kinase (CDK5) in human microglia cells, supporting a possible mechanism-of-action for its beneficial effect in AD.
In summary, we present an integrated, network-based artificial intelligence methodology to rapidly translate GWAS findings and multi-omics data to genotype-informed therapeutic discovery in AD.
Mitochondrial DNA (mtDNA) variation can affect phenotypic variation; therefore, knowing its distribution within and among individuals is of importance to understanding many human diseases. ...Intra-individual mtDNA variation (heteroplasmy) has been generally assumed to be random. We used massively parallel sequencing to assess heteroplasmy across ten tissues and demonstrate that in unrelated individuals there are tissue-specific, recurrent mutations. Certain tissues, notably kidney, liver and skeletal muscle, displayed the identical recurrent mutations that were undetectable in other tissues in the same individuals. Using RFLP analyses we validated one of the tissue-specific mutations in the two sequenced individuals and replicated the patterns in two additional individuals. These recurrent mutations all occur within or in very close proximity to sites that regulate mtDNA replication, strongly implying that these variations alter the replication dynamics of the mutated mtDNA genome. These recurrent variants are all independent of each other and do not occur in the mtDNA coding regions. The most parsimonious explanation of the data is that these frequently repeated mutations experience tissue-specific positive selection, probably through replication advantage.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Known risk variants explain only a small proportion of breast cancer heritability, particularly in Asian women. To search for additional genetic susceptibility loci for breast cancer, here we perform ...a meta-analysis of data from genome-wide association studies (GWAS) conducted in Asians (24,206 cases and 24,775 controls) and European descendants (122,977 cases and 105,974 controls). We identified 31 potential novel loci with the lead variant showing an association with breast cancer risk at P < 5 × 10
. The associations for 10 of these loci were replicated in an independent sample of 16,787 cases and 16,680 controls of Asian women (P < 0.05). In addition, we replicated the associations for 78 of the 166 known risk variants at P < 0.05 in Asians. These findings improve our understanding of breast cancer genetics and etiology and extend previous findings from studies of European descendants to Asian women.
PDF
