Predicting clinical progression trajectories of early Alzheimer's disease patients.

BACKGROUND: Models for forecasting individual clinical progression trajectories in early Alzheimer's disease (AD) are needed for optimizing clinical studies and patient monitoring. METHODS: Prediction models were constructed using a clinical trial training cohort (TC; n = 934) via a gradient boosting algorithm and then evaluated in two validation cohorts (VC 1, n = 235; VC 2, n = 421). Model inputs included baseline clinical features (cognitive function assessments, APOE ε4 status, and demographics) and brain magnetic resonance imaging (MRI) measures. RESULTS: The model using clinical features achieved R2 of 0.21 and 0.31 for predicting 2-year cognitive decline in VC 1 and VC 2, respectively. Adding MRI features improved the R2 to 0.29 in VC 1, which employed the same preprocessing pipeline as the TC. Utilizing these model-based predictions for clinical trial enrichment reduced the required sample size by 20% to 49%. DISCUSSION: Our validated prediction models enable baseline prediction of clinical progression trajectories in early AD, benefiting clinical trial enrichment and various applications.

Plasma pTau217 predicts continuous brain amyloid levels in preclinical and early Alzheimer's disease.

BACKGROUND: This study investigated the potential of phosphorylated plasma Tau217 ratio (pTau217R) and plasma amyloid beta (Aß) 42/Aß40 in predicting brain amyloid levels measured by positron emission tomography (PET) Centiloid (CL) for Alzheimer's disease (AD) staging and screening. METHODS: Quantification of plasma pTau217R and Aß42/Aß40 employed immunoprecipitation-mass spectrometry. CL prediction models were developed on a cohort of 904 cognitively unimpaired, preclinical and early AD subjects and validated on two independent cohorts. RESULTS: Models integrating pTau217R outperformed Aß42/Aß40 alone, predicting amyloid levels up to 89.1 CL. High area under the receiver operating characteristic curve (AUROC) values (89.3% to 94.7%) were observed across a broad CL range (15 to 90). Utilizing pTau217R-based models for low amyloid levels reduced PET scans by 70.5% to 78.6%. DISCUSSION: pTau217R effectively predicts brain amyloid levels, surpassing cerebrospinal fluid Aß42/Aß40's range. Combining it with plasma Aß42/Aß40 enhances sensitivity for low amyloid detection, reducing unnecessary PET scans and expanding clinical utility. GOV IDENTIFIERS: NCT02956486 (MissionAD1), NCT03036280 (MissionAD2), NCT04468659 (AHEAD3-45), NCT03887455 (ClarityAD) HIGHLIGHTS: Phosphorylated plasma Tau217 ratio (pTau217R) effectively predicts amyloid-PET Centiloid (CL) across a broad spectrum. Integrating pTau217R with Aß42/Aß40 extends the CL prediction upper limit to 89.1 CL. Combined model predicts amyloid status with high accuracy, especially in cognitively unimpaired individuals. This model identifies subjects above or below various CL thresholds with high accuracy. pTau217R-based models significantly reduce PET scans by up to 78.6% for screening out individuals with no/low amyloid.

Inherited variants at 3q13.33 and 3p24.1 are associated with risk of diffuse large B-cell lymphoma and implicate immune pathways.

We previously identified five single nucleotide polymorphisms (SNPs) at four susceptibility loci for diffuse large B-cell lymphoma (DLBCL) in individuals of European ancestry through a large genome-wide association study (GWAS). To further elucidate genetic susceptibility to DLBCL, we sought to validate two loci at 3q13.33 and 3p24.1 that were suggestive in the original GWAS with additional genotyping. In the meta-analysis (5662 cases and 9237 controls) of the four original GWAS discovery scans and three replication studies, the 3q13.33 locus (rs9831894; minor allele frequency [MAF] = 0.40) was associated with DLBCL risk [odds ratio (OR) = 0.83, P = 3.62 × 10-13]. rs9831894 is in linkage disequilibrium (LD) with additional variants that are part of a super-enhancer that physically interacts with promoters of CD86 and ILDR1. In the meta-analysis (5510 cases and 12 817 controls) of the four GWAS discovery scans and four replication studies, the 3p24.1 locus (rs6773363; MAF = 0.45) was also associated with DLBCL risk (OR = 1.20, P = 2.31 × 10-12). This SNP is 29 426-bp upstream of the nearest gene EOMES and in LD with additional SNPs that are part of a highly lineage-specific and tumor-acquired super-enhancer that shows long-range interaction with AZI2 promoter. These loci provide additional evidence for the role of immune function in the etiology of DLBCL, the most common lymphoma subtype.

Immune checkpoint-related serum proteins and genetic variants predict outcomes of localized prostate cancer, a cohort study.

BACKGROUND: The clinical predictors and biological mechanisms for localized prostate cancer (PCa) outcomes remain mostly unknown. We aim to evaluate the role of serum immune-checkpoint-related (ICK) proteins and genetic variations in predicting outcomes of localized PCa. METHODS: We profiled the serum levels of 14 ICK-related proteins (BTLA, GITR, HVEM, IDO, LAG-3, PD-1, PD-L1, PD-L2, Tim-3, CD28, CD80, 4-1BB, CD27, and CTLA-4) in 190 patients with localized PCa. The genotypes of 97 single nucleotide polymorphisms (SNPs) from 19 ICK-related genes were analyzed in an extended population (N = 1762). Meta-data from ArrayExpress and TCGA was employed to validate and to probe functional data. Patients were enrolled and tumor aggressiveness, biochemical recurrence (BCR), and progression information were obtained. Statistical analyses were performed analyzing associations between serum biomarkers, genotypes, mRNA and outcomes. RESULTS: We showed that serum (s)BTLA and sTIM3 levels were associated with PCa aggressiveness (P < 0.05). sCD28, sCD80, sCTLA4, sGITR, sHVEM and sIDO correlated with both BCR and progression risks (all P < 0.05). We further identified ICK variants were significantly associated with aggressiveness, BCR and progression. Among them, 4 SNPs located in CD80 (rs7628626, rs12695388, rs491407, rs6804441) were not only associated with BCR and progression risk, but also correlated with sCD80 level (P < 0.01). rs491407 was further validated in an independent cohort. The CD80 mRNA expression was associated with BCR (HR, 1.85, 95% CI 1.06-3.22, P = 0.03) in meta-analysis of validation cohorts. CONCLUSION: We highlight the prognostic value of serum ICK-related proteins for predicting aggressiveness, BCR and progression of PCa. The genetic variations and mRNA expression in CD80 could be predictors and potential targets of localized PCa.

Allostatic score and its associations with demographics, healthy behaviors, tumor characteristics, and mitochondrial DNA among breast cancer patients.

INTRODUCTION: Allostatic load (AL), a composite index, has been used to capture variation in life-course stresses. However, few studies have been carried out among breast cancer patients. METHODS: In this study, we examined the cross-sectional association of AL with demographics, healthy behaviors, tumor characteristics, and mitochondrial DNA copy number in breast cancer patients. The study used a sub-sample of 934 women with newly diagnosed breast cancer at M.D. Anderson from 2013 to 2018. To construct the AL score, the study used a battery of seventeen factors that represents the activity of five physiological systems: metabolic, cardiovascular, immunological, renal, and liver. RESULTS: AL was positively associated with the age of disease diagnosis (P = 0.002), and was higher in Black and Hispanic populations than White (P = 0.001 and 0.032, respectively). AL was also found more abundant in those who experienced marital dissolution (P = 0.006), lacked a college education (P = 0.045), currently smoked (P = 0.011), and had low levels of physical activity (P = 0.037) than their counterparts. The study then found that higher AL was associated with increased odds of having poorly differentiated tumors (Odds ratio (OR): 1.40, 95% confidence interval (CI): 1.28, 1.62). An additional significant association was observed between AL with estrogen receptor negative (ER-) (OR = 1.56, 95%CI: 1.02, 2.36) among Black patients. Finally, we observed a significant positive correlation between AL with leukocyte mitochondrial DNA copy number variation (P < 0.001). CONCLUSIONS: We conclude AL is influenced by selected demographics and healthy behaviors, and further is correlated with tumor characteristics and mitochondrial DNA copy number in breast cancer patients.

Impact of Wuhan lockdown on the spread of COVID-19 in China: a study based on the data of population mobility.

This study aimed to quantitatively assess the effectiveness of the Wuhan lockdown measure on controlling the spread of coronavirus diesase 2019 (COVID-19). : Firstly，estimate the daily new infection rate in Wuhan before January 23，2020 when the city went into lockdown by consulting the data of Wuhan population mobility and the number of cases imported from Wuhan in 217 cities of Mainland China. Then estimate what the daily new infection rate would have been in Wuhan from January 24 to January 30th if the lockdown measure had been delayed for 7 days，assuming that the daily new infection in Wuhan after January 23 increased in a high，moderate and low trend respectively (using exponential, linear and logarithm growth models). Based on that，calculate the number of infection cases imported from Wuhan during this period. Finally，predict the possible impact of 7-day delayed lockdown in Wuhan on the epidemic situation in China using the susceptible-exposed-infectious-removed (SEIR) model. : The daily new infection rate in Wuhan was estimated to be 0.021%，0.026%，0.029%，0.033% and 0.070% respectively from January 19 to January 23. And there were at least 20 066 infection cases in Wuhan by January 23，2020. If Wuhan lockdown measure had been delayed for 7 days，the daily new infection rate on January 30 would have been 0.335% in the exponential growth model，0.129% in the linear growth model，and 0.070% in the logarithm growth model. Correspondingly，there would have been 32 075，24 819 and 20 334 infection cases travelling from Wuhan to other areas of Mainland China，and the number of cumulative confirmed cases as of March 19 in Mainland China would have been 3.3-3.9 times of the officially reported number. Conclusions: Timely taking city-level lockdown measure in Wuhan in the early stage of COVID-19 outbreak is essential in containing the spread of the disease in China.

Impact of socioeconomic status，population mobility and control measures on COVID-10 development in major cities of China.

:To evaluate the impact of socioeconomic status，population mobility，prevention and control measures on the early-stage coronavirus disease 2019 (COVID-19) development in major cities of China. : The rate of daily new confirmed COVID-19 cases in the 51 cities with the largest number of cumulative confirmed cases as of February 19，2020 (except those in Hubei province) were collected and analyzed using the time series cluster analysis. It was then assessed according to three aspects，that is, socioeconomic status，population mobility，and control measures for the pandemic. : According to the analysis on the 51 cities，4 development patterns of COVID-19 were obtained，including a high-incidence pattern (in Xinyu)，a late high-incidence pattern (in Ganzi)，a moderate incidence pattern (in Wenzhou and other 12 cities)，and a low and stable incidence pattern (in Hangzhou and other 35 cities). Cities with different types and within the same type both had different scores on the three aspects. : There were relatively large difference on the COVID-19 development among different cities in China，possibly affected by socioeconomic status，population mobility and prevention and control measures that were taken. Therefore，a timely public health emergency response and travel restriction measures inside the city can interfere the development of the pandemic. Population flow from high risk area can largely affect the number of cumulative confirmed cases.

Predicting COVID-19 epidemiological trend by applying population mobility data in two-stage modeling.

:To predict the epidemiological trend of coronavirus disease 2019 (COVID-19) by mathematical modeling based on the population mobility and the epidemic prevention and control measures. : As of February 8，2020，the information of 151 confirmed cases in Yueqing，Zhejiang province were obtained，including patients' infection process，population mobility between Yueqing and Wuhan，etc. To simulate and predict the development trend of COVID-19 in Yueqing, the study established two-stage mathematical models，integrating the population mobility data with the date of symptom appearance of confirmed cases and the transmission dynamics of imported and local cases. : It was found that in the early stage of the pandemic，the number of daily imported cases from Wuhan (using the date of symptom appearance) was positively associated with the number of population travelling from Wuhan to Yueqing on the same day and 6 and 9 days before that. The study predicted that the final outbreak size in Yueqing would be 170 according to the number of imported cases estimated by consulting the population number travelling from Wuhan to Yueqing and the susceptible-exposed-infectious-recovered (SEIR) model; while the number would be 165 if using the reported daily number of imported cases. These estimates were close to the 170，the actual monitoring number of cases in Yueqing as of April 27，2020. : The two-stage modeling approach used in this study can accurately predict COVID-19 epidemiological trend.

Genetic variants in epithelial-mesenchymal transition genes as predictors of clinical outcomes in localized prostate cancer.

BACKGROUND: Epithelial-mesenchymal transition (EMT) plays a pivotal role in the progression of prostate cancer (PCa). However, little is known about genetic variants in the EMT pathway as predictors of aggressiveness, biochemical recurrence (BCR) and disease reclassification in localized PCa. PATIENTS AND METHODS: In this multistage study, we evaluated 5186 single nucleotide polymorphisms (SNPs) from 264 genes related to EMT pathway to identify SNPs associated with PCa aggressiveness and BCR in the MD Anderson PCa (MDA-PCa) patient cohort (N = 1762), followed by assessment of the identified SNPs with disease reclassification in the active surveillance (AS) cohort (N = 392). RESULTS: In the MDA-PCa cohort, 312 SNPs were associated with high D'Amico risk (P < 0.05), among which, 14 SNPs in 10 genes were linked to BCR risk. In the AS cohort, 2 of 14 identified SNPs (rs76779889 and rs7083961) in C-terminal Binding Proteins 2 gene were associated with reclassification risk. The associations of rs76779889 with different endpoints were: D'Amico high versus low, odds ratio [95% confidence interval (CI)] = 2.89 (1.32-6.34), P = 0.008; BCR, hazard ratio (HR) (95% CI) = 2.88 (1.42-5.85), P = 0.003; and reclassification, HR (95% CI) = 2.83 (1.40-5.74), P = 0.004. For rs7083961, the corresponding risk estimates were: D'Amico high versus low, odds ratio (95% CI) = 1.69 (1.12-2.57), P = 0.013; BCR, HR (95% CI) = 1.87 (1.15-3.02), P = 0.011 and reclassification, HR (95% CI) = 1.72 (1.09-2.72), P = 0.020. There were cumulative effects of these two SNPs on modulating these endpoints. CONCLUSION: Genetic variants in EMT pathway may influence the risks of localized PCa's aggressiveness, BCR and disease reclassification, suggesting their potential role in the assessment and management of localized PCa.

Patterns of racial/ethnic disparities in baseline health-related quality of life and relationship with overall survival in patients with colorectal cancer.

PURPOSE: Racial disparities are evident in colorectal cancer (CRC) prognosis with black patients experiencing worse outcomes than Hispanics and whites, yet mediators of these disparities are not fully known. The aim of this study is to identify variables that contribute to racial/ethnic disparities in health-related quality of life (HR-QoL) and overall survival in CRC. METHODS: Using SF-12 questionnaires, we assessed HR-QoL in 1132 CRC patients by calculating their physical (PCS) and mental composite summary (MCS) scores. Associations between poor PCS/MCS and sociodemographic factors were estimated and survival differences were identified by race/ethnicity. RESULTS: Hispanic patients who never married were at greater risk of poor PCS (OR 2.69; 95% CI 1.11-6.49; P = 0.028) than were currently married patients. College education was associated with a decreased risk of poor PCS in Hispanic and white, but not black, patients. Gender was significantly associated with poor MCS among white patients only. CRC patients who reported a poor PCS or MCS had poor survival, with differences in median survival times (MSTs) by race. The effect of PCS was strongest in white CRC patients with a difference in overall MST of > 116 months between those with favorable versus poor physical HR-QoL. Black patients who reported poor Physical and Mental HR-QoL showed significant risk of a poor outcome. CONCLUSION: These findings suggest that racial/ethnic disparities in CRC survival may be related to differences in HR-QoL. Identified mediators of HR-QoL could supplement current CRC management strategies to improve patients' survival.