Wake Forest University Health Sciences

CONTEXT: Postmenopausal women have a greater risk than men of developing Alzheimer disease, but studies of the effects of estrogen therapy on Alzheimer disease have been inconsistent. On July 8, 2002, the study drugs, estrogen plus progestin, in the Women's Health Initiative (WHI) trial were discontinued because of certain increased health risks in women receiving combined hormone therapy. OBJECTIVE: To evaluate the effect of estrogen plus progestin on the incidence of dementia and mild cognitive impairment compared with placebo. DESIGN, SETTING, AND PARTICIPANTS: The Women's Health Initiative Memory Study (WHIMS), a randomized, double-blind, placebo-controlled clinical trial, began enrolling participants from the Women's Health Initiative (WHI) estrogen plus progestin trial in May 1996. Of the 4894 eligible participants of the WHI study, 4532 (92.6%) postmenopausal women free of probable dementia, aged 65 years or older, and recruited from 39 of 40 WHI clinical centers were enrolled in the WHIMS. INTERVENTION: Participants received either 1 daily tablet of 0.625 mg of conjugated equine estrogen plus 2.5 mg of medroxyprogesterone acetate (n = 2229), or a matching placebo (n = 2303). MAIN OUTCOME MEASURES: Incidence of probable dementia (primary outcome) and mild cognitive impairment (secondary outcome) were identified through a structured clinical assessment. RESULTS: The mean (SD) time between the date of randomization into WHI and the last Modified Mini-Mental State Examination (3MSE) for all WHIMS participants was 4.05 (1.19) years. Overall, 61 women were diagnosed with probable dementia, 40 (66%) in the estrogen plus progestin group compared with 21 (34%) in the placebo group. The hazard ratio (HR) for probable dementia was 2.05 (95% confidence interval [CI], 1.21-3.48; 45 vs 22 per 10 000 person-years; P =.01). This increased risk would result in an additional 23 cases of dementia per 10 000 women per year. Alzheimer disease was the most common classification of dementia in both study groups. Treatment effects on mild cognitive impairment did not differ between groups (HR, 1.07; 95% CI, 0.74-1.55; 63 vs 59 cases per 10 000 person-years; P =.72). CONCLUSIONS: Estrogen plus progestin therapy increased the risk for probable dementia in postmenopausal women aged 65 years or older. In addition, estrogen plus progestin therapy did not prevent mild cognitive impairment in these women. These findings, coupled with previously reported WHI data, support the conclusion that the risks of estrogen plus progestin outweigh the benefits.

BACKGROUND: It is uncertain whether treatment of mild gestational diabetes mellitus improves pregnancy outcomes. METHODS: Women who were in the 24th to 31st week of gestation and who met the criteria for mild gestational diabetes mellitus (i.e., an abnormal result on an oral glucose-tolerance test but a fasting glucose level below 95 mg per deciliter [5.3 mmol per liter]) were randomly assigned to usual prenatal care (control group) or dietary intervention, self-monitoring of blood glucose, and insulin therapy, if necessary (treatment group). The primary outcome was a composite of stillbirth or perinatal death and neonatal complications, including hyperbilirubinemia, hypoglycemia, hyperinsulinemia, and birth trauma. RESULTS: A total of 958 women were randomly assigned to a study group--485 to the treatment group and 473 to the control group. We observed no significant difference between groups in the frequency of the composite outcome (32.4% and 37.0% in the treatment and control groups, respectively; P=0.14). There were no perinatal deaths. However, there were significant reductions with treatment as compared with usual care in several prespecified secondary outcomes, including mean birth weight (3302 vs. 3408 g), neonatal fat mass (427 vs. 464 g), the frequency of large-for-gestational-age infants (7.1% vs. 14.5%), birth weight greater than 4000 g (5.9% vs. 14.3%), shoulder dystocia (1.5% vs. 4.0%), and cesarean delivery (26.9% vs. 33.8%). Treatment of gestational diabetes mellitus, as compared with usual care, was also associated with reduced rates of preeclampsia and gestational hypertension (combined rates for the two conditions, 8.6% vs. 13.6%; P=0.01). CONCLUSIONS: Although treatment of mild gestational diabetes mellitus did not significantly reduce the frequency of a composite outcome that included stillbirth or perinatal death and several neonatal complications, it did reduce the risks of fetal overgrowth, shoulder dystocia, cesarean delivery, and hypertensive disorders. (ClinicalTrials.gov number, NCT00069576.)

Multifactorial mechanisms underlying late-onset Alzheimer's disease (LOAD) are poorly characterized from an integrative perspective. Here spatiotemporal alterations in brain amyloid-β deposition, metabolism, vascular, functional activity at rest, structural properties, cognitive integrity and peripheral proteins levels are characterized in relation to LOAD progression. We analyse over 7,700 brain images and tens of plasma and cerebrospinal fluid biomarkers from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Through a multifactorial data-driven analysis, we obtain dynamic LOAD-abnormality indices for all biomarkers, and a tentative temporal ordering of disease progression. Imaging results suggest that intra-brain vascular dysregulation is an early pathological event during disease development. Cognitive decline is noticeable from initial LOAD stages, suggesting early memory deficit associated with the primary disease factors. High abnormality levels are also observed for specific proteins associated with the vascular system's integrity. Although still subjected to the sensitivity of the algorithms and biomarkers employed, our results might contribute to the development of preventive therapeutic interventions.

Heavy alcohol consumption is an established risk factor for hypertension; the mechanism by which alcohol consumption impact blood pressure (BP) regulation remains unknown. We hypothesized that a genome-wide association study accounting for gene-alcohol consumption interaction for BP might identify additional BP loci and contribute to the understanding of alcohol-related BP regulation. We conducted a large two-stage investigation incorporating joint testing of main genetic effects and single nucleotide variant (SNV)-alcohol consumption interactions. In Stage 1, genome-wide discovery meta-analyses in ≈131K individuals across several ancestry groups yielded 3,514 SNVs (245 loci) with suggestive evidence of association (P < 1.0 x 10-5). In Stage 2, these SNVs were tested for independent external replication in ≈440K individuals across multiple ancestries. We identified and replicated (at Bonferroni correction threshold) five novel BP loci (380 SNVs in 21 genes) and 49 previously reported BP loci (2,159 SNVs in 109 genes) in European ancestry, and in multi-ancestry meta-analyses (P < 5.0 x 10-8). For African ancestry samples, we detected 18 potentially novel BP loci (P < 5.0 x 10-8) in Stage 1 that warrant further replication. Additionally, correlated meta-analysis identified eight novel BP loci (11 genes). Several genes in these loci (e.g., PINX1, GATA4, BLK, FTO and GABBR2) have been previously reported to be associated with alcohol consumption. These findings provide insights into the role of alcohol consumption in the genetic architecture of hypertension.

Insomnia is a highly prevalent, often debilitating, and economically burdensome form of sleep disturbance caused by various situational, medical, emotional, environmental and behavioral factors. Although several consensually-derived nosologies have described numerous insomnia phenotypes, research concerning these phenotypes has been greatly hampered by a lack of widely accepted operational research diagnostic criteria (RDC) for their definition. The lack of RDC has, in turn, led to inconsistent research findings for most phenotypes largely due to the variable definitions used for their ascertainment. Given this problem, the American Academy of Sleep Medicine (AASM) commissioned a Work Group (WG) to review the literature and identify those insomnia phenotypes that appear most valid and tenable. In addition, this WG was asked to derive standardized RDC for these phenotypes and recommend assessment procedures for their ascertainment. This report outlines the WG's findings, the insomnia RDC derived, and research assessment procedures the WG recommends for identifying study participants who meet these RDC.

OBJECTIVE: To determine whether there is a link between hypoglycaemia and mortality among participants in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial. DESIGN: Retrospective epidemiological analysis of data from the ACCORD trial. Setting Diabetes clinics, research clinics, and primary care clinics. PARTICIPANTS: Patients were eligible for the ACCORD study if they had type 2 diabetes, a glycated haemoglobin (haemoglobin A(1C)) concentration of 7.5% or more during screening, and were aged 40-79 years with established cardiovascular disease or 55-79 years with evidence of subclinical disease or two additional cardiovascular risk factors. Intervention Intensive (haemoglobin A(1C) <6.0%) or standard (haemoglobin A(1C) 7.0-7.9%) glucose control. OUTCOME MEASURES: Symptomatic, severe hypoglycaemia, manifest as either blood glucose concentration of less than 2.8 mmol/l (<50 mg/dl) or symptoms that resolved with treatment and that required either the assistance of another person or medical assistance, and all cause and cause specific mortality, including a specific assessment for involvement of hypoglycaemia. RESULTS: 10 194 of the 10 251 participants enrolled in the ACCORD study who had at least one assessment for hypoglycaemia during regular follow-up for vital status were included in this analysis. Unadjusted annual mortality among patients in the intensive glucose control arm was 2.8% in those who had one or more episodes of hypoglycaemia requiring any assistance compared with 1.2% for those with no episodes (53 deaths per 1924 person years and 201 deaths per 16 315 person years, respectively; adjusted hazard ratio (HR) 1.41, 95% CI 1.03 to 1.93). A similar pattern was seen among participants in the standard glucose control arm (3.7% (21 deaths per 564 person years) v 1.0% (176 deaths per 17 297 person years); adjusted HR 2.30, 95% CI 1.46 to 3.65). On the other hand, among participants with at least one hypoglycaemic episode requiring any assistance, a non-significantly lower risk of death was seen in those in the intensive arm compared with those in the standard arm (adjusted HR 0.74, 95% 0.46 to 1.23). A significantly lower risk was observed in the intensive arm compared with the standard arm in participants who had experienced at least one hypoglycaemic episode requiring medical assistance (adjusted HR 0.55, 95% CI 0.31 to 0.99). Of the 451 deaths that occurred in ACCORD up to the time when the intensive treatment arm was closed, one death was adjudicated as definitely related to hypoglycaemia. CONCLUSION: Symptomatic, severe hypoglycaemia was associated with an increased risk of death within each study arm. However, among participants who experienced at least one episode of hypoglycaemia, the risk of death was lower in such participants in the intensive arm than in the standard arm. Symptomatic, severe hypoglycaemia does not appear to account for the difference in mortality between the two study arms up to the time when the ACCORD intensive glycaemia arm was discontinued. TRIAL REGISTRATION: NCT00000620.

A genome-wide association study (GWAS) of educational attainment was conducted in a discovery sample of 101,069 individuals and a replication sample of 25,490. Three independent single-nucleotide polymorphisms (SNPs) are genome-wide significant (rs9320913, rs11584700, rs4851266), and all three replicate. Estimated effects sizes are small (coefficient of determination R(2) ≈ 0.02%), approximately 1 month of schooling per allele. A linear polygenic score from all measured SNPs accounts for ≈2% of the variance in both educational attainment and cognitive function. Genes in the region of the loci have previously been associated with health, cognitive, and central nervous system phenotypes, and bioinformatics analyses suggest the involvement of the anterior caudate nucleus. These findings provide promising candidate SNPs for follow-up work, and our effect size estimates can anchor power analyses in social-science genetics.

PURPOSE Observation is the current standard of care for smoldering multiple myeloma. We hypothesized that early intervention with lenalidomide could delay progression to symptomatic multiple myeloma. METHODS We conducted a randomized trial that assessed the efficacy of single-agent lenalidomide compared with observation in patients with intermediate- or high-risk smoldering multiple myeloma. Lenalidomide was administered orally at a dose of 25 mg on days 1 to 21 of a 28-day cycle. The primary end point was progression-free survival, with disease progression requiring the development of end-organ damage attributable to multiple myeloma and biochemical progression. RESULTS One hundred eighty-two patients were randomly assigned—92 patients to the lenalidomide arm and 90 to the observation arm. Median follow-up is 35 months. Response to therapy was observed in 50% (95% CI, 39% to 61%) of patients in the lenalidomide arm, with no responses in the observation arm. Progression-free survival was significantly longer with lenalidomide compared with observation (hazard ratio, 0.28; 95% CI, 0.12 to 0.62; P = .002). One-, 2-, and 3-year progression-free survival was 98%, 93%, and 91% for the lenalidomide arm versus 89%, 76%, and 66% for the observation arm, respectively. Only six deaths have been reported, two in the lenalidomide arm versus four in the observation arm (hazard ratio for death, 0.46; 95% CI, 0.08 to 2.53). Grade 3 or 4 nonhematologic adverse events occurred in 25 patients (28%) on lenalidomide. CONCLUSION Early intervention with lenalidomide in smoldering multiple myeloma significantly delays progression to symptomatic multiple myeloma and the development of end-organ damage.

Virtually all cells living in multicellular structures such as tissues and organs are encased in an extracellular matrix. One of the most important features of a biofilm is the extracellular polymeric substance that functions as a matrix, holding bacterial cells together. Yet very little is known about how the matrix forms or how matrix components encase bacteria during biofilm development. Pseudomonas aeruginosa forms environmentally and clinically relevant biofilms and is a paradigm organism for the study of biofilms. The extracellular polymeric substance of P. aeruginosa biofilms is an ill-defined mix of polysaccharides, nucleic acids, and proteins. Here, we directly visualize the product of the polysaccharide synthesis locus (Psl exopolysaccharide) at different stages of biofilm development. During attachment, Psl is anchored on the cell surface in a helical pattern. This promotes cell-cell interactions and assembly of a matrix, which holds bacteria in the biofilm and on the surface. Chemical dissociation of Psl from the bacterial surface disrupted the Psl matrix as well as the biofilm structure. During biofilm maturation, Psl accumulates on the periphery of 3-D-structured microcolonies, resulting in a Psl matrix-free cavity in the microcolony center. At the dispersion stage, swimming cells appear in this matrix cavity. Dead cells and extracellular DNA (eDNA) are also concentrated in the Psl matrix-free area. Deletion of genes that control cell death and autolysis affects the formation of the matrix cavity and microcolony dispersion. These data provide a mechanism for how P. aeruginosa builds a matrix and subsequently a cavity to free a portion of cells for seeding dispersal. Direct visualization reveals that Psl is a key scaffolding matrix component and opens up avenues for therapeutics of biofilm-related complications.

Although diagnostic medical imaging provides enormous benefits in the early detection and accuracy diagnosis of various diseases, there are growing concerns on the potential side effect of radiation induced genetic, cancerous and other diseases. How to reduce radiation dose while maintaining the diagnostic performance is a major challenge in the computed tomography (CT) field. Inspired by the compressive sensing theory, the sparse constraint in terms of total variation (TV) minimization has already led to promising results for low-dose CT reconstruction. Compared to the discrete gradient transform used in the TV method, dictionary learning is proven to be an effective way for sparse representation. On the other hand, it is important to consider the statistical property of projection data in the low-dose CT case. Recently, we have developed a dictionary learning based approach for low-dose X-ray CT. In this paper, we present this method in detail and evaluate it in experiments. In our method, the sparse constraint in terms of a redundant dictionary is incorporated into an objective function in a statistical iterative reconstruction framework. The dictionary can be either predetermined before an image reconstruction task or adaptively defined during the reconstruction process. An alternating minimization scheme is developed to minimize the objective function. Our approach is evaluated with low-dose X-ray projections collected in animal and human CT studies, and the improvement associated with dictionary learning is quantified relative to filtered backprojection and TV-based reconstructions. The results show that the proposed approach might produce better images with lower noise and more detailed structural features in our selected cases. However, there is no proof that this is true for all kinds of structures.

The "acid mantle" is a topic not only of historical interest, but also of clinical significance and has recently been linked to vital stratum corneum function. Despite compelling basic science evidence placing skin pH as a key factor in barrier homeostasis, stratum corneum integrity, and antimicrobial defense, application of the acid mantle concept in clinical care is lacking. We review recent basic science investigations into skin pH, discuss skin disorders characterized by aberrant pH, and finally discuss practical application for preservation of the acid mantle. Recognizing factors that alter skin pH and selecting products that preserve the acid mantle is of prime importance in treating dermatologic patients.

RATIONALE: Machine learning may be useful to characterize cardiovascular risk, predict outcomes, and identify biomarkers in population studies. OBJECTIVE: To test the ability of random survival forests, a machine learning technique, to predict 6 cardiovascular outcomes in comparison to standard cardiovascular risk scores. METHODS AND RESULTS: We included participants from the MESA (Multi-Ethnic Study of Atherosclerosis). Baseline measurements were used to predict cardiovascular outcomes over 12 years of follow-up. MESA was designed to study progression of subclinical disease to cardiovascular events where participants were initially free of cardiovascular disease. All 6814 participants from MESA, aged 45 to 84 years, from 4 ethnicities, and 6 centers across the United States were included. Seven-hundred thirty-five variables from imaging and noninvasive tests, questionnaires, and biomarker panels were obtained. We used the random survival forests technique to identify the top-20 predictors of each outcome. Imaging, electrocardiography, and serum biomarkers featured heavily on the top-20 lists as opposed to traditional cardiovascular risk factors. Age was the most important predictor for all-cause mortality. Fasting glucose levels and carotid ultrasonography measures were important predictors of stroke. Coronary Artery Calcium score was the most important predictor of coronary heart disease and all atherosclerotic cardiovascular disease combined outcomes. Left ventricular structure and function and cardiac troponin-T were among the top predictors for incident heart failure. Creatinine, age, and ankle-brachial index were among the top predictors of atrial fibrillation. TNF-α (tissue necrosis factor-α) and IL (interleukin)-2 soluble receptors and NT-proBNP (N-Terminal Pro-B-Type Natriuretic Peptide) levels were important across all outcomes. The random survival forests technique performed better than established risk scores with increased prediction accuracy (decreased Brier score by 10%-25%). CONCLUSIONS: Machine learning in conjunction with deep phenotyping improves prediction accuracy in cardiovascular event prediction in an initially asymptomatic population. These methods may lead to greater insights on subclinical disease markers without apriori assumptions of causality. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT00005487.

Bioprinting is an emerging technique used to fabricate viable, 3D tissue constructs through the precise deposition of cells and hydrogels in a layer-by-layer fashion. Despite the ability to mimic the native properties of tissue, printed 3D constructs that are composed of naturally-derived biomaterials still lack structural integrity and adequate mechanical properties for use in vivo, thus limiting their development for use in load-bearing tissue engineering applications, such as cartilage. Fabrication of viable constructs using a novel multi-head deposition system provides the ability to combine synthetic polymers, which have higher mechanical strength than natural materials, with the favorable environment for cell growth provided by traditional naturally-derived hydrogels. However, the complexity and high cost associated with constructing the required robotic system hamper the widespread application of this approach. Moreover, the scaffolds fabricated by these robotic systems often lack flexibility, which further restrict their applications. To address these limitations, advanced fabrication techniques are necessary to generate complex constructs with controlled architectures and adequate mechanical properties. In this study, we describe the construction of a hybrid inkjet printing/electrospinning system that can be used to fabricate viable tissues for cartilage tissue engineering applications. Electrospinning of polycaprolactone fibers was alternated with inkjet printing of rabbit elastic chondrocytes suspended in a fibrin-collagen hydrogel in order to fabricate a five-layer tissue construct of 1 mm thickness. The chondrocytes survived within the printed hybrid construct with more than 80% viability one week after printing. In addition, the cells proliferated and maintained their basic biological properties within the printed layered constructs. Furthermore, the fabricated constructs formed cartilage-like tissues both in vitro and in vivo as evidenced by the deposition of type II collagen and glycosaminoglycans. Moreover, the printed hybrid scaffolds demonstrated enhanced mechanical properties compared to printed alginate or fibrin-collagen gels alone. This study demonstrates the feasibility of constructing a hybrid inkjet printing system using off-the-shelf components to produce cartilage constructs with improved biological and mechanical properties.

Using family resilience theory, this study examined the effects of work‐family conflict and work‐family facilitation on mental health among working adults to gain a better understanding of work‐family fit. Data from the National Survey of Midlife Development in the United States (MIDUS) were used to compare different combinations of work‐family conflict and work‐family facilitation. Results suggest that family to work facilitation is a family protective factor that offsets and buffers the deleterious effects of work‐family conflict on mental health. The results across these outcomes suggest that work‐family conflict and facilitation must be considered separately, and that adult mental health is optimized when family to work facilitation is high and family to work and work to family conflict is low.

Abstract The heterogeneity of neurodegenerative diseases is a key confound to disease understanding and treatment development, as study cohorts typically include multiple phenotypes on distinct disease trajectories. Here we introduce a machine-learning technique—Subtype and Stage Inference (SuStaIn)—able to uncover data-driven disease phenotypes with distinct temporal progression patterns, from widely available cross-sectional patient studies. Results from imaging studies in two neurodegenerative diseases reveal subgroups and their distinct trajectories of regional neurodegeneration. In genetic frontotemporal dementia, SuStaIn identifies genotypes from imaging alone, validating its ability to identify subtypes; further the technique reveals within-genotype heterogeneity. In Alzheimer’s disease, SuStaIn uncovers three subtypes, uniquely characterising their temporal complexity. SuStaIn provides fine-grained patient stratification, which substantially enhances the ability to predict conversion between diagnostic categories over standard models that ignore subtype ( p = 7.18 × 10 −4 ) or temporal stage ( p = 3.96 × 10 −5 ). SuStaIn offers new promise for enabling disease subtype discovery and precision medicine.

RATIONALE: Accurate, early identification of patients at risk for developing acute lung injury (ALI) provides the opportunity to test and implement secondary prevention strategies. OBJECTIVES: To determine the frequency and outcome of ALI development in patients at risk and validate a lung injury prediction score (LIPS). METHODS: In this prospective multicenter observational cohort study, predisposing conditions and risk modifiers predictive of ALI development were identified from routine clinical data available during initial evaluation. The discrimination of the model was assessed with area under receiver operating curve (AUC). The risk of death from ALI was determined after adjustment for severity of illness and predisposing conditions. MEASUREMENTS AND MAIN RESULTS: Twenty-two hospitals enrolled 5,584 patients at risk. ALI developed a median of 2 (interquartile range 1-4) days after initial evaluation in 377 (6.8%; 148 ALI-only, 229 adult respiratory distress syndrome) patients. The frequency of ALI varied according to predisposing conditions (from 3% in pancreatitis to 26% after smoke inhalation). LIPS discriminated patients who developed ALI from those who did not with an AUC of 0.80 (95% confidence interval, 0.78-0.82). When adjusted for severity of illness and predisposing conditions, development of ALI increased the risk of in-hospital death (odds ratio, 4.1; 95% confidence interval, 2.9-5.7). CONCLUSIONS: ALI occurrence varies according to predisposing conditions and carries an independently poor prognosis. Using routinely available clinical data, LIPS identifies patients at high risk for ALI early in the course of their illness. This model will alert clinicians about the risk of ALI and facilitate testing and implementation of ALI prevention strategies. Clinical trial registered with www.clinicaltrials.gov (NCT00889772).

Abstract Activation of ferroptosis, a recently described mechanism of regulated cell death, dramatically inhibits growth of ovarian cancer cells. Given the importance of lipid metabolism in ferroptosis and the key role of lipids in ovarian cancer, we examined the contribution to ferroptosis of stearoyl-CoA desaturase (SCD1, SCD), an enzyme that catalyzes the rate-limiting step in monounsaturated fatty acid synthesis in ovarian cancer cells. SCD1 was highly expressed in ovarian cancer tissue, cell lines, and a genetic model of ovarian cancer stem cells. Inhibition of SCD1 induced lipid oxidation and cell death. Conversely, overexpression of SCD or exogenous administration of its C16:1 and C18:1 products, palmitoleic acid or oleate, protected cells from death. Inhibition of SCD1 induced both ferroptosis and apoptosis. Inhibition of SCD1 decreased CoQ10, an endogenous membrane antioxidant whose depletion has been linked to ferroptosis, while concomitantly decreasing unsaturated fatty acyl chains in membrane phospholipids and increasing long-chain saturated ceramides, changes previously linked to apoptosis. Simultaneous triggering of two death pathways suggests SCD1 inhibition may be an effective component of antitumor therapy, because overcoming this dual mechanism of cell death may present a significant barrier to the emergence of drug resistance. Supporting this concept, we observed that inhibition of SCD1 significantly potentiated the antitumor effect of ferroptosis inducers in both ovarian cancer cell lines and a mouse orthotopic xenograft model. Our results suggest that the use of combined treatment with SCD1 inhibitors and ferroptosis inducers may provide a new therapeutic strategy for patients with ovarian cancer. Significance: The combination of SCD1 inhibitors and ferroptosis inducers may provide a new therapeutic strategy for the treatment of ovarian cancer patients. See related commentary by Carbone and Melino, p. 5149

Tau is a hallmark pathology of Alzheimer's disease, and animal models have suggested that tau spreads from cell to cell through neuronal connections, facilitated by β-amyloid (Aβ). We test this hypothesis in humans using an epidemic spreading model (ESM) to simulate tau spread, and compare these simulations to observed patterns measured using tau-PET in 312 individuals along Alzheimer's disease continuum. Up to 70% of the variance in the overall spatial pattern of tau can be explained by our model. Surprisingly, the ESM predicts the spatial patterns of tau irrespective of whether brain Aβ is present, but regions with greater Aβ burden show greater tau than predicted by connectivity patterns, suggesting a role of Aβ in accelerating tau spread. Altogether, our results provide evidence in humans that tau spreads through neuronal communication pathways even in normal aging, and that this process is accelerated by the presence of brain Aβ.

Reduced glomerular filtration rate defines chronic kidney disease and is associated with cardiovascular and all-cause mortality. We conducted a meta-analysis of genome-wide association studies for estimated glomerular filtration rate (eGFR), combining data across 133,413 individuals with replication in up to 42,166 individuals. We identify 24 new and confirm 29 previously identified loci. Of these 53 loci, 19 associate with eGFR among individuals with diabetes. Using bioinformatics, we show that identified genes at eGFR loci are enriched for expression in kidney tissues and in pathways relevant for kidney development and transmembrane transporter activity, kidney structure, and regulation of glucose metabolism. Chromatin state mapping and DNase I hypersensitivity analyses across adult tissues demonstrate preferential mapping of associated variants to regulatory regions in kidney but not extra-renal tissues. These findings suggest that genetic determinants of eGFR are mediated largely through direct effects within the kidney and highlight important cell types and biological pathways.

Recent advances in omics technologies have led to unprecedented efforts characterizing the molecular changes that underlie the development and progression of a wide array of complex human diseases, including cancer. As a result, multi-omics analyses-which take advantage of these technologies in genomics, transcriptomics, epigenomics, proteomics, metabolomics, and other omics areas-have been proposed and heralded as the key to advancing precision medicine in the clinic. In the field of precision oncology, genomics approaches, and, more recently, other omics analyses have helped reveal several key mechanisms in cancer development, treatment resistance, and recurrence risk, and several of these findings have been implemented in clinical oncology to help guide treatment decisions. However, truly integrated multi-omics analyses have not been applied widely, preventing further advances in precision medicine. Additional efforts are needed to develop the analytical infrastructure necessary to generate, analyze, and annotate multi-omics data effectively to inform precision medicine-based decision-making.