Homopolymer switches mediate adaptive mutability in mismatch repair-deficient colorectal cancer.

Mismatch repair (MMR)-deficient cancer evolves through the stepwise erosion of coding homopolymers in target genes. Curiously, the MMR genes MutS homolog 6 (MSH6) and MutS homolog 3 (MSH3) also contain coding homopolymers, and these are frequent mutational targets in MMR-deficient cancers. The impact of incremental MMR mutations on MMR-deficient cancer evolution is unknown. Here we show that microsatellite instability modulates DNA repair by toggling hypermutable mononucleotide homopolymer runs in MSH6 and MSH3 through stochastic frameshift switching. Spontaneous mutation and reversion modulate subclonal mutation rate, mutation bias and HLA and neoantigen diversity. Patient-derived organoids corroborate these observations and show that MMR homopolymer sequences drift back into reading frame in the absence of immune selection, suggesting a fitness cost of elevated mutation rates. Combined experimental and simulation studies demonstrate that subclonal immune selection favors incremental MMR mutations. Overall, our data demonstrate that MMR-deficient colorectal cancers fuel intratumor heterogeneity by adapting subclonal mutation rate and diversity to immune selection.

The mutagenic forces shaping the genomic landscape of lung cancer in never smokers.

Lung cancer in never smokers (LCINS) accounts for up to 25% of all lung cancers and has been associated with exposure to secondhand tobacco smoke and air pollution in observational studies. Here, we evaluate the mutagenic exposures in LCINS by examining deep whole-genome sequencing data from a large international cohort of 871 treatment-naïve LCINS recruited from 28 geographical locations within the Sherlock-Lung study. KRAS mutations were 3.8-fold more common in adenocarcinomas of never smokers from North America and Europe, while a 1.6-fold higher prevalence of EGFR and TP53 mutations was observed in adenocarcinomas from East Asia. Signature SBS40a, with unknown cause, was found in most samples and accounted for the largest proportion of single base substitutions in adenocarcinomas, being enriched in EGFR-mutated cases. Conversely, the aristolochic acid signature SBS22a was almost exclusively observed in patients from Taipei. Even though LCINS exposed to secondhand smoke had an 8.3% higher mutational burden and 5.4% shorter telomeres, passive smoking was not associated with driver mutations in cancer driver genes or the activities of individual mutational signatures. In contrast, patients from regions with high levels of air pollution were more likely to have TP53 mutations while exhibiting shorter telomeres and an increase in most types of somatic mutations, including a 3.9-fold elevation of signature SBS4 (q-value=3.1 × 10-5), previously linked mainly to tobacco smoking, and a 76% increase of clock-like signature SBS5 (q-value=5.0 × 10-5). A positive dose-response effect was observed with air pollution levels, which correlated with both a decrease in telomere length and an elevation in somatic mutations, notably attributed to signatures SBS4 and SBS5. Our results elucidate the diversity of mutational processes shaping the genomic landscape of lung cancer in never smokers.

Sleep health among US Navy afloat versus ashore personnel in the Millennium Cohort Study.

Despite emerging public concern regarding the sleep health of military personnel over the past two decades, there remains a dearth of research examining sleep health among naval personnel assigned to sea duty. This study examined sleep metrics (e.g. fatigue, short sleep duration) and mental (e.g. posttraumatic stress disorder, depression) and physical health (e.g. type 2 diabetes, bodily pain) outcomes among naval personnel with recent sea duty (i.e. afloat) compared with naval personnel with recent shore duty (i.e. ashore). Prevalence ratios and mean differences for all outcomes were estimated and adjusted for demographic and military variables, and subsequently stratified by obesity. Sleep metrics were similar between afloat and ashore sailors except for short sleep duration, while sailors with recent shore duty had poorer physical health compared with those with recent sea duty. Stratified analyses suggested naval personnel with obesity had a higher proportion of nearly all adverse sleep-related health outcomes than those without obesity. Among participants without obesity, afloat personnel were more likely to report very short sleep (≤ 5 hours) and fewer hours of average nightly sleep, but were less likely to report physical health outcomes compared with ashore personnel. These findings suggest potential differences in sleep metrics and sleep-related health outcomes between afloat and ashore naval personnel. Additional research examining sleep outcomes using more objective measures is required to further investigate these findings, which may inform strategies to foster consolidated sleep despite environmental and occupational challenges in order to maintain high-performing naval personnel.

MVComp toolbox: MultiVariate Comparisons of brain MRI features accounting for common information across metrics.

Multivariate approaches have recently gained in popularity to address the physiological unspecificity of neuroimaging metrics and to better characterize the complexity of biological processes underlying behavior. However, commonly used approaches are biased by the intrinsic associations between variables, or they are computationally expensive and may be more complicated to implement than standard univariate approaches. Here, we propose using the Mahalanobis distance (D2), an individual-level measure of deviation relative to a reference distribution that accounts for covariance between metrics. To facilitate its use, we introduce an open-source python-based tool for computing D2 relative to a reference group or within a single individual: the MultiVariate Comparison (MVComp) toolbox. The toolbox allows different levels of analysis (i.e., group- or subject-level), resolutions (e.g., voxel-wise, ROI-wise) and dimensions considered (e.g., combining MRI metrics or WM tracts). Several example cases are presented to showcase the wide range of possible applications of MVComp and to demonstrate the functionality of the toolbox. The D2 framework was applied to the assessment of white matter (WM) microstructure at 1) the group-level, where D2 can be computed between a subject and a reference group to yield an individualized measure of deviation. We observed that clustering applied to D2 in the corpus callosum yields parcellations that highly resemble known topography based on neuroanatomy, suggesting that D2 provides an integrative index that meaningfully reflects the underlying microstructure. 2) At the subject level, D2 was computed between voxels to obtain a measure of (dis)similarity. The loadings of each MRI metric (i.e., its relative contribution to D2) were then extracted in voxels of interest to showcase a useful option of the MVComp toolbox. These relative contributions can provide important insights into the physiological underpinnings of differences observed. Integrative multivariate models are crucial to expand our understanding of the complex brain-behavior relationships and the multiple factors underlying disease development and progression. Our toolbox facilitates the implementation of a useful multivariate method, making it more widely accessible.

Decreased long-range temporal correlations in the resting-state functional magnetic resonance imaging blood-oxygen-level-dependent signal reflect motor sequence learning up to 2 weeks following training.

Decreased long-range temporal correlations (LRTC) in brain signals can be used to measure cognitive effort during task execution. Here, we examined how learning a motor sequence affects long-range temporal memory within resting-state functional magnetic resonance imaging signal. Using the Hurst exponent (HE), we estimated voxel-wise LRTC and assessed changes over 5 consecutive days of training, followed by a retention scan 12 days later. The experimental group learned a complex visuomotor sequence while a complementary control group performed tightly matched movements. An interaction analysis revealed that HE decreases were specific to the complex sequence and occurred in well-known motor sequence learning associated regions including left supplementary motor area, left premotor cortex, left M1, left pars opercularis, bilateral thalamus, and right striatum. Five regions exhibited moderate to strong negative correlations with overall behavioral performance improvements. Following learning, HE values returned to pretraining levels in some regions, whereas in others, they remained decreased even 2 weeks after training. Our study presents new evidence of HE's possible relevance for functional plasticity during the resting-state and suggests that a cortical subset of sequence-specific regions may continue to represent a functional signature of learning reflected in decreased long-range temporal dependence after a period of inactivity.

The impact of lesion side on bilateral upper limb coordination after stroke.

BACKGROUND: A stroke frequently results in impaired performance of activities of daily life. Many of these are highly dependent on effective coordination between the two arms. In the context of bimanual movements, cyclic rhythmical bilateral arm coordination patterns can be classified into two fundamental modes: in-phase (bilateral homologous muscles contract simultaneously) and anti-phase (bilateral muscles contract alternately) movements. We aimed to investigate how patients with left (LHS) and right (RHS) hemispheric stroke are differentially affected in both individual-limb control and inter-limb coordination during bilateral movements. METHODS: We used kinematic measurements to assess bilateral coordination abilities of 18 chronic hemiparetic stroke patients (9 LHS; 9 RHS) and 18 age- and sex-matched controls. Using KINARM upper-limb exoskeleton system, we examined individual-limb control by quantifying trajectory variability in each hand and inter-limb coordination by computing the phase synchronization between hands during anti- and in-phase movements. RESULTS: RHS patients exhibited greater impairment in individual- and inter-limb control during anti-phase movements, whilst LHS patients showed greater impairment in individual-limb control during in-phase movements alone. However, LHS patients further showed a swap in hand dominance during in-phase movements. CONCLUSIONS: The current study used individual-limb and inter-limb kinematic profiles and showed that bilateral movements are differently impaired in patients with left vs. right hemispheric strokes. Our results demonstrate that both fundamental bilateral coordination modes are differently controlled in both hemispheres using a lesion model approach. From a clinical perspective, we suggest that lesion side should be taken into account for more individually targeted bilateral coordination training strategies. TRIAL REGISTRATION: the current experiment is not a health care intervention study.

Visualizing and exploring patterns of large mutational events with SigProfilerMatrixGenerator.

BACKGROUND: All cancers harbor somatic mutations in their genomes. In principle, mutations affecting between one and fifty base pairs are generally classified as small mutational events. Conversely, large mutational events affect more than fifty base pairs, and, in most cases, they encompass copy-number and structural variants affecting many thousands of base pairs. Prior studies have demonstrated that examining patterns of somatic mutations can be leveraged to provide both biological and clinical insights, thus, resulting in an extensive repertoire of tools for evaluating small mutational events. Recently, classification schemas for examining large-scale mutational events have emerged and shown their utility across the spectrum of human cancers. However, there has been no computationally efficient bioinformatics tool that allows visualizing and exploring these large-scale mutational events. RESULTS: Here, we present a new version of SigProfilerMatrixGenerator that now delivers integrated capabilities for examining large mutational events. The tool provides support for examining copy-number variants and structural variants under two previously developed classification schemas and it supports data from numerous algorithms and data modalities. SigProfilerMatrixGenerator is written in Python with an R wrapper package provided for users that prefer working in an R environment. CONCLUSIONS: The new version of SigProfilerMatrixGenerator provides the first standardized bioinformatics tool for optimized exploration and visualization of two previously developed classification schemas for copy number and structural variants. The tool is freely available at https://github.com/AlexandrovLab/SigProfilerMatrixGenerator with an extensive documentation at https://osf.io/s93d5/wiki/home/ .

Modeling venous bias in resting state functional MRI metrics.

Resting-state (rs) functional magnetic resonance imaging (fMRI) is used to detect low-frequency fluctuations in the blood oxygen-level dependent (BOLD) signal across brain regions. Correlations between temporal BOLD signal fluctuations are commonly used to infer functional connectivity. However, because BOLD is based on the dilution of deoxyhemoglobin, it is sensitive to veins of all sizes, and its amplitude is biased by draining veins. These biases affect local BOLD signal location and amplitude, and may also influence BOLD-derived connectivity measures, but the magnitude of this venous bias and its relation to vein size and proximity is unknown. Here, veins were identified using high-resolution quantitative susceptibility maps and utilized in a biophysical model to investigate systematic venous biases on common local rsfMRI-derived measures. Specifically, we studied the impact of vein diameter and distance to veins on the amplitude of low-frequency fluctuations (ALFF), fractional ALFF (fALFF), Hurst exponent (HE), regional homogeneity (ReHo), and eigenvector centrality values in the grey matter. Values were higher across all distances in smaller veins, and decreased with increasing vein diameter. Additionally, rsfMRI values associated with larger veins decrease with increasing distance from the veins. ALFF and ReHo were the most biased by veins, while HE and fALFF exhibited the smallest bias. Across all metrics, the amplitude of the bias was limited in voxel-wise data, confirming that venous structure is not the dominant source of contrast in these rsfMRI metrics. Finally, the models presented can be used to correct this venous bias in rsfMRI metrics.

International Multicenter Study of Clinical Outcomes of Sinonasal Melanoma Shows Survival Benefit for Patients Treated with Immune Checkpoint Inhibitors and Potential Improvements to the Current TNM Staging System.

Objectives Sinonasal mucosal melanoma (SNMM) is an extremely rare and challenging sinonasal malignancy with a poor prognosis. Standard treatment involves complete surgical resection, but the role of adjuvant therapy remains unclear. Crucially, our understanding of its clinical presentation, course, and optimal treatment remains limited, and few advancements in improving its management have been made in the recent past. Methods We conducted an international multicenter retrospective analysis of 505 SNMM cases from 11 institutions across the United States, United Kingdom, Ireland, and continental Europe. Data on clinical presentation, diagnosis, treatment, and clinical outcomes were assessed. Results One-, three-, and five-year recurrence-free and overall survival were 61.4, 30.6, and 22.0%, and 77.6, 49.2, and 38.3%, respectively. Compared with disease confined to the nasal cavity, sinus involvement confers significantly worse survival; based on this, further stratifying the T3 stage was highly prognostic ( p < 0.001) with implications for a potential modification to the current TNM staging system. There was a statistically significant survival benefit for patients who received adjuvant radiotherapy, compared with those who underwent surgery alone (hazard ratio [HR] = 0.74, 95% confidence interval [CI]: 0.57-0.96, p = 0.021). Immune checkpoint blockade for the management of recurrent or persistent disease, with or without distant metastasis, conferred longer survival (HR = 0.50, 95% CI: 0.25-1.00, p = 0.036). Conclusions We present findings from the largest cohort of SNMM reported to date. We demonstrate the potential utility of further stratifying the T3 stage by sinus involvement and present promising data on the benefit of immune checkpoint inhibitors for recurrent, persistent, or metastatic disease with implications for future clinical trials in this field.

Mitotic tethering enables inheritance of shattered micronuclear chromosomes.

Chromothripsis, the shattering and imperfect reassembly of one (or a few) chromosome(s)1, is an ubiquitous2 mutational process generating localized and complex chromosomal rearrangements that drive genome evolution in cancer. Chromothripsis can be initiated by mis-segregation errors in mitosis3,4 or DNA metabolism5-7 that lead to entrapment of chromosomes within micronuclei and their subsequent fragmentation in the next interphase or following mitotic entry6,8-10. Here we use inducible degrons to demonstrate that chromothriptically produced pieces of a micronucleated chromosome are tethered together in mitosis by a protein complex consisting of mediator of DNA damage checkpoint 1 (MDC1), DNA topoisomerase II-binding protein 1 (TOPBP1) and cellular inhibitor of PP2A (CIP2A), thereby enabling en masse segregation to the same daughter cell. Such tethering is shown to be crucial for the viability of cells undergoing chromosome mis-segregation and shattering after transient inactivation of the spindle assembly checkpoint. Transient, degron-induced reduction in CIP2A following chromosome micronucleation-dependent chromosome shattering is shown to drive acquisition of segmental deletions and inversions. Analyses of pancancer tumour genomes showed that expression of CIP2A and TOPBP1 was increased overall in cancers with genomic rearrangements, including copy number-neutral chromothripsis with minimal deletions, but comparatively reduced in cancers with canonical chromothripsis in which deletions were frequent. Thus, chromatin-bound tethers maintain the proximity of fragments of a shattered chromosome enabling their re-encapsulation into, and religation within, a daughter cell nucleus to form heritable, chromothriptically rearranged chromosomes found in the majority of human cancers.

Using cortico-cerebellar structural patterns to classify early- and late-trained musicians.

A body of current evidence suggests that there is a sensitive period for musical training: people who begin training before the age of seven show better performance on tests of musical skill, and also show differences in brain structure-especially in motor cortical and cerebellar regions-compared with those who start later. We used support vector machine models-a subtype of supervised machine learning-to investigate distributed patterns of structural differences between early-trained (ET) and late-trained (LT) musicians and to better understand the age boundaries of the sensitive period for early musicianship. After selecting regions of interest from the cerebellum and cortical sensorimotor regions, we applied recursive feature elimination with cross-validation to produce a model which optimally and accurately classified ET and LT musicians. This model identified a combination of 17 regions, including 9 cerebellar and 8 sensorimotor regions, and maintained a high accuracy and sensitivity (true positives, i.e., ET musicians) without sacrificing specificity (true negatives, i.e., LT musicians). Critically, this model-which defined ET musicians as those who began their training before the age of 7-outperformed all other models in which age of start was earlier or later (between ages 5-10). Our model's ability to accurately classify ET and LT musicians provides additional evidence that musical training before age 7 affects cortico-cerebellar structure in adulthood, and is consistent with the hypothesis that connected brain regions interact during development to reciprocally influence brain and behavioral maturation.

Visualizing and exploring patterns of large mutational events with SigProfilerMatrixGenerator.

Background: All cancers harbor somatic mutations in their genomes. In principle, mutations affecting between one and fifty base pairs are generally classified as small mutational events. Conversely, large mutational events affect more than fifty base pairs, and, in most cases, they encompass copy-number and structural variants affecting many thousands of base pairs. Prior studies have demonstrated that examining patterns of somatic mutations can be leveraged to provide both biological and clinical insights, thus, resulting in an extensive repertoire of tools for evaluating small mutational events. Recently, classification schemas for examining large-scale mutational events have emerged and shown their utility across the spectrum of human cancers. However, there has been no standard bioinformatics tool that allows visualizing and exploring these large-scale mutational events. Results: Here, we present a new version of SigProfilerMatrixGenerator that now delivers integrated capabilities for examining large mutational events. The tool provides support for examining copy-number variants and structural variants under two previously developed classification schemas and it supports data from numerous algorithms and data modalities. SigProfilerMatrixGenerator is written in Python with an R wrapper package provided for users that prefer working in an R environment. Conclusions: The new version of SigProfilerMatrixGenerator provides the first standardized bioinformatics tool for optimized exploration and visualization of two previously developed classification schemas for copy number and structural variants. The tool is freely available at https://github.com/AlexandrovLab/SigProfilerMatrixGenerator with an extensive documentation at https://osf.io/s93d5/wiki/home/ .

Genomic Patterns of Malignant Peripheral Nerve Sheath Tumor (MPNST) Evolution Correlate with Clinical Outcome and Are Detectable in Cell-Free DNA.

Malignant peripheral nerve sheath tumor (MPNST), an aggressive soft-tissue sarcoma, occurs in people with neurofibromatosis type 1 (NF1) and sporadically. Whole-genome and multiregional exome sequencing, transcriptomic, and methylation profiling of 95 tumor samples revealed the order of genomic events in tumor evolution. Following biallelic inactivation of NF1, loss of CDKN2A or TP53 with or without inactivation of polycomb repressive complex 2 (PRC2) leads to extensive somatic copy-number aberrations (SCNA). Distinct pathways of tumor evolution are associated with inactivation of PRC2 genes and H3K27 trimethylation (H3K27me3) status. Tumors with H3K27me3 loss evolve through extensive chromosomal losses followed by whole-genome doubling and chromosome 8 amplification, and show lower levels of immune cell infiltration. Retention of H3K27me3 leads to extensive genomic instability, but an immune cell-rich phenotype. Specific SCNAs detected in both tumor samples and cell-free DNA (cfDNA) act as a surrogate for H3K27me3 loss and immune infiltration, and predict prognosis. SIGNIFICANCE: MPNST is the most common cause of death and morbidity for individuals with NF1, a relatively common tumor predisposition syndrome. Our results suggest that somatic copy-number and methylation profiling of tumor or cfDNA could serve as a biomarker for early diagnosis and to stratify patients into prognostic and treatment-related subgroups. This article is highlighted in the In This Issue feature, p. 517.

Visuo-motor transformations in the intraparietal sulcus mediate the acquisition of endovascular medical skill.

Performing endovascular medical interventions safely and efficiently requires a diverse set of skills that need to be practised in dedicated training sessions. Here, we used multimodal magnetic resonance (MR) imaging to determine the structural and functional plasticity and core skills associated with skill acquisition. A training group learned to perform a simulator-based endovascular procedure, while a control group performed a simplified version of the task; multimodal MR images were acquired before and after training. Using a well-controlled interaction design, we found strong multimodal evidence for the role of the intraparietal sulcus (IPS) in endovascular skill acquisition that is in line with previous work implicating the structure in visuospatial transformations including simple visuo-motor and mental rotation tasks. Our results provide a unique window into the multimodal nature of rapid structural and functional plasticity of the human brain while learning a multifaceted and complex clinical skill. Further, our results provide a detailed description of the plasticity process associated with endovascular skill acquisition and highlight specific facets of skills that could enhance current medical pedagogy and be useful to explicitly target during clinical resident training.

Uncovering novel mutational signatures by de novo extraction with SigProfilerExtractor.

Mutational signature analysis is commonly performed in cancer genomic studies. Here, we present SigProfilerExtractor, an automated tool for de novo extraction of mutational signatures, and benchmark it against another 13 bioinformatics tools by using 34 scenarios encompassing 2,500 simulated signatures found in 60,000 synthetic genomes and 20,000 synthetic exomes. For simulations with 5% noise, reflecting high-quality datasets, SigProfilerExtractor outperforms other approaches by elucidating between 20% and 50% more true-positive signatures while yielding 5-fold less false-positive signatures. Applying SigProfilerExtractor to 4,643 whole-genome- and 19,184 whole-exome-sequenced cancers reveals four novel signatures. Two of the signatures are confirmed in independent cohorts, and one of these signatures is associated with tobacco smoking. In summary, this report provides a reference tool for analysis of mutational signatures, a comprehensive benchmarking of bioinformatics tools for extracting signatures, and several novel mutational signatures, including one putatively attributed to direct tobacco smoking mutagenesis in bladder tissues.

Mapping pontocerebellar connectivity with diffusion MRI.

The cerebellum's involvement in cognitive, affective and motor functions is mediated by connections to different regions of the cerebral cortex. A distinctive feature of cortico-cerebellar loops that has been demonstrated in the animal work is a topographic organization that is preserved across its corticopontine, pontocerebellar, and cerebello-thalmo-cortical segments. Here we used tractography derived from diffusion imaging data to characterize the connections between the pons and the individual lobules of the cerebellum and generate a parcellation of the pons and middle cerebellar peduncle based on the pattern of connectivity. We identified a rostral to caudal gradient in the pons, similar to that observed in the animal work, such that rostral regions were preferentially connected to cerebellar lobules involved in non-motor, and caudal regions with motor regions. These findings advance our fundamental understanding of the cerebellum, and the parcellations we generated provide context for future research into the pontocerebellar tract's involvement in health and disease.

A genetic model for central chondrosarcoma evolution correlates with patient outcome.

BACKGROUND: Central conventional chondrosarcoma (CS) is the most common subtype of primary malignant bone tumour in adults. Treatment options are usually limited to surgery, and prognosis is challenging. These tumours are characterised by the presence and absence of IDH1 and IDH2 mutations, and recently, TERT promoter alterations have been reported in around 20% of cases. The effect of these mutations on clinical outcome remains unclear. The purpose of this study was to determine if prognostic accuracy can be improved by the addition of genomic data, and specifically by examination of IDH1, IDH2, and TERT mutations. METHODS: In this study, we combined both archival samples and data sourced from the Genomics England 100,000 Genomes Project (n = 356). Mutations in IDH1, IDH2, and TERT were profiled using digital droplet PCR (n = 346), whole genome sequencing (n=68), or both (n = 64). Complex events and other genetic features were also examined, along with methylation array data (n = 84). We correlated clinical features and patient outcomes with our genetic findings. RESULTS: IDH2-mutant tumours occur in older patients and commonly present with high-grade or dedifferentiated disease. Notably, TERT mutations occur most frequently in IDH2-mutant tumours, although have no effect on survival in this group. In contrast, TERT mutations are rarer in IDH1-mutant tumours, yet they are associated with a less favourable outcome in this group. We also found that methylation profiles distinguish IDH1- from IDH2-mutant tumours. IDH wild-type tumours rarely exhibit TERT mutations and tend to be diagnosed in a younger population than those with tumours harbouring IDH1 and IDH2 mutations. A major genetic feature of this group is haploidisation and subsequent genome doubling. These tumours evolve less frequently to dedifferentiated disease and therefore constitute a lower risk group. CONCLUSIONS: Tumours with IDH1 or IDH2 mutations or those that are IDHwt have significantly different genetic pathways and outcomes in relation to TERT mutation. Diagnostic testing for IDH1, IDH2, and TERT mutations could therefore help to guide clinical monitoring and prognostication.

Predicting future cognitive decline from non-brain and multimodal brain imaging data in healthy and pathological aging.

Previous literature has focused on predicting a diagnostic label from structural brain imaging. Since subtle changes in the brain precede a cognitive decline in healthy and pathological aging, our study predicts future decline as a continuous trajectory instead. Here, we tested whether baseline multimodal neuroimaging data improve the prediction of future cognitive decline in healthy and pathological aging. Nonbrain data (demographics, clinical, and neuropsychological scores), structural MRI, and functional connectivity data from OASIS-3 (N = 662; age = 46-96 years) were entered into cross-validated multitarget random forest models to predict future cognitive decline (measured by CDR and MMSE), on average 5.8 years into the future. The analysis was preregistered, and all analysis code is publicly available. Combining non-brain with structural data improved the continuous prediction of future cognitive decline (best test-set performance: R2 = 0.42). Cognitive performance, daily functioning, and subcortical volume drove the performance of our model. Including functional connectivity did not improve predictive accuracy. In the future, the prognosis of age-related cognitive decline may enable earlier and more effective individualized cognitive, pharmacological, and behavioral interventions.

Signatures of copy number alterations in human cancer.

Gains and losses of DNA are prevalent in cancer and emerge as a consequence of inter-related processes of replication stress, mitotic errors, spindle multipolarity and breakage-fusion-bridge cycles, among others, which may lead to chromosomal instability and aneuploidy1,2. These copy number alterations contribute to cancer initiation, progression and therapeutic resistance3-5. Here we present a conceptual framework to examine the patterns of copy number alterations in human cancer that is widely applicable to diverse data types, including whole-genome sequencing, whole-exome sequencing, reduced representation bisulfite sequencing, single-cell DNA sequencing and SNP6 microarray data. Deploying this framework to 9,873 cancers representing 33 human cancer types from The Cancer Genome Atlas6 revealed a set of 21 copy number signatures that explain the copy number patterns of 97% of samples. Seventeen copy number signatures were attributed to biological phenomena of whole-genome doubling, aneuploidy, loss of heterozygosity, homologous recombination deficiency, chromothripsis and haploidization. The aetiologies of four copy number signatures remain unexplained. Some cancer types harbour amplicon signatures associated with extrachromosomal DNA, disease-specific survival and proto-oncogene gains such as MDM2. In contrast to base-scale mutational signatures, no copy number signature was associated with many known exogenous cancer risk factors. Our results synthesize the global landscape of copy number alterations in human cancer by revealing a diversity of mutational processes that give rise to these alterations.