Abstract: The synaptonemal complex (SC) is intimately involved in the process of meiotic recombination in most organisms, but its exact role remains enigmatic. One reason for this uncertainty is that the overall structure of the SC is evolutionarily conserved, but many SC proteins are not. Two putative SC proteins have been identified in Drosophila : C(3)G and C(2)M. Mutations in either gene cause defects in SC structure and meiotic recombination. Although neither gene is well conserved at the amino acid level, the predicted secondary structure of C(3)G is similar to that of transversefilament proteins, and C(2)M is a distantly related member of the α-kleisin family that includes Rec8, a meiosis-specific cohesin protein. Here, we use immunogold labeling of SCs in Drosophila ovaries to localize C(3)G and C(2)M at the EM level. We show that both C(3)G and C(2)M are components of the SC, that the orientation of C(3)G within the SC is similar to other transverse-filament proteins, and that the N terminus of C(2)M is located in the central region adjacent to the lateral elements (LEs). Based on our data and the known phenotypes of C(2)M and C(3)G mutants, we propose a model of SC structure in which C(2)M links C(3)G to the LEs.

Abstract: To assess the relative importance of climate and humans in burning over recent millennia, we reconstruct fire history from three independent sources, specifically, historical, fire-scar, and charcoal data. We then compare the results to data on climate and population. We also construct a statistical model to determine the extent to which climate alone can predict biomass burning. The historical data were obtained from the United States Department of Agriculture Forest Service estimates of the extent, use, and destruction of original saw timber (i.e., trees older than 50 y in 1630 CE) from 1630 to 1940 CE ( 2 ). Fire-scar data ( n  = 359) were obtained from the International Multiproxy Paleofire Database, which provides annually resolved data on fires from around 1400 CE to present (primarily from dry interior ponderosa pine forests). We estimate temporal trends in fire by using the proportion of site records with scars for each year. Sedimentary charcoal accumulation rates from 69 records are used to identify decadal-to centennial-scale trends in biomass burning over the past three millennia, and a subset ( n  = 41) of records are further analyzed to reconstruct fire-episode frequency over this interval. Temperature, drought, and population changes are used to understand the changes in forest fire activity, while temperature and drought are used in a statistical regression model (Generalized Additive Model or GAM) to explain the variability in biomass burning during the past 1,500 y. Anthropogenic impacts on fire occur against the backdrop of climate variability. There have been marked human influences on western wildfires since Euro-American settlement, including increased ignitions (e.g., from forest clearance, agriculture, logging, and railroads), and fire exclusion (e.g., from landscape fragmentation, grazing, and suppression). Other significant impacts on vegetation and fire occurred indirectly, such as changes in plant succession pathways (e.g., when shrublands previously maintained by frequent fire converted to forest after fires were regularly excluded) and the introduction of nonnative species. Indigenous fire use prior to settlement varied in intensity, extent, and persistence, and probably varied with season, migration, and cultural and technological developments. Climate is generally considered to be the primary control of contemporary fire regimes in the western United States ( 1 ). Climate influences fire primarily through variations in temperature and precipitation (and thus available moisture). Increasing temperature leads to more fires; however, this is only true if sufficient vegetation is present to support the spread of fire. Precipitation is also linked to fire—there must be sufficient moisture to support continuous vegetation on the landscape, but not so much that fuels never become dry enough to burn. Forest fires in the western United States have been increasing in extent for several decades, prompting much research into the causes and consequences of such changes. The overall level of fire activity in a given place is governed by processes relating to climate, people, and vegetation that operate over decades and centuries; yet, most fire research is based on much shorter time scales. Given that future climate change is expected to drive fire activity well above its historical range of variability, a long-term perspective provides essential context to current changes. We use sedimentary charcoal accumulation rates to construct baseline levels of burning for the past 3,000 y in the American West; we then compare this record to independent fire-history data obtained from historical records and fire scars. We also create a statistical model, based only on independent temperature and drought reconstructions, that predicts 85% of the variability in biomass burnt (thought to reflect area burnt) prior to the 1800s, before human and ecological influences became dominant. Large shifts in biomass burning since the 1800s are not unprecedented, but their causes and effects differ greatly from climate-driven shifts in the past. Fire regimes are currently in disequilibrium with the climate, due to the opposing forces of fire exclusion practices (e.g., grazing and fire suppression) and global warming; consequently, a large “fire deficit” exists. The 20th Century Fire Deficit in the Western United States. Observed and predicted changes in biomass burning diverge in the late 1800s, despite increasing temperature and drought (Fig. 4 A ). Observed biomass burning, fire scars, charcoal-based fire frequencies, and human-caused fires decline to levels similar to the levels during the LIA. In contrast, predicted biomass burning rises from 1880 CE to present, which is consistent with increased temperature and drought. This pattern indicates that nonclimatic factors became the dominant control of fires around 1880 CE. The decline in fires during the 20th century may be explained by multiple factors. In the late 1800s, widespread domestic livestock grazing reduced grassy fuel loads, compacted soils, and greatly reduced fire frequencies. By 1900 CE, the western frontier had largely closed, and intentionally set fires probably declined due to changing attitudes and policies towards fire. In addition, landscape fragmentation from trail and road building limited the spread of fire. Furthermore, after the 1940s, fire suppression became highly effective, preventing the spread of many forest fires. However, ecological factors also played a role, as the number of young stands and aspen stands, which are resistant to burning, increased after logging and previous extensive burning. Consequently, a fire deficit now exists and has been growing throughout the 20th century, pushing fire regimes into disequilibrium with climate. Hence, while current levels of large-scale biomass burning ( 1 ) remain within the realm of natural variability during the past 1,000 y, if levels of burning were to come into equilibrium with climate, they would exceed the natural range of variability experienced in at least the last 3,000 y. Three independent fire-history reconstructions for the western United States show that there have been large changes in wildfires since the 1800s. In earlier periods, changes of this scale were driven by climate; in the past 200 y, human behavior has played a much larger role. Fire suppression practices have greatly reduced fire, whereas global warming has increased the probability of fire. A widening gap, or fire deficit, therefore exists between actual levels of burning and expected levels of burning given current climate conditions. Recent increases in catastrophic wildfires in the West are an indication of this deficit, and suggest that current fire suppression practices are unsustainable. Fires are projected to increase even further in coming decades, and may require reevaluation of fire management policies and potential investment of additional resources. Climate Controls Fire Until the Beginning of Euro-American Settlement of the West. A statistical model, calibrated using data from 500 to 1800 CE, predicts multidecadal-to-centennial changes in biomass burning from temperature and drought area indices. Climate explains most of the multidecadal-to century-scale variations of biomass burning. Temperature alone accounts for half of the total variance of biomass burning, while drought area explains about 1/3 of overall variance. Downward trends were recorded for temperature, drought, biomass burning, fire frequency (see full text), and predicted biomass burning during the past two millennia until the Settlement Era ( Fig. P1 A – E ). In contrast, the human population gradually increased until ca. 500 y ago, when Native American populations began to collapse after European contact ( Fig. P1 F ). The population began to recover around 350 y ago, and then rose dramatically since settlement. Biomass burning was high when climate changed rapidly at the beginning of the Medieval Climate Anomaly (MCA), which was around 1000 CE when both temperature and drought were also high. Fire activity was high again at the onset of the Little Ice Age (LIA), around 1400 CE, when drought was high. However, as the LIA progressed, biomass burning declined substantially, which coincided with large declines in temperature, drought, and population ( Fig. P1 A , D and E ). Fig. P1. ( A ) Smoothed and standardized 25-year (gray) and 100-year (red) trend line through standardized biomass burning records ( n  = 69) along with predicted biomass burning based on a GAM (black dashed line) fit to the 100-year charcoal values. ( B ) Smoothed proportions of dendrochronological sites recording fire scars. ( C ) Estimated historical sawtimber affected by lightning- and human-caused fires in the western United States ( 2 ) ( D ) Smoothed gridded temperature anomalies for the western United States ( 3 ). ( E ) Smoothed Palmer Drought Severity Index for the western United States ( 4 ). ( F ) Population estimates for the western United States ( 5 ). All smoothed curves are plotted with 95% bootstrap confidence intervals. The transition from the LIA into the Settlement Era is marked by a sharp increase in burning, as evidenced by historical records, fire-scar, and (observed and predicted) charcoal data. The increase in fire activity, which reached its maximum ca. 1850–1870 CE (Fig. 4 C ), is consistent with increased ignitions from land clearance, logging, agriculture, and railroads during settlement, and also with increasing temperature and drought, which reached a maximum between 1700 and 1900 CE ( Fig. P1 A – E ). Thus, climate and humans acted synergistically to increase fire.

Abstract: The Sample Analysis at Mars (SAM) investigation on the Mars Science Laboratory (MSL) Curiosity rover has detected oxidized nitrogen-bearing compounds during pyrolysis of scooped aeolian sediments and drilled sedimentary deposits within Gale crater. Total N concentrations ranged from 20 to 250 nmol N per sample. After subtraction of known N sources in SAM, our results support the equivalent of 110–300 ppm of nitrate in the Rocknest (RN) aeolian samples, and 70–260 and 330–1,100 ppm nitrate in John Klein (JK) and Cumberland (CB) mudstone deposits, respectively. Discovery of indigenous martian nitrogen in Mars surface materials has important implications for habitability and, specifically, for the potential evolution of a nitrogen cycle at some point in martian history. The detection of nitrate in both wind-drifted fines (RN) and in mudstone (JK, CB) is likely a result of N 2 fixation to nitrate generated by thermal shock from impact or volcanic plume lightning on ancient Mars. Fixed nitrogen could have facilitated the development of a primitive nitrogen cycle on the surface of ancient Mars, potentially providing a biochemically accessible source of nitrogen.

Abstract: The gap between chronological age (CA) and biological brain age, as estimated from magnetic resonance images (MRIs), reflects how individual patterns of neuroanatomic aging deviate from their typical trajectories. MRI-derived brain age (BA) estimates are often obtained using deep learning models that may perform relatively poorly on new data or that lack neuroanatomic interpretability. This study introduces a convolutional neural network (CNN) to estimate BA after training on the MRIs of 4,681 cognitively normal (CN) participants and testing on 1,170 CN participants from an independent sample. BA estimation errors are notably lower than those of previous studies. At both individual and cohort levels, the CNN provides detailed anatomic maps of brain aging patterns that reveal sex dimorphisms and neurocognitive trajectories in adults with mild cognitive impairment (MCI, N  = 351) and Alzheimer’s disease (AD, N  = 359). In individuals with MCI (54% of whom were diagnosed with dementia within 10.9 y from MRI acquisition), BA is significantly better than CA in capturing dementia symptom severity, functional disability, and executive function. Profiles of sex dimorphism and lateralization in brain aging also map onto patterns of neuroanatomic change that reflect cognitive decline. Significant associations between BA and neurocognitive measures suggest that the proposed framework can map, systematically, the relationship between aging-related neuroanatomy changes in CN individuals and in participants with MCI or AD. Early identification of such neuroanatomy changes can help to screen individuals according to their AD risk.

Abstract: Aberrant connectivity is implicated in many neurological and psychiatric disorders, including Alzheimer’s disease and schizophrenia. However, other than a few disease-associated candidate genes, we know little about the degree to which genetics play a role in the brain networks; we know even less about specific genes that influence brain connections. Twin and family-based studies can generate estimates of overall genetic influences on a trait, but genome-wide association scans (GWASs) can screen the genome for specific variants influencing the brain or risk for disease. To identify the heritability of various brain connections, we scanned healthy young adult twins with high-field, high-angular resolution diffusion MRI. We adapted GWASs to screen the brain’s connectivity pattern, allowing us to discover genetic variants that affect the human brain’s wiring. The association of connectivity with the SPON1 variant at rs2618516 on chromosome 11 (11p15.2) reached connectome-wide, genome-wide significance after stringent statistical corrections were enforced, and it was replicated in an independent subsample. rs2618516 was shown to affect brain structure in an elderly population with varying degrees of dementia. Older people who carried the connectivity variant had significantly milder clinical dementia scores and lower risk of Alzheimer’s disease. As a posthoc analysis, we conducted GWASs on several organizational and topological network measures derived from the matrices to discover variants in and around genes associated with autism ( MACROD2 ), development ( NEDD4 ), and mental retardation ( UBE2A ) significantly associated with connectivity. Connectome-wide, genome-wide screening offers substantial promise to discover genes affecting brain connectivity and risk for brain diseases.

Abstract: A recently identified variant within the fat mass and obesity-associated ( FTO ) gene is carried by 46% of Western Europeans and is associated with an ~1.2 kg higher weight, on average, in adults and an ~1 cm greater waist circumference. With 〉 1 billion overweight and 300 million obese persons worldwide, it is crucial to understand the implications of carrying this very common allele for the health of our aging population. FTO is highly expressed in the brain and elevated body mass index (BMI) is associated with brain atrophy, but it is unknown how the obesity-associated risk allele affects human brain structure. We therefore generated 3D maps of regional brain volume differences in 206 healthy elderly subjects scanned with MRI and genotyped as part of the Alzheimer's Disease Neuroimaging Initiative. We found a pattern of systematic brain volume deficits in carriers of the obesity-associated risk allele versus noncarriers. Relative to structure volumes in the mean template, FTO risk allele carriers versus noncarriers had an average brain volume difference of ~8% in the frontal lobes and 12% in the occipital lobes—these regions also showed significant volume deficits in subjects with higher BMI. These brain differences were not attributable to differences in cholesterol levels, hypertension, or the volume of white matter hyperintensities; which were not detectably higher in FTO risk allele carriers versus noncarriers. These brain maps reveal that a commonly carried susceptibility allele for obesity is associated with structural brain atrophy, with implications for the health of the elderly.

Abstract: Regions of the temporal and parietal lobes are particularly damaged in Alzheimer's disease (AD), and this leads to a predictable pattern of brain atrophy. In vivo quantification of subregional atrophy, such as changes in cortical thickness or structure volume, could lead to improved diagnosis and better assessment of the neuroprotective effects of a therapy. Toward this end, we have developed a fast and robust method for accurately quantifying cerebral structural changes in several cortical and subcortical regions using serial MRI scans. In 169 healthy controls, 299 subjects with mild cognitive impairment (MCI), and 129 subjects with AD, we measured rates of subregional cerebral volume change for each cohort and performed power calculations to identify regions that would provide the most sensitive outcome measures in clinical trials of disease-modifying agents. Consistent with regional specificity of AD, temporal-lobe cortical regions showed the greatest disease-related changes and significantly outperformed any of the clinical or cognitive measures examined for both AD and MCI. Global measures of change in brain structure, including whole-brain and ventricular volumes, were also elevated in AD and MCI, but were less salient when compared to changes in normal subjects. Therefore, these biomarkers are less powerful for quantifying disease-modifying effects of compounds that target AD pathology. The findings indicate that regional temporal lobe cortical changes would have great utility as outcome measures in clinical trials and may also have utility in clinical practice for aiding early diagnosis of neurodegenerative disease.

Abstract: The ε4 allele of the apolipoprotein E (APOE) gene is the major genetic risk factor for Alzheimer’s disease (AD), but limited work has suggested that APOE genotype may modulate disease phenotype. Carriers of the ε4 allele have been reported to have greater medial temporal lobe (MTL) pathology and poorer memory than noncarriers. Less attention has focused on whether there are domains of cognition and neuroanatomical regions more affected in noncarriers. Further, a major potential confound of prior in vivo studies is the possibility of different rates of clinical misdiagnosis for carriers vs. noncarriers. We compared phenotypic differences in cognition and topography of regional cortical atrophy of ε4 carriers ( n = 67) vs. noncarriers ( n = 24) with mild AD from the Alzheimer’s Disease Neuroimaging Initiative, restricted to those with a cerebrospinal fluid (CSF) molecular profile consistent with AD. Between-group comparisons were made for psychometric tests and morphometric measures of cortical thickness and hippocampal volume. Carriers displayed significantly greater impairment on measures of memory retention, whereas noncarriers were more impaired on tests of working memory, executive control, and lexical access. Consistent with this cognitive dissociation, carriers exhibited greater MTL atrophy, whereas noncarriers had greater frontoparietal atrophy. Performance deficits in particular cognitive domains were associated with disproportionate regional brain atrophy within nodes of cortical networks thought to subserve these cognitive processes. These convergent cognitive and neuroanatomic findings in individuals with a CSF molecular profile consistent with AD support the hypothesis that APOE genotype modulates the clinical phenotype of AD through influence on specific large-scale brain networks.

Abstract: Loss-of-function mutations in the genes associated with primary microcephaly (MCPH) reduce human brain size by about two-thirds, without producing gross abnormalities in brain organization or physiology and leaving other organs largely unaffected [Woods CG, et al. (2005) Am J Hum Genet 76:717–728]. There is also evidence suggesting that MCPH genes have evolved rapidly in primates and humans and have been subjected to selection in recent human evolution [Vallender EJ, et al. (2008) Trends Neurosci 31:637–644]. Here, we show that common variants of MCPH genes account for some of the common variation in brain structure in humans, independently of disease status. We investigated the correlations of SNPs from four MCPH genes with brain morphometry phenotypes obtained with MRI. We found significant, sex-specific associations between common, nonexonic, SNPs of the genes CDK5RAP2 , MCPH1 , and ASPM , with brain volume or cortical surface area in an ethnically homogenous Norwegian discovery sample ( n = 287), including patients with mental illness. The most strongly associated SNP findings were replicated in an independent North American sample ( n = 656), which included patients with dementia. These results are consistent with the view that common variation in brain structure is associated with genetic variants located in nonexonic, presumably regulatory, regions.