Distinct longevity mechanisms across and within species and their association with aging.

Lifespan varies within and across species, but the general principles of its control remain unclear. Here, we conducted multi-tissue RNA-seq analyses across 41 mammalian species, identifying longevity signatures and examining their relationship with transcriptomic biomarkers of aging and established lifespan-extending interventions. An integrative analysis uncovered shared longevity mechanisms within and across species, including downregulated Igf1 and upregulated mitochondrial translation genes, and unique features, such as distinct regulation of the innate immune response and cellular respiration. Signatures of long-lived species were positively correlated with age-related changes and enriched for evolutionarily ancient essential genes, involved in proteolysis and PI3K-Akt signaling. Conversely, lifespan-extending interventions counteracted aging patterns and affected younger, mutable genes enriched for energy metabolism. The identified biomarkers revealed longevity interventions, including KU0063794, which extended mouse lifespan and healthspan. Overall, this study uncovers universal and distinct strategies of lifespan regulation within and across species and provides tools for discovering longevity interventions.

Epigenomic Diversity in a Global Collection of Arabidopsis thaliana Accessions.

The epigenome orchestrates genome accessibility, functionality, and three-dimensional structure. Because epigenetic variation can impact transcription and thus phenotypes, it may contribute to adaptation. Here, we report 1,107 high-quality single-base resolution methylomes and 1,203 transcriptomes from the 1001 Genomes collection of Arabidopsis thaliana. Although the genetic basis of methylation variation is highly complex, geographic origin is a major predictor of genome-wide DNA methylation levels and of altered gene expression caused by epialleles. Comparison to cistrome and epicistrome datasets identifies associations between transcription factor binding sites, methylation, nucleotide variation, and co-expression modules. Physical maps for nine of the most diverse genomes reveal how transposons and other structural variants shape the epigenome, with dramatic effects on immunity genes. The 1001 Epigenomes Project provides a comprehensive resource for understanding how variation in DNA methylation contributes to molecular and non-molecular phenotypes in natural populations of the most studied model plant.

Nonalcoholic fatty liver disease risk and histologic severity are associated with genetic polymorphisms in children.

BACKGROUND AND AIMS: NAFLD is the most common chronic liver disease in children. Large pediatric studies identifying single nucleotide polymorphisms (SNPs) associated with risk and histologic severity of NAFLD are limited. Study aims included investigating SNPs associated with risk for NAFLD using family trios and association of candidate alleles with histologic severity. APPROACH AND RESULTS: Children with biopsy-confirmed NAFLD were enrolled from the NASH Clinical Research Network. The Expert Pathology Committee reviewed liver histology. Genotyping was conducted with allele-specific primers for 60 candidate SNPs. Parents were enrolled for trio analysis. To assess risk for NAFLD, the transmission disequilibrium test was conducted in trios. Among cases, regression analysis assessed associations with histologic severity. A total of 822 children with NAFLD had mean age 13.2 years (SD 2.7) and mean ALT 101 U/L (SD 90). PNPLA3 (rs738409) demonstrated the strongest risk ( p = 2.24 × 10 -14 ) for NAFLD. Among children with NAFLD, stratifying by PNPLA3 s738409 genotype, the variant genotype associated with steatosis ( p = 0.005), lobular ( p = 0.03) and portal inflammation ( p = 0.002). Steatosis grade associated with TM6SF2 ( p = 0.0009), GCKR ( p = 0.0032), PNPLA3 rs738409 ( p = 0.0053), and MTTP ( p = 0.0051). Fibrosis stage associated with PARVB rs6006473 ( p = 0.0001), NR1I2 ( p = 0.0021), ADIPOR2 ( p = 0.0038), and OXTR ( p = 0.0065). PNPLA3 rs738409 ( p = 0.0002) associated with borderline zone 1 NASH. CONCLUSIONS: This study demonstrated disease-associated SNPs in children with NAFLD. In particular, rs6006473 was highly associated with severity of fibrosis. These hypothesis-generating results support future mechanistic studies of development of adverse outcomes such as fibrosis and generation of therapeutic targets for NAFLD in children.

A time-series analysis of blood-based biomarkers within a 25-year longitudinal dolphin cohort.

Causal interactions and correlations between clinically-relevant biomarkers are important to understand, both for informing potential medical interventions as well as predicting the likely health trajectory of any individual as they age. These interactions and correlations can be hard to establish in humans, due to the difficulties of routine sampling and controlling for individual differences (e.g., diet, socio-economic status, medication). Because bottlenose dolphins are long-lived mammals that exhibit several age-related phenomena similar to humans, we analyzed data from a well controlled 25-year longitudinal cohort of 144 dolphins. The data from this study has been reported on earlier, and consists of 44 clinically relevant biomarkers. This time-series data exhibits three starkly different influences: (A) directed interactions between biomarkers, (B) sources of biological variation that can either correlate or decorrelate different biomarkers, and (C) random observation-noise which combines measurement error and very rapid fluctuations in the dolphin's biomarkers. Importantly, the sources of biological variation (type-B) are large in magnitude, often comparable to the observation errors (type-C) and larger than the effect of the directed interactions (type-A). Attempting to recover the type-A interactions without accounting for the type-B and type-C variation can result in an abundance of false-positives and false-negatives. Using a generalized regression which fits the longitudinal data with a linear model accounting for all three influences, we demonstrate that the dolphins exhibit many significant directed interactions (type-A), as well as strong correlated variation (type-B), between several pairs of biomarkers. Moreover, many of these interactions are associated with advanced age, suggesting that these interactions can be monitored and/or targeted to predict and potentially affect aging.

Soluble α-synuclein-antibody complexes activate the NLRP3 inflammasome in hiPSC-derived microglia.

Parkinson's disease is characterized by accumulation of α-synuclein (αSyn). Release of oligomeric/fibrillar αSyn from damaged neurons may potentiate neuronal death in part via microglial activation. Heretofore, it remained unknown if oligomeric/fibrillar αSyn could activate the nucleotide-binding oligomerization domain (NOD)-like receptor (NLR) family pyrin domain-containing 3 (NLRP3) inflammasome in human microglia and whether anti-αSyn antibodies could prevent this effect. Here, we show that αSyn activates the NLRP3 inflammasome in human induced pluripotent stem cell (hiPSC)-derived microglia (hiMG) via dual stimulation involving Toll-like receptor 2 (TLR2) engagement and mitochondrial damage. In vitro, hiMG can be activated by mutant (A53T) αSyn secreted from hiPSC-derived A9-dopaminergic neurons. Surprisingly, αSyn-antibody complexes enhanced rather than suppressed inflammasome-mediated interleukin-1ß (IL-1ß) secretion, indicating these complexes are neuroinflammatory in a human context. A further increase in inflammation was observed with addition of oligomerized amyloid-ß peptide (Aß) and its cognate antibody. In vivo, engraftment of hiMG with αSyn in humanized mouse brain resulted in caspase-1 activation and neurotoxicity, which was exacerbated by αSyn antibody. These findings may have important implications for antibody therapies aimed at depleting misfolded/aggregated proteins from the human brain, as they may paradoxically trigger inflammation in human microglia.

A 25-y longitudinal dolphin cohort supports that long-lived individuals in same environment exhibit variation in aging rates.

While it is believed that humans age at different rates, a lack of robust longitudinal human studies using consensus biomarkers meant to capture aging rates has hindered an understanding of the degree to which individuals vary in their rates of aging. Because bottlenose dolphins are long-lived mammals that develop comorbidities of aging similar to humans, we analyzed data from a well-controlled, 25-y longitudinal cohort of 144 US Navy dolphins housed in the same oceanic environment. Our analysis focused on 44 clinically relevant hematologic and clinical chemistry measures recorded during routine blood draws throughout the dolphins' lifetimes. Using stepwise regression and general linear models that accommodate correlations between measures obtained on individual dolphins, we demonstrate that, in a manner similar to humans, dolphins exhibit independent and linear age-related declines in four of these measures: hemoglobin, alkaline phosphatase, platelets, and lymphocytes. Using linear regressions and analyses of covariance with post hoc Tukey-Kramer tests to compare slopes (i.e., linear age-related rates) of our four aging rate biomarkers among 34 individual dolphins aging from 10 y to up to 40 y old, we could identify slow and accelerated agers and differentiate subgroups that were more or less likely to develop anemia and lymphopenia. This study successfully documents aging rate differences over the lifetime of long-lived individuals in a controlled environment. Our study suggests that nonenvironmental factors influencing aging rate biomarkers, including declining hemoglobin and anemia, may be targeted to delay the effects of aging in a compelling model of human biology.

signatureSearch: environment for gene expression signature searching and functional interpretation.

signatureSearch is an R/Bioconductor package that integrates a suite of existing and novel algorithms into an analysis environment for gene expression signature (GES) searching combined with functional enrichment analysis (FEA) and visualization methods to facilitate the interpretation of the search results. In a typical GES search (GESS), a query GES is searched against a database of GESs obtained from large numbers of measurements, such as different genetic backgrounds, disease states and drug perturbations. Database matches sharing correlated signatures with the query indicate related cellular responses frequently governed by connected mechanisms, such as drugs mimicking the expression responses of a disease. To identify which processes are predominantly modulated in the GESS results, we developed specialized FEA methods combined with drug-target network visualization tools. The provided analysis tools are useful for studying the effects of genetic, chemical and environmental perturbations on biological systems, as well as searching single cell GES databases to identify novel network connections or cell types. The signatureSearch software is unique in that it provides access to an integrated environment for GESS/FEA routines that includes several novel search and enrichment methods, efficient data structures, and access to pre-built GES databases, and allowing users to work with custom databases.

Hepatic PEMT Expression Decreases with Increasing NAFLD Severity.

Choline deficiency causes hepatic fat accumulation, and is associated with a higher risk of nonalcoholic fatty liver disease (NAFLD) and more advanced NAFLD-related hepatic fibrosis. Reduced expression of hepatic phosphatidylethanolamine N-methyltransferase (PEMT), which catalyzes the production of phosphatidylcholine, causes steatosis, inflammation, and fibrosis in mice. In humans, common PEMT variants impair phosphatidylcholine synthesis, and are associated with NAFLD risk. We investigated hepatic PEMT expression in a large cohort of patients representing the spectrum of NAFLD, and examined the relationship between PEMT genetic variants and gene expression. Hepatic PEMT expression was reduced in NAFLD patients with inflammation and fibrosis (i.e., nonalcoholic steatohepatitis or NASH) compared to participants with normal liver histology (ß = −1.497; p = 0.005). PEMT levels also declined with increasing severity of fibrosis with cirrhosis < incomplete cirrhosis < bridging fibrosis (ß = −1.185; p = 0.011). Hepatic PEMT expression was reduced in postmenopausal women with NASH compared to those with normal liver histology (ß = −3.698; p = 0.030). We detected a suggestive association between rs7946 and hepatic fibrosis (p = 0.083). Although none of the tested variants were associated with hepatic PEMT expression, computational fine mapping analysis indicated that rs4646385 may impact PEMT levels in the liver. Hepatic PEMT expression decreases with increasing severity of NAFLD in obese individuals and postmenopausal women, and may contribute to disease pathogenesis in a subset of NASH patients.

A Genome-Wide Association Study of 2304 Extreme Longevity Cases Identifies Novel Longevity Variants.

We performed a genome-wide association study (GWAS) of human extreme longevity (EL), defined as surviving past the 99th survival percentile, by aggregating data from four centenarian studies. The combined data included 2304 EL cases and 5879 controls. The analysis identified a locus in CDKN2B-AS1 (rs6475609, p = 7.13 × 10-8) that almost reached genome-wide significance and four additional loci that were suggestively significant. Among these, a novel rare variant (rs145265196) on chromosome 11 had much higher longevity allele frequencies in cases of Ashkenazi Jewish and Southern Italian ancestry compared to cases of other European ancestries. We also correlated EL-associated SNPs with serum proteins to link our findings to potential biological mechanisms that may be related to EL and are under genetic regulation. The findings from the proteomic analyses suggested that longevity-promoting alleles of significant genetic variants either provided EL cases with more youthful molecular profiles compared to controls or provided some form of protection from other illnesses, such as Alzheimer's disease, and disease progressions.

Comparison of phasing strategies for whole human genomes.

Humans are a diploid species that inherit one set of chromosomes paternally and one homologous set of chromosomes maternally. Unfortunately, most human sequencing initiatives ignore this fact in that they do not directly delineate the nucleotide content of the maternal and paternal copies of the 23 chromosomes individuals possess (i.e., they do not 'phase' the genome) often because of the costs and complexities of doing so. We compared 11 different widely-used approaches to phasing human genomes using the publicly available 'Genome-In-A-Bottle' (GIAB) phased version of the NA12878 genome as a gold standard. The phasing strategies we compared included laboratory-based assays that prepare DNA in unique ways to facilitate phasing as well as purely computational approaches that seek to reconstruct phase information from general sequencing reads and constructs or population-level haplotype frequency information obtained through a reference panel of haplotypes. To assess the performance of the 11 approaches, we used metrics that included, among others, switch error rates, haplotype block lengths, the proportion of fully phase-resolved genes, phasing accuracy and yield between pairs of SNVs. Our comparisons suggest that a hybrid or combined approach that leverages: 1. population-based phasing using the SHAPEIT software suite, 2. either genome-wide sequencing read data or parental genotypes, and 3. a large reference panel of variant and haplotype frequencies, provides a fast and efficient way to produce highly accurate phase-resolved individual human genomes. We found that for population-based approaches, phasing performance is enhanced with the addition of genome-wide read data; e.g., whole genome shotgun and/or RNA sequencing reads. Further, we found that the inclusion of parental genotype data within a population-based phasing strategy can provide as much as a ten-fold reduction in phasing errors. We also considered a majority voting scheme for the construction of a consensus haplotype combining multiple predictions for enhanced performance and site coverage. Finally, we also identified DNA sequence signatures associated with the genomic regions harboring phasing switch errors, which included regions of low polymorphism or SNV density.

Rare variant phasing using paired tumor:normal sequence data.

BACKGROUND: In standard high throughput sequencing analysis, genetic variants are not assigned to a homologous chromosome of origin. This process, called haplotype phasing, can reveal information important for understanding the relationship between genetic variants and biological phenotypes. For example, in genes that carry multiple heterozygous missense variants, phasing resolves whether one or both gene copies are altered. Here, we present a novel approach to phasing variants that takes advantage of unique properties of paired tumor:normal sequencing data from cancer studies. RESULTS: VAF phasing uses changes in variant allele frequency (VAF) between tumor and normal samples in regions of somatic chromosomal gain or loss to phase germline variants. We apply VAF phasing to 6180 samples from the Cancer Genome Atlas (TCGA) and demonstrate that our method is highly concordant with other standard phasing methods, and can phase an average of 33% more variants than other read-backed phasing methods. Using variant annotation tools designed to score gene haplotypes, we find a suggestive association between carrying multiple missense variants in a single copy of a cancer predisposition gene and earlier age of cancer diagnosis. CONCLUSIONS: VAF phasing exploits unique properties of tumor genomes to increase the number of germline variants that can be phased over standard read-backed methods in paired tumor:normal samples. Our phase-informed association testing results call attention to the need to develop more tools for assessing the joint effect of multiple genetic variants.

Identification of novel loci affecting circulating chromogranins and related peptides.

Chromogranins are pro-hormone secretory proteins released from neuroendocrine cells, with effects on control of blood pressure. We conducted a genome-wide association study for plasma catestatin, the catecholamine release inhibitory peptide derived from chromogranin A (CHGA), and other CHGA- or chromogranin B (CHGB)-related peptides, in 545 US and 1252 Australian subjects. This identified loci on chromosomes 4q35 and 5q34 affecting catestatin concentration (P = 3.40 × 10-30 for rs4253311 and 1.85 × 10-19 for rs2731672, respectively). Genes in these regions include the proteolytic enzymes kallikrein (KLKB1) and Factor XII (F12). In chromaffin cells, CHGA and KLKB1 proteins co-localized in catecholamine storage granules. In vitro, kallikrein cleaved recombinant human CHGA to catestatin, verified by mass spectrometry. The peptide identified from this digestion (CHGA360-373) selectively inhibited nicotinic cholinergic stimulated catecholamine release from chromaffin cells. A proteolytic cascade involving kallikrein and Factor XII cleaves chromogranins to active compounds both in vivo and in vitro.

Link between gut-microbiome derived metabolite and shared gene-effects with hepatic steatosis and fibrosis in NAFLD.

Previous studies have shown that gut-microbiome is associated with nonalcoholic fatty liver disease (NAFLD). We aimed to examine if serum metabolites, especially those derived from the gut-microbiome, have a shared gene-effect with hepatic steatosis and fibrosis. This is a cross-sectional analysis of a prospective discovery cohort including 156 well-characterized twins and families with untargeted metabolome profiling assessment. Hepatic steatosis was assessed using magnetic-resonance-imaging proton-density-fat-fraction (MRI-PDFF) and fibrosis using MR-elastography (MRE). A twin additive genetics and unique environment effects (AE) model was used to estimate the shared gene-effect between metabolites and hepatic steatosis and fibrosis. The findings were validated in an independent prospective validation cohort of 156 participants with biopsy-proven NAFLD including shotgun metagenomics sequencing assessment in a subgroup of the cohort. In the discovery cohort, 56 metabolites including 6 microbial metabolites had a significant shared gene-effect with both hepatic steatosis and fibrosis after adjustment for age, sex and ethnicity. In the validation cohort, 6 metabolites were associated with advanced fibrosis. Among them, only one microbial metabolite, 3-(4-hydroxyphenyl)lactate, remained consistent and statistically significantly associated with liver fibrosis in the discovery and validation cohort (fold-change of higher-MRE versus lower-MRE: 1.78, P < 0.001 and of advanced versus no advanced fibrosis: 1.26, P = 0.037, respectively). The share genetic determination of 3-(4-hydroxyphenyl)lactate with hepatic steatosis was RG :0.57,95%CI:0.27-0.80, P < 0.001 and with fibrosis was RG :0.54,95%CI:0.036-1, P = 0.036. Pathway reconstruction linked 3-(4-hydroxyphenyl)lactate to several human gut-microbiome species. In the validation cohort, 3-(4-hydroxyphenyl)lactate was significantly correlated with the abundance of several gut-microbiome species, belonging only to Firmicutes, Bacteroidetes and Proteobacteria phyla, previously reported as associated with advanced fibrosis. Conclusion: This proof of concept study provides evidence of a link between the gut-microbiome and 3-(4-hydroxyphenyl)lactate that shares gene-effect with hepatic steatosis and fibrosis. (Hepatology 2018).

A loop-counting method for covariate-corrected low-rank biclustering of gene-expression and genome-wide association study data.

A common goal in data-analysis is to sift through a large data-matrix and detect any significant submatrices (i.e., biclusters) that have a low numerical rank. We present a simple algorithm for tackling this biclustering problem. Our algorithm accumulates information about 2-by-2 submatrices (i.e., 'loops') within the data-matrix, and focuses on rows and columns of the data-matrix that participate in an abundance of low-rank loops. We demonstrate, through analysis and numerical-experiments, that this loop-counting method performs well in a variety of scenarios, outperforming simple spectral methods in many situations of interest. Another important feature of our method is that it can easily be modified to account for aspects of experimental design which commonly arise in practice. For example, our algorithm can be modified to correct for controls, categorical- and continuous-covariates, as well as sparsity within the data. We demonstrate these practical features with two examples; the first drawn from gene-expression analysis and the second drawn from a much larger genome-wide-association-study (GWAS).

Artificial Intelligence and Personalized Medicine.

The development of high-throughput, data-intensive biomedical research assays and technologies has created a need for researchers to develop strategies for analyzing, integrating, and interpreting the massive amounts of data they generate. Although a wide variety of statistical methods have been designed to accommodate 'big data,'  experiences with the use of artificial intelligence (AI) techniques suggest that they might be particularly appropriate. In addition,  the results of the application of these assays reveal a great heterogeneity in the pathophysiologic factors and processes that contribute to disease, suggesting that there is a need to tailor, or 'personalize,' medicines to the nuanced and often unique features possessed by individual patients. Given how important data-intensive assays are to revealing appropriate intervention targets and strategies for  treating an individual with a disease, AI can play an important role in the development of personalized medicines. We describe many areas where AI can play such a role and argue that AI's ability to advance personalized medicine will depend critically on not only the refinement of relevant assays, but also on ways of storing, aggregating, accessing, and ultimately integrating, the data they produce. We also point out the limitations of many AI techniques in developing personalized medicines as well as consider areas for further research.

Patterns of population epigenomic diversity.

Natural epigenetic variation provides a source for the generation of phenotypic diversity, but to understand its contribution to such diversity, its interaction with genetic variation requires further investigation. Here we report population-wide DNA sequencing of genomes, transcriptomes and methylomes of wild Arabidopsis thaliana accessions. Single cytosine methylation polymorphisms are not linked to genotype. However, the rate of linkage disequilibrium decay amongst differentially methylated regions targeted by RNA-directed DNA methylation is similar to the rate for single nucleotide polymorphisms. Association analyses of these RNA-directed DNA methylation regions with genetic variants identified thousands of methylation quantitative trait loci, which revealed the population estimate of genetically dependent methylation variation. Analysis of invariably methylated transposons and genes across this population indicates that loci targeted by RNA-directed DNA methylation are epigenetically activated in pollen and seeds, which facilitates proper development of these structures.

An investigation of indirect effects of personality features on anorexia nervosa severity through interoceptive dysfunction in individuals with lifetime anorexia nervosa diagnoses.

OBJECTIVE: This study examined a hypothesized pathway by which interoceptive dysfunction accounted for associations between personality features (harm avoidance, self-directedness, and perfectionism) and anorexia nervosa (AN) severity (indicated by drive for thinness, eating disorder-related preoccupations and rituals, and body mass index). METHOD: The study sample (n = 270, mean age = 28.47, 95.2% female, 98% White/Caucasian) consisted of probands and biological relatives who met DSM-IV criteria for lifetime diagnoses of AN (omitting criterion D, amenorrhea) drawn from the Price Foundation Anorexia Nervosa Affected Relative Pairs Study (AN-ARP). Participants completed measures assessing personality, interoceptive dysfunction, and eating pathology. RESULTS: Associations between personality features of low self-directedness and high perfectionism and indicators of AN severity (drive for thinness and eating disorder-related preoccupations and rituals) were significant, as were the hypothesized indirect pathways through interoceptive dysfunction. Neither harm avoidance nor body mass index was significantly related to other study variables, and the proposed indirect pathways involving these variables were not significant. DISCUSSION: Findings suggest that certain personality features may relate to AN severity, in part, through their associations with interoceptive dysfunction. Future research should examine prospective associations and the value of interventions targeting interoceptive dysfunction for interrupting the link between personality and AN severity.

p53-Dependent DNA damage response sensitive to editing-defective tRNA synthetase in zebrafish.

Brain and heart pathologies are caused by editing defects of transfer RNA (tRNA) synthetases, which preserve genetic code fidelity by removing incorrect amino acids misattached to tRNAs. To extend understanding of the broader impact of synthetase editing reactions on organismal homeostasis, and based on effects in bacteria ostensibly from small amounts of mistranslation of components of the replication apparatus, we investigated the sensitivity to editing of the vertebrate genome. We show here that in zebrafish embryos, transient overexpression of editing-defective valyl-tRNA synthetase (ValRS(ED)) activated DNA break-responsive H2AX and p53-responsive downstream proteins, such as cyclin-dependent kinase (CDK) inhibitor p21, which promotes cell-cycle arrest at DNA damage checkpoints, and Gadd45 and p53R2, with pivotal roles in DNA repair. In contrast, the response of these proteins to expression of ValRS(ED) was abolished in p53-deficient fish. The p53-activated downstream signaling events correlated with suppression of abnormal morphological changes caused by the editing defect and, in adults, reversed a shortened life span (followed for 2 y). Conversely, with normal editing activities, p53-deficient fish have a normal life span and few morphological changes. Whole-fish deep sequencing showed genomic mutations associated with the editing defect. We suggest that the sensitivity of p53 to expression of an editing-defective tRNA synthetase has a critical role in promoting genome integrity and organismal homeostasis.

Conservation of Distinct Genetically-Mediated Human Cortical Pattern.

The many subcomponents of the human cortex are known to follow an anatomical pattern and functional relationship that appears to be highly conserved between individuals. This suggests that this pattern and the relationship among cortical regions are important for cortical function and likely shaped by genetic factors, although the degree to which genetic factors contribute to this pattern is unknown. We assessed the genetic relationships among 12 cortical surface areas using brain images and genotype information on 2,364 unrelated individuals, brain images on 466 twin pairs, and transcriptome data on 6 postmortem brains in order to determine whether a consistent and biologically meaningful pattern could be identified from these very different data sets. We find that the patterns revealed by each data set are highly consistent (p<10-3), and are biologically meaningful on several fronts. For example, close genetic relationships are seen in cortical regions within the same lobes and, the frontal lobe, a region showing great evolutionary expansion and functional complexity, has the most distant genetic relationship with other lobes. The frontal lobe also exhibits the most distinct expression pattern relative to the other regions, implicating a number of genes with known functions mediating immune and related processes. Our analyses reflect one of the first attempts to provide an assessment of the biological consistency of a genetic phenomenon involving the brain that leverages very different types of data, and therefore is not just statistical replication which purposefully use very similar data sets.

Mission critical: the need for proteomics in the era of next-generation sequencing and precision medicine.

Next generation sequencing (NGS) has ignited an unprecedented pace of discovery in the biomedical sciences that is fundamentally transforming the way that we understand, diagnose and treat disease, and has motivated the belief that true precision medicine - medicine that is tailored to an individual's genetic, biochemical and exposure profile - will be a reality in the near term. With minimal sample requirement, NGS can enable the concurrent genome-wide study of genetic variations, transcriptomes, and certain epigenetic modifications. However, interrogating proteins as efficiently as DNA and RNA can be interrogated with NGS is lacking and this hampers more comprehensive views of molecular physiology and limits advances in biomedical science and precision medicine. The fact is that innovations in proteomic technologies pale in comparison to the advances in NGS, with current methodologies suffering from issues related to reproducibility, sensitivity, sample requirements, and limited multiplexing capacity. The development of proteomic technologies to overcome these limitations would fill the void in systems biology research, catalyze clinical innovations, and expedite the realization of precision medicine.