The effects of death and post-mortem cold ischemia on human tissue transcriptomes

Histologic and Quality Assessment of Genotype-Tissue Expression (GTEx) Research Samples: A Large Postmortem Tissue Collection

CONTEXT.—

The National Institutes of Health Genotype-Tissue Expression (GTEx) project was developed to elucidate how genetic variation influences gene expression in multiple normal tissues procured from postmortem donors.

OBJECTIVE.—

To provide critical insight into a biospecimen's suitability for subsequent analysis, each biospecimen underwent quality assessment measures that included evaluation for underlying disease and potential effects introduced by preanalytic factors.

DESIGN.—

Electronic images of each tissue collected from nearly 1000 postmortem donors were evaluated by board-certified pathologists for the extent of autolysis, tissue purity, and the type and abundance of any extraneous tissue. Tissue-specific differences in the severity of autolysis and RNA integrity were evaluated, as were potential relationships between these markers and the duration of postmortem interval and rapidity of death.

RESULTS.—

Tissue-specific challenges in the procurement and preservation of the nearly 30 000 tissue specimens collected during the GTEx project are summarized. Differences in the degree of autolysis and RNA integrity number were observed among the 40 tissue types evaluated, and tissue-specific susceptibilities to the duration of postmortem interval and rapidity of death were observed.

CONCLUSIONS.—

Ninety-five percent of tissues were of sufficient quality to support RNA sequencing analysis. Biospecimens, annotated whole slide images, de-identified clinical data, and genomic data generated for GTEx represent a high-quality and comprehensive resource for the scientific community that has contributed to its use in approximately 1695 articles. Biospecimens and data collected under the GTEx project are available via the GTEx portal and authorized access to the Database of Genotypes and Phenotypes; procedures and whole slide images are available from the National Cancer Institute.

Exploring transcriptomic signatures in sudden unexplained death (SUD) cases

BACKGROUND

Molecular autopsy in sudden unexplained death (SUD) has successfully identified pathogenic variants in cardiovascular genes in a substantial proportion of cases, contributing to prevention strategies in family members. However, many SUD cases remain genetically unresolved, prompting investigations into other omics technologies to better understand the pathogenic mechanisms leading to a sudden death event. In this study, whole transcriptome sequencing was performed on heart samples from 43 SUD cases and 17 heart-healthy controls, with the aim to identify disease-specific transcriptome signatures in sudden unexplained death.

RESULTS

PCA based on the top 500 genes with the highest variance among the samples showed no clear separation between SUD and controls or among the three SUD subgroups. DESeq2 identified 1,676 differentially expressed genes between SUD and controls with significantly upregulated genes involved in biological processes such as angiogenesis, blood vessel development, vasculogenesis and cell adhesion. Pathway analysis of the differentially expressed genes showed that most were downregulated and involved in amide/peptide biosynthesis and fatty acid metabolism. Additional analysis of SUD subgroups revealed unique gene expression patterns and highlighted differentially expressed genes within each subgroup.

CONCLUSION

Gene expression analysis of SUD heart tissue is a promising approach to identify cardiac disease-related pathways to further understand the pathological mechanisms leading to a sudden death event. However, due to the heterogeneity of the SUD cases and the unclear phenotype, further studies in larger cohorts are needed.

A multi-tissue longitudinal proteomics study to evaluate the suitability of post-mortem samples for pathophysiological research

Recent developments in mass spectrometry-based proteomics have established it as a robust tool for system-wide analyses essential for pathophysiological research. While post-mortem samples are a critical source for these studies, our understanding of how body decomposition influences the proteome remains limited. Here, we have revisited published data and conducted a clinically relevant time-course experiment in mice, revealing organ-specific proteome regulation after death, with only a fraction of these changes linked to protein autolysis. The liver and spleen exhibit significant proteomic alterations within hours post-mortem, whereas the heart displays only modest changes. Additionally, subcellular compartmentalization leads to an unexpected surge in proteome alterations at the earliest post-mortem interval (PMI). Additionally, we have conducted a comprehensive analysis of semi-tryptic peptides, revealing distinct consensus motifs for different organs, indicating organ-specific post-mortem protease activity. In conclusion, our findings emphasize the critical importance of considering PMI effects when designing proteomics studies, as these effects may significantly overshadow the impacts of diseases. Preferably, the samples should be taken in the operation room, especially for studies including subcellular compartmentalization or trans-organ comparison. In single-organ studies, the planning should involve careful control of PMI.

Hydroxyacyl-coenzyme A dehydrogenase: A biomarker for authentication of death from mechanical asphyxia

Death from mechanical asphyxia (DMA) refers to death from acute respiratory disorder caused by mechanical violence. Due to the absence of characteristic signs in corpses, it has been rather challenging to achieve the precise authentication of DMA. In this research, human pulmonary samples were collected and grouped according to different causes of death in search of potential biomarkers of DMA. Hydroxyacyl-CoA dehydrogenase (HADH) was identified significantly up-regulated in DMA group. Cell experiments were conducted to figure out the mechanism of the up-regulation of HADH. According to the results, we assumed acute and severe hypoxia caused by mechanical asphyxia contributed to the expression change of HADH, which could be a self-saving reaction of cells that are forced to adjust energy metabolism. Generally, HADH can be biomarker of DMA and help the precise authentication of DMA.

Interpretation of molecular autopsy findings in 45 sudden unexplained death cases: from coding region to untranslated region

Sudden unexplained death (SUD) can affect apparently healthy adolescents and young adults with no prior clinical symptoms and no clear diagnostic findings at autopsy. Although primary cardiac arrhythmias have been shown to be the direct cause of death in the majority of SUD cases, the genetic predisposition contributing to SUD remains incompletely understood. Currently, molecular autopsy is considered to be an effective diagnostic tool in the multidisciplinary management of SUD, but the analysis focuses mainly on the coding region and the significance of many identified variants remains unclear. Recent studies have demonstrated the strong association between human disease and genetic variants in untranslated regions (UTRs), highlighting the potential role of UTR variants in the genetic predisposition to SUD. In this study, we searched for UTR variants with likely functional effects in the exome data of 45 SUD cases. Among 244 genes associated with cardiac diseases, three candidate variants with high confidence of pathogenicity were identified in the UTRs of SCO2, CALM2 and TBX3 based on a rigorous filtering strategy. A functional assay further validated the effect of these candidate variants on gene transcriptional activity. In addition, the constraint metrics, intolerance indexes, and dosage sensitivity scores of genes affected by the candidate variants were considered when estimating the consequence of aberrant gene expression. In conclusion, our study presents a practical strategy for UTR variant prioritization and functional annotation, which could improve the interpretation of molecular autopsy findings in SUD cohorts.

Disentangling protein metabolic costs in human cells and tissues

While more data are becoming available on gene activity at different levels of biological organization, our understanding of the underlying biology remains incomplete. Here, we introduce a metabolic efficiency framework that considers highly expressed proteins (HEPs), their length, and biosynthetic costs in terms of the amino acids (AAs) they contain to address the observed balance of expression costs in cells, tissues, and cancer transformation. Notably, the combined set of HEPs in either cells or tissues shows an abundance of large and costly proteins, yet tissues compensate this with short HEPs comprised of economical AAs, indicating a stronger tendency toward mitigating costs. We additionally observe that short proteins are prevalent HEPs across individual cells and tissues, whereas long ones are more specific. Furthermore, the precise proportion of short, long, economical, or costly HEP classes indicates that particular cell types and tissues align more closely with the metabolic efficiency model, with some tissues displaying behavior akin to their constituent cells. Finally, tumors typically increase the production of short and low-cost HEPs compared with matched normal tissues, while genes that decrease their high expression levels in tumors often tend to be associated with high costs. Overall, the metabolic efficiency framework serves as a useful simplifying model for interpreting genome-wide expression data across scales.

Profiling cell identity and tissue architecture with single-cell and spatial transcriptomics

Single-cell transcriptomics has broadened our understanding of cellular diversity and gene expression dynamics in healthy and diseased tissues. Recently, spatial transcriptomics has emerged as a tool to contextualize single cells in multicellular neighbourhoods and to identify spatially recurrent phenotypes, or ecotypes. These technologies have generated vast datasets with targeted-transcriptome and whole-transcriptome profiles of hundreds to millions of cells. Such data have provided new insights into developmental hierarchies, cellular plasticity and diverse tissue microenvironments, and spurred a burst of innovation in computational methods for single-cell analysis. In this Review, we discuss recent advancements, ongoing challenges and prospects in identifying and characterizing cell states and multicellular neighbourhoods. We discuss recent progress in sample processing, data integration, identification of subtle cell states, trajectory modelling, deconvolution and spatial analysis. Furthermore, we discuss the increasing application of deep learning, including foundation models, in analysing single-cell and spatial transcriptomics data. Finally, we discuss recent applications of these tools in the fields of stem cell biology, immunology, and tumour biology, and the future of single-cell and spatial transcriptomics in biological research and its translation to the clinic.

Identification and validation of up-regulated TNFAIP6 in osteoarthritis with type 2 diabetes mellitus

Lines of evidence have indicated that type 2 diabetes mellitus (T2DM) is an independent risk factor for osteoarthritis (OA) progression. However, the study focused on the relationship between T2DM and OA at the transcriptional level remains empty. We downloaded OA- and T2DM-related bulk RNA-sequencing and single-cell RNA sequencing data from the Gene Expression Omnibus (GEO) dataset. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were performed to screen out hub genes between OA and T2DM, and functional enrichment was done. Single-cell sequencing analysis was further used to screen key genes on OA and T2DM datasets. Rat chondrocytes and human articular cartilage were used to validate biomarkers among OA and T2DM. Sixty-eight hub genes were obtained, which were mainly enriched in the inflammatory response. We found that the hub gene TNFAIP6 is not only closely related to OA and T2DM but also a marker of prehypertrophic chondrocytes, which are closely related to the progression of OA. TNFAIP6 was found to be significantly elevated in CD14 + monocytes in T2DM patients, and this group of cells can promote inflammation. Validation on rat chondrocytes and human cartilage showed that TNFAIP6 was highly expressed in OA and further increased in the presence of T2DM or high glucose. Our study identified several characteristic modules and hub genes in the pathogenesis of T2DM-induced OA, which may facilitate further investigation of its molecular mechanisms. Up-regulated TNFAIP6 may contribute to OA in patients with T2DM by the recruitment of pro-inflammatory CD14 + monocytes in the OA synovium, which provides a potential target for the diagnosis and treatment of T2DM-associated OA.

Differential Expression Analyses on Human Aortic Tissue Reveal Novel Genes and Pathways Associated With Abdominal Aortic Aneurysm Onset and Progression

BACKGROUND

Abdominal aortic aneurysms (AAAs) are focal dilatations of the abdominal aorta that expand progressively, increasing their risk of rupture. Rupture of an AAA is associated with high mortality rates, but the mechanisms underlying the initiation, expansion, and rupture of AAAs are not yet fully understood. We aimed to characterize the pathophysiology of AAAs and identify new genes associated with AAA initiation and progression.

METHODS AND RESULTS

This study used RNA sequencing data on 140 samples, becoming the largest RNA sequencing data set for differential expression studies of AAAs. We performed differential expression analyses and analyses of differential splicing between dilated and nondilated aortic tissue samples, and between AAAs of different diameters. We identified 3002 differentially expressed genes between AAAs and controls that were independent of ischemic time, 1425 of which were new. Additionally, 8 genes (EXTL3, ZFR, DUSP8, DISP1, USP33, VPS37C, ZNF784, RFX1) were differentially expressed between AAAs of varying diameters and between AAAs and control samples. Finally, 7 genes (SPP1, FHL1, GNAS, MORF4L2, HMGN1, ARL1, RNASE4) with differential splicing patterns were also differentially expressed genes between AAAs and controls, suggesting that splicing differences in these genes may contribute to the observed expression changes and disease development.

CONCLUSIONS

This study identifies new genes and splicing patterns associated with AAAs and validates previous relevant pathways on AAAs. These findings contribute to the understanding of the complex mechanisms underlying AAAs and may provide potential targets to limit AAA progression and mortality risk.

Time-dependent changes in genome-wide gene expression and post-transcriptional regulation across the post-death process in silkworm

Despite death marking the end of life, several gene expression and miRNA-mediated post-transcriptional regulation events may persist or be initiated. The silkworm (Bombyx mori) is a valuable model for exploring life processes, including death. In this study, we combined transcriptomics and miRNAomics analyses of young, old, and post-mortem silkworms across the entire process after death to unravel the dynamics of gene expression and miRNA-mediated post-transcriptional regulation. In total, 171 genes exhibited sustained differential expression in post-mortem silkworms compared to the pre-death state, which are primarily involved in nerve signalling, transport, and immune response. Post-mortem time-specific genes were associated with cell cycle regulation, thermogenesis, immunity, and zinc ion homeostasis. We found that the down-regulated expression of 36 genes related to transcription, epigenetic modification, and homeostasis resulted in a significant shift in global gene expression patterns at 2 h post-death. We also identified 5 mRNA-miRNA pairs (i.e. bmo-miR-2795-mhca, 2784-achi, 2762-oa1, 277-5p-creb, and 1000-tcb1) associated with stress hormone regulation, transcription activity, and signal transduction. The roles of these pairs were validated through in vivo experiments using miRNA mimics in silkworms. The findings provide valuable insights into the intricate mechanisms underlying the transcriptional and miRNA-mediated post-transcriptional regulation events in animals after death.

High expression of BBOX1 in paracancerous tissue is associated with poor prognosis in hepatocellular carcinoma patients

The molecular profile of paracancerous tissue has been reported to be prognostic for recurrence in patients with different cancers. This study investigated the clinical significance of the protein expression of gamma-butyrobetaine hydroxylase 1 (BBOX1) in tumor and paracancerous tissues of hepatocellular carcinoma (HCC) patients. This study assessed the role of BBOX1 mRNA in tumor and paracancerous tissues in HCC via bioinformatics analysis. The protein levels of BBOX1 in paired tumor and paracancerous tissues from 83 HCC patients were determined by immunohistochemistry. The associations among BBOX1 protein levels, clinicopathological characteristics and the survival probability of HCC patients were also analyzed. The results revealed that BBOX1 mRNA expression was significantly lower in HCC tissues than in noncancerous tissues. HCC patients with low BBOX1 mRNA expression had a significantly poorer overall survival than those with high BBOX1 expression did. Immunohistochemical analysis of BBOX1 protein expression further confirmed that its levels were markedly lower in HCC tissues than in paracancerous tissues. High BBOX1 expression in paracancerous tissues correlated with poor overall survival and disease-free survival in HCC patients. These findings suggest that the paracancerous BBOX1 expression might be a credible indicator for overall survival or disease-free survival in HCC patients.

Molecular mechanisms of lipid droplets-mitochondria coupling in obesity and metabolic syndrome: insights and pharmacological implications

Abnormal lipid accumulation is a fundamental contributor to obesity and metabolic disorders. Lipid droplets (LDs) and mitochondria (MT) serve as organelle chaperones in lipid metabolism and energy balance. LDs play a crucial role in lipid storage and mobilization, working in conjunction with MT to regulate lipid metabolism within the liver, brown adipose tissue, and skeletal muscle, thereby maintaining metabolic homeostasis. The novelty of our review is the comprehensive description of LD and MT interaction mechanisms. We also focus on the current drugs that target this metabolism, which provide novel approaches for obesity and related metabolism disorder treatment.

DNA methylation stability in cardiac tissues kept at different temperatures and time intervals

Investigating DNA methylation (DNAm) in cardiac tissues is vital for epigenetic research in cardiovascular diseases (CVDs). During cardiac surgery, biopsies may not be immediately stored due to a lack of human or technical resources at the collection site. Assessing DNAm stability in cardiac samples left in suboptimal conditions is crucial for applying DNAm analysis. We investigated the stability of DNAm in human cardiac tissues kept at 4 °C and 22 °C for periods of 1, 7, 14, and 28 days (exposed samples) using the Illumina Infinium MethylationEPIC v1.0 BeadChip Array. We observed high correlations between samples analysed immediately after tissue collection and exposed ones (R2 > 0.992). Methylation levels were measured as β-values and median absolute β-value differences (|∆β|) ranged from 0.0093 to 0.0119 in all exposed samples. Pairwise differentially methylated position (DMP) analysis revealed no DMPs under 4 °C (fridge temperature) exposure for up to 28 days and 22 °C (room temperature) exposure for one day, while 3,437, 6,918, and 3,824 DMPs were observed for 22 °C samples at 7, 14, and 28 days, respectively. This study provides insights into the stability of genome-wide DNAm, showing that cardiac tissue can be used for reliable DNAm analysis even when stored suboptimally after surgery.

Brain-body mitochondrial distribution patterns lack coherence and point to tissue-specific and individualized regulatory mechanisms

Energy transformation capacity is generally assumed to be a coherent individual trait driven by genetic and environmental factors. This predicts that some individuals should have high and others low mitochondrial oxidative phosphorylation (OxPhos) capacity across organ systems. Here, we test this assumption using multi-tissue molecular and enzymatic activities in mice and humans. Across up to 22 mouse tissues, neither mitochondrial OxPhos capacity nor mtDNA density were correlated between tissues (median r = -0.01-0.16), indicating that animals with high mitochondrial capacity in one tissue can have low capacity in other tissues. Similarly, the multi-tissue correlation structure of RNAseq-based indices of mitochondrial gene expression across 45 tissues from 948 women and men (GTEx) showed small to moderate coherence between only some tissues (regions of the same brain), but not between brain-body tissue pairs in the same person (median r = 0.01). Mitochondrial DNA copy number (mtDNAcn) also lacked coherence across organs and tissues. Mechanistically, tissue-specific differences in mitochondrial gene expression were attributable in part to i) tissue-specific activation of canonical energy sensing pathways including the transcriptional coactivator PGC-1 and the integrated stress response (ISR), and ii) proliferative activity across tissues. Finally, we identify subgroups of individuals with high mitochondrial gene expression in some tissues (e.g., heart) but low expression in others (e.g., skeletal muscle) who display different clinical phenotypic patterns. Taken together, these data raise the possibility that tissue-specific energy sensing pathways may contribute to the idiosyncratic mitochondrial distribution patterns associated with the inter-organ heterogeneity and phenotypic diversity among individuals.

Unraveling the Enigma of Organismal Death: Insights, Implications, and Unexplored Frontiers

Significant knowledge gaps exist regarding the responses of cells, tissues, and organs to organismal death. Examining the survival mechanisms influenced by metabolism and environment, this research has the potential to transform regenerative medicine, redefine legal death, and provide insights into life's physiological limits, paralleling inquiries in embryogenesis.

The Glycocalyx: The Importance of Sugar Coating the Blood-Brain Barrier

The endothelial glycocalyx (GCX), located on the luminal surface of vascular endothelial cells, is composed of glycoproteins, proteoglycans, and glycosaminoglycans. It plays a pivotal role in maintaining blood-brain barrier (BBB) integrity and vascular health within the central nervous system (CNS), influencing critical processes such as blood flow regulation, inflammation modulation, and vascular permeability. While the GCX is ubiquitously expressed on the surface of every cell in the body, the GCX at the BBB is highly specialized, with a distinct composition of glycans, physical structure, and surface charge when compared to GCX elsewhere in the body. There is evidence that the GCX at the BBB is disrupted and partially shed in many diseases that impact the CNS. Despite this, the GCX has yet to be a major focus of therapeutic targeting for CNS diseases. This review examines diverse model systems used in cerebrovascular GCX-related research, emphasizing the importance of selecting appropriate models to ensure clinical relevance and translational potential. This review aims to highlight the importance of the GCX in disease and how targeting the GCX at the BBB specifically may be an effective approach for brain specific targeting for therapeutics.

Quality and applicability of cadaveric donor eyes for molecular biology research: An Indian experience

PURPOSE

Human ocular tissue banking plays an important part in the advancement of translational research for identifying the molecular processes involved in disease etiology and pathogenesis. Timely obtaining a good-quality ocular tissue from a cadaveric donor is exceedingly difficult, especially in remote areas, with a variable transportation time (within 12-24 h), raising concerns about RNA quality and its subsequent applications. Therefore, we assessed the utility of retinal tissues from cadaver donor and enucleated eyes based on the RNA quality and gene expression by real-time polymerase chain reaction (PCR).

SETTINGS AND DESIGN

Prospective study.

METHODS

Retina tissues were separated from the donor/enucleated eyes received in the eye bank within 24 h of death (n = 15) and within an hour from OR (n = 3), respectively, and stored immediately at -80 degree. RNA was isolated using trizol, and the quantity and quality were assessed using Qubit and agarose gel electrophoresis, respectively. QPCR was performed for measuring the expression of different retinal-specific genes. The cellular viability of the retina was assessed by establishing explant primary cell cultures.

STATISTICAL ANALYSIS

The data were calculated as an average of normalised Ct values ± standard error of the mean.

RESULTS

RNA obtained from cadaveric tissues despite being partially degraded showed a uniform strong gene expression of several retinal-specific genes such as PAX6, RHO, TUBB3, CRX , and ALDH1L1 . The primary cultures established from cadaveric tissues showed viable cells.

CONCLUSION

The cadaver donor tissues collected within 24 hours of death can be effectively utilized for gene expression profiling.

CapTrap-seq: a platform-agnostic and quantitative approach for high-fidelity full-length RNA sequencing

Long-read RNA sequencing is essential to produce accurate and exhaustive annotation of eukaryotic genomes. Despite advancements in throughput and accuracy, achieving reliable end-to-end identification of RNA transcripts remains a challenge for long-read sequencing methods. To address this limitation, we develop CapTrap-seq, a cDNA library preparation method, which combines the Cap-trapping strategy with oligo(dT) priming to detect 5' capped, full-length transcripts. In our study, we evaluate the performance of CapTrap-seq alongside other widely used RNA-seq library preparation protocols in human and mouse tissues, employing both ONT and PacBio sequencing technologies. To explore the quantitative capabilities of CapTrap-seq and its accuracy in reconstructing full-length RNA molecules, we implement a capping strategy for synthetic RNA spike-in sequences that mimics the natural 5'cap formation. Our benchmarks, incorporating the Long-read RNA-seq Genome Annotation Assessment Project (LRGASP) data, demonstrate that CapTrap-seq is a competitive, platform-agnostic RNA library preparation method for generating full-length transcript sequences.

Divergent landscapes of A-to-I editing in postmortem and living human brain

Adenosine-to-inosine (A-to-I) editing is a prevalent post-transcriptional RNA modification within the brain. Yet, most research has relied on postmortem samples, assuming it is an accurate representation of RNA biology in the living brain. We challenge this assumption by comparing A-to-I editing between postmortem and living prefrontal cortical tissues. Major differences were found, with over 70,000 A-to-I sites showing higher editing levels in postmortem tissues. Increased A-to-I editing in postmortem tissues is linked to higher ADAR and ADARB1 expression, is more pronounced in non-neuronal cells, and indicative of postmortem activation of inflammation and hypoxia. Higher A-to-I editing in living tissues marks sites that are evolutionarily preserved, synaptic, developmentally timed, and disrupted in neurological conditions. Common genetic variants were also found to differentially affect A-to-I editing levels in living versus postmortem tissues. Collectively, these discoveries offer more nuanced and accurate insights into the regulatory mechanisms of RNA editing in the human brain.

Exploring the Molecular Mechanism of Comorbidity of Type 2 Diabetes Mellitus and Colorectal Cancer: Insights from Bulk Omics and Single-Cell Sequencing Validation

The relationship between type 2 diabetes mellitus (T2DM) and colorectal cancer (CRC) has long been extensively recognized, but their crosstalk mechanisms based on gene regulation remain elusive. In our study, for the first time, bulk RNA-seq and single-cell RNA-seq data were used to explore the shared molecular mechanisms between T2DM and CRC. Moreover, Connectivity Map and molecular docking were employed to determine potential drugs targeting the candidate targets. Eight genes (EVPL, TACSTD2, SOX4, ETV4, LY6E, MLXIPL, ENTPD3, UGP2) were identified as characteristic comorbidity genes for T2DM and CRC, with EVPL and ENTPD3 further identified as core comorbidity genes. Our results demonstrated that upregulation of EVPL and downregulation of ENTPD3 were intrinsic molecular features throughout T2DM and CRC and were significantly associated with immune responses, immune processes, and abnormal immune landscapes in both diseases. Single-cell analysis highlighted a cancer-associated fibroblast (CAF) subset that specifically expressed ENTPD3 in CRC, which exhibited high heterogeneity and unique tumor-suppressive features that were completely different from classical cancer-promoting CAFs. Furthermore, ENTPD3+ CAFs could notably predict immunotherapy response in CRC, holding promise to be an immunotherapy biomarker at the single-cell level. Finally, we identified that droperidol may be a novel drug simultaneously targeting EVPL and ENTPD3. In conclusion, previous studies have often focused solely on metabolic alterations common to T2DM and CRC. Our study establishes EVPL and ENTPD3 as characteristic molecules and immune biomarkers of comorbidity in T2DM and CRC patients, and emphasizes the importance of considering immunological mechanisms in the co-development of T2DM and CRC.

Patterns of Unwanted Biological and Technical Expression Variation Among 49 Human Tissues

Tissue gene expression studies are impacted by biological and technical sources of variation, which can be broadly classified into wanted and unwanted variation. The latter, if not addressed, results in misleading biological conclusions. Methods have been proposed to reduce unwanted variation, such as normalization and batch correction. A more accurate understanding of all causes of variation could significantly improve the ability of these methods to remove unwanted variation while retaining variation corresponding to the biological question of interest. We used 17,282 samples from 49 human tissues in the Genotype-Tissue Expression data set (v8) to investigate patterns and causes of expression variation. Transcript expression was transformed to z-scores, and only the most variable 2% of transcripts were evaluated and clustered based on coexpression patterns. Clustered gene sets were assigned to different biological or technical causes based on histologic appearances and metadata elements. We identified 522 variable transcript clusters (median: 11 per tissue) among the samples. Of these, 63% were confidently explained, 16% were likely explained, 7% were low confidence explanations, and 14% had no clear cause. Histologic analysis annotated 46 clusters. Other common causes of variability included sex, sequencing contamination, immunoglobulin diversity, and compositional tissue differences. Less common biological causes included death interval (Hardy score), disease status, and age. Technical causes included blood draw timing and harvesting differences. Many of the causes of variation in bulk tissue expression were identifiable in the Tabula Sapiens data set of single-cell expression. This is among the largest explorations of the underlying sources of tissue expression variation. It uncovered expected and unexpected causes of variable gene expression and demonstrated the utility of matched histologic specimens. It further demonstrated the value of acquiring meaningful tissue harvesting metadata elements to use for improved normalization, batch correction, and analysis of both bulk and single-cell RNA-seq data.

Divergent landscapes of A-to-I editing in postmortem and living human brain

Adenosine-to-inosine (A-to-I) editing is a prevalent post-transcriptional RNA modification within the brain. Yet, most research has relied on postmortem samples, assuming it is an accurate representation of RNA biology in the living brain. We challenge this assumption by comparing A-to-I editing between postmortem and living prefrontal cortical tissues. Major differences were found, with over 70,000 A-to-I sites showing higher editing levels in postmortem tissues. Increased A-to-I editing in postmortem tissues is linked to higher ADAR1 and ADARB1 expression, is more pronounced in non-neuronal cells, and indicative of postmortem activation of inflammation and hypoxia. Higher A-to-I editing in living tissues marks sites that are evolutionarily preserved, synaptic, developmentally timed, and disrupted in neurological conditions. Common genetic variants were also found to differentially affect A-to-I editing levels in living versus postmortem tissues. Collectively, these discoveries illuminate the nuanced functions and intricate regulatory mechanisms of RNA editing within the human brain.

A computational approach to estimate postmortem interval using postmortem computed tomography of multiple tissues based on animal experiments

The estimation of postmortem interval (PMI) is a complex and challenging problem in forensic medicine. In recent years, many studies have begun to use machine learning methods to estimate PMI. However, research combining postmortem computed tomography (PMCT) with machine learning models for PMI estimation is still in early stages. This study aims to establish a multi-tissue machine learning model for PMI estimation using PMCT data from various tissues. We collected PMCT data of seven tissues, including brain, eyeballs, myocardium, liver, kidneys, erector spinae, and quadriceps femoris from 10 rabbits after death. CT images were taken every 12 h until 192 h after death, and HU values were extracted from the CT images of each tissue as a dataset. Support vector machine, random forest, and K-nearest neighbors were performed to establish PMI estimation models, and after adjusting the parameters of each model, they were used as first-level classification to build a stacking model to further improve the PMI estimation accuracy. The accuracy and generalized area under the receiver operating characteristic curve of the multi-tissue stacking model were able to reach 93% and 0.96, respectively. Results indicated that PMCT detection could be used to obtain postmortem change of different tissue densities, and the stacking model demonstrated strong predictive and generalization abilities. This approach provides new research methods and ideas for the study of PMI estimation.

Cellular energy regulates mRNA degradation in a codon-specific manner

Codon optimality is a major determinant of mRNA translation and degradation rates. However, whether and through which mechanisms its effects are regulated remains poorly understood. Here we show that codon optimality associates with up to 2-fold change in mRNA stability variations between human tissues, and that its effect is attenuated in tissues with high energy metabolism and amplifies with age. Mathematical modeling and perturbation data through oxygen deprivation and ATP synthesis inhibition reveal that cellular energy variations non-uniformly alter the effect of codon usage. This new mode of codon effect regulation, independent of tRNA regulation, provides a fundamental mechanistic link between cellular energy metabolism and eukaryotic gene expression.

Evidence of a pan-tissue decline in stemness during human aging

Despite their biological importance, the role of stem cells in human aging remains to be elucidated. In this work, we applied a machine learning methodology to GTEx transcriptome data and assigned stemness scores to 17,382 healthy samples from 30 human tissues aged between 20 and 79 years. We found that ~60% of the studied tissues exhibit a significant negative correlation between the subject's age and stemness score. The only significant exception was the uterus, where we observed an increased stemness with age. Moreover, we observed that stemness is positively correlated with cell proliferation and negatively correlated with cellular senescence. Finally, we also observed a trend that hematopoietic stem cells derived from older individuals might have higher stemness scores. In conclusion, we assigned stemness scores to human samples and show evidence of a pan-tissue loss of stemness during human aging, which adds weight to the idea that stem cell deterioration may contribute to human aging.

Immunohistochemical expression of HMGB1 and related proteins in the skin as a possible tool for determining post-mortem interval: a preclinical study

Determining the post-mortem interval (PMI) is one of forensic pathology's primary objectives and one of its most challenging tasks. Numerous studies have demonstrated the accuracy of histomorphology and immunohistochemical investigations in determining the time of death. Nevertheless, the skin, a robust and easy-to-remove tissue, has only been partially analyzed so far. By studying 20 adult male mice, we tried to determine whether post-mortem immunohistochemical detection in the skin of HMGB1 proteins and associated components (Beclin1 and RAGE) could be used for this purpose. We discovered that nuclear HMGB1 overexpression indicates that death occurred within the previous 12 h, nuclear HMGB1 negativization with high cytoplasmic HMGB1 intensity indicates that death occurred between 12 and 36 h earlier and cytoplasmic HMGB1 negativization indicates that more than 48 h have passed since death. RAGE and Beclin1 levels in the cytoplasm also decreased with time. The latter proteins' negativization might indicate that more than 24 and 36 h, respectively, have passed from the time of death. These indicators might potentially be helpful in forensic practice for determining the PMI using immunohistochemistry.

Postmortem Minimally Invasive Autopsy in Critically Ill COVID-19 Patients at the Bedside: A Proof-of-Concept Study at the ICU

BACKGROUND

Economic restrictions and workforce cuts have continually challenged conventional autopsies. Recently, the COVID-19 pandemic has added tissue quality and safety requirements to the investigation of this disease, thereby launching efforts to upgrade autopsy strategies.

METHODS

In this proof-of-concept study, we performed bedside ultrasound-guided minimally invasive autopsy (US-MIA) in the ICU of critically ill COVID-19 patients using a structured protocol to obtain non-autolyzed tissue. Biopsies were assessed for their quality (vitality) and length of biopsy (mm) and for diagnosis. The efficiency of the procedure was monitored in five cases by recording the time of each step and safety issues by swabbing personal protective equipment and devices for viral contamination.

FINDINGS

Ultrasound examination and tissue procurement required a mean time period of 13 min and 54 min, respectively. A total of 318 multiorgan biopsies were obtained from five patients. Quality and vitality standards were fulfilled, which not only allowed for specific histopathological diagnosis but also the reliable detection of SARS-CoV-2 virions in unexpected organs using electronic microscopy and RNA-expressing techniques.

INTERPRETATION

Bedside multidisciplinary US-MIA allows for the fast and efficient acquisition of autolytic-free tissue and offers unappreciated potential to overcome the limitations of research in postmortem studies.

Obesity and diabetes mellitus are associated with SARS-CoV-2 outcomes without influencing signature genes of extrapulmonary immune compartments at the RNA level

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which is responsible for eliciting Coronavirus disease 2019 (COVID-19) still challenges healthcare services worldwide. While many patients only suffer from mild symptoms, patients with some pre-existing medical conditions are at a higher risk for a detrimental course of disease. However, the underlying mechanisms determining disease course are only partially understood. One key factor influencing disease severity is described to be immune-mediated. In this report, we describe a post-mortem analysis of 45 individuals who died from SARS-CoV-2 infection. We could show that although sociodemographic factors and premedical conditions such as obesity and diabetes mellitus reduced survival time in our cohort, they were not associated with changes in the expression of immune-related signature genes at the RNA level in the blood, the gut, or the liver between these different groups. Our data indicate that obesity and diabetes mellitus influence SARS-CoV-2-related mortality, without influencing the extrapulmonary gene expression of immunity-related signature genes at the RNA level.

Transcription readthrough is prevalent in healthy human tissues and associated with inherent genomic features

Transcription termination is a crucial step in the production of conforming mRNAs and functional proteins. Under cellular stress conditions, the transcription machinery fails to identify the termination site and continues transcribing beyond gene boundaries, a phenomenon designated as transcription readthrough. However, the prevalence and impact of this phenomenon in healthy human tissues remain unexplored. Here, we assessed transcription readthrough in almost 3000 transcriptome profiles representing 23 human tissues and found that 34% of the expressed protein-coding genes produced readthrough transcripts. The production of readthrough transcripts was restricted in genomic regions with high transcriptional activity and was associated with inefficient splicing and increased chromatin accessibility in terminal regions. In addition, we showed that these transcripts contained several binding sites for the same miRNA, unravelling a potential role as miRNA sponges. Overall, this work provides evidence that transcription readthrough is pervasive and non-stochastic, not only in abnormal conditions but also in healthy tissues. This suggests a potential role for such transcripts in modulating normal cellular functions.

Complexity of human death: its physiological, transcriptomic, and microbiological implications

Human death is a complex, time-governed phenomenon that leads to the irreversible cessation of all bodily functions. Recent molecular and genetic studies have revealed remarkable experimental evidence of genetically programmed cellular death characterized by several physiological processes; however, the basic physiological function that occurs during the immediate postmortem period remains inadequately described. There is a paucity of knowledge connecting necrotic pathologies occurring in human organ tissues to complete functional loss of the human organism. Cells, tissues, organs, and organ systems show a range of differential resilience and endurance responses that occur during organismal death. Intriguingly, a persistent ambiguity in the study of postmortem physiological systems is the determination of the trajectory of a complex multicellular human body, far from life-sustaining homeostasis, following the gradual or sudden expiry of its regulatory systems. Recent groundbreaking investigations have resulted in a paradigm shift in understanding the cell biology and physiology of death. Two significant findings are that (i) most cells in the human body are microbial, and (ii) microbial cell abundance significantly increases after death. By addressing the physiological as well as the microbiological aspects of death, future investigations are poised to reveal innovative insights into the enigmatic biological activities associated with death and human decomposition. Understanding the elaborate crosstalk of abiotic and biotic factors in the context of death has implications for scientific discoveries important to informing translational knowledge regarding the transition from living to the non-living. There are important and practical needs for a transformative reestablishment of accepted models of biological death (i.e., artificial intelligence, AI) for more precise determinations of when the regulatory mechanisms for homeostasis of a living individual have ceased. In this review, we summarize mechanisms of physiological, genetic, and microbiological processes that define the biological changes and pathways associated with human organismal death and decomposition.

Novel method for collecting hippocampal interstitial fluid extracellular vesicles (EVISF ) reveals sex-dependent changes in microglial EV proteome in response to Aβ pathology

Brain-derived extracellular vesicles (EVs) play an active role in Alzheimer's disease (AD), relaying important physiological information about their host tissues. The internal cargo of EVs is protected from degradation, making EVs attractive AD biomarkers. However, it is unclear how circulating EVs relate to EVs isolated from disease-vulnerable brain regions. We developed a novel method for collecting EVs from the hippocampal interstitial fluid (ISF) of live mice. EVs (EVISF ) were isolated via ultracentrifugation and characterized by nanoparticle tracking analysis, immunogold labelling, and flow cytometry. Mass spectrometry and proteomic analyses were performed on EVISF cargo. EVISF were 40-150 nm in size and expressed CD63, CD9, and CD81. Using a model of cerebral amyloidosis (e.g., APPswe, PSEN1dE9 mice), we found protein concentration increased but protein diversity decreased with Aβ deposition. Genotype, age, and Aβ deposition modulated proteostasis- and immunometabolic-related pathways. Changes in the microglial EVISF proteome were sexually dimorphic and associated with a differential response of plaque associated microglia. We found that female APP/PS1 mice have more amyloid plaques, less plaque associated microglia, and a less robust- and diverse- EVISF microglial proteome. Thus, in vivo microdialysis is a novel technique for collecting EVISF and offers a unique opportunity to explore the role of EVs in AD.

[Interdisciplinary ultrasound-guided, minimally invasive autopsy in COVID-19-deceased patients in the intensive care unit of a university hospital : A proof-of-concept study]

In this feasibility study, we carried out in an interdisciplinary team standardised, ultrasound-guided, minimally invasive autopsy (US-MIA) directly at the bedside of patients who died of COVID-19 in the intensive care unit of the Rechts der Isar Hospital of the Technical University Munich (TUM). The aim of the study was to verify the feasibility, time efficiency and infection hygiene aspects of the process, as well as the quality of the tissue samples. Our results show that bedside US-MIA is suitable for obtaining tissue samples before the onset of postmortem autolysis, and that it can also be carried out quickly and safely. The potential of US-MIA, which has gained little recognition so far, deserves special attention in the context of postmortem diagnosis, research and quality assurance. In the future, these strengths of US-MIA could help to lead postmortem diagnosis into the modern age of pathological deep analytics ("omics").

Comparison of gene expression in living and postmortem human brain

Molecular mechanisms of neuropsychiatric disorders are challenging to study in human brain. For decades, the preferred model has been to study postmortem human brain samples despite the limitations they entail. A recent study generated RNA sequencing data from biopsies of prefrontal cortex from living patients with Parkinson's Disease and compared gene expression to postmortem tissue samples, from which they found vast differences between the two. This led the authors to question the utility of postmortem human brain studies. Through re-analysis of the same data, we unexpectedly found that the living brain tissue samples were of much lower quality than the postmortem samples across multiple standard metrics. We also performed simulations that illustrate the effects of ignoring RNA degradation in differential gene expression analyses, showing the effects can be substantial and of similar magnitude to what the authors find. For these reasons, we believe the authors' conclusions are unjustified. To the contrary, while opportunities to study gene expression in the living brain are welcome, evidence that this eclipses the value of postmortem analyses is not apparent.

Metabolomics investigation of post-mortem human pericardial fluid

INTRODUCTION

Due to its peculiar anatomy and physiology, the pericardial fluid is a biological matrix of particular interest in the forensic field. Despite this, the available literature has mainly focused on post-mortem biochemistry and forensic toxicology, while to the best of authors' knowledge post-mortem metabolomics has never been applied. Similarly, estimation of the time since death or post-mortem interval based on pericardial fluids has still rarely been attempted.

OBJECTIVES

We applied a metabolomic approach based on 1H nuclear magnetic resonance spectroscopy to ascertain the feasibility of monitoring post-mortem metabolite changes on human pericardial fluids with the aim of building a multivariate regression model for post-mortem interval estimation.

METHODS

Pericardial fluid samples were collected in 24 consecutive judicial autopsies, in a time frame ranging from 16 to 170 h after death. The only exclusion criterion was the quantitative and/or qualitative alteration of the sample. Two different extraction protocols were applied for low molecular weight metabolites selection, namely ultrafiltration and liquid-liquid extraction. Our metabolomic approach was based on the use of 1H nuclear magnetic resonance and multivariate statistical data analysis.

RESULTS

The pericardial fluid samples treated with the two experimental protocols did not show significant differences in the distribution of the metabolites detected. A post-mortem interval estimation model based on 18 pericardial fluid samples was validated with an independent set of 6 samples, giving a prediction error of 33-34 h depending on the experimental protocol used. By narrowing the window to post-mortem intervals below 100 h, the prediction power of the model was significantly improved with an error of 13-15 h depending on the extraction protocol. Choline, glycine, ethanolamine, and hypoxanthine were the most relevant metabolites in the prediction model.

CONCLUSION

The present study, although preliminary, shows that PF samples collected from a real forensic scenario represent a biofluid of interest for post-mortem metabolomics, with particular regard to the estimation of the time since death.

Post-mortem CT radiomics for the prediction of time since death

OBJECTIVES

Post-mortem interval (PMI) estimation has long been relying on sequential post-mortem changes on the body as a function of extrinsic, intrinsic, and environmental factors. Such factors are difficult to account for in complicated death scenes; thus, PMI estimation can be compromised. Herein, we aimed to evaluate the use of post-mortem CT (PMCT) radiomics for the differentiation between early and late PMI.

METHODS

Consecutive whole-body PMCT examinations performed between 2016 and 2021 were retrospectively included (n = 120), excluding corpses without an accurately reported PMI (n = 23). Radiomics data were extracted from liver and pancreas tissue and randomly split into training and validation sets (70:30%). Following data preprocessing, significant features were selected (Boruta selection) and three XGBoost classifiers were built (liver, pancreas, combined) to differentiate between early (< 12 h) and late (> 12 h) PMI. Classifier performance was assessed with receiver operating characteristics (ROC) curves and areas under the curves (AUC), which were compared by bootstrapping.

RESULTS

A total of 97 PMCTs were included, representing individuals (23 females and 74 males) with a mean age of 47.1 ± 23.38 years. The combined model achieved the highest AUC reaching 75% (95%CI 58.4-91.6%) (p = 0.03 compared to liver and p = 0.18 compared to pancreas). The liver-based and pancreas-based XGBoost models achieved AUCs of 53.6% (95%CI 34.8-72.3%) and 64.3% (95%CI 46.7-81.9%) respectively (p > 0.05 for the comparison between liver- and pancreas-based models).

CONCLUSION

The use of radiomics analysis on PMCT examinations differentiated early from late PMI, unveiling a novel image-based method with important repercussions in forensic casework.

CLINICAL RELEVANCE STATEMENT

This paper introduces the employment of radiomics in forensic diagnosis by presenting an effective automated alternative method of estimating post-mortem interval from targeted tissues, thus paving the way for improvement in speed and quality of forensic investigations.

KEY POINTS

• A combined liver-pancreas radiomics model differentiated early from late post-mortem intervals (using a 12-h threshold) with an area under the curve of 75% (95%CI 58.4-91.6%). • XGBoost models based on liver-only or pancreas-only radiomics demonstrated inferior performance to the combined model in predicting the post-mortem interval.

Using autopsies to dissect COVID-19 pathogenesis

The emergence of SARS-CoV-2 has resulted in millions of deaths as a result of COVID-19. Suitable models were missing at the beginning of the pandemic, and studies investigating disease pathogenesis relied on patients who had succumbed to COVID-19. Since then, autopsies of patients have substantially contributed to our understanding of the pathogenesis of COVID-19 and associated major organ complications. Here we summarize how autopsies have complemented experimental studies, mainly in animal models, and how they have facilitated critical knowledge of COVID-19 to improve daily clinical practice and develop therapeutic interventions. Employing advanced histopathologic and molecular genetic methods in post-mortem tissues, the COVID-19 pandemic has highlighted the importance of autopsies for virology research and clinical practice in current and emerging infectious diseases.

Transcriptomic analysis reveals a tissue-specific loss of identity during ageing and cancer

INTRODUCTION

Understanding changes in cell identity in cancer and ageing is of great importance. In this work, we analyzed how gene expression changes in human tissues are associated with tissue specificity during cancer and ageing using transcriptome data from TCGA and GTEx.

RESULTS

We found significant downregulation of tissue-specific genes during ageing in 40% of the tissues analyzed, which suggests loss of tissue identity with age. For most cancer types, we have noted a consistent pattern of downregulation in genes that are specific to the tissue from which the tumor originated. Moreover, we observed in cancer an activation of genes not usually expressed in the tissue of origin as well as an upregulation of genes specific to other tissues. These patterns in cancer were associated with patient survival. The age of the patient, however, did not influence these patterns.

CONCLUSION

We identified loss of cellular identity in 40% of the tissues analysed during human ageing, and a clear pattern in cancer, where during tumorigenesis cells express genes specific to other organs while suppressing the expression of genes from their original tissue. The loss of cellular identity observed in cancer is associated with prognosis and is not influenced by age, suggesting that it is a crucial stage in carcinogenesis.

Genome annotation: From human genetics to biodiversity genomics

Within the next decade, the genomes of 1.8 million eukaryotic species will be sequenced. Identifying genes in these sequences is essential to understand the biology of the species. This is challenging due to the transcriptional complexity of eukaryotic genomes, which encode hundreds of thousands of transcripts of multiple types. Among these, a small set of protein-coding mRNAs play a disproportionately large role in defining phenotypes. Due to their sequence conservation, orthology can be established, making it possible to define the universal catalog of eukaryotic protein-coding genes. This catalog should substantially contribute to uncovering the genomic events underlying the emergence of eukaryotic phenotypes. This piece briefly reviews the basics of protein-coding gene prediction, discusses challenges in finalizing annotation of the human genome, and proposes strategies for producing annotations across the eukaryotic Tree of Life. This lays the groundwork for obtaining the catalog of all genes-the Earth's code of life.

Large-scale assessment of pros and cons of autopsy-derived or tumor-matched tissues as the norms for gene expression analysis in cancers

Normal tissues are essential for studying disease-specific differential gene expression. However, healthy human controls are typically available only in postmortal/autopsy settings. In cancer research, fragments of pathologically normal tissue adjacent to tumor site are frequently used as the controls. However, it is largely underexplored how cancers can systematically influence gene expression of the neighboring tissues. Here we performed a comprehensive pan-cancer comparison of molecular profiles of solid tumor-adjacent and autopsy-derived "healthy" normal tissues. We found a number of systemic molecular differences related to activation of the immune cells, intracellular transport and autophagy, cellular respiration, telomerase activation, p38 signaling, cytoskeleton remodeling, and reorganization of the extracellular matrix. The tumor-adjacent tissues were deficient in apoptotic signaling and negative regulation of cell growth including G2/M cell cycle transition checkpoint. We also detected an extensive rearrangement of the chemical perception network. Molecular targets of 32 and 37 cancer drugs were over- or underexpressed, respectively, in the tumor-adjacent norms. These processes may be driven by molecular events that are correlated between the paired cancer and adjacent normal tissues, that mostly relate to inflammation and regulation of intracellular molecular pathways such as the p38, MAPK, Notch, and IGF1 signaling. However, using a model of macaque postmortal tissues we showed that for the 30 min - 24-hour time frame at 4ºC, an RNA degradation pattern in lung biosamples resulted in an artifact "differential" expression profile for 1140 genes, although no differences could be detected in liver. Thus, such concerns should be addressed in practice.

Resveratrol activation of SIRT1/MFN2 can improve mitochondria function, alleviating doxorubicin-induced myocardial injury

Background

Doxorubicin is a widely used cytotoxic chemotherapy agent for treating different malignancies. However, its use is associated with dose-dependent cardiotoxicity, causing irreversible myocardial damage and significantly reducing the patient's quality of life and survival. In this study, an animal model of doxorubicin-induced cardiomyopathy was used to investigate the pathogenesis of doxorubicin-induced myocardial injury. This study also investigated a possible treatment strategy for alleviating myocardial injury through resveratrol therapy in vitro.

Methods

Adult male C57BL/6J mice were randomly divided into a control group and a doxorubicin group. Body weight, echocardiography, surface electrocardiogram, and myocardial histomorphology were measured. The mechanisms of doxorubicin cardiotoxicity in H9c2 cell lines were explored by comparing three groups (phosphate-buffered saline, doxorubicin, and doxorubicin with resveratrol).

Results

Compared to the control group, the doxorubicin group showed a lower body weight and higher systolic arterial pressure, associated with reduced left ventricular ejection fraction and left ventricular fractional shortening, prolonged PR interval, and QT interval. These abnormalities were associated with vacuolation and increased disorder in the mitochondria of cardiomyocytes, increased protein expression levels of α-smooth muscle actin and caspase 3, and reduced protein expression levels of Mitofusin2 (MFN2) and Sirtuin1 (SIRT1). Compared to the doxorubicin group, doxorubicin + resveratrol treatment reduced caspase 3 and manganese superoxide dismutase, and increased MFN2 and SIRT1 expression levels.

Conclusion

Doxorubicin toxicity leads to abnormal mitochondrial morphology and dysfunction in cardiomyocytes and induces apoptosis by interfering with mitochondrial fusion. Resveratrol ameliorates doxorubicin-induced cardiotoxicity by activating SIRT1/MFN2 to improve mitochondria function.

A study of gene expression in the living human brain

A goal of medical research is to determine the molecular basis of human brain health and illness. One way to achieve this goal is through observational studies of gene expression in human brain tissue. Due to the unavailability of brain tissue from living people, most such studies are performed using tissue from postmortem brain donors. An assumption underlying this practice is that gene expression in the postmortem human brain is an accurate representation of gene expression in the living human brain. Here, this assumption - which, until now, had not been adequately tested - is tested by comparing human prefrontal cortex gene expression between 275 living samples and 243 postmortem samples. Expression levels differed significantly for nearly 80% of genes, and a systematic examination of alternative explanations for this observation determined that these differences are not a consequence of cell type composition, RNA quality, postmortem interval, age, medication, morbidity, symptom severity, tissue pathology, sample handling, batch effects, or computational methods utilized. Analyses integrating the data generated for this study with data from earlier landmark studies that used tissue from postmortem brain donors showed that postmortem brain gene expression signatures of neurological and mental illnesses, as well as of normal traits such as aging, may not be accurate representations of these gene expression signatures in the living brain. By using tissue from large cohorts living people, future observational studies of human brain biology have the potential to (1) determine the medical research questions that can be addressed using postmortem tissue as a proxy for living tissue and (2) expand the scope of medical research to include questions about the molecular basis of human brain health and illness that can only be addressed in living people (e.g., "What happens at the molecular level in the brain as a person experiences an emotion?").

Considerations for reproducible omics in aging research

Technical advancements over the past two decades have enabled the measurement of the panoply of molecules of cells and tissues including transcriptomes, epigenomes, metabolomes and proteomes at unprecedented resolution. Unbiased profiling of these molecular landscapes in the context of aging can reveal important details about mechanisms underlying age-related functional decline and age-related diseases. However, the high-throughput nature of these experiments creates unique analytical and design demands for robustness and reproducibility. In addition, 'omic' experiments are generally onerous, making it crucial to effectively design them to eliminate as many spurious sources of variation as possible as well as account for any biological or technical parameter that may influence such measures. In this Perspective, we provide general guidelines on best practices in the design and analysis of omic experiments in aging research from experimental design to data analysis and considerations for long-term reproducibility and validation of such studies.

CapTrap-Seq: A platform-agnostic and quantitative approach for high-fidelity full-length RNA transcript sequencing

Long-read RNA sequencing is essential to produce accurate and exhaustive annotation of eukaryotic genomes. Despite advancements in throughput and accuracy, achieving reliable end-to-end identification of RNA transcripts remains a challenge for long-read sequencing methods. To address this limitation, we developed CapTrap-seq, a cDNA library preparation method, which combines the Cap-trapping strategy with oligo(dT) priming to detect 5'capped, full-length transcripts, together with the data processing pipeline LyRic. We benchmarked CapTrap-seq and other popular RNA-seq library preparation protocols in a number of human tissues using both ONT and PacBio sequencing. To assess the accuracy of the transcript models produced, we introduced a capping strategy for synthetic RNA spike-in sequences that mimics the natural 5'cap formation in RNA spike-in molecules. We found that the vast majority (up to 90%) of transcript models that LyRic derives from CapTrap-seq reads are full-length. This makes it possible to produce highly accurate annotations with minimal human intervention.

Mapping human adult hippocampal neurogenesis with single-cell transcriptomics: Reconciling controversy or fueling the debate?

The notion of exploiting the regenerative potential of the human brain in physiological aging or neurological diseases represents a particularly attractive alternative to conventional strategies for enhancing or restoring brain function. However, a major first question to address is whether the human brain does possess the ability to regenerate. The existence of human adult hippocampal neurogenesis (AHN) has been at the center of a fierce scientific debate for many years. The advent of single-cell transcriptomic technologies was initially viewed as a panacea to resolving this controversy. However, recent single-cell RNA sequencing studies in the human hippocampus yielded conflicting results. Here, we critically discuss and re-analyze previously published AHN-related single-cell transcriptomic datasets. We argue that, although promising, the single-cell transcriptomic profiling of AHN in the human brain can be confounded by methodological, conceptual, and biological factors that need to be consistently addressed across studies and openly discussed within the scientific community.

A miRNome analysis at the early postmortem interval

The postmortem interval (PMI) is the time elapsing since the death of an individual until the body is examined. Different molecules have been analyzed to better estimate the PMI with variable results. The miRNAs draw attention in the forensic field to estimate the PMI as they can better support degradation. In the present work, we analyzed the miRNome at early PMI in rats' skeletal muscle using the Affymetrix GeneChip™ miRNA 4.0 microarrays. We found 156 dysregulated miRNAs in rats' skeletal muscle at 24 h of PMI, out of which 84 were downregulated, and 72 upregulated. The miRNA most significantly downregulated was miR-139-5p (FC = -160, p = 9.97 × 10^-11), while the most upregulated was rno-miR-92b-5p (FC = 241.18, p = 2.39 × 10^-6). Regarding the targets of these dysregulated miRNAs, the rno-miR-125b-5p and rno-miR-138-5p were the miRNAs with more mRNA targets. The mRNA targets that we found in the present study participate in several biological processes such as interleukin secretion regulation, translation regulation, cell growth, or low oxygen response. In addition, we found a downregulation of SIRT1 mRNA and an upregulation of TGFBR2 mRNA at 24 h of PMI. These results suggest there is an active participation of miRNAs at early PMI which could be further explored to identify potential biomarkers for PMI estimation.

Pervasive effects of RNA degradation on Nanopore direct RNA sequencing

Oxford Nanopore direct RNA sequencing (DRS) is capable of sequencing complete RNA molecules and accurately measuring gene and isoform expression. However, as DRS is designed to profile intact RNA, expression quantification may be more heavily dependent upon RNA integrity than alternative RNA sequencing methodologies. It is currently unclear how RNA degradation impacts DRS or whether it can be corrected for. To assess the impact of RNA integrity on DRS, we performed a degradation time series using SH-SY5Y neuroblastoma cells. Our results demonstrate that degradation is a significant and pervasive factor that can bias DRS measurements, including a reduction in library complexity resulting in an overrepresentation of short genes and isoforms. Degradation also biases differential expression analyses; however, we find that explicit correction can almost fully recover meaningful biological signal. In addition, DRS provided less biased profiling of partially degraded samples than Nanopore PCR-cDNA sequencing. Overall, we find that samples with RNA integrity number (RIN) > 9.5 can be treated as undegraded and samples with RIN > 7 can be utilized for DRS with appropriate correction. These results establish the suitability of DRS for a wide range of samples, including partially degraded in vivo clinical and post-mortem samples, while limiting the confounding effect of degradation on expression quantification.

What happens in the brain when we die? Deciphering the neurophysiology of the final moments in life

When do we die and what happens in the brain when we die? The mystery around these questions has engaged mankind for centuries. Despite the challenges to obtain recordings of the dying brain, recent studies have contributed to better understand the processes occurring during the last moments of life. In this review, we summarize the literature on neurophysiological changes around the time of death. Perhaps the only subjective description of death stems from survivors of near-death experiences (NDEs). Hallmarks of NDEs include memory recall, out-of-body experiences, dreaming, and meditative states. We survey the evidence investigating neurophysiological changes of these experiences in healthy subjects and attempt to incorporate this knowledge into the existing literature investigating the dying brain to provide valuations for the neurophysiological footprint and timeline of death. We aim to identify reasons explaining the variations of data between studies investigating this field and provide suggestions to standardize research and reduce data variability.

Proteome alterations in human autopsy tissues in relation to time after death

Protein expression is a primary area of interest for routine histological diagnostics and tissue-based research projects, but the limitations of its post-mortem applicability remain largely unclear. On the other hand, tissue specimens obtained during autopsies can provide unique insight into advanced disease states, especially in cancer research. Therefore, we aimed to identify the maximum post-mortem interval (PMI) which is still suitable for characterizing protein expression patterns, to explore organ-specific differences in protein degradation, and to investigate whether certain proteins follow specific degradation kinetics. Therefore, the proteome of human tissue samples obtained during routine autopsies of deceased patients with accurate PMI (6, 12, 18, 24, 48, 72, 96 h) and without specific diseases that significantly affect tissue preservation, from lungs, kidneys and livers, was analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). For the kidney and liver, significant protein degradation became apparent at 48 h. For the lung, the proteome composition was rather static for up to 48 h and substantial protein degradation was detected only at 72 h suggesting that degradation kinetics appear to be organ specific. More detailed analyses suggested that proteins with similar post-mortem kinetics are not primarily shared in their biological functions. The overrepresentation of protein families with analogous structural motifs in the kidney indicates that structural features may be a common factor in determining similar postmortem stability. Our study demonstrates that a longer post-mortem period may have a significant impact on proteome composition, but sampling within 24 h may be appropriate, as degradation is within acceptable limits even in organs with faster autolysis.