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Redefining ALS: Large-scale proteomic profiling reveals a prolonged pre-diagnostic phase with immune, muscular, metabolic, and brain involvement.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder with a largely unknown duration and pathophysiology of the pre-diagnostic phase, especially for the common non-monogenic form. METHODS: We leveraged the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort with up to 30 years of follow-up to identify incident ALS cases across five European countries. Pre-diagnostic plasma samples from initially healthy participants underwent high-throughput proteomic profiling (7,285 protein markers, SomaScan). Cox proportional hazards models based on 4,567 participants (including 172 incident ALS cases) were used to identify protein biomarkers associated with future ALS diagnosis. Top results were indirectly validated in two independent case-control studies of prevalent ALS (n=417 ALS, 852 controls). Functional annotation included cross-disease comparisons, gene set and tissue enrichment testing, organ-specific proteomic clocks, and the application of large-language models (LLM). FINDINGS: Five proteins (SECTM1, CA3, THAP4, KLHL41, SLC26A7) were identified as significant pre-diagnostic ALS biomarkers (FDR=0.05), detectable approximately two decades before diagnosis. Of these, all except SECTM1 were indirectly validated in independent cohorts of prevalent ALS cases, supporting their clinical significance. Additionally, 22 nominally significant (p<0.05) pre-diagnostic biomarkers were FDR-significant in prevalent ALS with consistent effect directions. Cross-disease comparisons with pre-diagnostic Parkinson's and Alzheimer's disease suggested a largely specific pre-diagnostic ALS biomarker signature. Gene ontology and tissue enrichment highlighted early involvement of immune, muscle, metabolic, and digestive processes. Furthermore, analyses of proteomic clocks revealed accelerated aging in brain-cognition, immune, and muscle tissues before clinical diagnosis. Druggability and LLM analyses revealed possible therapeutic targets and novel strategies, emphasizing translational relevance. INTERPRETATION: Our study provides first evidence of ultra-early molecular changes in common ALS up to two decades prior to clinical onset, mainly affecting immune, muscle, metabolic, digestive, and cognitive systems. Our study nominates several compelling candidates for risk stratification studies and novel therapeutic targets for early intervention. FUNDING: Clinical Research in ALS and Related Disorders for Therapeutic Development (CreATe) Consortium, Cure Alzheimer's Fund, Michael J Fox Foundation, Interdisciplinary Centre for Clinical Research, University M&#xfc;nster.

Journal Article↗

Identification of novel human genes evolutionarily conserved in Caenorhabditis elegans by comparative proteomics.

Modern biomedical research greatly benefits from large-scale genome-sequencing projects ranging from studies of viruses, bacteria, and yeast to multicellular organisms, like Caenorhabditis elegans. Comparative genomic studies offer a vast array of prospects for identification and functional annotation of human ortholog genes. We presented a novel comparative proteomic approach for assembling human gene contigs and assisting gene discovery. The C. elegans proteome was used as an alignment template to assist in novel human gene identification from human EST nucleotide databases. Among the available 18,452 C. elegans protein sequences, our results indicate that at least 83% (15,344 sequences) of C. elegans proteome has human homologous genes, with 7,954 records of C. elegans proteins matching known human gene transcripts. Only 11% or less of C. elegans proteome contains nematode-specific genes. We found that the remaining 7,390 sequences might lead to discoveries of novel human genes, and over 150 putative full-length human gene transcripts were assembled upon further database analyses. [The sequence data described in this paper have been submitted to the

Amino Acid Sequence↗

G protein-coupled receptor genes in the FANTOM2 database.

G protein-coupled receptors (GPCRs) comprise the largest family of receptor proteins in mammals and play important roles in many physiological and pathological processes. Gene expression of GPCRs is temporally and spatially regulated, and many splicing variants are also described. In many instances, different expression profiles of GPCR gene are accountable for the changes of its biological function. Therefore, it is intriguing to assess the complexity of the transcriptome of GPCRs in various mammalian organs. In this study, we took advantage of the FANTOM2 (Functional Annotation Meeting of Mouse cDNA 2) project, which aimed to collect full-length cDNAs inclusively from mouse tissues, and found 410 candidate GPCR cDNAs. Clustering of these clones into transcriptional units (TUs) reduced this number to 213. Out of these, 165 genes were represented within the known 308 GPCRs in the Mouse Genome Informatics (MGI) resource. The remaining 48 genes were new to mouse, and 14 of them had no clear mammalian ortholog. To dissect the detailed characteristics of each transcript, tissue distribution pattern and alternative splicing were also ascertained. We found many splicing variants of GPCRs that may have a relevance to disease occurrence. In addition, the difficulty in cloning tissue-specific and infrequently transcribed GPCRs is discussed further.

Alternative Splicing↗

Cytoscape: a software environment for integrated models of biomolecular interaction networks.

Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.

Algorithms↗

Global survey of chromatin accessibility using DNA microarrays.

An increasing number of studies indicate a central role for chromatin remodeling in the regulation of gene expression. Current methods for high-resolution studies of the relationship between chromatin accessibility and transcription are low throughput, making a genome-wide study impractical. To enable the simultaneous measurement of the global chromatin accessibility state at the resolution of single genes, we developed the Chromatin Array technique, in which chromatin is separated by its condensation state using either the solubility differences of mono- and oligonucleosomes in specific buffers or controlled DNase I digestion and selection of the large refractory (condensed) DNA fragments. By probing with a comparative genomic hybridization style microarray, we can determine the condensation state of thousands of individual loci and correlate this with transcriptional activity. Applying this technique to the breast tumor model cell line, MCF7, we found that when the condensation is homogeneous in the population of cells, expression is inversely proportional to the level of accessibility and the two methods of accessibility-based target selection correlate well. Using functional annotation and comparative genomic hybridization data, we have begun to decipher the possible biological implications of the relationship between chromatin accessibility and expression.

Breast Neoplasms↗

Functional cloning, sorting, and expression profiling of nucleic acid-binding proteins.

A major challenge in the post-sequencing era is to elucidate the activity and biological function of genes that reside in the human genome. An important subset includes genes that encode proteins that regulate gene expression or maintain the structural integrity of the genome. Using a novel oligonucleotide-binding substrate as bait, we show the feasibility of a modified functional expression-cloning strategy to identify human cDNAs that encode a spectrum of nucleic acid-binding proteins (NBPs). Approximately 170 cDNAs were identified from screening phage libraries derived from a human colorectal adenocarcinoma cell line and from noncancerous fetal lung tissue. Sequence analysis confirmed that virtually every clone contained a known DNA- or RNA-binding motif. We also report on a complementary sorting strategy that, in the absence of subcloning and protein purification, can distinguish different classes of NBPs according to their particular binding properties. To extend our functional annotation of NBPs, we have used GeneChip expression profiling of 14 different breast-derived cell lines to examine the relative transcriptional activity of genes identified in our screen and cluster analysis to discover other genes that have similar expression patterns. Finally, we present strategies to analyze the upstream regulatory region of each gene within a cluster group and select unique combinations of transcription factor binding sites that may be responsible for dictating the observed synexpression.

Adenocarcinoma↗

A cross-genomic approach for systematic mapping of phenotypic traits to genes.

We present a computational method for de novo identification of gene function using only cross-organismal distribution of phenotypic traits. Our approach assumes that proteins necessary for a set of phenotypic traits are preferentially conserved among organisms that share those traits. This method combines organism-to-phenotype associations,along with phylogenetic profiles,to identify proteins that have high propensities for the query phenotype; it does not require the use of any functional annotations for any proteins. We first present the statistical foundations of this approach and then apply it to a range of phenotypes to assess how its performance depends on the frequency and specificity of the phenotype. Our analysis shows that statistically significant associations are possible as long as the phenotype is neither extremely rare nor extremely common; results on the flagella,pili, thermophily,and respiratory tract tropism phenotypes suggest that reliable associations can be inferred when the phenotype does not arise from many alternate mechanisms.

Bacterial Proteins↗

Identification and classification of differentially expressed genes in renal cell carcinoma by expression profiling on a global human 31,500-element cDNA array.

We investigated the changes in gene expression accompanying the development and progression of kidney cancer by use of 31,500-element complementary DNA arrays. We measured expression profiles for paired neoplastic and noncancerous renal epithelium samples from 37 individuals. Using an experimental design optimized for factoring out technological and biological noise, and an adapted statistical test, we found 1738 differentially expressed cDNAs with an expected number of six false positives. Functional annotation of these genes provided views of the changes in the activities of specific biological pathways in renal cancer. Cell adhesion, signal transduction, and nucleotide metabolism were among the biological processes with a large proportion of genes overexpressed in renal cell carcinoma. Down-regulated pathways in the kidney tumor cells included small molecule transport, ion homeostasis, and oxygen and radical metabolism. Our expression profiling data uncovered gene expression changes shared with other epithelial tumors, as well as a unique signature for renal cell carcinoma. [Expression data for the differentially expressed cDNAs are available as a Web supplement at http://www.dkfz-heidelberg.de/abt0840/whuber/rcc.]

Carcinoma, Renal Cell↗

Applications of a rat multiple tissue gene expression data set.

With the sequencing and assembly of the rat genome comes the difficult task of assigning functions to genes. Tissue localization of gene expression gives some information about the potential role of a gene in physiology. Various examples of the utility of multiple tissue gene expression data sets are illustrated here. First, we highlight their use in finding genes that might play an important role in a particular tissue on the basis of exclusive expression in that tissue or coexpression with a gene or genes with known function. Second, we show how this data might be used to explain known phenotypic differences between strains. Third, we show how expression patterns of genes in a genomic interval might identify candidate genes in quantitative trait loci (QTL) mapping studies. Lastly, we show how multiple tissue and species data can help researchers prioritize follow up studies to microarray experiments. All of these applications of multiple tissue gene expression data sets will play a role in functionally annotating the rat genome.

Animals↗

Transcriptome analysis for the chicken based on 19,626 finished cDNA sequences and 485,337 expressed sequence tags.

We present an analysis of the chicken (Gallus gallus) transcriptome based on the full insert sequences for 19,626 cDNAs, combined with 485,337 EST sequences. The cDNA data set has been functionally annotated and describes a minimum of 11,929 chicken coding genes, including the sequence for 2260 full-length cDNAs together with a collection of noncoding (nc) cDNAs that have been stringently filtered to remove untranslated regions of coding mRNAs. The combined collection of cDNAs and ESTs describe 62,546 clustered transcripts and provide transcriptional evidence for a total of 18,989 chicken genes, including 88% of the annotated Ensembl gene set. Analysis of the ncRNAs reveals a set that is highly conserved in chickens and mammals, including sequences for 14 pri-miRNAs encoding 23 different miRNAs. The data sets described here provide a transcriptome toolkit linked to physical clones for bioinformaticians and experimental biologists who wish to use chicken systems as a low-cost, accessible alternative to mammals for the analysis of vertebrate development, immunology, and cell biology.

Animals↗

Making connections between novel transcription factors and their DNA motifs.

The key components of a transcriptional regulatory network are the connections between trans-acting transcription factors and cis-acting DNA-binding sites. In spite of several decades of intense research, only a fraction of the estimated approximately 300 transcription factors in Escherichia coli have been linked to some of their binding sites in the genome. In this paper, we present a computational method to connect novel transcription factors and DNA motifs in E. coli. Our method uses three types of mutually independent information, two of which are gleaned by comparative analysis of multiple genomes and the third one derived from similarities of transcription-factor-DNA-binding-site interactions. The different types of information are combined to calculate the probability of a given transcription-factor-DNA-motif pair being a true pair. Tested on a study set of transcription factors and their DNA motifs, our method has a prediction accuracy of 59% for the top predictions and 85% for the top three predictions. When applied to 99 novel transcription factors and 70 novel DNA motifs, our method predicted 64 transcription-factor-DNA-motif pairs. Supporting evidence for some of the predicted pairs is presented. Functional annotations are made for 23 novel transcription factors based on the predicted transcription-factor-DNA-motif connections.

Algorithms↗

Genome-wide computational prediction of transcriptional regulatory modules reveals new insights into human gene expression.

The identification of regulatory regions is one of the most important and challenging problems toward the functional annotation of the human genome. In higher eukaryotes, transcription-factor (TF) binding sites are often organized in clusters called cis-regulatory modules (CRM). While the prediction of individual TF-binding sites is a notoriously difficult problem, CRM prediction has proven to be somewhat more reliable. Starting from a set of predicted binding sites for more than 200 TF families documented in Transfac, we describe an algorithm relying on the principle that CRMs generally contain several phylogenetically conserved binding sites for a few different TFs. The method allows the prediction of more than 118,000 CRMs within the human genome. A subset of these is shown to be bound in vivo by TFs using ChIP-chip. Their analysis reveals, among other things, that CRM density varies widely across the genome, with CRM-rich regions often being located near genes encoding transcription factors involved in development. Predicted CRMs show a surprising enrichment near the 3' end of genes and in regions far from genes. We document the tendency for certain TFs to bind modules located in specific regions with respect to their target genes and identify TFs likely to be involved in tissue-specific regulation. The set of predicted CRMs, which is made available as a public database called PReMod (http://genomequebec.mcgill.ca/PReMod), will help analyze regulatory mechanisms in specific biological systems.

Algorithms↗

Zooming in on the human-mouse comparative map: genome conservation re-examined on a high-resolution scale.

Over the past decade, conservation of genetic linkage groups has been shown in mammals and used to great advantage, fueling significant exchanges of gene mapping and functional information especially between the genomes of humans and mice. As human physical maps increase in resolution from chromosome bands to nucleotide sequence, comparative alignments of mouse and human regions have revealed striking similarities and surprising differences between the genomes of these two best-mapped mammalian species. Whereas, at present, very few mouse and human regions have been compared on the physical level, existing studies provide intriguing insights to genome evolution, including the observation of recent duplications and deletions of genes that may play significant roles in defining some of the biological differences between the two species. Although high-resolution conserved marker-based maps are currently available only for human and mouse, a variety of new methods and resources are speeding the development of comparative maps of additional organisms. These advances mark the first step toward establishment of the human genome as a reference map for vertebrate species, providing evolutionary and functional annotation to human sequence and vast new resources for genetic analysis of a variety of commercially, medically, and ecologically important animal models.

Animals↗

A computer-based method of selecting clones for a full-length cDNA project: simultaneous collection of negligibly redundant and variant cDNAs.

We describe a computer-based method that selects representative clones for full-length sequencing in a full-length cDNA project. Our method classifies end sequences using two kinds of criteria, grouping, and clustering. Grouping places together variant cDNAs, family genes, and cDNAs with sequencing errors. Clustering separates those cDNA clones into distinct clusters. The full-length sequences of the clones selected by grouping are determined preferentially, and then the sequences selected by clustering are determined. Grouping reduced the number of rice cDNA clones for full-length sequencing to 21% and mouse cDNA clones to 25%. Rice full-length sequences selected by grouping showed a 1.07-fold redundancy. Mouse full-length sequences showed a 1.04-fold redundancy, which can be reduced by approximately 30% from the selection using our previous method. To estimate the coverage of unique genes, we used FANTOM (Functional Annotation of RIKEN Mouse cDNA Clones) clusters (). Grouping covered almost all unique genes (93% of FANTOM clusters), and clustering covered all genes. Therefore, our method is useful for the selection of appropriate representative clones for full-length sequencing, thereby greatly reducing the cost, labor, and time necessary for this process.

Animals↗

Analogous enzymes: independent inventions in enzyme evolution.

It is known that the same reaction may be catalyzed by structurally unrelated enzymes. We performed a systematic search for such analogous (as opposed to homologous) enzymes by evaluating sequence conservation among enzymes with the same enzyme classification (EC) number using sensitive, iterative sequence database search methods. Enzymes without detectable sequence similarity to each other were found for 105 EC numbers (a total of 243 distinct proteins). In 34 cases, independent evolutionary origin of the suspected analogous enzymes was corroborated by showing that they possess different structural folds. Analogous enzymes were found in each class of enzymes, but their overall distribution on the map of biochemical pathways is patchy, suggesting multiple events of gene transfer and selective loss in evolution, rather than acquisition of entire pathways catalyzed by a set of unrelated enzymes. Recruitment of enzymes that catalyze a similar but distinct reaction seems to be a major scenario for the evolution of analogous enzymes, which should be taken into account for functional annotation of genomes. For many analogous enzymes, the bacterial form of the enzyme is different from the eukaryotic one; such enzymes may be promising targets for the development of new antibacterial drugs.

Amino Acid Sequence↗

Genome-wide identification of Arabidopsis coiled-coil proteins and establishment of the ARABI-COIL database.

Increasing evidence demonstrates the importance of long coiled-coil proteins for the spatial organization of cellular processes. Although several protein classes with long coiled-coil domains have been studied in animals and yeast, our knowledge about plant long coiled-coil proteins is very limited. The repeat nature of the coiled-coil sequence motif often prevents the simple identification of homologs of animal coiled-coil proteins by generic sequence similarity searches. As a consequence, counterparts of many animal proteins with long coiled-coil domains, like lamins, golgins, or microtubule organization center components, have not been identified yet in plants. Here, all Arabidopsis proteins predicted to contain long stretches of coiled-coil domains were identified by applying the algorithm MultiCoil to a genome-wide screen. A searchable protein database, ARABI-COIL (http://www.coiled-coil.org/arabidopsis), was established that integrates information on number, size, and position of predicted coiled-coil domains with subcellular localization signals, transmembrane domains, and available functional annotations. ARABI-COIL serves as a tool to sort and browse Arabidopsis long coiled-coil proteins to facilitate the identification and selection of candidate proteins of potential interest for specific research areas. Using the database, candidate proteins were identified for Arabidopsis membrane-bound, nuclear, and organellar long coiled-coil proteins.

Algorithms↗

Comparative genomics of the pennate diatom Phaeodactylum tricornutum.

Diatoms are one of the most important constituents of phytoplankton communities in aquatic environments, but in spite of this, only recently have large-scale diatom-sequencing projects been undertaken. With the genome of the centric species Thalassiosira pseudonana available since mid-2004, accumulating sequence information for a pennate model species appears a natural subsequent aim. We have generated over 12,000 expressed sequence tags (ESTs) from the pennate diatom Phaeodactylum tricornutum, and upon assembly into a nonredundant set, 5,108 sequences were obtained. Significant similarity (E < 1E-04) to entries in the GenBank nonredundant protein database, the COG profile database, and the Pfam protein domains database were detected, respectively, in 45.0%, 21.5%, and 37.1% of the nonredundant collection of sequences. This information was employed to functionally annotate the P. tricornutum nonredundant set and to create an internet-accessible queryable diatom EST database. The nonredundant collection was then compared to the putative complete proteomes of the green alga Chlamydomonas reinhardtii, the red alga Cyanidioschyzon merolae, and the centric diatom T. pseudonana. A number of intriguing differences were identified between the pennate and the centric diatoms concerning activities of relevance for general cell metabolism, e.g. genes involved in carbon-concentrating mechanisms, cytosolic acetyl-Coenzyme A production, and fructose-1,6-bisphosphate metabolism. Finally, codon usage and utilization of C and G relative to gene expression (as measured by EST redundance) were studied, and preferences for utilization of C and CpG doublets were noted among the P. tricornutum EST coding sequences.

Animals↗

Comparative plant genomics resources at PlantGDB.

PlantGDB (http://www.plantgdb.org/) is a database of plant molecular sequences. Expressed sequence tag (EST) sequences are assembled into contigs that represent tentative unique genes. EST contigs are functionally annotated with information derived from known protein sequences that are highly similar to the putative translation products. Tentative Gene Ontology terms are assigned to match those of the similar sequences identified. Genome survey sequences are assembled similarly. The resulting genome survey sequence contigs are matched to ESTs and conserved protein homologs to identify putative full-length open reading frame-containing genes, which are subsequently provisionally classified according to established gene family designations. For Arabidopsis (Arabidopsis thaliana) and rice (Oryza sativa), the exon-intron boundaries for gene structures are annotated by spliced alignment of ESTs and full-length cDNAs to their respective complete genome sequences. Unique genome browsers have been developed to present all available EST and cDNA evidence for current transcript models (for Arabidopsis, see the AtGDB site at http://www.plantgdb.org/AtGDB/; for rice, see the OsGDB site at http://www.plantgdb.org/OsGDB/). In addition, a number of bioinformatic tools have been integrated at PlantGDB that enable researchers to carry out sequence analyses on-site using both their own data and data residing within the database.

Computational Biology↗