Multimarker Analysis Research Articles

Spatial Organization and Prognostic Significance of NK and NKT-like Cells via Multimarker Analysis of the Colorectal Cancer Microenvironment.

Although tumor-infiltrating T cells hold a beneficial prognostic role in colorectal cancer, other lymphocytic populations are less characterized. We developed a multiplexed immunofluorescence assay coupled with digital image analysis and machine learning to identify natural killer (NK) cells (NCAM1+CD3-), natural killer T-like (NKT-like) cells (NCAM1+CD3+), and T cells (NCAM1-CD3+) within the PTPRC+ (CD45+) cell population and to measure their granzyme B (GZMB; cytotoxicity marker) and FCGR3A (CD16a; NK-cell maturity marker) expression. We evaluated immune cell densities and spatial configuration in 907 incident colorectal carcinoma cases within two prospective cohort studies. We found that T cells were approximately 100 times more abundant than NK and NKT-like cells. Overall, NK cells showed high GZMB expression and were located closer to tumor cells than T and NKT-like cells. In T and NKT-like cells, GZMB expression was enriched in cells in closer proximity to tumor cells. Higher densities of both T and NKT-like cells associated with longer cancer-specific survival, independent of potential confounders (P trend < 0.0007). Higher stromal GZMB+ and FCGR3A+ NK-cell densities associated with longer cancer-specific survival (P trend < 0.003). For T and NKT-like cells, greater proximity to tumor cells associated with longer cancer-specific survival (P trend < 0.0001). These findings indicate that cytotoxic NCAM1+CD3-GZMB+ NK cells and NCAM1+CD3+ NKT-like cells are relatively rare lymphocytic populations within the colorectal cancer microenvironment and show distinct spatial configuration and associations with patient outcome. The results highlight the utility of a quantitative multimarker assay for in situ, single-cell immune biomarker evaluation and underscore the importance of spatial context for tumor microenvironment characterization.

Genetic variants in the Hedgehog signaling pathway genes are associated with gastric cancer risk in a Chinese Han population.

The Hedgehog signaling pathway participates in the occurrence and progression of cancers including gastric cancer. We conducted this study to evaluate whether genetic variants in the Hedgehog signaling pathway genes would affect gastric cancer risk. Multi-marker Analysis of GenoMic Annotation (MAGMA) was used to investigate the aggregated genetic effects of single nucleotide polymorphisms (SNPs) assigned to candidate genes. The relationship between SNPs and gastric cancer risk was estimated by multivariate logistic regression analyses. Gene expression was calculated using databases obtained from The Cancer Genome Atlas (TCGA) and The Gene Expression Omnibus (GEO). Kaplan‐Meier plotter was used to evaluate the association between gene expression with gastric cancer survival. Tumor Immune Estimation Resource 2.0 (TIMER 2.0) was applied to determine the correlation between selected gene expression and the immune cell infiltration degree. We identified that the G allele of rs2990912 in KIF27 was associated with higher gastric cancer risk, especially in the young and male subgroups. The expression ofKIF27 in gastric cancer tissues was higher than that in normal tissues, leading to poor survival in gastric cancer patients. Besides, KIF27 expression was related to immune cell infiltration and positively correlated with PD-L1 expression. Our findings highlight the key role of genetic variation in the Hedgehog signaling pathway genes in gastric cancer susceptibility, which may provide important insights into the diagnosis, prognosis, and treatment of gastric cancer.

Genome-Wide Association Mapping of Crown and Brown Rust Resistance in Perennial Ryegrass.

A population of 239 perennial ryegrass (Lolium perenne L.) genotypes was analyzed to identify marker-trait associations for crown rust (Puccinia coronata f. sp. lolii) and brown rust (Puccinia graminis f. sp. loliina) resistance. Phenotypic data from field trials showed a low correlation (r = 0.17) between the two traits. Genotypes were resequenced, and a total of 14,538,978 SNPs were used to analyze population structure, linkage disequilibrium (LD), and for genome-wide association study. The SNP heritability (h2SNP) was 0.4 and 0.8 for crown and brown rust resistance, respectively. The high-density SNP dataset allowed us to estimate LD decay with the highest possible precision to date for perennial ryegrass. Results showed a low LD extension with a rapid decay of r2 value below 0.2 after 520 bp on average. Additionally, QTL regions for both traits were detected, as well as candidate genes by applying Genome Complex Trait Analysis and Multi-marker Analysis of GenoMic Annotation. Moreover, two significant genes, LpPc6 and LpPl6, were identified for crown and brown rust resistance, respectively, when SNPs were aggregated to the gene level. The two candidate genes encode proteins with phosphatase activity, which putatively can be induced by the host to perceive, amplify and transfer signals to downstream components, thus activating a plant defense response.

Genetic Polymorphisms Involved in Mitochondrial Metabolism and Pancreatic Cancer Risk.

The mitochondrial metabolism has been associated with pancreatic ductal adenocarcinoma (PDAC) risk. Recent evidence also suggests the involvement of the genetic variability of the mitochondrial function in several traits involved in PDAC etiology. However, a systematic investigation of the genetic variability of mitochondrial genome (mtSNP) and of all the nuclear genes involved in its functioning (n-mtSNPs) has never been reported. We conducted a two-phase association study of mtSNPs and n-mtSNPs to assess their effect on PDAC risk. We analyzed 35,297 n-mtSNPs and 101 mtSNPs in up to 55,870 individuals (12,884 PDAC cases and 42,986 controls). In addition, we also conducted a gene-based analysis on 1,588 genes involved in mitochondrial metabolism using Multi-marker Analysis of GenoMic Annotation (MAGMA) software. In the discovery phase, we identified 49 n-mtSNPs and no mtSNPs associated with PDAC risk (P < 0.05). In the second phase, none of the findings were replicated. In the gene-level analysis, we observed that three genes (TERT, SUGCT, and SURF1) involved in the mitochondrial metabolism showed an association below the Bonferroni-corrected threshold of statistical significance (P = 0.05/1588 = 3.1 × 10-5). Even though the mitochondrial metabolism might be involved in PDAC etiology, our results, obtained in a study with one of the largest sample sizes to date, show that neither n-mtSNPs nor mtSNPs are associated with PDAC risk. This large case-control study does not support a role of the genetic variability of the mitochondrial function in PDAC risk.

Cancer Stem Cell-Like Circulating Tumor Cells Are Prognostic in Non-Small Cell Lung Cancer.

Despite recent advances in the treatment of non-small cell lung cancer (NSCLC), less than 10% of patients survive the first five years when the disease has already spread at primary diagnosis. Methods: Blood samples were taken from 118 NSCLC patients at primary diagnosis or at progression of the disease before the start of a new treatment line and enriched for circulating tumor cells (CTCs) by microfluidic Parsortix™ (Angle plc, Guildford GU2 7AF, UK) technology. The gene expression of epithelial cancer stem cell (CSC), epithelial to mesenchymal (EMT), and lung-related markers was assessed by qPCR, and the association of each marker with overall survival (OS) was evaluated using log-rank tests. Results: EpCAM was the most prevalent transcript, with 53.7% positive samples at primary diagnosis and 25.6% at recurrence. EpCAM and CK19, as well as NANOG, PROM1, TERT, CDH5, FAM83A, and PTHLH transcripts, were associated with worse OS. However, only the CSC-specific NANOG and PROM1 were related to the outcome both at primary diagnosis (NANOG: HR 3.21, 95%CI 1.02–10.14, p = 0.016; PROM1: HR 4.23, 95% CI 0.65–27.56, p = 0.007) and disease progression (NANOG: HR 4.17, 95%CI 0.72–24.14, p = 0.025; PROM1: HR 4.77, 95% CI 0.29–78.94, p = 0.032). Conclusions: The present study further underlines the relevance of the molecular characterization of CTCs. Our multi-marker analysis highlighted the prognostic value of cancer stem cell-related transcripts at primary diagnosis and disease progression.

Comprehensive analyses of RNA-seq and genome-wide data point to enrichment of neuronal cell type subsets in neuropsychiatric disorders

Neurological and psychiatric disorders, including substance use disorders, share a range of symptoms, which could be the result of shared genetic background. Many genetic loci have been identified for these disorders using genome-wide association studies, but conclusive evidence about cell types wherein these loci are active is lacking. We aimed to uncover implicated brain cell types in neuropsychiatric traits and to assess consistency in results across RNA datasets and methods. We therefore comprehensively employed cell type enrichment methods by integrating single-cell transcriptomic data from mouse brain regions with an unprecedented dataset of 42 human genome-wide association study results of neuropsychiatric, substance use and behavioral/quantitative brain-related traits (n = 12,544,007 individuals). Single-cell transcriptomic datasets from the Karolinska Institute and 10x Genomics were used. Cell type enrichment was determined using Linkage Disequilibrium Score Regression, Multi-marker Analysis of GenoMic Annotation, and Data-driven Expression Prioritized Integration for Complex Traits. We found the largest degree of consistency across methods for implication of pyramidal cells in schizophrenia and cognitive performance. For other phenotypes, such as bipolar disorder, two methods implicated the same cell types, i.e., medium spiny neurons and pyramidal cells. For autism spectrum disorders and anorexia nervosa, no consistency in implicated cell types was observed across methods. We found no evidence for astrocytes being consistently implicated in neuropsychiatric traits. In conclusion, we provide comprehensive evidence for a subset of neuronal cell types being consistently implicated in several, but not all psychiatric disorders, while non-neuronal cell types seem less implicated.

Functional variants of RPS6KB1 and PIK3R1 in the autophagy pathway genes and risk of bladder cancer

Autophagy plays a critical role in cancer, since it can either suppress tumorigenesis by inhibiting cancer cell survival, or facilitate tumorigenesis by promoting cancer cell proliferation and tumor growth. However, the role of genetic variants of autophagy-regulated key genes for bladder cancer risk remained unclear. Here, we aimed to explore the association of bladder cancer with genetic variants on genes involved in autophagy pathway. Gene-based analysis was performed with multi-marker analysis of genomic annotation (MAGMA) in 580 bladder cancer cases and 1101 controls. The logistic regression model was used to calculate the SNP effects on bladder cancer susceptibility. Expression quantitative trait loci (eQTL) analysis was conducted by the genotype-tissue expression (GTEx) project. Gene expression was evaluated based on the Cancer Genome Atlas (TCGA) database. Three potentially functional SNPs RPS6KB1 rs1292038, PIK3R1 rs34303, and rs56352616 were demonstrated to be associated with risk of bladder cancer (OR = 0.71, 95% CI = 0.61-0.82, P = 7.88 × 10-6 for rs1292038; OR = 1.25, 95% CI = 1.09-1.45, P = 2.11 × 10-3 for rs34303; OR = 0.74, 95% CI = 0.62-0.90, P = 2.47 × 10-3 for rs56352616). An increasing number of risk genotypes of these three SNPs were associated with a higher risk of developing bladder cancer. Besides, rs1292038 exhibited an eQTL effect for RPS6KB1 in whole blood (P = 3.90 × 10-7). Furthermore, the higher expression of RPS6KB1 and lower expression of PIK3R1 were both significantly associated with bladder cancer risk. Our findings indicated that genetic variants in autophagy pathway genes RPS6KB1 and PIK3R1 confer bladder cancer susceptibility.

Genome-wide association study of a thermo-tolerance indicator in pregnant ewes exposed to an artificial heat-stressed environment.

Environmental heat stress negatively influences sheep production in warm semi-arid regions. An animal's ability to tolerate warm weather is difficult to measure naturally due to environmental variability and genetic variation between animals. In this study we developed a thermo-tolerance indicator (TTI) to define heat stress tolerance in pregnant sheep in a controlled environment. Next, we performed a genome-wide association study (GWAS) to identify genomic regions and target genes associated with thermo-tolerance in sheep. Pregnant Columbia-Rambouillet crossbred ewes (n=127) were heat-stressed inside a climate-controlled chamber for 57 days by increasing the temperature-humidity index to ≥30. Rectal temperature (RT) and feed intake (FI) data were collected daily and used for the predictive TTI analysis. After the tenth day of heat stress, the regression analyses revealed that FI was stable; however, when the ewe's RT exceeded 39.8°C their FI was less than thermo-tolerant ewes. This average predicted temperature was used to classify each ewe as heat stress tolerant (≤39.8°C) and non-heat stress tolerant (>39.8°C). A GWAS analysis was performed and genomic regions were compared between heat stress tolerant and non-tolerant ewes. The single-marker genomic analysis detected 16 single nucleotide polymorphisms (SNP) associated with heat stress tolerance (P<0.0001), whereas the multi-marker Bayesian analysis identified 8 overlapped 1-Mb chromosomal regions accounting for 11.39% of the genetic variation associated with tolerance to heat stress. Four intragenic SNP showed a remarkable contribution to thermo-tolerance, and these markers were within the genes FBXO11 (rs407804467), PHC3 (rs414179061), TSHR (rs418575898) and STAT1 (rs417581105). In conclusion, genomic regions harboring four intragenic SNP were associated with heat stress tolerance, and these candidate genes are proposed to influence heat tolerance in pregnant ewes subjected to an artificially induced warm climate. Moreover, these genetic markers could be suitable for use in further genetic selection programs in sheep managed in semi-arid regions.

Genome-Wide Association Meta-Analysis Supports Genes Involved in Valve and Cardiac Development to Associate With Mitral Valve Prolapse.

Mitral valve prolapse (MVP) is a common cardiac valve disease, which affects 1 in 40 in the general population. Previous genome-wide association study has identified 6 risk loci for MVP. But these loci explained only partially the genetic risk for MVP. We aim to identify additional risk loci for MVP by adding data set from the UK Biobank. We also incorporated 434 MVP cases and 4527 controls from the UK Biobank for discovery analyses. Genetic association was conducted using SNPTEST and meta-analyses using METAL. We used Functional Mapping and Annotation of Genome-Wide Association Studies for post-genome-wide association study annotations and Multi-marker Analysis of GenoMic Annotation for gene-based and gene-set analyses. We found Trans-Omics for Precision Medicine imputation to perform better in terms of accuracy in the lower ranges of minor allele frequency below 0.1. Our updated meta-analysis included UK Biobank study for ≈8 million common single-nucleotide polymorphisms (minor allele frequency >0.01) and replicated the association on Chr2 as the top association signal near TNS1. We identified an additional risk locus on Chr1 (SYT2) and 2 suggestive risk loci on chr8 (MSRA) and chr19 (FBXO46), all driven by common variants. Gene-based association using Multi-marker Analysis of GenoMic Annotation revealed 6 risk genes for MVP with pronounced expression levels in cardiovascular tissues, especially the heart and globally part of enriched GO terms related to cardiac development. We report an updated meta-analysis genome-wide association study for MVP using dense imputation coverage and an improved case-control sample. We describe several loci and genes with MVP spanning biological mechanisms highly relevant to MVP, especially during valve and heart development.

Mapping gene and gene pathways associated with coronary artery disease: a CARDIoGRAM exome and multi-ancestry UK biobank analysis

Coronary artery disease (CAD) genome-wide association studies typically focus on single nucleotide variants (SNVs), and many potentially associated SNVs fail to reach the GWAS significance threshold. We performed gene and pathway-based association (GBA) tests on publicly available Coronary ARtery DIsease Genome wide Replication and Meta-analysis consortium Exome (n = 120,575) and multi ancestry pan UK Biobank study (n = 442,574) summary data using versatile gene-based association study (VEGAS2) and Multi-marker analysis of genomic annotation (MAGMA) to identify novel genes and pathways associated with CAD. We included only exonic SNVs and excluded regulatory regions. VEGAS2 and MAGMA ranked genes and pathways based on aggregated SNV test statistics. We used Bonferroni corrected gene and pathway significance threshold at 3.0 × 10–6 and 1.0 × 10–5, respectively. We also report the top one percent of ranked genes and pathways. We identified 17 top enriched genes with four genes (PCSK9, FAM177, LPL, ARGEF26), reaching statistical significance (p ≤ 3.0 × 10–6) using both GBA tests in two GWAS studies. In addition, our analyses identified ten genes (DUSP13, KCNJ11, CD300LF/RAB37, SLCO1B1, LRRFIP1, QSER1, UBR2, MOB3C, MST1R, and ABCC8) with previously unreported associations with CAD, although none of the single SNV associations within the genes were genome-wide significant. Among the top 1% non-lipid pathways, we detected pathways regulating coagulation, inflammation, neuronal aging, and wound healing.

Modern Imaging Technologies of Mast Cells for Biology and Medicine (Review).

Mast cells play an important role in the body defense against allergens, pathogens, and parasites by participating in inflammation development. However, there is evidence for their contributing to the pathogenesis of a number of atopic, autoimmune, as well as cardiovascular, oncologic, neurologic, and other diseases (allergy, asthma, eczema, rhinitis, anaphylaxis, mastocytosis, multiple sclerosis, rheumatoid arthritis, inflammatory gastrointestinal and pulmonary diseases, migraine, etc.). The diagnosis of many diseases and the study of mast cell functions in health and disease require their identification; so, the knowledge on adequate imaging techniques for mast cells in humans and different species of animals is of particular importance.The present review summarizes the data on major methods of mast cell imaging: enzyme histochemistry, immunohistochemistry, as well as histochemistry using histological stains. The main histological stains bind to heparin and other acidic mucopolysaccharides contained in mast cells and stain them metachromatically. Among these are toluidine blue, methylene blue (including that contained in May-Grünwald–Giemsa stain), thionin, pinacyanol, and others. Safranin and fluorescent dyes: berberine and avidin — also bind to heparin. Longer staining with histological dyes or alcian blue staining is needed to label mucosal and immature mast cells.Advanced techniques — enzyme histochemistry and especially immunohistochemistry — enable to detect mast cells high-selectively using a reaction to tryptases and chymases (specific proteases of these cells). In the immunohistochemical study of tryptases and chymases, species-specific differences in the distribution of the proteases in mast cells of humans and animals should be taken into account for their adequate detection. The immunohistochemical reaction to immunoglobulin E receptor (FcεRI) and c-kit receptor is not specific to mast cells, although the latter is important to demonstrate their proliferation in normal and malignant growth.Correct fixation of biological material is also discussed in the review as it is of great significance for histochemical and immunohistochemical mast cell detection.Fluorescent methods of immunohistochemistry and a multimarker analysis in combination with confocal microscopy are reported to be new technological approaches currently used to study various mast cell populations.

Gene Set Enrichment Analsyes Identify Pathways Involved in Genetic Risk for Diabetic Retinopathy

We analyzed DR GWAS meta-analyses performed on 3246 Europeans and 2611 African Americans with type 2 diabetes. Gene sets relevant to 5 key DR pathophysiology processes were investigated: tissue injury, vascular events, metabolic events and glial dysregulation, neuronal dysfunction, and inflammation. Keywords relevant to these processes were queried in 4 pathway and ontology databases. Two GSEA methods, Meta-Analysis Gene set Enrichment of variaNT Associations (MAGENTA) and Multi-marker Analysis of GenoMic Annotation (MAGMA), were used. Gene sets were defined to be enriched for gene associations with DR if the P value corrected for multiple testing (Pcorr) was <.05. Five gene sets were significantly enriched for numerous modest genetic associations with DR in one method (MAGENTA or MAGMA) and also at least nominally significant (uncorrected P < .05) in the other method. These pathways were regulation of the lipid catabolic process (2-fold enrichment, Pcorr=.014); nitric oxide biosynthesis (1.92-fold enrichment, Pcorr=.022); lipid digestion, mobilization, and transport (1.6-fold enrichment, P=.032); apoptosis (1.53-fold enrichment, P=.041); and retinal ganglion cell degeneration (2-fold enrichment, Pcorr=.049). The interferon gamma (IFNG) gene, previously implicated in DR by protein-protein interactions in our GWAS, was among the top ranked genes in the nitric oxide pathway (best variant P=.0001). These GSEA indicate that variants in genes involved in oxidative stress, lipid transport and catabolism, and cell degeneration are enriched for genes associated with DR risk. NOTE: Publication of this article is sponsored by the American Ophthalmological Society.

Downregulation by CNNM2 of ATP5MD expression in the 10q24.32 schizophrenia-associated locus involved in impaired ATP production and neurodevelopment

Genome-wide association studies (GWAS) have accelerated the discovery of numerous genetic variants associated with schizophrenia. However, most risk variants show a small effect size (odds ratio (OR) <1.2), suggesting that more functional risk variants remain to be identified. Here, we employed region-based multi-marker analysis of genomic annotation (MAGMA) to identify additional risk loci containing variants with large OR value from Psychiatry Genomics Consortium (PGC2) schizophrenia GWAS data and then employed summary-data-based mendelian randomization (SMR) to prioritize schizophrenia susceptibility genes. The top-ranked susceptibility gene ATP5MD, encoding an ATP synthase membrane subunit, is observed to be downregulated in schizophrenia by the risk allele of CNNM2-rs1926032 in the schizophrenia-associated 10q24.32 locus. The Atp5md knockout (KO) in mice was associated with abnormal startle reflex and gait, and ATP5MD knockdown (KD) in human induced pluripotent stem cell-derived neurons disrupted the neural development and mitochondrial respiration and ATP production. Moreover, CNNM2-rs1926032 KO could induce downregulation of ATP5MD expression and disruptions of mitochondrial respiration and ATP production. This study constitutes an important mechanistic component that links schizophrenia-associated CNNM2 regions to disruption in energy adenosine system modulation and neuronal function by long-distance chromatin domain downregulation of ATP5MD. This pathogenic mechanism provides therapeutic implications for schizophrenia.

Genetic architecture of root and shoot ionomes in rice (Oryza sativa L.)

Key messageAssociation analysis for ionomic concentrations of 20 elements identified independent genetic factors underlying the root and shoot ionomes of rice, providing a platform for selecting and dissecting causal genetic variants.Understanding the genetic basis of mineral nutrient acquisition is key to fully describing how terrestrial organisms interact with the non-living environment. Rice (Oryza sativa L.) serves both as a model organism for genetic studies and as an important component of the global food system. Studies in rice ionomics have primarily focused on above ground tissues evaluated from field-grown plants. Here, we describe a comprehensive study of the genetic basis of the rice ionome in both roots and shoots of 6-week-old rice plants for 20 elements using a controlled hydroponics growth system. Building on the wealth of publicly available rice genomic resources, including a panel of 373 diverse rice lines, 4.8 M genome-wide single-nucleotide polymorphisms, single- and multi-marker analysis pipelines, an extensive tome of 321 candidate genes and legacy QTLs from across 15 years of rice genetics literature, we used genome-wide association analysis and biparental QTL analysis to identify 114 genomic regions associated with ionomic variation. The genetic basis for root and shoot ionomes was highly distinct; 78 loci were associated with roots and 36 loci with shoots, with no overlapping genomic regions for the same element across tissues. We further describe the distribution of phenotypic variation across haplotypes and identify candidate genes within highly significant regions associated with sulfur, manganese, cadmium, and molybdenum. Our analysis provides critical insight into the genetic basis of natural phenotypic variation for both root and shoot ionomes in rice and provides a comprehensive resource for dissecting and testing causal genetic variants.

Genetic basis of lacunar stroke: a pooled analysis of individual patient data and genome-wide association studies

SummaryBackgroundThe genetic basis of lacunar stroke is poorly understood, with a single locus on 16q24 identified to date. We sought to identify novel associations and provide mechanistic insights into the disease.MethodsWe did a pooled analysis of data from newly recruited patients with an MRI-confirmed diagnosis of lacunar stroke and existing genome-wide association studies (GWAS). Patients were recruited from hospitals in the UK as part of the UK DNA Lacunar Stroke studies 1 and 2 and from collaborators within the International Stroke Genetics Consortium. Cases and controls were stratified by ancestry and two meta-analyses were done: a European ancestry analysis, and a transethnic analysis that included all ancestry groups. We also did a multi-trait analysis of GWAS, in a joint analysis with a study of cerebral white matter hyperintensities (an aetiologically related radiological trait), to find additional genetic associations. We did a transcriptome-wide association study (TWAS) to detect genes for which expression is associated with lacunar stroke; identified significantly enriched pathways using multi-marker analysis of genomic annotation; and evaluated cardiovascular risk factors causally associated with the disease using mendelian randomisation.FindingsOur meta-analysis comprised studies from Europe, the USA, and Australia, including 7338 cases and 254 798 controls, of which 2987 cases (matched with 29 540 controls) were confirmed using MRI. Five loci (ICA1L-WDR12-CARF-NBEAL1, ULK4, SPI1-SLC39A13-PSMC3-RAPSN, ZCCHC14, ZBTB14-EPB41L3) were found to be associated with lacunar stroke in the European or transethnic meta-analyses. A further seven loci (SLC25A44-PMF1-BGLAP, LOX-ZNF474-LOC100505841, FOXF2-FOXQ1, VTA1-GPR126, SH3PXD2A, HTRA1-ARMS2, COL4A2) were found to be associated in the multi-trait analysis with cerebral white matter hyperintensities (n=42 310). Two of the identified loci contain genes (COL4A2 and HTRA1) that are involved in monogenic lacunar stroke. The TWAS identified associations between the expression of six genes (SCL25A44, ULK4, CARF, FAM117B, ICA1L, NBEAL1) and lacunar stroke. Pathway analyses implicated disruption of the extracellular matrix, phosphatidylinositol 5 phosphate binding, and roundabout binding (false discovery rate <0·05). Mendelian randomisation analyses identified positive associations of elevated blood pressure, history of smoking, and type 2 diabetes with lacunar stroke.InterpretationLacunar stroke has a substantial heritable component, with 12 loci now identified that could represent future treatment targets. These loci provide insights into lacunar stroke pathogenesis, highlighting disruption of the vascular extracellular matrix (COL4A2, LOX, SH3PXD2A, GPR126, HTRA1), pericyte differentiation (FOXF2, GPR126), TGF-β signalling (HTRA1), and myelination (ULK4, GPR126) in disease risk.FundingBritish Heart Foundation.

Investigating pollination strategies in disturbed habitats: the case of the narrow-endemic toadflax Linaria tonzigii (Plantaginaceae) on mountain screes

Plant mating systems may reflect an adaptation to a habitat type, with self-pollination being potentially common in unstable and disturbed conditions. We investigated the reproductive ecology of an Alpine, narrow-range toadflax, Linaria tonzigii Lona (Plantaginaceae), occurring in steep and dynamic mountain screes. We explored self-compatibility and spontaneous autogamy, seed viability, daily nectar production, pollinator behaviour and pollen transfer in wild populations, using hand pollination treatments, quantification of nectar volume, viability Tetrazolium assay, active pollinator sampling and video recordings, and UV-bright dust for pollen substitution. After ex novo sequencing of several genetic regions of L. tonzigii, we performed a multi-marker phylogenetic analysis of 140 Linaria species and tracked the occurrence of the self-compatibility trait. Our results showed that this species is self-compatible, pollinated mostly via spontaneous autogamy and pollinator-mediated geitonogamy, and self-pollinated seeds are as viable as cross-pollinated ones. Selfing could be due to pollinator rarity because, despite the studied species providing a high nectar volume, wild bees, moths and small beetles infrequently visited its flowers in the sparsely vegetated scree slopes. In addition, a preliminary survey showed a low genetic haplotype diversity in the study plant. Moreover, the phylogeny shows that self-compatibility is scattered in the tree, suggesting the adaptive nature of this reproductive trait in the genus Linaria. This study supports for theories that high prevalence of selfing is an adaptation to environments unfavourable for cross-pollination, and particularly where pollinators are rare, such as in perturbed, poorly vegetated high-elevation habitats.

Iterative Variable Selection for High-Dimensional Data: Prediction of Pathological Response in Triple-Negative Breast Cancer

Over the last decade, regularized regression methods have offered alternatives for performing multi-marker analysis and feature selection in a whole genome context. The process of defining a list of genes that will characterize an expression profile remains unclear. It currently relies upon advanced statistics and can use an agnostic point of view or include some a priori knowledge, but overfitting remains a problem. This paper introduces a methodology to deal with the variable selection and model estimation problems in the high-dimensional set-up, which can be particularly useful in the whole genome context. Results are validated using simulated data and a real dataset from a triple-negative breast cancer study.

Detection of Melanoma Cells in Lymphatic Drainage (LD) After Lymph Nodes Dissection Via Nested RT-PCR Analysis of Molecular Melanocytic Markers.

We present the assay based on multimarker analysis of mRNA transcripts associated with melanocytic cells detected in lymphatic fluid collected after lymph node dissection. Positive results of reverse transcriptase polymerase chain reaction (RT-PCR) test have a strong relationship with melanoma recurrence and disease-specific survival time in stage III melanoma.

Added value of cerebrospinal fluid multimarker analysis in diagnosis and progression of dementia.

Recently, some emerging cerebrospinal fluid (CSF) markers have been proposed as diagnostic tools for Alzheimer disease (AD) that can have an effect on disease progression. We analyze the accuracy of these CSF markers for diagnosis of AD in reference to brain amyloid positron emission tomography (PET). We also investigated whether they help in differentiating AD from other dementias and examined their influence in tracing the progression to dementia. Amyloid-β (Aβ) 1-42, total tau (t-tau), phosphorylated tau, Aβ40 , Aβ38 , beta-site amyloid precursor protein cleaving enzyme 1 (BACE-1), neurogranin (ng), phosphorylated neurofilament heavy-chain, and α-synuclein (α-syn) CSF levels were analyzed in 319 subjects, among whom 57 also underwent an amyloid PET scan. We also analyzed longitudinal clinical data from 239 subjects. Emerging CSF markers, especially ng/BACE-1 ratio (area under the curve = 0.77) and their combinations with core AD CSF markers (all AUCs >0.85), showed high accuracy to discriminate amyloid PET positivity. Subjects with AD had higher CSF BACE-1, ng, and α-syn levels than those with non-AD dementia. CSF t-tau/α-syn ratio was higher in subjects with dementia with Lewy bodies than in those with frontotemporal dementia. Most emerging/core AD ratios predicted a faster conversion from mild cognitive impairment (MCI) stage to AD and appeared to be helpful when core AD CSF markers were discordant. In addition, the rate of cognitive decline was associated with all CSF core AD markers, several emerging/core AD two-marker ratios, and CSF ng levels. These results suggest that emerging biomarkers in conjunction with core AD markers improve diagnosis of AD, are associated with the conversion from MCI into AD, and predict a faster progression of dementia.

Germline variation in the insulin-like growth factor pathway and risk of Barrett's esophagus and esophageal adenocarcinoma.

Genome-wide association studies (GWAS) of esophageal adenocarcinoma (EAC) and its precursor, Barrett's esophagus (BE), have uncovered significant genetic components of risk, but most heritability remains unexplained. Targeted assessment of genetic variation in biologically relevant pathways using novel analytical approaches may identify missed susceptibility signals. Central obesity, a key BE/EAC risk factor, is linked to systemic inflammation, altered hormonal signaling and insulin-like growth factor (IGF) axis dysfunction. Here, we assessed IGF-related genetic variation and risk of BE and EAC. Principal component analysis was employed to evaluate pathway-level and gene-level associations with BE/EAC, using genotypes for 270 single-nucleotide polymorphisms (SNPs) in or near 12 IGF-related genes, ascertained from 3295 BE cases, 2515 EAC cases and 3207 controls in the Barrett's and Esophageal Adenocarcinoma Consortium (BEACON) GWAS. Gene-level signals were assessed using Multi-marker Analysis of GenoMic Annotation (MAGMA) and SNP summary statistics from BEACON and an expanded GWAS meta-analysis (6167 BE cases, 4112 EAC cases, 17 159 controls). Global variation in the IGF pathway was associated with risk of BE (P = 0.0015). Gene-level associations with BE were observed for GHR (growth hormone receptor; P = 0.00046, false discovery rate q = 0.0056) and IGF1R (IGF1 receptor; P = 0.0090, q = 0.0542). These gene-level signals remained significant at q < 0.1 when assessed using data from the largest available BE/EAC GWAS meta-analysis. No significant associations were observed for EAC. This study represents the most comprehensive evaluation to date of inherited genetic variation in the IGF pathway and BE/EAC risk, providing novel evidence that variation in two genes encoding cell-surface receptors, GHR and IGF1R, may influence risk of BE.