PECLIDES Neuro: A Personalisable Clinical Decision Support System for Neurological Diseases.

Neurodegenerative diseases such as Alzheimer's and Parkinson's impact millions of people worldwide. Early diagnosis has proven to greatly increase the chances of slowing down the diseases' progression. Correct diagnosis often relies on the analysis of large amounts of patient data, and thus lends itself well to support from machine learning algorithms, which are able to learn from past diagnosis and see clearly through the complex interactions of a patient's symptoms and data. Unfortunately, many contemporary machine learning techniques fail to reveal details about how they reach their conclusions, a property considered fundamental when providing a diagnosis. Here we introduce our Personalisable Clinical Decision Support System (PECLIDES), an algorithmic process formulated to address this specific fault in diagnosis detection. PECLIDES provides a clear insight into the decision-making process leading to a diagnosis, making it a gray box model. Our algorithm enriches the fundamental work of Masheyekhi and Gras in data integration, personal medicine, usability, visualization, and interactivity. Our decision support system is an operation of translational medicine. It is based on random forests, is personalisable and allows a clear insight into the decision-making process. A well-structured rule set is created and every rule of the decision-making process can be observed by the user (physician). Furthermore, the user has an impact on the creation of the final rule set and the algorithm allows the comparison of different diseases as well as regional differences in the same disease. The algorithm is applicable to various decision problems. In this paper we will evaluate it on diagnosing neurological diseases and therefore refer to the algorithm as PECLIDES Neuro

Explainable 2D Vision Models for 3D Medical Data

Training Artificial Intelligence (AI) models on three-dimensional image data presents unique challenges compared to the two-dimensional case: Firstly, the computational resources are significantly higher, and secondly, the availability of large pretraining datasets is often limited, impeding training success. In this study, we propose a simple approach of adapting 2D networks with an intermediate feature representation for processing 3D volumes. Our method involves sequentially applying these networks to slices of a 3D volume from all orientations. Subsequently, a feature reduction module combines the extracted slice features into a single representation, which is then used for classification. We evaluate our approach on medical classification benchmarks and a real-world clinical dataset, demonstrating comparable results to existing methods. Furthermore, by employing attention pooling as a feature reduction module we obtain weighted importance values for each slice during the forward pass. We show that slices deemed important by our approach allow the inspection of the basis of a model's prediction

Age-dependent clinical outcomes in primary versus oral anticoagulation-related intracerebral hemorrhage

Aims This study determined the influence of age on bleeding characteristics and clinical outcomes in primary spontaneous (non-OAC), vitamin K antagonist-related (VKA-) and non-vitamin K antagonist oral anticoagulant-related (NOAC-) ICH. Methods Pooled individual patient data of multicenter cohort studies were analyzed by logistic regression modelling and propensity-score-matching (PSM) to explore the influence of advanced age on clinical outcomes among non-OAC-, VKA-, and NOAC-ICH. Primary outcome measure was functional outcome at three months assessed by the modified Rankin Scale, dichotomized into favorable (mRS = 0–3) and unfavorable (mRS = 4–6) functional outcome. Secondary outcome measures included mortality, hematoma characteristics, and frequency of invasive interventions. Results In VKA-ICH 33.5% (670/2001), in NOAC-ICH 44.2% (69/156) and in non-OAC-ICH 25.2% (254/1009) of the patients were ≥80 years. After adjustment for treatment interventions and relevant parameters, elderly ICH patients comprised worse functional outcome at three months (adjusted odds ratio (aOR) in VKA-ICH: 1.49 (1.21–1.84); p < 0.001; NOAC-ICH: 2.01 (0.95–4.26); p = 0.069; non-OAC-ICH: 3.54 (2.50–5.03); p < 0.001). Anticoagulation was significantly associated with worse functional outcome below the age of 70 years, (aOR: 2.38 (1.78–3.16); p < 0.001), but not in patients of ≥70 years (aOR: 1.21 (0.89–1.65); p = 0.217). The differences in initial ICH volume and extent of ICH enlargement between OAC-ICH and non-OAC-ICH gradually decreased with increasing patient age. Conclusions As compared to elderly ICH-patients, in patients <70 years OAC-ICH showed worse clinical outcomes compared to non-OAC-ICH because of larger baseline ICH-volumes and extent of hematoma enlargement. Treatment strategies aiming at neutralizing altered coagulation should be aware of these findings

Genetic association study of QT interval highlights role for calcium signaling pathways in myocardial repolarization.

The QT interval, an electrocardiographic measure reflecting myocardial repolarization, is a heritable trait. QT prolongation is a risk factor for ventricular arrhythmias and sudden cardiac death (SCD) and could indicate the presence of the potentially lethal mendelian long-QT syndrome (LQTS). Using a genome-wide association and replication study in up to 100,000 individuals, we identified 35 common variant loci associated with QT interval that collectively explain ∼8-10% of QT-interval variation and highlight the importance of calcium regulation in myocardial repolarization. Rare variant analysis of 6 new QT interval-associated loci in 298 unrelated probands with LQTS identified coding variants not found in controls but of uncertain causality and therefore requiring validation. Several newly identified loci encode proteins that physically interact with other recognized repolarization proteins. Our integration of common variant association, expression and orthogonal protein-protein interaction screens provides new insights into cardiac electrophysiology and identifies new candidate genes for ventricular arrhythmias, LQTS and SCD

The challenges of genome-wide interaction studies: Lessons to learn from the analysis of HDL blood levels

Genome-wide association studies (GWAS) have revealed 74 single nucleotide polymorphisms (SNPs) associated with high-density lipoprotein cholesterol (HDL) blood levels. This study is, to our knowledge, the first genome-wide interaction study (GWIS) to identify SNP6SNP interactions associated with HDL levels. We performed a GWIS in the Rotterdam Study (RS) cohort I (RS-I) using the GLIDE tool which leverages the massively parallel computing power of Graphics Processing Units (GPUs) to perform linear regression on all genome-wide pairs of SNPs. By performing a meta-analysis together with Rotterdam Study cohorts II and III (RS-II and RS-III), we were able to filter 181 interaction terms with a p-value, 1 · 1028 that replicated in the two independent cohorts. We were not able to replicate any of these interaction term in the AGES, ARIC, CHS, ERF, FHS and NFBC-66 cohorts (Ntotal = 30, 011) when adjusting for multiple testing. Our GWIS resulted in the consistent finding of a possible interaction between rs774801 in ARMC8 (ENSG00000114098) and rs12442098 in SPATA8 (ENSG00000185594) being associated with HDL levels. However, p-values do not reach the preset Bonferroni correction of the p-values. Our study suggest that even for highly genetically determined traits such as HDL the sample sizes needed to detect SNP6SNP interactions are large and the 2-step filtering approaches do not yield a solution. Here we present our analysis plan and our reservations concerning GWIS

Hundreds of variants clustered in genomic loci and biological pathways affect human height

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

Synthetic Double-Stranded RNAs Are Adjuvants for the Induction of T Helper 1 and Humoral Immune Responses to Human Papillomavirus in Rhesus Macaques

Toll-like receptor (TLR) ligands are being considered as adjuvants for the induction of antigen-specific immune responses, as in the design of vaccines. Polyriboinosinic-polyribocytoidylic acid (poly I:C), a synthetic double-stranded RNA (dsRNA), is recognized by TLR3 and other intracellular receptors. Poly ICLC is a poly I:C analogue, which has been stabilized against the serum nucleases that are present in the plasma of primates. Poly I:C12U, another analogue, is less toxic but also less stable in vivo than poly I:C, and TLR3 is essential for its recognition. To study the effects of these compounds on the induction of protein-specific immune responses in an animal model relevant to humans, rhesus macaques were immunized subcutaneously (s.c.) with keyhole limpet hemocyanin (KLH) or human papillomavirus (HPV)16 capsomeres with or without dsRNA or a control adjuvant, the TLR9 ligand CpG-C. All dsRNA compounds served as adjuvants for KLH-specific cellular immune responses, with the highest proliferative responses being observed with 2 mg/animal poly ICLC (p = 0.002) or 6 mg/animal poly I:C12U (p = 0.001) when compared with immunization with KLH alone. Notably, poly ICLC—but not CpG-C given at the same dose—also helped to induce HPV16-specific Th1 immune responses while both adjuvants supported the induction of strong anti-HPV16 L1 antibody responses as determined by ELISA and neutralization assay. In contrast, control animals injected with HPV16 capsomeres alone did not develop substantial HPV16-specific immune responses. Injection of dsRNA led to increased numbers of cells producing the T cell–activating chemokines CXCL9 and CXCL10 as detected by in situ hybridization in draining lymph nodes 18 hours after injections, and to increased serum levels of CXCL10 (p = 0.01). This was paralleled by the reduced production of the homeostatic T cell–attracting chemokine CCL21. Thus, synthetic dsRNAs induce an innate chemokine response and act as adjuvants for virus-specific Th1 and humoral immune responses in nonhuman primates

Exome-chip meta-analysis identifies novel loci associated with cardiac conduction, including ADAMTS6.

BACKGROUND: Genome-wide association studies conducted on QRS duration, an electrocardiographic measurement associated with heart failure and sudden cardiac death, have led to novel biological insights into cardiac function. However, the variants identified fall predominantly in non-coding regions and their underlying mechanisms remain unclear. RESULTS: Here, we identify putative functional coding variation associated with changes in the QRS interval duration by combining Illumina HumanExome BeadChip genotype data from 77,898 participants of European ancestry and 7695 of African descent in our discovery cohort, followed by replication in 111,874 individuals of European ancestry from the UK Biobank and deCODE cohorts. We identify ten novel loci, seven within coding regions, including ADAMTS6, significantly associated with QRS duration in gene-based analyses. ADAMTS6 encodes a secreted metalloprotease of currently unknown function. In vitro validation analysis shows that the QRS-associated variants lead to impaired ADAMTS6 secretion and loss-of function analysis in mice demonstrates a previously unappreciated role for ADAMTS6 in connexin 43 gap junction expression, which is essential for myocardial conduction. CONCLUSIONS: Our approach identifies novel coding and non-coding variants underlying ventricular depolarization and provides a possible mechanism for the ADAMTS6-associated conduction changes.BH

Genetic Interactions with Age, Sex, Body Mass Index, and Hypertension in Relation to Atrial Fibrillation: The AFGen Consortium

It is unclear whether genetic markers interact with risk factors to influence atrial fibrillation (AF) risk. We performed genome-wide interaction analyses between genetic variants and age, sex, hypertension, and body mass index in the AFGen Consortium. Study-specific results were combined using meta-analysis (88,383 individuals of European descent, including 7,292 with AF). Variants with nominal interaction associations in the discovery analysis were tested for association in four independent studies (131,441 individuals, including 5,722 with AF). In the discovery analysis, the AF risk associated with the minor rs6817105 allele (at the PITX2 locus) was greater among subjects ≤ 65 years of age than among those > 65 years (interaction p-value = 4.0 × 10-5). The interaction p-value exceeded genome-wide significance in combined discovery and replication analyses (interaction p-value = 1.7 × 10-8). We observed one genome-wide significant interaction with body mass index and several suggestive interactions with age, sex, and body mass index in the discovery analysis. However, none was replicated in the independent sample. Our findings suggest that the pathogenesis of AF may differ according to age in individuals of European descent, but we did not observe evidence of statistically significant genetic interactions with sex, body mass index, or hypertension on AF risk

Discovery of novel heart rate-associated loci using the Exome Chip

Resting heart rate is a heritable trait, and an increase in heart rate is associated with increased mortality risk. Genome-wide association study analyses have found loci associated with resting heart rate, at the time of our study these loci explained 0.9% of the variation. This study aims to discover new genetic loci associated with heart rate from Exome Chip meta-analyses. Heart rate was measured from either elecrtrocardiograms or pulse recordings. We meta-analysed heart rate association results from 104 452 European-ancestry individuals from 30 cohorts, genotyped using the Exome Chip. Twenty-four variants were selected for follow-up in an independent dataset (UK Biobank, N = 134 251). Conditional and gene-based testing was undertaken, and variants were investigated with bioinformatics methods. We discovered five novel heart rate loci, and one new independent low-frequency non-synonymous variant in an established heart rate locus (KIAA1755). Lead variants in four of the novel loci are non-synonymous variants in the genes C10orf71, DALDR3, TESK2 and SEC31B. The variant at SEC31B is significantly associated with SEC31B expression in heart and tibial nerve tissue. Further candidate genes were detected from long-range regulatory chromatin interactions in heart tissue (SCD, SLF2 and MAPK8). We observed significant enrichment in DNase I hypersensitive sites in fetal heart and lung. Moreover, enrichment was seen for the first time in human neuronal progenitor cells (derived from embryonic stem cells) and fetal muscle samples by including our novel variants. Our findings advance the knowledge of the genetic architecture of heart rate, and indicate new candidate genes for follow-up functional studies