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The big book of useless knowledge : 250 of the coolest, weirdest, and most unbelievable facts you won't be taught in school
An illustrated compendium of mind-bogglingly random facts you won't be taught in school.
CHILDBOOK
Exome sequencing and analysis of 454,787 UK Biobank participants
A major goal in human genetics is to use natural variation to understand the phenotypic consequences of altering each protein-coding gene in the genome. Here we used exome sequencing
1
to explore protein-altering variants and their consequences in 454,787 participants in the UK Biobank study
2
. We identified 12 million coding variants, including around 1 million loss-of-function and around 1.8 million deleterious missense variants. When these were tested for association with 3,994 health-related traits, we found 564 genes with trait associations at
P
≤ 2.18 × 10
−11
. Rare variant associations were enriched in loci from genome-wide association studies (GWAS), but most (91%) were independent of common variant signals. We discovered several risk-increasing associations with traits related to liver disease, eye disease and cancer, among others, as well as risk-lowering associations for hypertension (
SLC9A3R2
), diabetes (
MAP3K15
,
FAM234A
) and asthma (
SLC27A3
). Six genes were associated with brain imaging phenotypes, including two involved in neural development (
GBE1
,
PLD1
). Of the signals available and powered for replication in an independent cohort, 81% were confirmed; furthermore, association signals were generally consistent across individuals of European, Asian and African ancestry. We illustrate the ability of exome sequencing to identify gene–trait associations, elucidate gene function and pinpoint effector genes that underlie GWAS signals at scale.
Whole-exome sequencing analysis of 454,787 individuals in the UK Biobank is used to examine the association of protein-coding variants with nearly 4,000 health-related traits, identifying 564 distinct genes with significant trait associations.
Journal Article
Full-Quantum Treatment of Molecular Systems Confirms Novel Supracence Photonic Properties
Our understanding of molecules has stagnated at a single quantum system, with atoms as Newtonian particles and electrons as quantum particles. Here, however, we reveal that both atoms and electrons in a molecule are quantum particles, and their quantum–quantum interactions create a previously unknown, newfangled molecular property—supracence. Molecular supracence is a phenomenon in which the molecule transfers its potential energy from quantum atoms to photo-excited electrons so that the emitted photon has more energy than that of the absorbed one. Importantly, experiments reveal such quantum energy exchanges are independent of temperature. When quantum fluctuation results in absorbing low-energy photons, yet still emitting high-energy photons, supracence occurs. This report, therefore, reveals novel principles governing molecular supracence via experiments that were rationalized by full quantum (FQ) theory. This advancement in understanding predicts the super-spectral resolution of supracence, and molecular imaging confirms such innovative forecasts using closely emitting rhodamine 123 and rhodamine B in living cell imaging of mitochondria and endosomes.
Journal Article
A Protein-Truncating HSD17B13 Variant and Protection from Chronic Liver Disease
A genetic variant conferring a loss of function on the enzyme hydroxysteroid 17-beta dehydrogenase 13, expressed in the membrane surrounding the hepatic lipid droplet, was associated with a reduced risk of chronic liver disease.
Journal Article
Genome-wide analysis provides genetic evidence that ACE2 influences COVID-19 risk and yields risk scores associated with severe disease
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) enters human host cells via angiotensin-converting enzyme 2 (ACE2) and causes coronavirus disease 2019 (COVID-19). Here, through a genome-wide association study, we identify a variant (rs190509934, minor allele frequency 0.2–2%) that downregulates
ACE2
expression by 37% (
P
= 2.7 × 10
−
8
) and reduces the risk of SARS-CoV-2 infection by 40% (odds ratio = 0.60,
P
= 4.5 × 10
−
13
), providing human genetic evidence that ACE2 expression levels influence COVID-19 risk. We also replicate the associations of six previously reported risk variants, of which four were further associated with worse outcomes in individuals infected with the virus (in/near
LZTFL1
, MHC,
DPP9
and
IFNAR2
). Lastly, we show that common variants define a risk score that is strongly associated with severe disease among cases and modestly improves the prediction of disease severity relative to demographic and clinical factors alone.
Genome-wide meta-analysis of SARS-CoV-2 susceptibility and severity phenotypes in up to 756,646 samples identifies a rare protective variant proximal to
ACE2
. A 6-SNP genetic risk score provides additional predictive power when added to known risk factors.
Journal Article
BIDS apps: Improving ease of use, accessibility, and reproducibility of neuroimaging data analysis methods
The rate of progress in human neurosciences is limited by the inability to easily apply a wide range of analysis methods to the plethora of different datasets acquired in labs around the world. In this work, we introduce a framework for creating, testing, versioning and archiving portable applications for analyzing neuroimaging data organized and described in compliance with the Brain Imaging Data Structure (BIDS). The portability of these applications (BIDS Apps) is achieved by using container technologies that encapsulate all binary and other dependencies in one convenient package. BIDS Apps run on all three major operating systems with no need for complex setup and configuration and thanks to the comprehensiveness of the BIDS standard they require little manual user input. Previous containerized data processing solutions were limited to single user environments and not compatible with most multi-tenant High Performance Computing systems. BIDS Apps overcome this limitation by taking advantage of the Singularity container technology. As a proof of concept, this work is accompanied by 22 ready to use BIDS Apps, packaging a diverse set of commonly used neuroimaging algorithms.
Journal Article
Exome sequencing and characterization of 49,960 individuals in the UK Biobank
The UK Biobank is a prospective study of 502,543 individuals, combining extensive phenotypic and genotypic data with streamlined access for researchers around the world
1
. Here we describe the release of exome-sequence data for the first 49,960 study participants, revealing approximately 4 million coding variants (of which around 98.6% have a frequency of less than 1%). The data include 198,269 autosomal predicted loss-of-function (LOF) variants, a more than 14-fold increase compared to the imputed sequence. Nearly all genes (more than 97%) had at least one carrier with a LOF variant, and most genes (more than 69%) had at least ten carriers with a LOF variant. We illustrate the power of characterizing LOF variants in this population through association analyses across 1,730 phenotypes. In addition to replicating established associations, we found novel LOF variants with large effects on disease traits, including
PIEZO1
on varicose veins,
COL6A1
on corneal resistance,
MEPE
on bone density, and
IQGAP2
and
GMPR
on blood cell traits. We further demonstrate the value of exome sequencing by surveying the prevalence of pathogenic variants of clinical importance, and show that 2% of this population has a medically actionable variant. Furthermore, we characterize the penetrance of cancer in carriers of pathogenic
BRCA1
and
BRCA2
variants. Exome sequences from the first 49,960 participants highlight the promise of genome sequencing in large population-based studies and are now accessible to the scientific community.
Exome sequences from the first 49,960 participants in the UK Biobank highlight the promise of genome sequencing in large population-based studies and are now accessible to the scientific community.
Journal Article
Genetics of blood lipids among ~300,000 multi-ethnic participants of the Million Veteran Program
The Million Veteran Program (MVP) was established in 2011 as a national research initiative to determine how genetic variation influences the health of US military veterans. Here we genotyped 312,571 MVP participants using a custom biobank array and linked the genetic data to laboratory and clinical phenotypes extracted from electronic health records covering a median of 10.0 years of follow-up. Among 297,626 veterans with at least one blood lipid measurement, including 57,332 black and 24,743 Hispanic participants, we tested up to around 32 million variants for association with lipid levels and identified 118 novel genome-wide significant loci after meta-analysis with data from the Global Lipids Genetics Consortium (total
n
> 600,000). Through a focus on mutations predicted to result in a loss of gene function and a phenome-wide association study, we propose novel indications for pharmaceutical inhibitors targeting PCSK9 (abdominal aortic aneurysm), ANGPTL4 (type 2 diabetes) and PDE3B (triglycerides and coronary disease).
Analysis of genetic data and blood lipid measurements from over 300,000 participants in the Million Veteran Program identifies new associations for blood lipid traits.
Journal Article
Using causal methods to map symptoms to brain circuits in neurodevelopment disorders: moving from identifying correlates to developing treatments
A wide variety of model systems and experimental techniques can provide insight into the structure and function of the human brain in typical development and in neurodevelopmental disorders. Unfortunately, this work, whether based on manipulation of animal models or observational and correlational methods in humans, has a high attrition rate in translating scientific discovery into practicable treatments and therapies for neurodevelopmental disorders.
With new computational and neuromodulatory approaches to interrogating brain networks, opportunities exist for “bedside-to bedside-translation” with a potentially shorter path to therapeutic options. Specifically, methods like lesion network mapping can identify brain networks involved in the generation of complex symptomatology, both from acute onset lesion-related symptoms and from focal developmental anomalies. Traditional neuroimaging can examine the generalizability of these findings to idiopathic populations, while non-invasive neuromodulation techniques such as transcranial magnetic stimulation provide the ability to do targeted activation or inhibition of these specific brain regions and networks. In parallel, real-time functional MRI neurofeedback also allow for endogenous neuromodulation of specific targets that may be out of reach for transcranial exogenous methods.
Discovery of novel neuroanatomical circuits for transdiagnostic symptoms and neuroimaging-based endophenotypes may now be feasible for neurodevelopmental disorders using data from cohorts with focal brain anomalies. These novel circuits, after validation in large-scale highly characterized research cohorts and tested prospectively using noninvasive neuromodulation and neurofeedback techniques, may represent a new pathway for symptom-based targeted therapy.
Journal Article
STEFA G03 – Joint collaborative exercise for document examination, DNA, fingerprints and handwriting
This article will describe the processes involved in developing the first pan-European multi-disciplinary forensic Collaborative Exercise (CE), focusing on the concepts, planning, design, preparation, implementation, co-ordination and evaluation of the CE. The results of this project demonstrate that it is feasible to develop and run a multi-discipline forensic Collaborative Exercise with results that can help to develop best practice and procedures for examining threatening letters in the future.
Journal Article