97 research outputs found
Identification of novel loci associated with hip shape: a meta-analysis of genomewide association studies
No full textAbstract not available.Denis A Baird, Daniel S Evans, Frederick K Kamanu, Jennifer S Gregory, Fiona R Saunders, Claudiu V Giuraniuc, Rebecca J Barr, Richard M Aspden, Deborah Jenkins, Douglas P Kiel, Eric S Orwoll, Steven R Cummings, Nancy E Lane, Benjamin H Mullin, Frances MK Williams, J Brent Richards, Scott G Wilson, Tim D Spector, Benjamin G Faber, Deborah A Lawlor, Elin Grundberg, Claes Ohlsson, Ulrika Pettersson-Kymmer, Terence D Capellini, Daniel Richard, Thomas J Beck, David M Evans, Lavinia Paternoster, David Karasik, and Jonathan H Tobia
Process evaluation for complex interventions in primary care: understanding trials using the normalization process model
No full textBackground: the Normalization Process Model is a conceptual tool intended to assist in understanding the factors that affect implementation processes in clinical trials and other evaluations of complex interventions. It focuses on the ways that the implementation of complex interventions is shaped by problems of workability and integration.Method: in this paper the model is applied to two different complex trials: (i) the delivery of problem solving therapies for psychosocial distress, and (ii) the delivery of nurse-led clinics for heart failure treatment in primary care.Results: application of the model shows how process evaluations need to focus on more than the immediate contexts in which trial outcomes are generated. Problems relating to intervention workability and integration also need to be understood. The model may be used effectively to explain the implementation process in trials of complex interventions.Conclusion: the model invites evaluators to attend equally to considering how a complex intervention interacts with existing patterns of service organization, professional practice, and professional-patient interaction. The justification for this may be found in the abundance of reports of clinical effectiveness for interventions that have little hope of being implemented in real healthcare setting
Genome-wide association summary statistics for back pain
No full text<p>The dataset contains results of a genome-wide association study of back pain. Two files contain association summary statistics for discovery GWAS based on the analysis of 350,000 white British individuals from the UK Biobank and meta-analysis GWAS based on the meta-analysis of the same 350,000 individuals and additional 103,862 individuals of European Ancestry from the UK biobank (total N = 453,862). The phenotype of back pain was defined by the answer provided by the UK biobank participants to the following question: "Pain type(s) experienced in last month". Those who reported “Back pain”, were considered as cases, all the rest were considered as controls. Individuals who did not reply or replied: "Prefer not to answer" or "Pain all over the body" were excluded. This dataset is also available for graphical exploration in the genomic context at <a href="http://gwasarchive.org/">http://gwasarchive.org</a>. </p>
<p>The data are provided on an "AS-IS" basis, without warranty of any type, expressed or implied, including but not limited to any warranty as to their performance, merchantability, or fitness for any particular purpose. If investigators use these data, any and all consequences are entirely their responsibility. By downloading and using these data, you agree that you will cite the appropriate publication in any communications or publications arising directly or indirectly from these data; for utilisation of data available prior to publication, you agree to respect the requested responsibilities of resource users under 2003 Fort Lauderdale principles; you agree that you will never attempt to identify any participant. This research has been conducted using the UK Biobank Resource and the use of the data is guided by the principles formulated by the UK Biobank.</p>
<p><strong>When using downloaded data, please cite corresponding paper and this repository:</strong></p>
<ol>
<li>Insight into the genetic architecture of back pain and its risk factors from a study of 509,000 individuals. Freidin, Maxim; Tsepilov, Yakov; Palmer, Melody; Karssen, Lennart; Suri, Pradeep; Aulchenko, Yurii; Williams, Frances MK,# CHARGE Musculoskeletal Working Group. PAIN: February 06, 2019 - Volume Articles in Press - Issue - p<br>
doi: 10.1097/j.pain.0000000000001514</li>
<li>Maxim B Freidin, Yakov A Tsepilov, Melody Palmer, Lennart Karssen, CHARGE Musculoskeletal Working Group, Pradeep Suri, … Frances MK Williams. (2018). Genome-wide association summary statistics for back pain (Version 1) [Data set]. Zenodo. http://doi.org/10.5281/zenodo.1319332</li>
</ol>
<p><strong>Funding:</strong></p>
<p>This study was supported by the European Community’s Seventh Framework Programme funded project PainOmics (Grant agreement # 602736). <br>
The research has been conducted using the UK Biobank Resource (project # 18219).</p>
<p>The development of software implementing SMR/HEIDI test and database for GWAS results was supported by the Russian Ministry of Science and Education under the 5-100 Excellence Program”.</p>
<p>Dr. Suri’s time for this work was supported by VA Career Development Award # 1IK2RX001515 from the United States (U.S.) Department of Veterans Affairs Rehabilitation Research and Development Service. The contents of this work do not represent the views of the U.S. Department of Veterans Affairs or the United States Government.</p>
<p>Dr. Tsepilov’s time for this work was supported in part by the Russian Ministry of Science and Education under the 5-100 Excellence Program.</p>
<p><strong>Column headers - discovery (350K)</strong></p>
<ol>
<li>CHR: chromosome</li>
<li>POS: position (GRCh37 build) </li>
<li>ID: SNP rsID</li>
<li>REF: reference allele (coded as "0")</li>
<li>ALT: effect allele (coded as "1")</li>
<li>CASE_ALLELE_CT: allele observation count in cases</li>
<li>CTRL_ALLELE_CT: allele observation count in controls</li>
<li>ALT_FREQ: effect allele frequency </li>
<li>MACH_R2: imputation quality</li>
<li>TEST: model of association test (additive)</li>
<li>OBS_CT: sample size</li>
<li>BETA: effect size of effect allele</li>
<li>SE: standard error of effect size</li>
<li>T_STAT: Z-value of effect allele</li>
<li>P: P-value of association (without GC correction)</li>
<li>MAF: minor allele frequency</li>
</ol>
<p><strong>Column headers - meta-analysis (450K)</strong></p>
<ol>
<li>MarkerName: SNP rsID</li>
<li>Allele1: effect allele (coded as "1")</li>
<li>Allele2: reference allele (coded as "0")</li>
<li>Freq1: effect allele frequency</li>
<li>FreqSE: standard error of effect allele frequency</li>
<li>Effect: effect size of effect allele</li>
<li>StdErr: standard error of effect size</li>
<li>P-value: P-value of association (without GC correction)</li>
<li>Direction: sign of effect in discovery and replication samples</li>
<li>n_total: Total sample size</li>
<li>CHR: chromosome</li>
<li>POS: position (GRCh37 build) </li>
<li>MACH_R2_discovery: imputation quality in discovery sample</li>
</ol>
OLSIA: Open Lumbar Spine Image Analysis - A 3D Slicer Extension for Segmentation, Grading, and Intervertebral Disc Height Index with Multi-Dataset Validation
No full textAbstract
Study Design:
Retrospective and cross-sectional study
Objective:
The study aims to develop an open software for lumbar spine image analysis enabling no-code approach to lumbar spine segmentation, grading, and intervertebral disc height index (DHI) calculations with robust evaluation of the application on six external datasets from diverse geographical regions.
Summary of data:
The datasets used include NFBC1966 (Finland), HKDDC (Hong Kong), TwinsUK (UK), CETIR (Spain), NCSD (Hungary), SPIDER (Netherlands), and Mendeley (global). Thirty participants from each dataset were sampled for external evaluation and NFBC1966 was used for training. Annotation was performed on T2-weighted mid-sagittal slices of vertebral bodies L1-S1 and intervertebral discs L1/2-L5/S1.
Materials and Methods:
Open Lumbar Spine Image Analysis (OLSIA) application was developed to include no-code approach tools for automated segmentation, grading, DHI calculation, and batch processing capabilities by integrating the deep learning (DL) models. DL models were trained on the NFBC1966 dataset with augmentation (histogram clipping, median filtering, geometric scaling) to improve generalization. Inter-rater agreement was assessed using Dice similarity coefficient (DSC), Bland-Altman (BA) analysis for DHI measurements and a paired t-test for statistical significance.
Results:
Our application demonstrated 222-fold improvement in processing time compared to performing manually lumbar spine segmentation, grading and DHI calculation tasks. OLSIA’s segmentation performance exhibited close correspondence with the inter-rater agreement across all six external datasets. Inter-rater reliability was high (mean DSC>90). Although paired t-test on DHI measurements is significant (P<0.05), the mean difference (0.02) of DHI from the BA plots indicates low systematic bias.
Conclusion:
We introduced OLSIA, a user-friendly interface for lumbar spine segmentation, grading, and intervertebral DHI calculation. OLSIA empowers researchers from diverse backgrounds to efficiently use the no-code tools to accelerate their radiomics and lumbar spine image analysis workflows.Abstract
Study Design:
Retrospective and cross-sectional study
Objective:
The study aims to develop an open software for lumbar spine image analysis enabling no-code approach to lumbar spine segmentation, grading, and intervertebral disc height index (DHI) calculations with robust evaluation of the application on six external datasets from diverse geographical regions.
Summary of data:
The datasets used include NFBC1966 (Finland), HKDDC (Hong Kong), TwinsUK (UK), CETIR (Spain), NCSD (Hungary), SPIDER (Netherlands), and Mendeley (global). Thirty participants from each dataset were sampled for external evaluation and NFBC1966 was used for training. Annotation was performed on T2-weighted mid-sagittal slices of vertebral bodies L1-S1 and intervertebral discs L1/2-L5/S1.
Materials and Methods:
Open Lumbar Spine Image Analysis (OLSIA) application was developed to include no-code approach tools for automated segmentation, grading, DHI calculation, and batch processing capabilities by integrating the deep learning (DL) models. DL models were trained on the NFBC1966 dataset with augmentation (histogram clipping, median filtering, geometric scaling) to improve generalization. Inter-rater agreement was assessed using Dice similarity coefficient (DSC), Bland-Altman (BA) analysis for DHI measurements and a paired t-test for statistical significance.
Results:
Our application demonstrated 222-fold improvement in processing time compared to performing manually lumbar spine segmentation, grading and DHI calculation tasks. OLSIA’s segmentation performance exhibited close correspondence with the inter-rater agreement across all six external datasets. Inter-rater reliability was high (mean DSC>90). Although paired t-test on DHI measurements is significant (P<0.05), the mean difference (0.02) of DHI from the BA plots indicates low systematic bias.
Conclusion:
We introduced OLSIA, a user-friendly interface for lumbar spine segmentation, grading, and intervertebral DHI calculation. OLSIA empowers researchers from diverse backgrounds to efficiently use the no-code tools to accelerate their radiomics and lumbar spine image analysis workflows
Genome-wide association summary statistics for back pain
No full textThe dataset contains results of a genome-wide association study of back pain. Two files contain association summary statistics for discovery GWAS based on the analysis of 350,000 white British individuals from the UK Biobank and meta-analysis GWAS based on the meta-analysis of the same 350,000 individuals and additional 103,862 individuals of European Ancestry from the UK biobank (total N = 453,862). The phenotype of back pain was defined by the answer provided by the UK biobank participants to the following question: "Pain type(s) experienced in last month". Those who reported “Back pain”, were considered as cases, all the rest were considered as controls. Individuals who did not reply or replied: "Prefer not to answer" or "Pain all over the body" were excluded. This dataset is also available for graphical exploration in the genomic context at http://gwasarchive.org. The data are provided on an "AS-IS" basis, without warranty of any type, expressed or implied, including but not limited to any warranty as to their performance, merchantability, or fitness for any particular purpose. If investigators use these data, any and all consequences are entirely their responsibility. By downloading and using these data, you agree that you will cite the appropriate publication in any communications or publications arising directly or indirectly from these data; for utilisation of data available prior to publication, you agree to respect the requested responsibilities of resource users under 2003 Fort Lauderdale principles; you agree that you will never attempt to identify any participant. This research has been conducted using the UK Biobank Resource and the use of the data is guided by the principles formulated by the UK Biobank. When using downloaded data, please cite corresponding paper and this repository: Insight into the genetic architecture of back pain and its risk factors from a study of 509,000 individuals. Freidin, Maxim; Tsepilov, Yakov; Palmer, Melody; Karssen, Lennart; Suri, Pradeep; Aulchenko, Yurii; Williams, Frances MK,# CHARGE Musculoskeletal Working Group. PAIN: February 06, 2019 - Volume Articles in Press - Issue - p doi: 10.1097/j.pain.0000000000001514 Maxim B Freidin, Yakov A Tsepilov, Melody Palmer, Lennart Karssen, CHARGE Musculoskeletal Working Group, Pradeep Suri, … Frances MK Williams. (2018). Genome-wide association summary statistics for back pain (Version 1) [Data set]. Zenodo. http://doi.org/10.5281/zenodo.1319332 Funding: This study was supported by the European Community’s Seventh Framework Programme funded project PainOmics (Grant agreement # 602736). The research has been conducted using the UK Biobank Resource (project # 18219). The development of software implementing SMR/HEIDI test and database for GWAS results was supported by the Russian Ministry of Science and Education under the 5-100 Excellence Program”. Dr. Suri’s time for this work was supported by VA Career Development Award # 1IK2RX001515 from the United States (U.S.) Department of Veterans Affairs Rehabilitation Research and Development Service. The contents of this work do not represent the views of the U.S. Department of Veterans Affairs or the United States Government. Dr. Tsepilov’s time for this work was supported in part by the Russian Ministry of Science and Education under the 5-100 Excellence Program. Column headers - discovery (350K) CHR: chromosome POS: position (GRCh37 build) ID: SNP rsID REF: reference allele (coded as "0") ALT: effect allele (coded as "1") CASE_ALLELE_CT: allele observation count in cases CTRL_ALLELE_CT: allele observation count in controls ALT_FREQ: effect allele frequency MACH_R2: imputation quality TEST: model of association test (additive) OBS_CT: sample size BETA: effect size of effect allele SE: standard error of effect size T_STAT: Z-value of effect allele P: P-value of association (without GC correction) MAF: minor allele frequency Column headers - meta-analysis (450K) MarkerName: SNP rsID Allele1: effect allele (coded as "1") Allele2: reference allele (coded as "0") Freq1: effect allele frequency FreqSE: standard error of effect allele frequency Effect: effect size of effect allele StdErr: standard error of effect size P-value: P-value of association (without GC correction) Direction: sign of effect in discovery and replication samples n_total: Total sample size CHR: chromosome POS: position (GRCh37 build) MACH_R2_discovery: imputation quality in discovery sample {"references": ["10.1097/j.pain.0000000000001514"]
A new 5-lipoxygenase inhibitor seems to be safe and effective for the treatment of osteoarthritis
No full textThere is a clear need for both disease-modifying agents and alternative analgesic therapies in osteoarthritis. Currently, there are none of the former, and the latter are limited by adverse effects, particularly gastrointestinal and cardiovascular effects. A new class of analgesic agent that is under investigation inhibits 5-lipoxygenase (5-LOX), the enzyme that catalyzes the conversion of membrane-bound arachidonic acid to leukotrienes. As leukotrienes are implicated in a wide variety of pathologies, the potential of 5-LOX inhibitors has been explored in conditions as diverse as asthma, acute mountain sickness and coronary artery disease. A new 5-LOX inhibitor, derived from a herb, has undergone a phase II trial in osteoarthritis with promising results. Although a putative mechanism of action suggests a disease-modifying effect, the important outcomes from this trial are good symptom response and a low adverse effect profile, albeit in the small number of patients studied
Effect of praziquantel treatment of Schistosoma mansoni during pregnancy on immune responses to schistosome antigens among the offspring: results of a randomised, placebo-controlled trial.
No full textBACKGROUND: Offspring of women with schistosomiasis may exhibit immune responsiveness to schistosomes due to in utero sensitisation or trans-placental transfer of antibodies. Praziquantel treatment during pregnancy boosts maternal immune responses to schistosome antigens and reduces worm burden. Effects of praziquantel treatment during pregnancy on responses among offspring are unknown. METHODS: In a trial of anthelminthic treatment during pregnancy in Uganda (ISRCTN32849447; http://www.controlled-trials.com/ISRCTN32849447/elliott), offspring of women with Schistosoma mansoni were examined for cytokine and antibody responses to schistosome worm (SWA) and egg (SEA) antigen, in cord blood and at age one year. Relationships to maternal responses and pre-treatment infection intensities were examined, and responses were compared between the offspring of women who did, or did not receive praziquantel treatment during pregnancy. RESULTS: Of 388 S. mansoni-infected women studied, samples were obtained at age one year from 215 of their infants. Stool examination for S. mansoni eggs was negative for all infants. Cord and infant samples were characterised by very low cytokine production in response to schistosome antigens with the exception of cord IL-10 responses, which were substantial. Cord and infant cytokine responses showed no association with maternal responses. As expected, cord blood levels of immunoglobulin (Ig) G to SWA and SEA were high and correlated with maternal antibodies. However, by age one year IgG levels had waned and were hardly detectable. Praziquantel treatment during pregnancy showed no effect on cytokine responses or antibodies levels to SWA or SEA either in cord blood or at age one year, except for IgG1 to SWA, which was elevated in infants of treated mothers, reflecting maternal levels. There was some evidence that maternal infection intensity was positively associated with cord blood IL-5 and IL-13 responses to SWA, and IL-5 responses to SEA, and that this association was modified by treatment with praziquantel. CONCLUSIONS: Despite strong effects on maternal infection intensity and maternal immune responses, praziquantel treatment of infected women during pregnancy had no effect on anti-schistosome immune responses among offspring by age one year. Whether the treatment will impact upon the offspring's responses on exposure to primary schistosome infection remains to be elucidated. TRIAL REGISTRATION: ISRCTN: ISRCTN32849447
Tables S2-S3. SMR-HEIDI results for 8q24.21 locus between back pain and other phenotypes.
No full textSupplementary Table S2. SMR-HEIDI results for 8q24.21 locus between back pain and other complex traits.
Column headers of Tables S2:
Secondary Trait Name: Name of complex trait
Dataset: Name of dataset (UKB Neale's lab or UKB Gene Atlas)
Index_SNP: RsID of SNP used as target in SMR-HEID analysis
Proxy_SNP: RsID of top SNP in the selected locus - SNP presented in both GWAS data with minimum P-values in back pain GWAS
r(proxy_SNP,index_SNP): linkage disequilibrium coefficient between index and proxy SNP
beta_SMR: Beta SMR for proxy SNP
p_SMR: P-value of beta SMR
qFDR-BH SMR: P-value of beta SMR after Bonferroni correction
p_HEIDI: P-value of HEIDI test
n_HEIDI: Number of SNPs used in HEIDI test
SNPs_HEIDI: List of rsID of SNPs used in HEIDI test
Supplementary Table S3. SMR-HEIDI results for 8q24.21 locus between back pain and expression of genes.
Column headers of Tables S3:
Secondary Trait Name: Name of complex trait
Tissue: Name of the tissue from which the samples were taken to study gene expression
Gene_name: Gene name corresponding to the transcript name
Transcript Name: Transcript name (ID)
Dataset: Name of dataset (CEDAR, GTEx_v6)
beta_SMR: Beta SMR for proxy SNP
p_SMR: P-value of beta SMR
qFDR-BH SMR: P-value of beta SMR after Bonferroni correction
p_HEIDI: P-value of HEIDI test
n_HEIDI: Number of SNPs used in HEIDI test
SNPs_HEIDI: List of rsID of SNPs used in HEIDI test
Part of the article: Williams FMK et al. "Sequence variation at 8q24.21 and risk of back pain"</p
Are intra-articular injections of hylan more effective than injections of hyaluronic acid for knee osteoarthritis?
No full textLong-chain omega-3 polyunsaturated fatty acids in relation to gut integrity, growth and cognitive development of rural African children
No full textBackground
and
rationale:
Weaning
foods
fed
to
infants
in
rural
Gambia
are
often
contaminated,
resulting
in
infections
which
contribute
to
initiating
a
persistent
inflammation
of
the
gut.
This
enteropathy,
which
causes
intestinal
damage
and
malabsorption,
is
strongly
associated
with
the
high
degree
of
growth
faltering
seen
in
Gambian
infants.
There
is
evidence
that
supplementary
omega-3
long-chain
polyunsaturated
fatty
acids
(n-3
LCPs)
might
ameliorate
this
damage
by
reducing
gastro-intestinal
inflammation.
Additionally,
n-3
LCPs
have
been
shown
to
benefit
mental
development
and
problem-solving
ability
in
infants,
but
this
has
not
yet
been
tested
in
an
African
population.
Methods:
A
randomised,
double-blind,
controlled
trial
(500mg
combined
n-3
LCPs
per
day
for
six
months)
was
conducted
in
a
population
of
rural
African
infants
aged
3
months
-
9
months.
The
primary
outcomes
were
infant
anthropometric
indicators
and
gut
integrity
(measured
by
urinary
lactulose-mannitol
ratios).
Plasma
fatty
acid
status
(plasma
fatty
acid
profiles),
cognitive
development
(Willatts
Test
and
an
attention
assessment
at
12
months
of
age),
intestinal
mucosal
inflammation
(faecal
calprotectin),
and
daily
morbidities
were
the
secondary
outcome
measures.
Results:
One-hundred
and
seventy-two
Gambian
infants
completed
the
trial.
Except
for
an
increase
in
mid-upper-arm
circumference
z-scores
in
the
intervention
group
(95%
Cl:
0.06,0.56;
p=0.017),
no
significant
differences
between
treatment
groups
were
detected
for
growth
and
lactulose-mannitol
ratios
at
9
months.
At
12
months
mid-upper-arm
circumference
remained
greater
in
the
intervention
group,
and
significant
increases
in
skinfold
thicknesses
were
detected
(pSO.022
for
ali).
Supplementation
resulted
in
a
significant
increase
in
plasma
n-3
LCP
levels
(p<O.001)
and
decrease
in
n-6
LCP:n-3
LCP
ratios
(p<O.OOl).
Plasma
n-6
fatty
acid
levels
were
not
affected.
No
difference
was
detected
for
the
other
secondary
outcomes.
Conclusion:
Fish
oil
supplementation
proved
safe
and
successfully
increased
plasma
n-3
fatty
acid
status,
but
the
results
of
this
trial
do
not
support
the
use
of
supplementary
n-3
LCPs
in
young,
breast-fed,
rural
Gambian
infants
for
improving
overall
growth
performance,
intestinal
integrity,
and
cognitive
development,
or
reducing
intestinal
and
systemic
inflammatio
- …
