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8th April 2022
The use of an MRI-based deep learning algorithm has been shown to be superior to both amyloid and tau pathology biomarkers for the detection of prodromal Alzheimer’s disease (AD) according to a study by researchers from the Department of Biomedical Engineering, Columbia University, New York,
Alzheimer’s disease biomarkers play an important role in the early diagnosis of the disease and neuropathological hallmarks include amyloid β (Aβ)-containing plaques and tau-containing neurofibrillary tangles throughout the brain. The current AD biomarkers are based on amyloid-β plaques and of tau-related neuro-degeneration whereas brain positron emission tomography can also be used in the diagnosis of Alzheimer dementia.
MRI-based deep learning systems are able to assist with both AD classification and AD’s structural neuroimaging signatures and, for the present study, the US team wondered if a deep learning algorithm might be either comparable to, or even better than, existing biomarkers for the identification of the disease. In addition, because there are cellular changes prior to evidence of neuronal loss, it might be possible for a deep learning system to detect some of these more nuanced changes prior to the development of AD. The development of AD is progressive and transitions from a prodromal stage, characterised by mild cognitive impairment (MCI), before the onset of dementia. However, the diagnosis of prodromal AD in a patient with MCI is difficult. Therefore, if a deep learning algorithm could identify prodromal AD it would represent an invaluable ‘add-on’ to the conventionally acquired MRI scan and have potential utility as a screening tool. The team therefore wanted to train the MRI-based deep learning algorithm to recognise the prodromal phase and then compared the diagnostic performance against current biomarkers including cerebrospinal fluid (CSF) tau and amyloid beta levels (AB) as well as the tau/AB ratio.
MRI-based deep learning diagnostic accuracy
The deep learning algorithm was first trained using 975 MRI scans from AD patients compared to 1943 MRI scans from control patients. Using receiver operating characteristic analysis (ROC), the deep learning algorithm classified AD dementia compared to healthy controls with an area under the curve (AUC) of 0.973.
Next, the team identified two cohorts of patients; one group diagnosed with MCI but who remained stable over time, and a second group who subsequently progressed to AD. For both groups, CFS amyloid and tau biomarker values were available and used for comparative purposes. Using ROC analysis, the researcher found that the AUC for the deep learning algorithm was 0.788 for distinguishing between the MCI stable and progressive groups. The corresponding CSF AB, tau and tau/AB ratio AUC values for the same comparison were 0.702, 0.682 and 0.703 respectively and all differences were statistically significant. In other words, the deep learning algorithm was the best tool for identifying patients with prodromal AD.
Using survival analysis, the researchers also found that the deep learning algorithm outperformed the biomarkers in predicting progression to full AD dementia.
They concluded that the MRI-based deep learning could enhance the value of existing MRI scans by identifying useful information for the purpose of prodromal AD detection, adding that this approach potentially reduces patient burden, risk, and cost.
Feng X et al. A deep learning MRI approach outperforms other biomarkers of prodromal Alzheimer’s disease Alzheimers Res Ther 2022.
11th January 2022
NMR-based metabolomic biomarkers which identify specific disease patterns, can be used to assist in the diagnosis of cancer in patients who present with non-specific signs and symptoms and even distinguish between those with and without metastatic disease. This was an important finding by a team from the Department of Oncology, University of Oxford, United Kingdom.
The earlier most cancers are detected, the better the prognosis. For example, colorectal cancer, when identified at stage 1 has a 97.7% survival which falls to only 43.9% if detected at stage 4. Although there are often classic symptoms and signs of a possible cancer, e.g. palpable abnormalities such as a breast lump or haematuria, diagnosis becomes more difficult where the has non-specific symptoms such as fatigue.
One potential solution to the diagnosis of a cancer in patients who have non-specific signs and symptoms is metabolomics which can rapidly supply information on thousands of molecules and hence serve as a biofluid-based diagnostic method. The technique aims to comprehensively identify endogenous metabolites in biological systems, providing a complete biochemical phenotype of a cell, tissue, or whole organism, using established analytical techniques such as nuclear magnetic resonance spectroscopy (NMR) or gas chromatography-mass spectrometry (GC-MS). Using an NMR-based metabolomic approach, the Oxford team had previously and successfully detected tumours at the micro metastatic stage based on analysis of urine metabolomics.
For the present study, they hypothesised that biomarkers within the blood metabolome could identify patients referred from primary care with suspected cancer but largely non-specific symptoms, or those deemed to be at ‘low risk, but not no-risk’. In other words, the researchers felt that they would be ale to distinguish between those with and without a cancer and even to identify patients with metastatic disease.
They recruited patients aged 40 years and over who were not referred under the specific ‘2-week wait’ cancer specific pathway and those with one of the following symptoms: unexplained weight loss, severe unexplained fatigue, persistent nausea or appetite loss, new atypical pain, an unexplained laboratory finding or finally, where the primary care physician had a suspicion (i.e., ‘gut feeling’) of cancer. Prior to the metabolomics analysis, patients were randomised into a modelling set and an independent test set which was used to determine the ability of the models to classify new patients.
Blood samples were collected and analysed by NMR-based metabolomics and receiver operator characteristic curves were constructed and the area under the curves (AUC) examined.
A total of 284 patients with a mean age of 68 years (57% male) were included in the analysis. The most common reasons for referral were weight loss (64%), ‘gut feeling’ of the referring physician (63%), unexplained laboratory results (37%), fatigue (29%), non-specific pain (28%) and nausea/appetite loss (27%). On average, referred patients had at least two of these symptoms.
For distinguishing between patients who were unwell with the above non-specific symptoms and those with a solid tumour diagnosis, the modelling plasma metabolome had an AUC of 0.91 and showed a sensitivity of 94% (95% CI 73 – 99) and a specificity of 82% (95% CI 75 – 87) at detecting cancer.
For the identification set, the AUC was 0.83 giving a sensitivity of 71% and a specificity of 70%. In addition, the model showed a sensitivity of 94% and a specificity of 88% for distinguishing between metastatic and non-metastatic disease.
Interestingly, the authors also examined whether the metabolomics model could identify early-stage cancers before conventional imaging and found that this was possible for 2 out of 5 patients.
Although a preliminary study, the authors concluded that NMR-based metabolomics represented a sensitive and specific means for the identification of solid organ tumours in patients with non-specific symptoms, who have been traditionally hard to diagnosis. They called for the technique to be tested in a larger cohort of patients.
Larkin JR et al. Metabolomic Biomarkers in Blood Samples Identify Cancers in a Mixed Population of Patients with Nonspecific Symptoms Clin Cancer Res 2022
27th September 2021
Cardiovascular diseases (CVDs) cause an estimated 17.9 million deaths every year and globally, account for 32% of all mortalities. Reduced intake of fats, and in particular, saturated fats, has become a central recommendation for many years. For example, the NHS suggests that men should eat no more than 30g per day of saturated fat. In fact, reducing intake of saturated fat has been suggested as a means of reducing cardiovascular events, especially if the fat is replaced with unsaturated fats. However, in recent years, meta-analyses of randomised trials and observational studies found no beneficial effects of reducing saturated fat intake intake on cardiovascular disease (CVD) and total mortality, and instead found protective effects against stroke. Although studies linking fact intake and cardiovascular disease have often relied upon self-reported intake, these can be unreliable. This led an international team of researchers, led by The George Institute for Global Health, University of New South Wales, Australia, to investigate the association between serum levels of pentadecanoic acid (15:0), a biomarker for dairy fat intake and both incident cardiovascular disease (CVD) and all-cause mortality in a Swedish Cohort. The 15:0 was measured at baseline together with a series of questionnaires, between 1997 and 1999 and follow-up information was collected until December 2014. The primary outcomes of interest were incident CVD and all-cause mortality which were obtained from death registries and reported as hazard ratios. In addition, the authors included the results of their study in a systematic review and meta-analysis with a number of other studies.
The study included 4,150 adults with a mean age of 60.5 years (51% female) at baseline and who were followed for a median of 16.6 years. During this time there were 578 incident CVD events and 676 deaths (198 due to CVD). Higher serum 15:0 levels were associated with a lower incident CVD (hazard ratio, HR = 0.75, 95% CI 0.61 – 0.93, p = 0.009). However, there was no significant association of 15:0 serum levels with all-cause mortality (p = 0.38).
In the meta-analysis which included 18 studies and 42,736 participants, comparing the highest to lowest serum 15:0 levels, was associated with a 12% reduction in CVD (HR = 0.88, 95% CI 0.78 – 0.99) but as with the single study, there was no association with all-cause mortality.
The authors concluded that higher levels of 15:0, which are related to an increased intake of dairy fats, was associated with a lower risk of incident CVD and that these findings were supported by the meta-analysis. They called for further studies to ascertain the causality of this relationship and the potential role of dairy foods in CVD prevention.
17th August 2021
Ulcerative colitis is a bowel disease characterised by inflammation in the large bowel and rectum. It is a chronic, relapsing, remitting disease with an estimated prevalence of 9 to 20 cases per 100,000 people per year and which causes diarrhoea, abdominal pain and rectal bleeding. While the underlying aetiology is uncertain, it is believed to arise from exposure to environmental triggers in susceptible individuals. Furthermore, it is widely accepted that treating the disease at an earlier stage is the preferred strategy, particularly as once the diagnosis is established, bowel damage is already present in the majority of patients highlighting the need to identify possible early disease markers. Though research has already identified several inflammatory protein biomarkers that are predictive of Crohn’s disease within 5 years, there are currently no known relevant protein biomarkers for ulcerative colitis.
In trying to identify any such relevant protein biomarkers, a team from the Department of Gastroenterology, Faculty of Medicine and Health, Orebro University, Sweden, performed a case-control study comparing pre-diagnostic plasma samples of those who later developed ulcerative colitis (cases) with those who remained free of the disease (controls). In an effort to determine the influence of genetics and environmental factors, the researchers also examined twin pairs and healthy controls. The team used principal component analysis to identify specific proteins that were elevated in either case or control patients.
The researchers focused on 92 different potential protein biomarkers and obtained pre-diagnostic plasma samples from 72 individuals who later developed ulcerative colitis and 140 matched healthy controls. The median age of both case and control cohorts was 50 years (47% male) and the median time from when the pre-diagnostic samples were taken before diagnosis was 4.8 years. Analysis of the protein biomarkers revealed a total of six specific proteins that differentiated between cases and controls (p < 0.05) and which remained significantly elevated (after adjustments for age, sex and smoking status). An analysis of the area under the receiver operating curves showed that these six proteins had a valve of 0.92. Among the of twin samples, only four of these six proteins were discriminatory for ulcerative colitis.
In a discussion of their findings, the authors highlighted the importance of identifying predictive signatures for ulcerative colitis and concluded that the up-regulation of these six protein biomarkers were highly predictive of the subsequent development of ulcerative colitis and concluded that this provided a novel means of identifying patients who were likely to develop the disease in the future.
Bergemalm D et al. Systemic inflammation in pre-clinical ulcerative colitis. Gastroenterology 2021
13th August 2021
Tau is a microtubule-associated protein in neurons but aberrant assembly of the protein is present in neurodegenerative disorders. However, while abnormalities in the assembly of tau appear to be strongly associated with the development of disorders such as dementia and Alzheimer’s disease, it remains unclear how this links with upstream events. Tau levels can now be measured in blood and higher levels have been associated with cognitive decline and with the development of Alzheimer’s disease. Increased physical exercise improves blood flow to the brain and greater levels of activity appear to be associated with a reduced risk of developing degenerative conditions such as Alzheimer’s disease. Given that tau levels can serve as a biomarker of cognitive decline what remains uncertain is whether it is possible to correlate changes cognition with preventative strategies such as physical exercise over time. This was the aim of a study by a team from the Rush Institute for Healthy Aging, Rush University, Chicago, US. They used data contained within the Chicago Health and Aging Project (CHAP), which is a population-based cohort of African Americans and White participants, 65 years and older. The CHAP study is designed to explore chronic common health problems, especially risk factors for incident Alzheimer’s disease.
For the present study, the researchers included participants older than 65 years and without Alzheimer’s disease at baseline. Samples of tau were measured between 1994 and 2012 and frozen and later assayed. The team collected information on the levels of physical activity of participants and categorised this as either low, medium and high. Medium activity was where it was for less than 150 minutes per week, or high, if greater than 150 minutes. Low levels indicated that participants did not undertake any physical activity. Tau blood levels were also measured and considered as either high (> 0.40 pg/ml) or low (<0.40 pg/ml) based on earlier data suggesting a higher rate of cognitive decline in those with levels greater than 0.40. The main outcome of the study was global cognitive function based on a battery of tests and the measurement duration for the study was 18 years.
A total of 1159 participants were included with a mean age of 77.4 years (63% female) and with 60% of African American descent. In participants with a high tau level (> 0.40 pg/ml) and a medium level of physical activity, there was a 58% slower rate of cognitive decline per year compared to those undertaking little physical activity. Similarly, in those with high tau levels and high physical activity, the rate of cognitive decline was 41% slower than those with low activity. Even where tau levels were low, medium physical activity was associated with a 2% slower rate of decline and a 27% lower rate for those with high physical activity.
The authors concluded that physical activity was associated with a much slower decline in cognitive function among those with both low and high tau levels and that this could be easily measured with tau levels. They called for future studies to examine the relationship between tau levels and other forms (i.e., strength training) of physical activity.
Desai P et al. Longitudinal Association of Total Tau Concentrations and Physical Activity with Cognitive Decline in a Population Sample. JAMA Netw Open 2021
11th August 2021
Systemic sclerosis can be defined as a systemic connective tissue disease. It is characterised by small vessel vasculopathy, production of autoantibodies and dysfunctional fibroblasts, with an increased deposition of extracellular matrix. In a UK study, the prevalence of systemic sclerosis was estimated to be 19.4 per million person-years and 4.7 times more common in women. In contrast, a US study estimated prevalence of 50 – 300 cases per million. Clinically, patients present with skin thickening, Raynaud’s syndrome and polyarthralgia. Fibrosis of the lung is known to be a complication of systemic sclerosis, leading to systemic sclerosis-associated interstitial lung disease (SS-ILD) and pulmonary hypertension. The presence of system sclerosis reduces life-expectancy by 16 to 34 years and studies suggest that SS-ILD is associated with a 2.6 greater increased risk of death. However, there is a lack of data on potential biomarkers of lung function, hindering the assessment of current and future disease progression.
Some work has revealed an accumulation of myofibroblasts in fibrotic skin in patients with systemic sclerosis and a loss of intradermal adipose tissue. Furthermore, patients with systemic sclerosis have been found to have lower levels of serum adiponectin, a hormone secreted by adipose tissue. Other data has suggested that one particular adipokine, CTRP9 is elevated in patient with patients with systemic sclerosis. This led a team from the Department of Medicine, Division of Rheumatology, University of California, US, to examine whether CTRP9 could serve as a biomarker with predictive valve for pulmonary function in patients with SS-ILD. The team turned to a patient registry to retrospectively examine this relationship and included patients with documented pulmonary tests over a 48-month interval and where CTRP9 levels had been initially recorded. They split patients into a high and low group according to CTRP9 levels and set the primary outcome of interest as forced vital capacity percent predicted (FVC%), which is valid measure of disease severity in SS-ILD.
A total of 61 patients with a mean age of 53.5 years (77.3% female) were included in the analysis. Elevated circulating CTRP9 levels were associated with significantly lower FVC% levels at baseline (72% vs 80%, p = 0.02) and after 48 months (68% vs 84%, p = 0.001). In addition, the researcher sought to determine whether CTRP9 levels could predict disease stability, which they defined as less than 3% decrease in FVC% over 48 months. The analysis showed that a low baseline CTRP9 level had a sensitivity of 73% and a specificity of 45% for disease stability.
The authors discussed how their findings clearly indicated that the presence of elevated CTRP9 was associated with more severe lung disease. They concluded that CTRP9 could represent a prognostic biomarker and a possible therapeutic target for SS-ILD.
Yang MM et al. Circulating CTRP9 is associated with severity of systemic sclerosis-associated interstitial lung disease. Arthritis Care Res 2021
5th August 2021
The term interstitial lung disease (ILD) is an umbrella term to describe a group of diseases all of which are characterised by inflammation or fibrosis of the alveolar wall and impairment of gas exchange. One form of ILD is connective tissue disease-associated ILD (CTD-ILD) and which occurs in patients with a connective tissue disease such as Sjogren’s syndrome, systemic lupus erythematosus and polymyositis, with an estimated incidence of 15% of the population. Other forms of ILD include idiopathic pulmonary fibrosis (IPF) and which has an estimated worldwide prevalence of 13 to 20 cases per 100,000. The diagnosis of ILD and identification of the underlying cause can be challenging and relies upon a combination of blood, imaging and pulmonary function tests.
The precise cause of ILD is unclear although proposed aetiologies have included an imbalance between oxidant-antioxidant factors, particularly in idiopathic pulmonary fibrosis as well as an increased level of advanced glycation end-products (AGE). Furthermore, increased levels of matrix metalloproteinase-7 (MMP-7) is also involved as witnessed by elevated levels in those with IPF. Nevertheless, differentiating between CTD-ILD and other forms of ILD such as IPF is important because the treatment is different. This led a team from the Respiratory Service, University of Virgen de la Victoria Hospital, Malaga, Spain, to explore whether it was possible to use several serum molecules to differentiate between IPF and CTD-ILD. The team recruited patients with both IPF and CTD-ILD and after a single visit to the hospital, blood samples were taken together and the levels of AGE, advanced oxidation protein products (AOPP) and MMP-7 determined. The performance of each marker was assessed using the area under the receiver operating characteristic curve (AUC) and used to determine the sensitivity and specificity of each biomarker.
In total there were 73 patients, 29 with IPF and 14 CTD-ILD and 30 healthy controls. The average age of participants was not significantly different and approximately 63 years. Mean levels of AGE, AOPP and MMP-7 were all elevated in both the CTD-ILD and IPF groups compared to controls. The AUC for AGE was 0.78 (95% CI 0.60–0.97) for patients with IPF, 0.80 for AOPP and 0.96 for MMP-7. In addition, the AUC for AGE was higher for CTD-ILD than for IPF (0.95, 95% CI 0.86 – 1.0). Using MMP-7 as a biomarker, for both conditions, the sensitivity was 92.3% for IPF and 100% for CTD-ILD and the corresponding specificities were both 92.9%. However, combining the biomarkers, AGE and MMP-7, increased the sensitivity for distinguishing between IPF and CTD-ILD to 93.3% and the specificity 100%.
In their discussion, the authors noted that while all three biomarkers were elevated in patients with the different forms of ILD, the combination of two of these markers (MMP-7 and AGE) was able to differentiate between the CTD-ILD and IPF and might therefore serve as an important biomarker in clinical practice.
23rd July 2021
Knowledge about COVID-19 has advanced at rapid pace over the last 15 months and with a large number of patients being admitted to hospital, it is of upmost importance to be able to assess which patients are at the highest risk of disease progression. Based on earlier observational studies, it has become clear that older patients and those with co-morbidities are more likely to develop severe disease and several biomarkers including C-reactive protein and procalcitonin, have been shown to be associated with severe disease. A further potential complication of COVID-19 is bacterial co-infection though in an analysis of 24 studies including 3338 patients, the presence of bacterial co-infection in COVID-19 was found to be very low at 6.9%. Nevertheless, whether the use of biomarkers such as procalcitonin could be used to identify bacterial co-infection among patients with COVID-19 has been suggested as a potentially valid strategy, but there is a lack of evidence to support this approach.
This absence of evidence prompted a team from the Department of Internal Medicine, Haga Teaching Hospital, Den Haag, The Netherlands, to retrospectively evaluate the association between multiple biomarkers, including procalcitonin and the clinical and microbiological outcomes in patients hospitalised with COVID-19. The team used data from the PredictED study, a single centre, prospective observational study, designed to evaluate procalcitonin as a marker for bacteraemia in patients who present to the emergency department. While the original study was designed to examine all patients admitted to the emergency department, the authors turned to a subset of patients with PCR-confirmed COVID-19. A number of tests were undertaken, including blood cultures, C-reactive protein and procalcitonin although the results of this latter test were not immediately available to the treating clinician. The primary outcome of the study was the incidence of bacterial co-infection at the initial emergency department presentation and its association with procalcitonin.
The subset of COVID-19 patients testing positive for the virus was 142 with a mean age of 61 years (66% male). More than half of these patients had co-morbidities including diabetes (25%) and cardiovascular disease (24%) and from the complete cohort, 41 developed severe COVID-19, all of whom were hospitalised and 24 (17%) subsequently died within 30 days. Procalcitonin levels were significantly associated with the development of severe disease (odds ratio, OR = 1.8, 95% CL 1.3 – 2.2), as were higher levels of the biomarker. In addition, C reactive protein levels were also significantly associated with more severe disease (OR = 1.8, 95% CI 1.3–2.6). Using the area under the receiver operating curve for procalcitonin, the predictive value was 0.76.
Commenting on their results, the authors noted that procalcitonin demonstrated the highest discriminatory power between severe and non-severe COVID-19. Although only a small number of COVID-19 patients (1.4%) had a bacterial co-infection, the authors concluded that measurement of procalcitonin levels appeared to be a promising approach to help clinicians recognise patients a higher risk of more severe COVID-19 infection.
Kaal A et al. Diagnostic yield of bacteriological tests and predictors of severe outcome in adult patients with COVID-19 presenting to the emergency department. Emerg Med J 2021
27th April 2021
In a large, prospective study of nearly half a million individuals, higher intakes of fish intake were associated with a reduced all-cause mortality. One factor associated with biological ageing is the length of telomeres, which are strands of DNA at the ends of chromosomes and there is good evidence that telomere shortening is associated with increased mortality and how among individuals who consume higher amounts of omega-3 fatty acids, there is a reduced risk of telomere shortening. Moreover, increased physiological stress is a risk factor for many physical and mental health diseases and again, there is a suggestion that the pro-inflammatory response to psychological stress is attenuated to some extent by omega-3 fatty acids. Taken together, these results suggest that supplementing with omega-3 fatty acids may positively impact on markers of stress reactivity. This was the hypothesis considered by a team from the Institute for Behaviour Medicine Research, the Ohio State University College of Medicine, Ohio, US who examined a group of individual’s response to a social stress test. The team randomised participants into three groups who received either 2.5g/day, 1.25g/day of omega-3 or placebo for 4 months. At baseline, all participants were required to undergo the stress test which involved delivering a 5-minute speech without the use of aids or notes. Both saliva and blood samples were collected before the stress test and at 0.75, 1.25, 1.75 and 2 hours after and the test repeated at the end of the study. Parameters evaluated included cortisol, telomerase (an enzyme that maintains and restores telomeres) and several pro-inflammatory markers, interleukins 6, 10 and 12 as well as tumour necrosis factor (TNF). Participants were also required to score their anxiety levels before and after the test.
A total of 138 individuals were recruited (63% female) with a mean age of 51.1 years and with 72% of white ethnicity. Among those taking 2.5g/day of omega-3, their salvia cortisol levels were 19% lower throughout the final stress test compared to those given placebo (p = 0.01) although this difference was not significant for the 1.25g/day group. Similarly, the high dose supplement group had a 33% lower interleukin-6 level compared to placebo (p = 0.007). However, there were no differences with the other interleukin levels or of TNF. While telomerase levels remained unchanged in both supplement groups, levels dropped between 45 and 120 minutes after the stress test by 24%.
The authors commented on how 2.5g/day of omega-3 fatty acid supplementation blocked the stress-related decline in telomerase level as well as reducing levels of both cortisol and the pro-inflammatory interleukin-6 in a dose dependent manner. They suggested that omega-3 supplements had a unique stress-buffering effect on biomarkers of cellular ageing, concluding that while their data were preliminary, if replicated, it could limit the impact of repeated stress.
Madison AA et al. Omega-3 supplementation and stress reactivity of cellular ageing biomarkers: an ancillary sub-study of a randomised, controlled trial in midlife adults. Mol Psychiatry 2021.