Professor Frances Williams’ Chronic Pain and Hearing Loss Research Group, part of our team at TwinsUK, has recently published another piece of the puzzle in the quest to understand and treat tinnitus.
The large project – funded by Tinnitus UK as part of their Large Research Grants Programme – spanned Sweden and the UK, recruiting participants with tinnitus and matched controls firstly in over 1,000 participants in Sweden and then ran a replication of the study in over 1,000 twins from Twins UK. The primary objective of the research was to identify biomarkers for tinnitus.
Co-author Max Freiden said:
“It is difficult to establish biomarkers to detect or treat the disorder, because tinnitus is heterogeneous, indicating that various factors determine whether a person develops tinnitus.”
Surprisingly, tinnitus shares several signs and symptoms with chronic pain. Neuroimaging suggests similar disturbances in the prefrontal cortex of the brain, leading to distorted interpretation of sensory inputs, such as sound. A localised brain inflammatory response, detectable in the bloodstream, has been reported to occur with chronic pain. The team investigated whether inflammatory biomarkers could be found in people with tinnitus, hypothesising that chronic pain and constant tinnitus may be associated with neuroinflammation.
Importantly, factors unrelated to hearing difficulties that affect inflammatory marker levels, such as age, sex, and body mass index, were accounted for. Tinnitus tends to be accompanied by stress, anxiety, depression, hypersensitivity to sound, face pain, and headache; however, none of these conditions were related to inflammatory marker levels. While a weak association of five inflammatory proteins was seen in the Swedish cohort, the finding was not replicated in the UK cohort, leading researchers to conclude there is a lack of association between plasma biomarkers and constant tinnitus. Other research has shown that biomarkers can be derived from electrophysiological measures, but this does not appear to be the case for blood biomarkers.
Although the team didn’t find a tinnitus biomarker, negative results are considered progress and constitute an important aspect of directing future research and treatment. Such advancements are only possible with the generous research investments from charities like Tinnitus UK, and the important contribution of participants from TwinsUK and others who consent to research.
Researchers from TwinsUK have recently identified eight biochemical compounds measured in stool (faecal metabolites) that are involved in prediabetes and type-2 diabetes risk in a large study. Impaired fasting glucose, also known as prediabetes, refers to elevated blood sugar levels that are not high enough to mean that the person has type.2 diabetes. Most importantly, prediabetes is a reversible condition: you can prevent or delay prediabetes from turning into type-2 diabetes with well-established lifestyle changes. However, over 80% of individuals with prediabetes remain unaware of their condition. Previous research found a link between type-2 diabetes, prediabetes and the bacteria living in our gut, but mechanisms remain elusive. Faecal metabolites can provide valuable insights into their metabolic health, as they are the result of various metabolic processes occurring in the body, including the digestion and breakdown of food, as well as the activities of gut bacteria.
The team analysed the gut microbiome and blood glucose levels collected from 1,018 TwinsUK participants, and then checked their findings in an additional cohort from Germany. The researchers discovered eight specific faecal metabolites linked to prediabetes risk. Importantly, though these metabolites were chemicals or substances that are not naturally found in the body and come from outside sources, they were still reflective of the individuals’ gut bacteria, suggesting a complex interplay between the gut microbiome and the host’s metabolic processes. Moreover, these metabolites were also predictive of type-2 diabetes in a sub-analysis, showing a potential connection with the development of type-2 diabetes.
First author Ana Nogal stated:
“Our findings open up new avenues for understanding the role of the gut microbiome in prediabetes and type-2 diabetes. The gut microbiome seems to influence the intestinal absorption or excretion of compounds that are not produced by the human body, and this is linked to prediabetes risk, adding another layer to the complex web of interactions between the gut microbiota and metabolic health.”
Senior author Cristina Menni explained:
“This research has the potential to transform our understanding of prediabetes and type-2 diabetes development, offering new insights into the role of the gut microbiome. The implications of this study are far-reaching, and it has the potential to pave the way for innovative treatments and preventive measures for these prevalent metabolic conditions.”
The study highlights the importance of considering the gut microbiome’s impact on the absorption and excretion of compounds in understanding the onset of type-2 diabetes. Further research is needed to explore this mechanism and its potential implications for diabetes prevention and management.
In a groundbreaking collaborative effort encompassing six intercontinental cohorts including TwinsUK, the Consortium of Metabolomics Studies (COMETS) has identified 10 novel molecules measured in serum that were associated with incident myocardial infarction (MI), commonly known as a heart attack. This research, representing the largest of its kind, included 7,897 people and has far-reaching implications for identifying at-risk individuals before the onset of this life-threatening condition.
MI is a leading global cause of death and disability, underscoring the importance of early prediction and intervention. Previous studies measuring hundreds of serum molecules to identify biomarkers of MI have been restricted by limited participant numbers and/or demographic diversity. However, COMETS’ extensive research has addressed these limitations.
In this study, individuals averaging 66 years of age were drawn from six distinct international cohorts, with their blood metabolomes analyzed. Coupled with data on 1,373 MI cases, the researchers executed a two-stage Individual Patient Data meta-analysis.
The results were nothing short of groundbreaking. 56 metabolites, including 21 lipids and 17 amino acids, were linked to incident MI, with 10 of them not being reported before notably, the carbohydrate mannitol/sorbitol emerged with the highest increased risk, while glutamine exhibited the most significant decrease in risk.
Moreover, these identified metabolites were substantially enriched in pathways previously associated with cardiovascular diseases, such as aminoacyl-tRNA biosynthesis. This reinforces the potential clinical relevance of these biomarkers.
Senior author Cristina Menni explained:
‘The identified molecules offer a promising avenue for early detection and risk assessment before the onset of heart disease. This is a significant breakthrough in cardiovascular research, as it can potentially enable healthcare professionals to identify individuals at risk of heart attacks well in advance, allowing for proactive interventions and personalized healthcare strategies.’
First author Ana Nogal said:
‘The implications of this study are profound. The identified metabolites could serve as powerful tools for identifying individuals at high risk of MI before the disease manifests clinically. As a result, this research not only advances our comprehension of the molecular changes underlying MI development but also opens new avenues for clinical prediction and a more profound understanding of causal mechanisms.’
In a world where heart attacks remain a major public health concern, COMETS’ collaborative effort signifies the importance of multidisciplinary research and holds the promise of uncovering universal biomarkers that can save countless lives.
Children between the ages of 12 and 16 with a higher body mass index (BMI) are more susceptible to developing symptoms of depression, according to a recent study conducted by researchers from TwinsUK. The findings emphasize the importance of understanding the connection between mental health and weight in adolescence and suggest that early intervention strategies could be beneficial.
The research, published in Psychological Medicine, used data from over 10,000 twins participating in the Twins Early Development Study (TEDS) and our TwinsUK cohort. Twins born between 1994 and 1996 self-reported depressive symptoms, including low mood, loneliness, and exhaustion, at ages 12, 16, and 21. The study’s key findings indicate a significant link between higher BMI and depression among individuals aged 12 to 16, with weaker association in the 16 to 21 age group.
The team also found that children with a higher BMI during early adolescence were at an increased risk of developing depression later in life than those who experienced depression first and then saw an increase in their BMI.
First author, Dr. Ellen Thompson explained:
“Understanding the relationship between mental ill-health and weight in adolescence is vital to provide timely support where needed. This study shows a stronger association between having a higher BMI at age 12 years and subsequent depression symptoms at age 16 years than the reverse.”
The study also highlighted that environmental factors played a significant role in the connection between BMI and depression at each age. While the study did not delve into the specific reasons for this effect, prior research has suggested that factors like body dissatisfaction and weight-related stigma from external sources could contribute to the association.
Surprisingly, the study’s results remained consistent even after adjusting for socio-economic status, dispelling the notion from previous research that poverty might be the primary risk factor in this relationship.
This shows the importance of early adolescence as a crucial period for addressing the potential consequences of higher BMI on mental health. Preventative measures, such as support structures and positive body image messages, could be incorporated into Personal, Social, Health and Economic (PSHE) education to counteract depressive symptoms in young teens.
Co-senior author, Professor Claire Steves said:
“Using the TwinsUK cohort, which focuses on older adult twins, our study showed that the relationship between BMI and depression was much weaker in later life. The exact reasons for these changes over the life course need further investigation.”
Researchers from TwinsUK have recently published a systematic review and meta-analysis examining the current efficacy of artificial intelligence (AI) machine learning applications that read MRI scans of degenerate discs. Working in the pain research team under Professor Frances Williams at King’s College London, researchers are motivated to glean the latest insights in developments to low back pain causes or treatment. Low back pain is the lead cause of disability globally and can fundamentally reduce patient quality of life. Intervertebral disc degeneration is a main cause of low back pain and Williams’ team is heavily invested in pioneering research into causes, diagnoses and treatments for the condition.
Disc degeneration is a normal part of aging, however sometimes it is accompanied by disabling pain and interventions are required. This systematic review and meta-analysis specifically focused on machine learning (ML) algorithms that read lumbar magnetic resonance imaging (MRI) scans. Assessing disc degeneration is a time-consuming endeavour for radiologists, accurate machine learning algorithms that could fulfill this task, would represent a huge saving of work hours for health services across the globe. Fully exploiting AI technology could allow efficiency in identifying lumbar disc degeneration as well as other spinal conditions, and speed triaging patients for surgery or physiotherapy treatments.
The systematic review found several studies with a computer science research focus that reported machine learning algorithms could do the job of radiologists, or that their approach could lead to diagnostic technology. Unfortunately, much of this software is not rigorously tested and most of the included studies had small numbers of participants. A systematic review and meta-analysis aim to the contribution of several small studies, however lack of replication (running the algorithm again in a totally new group of scans) was another stark omission from most of the included studies.
In science, the best type of research is validated in different groups of participants and run multiple times. This should be a standard practice for medical treatments or tools. However they found that generally, these algorithms were not validated, and reports of added benefit to the assessment of disc degeneration were concluded perhaps prematurely.
The technology is exciting as it does offer a real promise to the future of MRI reading and spinal assessments and ultimately better outcomes in patients with low back pain.
Authors Roger Compte and Isabelle Granville Smith explained:
“We suggest future research should incorporate several machine learning approaches, such as adding semi- and un-supervised learning to supervised learning approaches. MRIs inherently contain vast quantities of information; of which the human eye is only capable of gleaning part. Designing machine learning algorithms that better take advantage of MRI data arrays may be a means to progress their reliability and accuracy to be comparable to and may one day surpass human radiologists.“
Researchers from TwinsUK have found that rather than being protective, high protein intake is associated with loss of muscle mass in healthy over-60s.
This surprising finding comes from a study of 3,302 twins from the TwinsUK cohort.
Sarcopenia is associated with ageing and occurs when there is an accelerated loss of skeletal muscle mass and function. This can lead to negative outcomes such as frailty, reduced function in day-to-day activities, and increased risk of falls. The study aimed to investigate factors linked with skeletal muscle strength, mass and sarcopenia, particularly intake of protein, and to evaluate if shared twin characteristics are important.
The team studied twins who consumed the optimal recommended protein intake as the reference group (1.0–1.3 g/kg/day) and found that there was no significant link between protein intake (neither high nor low) and low muscle strength, or between low intake of protein and sarcopenia.
Results showed that high protein intake on the other hand was associated with decreased muscle mass, while low protein intake was protective. High protein intake was also linked with sarcopenia, even after adjusting for demographic, anthropometric (physical measures of a person’s size, form, and functional capacities) and dietary factors.
The study also found that the strength of muscles is linked with age, education, income, diet, appetite and diversity in the gut microbiome. However, the link between muscle strength and weight, body mass index, healthy eating index, protein intake, and gut microbiome diversity were not significantly influenced by shared twin factors. This means that treatments targeting these factors may be effective in preventing or treating sarcopenia.
First author Dr Mary Ni Lochlainn explains:
“We know high quality protein intake is essential for muscle health, however, it is important to consider that not all sources of protein contain the full range of essential amino acids, and that it may be important to eat some sources of protein in moderation.”
“While our participants were healthy volunteers, the results give valuable insight into the link between diet and sarcopenia. Further research is needed to investigate this further, including looking at longitudinal data in cohorts with an increased number of participants who live with sarcopenia.”
A recent study has found that brain-age could help with early detection of dementia in patients. The team, which included TwinsUK Clinical Director Professor Claire Steves, found that patients who visited memory clinics with brains that appeared to look older had a higher risk of dementia.
Dementia is a general term for loss of memory, language, problem-solving and other thinking abilities that are severe enough to affect everyday activities.
Some years ago, members from TwinsUK took part in an MRI brain study which was used to define a brain-age score – a way of marking the age of a person from the structure of their brain. This data was used to develop a way of determining whether someone’s brain looks older or younger than their years. In the present study, the team analysed MRI brain scans from patients referred to memory clinics to determine their brain-age, and tracked which patients developed dementia through linking to their electronic health records in the years that followed.
The researchers found that patients with higher brain-age were more likely to receive a subsequent dementia diagnosis. The results from this study show that neuroimaging biomarkers like brain-age are useful clinically in managing people with memory problems. The next stage is for doctors to put this into practice regularly, so that everyone affected by memory issues can benefit from it.
Professor Claire Steves said:
“I would like to sincerely thank the twins who contributed to this study by being willing to have MRI scans, as the study shows the potential of using quantitative techniques to study the structure and function of the central nervous system in closing the gap between basic research and it being applied in clinical settings.”
The number of people with dementia around the world is increasing, and this is driving research to improve ways of identifying earlier individuals at greatest risk of being diagnosed with the disease. Being able to identify dementia in patients early on has important significance for planning future care, interventions, and clinical trials.
One in six (17%) middle-aged people who report being infected by SARS-CoV-2 also report long COVID symptoms, while this falls to one in 13 (7.8%) among younger adults who reported having Covid-19, according to a new study led by King’s and UCL which is now published in Nature.
The preliminary findings, part of the UKRI-NIHR funded multi-institution CONVALESCENCE study and submitted to the preprint server medRxiv, also found that women were 50% more likely to report long COVID than men, and that the risk for long COVID symptoms increases with age, is linked to poorer pre-pandemic mental and physical health and is associated with a previous diagnosis of asthma. Non-white ethnic minority groups had lower odds of reporting long COVID (about 70% less likely).
Using a stricter definition of long COVID as impacting routine daily activities, the researchers found that it affected 1.2% of 20-year-olds who had Covid-19, but 4.8% of people in middle age.
The researchers analysed anonymised data from 1.2 million primary health records across the UK together with 10 population-based cohort studies with 45,096 participants. Using existing cohort studies, whose participants are surveyed regularly, allowed the research team to include cases not reported to the GP and to look at people’s health before the pandemic.
Knowing which factors increase the risk of long COVID is an important first step in understanding how best to prevent and treat this condition.
Professor Nishi Chaturvedi (MRC Unit for Lifelong Health and Ageing at UCL), who leads the ongoing CONVALESCENCE study, said: “Getting consistent findings from this combination of many different studies gives us greater confidence that our findings are robust, which is critical given that we know so little about long COVID.”
First author Dr Ellen Thompson, of King’s College London, said:
“It’s really important to identify risk factors in the population so we can prepare and devise prevention strategies, protecting people at increased risk of poor outcomes from COVID-19.”
First author Dr Dylan Williams (MRC Unit for Lifelong Health & Ageing at UCL) said:
“Amassing this body of evidence would usually take many months or years to assemble but we achieved this more quickly through massive, constant collaboration by researchers at many different institutions.
Dr Claire Steves from the School of Life Course Sciences said:
“Our findings hint at the mechanisms behind long COVID. Next, we need to identify the predispositions that might explain, for example, why women or individuals with asthma appear to be at higher risk. Could a liability to suffer from autoimmunity or allergies play a role? Establishing concrete research avenues to go down will eventually lead to benefits for people with long COVID.”
The study forms part of the larger COVID-19 Longitudinal Health and Wellbeing National Core Study, which is investigating the health, social and economic impacts of the COVID-19 pandemic by combining rich pre-COVID data collected from participants of numerous national research studies with national anonymised electronic health records.
The researchers investigated if the risks of developing long-term Covid symptoms differed by several pre-pandemic socioeconomic and health characteristics. Coordinated analyses of the longitudinal studies and health records data showed consistently that female sex and increasing age (up to 70 years) were associated with increased odds of long COVID.
Pre-existing adverse mental health was associated with a 50% increase in the odds of reporting long COVID, while asthma was the only specific prior medical condition consistently associated with greater risk of developing lasting Covid-19 symptoms (a 32% increase). Participants were identified as having pre-existing adverse mental health if they had been diagnosed with one of a number of conditions such as depression and bipolar disorder, or their responses to questionnaires indicated they had a mental health condition before the pandemic.
Analysis was conducted on 6,899 individuals self-reporting COVID-19 from 45,096 surveyed adult participants of ongoing longitudinal studies in the UK, and on 3,327 cases assigned a long COVID code in primary care electronic health records out of 1,199,812 adults diagnosed with acute COVID-19. Long COVID, identified as Post-COVID-19 syndrome in the study, is defined as symptoms persisting for longer than 12 weeks after the initial infection.
The research team included researchers at the Universities of Bristol, Edinburgh, Glasgow, and Oxford, as well as the London School of Hygiene & Tropical Medicine, and the Bradford Royal Infirmary.
Dr Fiona Glen, programme director for the NICE Centre for Guidelines, said:
“There is still much we do not know about the long-term effects of COVID-19. We continue to monitor and assess the latest evidence on the long-term effects allowing us to continuously update our guideline recommendations. We welcome this new research which will ensure we have a better understanding of how to manage the care and treatment of patients with prolonged symptoms of COVID-19.”
Exposure to natural environments, also known as greenspace, has been shown to have a positive influence on our health, but the mechanisms as to why are still not clear. We know from previous research that gut bacteria is linked with inflammatory illnesses; inflammatory illnesses are also more prevalent in urban areas and in individuals who have lower levels of exposure to greenspace. Therefore, gut bacteria could act as one of the links between greenspace and health.
The team studied 2,443 participants from the TwinsUK cohort to see if there was a difference in gut bacteria in individuals living in rural and urban environments. The researchers looked at the amount of greenspace at three different distances from a participant’s home: 800 m, 3000 m, and 5000 m. The aim was to understand if there was any evidence of bacteria differing with the amount of greenspace.
The team found there were differences in bacteria between different greenspace areas and when comparing rural versus –urban microbes. One hypothesised reason could be that people are exposed to a range of microorganisms and therefore have a stronger immune system as they are exposed to a wider range of bacteria. Levels of bacteria associated with disease were higher in individuals living in more urban environments compared to rural environments.
A limitation of the study was the broad interpretation of “greenspace” as being any area in a non-urban environment. This meant that factors like the accessibility of land or the type and quality of habitats that were present could not be considered. Further work could design experiments to understand this further by comparing urban areas with high, accessible greenspace with urban areas of low, accessible greenspace.
The different microrganisms residing along the human digestive tract, along with the things these microbes produce is collectively called the human gut microbiome. It has a crucial role as it interacts with the immune system, is vital for processing nutrients and protects individuals against pathogens.
First author Ruth Bowyer said:
“The results show that there are geographical patterns in the composition of the microbiota which does not appear to be explained by diet, BMI (Body Mass Index), and health deficit. Therefore, the results bring to light the potential importance of considering non-lifestyle factors that could affect microbiota composition.”
A new study has found women ‘age’ significantly faster in the perimenopausal period, based on analysis of the IgG glycome. This finding indicates the potential of using the IgG glycome composition as an early predictor for perimenopause.
The study, published in iScience and led by a team of researchers from the Genos Glycoscience Research Laboratory in Zagreb, Croatia, Newson Health Menopause & Wellbeing in Stratford upon Avon and King’s College London followed nearly 2000 women for 15 years and analysed their IgG glycans several times during that period. IgG glycans, otherwise known as immunoglobulin G glycome, is an abundant antibody and has been shown to be a biomarker of an individual’s health.
Researchers analysed IgG glycome composition in 5,080 samples from 1,940 females during their transition from before menopause (premenopause) to postmenopause. Many of these samples were taken from TwinsUK which is the largest twin registry in the UK and led by researchers from King’s College London.
Analysis of the IgG glycome in multiple samples from the same individuals was able to show the association between perimenopause and the changes in the IgG glycome composition. This period showed the IgG glycome changing from an inflammation-suppressive to proinflammatory. While this is common as we age, researchers saw this change happen rapidly as women transitioned from a regular cycle to menopause.
This change in IgG glycans is associated with many health risks that accompany menopause. In some diseases like rheumatoid arthritis and cardiovascular diseases, this change can occur years before disease onset. This suggests glycans and chronic inflammation is linked and the transformation of IgG glycans plays a part in developing the disease.
Perimenopause can last up to 15 years and is challenging to diagnose due to highly irregular hormonal cycles. As a result of poor awareness and inappropriate use of hormonal tests, women are often misdiagnosed with conditions such as fibromyalgia, migraines, depression, or chronic fatigue syndrome and are frequently prescribed antidepressants despite the lack of evidence to support their use to improve the low mood associated with perimenopause or menopause. This study shows it may be possible to use IgG glycans to predict perimenopause.
Senior author Dr. Cristina Menni from King’s College London said:
“Perimenopause is poorly diagnosed due to highly irregular hormonal cycles and symptoms that can last for as long as 15 years. Currently, there is no accurate diagnostic test for perimenopause. Adding an easily quantifiable novel early biomarker of perimenopause could be a valuable improvement to current clinical praxis.”
