1. Cognitive Decline Associated with Certain Personality Traits
Fom American Psychological Association
People who are organized, with high levels of self-discipline, may be less likely to develop mild cognitive impairment as they age, while people who are moody or emotionally unstable are more likely to experience cognitive decline late in life, according to research published by the American Psychological Association.
The research, published in the Journal of Personality and Social Psychology, focused on the role three of the so-called “Big Five” personality traits (conscientiousness, neuroticism and extraversion) play in cognitive functioning later in life.
“Personality traits reflect relatively enduring patterns of thinking and behaving, which may cumulatively affect engagement in healthy and unhealthy behaviors and thought patterns across the lifespan,” said lead author Tomiko Yoneda, PhD, of the University of Victoria. “The accumulation of lifelong experiences may then contribute to susceptibility of particular diseases or disorders, such as mild cognitive impairment, or contribute to individual differences in the ability to withstand age-related neurological changes.”
Individuals who score high in conscientiousness tend to be responsible, organized, hard-working and goal-directed. Those who score high on neuroticism have low emotional stability and have a tendency toward mood swings, anxiety, depression, self-doubt and other negative feelings. Extraverts draw energy from being around others and directing their energies toward people and the outside world. They tend to be enthusiastic, gregarious, talkative and assertive, according to Yoneda.
To better understand the relationship between personality traits and cognitive impairment later in life, researchers analyzed data from 1,954 participants in the Rush Memory and Aging Project, a longitudinal study of older adults living in the greater Chicago metropolitan region and northeastern Illinois. Participants without a formal diagnosis of dementia were recruited from retirement communities, church groups, and subsidized senior housing facilities beginning in 1997 and continuing to the present. Participants received a personality assessment and agreed to annual assessments of their cognitive abilities. The study included participants who had received at least two annual cognitive assessments or one assessment prior to death.
Participants who scored either high on conscientiousness or low in neuroticism were significantly less likely to progress from normal cognition to mild cognitive impairment over the course of the study.
“Scoring approximately six more points on a conscientiousness scale ranging 0 to 48 was associated with a 22% decreased risk of transitioning from normal cognitive functioning to mild cognitive impairment,” said Yoneda. “Additionally, scoring approximately seven more points on a neuroticism scale of 0 to 48 was associated with a 12% increased risk of transition.”
Researchers found no association between extraversion and ultimate development of mild cognitive impairment, but they did find that participants who scored high on extraversion — along with those who scored either high on conscientiousness or low in neuroticism — tended to maintain normal cognitive functioning longer than others.
For example, 80-year-old participants who were high in conscientiousness were estimated to live nearly two years longer without cognitive impairment compared with individuals who were low in conscientiousness. Participants high in extraversion were estimated to maintain healthy cognition for approximately a year longer. In contrast, high neuroticism was associated with at least one less year of healthy cognitive functioning, highlighting the harms associated with the long-term experience of perceived stress and emotional instability, according to Yoneda.
Additionally, individuals lower in neuroticism and higher in extraversion were more likely to recover to normal cognitive function after receiving a previous diagnosis of mild cognitive impairment, suggesting that these traits may be protective even after an individual starts to progress to dementia. In the case of extraversion, this finding may be indicative of the benefits of social interaction for improving cognitive outcomes, according to Yoneda.
There was no association between any of the personality traits and total life expectancy.
Yoneda noted that the findings are limited due to the primarily white (87%) and female (74%) makeup of the participants. Participants were also highly educated, with nearly 15 years of education on average. Future research is necessary on more diverse samples of older adults and should include the other two of the big five personality traits (agreeableness and openness) to be more generalizable and provide a broader understanding of the impact of personality traits on cognitive processes and mortality later in life, she said.
1. Tomiko Yoneda, Eileen Graham, Tristen Lozinski, David A. Bennett, Daniel Mroczek, Andrea M. Piccinin, Scott M. Hofer, Graciela Muniz-Terrera. Personality traits, cognitive states, and mortality in older adulthood. Journal of Personality and Social Psychology, 2022; DOI: 10.1037/pspp0000418
2. Clear Genetic Risk for Schizophrenia
From Broad Institute of MIT and Harvard
In a landmark genetic study of more than 121,000 people, an international consortium called SCHEMA, led by researchers at the Broad Institute of MIT and Harvard, has identified extremely rare protein-disrupting mutations in 10 genes that strongly increase an individual’s risk of developing schizophrenia — in one instance, by more than 20-fold. A second, complementary study in a larger but overlapping group of 320,400 people, conducted by the Psychiatric Genomics Consortium (PGC) and including the same Broad researchers, brings to 287 the number of regions of the genome associated with schizophrenia risk, including ones containing genes identified by SCHEMA.
Together, these studies underscore an emerging view of schizophrenia as a breakdown in communication at the synapse (the junction between neurons), and illustrate how different kinds of genetic variation affecting the same genes can influence the risk for different psychiatric and neurodevelopmental disorders. The two studies appear together in the journal Nature.
“Psychiatric disorders have been a black box for a very long time. Unlike cardiovascular disease or cancer, we have had very few biological clues to disease mechanisms,” said Tarjinder Singh, a postdoctoral fellow in the Stanley Center for Psychiatric Research at the Broad Institute. “As a result, we have lacked the necessary insights for development of much needed new treatments. Instead we have been iterating on the antipsychotic drugs serendipitously discovered more than 70 years ago.” Singh, who is also in the Analytic and Translational Genetics Unit (ATGU) at Massachusetts General Hospital, is a collaborator on the PGC study, and a co-corresponding author of the SCHEMA study.
“Identifying these 10 genes is a watershed moment in schizophrenia research because each one of them provides a solid foundation for launching biological inquiry,” said Benjamin Neale, another co-corresponding author on the SCHEMA study, a PGC collaborator, an institute member and director of genetics in the Stanley Center, co-director of the institute’s Program in Medical and Population Genetics, and faculty of the Mass General ATGU. “By sequencing the DNA of thousands of people, we are starting to see exactly which genes matter. These discoveries are the starting point for developing new therapies that treat the root cause of this devastating condition.”
“We’ve tried for years and years to gain this kind of traction on the biology of schizophrenia,” said Broad core institute member and Stanley Center director Steven Hyman. “Realistically, it will take yet more years to translate these results into biomarkers and treatments that will make a difference in the lives of people who are suffering with this devastating illness. But it is highly motivating to have a compelling path forward.”
A global collection
The SCHEMA and PGC findings are the fruit of a decade-long push led by researchers in the Stanley Center and nearly four dozen other institutions around the world. Both projects aim to gather and compare DNA from large numbers of people with and without schizophrenia. By working together, investigators across the PGC have built a dataset that now includes more than 320,400 people from collections across the world, including people of European, Finnish, African American, LatinX, East Asian, and Ashkenazi Jewish descent. The SCHEMA cohort comprises a subset of that, representing more than 121,000 people.
The two groups have followed complementary paths in their study of schizophrenia genetics. Since 2009, the PGC team has conducted increasingly larger genome-wide association studies cataloging common genetic variations called single nucleotide polymorphisms (or SNPs) that contribute to schizophrenia risk.
The SCHEMA (SCHizophrenia Exome Meta-Analysis) Consortium — which came together in 2017 — focuses on the exome, the nearly two-percent of the genome that encodes proteins. Specifically, the SCHEMA Consortium looked for variants that would either knock out or markedly alter a gene’s ability to produce functioning proteins.
“There’s 10 years worth of data represented in these studies,” said Sinéad Chapman, the director, global genetics project management in the Stanley Center who, along with team members Christine Stevens, Caroline Cusick, and many others, spent hundreds of hours ensuring that the samples and data from the SCHEMA collaborators were properly processed and tracked for these analyses. “It was quite a manual process, as there isn’t one magic system to connect all the samples and data and all of their related regulatory and clinical information.”
According to Singh, these two studies were possible because the necessary pieces were finally in place. “The genomic technologies, the sequencing infrastructure, the computational tools needed to understand the data they produce, have advanced dramatically in the last two decades,” he said. “The most important piece was the global commitment on the part of PGC and SCHEMA members to share samples and data across institutions and nations to achieve the numbers of people needed to bring these rare mutations to light.”
By sequencing whole exomes from 24,248 people with schizophrenia and 97,322 without, the SCHEMA team identified ultra-rare variants in 10 genes that dramatically increased a person’s risk of developing schizophrenia. These variants, called PTVs for “protein truncating variants,” prevent cells from producing a gene’s full-length functional protein.
“In general, any given person has a roughly one percent chance of developing schizophrenia in their lifetime,” said Neale. “But if you have one of these mutations, it becomes a 10, 20, even 50 percent chance.”
Their findings also hint at an additional 22 genes that also likely influence schizophrenia risk, and which may prove significant after further study. Data from the SCHEMA study are available at schema.broadinstitute.org.
Together, these genes point to dysfunction at the synapse — where neurons connect and communicate with each other — as a possible cause of schizophrenia. This idea first emerged several years ago, thanks in part to a 2016 study from researchers at the Broad’s Stanley Center, Harvard Medical School, and Boston Children’s Hospital. In that study, they described for the first time how variations in a single gene — complement component 4, or C4 — raises schizophrenia risk by triggering excessive “pruning” of synapses.
Insights into two of the 10 genes from the SCHEMA study, GRIN2A and GRIA3, further implicate the synapse as a key part of schizophrenia’s mechanistic roots. These two genes encode portions of the glutamate receptor, a cellular antenna found at the synapse that allows neurons to receive chemical signals from neighboring neurons. Pharmacological studies have previously suggested that glutamate signaling may be involved in schizophrenia, but the SCHEMA study provides the first solid genetic evidence of this. Additionally, GRIN2A activity in the brain peaks during adolescence, around the time people suffering schizophrenia begin to experience symptoms.
Most of the SCHEMA genes, however, have never before been associated with a brain disorder or neuron-specific functions. One gene (SETD1A) is involved in transcriptional regulation. Another (CUL1) helps the cell recycle old or unneeded proteins, while yet another (XPO7) helps chaperone molecules out of the cell’s nucleus. Yet in the SCHEMA analysis, PTVs in these genes drive a 20- to 52-fold increase in schizophrenia risk.
“We don’t yet have a well-developed framework for understanding how these genes might play a role in schizophrenia,” said SCHEMA co-corresponding author and PGC collaborator Mark Daly, who is also an institute member in the Stanley Center, Mass General ATGU faculty, and director of the Institute for Molecular Medicine, Finland. “These genes will ultimately lead to some new insights, but are going to require a lot of experimental follow-up to see where they might fit in the puzzle.”
Separately, the PGC team examined common genetic variations in 76,755 people with schizophrenia and 243,649 without, finding 287 regions of the genome (or loci) as having some involvement in schizophrenia risk, an increase of 94 loci since the last PGC analysis released in 2019. With further analysis they identified 120 genes that potentially increase risk for schizophrenia. Several of these genes were also identified in the SCHEMA study.
The PGC team also found that the genomic regions they implicated are largely active only in neurons, only in the brain, and affect mechanisms that directly impact neuron function, such as synaptic structure and organization.
The nature and effect of the variants detected by PGC differed in some ways from the SCHEMA findings. For instance, the damaging protein-coding GRIN2A mutations SCHEMA identified are extremely rare and raise schizophrenia risk 24-fold. The variants found in the PGC study are far more common and change GRIN2A expression, increasing risk by only 1.06-fold.
However, the fact that both studies’ findings converge similar groups of genes and similar biological mechanisms suggests that genetic discoveries are beginning to home in on core aspects of schizophrenia biology, and are close to broader insights into the mechanisms underlying schizophrenia progression.
“Our hope was that we would end up with some amount of overlap in the stories that the common and rare variant associations were telling us,” said Neale. “And we see overlap pointing to a relationship between synaptic biology and schizophrenia risk.”
Revelations into shared risk
The SCHEMA data also shed light on how psychiatric and neurodevelopmental disorders more broadly can share genetic risk. For instance, several SCHEMA genes, including GRIN2A, have previously been implicated with neurodevelopmental conditions such as epilepsy, developmental delay, and intellectual disability.
But by comparing their data from that of other large-scale studies, the SCHEMA team noted that the overlaps they saw were driven by different kinds of mutations: PTVs for schizophrenia, missense mutations (which can lead to amino acid swaps that modify a protein’s activity) for the neurodevelopmental conditions.
“We see that a spectrum of consequences can arise from different kinds of mutation in the same genes,” Neale noted. “We have a lot more to do and a lot more to learn about what these genes do, what variations in these genes do, and what the biological consequences of genetic variation really are writ large.”
“This point is critical for gaining insight into how genetics works across brain disorders,” Daly added. “We need to make sure that we don’t take a siloed view of these data, and instead remain open to learning what these genetics has to teach us across phenotypes.”
And indeed, this perspective is already bearing fruit. In a separate study published in Nature Genetics, members of the international Bipolar Exome Consortium (BipEx), including Neale, report how comparisons of SCHEMA and BipEx data have helped reveal rare PTVs in the gene AKAP11 gene that raise the risk of bipolar disorder several-fold, making it the strongest genetic risk factor found for bipolar disorder to date.
Fitting the puzzle pieces together
Already a great deal of work is being done to model the effects of the SCHEMA mutations in the laboratory. Researchers also recognize that there are many additional genetic discoveries waiting to be found.
“These first 10 genes are really only the beginning of genetic discovery,” Neale said. “There is pretty clear evidence that there are many more genes to discover using the same kind of approach. But we fundamentally need bigger sample sizes to be able to reveal those additional genes.
“But, if you have more pieces of the puzzle,” he continued, “it might be a little bit easier to fit them together and come into a slightly more coherent mechanistic view of schizophrenia, and how we might start to approach those processes with the hope of improving patient’s lives.”
“The biological complexity of schizophrenia is truly daunting, but this combination of rare protein altering variants from exome sequencing and common variants from GWAS have put us on our way to understanding the roots of that complexity,” said Hyman. “In these results, we may be seeing how synaptic abnormalities or losses begin in schizophrenia, giving us openings to diagnosing and treating people much earlier than we can today.”
“With schizophrenia, like with other complex disorders, I think we will ultimately find that many processes are involved in risk or protection,” Daly added. “Understanding that may turn out to be one of the most complex undertakings in genetics and biology.”
1. Tarjinder Singh, Timothy Poterba, David Curtis, Huda Akil, Mariam Al Eissa, Jack D. Barchas, Nicholas Bass, Tim B. Bigdeli, Gerome Breen, Evelyn J. Bromet, Peter F. Buckley, William E. Bunney, Jonas Bybjerg-Grauholm, William F. Byerley, Sinéad B. Chapman, Wei J. Chen, Claire Churchhouse, Nicholas Craddock, Caroline M. Cusick, Lynn DeLisi, Sheila Dodge, Michael A. Escamilla, Saana Eskelinen, Ayman H. Fanous, Stephen V. Faraone, Alessia Fiorentino, Laurent Francioli, Stacey B. Gabriel, Diane Gage, Sarah A. Gagliano Taliun, Andrea Ganna, Giulio Genovese, David C. Glahn, Jakob Grove, Mei-Hua Hall, Eija Hämäläinen, Henrike O. Heyne, Matti Holi, David M. Hougaard, Daniel P. Howrigan, Hailiang Huang, Hai-Gwo Hwu, René S. Kahn, Hyun Min Kang, Konrad J. Karczewski, George Kirov, James A. Knowles, Francis S. Lee, Douglas S. Lehrer, Francesco Lescai, Dolores Malaspina, Stephen R. Marder, Steven A. McCarroll, Andrew M. McIntosh, Helena Medeiros, Lili Milani, Christopher P. Morley, Derek W. Morris, Preben Bo Mortensen, Richard M. Myers, Merete Nordentoft, Niamh L. O’Brien, Ana Maria Olivares, Dost Ongur, Willem H. Ouwehand, Duncan S. Palmer, Tiina Paunio, Digby Quested, Mark H. Rapaport, Elliott Rees, Brandi Rollins, F. Kyle Satterstrom, Alan Schatzberg, Edward Scolnick, Laura J. Scott, Sally I. Sharp, Pamela Sklar, Jordan W. Smoller, Janet L. Sobell, Matthew Solomonson, Eli A. Stahl, Christine R. Stevens, Jaana Suvisaari, Grace Tiao, Stanley J. Watson, Nicholas A. Watts, Douglas H. Blackwood, Anders D. Børglum, Bruce M. Cohen, Aiden P. Corvin, Tõnu Esko, Nelson B. Freimer, Stephen J. Glatt, Christina M. Hultman, Andrew McQuillin, Aarno Palotie, Carlos N. Pato, Michele T. Pato, Ann E. Pulver, David St. Clair, Ming T. Tsuang, Marquis P. Vawter, James T. Walters, Thomas M. Werge, Roel A. Ophoff, Patrick F. Sullivan, Michael J. Owen, Michael Boehnke, Michael C. O’Donovan, Benjamin M. Neale, Mark J. Daly. Rare coding variants in ten genes confer substantial risk for schizophrenia. Nature, 2022; DOI: 10.1038/s41586-022-04556-w
2. Vassily Trubetskoy et al. Mapping genomic loci implicates genes and synaptic biology in schizophrenia. Nature, 2022; DOI: 10.1038/s41586-022-04434-5
3. Palmer DS, and the Bipolar Exome Consortium. Exome sequencing in bipolar disorder identifies AKAP11 as a risk gene shared with schizophrenia. Nature Genetics, 2022 DOI: 10.1038/s41588-022-01034-x
3. Using Only Text Data to Screen for PTSD?
From University of Alberta
University of Alberta researchers have trained a machine learning model to identify people with post-traumatic stress disorder with 80 per cent accuracy by analyzing text data. The model could one day serve as an accessible and inexpensive screening tool to support health professionals in detecting and diagnosing PTSD or other mental health disorders through telehealth platforms.
Psychiatry PhD candidate Jeff Sawalha, who led the project, performed a sentiment analysis of text from a dataset created by Jonathan Gratch at USC’s Institute for Creative Technologies. Sentiment analysis involves taking a large body of data, such as the contents of a series of tweets, and categorizing them — for example, seeing how many are expressing positive thoughts and how many are expressing negative thoughts.
“We wanted to strictly look at the sentiment analysis from this dataset to see if we could properly identify or distinguish individuals with PTSD just using the emotional content of these interviews,” said Sawalha.
The text in the USC dataset was gathered through 250 semi-structured interviews conducted by an artificial character, Ellie, over video conferencing calls with 188 people without PTSD and 87 with PTSD.
Sawalha and his team were able to identify individuals with PTSD through scores indicating that their speech featured mainly neutral or negative responses.
“This is in line with a lot of the literature around emotion and PTSD. Some people tend to be neutral, numbing their emotions and maybe not saying too much. And then there are others who express their negative emotions.”
The process is undoubtedly complex. For example, even a simple phrase like “I didn’t hate that” could prove challenging to categorize, explained Russ Greiner, study co-author, professor in the Department of Computing Science and founding scientific director of the Alberta Machine Intelligence Institute. However, the fact that Sawalha was able to glean information about which individuals had PTSD from the text data alone opens the door to the possibility of applying similar models to other datasets with other mental health disorders in mind.
“Text data is so ubiquitous, it’s so available, you have so much of it,” Sawalha said. “From a machine learning perspective, with this much data, it may be better able to learn some of the intricate patterns that help differentiate people who have a particular mental illness.”
Next steps involve partnering with collaborators at the U of A to see whether integrating other types of data, such as speech or motion, could help enrich the model. Additionally, some neurological disorders like Alzheimer’s as well as some mental health disorders like schizophrenia have a strong language component, Sawalha explained, making them another potential area to analyze.
1. Jeff Sawalha, Muhammad Yousefnezhad, Zehra Shah, Matthew R. G. Brown, Andrew J. Greenshaw, Russell Greiner. Detecting Presence of PTSD Using Sentiment Analysis From Text Data. Frontiers in Psychiatry, 2022; 12 DOI: 10.3389/fpsyt.2021.811392
4. Screening Bone Loss Using Hormone Levels
From University of California – Los Angeles Health Sciences
Physicians may be able to determine if menopause-related bone loss is already in progress or about to begin by measuring the level of a hormone that declines as women approach their final menstrual period, new UCLA research finds.
The findings could help physicians determine when, and how, to treat bone loss in women as they age before that bone loss causes significant health issues, according to the study. Specifically, the study found that for women 42 and older who are not yet postmenopausal, levels of anti-Mullerian hormone, or AMH, can be used to determine if they are experiencing, or about to experience, bone loss related to their transition into menopause.
The findings will be published April 4 in the peer-reviewed Journal of Bone and Mineral Research.
“To be able to intervene and reduce the rate and amount of bone loss, we need to know if this loss is imminent or already ongoing,” said the study’s lead author, Dr. Arun Karlamangla, a professor of medicine in the division of geriatrics at the David Geffen School of Medicine at UCLA. “We do not reliably know before it actually happens when a woman’s last menstrual period will be, so we cannot tell whether it is time to do something about bone loss.”
Bone loss typically begins about a year before a woman’s last menstrual period, Karlamangla said.
Women experience significant bone loss during the menopause transition, a roughly three-year window that brackets the final menstrual period and is accompanied by other symptoms such as irregular menstrual cycles, hot flashes, and mood and sleep disorders. Levels of the AMH decline as a woman’s final menstrual period draws closer.
The researchers examined data from the Study of Women’s Health Across the Nation, or SWAN, a multisite, multi-ethnic study examining the changes women undergo during the transition to menopause.
They found that 17% of premenopausal women age 42 or older will have lost a significant fraction of their peak bone mass within two to three years of the date a physician makes the prediction. But among those with less than 50 picograms of AMH per milliliter of blood, nearly double the percentage, 33%, will have lost a significant fraction of peak bone mass in the same timeframe. (A picogram is one-trillionth of a gram.)
In addition, 42% of women in early perimenopause — meaning that they have irregular menstrual bleeding but with no more than a three-month gap between periods — will have lost a significant fraction of peak bone mass within two to three years. But among women in early perimenopause with AMH levels below 25 pg/mL, 65% will have lost a significant percentage of peak bone mass in that time.
The study has some limitations, the researchers note. The findings cannot be applied to women who are already taking osteoporosis medications, have undergone a hysterectomy prior to their final period, or have used exogenous sex hormones during the transition to menopause; and the study did not include Hispanic women, nor did it include women who became menopausal before age 42.
“These findings make feasible the designing and testing of midlife interventions to prevent or delay osteoporosis in women,” the study’s authors write.
The Study of Women’s Health Across the Nation is supported by the National Institutes of Health through the National Institute on Aging, the National Institute of Nursing Research and the NIH Office of Research on Women’s Health.
The study’s co-authors are Dr. Albert Shieh and Dr. Gail Greendale of UCLA; Dr. Elaine Yu, Dr. Sherri-Ann Burnett-Bowie, Dr. Patrick Sluss and Dr. Joel Finkelstein of Harvard University; Deborah Martin of the University of Pittsburgh; and Anthony Morrison of Motive Biosciences.
1. Arun S Karlamangla, Albert Shieh, Gail A Greendale, Elaine W Yu, Sherri‐Ann M Burnett‐Bowie, Patrick M Sluss, Deborah Martin, Anthony Morrison, Joel S Finkelstein. Anti‐Mullerian Hormone as Predictor of Future and Ongoing Bone Loss During the Menopause Transition. Journal of Bone and Mineral Research, 2022; DOI: 10.1002/jbmr.4525
5. Post Concussion Symptoms May be From Damaged Nerve
From Lund University
Depression, dizziness, difficulty focusing the gaze and balance problems. Many professional athletes who have sustained head trauma in sports have lingering symptoms that affect everyday life. Little help has been available as the cause has been unknown. A clinical study from Lund University in Sweden can now show that the problems originate in an injury to the vestibular nerve.
Athletes in contact sports such as ice hockey, football and skiing have an increased risk of sustaining a head injury. If the impact is severe enough, the athlete can suffer a concussion. Even minor head injuries can have serious consequences. The problems have been brought to light within American football, where players who have suffered from repeated concussions have developed dementia, severe depression and cognitive impairment.
In many cases, the symptoms after a concussion are temporary, but an increasing number of athletes experience long-term problems that make it difficult to work, go to school or play sports. The symptoms are aggravated by activity or impressions and include headaches, depression, anxiety, nausea, difficulty focusing and problems with balance.
“It has been unclear what causes the symptoms, and it is difficult for healthcare professionals to help these athletes. We wanted to investigate this further to find out what really causes the symptoms,” says Niklas Marklund, professor of neurosurgery at Lund University, consultant at Skåne University Hospital with a scientific interest in sports-related head injuries and one of the researchers behind the article.
A total of 42 people were included in the study. One group included 21 healthy athletes without previous trauma to the head, and the other 21 athletes who all suffered from sports-related concussions and who had experienced persisting symptoms for more than six months. All the participants underwent various tests in which the researchers examined, among other things, their balance organs. Using a so-called 7-Tesla MRI, the athletes’ brains were studied to understand more about what caused the symptoms. The researchers found impaired function of the balance organs in the inner ear of 13 athletes in the group with long-term problems. In the group of healthy athletes 3 people had similar findings.
“The test results show that the injury is located to the vestibular nerve, which is connected to the semicircular canals in a cavity inside the skull, and which is directly adjacent to the cochlea in the ear. These injuries lead to the inward nerve impulses not working properly, and the brain therefore does not receive important information about body movements and sensory impressions required to maintain a good balance,” says Anna Gard, doctoral student at Lund University, resident in neurosurgery at Skåne University Hospital and first author of the study.
When you suffer from a concussion, it is often because the head rotates too fast, for example when tackling in ice hockey.
“We have not examined athletes with short-term problems after blows to the head, so we cannot say anything about them. This study applies to athletes with prolonged symptoms after concussion. The rotation of the head that occurs in connection with a concussion could lead to a stretch of the vestibular nerve, which then leads to impaired function. Now that we have more knowledge about where the problems are located, it is easier to find possible therapies that could help these athletes,” concludes Niklas Marklund.
1. Anna Gard, Ali Al-Husseini, Evgenios N. Kornaropoulos, Alessandro De Maio, Yelverton Tegner, Isabella Björkman-Burtscher, Karin Markenroth Bloch, Markus Nilsson, Måns Magnusson, Niklas Marklund. Post-Concussive Vestibular Dysfunction Is Related to Injury to the Inferior Vestibular Nerve. Journal of Neurotrauma, 2022; DOI: 10.1089/neu.2021.0447
News Briefs – NaturalPath
1. Linking Heart Disease in People with Diabetes Using Gene Mapping
From American Heart Association
A risk score based on a gene map predicted the likelihood of high blood pressure leading to heart problems or stroke in people with Type 2 diabetes, according to a study published today in the American Heart Association’s peer-reviewed journal Hypertension. This tool may be especially useful in guiding treatment for people who are newly diagnosed with Type 2 diabetes or for those with prediabetes.
Previous research has confirmed adults with Type 2 diabetes are twice as likely to have a heart attack or stroke than people who do not have Type 2 diabetes. Various measures of health status, such as blood pressure, cholesterol and blood sugar levels, are commonly used to determine a person’s risk for developing heart disease. In this study, researchers explored whether genetic variants linked with high blood pressure are also linked to later heart disease or stroke for people with Type 2 diabetes and used that information to determine a risk score.
“Increased genetic risk of high blood pressure may predispose some people with Type 2 diabetes to a higher risk of heart attack, stroke or cardiovascular death,” said lead study author Pankaj Arora, M.D., director of the Cardiogenomics Clinic Program and the Cardiology Clinical and Translational Research Program at the University of Alabama at Birmingham. “We conducted the study to determine if this genetic risk score can identify people with Type 2 diabetes who have a higher risk for cardiovascular events and if tight control of blood sugar impacts the link between genetic hypertension risk and cardiovascular outcomes.”
Arora and colleagues assessed the health records of 6,335 participants in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial database for whom genetic data were available. The study group consisted of 37% women, and participants self-identified their race or ethnicity: 15% were African American, 6% were Hispanic; 70% were white; and 9% selected the category “other.” All participants had Type 2 diabetes and elevated blood pressure, and they were followed for 3.5 years.
A genetic variant map of more than 1,000 common genetic variants known to affect blood pressure was compared to the DNA of the study participants to determine participants’ genetic risk. More matches among the participant’s DNA and the map of known blood pressure genetic variants equated to a higher genetic risk score.
Researchers found that the genetic risk score identified study participants with a higher risk of cardiovascular events:
- For people with higher than average genetic risk scores, each degree higher was associated with a 12% higher risk of heart disease or stroke events.
- The association of genetic risk with cardiovascular events was the same even if participants were taking medicines to manage blood sugar levels.
Further evaluation of genetic risk scores in people who do not have Type 2 diabetes is needed to be able to apply these findings more broadly.
Arora and colleagues also noted the findings about differences in individuals’ genetic risk scores for high blood pressure did not entirely explain why intensive glycemic control (aggressive treatment with insulin, medications, diet and exercise) did not appear to have a cardiovascular benefit for people with long-standing Type 2 diabetes.
“However, a genetic risk score maybe helpful for people newly diagnosed with Type 2 diabetes to identify who should have more intense lifestyle changes, such as changes in diet and exercise, and more aggressive management of weight, blood pressure and smoking cessation,” said Arora.
“If you have Type 2 diabetes, there’s a lot you can do to reduce your risk for heart disease,” said Eduardo Sanchez, M.D., M.P.H., FAHA, FAAFP, the American Heart Association’s chief medical officer for prevention, who is the clinical lead for Know Diabetes by Heart, a collaborative initiative between the American Heart Association and the American Diabetes Association addressing the link between diabetes and cardiovascular disease. “In addition to blood sugar control, which is absolutely paramount, we highly encourage people living with Type 2 diabetes to talk with their health care team about other personal and familial risk factors for heart disease or stroke, and what they can do to manage or modify them.”
Co-authors include Vibhu Parcha, M.D.; Akhil Pampana, M.S.; Adam Bress, Pharm.D., M.S.; Marguerite R. Irvin, Ph.D.; and Garima Arora, M.D.
1. Vibhu Parcha, Akhil Pampana, Adam P. Bress, Marguerite R. Irvin, Garima Arora, Pankaj Arora. Association of Polygenic Risk Score With Blood Pressure and Adverse Cardiovascular Outcomes in Individuals With Type II Diabetes: Insights From the ACCORD Trial. Hypertension, 2022; DOI: 10.1161/HYPERTENSIONAHA.122.18976
2. High Blood Pressure May be Related to a Bias Toward Perceiving Anger in Others
From University of Konstanz
Men with high blood pressure have a biased recognition of other people’s anger, as shown in a new study.
Hypertension is a disease. However, in the majority of cases, there is no clear medical explanation, referred to as “essential hypertension.” Could psychological factors play a role? In this context, Konstanz biological health psychologists Alisa Auer and Professor Petra Wirtz conducted a study in male participants over several years together with colleagues from Konstanz (Germany) and Switzerland. The researchers wanted to better understand the psychobiosocial mechanisms in hypertension, since previous work in this area has left many questions open.
In an article published in the Annals of Behavioral Medicine on 22nd March 2022, they show that compared to a healthy control group, men with essential hypertension more often recognized angry expressions when they looked into the faces of others. In addition, this anger recognition bias seems to contribute to blood pressure increases over time if someone tends to frequently and intensively experience anger. This tendency is called “trait anger.”
Recognition of mixed emotions
In their study in 145 hypertensive and normotensive men, researchers presented different pictures of people who were angry. However, the pictures did not just display anger alone, but combined anger with one of three other emotions: fear, happiness, and sadness. The background for this approach is that, in everyday life, people’s faces rarely show just one emotion. Mixed emotions are more prevalent. Each of the computer-morphed pictures showed two emotions with varying affect intensities. Participants were asked which emotion they saw in the pictures.
“Hypertensive men recognized anger more often than any other emotion,” Alisa Auer says. “So, they overrated anger displayed in other people’s faces as compared to our healthy control group.” Petra Wirtz adds: “Overrating anger displayed by other persons seems to affect whether high ‘trait anger’ contributes to blood pressure increases over time.” Hence, interpersonal factors seem to play a role in essential hypertension. The expectation of associations between hypertension and social aspects was one of the reasons why the study was supported by the Cluster of Excellence “Centre for the Advanced Study of Collective Behaviour.”
Improving treatment of essential hypertension
Auer and Wirtz hope that their results will be examined and confirmed by other researchers. “Then, a next step would be to offer people with essential hypertension a more targeted support,” says Alisa Auer, who is currently completing her doctorate in Psychology. Auer is thinking of “therapeutic treatments that address a person’s perception of social environments in order to protect them from other people´s anger.”
Such therapeutic interventions would be important, because blood pressure lowering medication only treats the consequences of hypertension, but does not address potential causes. In addition, hypertension is one of the major risk factors for cardiovascular disease. In 2020, as in previous years, the Federal Statistical Office (Destatis) listed cardiovascular disease as the leading cause of death in Germany. “338,001 deaths, or more than one third of all deaths (34%), can be attributed to cardiovascular disease,” Destatis reports. Cardiovascular disease is especially deadly for older people: 93% of those who died of cardiovascular disease were 65 years or older.
What about women? The researchers hope that future studies will include women. Since women may possibly differ in their emotion recognition from men and as fewer women suffer from hypertension, the study initially focused on men.
1. Alisa Auer, Roland von Känel, Ilona Lang, Livia Thomas, Claudia Zuccarella-Hackl, Cathy Degroote, Angelina Gideon, Roland Wiest, Petra H Wirtz. Do Hypertensive Men Spy With an Angry Little Eye? Anger Recognition in Men With Essential Hypertension – Cross-sectional and Prospective Findings. Annals of Behavioral Medicine, 2022; DOI: 10.1093/abm/kaab108
3. Cannabis Poses Threat to Babies Exposed During Pregnancy – Obesity and High Blood Sugar
From The Endocrine Society
Cannabis use among pregnant women is on the rise and may be associated with negative health outcomes in children, according to a new study published in the Endocrine Society’s Journal of Clinical Endocrinology and Metabolism.
A 2016 study in Colorado revealed that up to 22% of pregnant women had detectable levels of cannabinoids in their body. Women who use cannabis, both tetrahydrocannabinol (THC) and cannabidiol (CBD), during pregnancy could be putting their child at risk for low birth weight and behavioral problems. Exposure to cannabinoids may also increase the child’s future risk of obesity and high blood sugar.
Part of CBD’s popularity is that it is marketing as being “nonpsychoactive,” and that consumers can reap health benefits from the plant without the high. CBD is advertised as providing relief for anxiety, depression and post-traumatic stress disorder. It is also marketed to promote sleep.
“We found that cannabis use during pregnancy was linked to increased fat mass percentage and fasting glucose levels in 5-year-old children,” said Brianna Moore, Ph.D., of the Colorado School of Public Health in Aurora, Colo. “We would encourage women to refrain from using any cannabis while pregnant or breastfeeding to minimize adverse health effects in the offspring.”
The researchers studied urine samples from 103 pregnant women, 15% of whom had detectable levels of cannabinoids (such as THC and CBD) in their urine. These mothers’ 5-year-old children had higher fat mass and fasting glucose levels compared to children who were not exposed to cannabis during pregnancy.
“More studies are needed to understand how exposure to different cannabinoids during pregnancy may impact the offspring,” Moore said.
Other authors of this study include: Katherine Sauder and Dana Dabelea of the Colorado School of Public Health and the University of Colorado School of Medicine in Aurora, Colo.; Allison Shapiro of the University of Colorado Anschutz Medical Campus in Aurora Colo.; and Tessa Crume and Gregory Kinney of the Colorado School of Public Health in Aurora Colo.
The study received funding from the National Institutes of Health.
1. Brianna F Moore, Katherine A Sauder, Allison L B Shapiro, Tessa Crume, Gregory L Kinney, Dana Dabelea. Fetal Exposure to Cannabis and Childhood Metabolic Outcomes: The Healthy Start Study. The Journal of Clinical Endocrinology & Metabolism, 2022 DOI: 10.1210/clinem/dgac101
4. A Microchip to Help Sperm Swim the Right Direction
From Florida Atlantic University
The female genital tract can be a hostile environment for conception. Out of about 100 million sperm, only a few hundred make it to the fallopian tubes. Guided by a directional movement called rheotaxis, sperm cells swim against the cervical mucus flow to reach the egg for fertilization. This journey, however, is even more critical when considering infertility. Sperm motility — the ability to swim the right way — is key.
By taking advantage of this natural rheotaxis behavior of sperm, researchers from Florida Atlantic University’s College of Engineering and Computer Science have developed a microfluidic chip for sperm sorting that is fast, inexpensive, easy to operate and efficiently isolates healthy sperm directly from semen. Importantly, it effortlessly collects sorted sperm cells from the collecting chamber while minimizing contamination by deformed or dead sperm cells.
Assisted reproductive technologies such as in vitro fertilization (IVF), intrauterine insemination and intracytoplasmic sperm injection all require healthy sperm cells for a successful outcome. Current centrifugation methods for sperm sorting require multiple steps, multiple types of equipment and take about two hours to isolate sperm cells. These methods damage sperm during processing and induce significant DNA fragmentation and oxidative stress.
Results of the study, published in the journal Analyst of the Royal Society of Chemistry, showed that sperm cells isolated from the collecting chamber in this microfluidic chip exhibited significantly higher motility (almost 100 percent), a higher number of morphologically normal cells and substantially lower DNA fragmentation, which is a crucial parameter for the fertilization process. In addition, the developed chip provides more than enough cells required for a successful intracytoplasmic sperm injection due to the amount and quality of sperm cells isolated using the chip.
“Operating our chip is very easy. Once the semen is loaded into the sample inlet chamber, the competent sperm cells start moving against the fluid flow toward the collecting chamber from where they can easily be collected,” said Waseem Asghar, Ph.D., senior author, an associate professor in FAU’s Department of Electrical Engineering and Computer Science, and a member of the FAU Institute for Human Health and Disease Intervention (I-Health) and FAU Institute for Sensing and Embedded Network Systems Engineering (I-SENSE). “Furthermore, this chip offers a one-step, one-hour operational benefit, which an operator can use with minimal training.”
The study also validates that rheotaxis selects the healthy, motile, and higher velocity sperm cells for the fertilization process.
“The assembly of the microfluidic chip is low-cost, and the reagents used in the chip to separate sperm cells are only a few milliliters, therefore, the commercial cost of the chip would be less than $5,” said Asghar. “Moreover, this technology will considerably reduce the economic burden of fertility implementations and both the chip and the sperm cells isolated from it offer great clinical significance and applicability.”
The microfluidic chip consists of four cylindrical chambers that are connected through the microchannels. The four chambers are the fluid inlet chamber, collecting chamber, sample inlet chamber, and waste collection chamber. The channel between the collecting chamber and sample inlet contains microgrooves to guide the sperm cells in addition to the fluid flow for the rheotaxis movement of the sperm cells towards the collecting chamber.
The shear stress inside the device is generated by fluid flow using a syringe pump. A raw semen sample is then added to the sample inlet chamber from where functional sperm cells will swim towards the collecting chamber, effectively separating themselves from dead and immotile sperm.
“Conventional centrifugation often compromises the integrity of sperm cells. This research study demonstrates that the microfluidic chip developed by professor Asghar and his colleagues eliminates this issue,” said Stella Batalama, Ph.D., dean, College of Engineering and Computer Science. “This novel technology offers a platform where the sperm cells experience different shear stress in different parts of the chip, which facilitates the isolation of competent sperm cells without impacting their integrity.”
In the United States, an estimated 15 percent of couples have trouble conceiving. Globally, approximately 48.5 million couples experience infertility. According to the U.S. Centers for Disease Control and Prevention, 12 percent of women of childbearing age have used an infertility service. All treatment costs for infertility can range from $5,000 to $73,000. The average patient goes through two IVF cycles, bringing the total cost of this procedure, including medications, between $40,000 and $60,000. An estimated 85 percent of IVF costs are often paid out-of- pocket.
Study co-authors are Sandhya Sharma and Md. Alam Kabir, Ph.D. candidates in the Asghar Laboratory, Micro and Nanotechnology in Medicine, FAU Department of Electrical Engineering and Computer Science.
1. Sandhya Sharma, Md. Alamgir Kabir, Waseem Asghar. Selection of healthy sperm based on positive rheotaxis using a microfluidic device. The Analyst, 2022; DOI: 10.1039/d1an02311j
5. A Healthy Whole-Foods Diet Emphasizing Plant-Based Foods is Still Prevents Diabetes
New research published in Diabetologia (the journal of the European Association for the Study of Diabetes [EASD]) finds that the consumption of healthy plant-based foods, including fruits, vegetables, nuts, coffee, and legumes, is associated with a lower risk of developing type 2 diabetes (T2D) in generally healthy people and support their role in diabetes prevention.
The study was conducted by Professor Frank Hu and colleagues at the Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA, and aimed to identify the metabolite profiles related to different plant-based diets and investigate possible associations between those profiles and the risk of developing T2D.
A metabolite is a substance used or produced by the chemical processes in a living organism and includes the vast number of compounds found in different foods as well as the complex variety of molecules created as those compounds are broken down and transformed for use by the body. Differences in the chemical makeup of foods means that an individual’s diet should be reflected in their metabolite profile. Recent technological advances in the field of high-throughput metabolomics profiling have ushered in a new era of nutritional research. Metabolomics is defined as the comprehensive analysis and identification of all the different metabolites present within a biological sample.
Over 90% of diabetes cases are the type 2 form, and the condition poses a major threat to health around the world. Global prevalence of the disease in adults has more than tripled in less than two decades, with cases increasing from around 150 million in 2000 to over 450 million in 2019 and projected to rise to around 700 million in 2045.
The global health burden of T2D is further increased by the numerous complications arising from the disease, both macrovascular, such as cardiovascular disease, and microvascular, which damage the kidneys, the eyes, and the nervous system. The diabetes epidemic is primarily caused by unhealthy diets, having overweight or obesity, genetic predisposition, and other lifestyle factors such as a lack of exercise. Plant-based diets, especially healthy ones rich in high quality foods such as whole grains, fruits, and vegetables, have been associated with a lower risk of developing T2D but the underlying mechanisms involved are not fully understood.
The team conducted an analysis of blood plasma samples and dietary intake of 10,684 participants from three prospective cohorts (Nurses’ Health Study, Nurses’ Health Study II and Health Professionals Follow-up Study). Participants were predominantly white, middle-aged (mean age 54 years), and with a mean body mass index (BMI) of 25.6kg/m2.
Study participants completed food frequency questionnaires (FFQs) which were scored according to their adherence to three plant-based diets: an overall Plant-based Diet Index (PDI), a healthy Plant-based Diet Index (hPDI), and an Unhealthy Plant-Based Diet Index (uPDI). Diet indices were based on that individual’s intake of 18 food groups: healthy plant foods (whole grains, fruits, vegetables, nuts, legumes, vegetable oils, and tea/coffee); unhealthy plant foods (refined grains, fruit juices, potatoes, sugar-sweetened beverages, and sweets/desserts); and animal foods (animal fats, dairy, eggs, fish/seafood, meat, and miscellaneous animal-based foods). The team distinguished between healthy and unhealthy plant foods according to their association with T2D, cardiovascular disease, certain cancers, and other conditions, including obesity and high blood pressure.
The researchers tested blood samples taken back in late 1980s and 1990s in the early phase of the three studies mentioned above to create metabolite profile scores for the participants, and any cases of incident T2D during the follow-up period of the study were recorded. Analyses of these data together with the diet index scores enabled the team to find any correlations between metabolite profile, diet index, and T2D risk.
The study found that compared with participants who did not develop T2D, those who were diagnosed with the disease during follow-up had a lower intake of healthy plant-based foods, as well as lower scores for PDI and hPDI. In addition, they had a higher average BMI, and were more likely to have high blood pressure and cholesterol levels, use blood pressure and cholesterol drugs, have a family history of diabetes, and be less physically active.
The metabolomics data revealed that plant-based diets were associated with unique multi-metabolite profiles, and that these patterns differed significantly between the healthy and unhealthy plant-based diets. In addition, metabolite profile scores for both the overall plant-based diet and the healthy plant-based diet were inversely associated with incident T2D in a generally healthy population, independent of BMI, and other diabetes risk factors, while no association was observed for the unhealthy plant-based diet. As a result, higher metabolite profile scores for PDI and hPDI indicated both closer adherence to those diets and having a lower risk of developing T2D.
Further analysis revealed that after adjusting for levels of trigonelline, hippurate, isoleucine, a small set of triacyglycerols (TAGs), and several other intermediate metabolites, the association between plant-based diets and T2D largely disappeared, suggesting that they might play a key role in linking those diets to incident diabetes. Trigonelline, for example, is found in coffee and has demonstrated beneficial effects on insulin resistance in animal studies, while higher levels of hippurate are associated with better glycaemic control, enhanced insulin secretion and lower risk of T2D. The team suggest that these metabolites could be investigated further and may provide mechanistic explanations of how plant-based diets can have a beneficial effect on T2D risk.
Professor Hu explains: “While it is difficult to tease out the contributions of individual foods because they were analysed together as a pattern, individual metabolites from consumption of polyphenol-rich plant foods like fruits, vegetables, coffee, and legumes are all closely linked to healthy plant-based diet and lower risk of diabetes.”
The authors conclude: “Our findings support the beneficial role of healthy plant-based diets in diabetes prevention and provide new insights for future investigation…our findings regarding the intermediate metabolites are at the moment intriguing but further studies are needed to confirm their causal role in the associations of plant-based diets and the risk of developing type 2 diabetes.”
Since they only collected blood samples at one point in time, the authors also believe that long-term repeated metabolomics data are needed to understand how dietary changes relate to changes in metabolome, thereby influencing T2D risk.
1. Fenglei Wang, Megu Y. Baden, Marta Guasch-Ferré, Clemens Wittenbecher, Jun Li, Yanping Li, Yi Wan, Shilpa N. Bhupathiraju, Deirdre K. Tobias, Clary B. Clish, Lorelei A. Mucci, A. Heather Eliassen, Karen H. Costenbader, Elizabeth W. Karlson, Alberto Ascherio, Eric B. Rimm, JoAnn E. Manson, Liming Liang, Frank B. Hu. Plasma metabolite profiles related to plant-based diets and the risk of type 2 diabetes. Diabetologia, 2022; DOI: 10.1007/s00125-022-05692-8