The findings, now published in Genetics in Medicine OPEN, revealed a correlation between occurrences of complex genetic disorders in those families with increased levels of consanguinity when compared to unaffected populations. Consanguinity is when both parents contribute similar genetic markers to an offspring, such as by sharing a common ancestor, and the genetic information from both the genome inherited from the father and that from the mother are identical.

“We observed that the areas on the chromosome known as ROH, regions of homozygosity, were longer in those individuals in which there was a higher degree of parental consanguinity when compared to those with less,” said Dr. Zeynep Coban-Akdemir, postdoctoral associate in molecular and human genetics at Baylor and currently assistant professor at UTHealth School of Public Health as well as co-lead author on the study. “We can see what is happening when consanguinity is at play and also when new genetic variations are introduced into the family unit of the clan or tribe representing more distant ancestors.”

Dr. Xiaofei Song, a former Baylor graduate student now working as an assistant professor at Moffitt Cancer Center, said, “We further applied a statistical method to systematically assess the impact of these genetic variations on disease. Our results indicate that the newly introduced genetic variations can better explain the clinical features observed in our patients.” Song also is co-lead author on the study.

“The published study contributes to the field of both rare disease and population genomics. From a trainee perspective, the article provides a valuable resource for comprehending fundamental concepts of human genetics and applying diverse computational methods to elucidate these concepts,” said Ph.D candidate Tugce Bozkurt-Yozgatli, with the Acibadem University in Istanbul, Turkey.

Coban-Akdemir, who worked in the Lupski Lab at Baylor where the research was conducted, says this is an important part of the findings because it reveals how genes act within different populations and clans to contribute to different recessive genetic disorders.

The population studied was a cohort of individuals originating from Turkey that is known to have different variations in genetic markers when compared to other populations from greater Europe. Researchers created and analyzed a database of variants derived from exome sequencing, a genomics assay providing a glimpse into genetic variation genomewide, of 773 unrelated volunteers who were affected with various suspected rare Mendelian disease traits, which are diseases caused by a mutation in a single gene and clearly passed down from one generation to the next in accordance with Gregor Mendel expectations. They were compared to another database created by the same researchers of 643 unaffected relatives.

Roughly half of the genetic variants in this Turkish group are not present in greater European control populations that are found in shared databases commonly used by genetic researchers.

“This group of Turkish individuals and families gives us insight into genetics that the average population doesn’t provide. What we found in this Turkish population is very unique. Not only is this group underrepresented in larger databases, but it shows us that they have an enriched genetic variation that is only seen within this population when compared to European populations,” Coban-Akdemir said.

Dr. Davut Pehlivan, assistant professor of pediatrics — neurology at Baylor, said on a single individual there are around 40 million Watson-Crick base pair variations within our DNA.

“The Human Genome Project opened the doors for researchers to investigate entire genomic DNA complement using next-generation sequencing technology. However, more struggles appeared with these advancements. For example, it is hard to pinpoint which variant is causing disease among 40 million variations of our DNA. Studying healthy populations helps us to eliminate many of these common variations from consideration. Thus, we studied both patients and their healthy relatives in the Turkish population.” Pehlivan said. “There are a lot of changes in the genome, and we don’t fully understand the meaning of all of those details, but the data from this population study will help all investigators around the world who are trying to interpret the results of other variants in the human genome DNA.”

Pehlivan described gathering the information and families wanting to participate in genomics research beginning in 2010, traveling long distances to rural areas where the patients were mostly located, a human interest story itself, to make sure the database and clinical information would show an accurate representation for these families.

“We discovered more than 200 genes that contributed to the existing body of disease gene associations. This will help us get closer to understanding, in this population and in others, what is causing these diseases and the human biological perturbation underlying a broad scope of diseases. Our studies will open new avenues of research in human biology and genome biology and eventually help to potentially bring nucleic acid treatments, something used to develop the COVID vaccine, to the patients and families” Pehlivan said.

“This team of researchers is not just helping the population that they studied, but their findings also can be applied to many populations. We all are very different individuals on this planet, yet our genes act very similarly, and we all share a common humanity. So, understanding how genetic disorders work helps us to support affected families across the globe,” said Dr. James R. Lupski, the Cullen Foundation Endowed Chair in Genetics and Genomics at Baylor.

In the past, Coban-Akdemir and Dr. Claudia M.B Carvalho, previously with Baylor and currently in her own laboratory at the Pacific Northwest Research Institute (PNRI) in Seattle who also contributed to this study, have worked on studying variants of genes to identify causes of diseases through production of truncated or altered proteins that take on a new or different function. Their work also focused on databases of populations with and without genetic disease. Their current work reflects the importance of diversity and inclusion as work continues to reveal causes of genetic diseases.

This work was supported in part by the U.S. National Human Genome Research Institute /National Heart Lung and Blood Institute grant number UM1HG006542 to the Baylor Hopkins Center for Mendelian Genomics (BHCMG), the U.S. National Human Genome Research Institute U01HG011758 to the Baylor College of Medicine for the Genomics Research to Elucidate the Genetics of Rare Disease consortium (BCM-GREGoR), the National Institute of Neurological Disorders and Stroke Q22 (NINDS) R35NS105078, and the National Human Genome Research Institute U54-HG003273. J.E.P. was supported by NHGRI K08 HG008986.

This result provided new information. “To our knowledge, there are no previous reports on the bitter-blocking effect of this diabetes drug,” said first author Ha Nguyen, PhD, Monell Postdoctoral Fellow.Rosiglitizone was identified as a potential bitter blocker using tests of human cells from taste tissue, a method of screening developed by Monell and DiscoveryBiomed, Inc., now Eurofins.

The team conducted taste-testing experiments on research participants in the United States and Poland, and they found that adding rosiglitazone to the medicines reduced bitterness for many, but not all, research participants.

“People differ, and we need to test many types of people from different parts of the world to make sure that efforts to reduce bitterness and make medicines easier to take work well for all people,” said senior author Danielle Reed, PhD, Monell Chief Science Officer.

These results suggest having more blockers to choose from will help entirely suppress the bitterness of many types of medicines for a wide range of populations and ancestries. Mixtures of several blockers may help attain a low-to-zero-bitterness standard for even the most bitter-tasting medicines.

“Although rosiglitazone was only partially effective as a bitter blocker in this study, modifying these drugs to improve potency, palatability, and efficacy may allow us to find a better version of this drug,” said Nguyen. “Rosiglitazone is valuable as a bitter blocker because it is potentially effective in most people and is part of a class of drugs already approved worldwide for treating diabetes.”

Next steps in this line of research include a similar study that measures bitter blocking in several hundred African and Asian immigrants to add to the diversity of participants’ ancestries with regard to bitter taste.

This work was supported by the National Institutes of Health (R42 DC017693), the Monell Chemical Senses Center’s Carol M. Christensen Postdoctoral Fellowship in Human Chemosensory Science Fund, and Monell Chemical Senses Center Institutional Funds.

The study, published today in the Proceedings of the National Academy of Sciences, uses climate and agricultural data from Brazil. It finds that climate change has a cascading effect on farming, leading to increased loan defaults for one of the nation’s largest public sector banks. Over the next three decades, climate-driven loan defaults could increase by up to 7%, according to the study.

The projections in the paper revealed that although temperatures are rising everywhere, there is substantial variation in what that looks like from region to region, which underscores the need to build distinct types of physical and financial resilience.

For example, parts of northern Brazil are predicted to have more dramatic seasonal swings around 2050, with heavier rainfall in winter and drier summers, so policymakers should be thinking about the need for water storage by building dams and reservoirs as well as increasing groundwater storage capacity. Conversely, central Brazil may have fairly steady weather, but will have higher overall temperatures, pointing to a need for heat-resistant crops.

The authors of the paper used a statistical approach pairing past climate data in Brazil with information on crop productivity, farm revenue and agricultural loan performance. They combined this data with climate simulations to predict future weather conditions and their impacts on farming and how those changes will affect financial institutions.

“A difficulty in studying climate impacts on agriculture is that there are all sorts of adaptations happening all the time that aren’t easily observed, but are really important for understanding vulnerability and how risk is changing,” said coauthor Jennifer Burney, professor of environmental science at UC San Diego’s School of Global Policy and Strategy and Scripps Institution of Oceanography. “We were able to distinguish signals from different types of climate impacts and which ones led to this larger financial risk.”

Systematic thinking about building resilience against climate change around the globe

A key objective of the research is to support resilient food security under a changing climate, which requires understanding of when small climate shifts might have outsized impacts, spilling across regions or into other sectors through institutions like trade and banking.

Understanding the systemic risk posed by climate change is especially helpful for policymakers and disaster relief agencies, as climate change has increasingly become a national security threat. To that end, the statistical approach developed in the study could be applied around the globe.

“The technique we developed will help populations identify where they are most vulnerable, how climate change will hurt them the most economically and what institutions they should focus on to build resilience,” said study coauthor Craig McIntosh, professor of economics at the School of Global Policy and Strategy.

For example, some governments in the Western Pacific region buy extra food on the global market in emerging El Niño years, when their own crop productivity suffers. The statistical approach used in the study could help governments around the world understand their own climate conditions and whether local, regional or international institutions will be best placed to address them.

The research could be especially helpful with the development of the loss and damage fund established by the United Nations in 2022. The fund is designed to help compensate developing nations that have contributed the least to the climate crisis but have been facing the brunt of its devastating floods, drought and sea-level rise.

“Our technique could help countries think about where the resilience returns would be highest for the money spent,” said Krislert Samphantharak, professor of economics at the School of Global Policy and Strategy. “This technique also helps to identify where international reinsurance might be needed.”

The “Empirical Modeling of Agricultural Climate Risk” study was also coauthored by Bruno Lopez-Videla, who earned a Ph.D. in economics from UC San Diego in 2021 and Alexandre Gori Maia of the Universidade Estadual de Campinas in Brazil.

Heart attack is a common disease with risks of serious complications. It has long been unclear what the best strategy is for treating narrowings in coronary arteries separate from the specific vessel that caused the infarction.

A new large Swedish study has investigated whether it is sufficient to treat only the coronary artery that caused the infarction, or whether long-term results are better if other narrowed vessels are also treated with balloon dilation as a preventive measure.

The clinical randomized study included 1542 patients from 32 hospitals in 7 countries. In the Swedish part, the SWEDEHEART registry was used to conduct the randomization and collect data. Patients were followed up for five years after the procedure.

The results show no difference between the groups in terms of new heart attacks, new unplanned balloon dilations or the total number of all-cause deaths.

“This is somewhat surprising. Our hypothesis was that it would be beneficial to do preventive angioplasty,” says Felix Böhm, a senior physician at the Department of Clinical Sciences, Danderyd Hospital at Karolinska Institutet, who led the study.

However, when it comes to problems with angina, the study shows that it is possible to avoid patients coming back for new balloon dilations through preventive treatment. According to Felix Böhm, this suggests that we should still aim for complete treatment of all vessels.

“But for those patients where there is some circumstance that makes a complete revascularization complicated, one might choose to wait, since there was no difference in the most serious complications — new heart attack and death,” says Felix Böhm.

If problems with angina occur, these patients can then come back later for a new treatment, according to Felix Böhm.

“A positive finding of the study was that most patients do not come back with new problems, regardless of the treatment strategy chosen. “Nowadays, heart attack patients are so well treated with drugs that it is difficult to find other interventions that provide further significant risk reduction,” says Felix Böhm.

The researchers will now go on to investigate how angina and other quality of life parameters in the patients were affected by the different treatment strategies, as well as health economic aspects of the chosen strategy.

The research was conducted by Uppsala Clinical Research Center (UCR) at Uppala University. The legal sponsor was Karolinska University Hospital. The study was funded by the Swedish Research Council, Hjärt-Lungfonden, Region Stockholm, Abbott and Boston Scientific. The companies had no influence on study design, results analysis or article writing.

BeatProfiler, new tool to rapidly analyze heart cell function

Researchers at Columbia Engineering unveiled a groundbreaking new tool today that addresses these challenges head-on. BeatProfiler is a comprehensive software that automates the analysis of heart cell function from video data and is the first system to integrate the analysis of different heart function indicators, such as contractility, calcium handling, and force output into one tool, speeding up the process significantly and reducing the chance for errors. BeatProfiler enabled the researchers to not only distinguish between different diseases and levels of their severity but also to rapidly and objectively test drugs that affect heart function. The study was published on April 8 in IEEE Open Journal of Engineering in Medicine and Biology.

“This is truly a transformative tool,” said project leader Gordana Vunjak-Novakovic, University Professor and the Mikati Foundation Professor of Biomedical Engineering, Medical Sciences, and Dental Medicine at Columbia. “It’s fast, comprehensive, automated, and compatible with a broad range of computer platforms so it is easily accessible to investigators and clinicians.”

Software is open-source

The team, which included Barry Fine, assistant professor of medicine (in Cardiology) at Columbia University Irving Medical Center, elected not to file a patent application, and instead are offering the AI software as open source, so it can be directly used — for free — by any lab. They believe that this is important for disseminating the results of their research, as well as for getting feedback from users in academic, clinical, and commercial labs that can help the team to further refine the software.

The need to diagnose heart disease quickly and accurately

This project was driven, like much of Vunjak-Novakovic’s research, by a clinical need to diagnose heart diseases more quickly and accurately. This was a project that was several years in the making in which the team added different features piece by piece. While the overarching need was to develop a tool that could better capture the function of the cardiac models that the team was building to study cardiac diseases and assess the efficacy of potential therapeutics, the researchers had an urgent need to quickly and accurately assess the function of their cardiac models in real-time.

As the lab was making more and more cardiac tissues through innovations such as milliPillar and multiorgan tissue models, the increased capabilities of the tissues required the researchers to develop a method to more rapidly quantify the function of cardiomyocytes (heart muscle cells) and tissues to enable studies exploring genetic cardiomyopathies, cosmic radiation, immune-mediated inflammation, and drug discovery.

Collaborators in software development, machine learning, and more

In the last year and a half, lead author Youngbin Kim and his coauthors developed a graphical user interface (GUI) on top of the code so that biomedical researchers with no coding expertise could easily analyze the data with just a few clicks. This brought together experts in software development (for the GUI development), machine learning (for developing computer vision technology and disease/drug classifiers), signal processing (for processing contractile and calcium signals), engineering (translating pillar deflection on the cardiac platform to mechanical force), and user experience by lab members (to give feedback for improvements in the interface).

The results

The study showed that BeatProfiler could accurately analyze cardiomyocyte function, outperforming existing tools by being faster — up to 50 times in some cases — and more reliable. It detected subtle changes in engineered heat tissue force response that other tools might miss.

“This level of analysis speed and versatility is unprecedented in cardiac research,” said Kim, a PhD candidate in Vunjak-Novakovic’s lab at Columbia Engineering. “Using machine learning, the functional measurements analyzed by BeatProfiler helped us to distinguish between diseased and healthy heart cells with high accuracy and even to classify different cardiac drugs based on how they affect the heart.”

What’s next

The team is working to expand BeatProfiler’s capabilities for new applications in heart research, including a full spectrum of diseases that affect the pumping of the heart, and drug development. To ensure that BeatProfiler can be applied to a wide variety of research questions, they are testing and validating its performance across additional in vitro cardiac models, including different engineered heart tissue models. They are also refining their machine-learning algorithm to extend and generalize its use to a variety of heart diseases and drug effect classification. The long-term goal is to adapt BeatProfiler to pharmaceutical settings to speed up the testing of hundreds of thousands of candidate drugs at once.