Daily Archives: June 11, 2022

Research tools, cell lines, and other technologies, many of which are patented, are useful for, but separate from, the product or therapy being developed. When the question of third-party patent rights is raised with respect to such patented technologies, many partners dismiss the concern on the ground that the development of the product or therapy is being conducted in support of a Biologics License Application (BLA) to FDA, and therefore is immune from an infringement lawsuit pursuant to the development safe harbor.

Indeed, in the United States, 35 USC 271(e)(1) expressly exempts from an infringement suit certain otherwise infringing acts, so long as they are conducted solely for uses reasonably related to the development and submission of information under a Federal law that regulates the manufacture, use, or sale of drugs or biological products.

Similar exemptions exist under the laws of many other jurisdictions. Historically, this safe harbor, also known as the Bolar exemption, has been broadly construed in the U.S. However, as recent case law indicates, where a patented research tool such as a cultured host cell useful in the manufacture of a gene therapy product or a fluorescent protein is itself not subject to FDA premarket approval, the safe harbor may not apply.

As additional patented research tools become available, developers of CTGT products would be prudent to include any potential development technologies as part of their freedom-to-operate analysis moving forward. And in development collaboration arrangements, companies should ensure that their partners engaged in development work have secured the appropriate licenses for the conduct of such development activities.

This article is the fifth in our 2022 series, Trends in Cell, Tissue, and Gene Therapies, which aims to help you stay informed about the broad array of legal and regulatory issues affecting companies operating in the regenerative medicine space. From clinical studies, to obtaining patents, to scaling up manufacturing, our global team will discuss novel issues arising in all parts of the world, including unique deal-making, litigation, and inspections concerns for CTGT companies.

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CTGT transactions: Beware of ripples in the safe harbor - JD Supra

Both I and my girlfriend, have children from previous relationships. But still, one child is not enough. It doesnt feel like I got enough enjoyment with children. And I think its good to have children because somebody needs to take over in the future, Smigrodzki said. So, between my girlfriend and I, we decided to have a child.

Due to his girlfriends age, one of the couples only options was IVF.

Smigrodzki was interested in also using the tests offered by Genomic Prediction. They met with an IVF doctor in Charlotte, North Carolina. Since the testing was new, the company sent a scientist to explain the technology to the doctors on the IVF team.

During the next visit, our physician told us that they would not let us use the technology, because that [would be] unethical.

Smigrodzki disagreed with the doctors decision.

A physician who tells you that they will not use a life and health-saving technology because its unethical is a physician who is making a big mistake. Theres absolutely no credible reasoning that would justify this kind of a decision, Smigrodzki said.

This wouldnt be the last time Genomic Prediction caused tension. Controversy and resistance seem to follow the company.

Stephen Hsu, a co-founder of Genomic Prediction, said he became interested in computational genomics about 10 years ago.

It became possible to build predictors using machine learning and artificial intelligence, which would look directly at the DNA of an individual and could tell whether someone was at unusually high risk, for example, for a specific disease condition. When we started seeing how powerful these techniques were, we realized one of the most obvious applications of it would be in embryo selection, Hsu said.

IVF clinics have long tested embryos for genetic diseases. But what differentiates Genomic Prediction from routine genetic testing is the companys promise to give an overall health impression of an embryo not just testing to see if it has a specific disease or not.

This is much more complicated than screening, say, for Huntingtons disease. A single gene causes that disease, and tests for Huntingtons disease have a 99.9% accuracy rate. But test results for complex conditions, meaning they involve many, even thousands of genes, like heart disease or diabetes, are much less precise. So instead of giving definitive results, Genomic Prediction provides a risk score an estimate of how likely an embryo will be to develop a disease.

One very common case, which weve seen many times already, is a couple comes in and they know they have a family history of x. And just to take a concrete example, x could be breast cancer. So it could be that in the mothers family tree, there are women that had breast cancer, said Hsu.

And they may just say, Look, I saw my aunt die from breast cancer, and I just dont want it to happen to my daughter. So, I just want to make sure that of the embryos we look at, I want the one we implant to be normal risk, not high risk.'

Testing for breast cancer risk may not sound all that controversial. But you could imagine where this could go.

Remember that Smigrodzkis first IVF doctors refused to administer the test, calling it unethical.

To start, the same technology that can test for complex diseases can also test for things like eye color, skin tone, or height.

So, the accuracy with which one can predict height, from DNA alone, for people who have good family environments, you know, growing up, the error is less than three centimeters now, Hsu said.

That means the scientists at Genomic Prediction say theyre able to predict adult height within a bit more than an inch before you are even born. But they are not doing that yet.

We only provide risk scores for very impactful common diseases. Because its just too controversial, people just get too excited, Hsu said. We can make predictions about IQ scores of individuals. But we do not provide any of that information in our IVF service, just because its too controversial.

But what about traits that fall somewhere in the middle of eye color and disease risk?

We can predict BMI [body mass index], Hsu said. And theres a whole complex of health problems that come with being significantly overweight. Now, are we going to report BMI prediction scores? Would people call us fat shaming if we did that? As you know, its extremely delicate.

Hsu and his company are pioneers with this type of genetic testing. They are making choices on what diseases and traits to test for, how accurate the tests should be, and if they should even offer the test. And the work they are doing will influence the direction this industry takes.

There are guidelines from the American Society for Reproductive Medicine. And those guidelines support the use of this kind of technology to prevent disease, they do not explicitly support the use of this kind of technology for cosmetic purposes, and they dont really talk about IQ, Hsu said.

So, its kind of a gray area. Were certainly not forbidden from doing it, but we just chose not to do it. Because from our perspective, theres so much good that you can do just on the purely medical health risk front, that we dont want that to get drowned out by this other stuff.

Hsu never explicitly said where he draws the line. But he did say that people should have a better understanding of these tests.

People should become aware of how the technology works, how does heredity work, how the genes work people should learn that. And then, through a kind of democratic process, they should decide this is the kind of society we want to be. This is what we should allow. We like gene editing, we dont like gene editing, we like embryo selection, we dont, he said.

He says this technology, the ability to screen embryos for diseases and even non-disease traits, is becoming more sophisticated, and more importantly, it is becoming more available. There are other companies that plan to offer similar testing.

Even though Genomic Prediction doesnt offer scores based on intelligence, a recent article in Bloomberg follows a couples journey with embryo selection. The couple used Genomic Prediction and wanted more data than the company offers, so they downloaded the raw embryo data. They analyzed it to weigh the odds of mental health traits, like stress management and chronically low mood. They told Bloomberg that what was most important to them was mental health and performance.

As this genetic modeling continues to improve and become more wide-spread, we must start asking the hard questions: How will we use it?

Laura Hercher, director of research in human genetics at Sarah Lawrence College in Bronxville, New York, says almost everything to do with embryos and manipulation of embryos stirs up some controversy.

Hercher is a trained clinical genetic counselor, licensed to work with patients. But lately, she spends her time educating on ethical, legal, and social issues in genomic medicine. She says these test results are much more nuanced than they may seem.

Ive talked to a lot of genetic counselors about embryo testing. And mostly we have a good laugh. I always say if I was going to write a textbook on genetics which, God forbid I would entitle it, It Turned Out to be More Complicated Than They Thought.'

One of the biggest challenges with these risk scores is that scientists simply dont know all of the genes involved with complex conditions like heart disease or cancer.

Another problem is that the information scientists do have comes from genetic databases with overwhelming white, European participants. Applying that data to other populations, some scientists say, is misleading.

Its population data, which means that you have to be very careful about how you use it for an individual, Hercher said.

These genetic tests say something about your risk, the way your zip code, when youre born says something about your risk. If we calculated it over a population, and said, whats your chance of going to college based on the zip code you were born in? We could trace a relationship, right? Thats intuitive. But it would not be causal it would not be the end point.

So, the tests arent perfect. But they will continue to improve. Already, parents who use IVF can select an embryo based on its biological sex, which is not a concerning medical condition. They can also screen embryos for rare, devastating disorders like Huntingtons disease. But soon, testing could include conditions that may or may not be considered a serious medical concern.

Hercher said, take ADHD or autism, for example.

People might fear these conditions, they might particularly fear them based on sort of worst-case scenario thinking, that it can get very bad. But also, these are medical labels we have applied in some cases, to things that were well within the spectrum of, really normal behavior, said Hercher. And I think globally, big picture, when people look at the use of these technologies with embryos, one of their fears has to have something to do about reducing our vision of what is normal and acceptable in the human population. And specifically doing that, for people who can pay for it.

Stephen Hsu from Genomic Prediction said that his company was starting to see inquiries from couples interested in doing IVF just so they could do the embryo selection process. Couples tell him:

Hey, we heard about this, and it just seems like such a smart thing to do. Were actually considering doing IVF. Because we can get a better health outcome for our children, even though were not necessarily having fertility issues, Hsu said.

IFV is already very expensive, and the additional genetic test itself is about $2,000 per cycle. Hercher warns that we must be careful about how this difference in access will impact society.

So, how do you draw the actual lines there? I think the only way to do it is to try and bring the population along with you, Hercher said, to try and explain the limitations of the genetics and explain the negative effects of too much selection and too much trying to control what a child is like.

With all of that in place, Hercher said she doesnt, see an option other than to trust parents to make decent decisions.

Fundamentally, one reason why we dont want to get into selection of things that are less like diseases and more like traits, she added, is that what we owe our children above everything else, is to accept them and love them as they are.

Rafal Smigrodzki says it was his sense of fatherly responsibility that influenced his decision.

You see, its all about the children. Its not about us, right? Smigrodzki said. He said he expects that children would be grateful if parents choose certain traits for them, like intelligence.

Intelligence is a good, Smigrodzki said Its not a weapon that we use against each other in a fight. Its actually something that we use to understand and control the world. And its precisely our intelligence that gives us the ability to progress to build civilization. So, theres absolutely nothing wrong, in my opinion, in selecting an embryo based on intelligence.

For Smigrodzki and his girlfriend, they ultimately found an IVF provider in Washington D.C. that was willing to work with Genomic Prediction. They started with 16 embryos and eventually had five surviving embryos genetically tested.

Out of the remaining five, one had a chromosomal abnormality, so it was immediately rejected. And out of the four remaining ones Genomic Prediction provided a list of odds for different conditions, including cancer, diabetes, hypertension, and cardiovascular disease, he said.

Its up to the parents to decide how to weigh those odds. Smigrodzki decided to select the embryo with the lowest risk of heart disease. Later, Genomic Prediction came up with an overall, embryonic health score, taking into account each possible condition, the odds, and the potential for a higher quality of life. Smigrodzki later had those embryonic health scores calculated for the four embryos he had to choose from.

The embryo that became Aurea [had] by far the best health score of the four of them. So, it means that I could congratulate myself because I selected the best embryo.

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Startup offers genetic testing that promises to predict healthiest embryo - WHYY

Womens Health Research at Yale today announced funding for three new studies. They include one of the first studies to examine sex differences in treating neuroendocrine neoplasms (NENs), a rare form of cancer often found in the gastrointestinal tract. The second study will examine the effect of gender-affirming hormone therapy during adolescence on bone development. The third study will utilize machine-learning and brain imaging techniques to understand the mechanisms through which a particular genetic variant increases the risk for developing Alzheimers disease more significantly for women than men.

The more we investigate the role of sex and gender on our health, the more we learn how differences can lead to quite large impacts, said WHRY Director Carolyn M. Mazure, PhD. These new studies explore critical features of health and disease to ensure that everyone has the best health care throughout life. Such care starts with research that considers all aspects of biology and behavior that make us unique.

The new studies ask significant questions with practical consequences for health. Can analyses of a large U.S. database and multiple completed clinical trials in patients with NENs identify sex-based differences in treatment-related side effects? And, can these studies help inform additional research to identify changes in DNA that are associated with these side effects? Can data collected using state-of-the-art bone density equipment and analysis techniques guide efforts to minimize short- and long-term risks for bone growth to adolescent individuals undergoing gender affirming hormone therapy? And can newly designed neuroimaging techniques successfully map the relationships among brain circuitry, sex, aging, and cognitive task performance to inform the development of new targeted prevention strategies and therapies for the estimated 15% to 25% of women who carry the single greatest known genetic risk factor for Alzheimers disease?

This years Wendy U. and Thomas C. Naratil Pioneer Award has been granted to Dr. Pamela Kunz. With co-funding from Yale Cancer Center, Dr. Kunz will study sex-based differences in adverse events associated with treating neuroendocrine neoplasms (NENs).

About 12,000 people in the United States are diagnosed with an NEN every year, a number that has been increasing for years as diagnostic techniques have improved and awareness has grown. Though rare by incidence, NENs are the second most prevalent gastrointestinal cancer after colorectal cancer, due largely to their slow growth. Research has shown that treatment-related toxicities are common among patients treated for these cancers, contributing to poor quality of life, worse outcomes, and increased costs both to the patient and the health care system. These challenges are especially important in chronic cancers such as NENs.

And while large population-based studies suggest that there are sex differences in the number of patients diagnosed with NENs each year, where the cancer starts, and survival rates, there have been few studies dedicated to the role sex plays in the side effects of treating these tumors.

One such study showed that female patients undergoing treatment for NENs had twice the rate of low platelets (cells that help blood clot) and five times the risk of low white blood cells (the cells that fight infection). These increased side effects have the potential for many negative downstream consequences for female patients involving quality of life, financial costs, and outcomes, particularly if treatments are interrupted or doses reduced.

Dr. Kunz, an oncologist, associate professor of medicine at Yale School of Medicine, and director of the Center for Gastrointestinal Cancers at Smilow Cancer Hospital and Yale Cancer Center, is utilizing a large U.S. database of patient information to provide an important biological window into such sex differences in NEN treatment side effects. Her team will also identify candidate genes or common gene variations that are associated with the risk of a single toxicity from treatment or a cluster of related toxicities.

By identifying sex differences and genetic predictors of these side effects, researchers can then tailor treatments to reduce the toxicity of the treatments and improve survival rates.

As a female doctor who treats gastrointestinal cancers and an advocate for gender equity, I am eager to apply the lens of equity to my own research, said Kunz, who also serves as the vice chief of diversity, equity, and inclusion for the medical oncology section at Yale Cancer Center. If we confirm an increase in treatment-related side effects for female patients with NENs, we can propose proactive steps to better understand and lower these risks.

The sex hormones estrogen and testosterone are critical regulators of bone health, contributing in different but complementary ways to the development of bone strength and structure during puberty. The typical patterns and timing of pubertal development are significantly altered in transgender youth who undergo gender-affirming hormone therapy (GAHT) during adolescence, and the effects of these hormonal regimens on the process of bone development are not fully understood.

Transgender youth, particularly youth transitioning from male to female, may have delays in development of overall bone strength that improve over time.

However, overall bone strength reflects a basic, single approximation of a dynamic process that can vary greatly among individuals. Newer assessments of bone structure can now account for variations in bone strength within the bone, which may help to predict fracture risk over time. But there are limited data for these newer measurements to determine what might be usual in youth undergoing gender-affirming hormone therapy, an increasingly common but understudied treatment.

In a survey published by The Trevor Project in 2019, nearly 2% of youth identified as transgender, more than double a 2017 estimate from a survey of adults. And while not every transgender individual undergoes gender-affirming hormone therapy, young people identifying as transgender and their families need more information about the effects of GAHT on bone health to minimize risk and improve long-term health outcomes.

With a grant from WHRY, Dr. Stuart Weinzimer, professor of pediatrics at Yale School of Medicine, will work with youth extensively screened psychologically and medically through Yales Pediatrics Gender Program prior to choosing GAHT. Dr. Weinzimer will utilize the latest and most sophisticated measures of bone health to characterize the changes in the density, quality, and architecture of bones as well as the metabolic markers of bone health over the first year of gender-affirming hormone treatment in transgender youth. In addition, Dr. Weinzimers team will identify demographic, clinical, and behavioral variables such as diet and exercise that may facilitate or interfere with normal skeletal health in this population as they age.

We are focusing on the first year of treatment because this is the time of maximal alterations in the hormonal environment, Weinzimer said. This study will not only collect important data on individuals assigned female at birth and those who are affirmed in the female gender undergoing treatment but will also guide providers in developing hormone treatment regimens that minimize short- and long-term risks and optimize skeletal health over time.

Weinzimer is recruiting transgender adolescents prior to initiating either testosterone or estrogen treatment, analyzing bone health within each group from baseline measurements through the end of the year and between the two groups receiving different hormones. He will also assess the potential effects of prior use of puberty blockers on biological markers of bone health at the beginning of the study and after one year.

These data will ultimately help us to understand if current treatments are effective in optimizing skeletal health when initiating affirming hormone therapies and the role played by non-pharmacological influences, such as physical activity and diet, in the trajectories of these metrics over time, Weinzimer said. Given the increasing number of adolescents undergoing gender-affirming treatments, it is vital to understand how these therapies either increase or mitigate risk so that we can provide informed counseling and identify potential interventions."

About two-thirds of the six million people affected by Alzheimers disease (AD) in the United States are women. The reasons for this gender difference include the average longer lifespan of women as well as social determinants of health that are not as easily accessed by women, such as higher education, opportunities for physical fitness, and stimulating employment which all provide protective benefits for brain health as we age. But research continues to reveal the role of biological factors as well.

For example, a genetic variant of the apolipoprotein E (APOE) gene on chromosome 19, known as the APOE-4 allele, accounts for up to 50% of genetic risk for Alzheimers disease. APOE helps to create a protein involved in carrying cholesterol and other types of fat through the bloodstream. Women who carry one or two copies of this allele (people inherit one APOE allele from each parent) face a four- to twelvefold increased risk of Alzheimers disease as they age. In comparison, men who carry just one APOE-4 allele have little or no increased risk.

Approximately 25% of the U.S. population carries at least one APOE-4 allele. But we only have limited understanding of how this genetic variant interacts with brain connections to increase womens vulnerability to AD.

With a two-year WHRY grant, Dr. Carolyn Anne Fredericks is using magnetic resonance imaging (MRI) with a new technique developed at Yale by Dr. Todd Constable, director of MRI Research, and colleagues, to understand the functional impact of APOE-4 on the brains of women who develop Alzheimers disease and create new opportunities for targeted therapies. Known as connectome-based predictive modeling, the technique provides a map of connections within the brain to match with non-imaging biological markers associated with a predictor of interest, such as a behavior or a gene. For this study, the researchers will seek robust predictors for the presence of an APOE-4 allele as well as short-term memory performance and compare the results for women and men.

We dont yet understand whether there are specific aspects of brain connectivity that predict poorer memory test performance in women, as opposed to men, and whether these are affected by the inclusion of other variables, such as level of education, said Dr. Fredericks, an assistant professor of neurology and a clinician specializing in neurodegenerative disorders. Gaining this knowledge would motivate future work targeting these connections for future therapy, whether behavioral or drug-based.

Previous neuroimaging studies attempting to address the relationship between sex, aging, and cognitive task performance have been hampered by relevantly small datasets with limited power and capacity to generalize to larger populations, as well as analytical techniques that are not often validated and have limited predictive power.

Dr. Fredericks will access a large database of individuals who are cognitively healthy yet have abnormal Alzheimers protein build up in their brains as documented by a specialized positron emission tomography (PET) scan. In addition to APOE genotype, the database also includes extensive health information and MRI data. She will use connectome-based predictive modeling to avoid over-fitting to any specific data set and increase the likelihood findings will be applicable to larger populations.

We believe that this work has the potential to inform the development of new targeted therapies for the 15 to 25% of women carry at least one 4 allele, Fredericks said. As well as for women with poorer short-term memory performance, particularly related to lower cognitive reserve, who are at future risk of Alzheimers disease.

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WHRY Funds Studies on Sex Differences in Treating Gastrointestinal Cancers, Bone Health in Transgender Youth, and the Greater Risk for Alzheimer's...

Research funded by the grant will capitalize on the development of biomarkers and advanced imaging by scientists at the Keck School of Medicine of USC to launch studies tracking changes in the blood-brain barrier, neurovascular function and cognition.

By Hope Hamashige

Blood vessels in the brain (Credit: Stevens INI)

The National Institute on Aging, a division of the National Institutes of Health, awarded Berislav Zlokovic, MD, PhD, director of the Zilkha Neurogenetic Institute, and Arthur W. Toga, PhD, director of the USC Mark and Mary Stevens Neuroimaging and Informatics Institute (Stevens INI), $16.1 million to continue research on the role that blood vessel dysfunction plays in the development of dementia and Alzheimers disease.

Berislav Zlokovic, MD, PhD, director of the Zilkha Neurogenetic Institute (Photo USC)

There is increasing evidence that neurovasculature has a major role in early cognitive decline, said Zlokovic, chair and professor of physiology and neurosciences at the Keck School of Medicine of USC. This grant allows us to continue important research on how changes in the blood-brain barrier and blood flow interact with amyloid-beta and tau pathology to trigger structural and functional changes in the brain leading to cognitive impairment and early Alzheimers disease.

More than 30 years ago, Zlokovic was among the first to propose that flaws in the blood-brain barrier, which keeps harmful substances in the blood from moving into brain tissue, could be the early, underlying cause of most cognitive disorders, rather than the accumulation of amyloid beta plaque, which had long been the focus of Alzheimers research. With this award, he and his colleagues can further test this so-called neurovascular hypothesis.

This work will build on our earlier work, which has shown that people can progress to mild cognitive impairment, independent of amyloid beta and tau if the blood-brain barrier is damaged, said Zlokovic.

Documenting Alzheimers disease progression

The funding will allow the team of researchers to launch longitudinal studies comparing the progress of more than 400 people who have a genetic variant putting them at high risk for developing Alzheimers disease known as apolipoprotein E4 (APOE4) with more than 450 people with APOE3, a different variant which puts them at lower risk for developing Alzheimers disease.

About 75% of the participants will be cognitively unimpaired at the start of the study and about 25% will have only mild impairment. The researchers will follow them for five years, tracking changes in the blood-brain barrier, blood flow and the brains structure and function while monitoring participants for cognitive impairment, using neuroimaging and molecular biomarkers indicating blood vessel dysfunction, which were developed by Zlokovic, and advanced brain imaging technology developed by Toga.

Perivascular spaces in the brain highlighted using data from the Stevens INIs ultra-high field 7T MRI scanner Credit: Stevens INI

Using our ultra-high field 7T magnetic resonance imaging (MRI) scanner has transformed our understanding of how fluid-filled regions in the brain perivascular spaces impact brain health. Here at the Stevens INI, we have successfully used this advanced imaging to facilitate breakthroughs, including the central role that perivascular space plays in brain changes associated with aging, including neurodegenerative disorders, said Toga, Provost Professor of Ophthalmology, Neurology, Psychiatry and the Behavioral Sciences, Radiology and Engineering at the Keck School of Medicine. Our imaging capabilities have allowed us to create a multimodal assessment of the role of neurovasculature in cognitive decline, a comprehensive research program on perivascular spaces, and numerous close-up investigations of how fluids travel through the brain, including via the blood-brain barrier. Im thrilled to have received this funding to continue our work in partnership with Dr. Zlokovic.

Arthur W. Toga, PhD, director, Mark and Mary Stevens Neuroimaging and Informatics Institute Director. (Photo INI)

Researchers hope the work will lead to a better understanding of the onset and progression of Alzheimers disease and the identification of the best interventions for different stages of the disease.

Testing treatments in the lab

Simultaneously, the team will conduct complementary laboratory research using mice that have been genetically altered to carry human APOE gene variants to help document changes in the brain that lead to cognitive decline and to test a potential treatment.

The treatment is an experimental neuroprotective enzyme co-developed by Zlokovics team, in collaboration with John Griffin, PhD, from the Scripps Research Institute, called 3K3A-APC, an engineered form of human activated protein C. Researchers will test it in the altered mice to see if it can protect the integrity of the blood-brain barrier and prevent cognitive decline. In addition they hope to examine whether this type of intervention is effective at the earliest signs of vascular dysfunction or at later stages of disease in mouse models that also have amyloid beta and tau. The National Institute of Neurological Disorders and Stroke (NINDS) recently awarded funding for a pivotal Phase 3 clinical trial of 3K3A-APC in stroke patients, led by Patrick Lyden, MD, professor of physiology and neuroscience at the Zilkha Neurogenetic Institute.

We hope that the results of this research will eventually lead us to new treatments for people with the APOE4 gene, said Zlokovic.

Turning biomarkers into a blood test for Alzheimers disease

Zlokovic added that they continue to improve on key molecular biomarkers, and he hopes eventually to discover biomarkers detectible in blood, which would make the process of identifying people at risk for Alzheimers disease simpler and more accessible.

We have been pursuing several avenues of research that all complement one another, said Zlokovic. We believe that this research will contribute to important new findings about the pathogenesis of cognitive decline and will also lead to development of important new therapies for cognitive impairment, dementia and Alzheimers disease.

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NIH awards USC more than $16 million for research on vascular dysfunction and Alzheimer's disease | Keck School of Medicine of USC - University of...

Introduction

Globally, metformin is favored as first-line anti-hyperglycemic therapy for type 2 diabetes (T2D). It is consumed by more than 150 million people annually due to its affordable price, safety, and considerable pleiotropic effects that have a positive impact on glycemic control, insulin resistance, cardiovascular health, and cancer in T2D patients.1 Its main anti-hyperglycemic effects described as suppression of hepatic glucose production and increased insulin-induced glucose uptake in skeletal muscle without stimulating insulin secretion, make this biguanide a prominent drug for treatment nave TD2 patients.1

In addition, metformin improves obesity-associated inflammatory effects and reduces body weight, thus, it is widely prescribed in countries with a high prevalence of obesity and T2D, such as the United States and Mexico.24 The pharmacodynamics of this biguanide is decisive to achieve the therapeutic goal, including the gastrointestinal side effects involved in non-adherence to treatment.5 In the enterocyte, the OCT1 protein is the transmembrane channel through which metformin is absorbed to reach the circulation, and consequently, the liver. In hepatocytes, OCT1 is the main route of metformin uptake due to its subsequent effect on the phosphorylation of T172 in the alpha subunit of AMP-activated protein kinase (AMPK), promoting the inhibition of the mitochondrial respiratory chain complex 1 and mG3PDH enzymatic activity, which leads to one of its main anti-hyperglycemic effects: a decrease in hepatic gluconeogenesis.5

Lifestyle modifications, such as diet, physical activity, and psychology counseling are essential to achieve glycemic control in patients with T2D. In particular, the nutritional approach is directly related to the success of the pharmacological therapy since nutrient absorption may influence the pharmacokinetics of metformin and its subsequent anti-hyperglycemic effects.6,7 However, the traditional nutritional approach for T2D patients is focused on weight control and macronutrient quantification, such as complex and simple carbohydrates, soluble fiber and saturated fats since international guidelines for these patients provide limited information on the role of most micronutrients on glycemic control. Furthermore, the interaction between micronutrients and metformin therapy on glycemic and metabolic control in patients with T2D has been poorly explored.6

Recent studies have identified more than 30 polymorphisms in the SLC22A1/OCT1 gene with different effects associated with the metformin response in various ethnic groups. The Met408Val polymorphism (rs628031) of the SLC22A1/OCT1 gene has been the most explored with metformin responses and its genetic effect has differed between studied populations.8,9 Another study using a mouse model with a high-fat-diet (HFD) for 24 weeks reported a decrease in OCT1 mRNA expression of up to 79% in the liver, kidney and intestine of HFD-fed mice, and the expression of OCT1 protein was significantly down-regulated in obese mice at week 12, suggesting that the HFD may have effects on SLC22A1/OCT1 expression, including the pharmacodynamic and therapeutic effects described above.7 However, further studies are required to evaluate variability in glycemic responses to metformin in specific populations due to the pronounced differences in dietary habits around the world, particularly in the micronutrient intake.

In this context, providing an education based in precision medicine (considering clinical, biochemical, pharmacological, and genetic information) is becoming the novel therapeutic approach to improve adherence and pharmacological treatment success on glycemic control, according to individual requirements of T2D patients. The aim of this study was to analyze the effect of metformin and diet on glycemic control and its association with the Met408Val SLC22A1/OCT1 polymorphism (rs628031) in patients with T2D from western Mexico.

From a cohort of 432 patients with T2D,10 a total of 240 subjects were included in this cross-sectional study. Participants received nutritional consultations and psychological counseling from the nutritional program DIABETIMSS. This program aimed to promote and motivate a greater adherence to pharmacological treatment and improve lifestyle to achieve the therapeutic goal involving glycemic control. The inclusion criteria were: (i) T2D diagnosis according to the American Diabetes Association (ADA) criteria:11 fasting glucose level (126 mg/dL) and/or glucose tolerance test >200 mg/dL 2 hours after the glucose load, and (ii) a record of the anti-hyperglycemic treatment. The exclusion criteria were as follows: (i) pregnant or lactating women, (ii) the presence of comorbidities such as cancer, endocrine, gastrointestinal, autoimmune, liver and kidney diseases, (iii) history of substance abuse, and/or (iv) clinically evident complications such as neuropathy or retinopathy. This study was conducted between August and November 2021 at the Specialized Unit in Research, Development and Innovation in Genomic Medicine from the Nayarit Center for Innovation and Technology Transfer of the Autonomous University of Nayarit, Mexico.

This study was reviewed and approved by the Local Health Research and Ethic Committee 1801 (code: R-2021-1801-017), Family Medicine Unit Number 24, Nayarit. Mexican Social Security Institute. We considered the updated version of the Helsinki Declaration-Ethical Principles for Medical Research Involving Human Subject on the 64th WMA General Assembly from, Fortaleza, Brazil, 2013, in the development of this work.11 All participants were recruited through open invitation and they provided written informed consent for inclusion in this study.

General data, pathological personal history, pharmacological treatment, and the anthropometric variables were collected by a medical team with validated methods and standardized procedures. Anti-hyperglycemic therapy was classified as: (i) metformin monotherapy, (ii) dual therapy: metformin + glibenclamide and metformin + insulin, and (iii) triple therapy: metformin + glibenclamide + insulin. The minimum duration of anti-hyperglycemic therapy was one year and therapeutic efficacy was evaluated with HbA1c values according to the ADA criteria (%HbA1c <7).12

Body composition was determined using an electrical bioimpedance equipment (Tanita SC-331S, body composition analyzer, Tanita Corporation, Japan). Waist circumference (WC) was measured using a stretch-resistant tape.13 The body mass index (BMI kg/m2) results were defined as normal weight (18.524.9 kg/m2), overweight (25.029.9 kg/m2) and obesity ( 30 kg/m2) according to the World Health Organization (WHO) criteria.14

Dietary information was collected using a 24-hour recall. Patients were instructed to illustrate the portion and specify the quantities as precisely as possible using food scale models (Nasco) based on the Mexican food composition table.15 Energy intake, macronutrient and micronutrient composition were analyzed by trained dietitians using the Nutritionist Pro Diet Analysis software (Axxya Systems, Stafford, TX, USA). General recommendations by the Ministry of Health were used to compare the dietary reference values.16

After a 12-hour fast, 10 mL of blood sample was taken by venipuncture and immediately centrifuged at 3500 rpm for 15 min to separate serum, then samples were frozen at 80C and stored until later use. The Cobas 6000 analyzer (Roche Diagnostics International Ltd, Risch-Rotkreuz, Switzerland) was used to quantify biochemical parameters, which include glucose, total cholesterol (TC), triglycerides (TG) and high-density lipoprotein cholesterol (HDL-c) using commercial kits. Glycosylated hemoglobin (%Hb1Ac) was determined using the turbidimetric immunoassay inhibition method. Low-density lipoprotein cholesterol (LDL-c) was calculated with the Friedewald formula, except when TG levels were higher than 400 mg/dL.17 The non-high-density lipoprotein cholesterol (non-HDL-c) was evaluated subtracting TC-HDL-c and the triglyceride-glucose index (TyG index) was estimated with the formula Ln [fasting triglycerides (mg/dL) fasting glucose (mg/dL)/2] to determine insulin resistance diagnosis.18 Reference values of biochemical tests were according to the ATP III and ADA guidelines.12,19

The modified salting-out method was carried out to extract and purify genomic DNA (gDNA) from whole blood20 and it was quantified using nano spectrophotometry with the Nanodrop One equipment (Thermo ScientificTM, Massachusetts, United States). The genotyping of the Met408Val (rs628031) SLC22A1/OCT1 polymorphism was performed by real-time PCR in a LightCycler 96 instrument (Roche Diagnostics, Mannheim, Germany) using TaqMan SNP genotyping assays (catalog number C___8709275_60; ThermoFisher Scientific). The sequence context was CGTGGGCCGCATCTACCCCATGGCC[G/A]TGTCAAATTTGTTGGCGGGGGCAGC.

The accuracy of the genotyping assay was verified using positive controls of DNA samples corresponding to the three possible genotypes (GG, GA & AA) and negative controls in each 96-well plate assay. Twenty percent of the samples were tested in duplicate as a quality control measure and 100% reproducibility was obtained. The Hardy-Weinberg equilibrium (HWE) and analysis of molecular variance (AMOVA) were estimated using Arlequin software (version 3.0).

The sample size was calculated using the formula for a simple correlation where the population genetic data was obtained from the 1000 Genomes Project (America= 0.22). For a 95% confidence level and 80% power, a minimum sample size of 160 participants was required. The data was analyzed using the statistical program Stata 12 (StataCorp LLC, College Station, TX, USA; http://www.stata.com) and SPSS Statistics software version 25.0 for Windows (IBM Corp, Inc., Chicago, IL, United States). First, the KolmogorovSmirnov test was used to evaluate the normality of the data and the Levenes test to verify the homogeneity of the study variables. Descriptive statistics were used to describe the main characteristics of participants. Data with normal distribution were analyzed through parametric statistical tests (Students t-test and one-way ANOVA with their respective post hoc tests) and non-normal data with non-parametric statistical tests (KruskalWallis and MannWhitney U). The chi-square test was used when variables were categorical. The interactions between SLC22A1/OCT1 gene and diet nutrients were obtained through multiple linear regression tests adjusted by age, sex, BMI, years with T2D, type of anti-hyperglycemic therapy and energy intake as covariates and %Hb1Ac levels and TyG index as dependent variables. The tests with significant p-values were corrected using the Bonferroni post hoc method. The partial correlation coefficients were performed to assess the relation between nutrient intake with %HbA1c levels and TyG index analyzed by metformin and dual therapy groups considering the carrier allele. A p-value <0.05 was considered statistically significant.

The clinical, anthropometric and biochemical characteristics of patients with T2D by anti-hyperglycemic therapy are shown in Table 1. Overall, the total sample had excessive adiposity due to a BMI >30 kg/m2, body fat percentage >30% and waist circumference >100 cm. The time of T2D evolution was different according to the anti-hyperglycemic therapy. Subjects taking metformin as monotherapy had a significantly shorter time with T2D than those taking dual or triple anti-hyperglycemic therapy (4.55.4 vs 10.69.5 and 12.810.4, p<0.001). As expected, this same difference was observed at the time of anti-hyperglycemic therapy consumption (4.35.2 vs 9.38.0 and 12.410.2, p<0.001) (Table 1).

Table 1 Clinical Features and Biochemical Profile of Patients with T2D According to Anti-Hyperglycemic Therapy

With respect to the glycemic profile, T2D patients showed an average of blood concentrations above the reference values, but these parameters were different according to the type of anti-hyperglycemic treatment. Glucose, %HbA1c and TyG index were lower in the metformin monotherapy group than the other anti-hyperglycemic therapy groups, particularly those with dual therapy (p<0.01) (Table 1). Moreover, the individuals with metformin as monotherapy had a higher frequency of glycemic control (%HbA1c <7.0) compared with the dual and triple treatment schemes (77% vs 35% and 15%, respectively; p<0.001). On the other hand, those patients receiving dual therapy (metformin+glibenclamide/metformin+insulin) presented the highest frequency of insulin resistance according to the TyG index, compared to those patients receiving metformin monotherapy (98% vs 92%, p=0.049) (Table 1). No statistically significant differences in age, sex, anthropometric profile, and lipid profile between type of anti-hyperglycemic therapy were found.

The macronutrient and micronutrient intake by anti-hyperglycemic therapy are shown in Table 2. Regardless of the type of pharmacological treatment, total consumptions of sugar, protein, fat, saturated fatty acids (SFA), and dietary cholesterol for all patients were above the recommendations for a healthy and balanced diet. Also, lower intakes of polyunsaturated fatty acids (PUFA), dietary fiber, and micronutrients as well calcium, magnesium, zinc, and vitamin D were observed in all study groups. Interestingly, a high intake of potassium was documented in the three anti-hyperglycemic therapy groups. There were no direct associations between anti-hyperglycemic therapy (Table 2.)

Table 2 Nutrient Intakes of T2D Patients According to Anti-Hyperglycemic Therapy

The distribution of the Met408Val (rs628031) polymorphism in the SLC22A1/OCT1 gene is shown in Table 3. Genotype frequencies were GG homozygotes (76.6%), GA heterozygotes (21.5%) and AA homozygotes (1.9%). The allele frequency was 87.4% for the ancestral allele G and 12.6% for the risk allele A. This polymorphism was in Hardy Weinberg equilibrium (HWE), p=0.750. Also, the analysis of molecular variance (AMOVA) revealed a genetically homogeneous sample (p=0.439). The frequency distribution analysis based on glycemic control (%HbA1c <7) showed a slightly higher frequency trend of the AA risk genotype in T2D patients without glycemic control compared to those with glycemic control (4.5% vs 0.0%, p=0.204). Genotype frequencies of GG and GA were similar in both group analyses (Table 3).

Table 3 SLC22A1/OCT1 (rs628031) Genotype and Allele Distribution Among Patients with T2D According of the Glycemic and Type of Anti-Hyperglycemic Therapy

Regarding the type of anti-hyperglycemic therapy, a higher frequency of genotype GA heterozygote was observed in those patients receiving metformin monotherapy compared to the dual therapy group; however, this difference was not statistically significant (22.9% vs 13.0%, p=0.142). The frequency of the risk AA genotype was 1.2% for the metformin monotherapy group, 4.4% for the dual therapy group and 0.0% for the triple therapy group (Table 3). The frequencies for ancestral allele G and for risk allele A were similar regardless of glycemic control (p=1.000) and type of anti-hyperglycemic therapy (p=0.208).

Regarding clinical variables of interest by alleles, no differences in age and sex were observed between study groups. In carriers of the risk allele A, the mean duration of T2D was 2.52.7 years and 2.22.1 years for anti-hyperglycemic therapy, and they were significantly lower than for carriers of the G allele who had a mean T2D duration of 5.36.4 years (p=0.047) and 5.05.9 years for anti-hyperglycemic therapy (p=0.038) (Table 4). The average BMI in carriers of the risk allele A was 32.18.3 kg/m2 and 29.44.9 kg/m2 in G allele carriers with no significant differences (p=0.426). The frequency of patients with normal weight was lower (16% allele G vs 10% allele A), while overweight and obesity showed higher frequencies in both groups, however, these differences were not significant (p=0.215) (Table 4).

Table 4 Clinical Features and Biochemical Profile of T2D Patients According to Alleles of Met408Val (rs628031) SLC22A1/OCT1 Polymorphism in Monotherapy with Metformin

For glycemic control, no significant differences were observed by alleles with mean glucose levels below 130 mg/dL in both study groups. The average %HbA1c reflects that both groups are in glycemic control (<7%), with more than 70% of the subjects achieving this goal, however, the mean TyG index is above the recommended score and more than 90% of the subjects have insulin resistance by this index (Table 4). Serum lipid levels, total cholesterol, triglycerides, and non-HDL-c were within the recommended levels for both groups, but HDL-c was below the suggested range, while LDL-c was close to the recommended value, and no significant differences were found for each of these variables (Table 4).

Nutrient intakes did not show significant differences by group in most of the macronutrient and micronutrient recorded data with an average caloric intake of less than 2000 kilocalories per day. However, it should be highlighted that the total intake of sugar, protein, fat, SFA, and MUFA in both groups was above the recommended values as well as dietary cholesterol and potassium, whereas for PUFA, dietary fiber, magnesium, zinc and calcium, the intake was lower than the recommended intake for both groups. In addition, vitamin D intake in both groups was below the recommended dose and significantly higher in carriers of the risk allele A compared to G allele carriers (p=0.004) (Table 5).

Table 5 Nutrient Intake of T2D Patients According to Alleles of the SLC22A1/OCT1 (rs628031) Polymorphism in Monotherapy with Metformin

Statistical analyses showed relevant gene-diet interactions associated with glycemic outcomes. First, risk allele A carriers with a high calcium intake showed increased %HbA1c levels, which was not observed in non-risk allele G carriers (P int.=0.028) (Figure 1A). In this context, only in the group receiving metformin monotherapy and carriers of the risk allele A, we found a positive correlation between calcium intake and %Hb1Ac levels (r=0.682, p=0.010), controlled by age, sex, and energy intake (Figure 1B). Secondly, elevated TyG index levels were found after high potassium intake only in carriers of the risk allele A (P int.=0.027) (Figure 2A), and a positive correlation between potassium intake and TyG index, only in the group receiving metformin monotherapy and carriers of the risk allele A (r=0.593, p=0.033), controlled by age, sex and energy intake (Figure 2B). Additionally, we performed the same correlations of calcium intake vs %Hb1Ac levels (p=0.948) and potassium intake vs TyG index (p=0.159) within all groups, but without statistical significance. Then, we performed the analysis considering drug treatment (monotherapy vs dual or more drugs), but results did not reach statistical significance (p>0.05). Lastly, the only positive correlation was for patients under monotherapy with metformin and carriers of the risk allele A (Figures 1B and 2B).

Figure 1 Interaction and correlation between dietary calcium and OCT1 polymorphism regarding HbA1c. (A) Interaction between dietary calcium and OCT1 polymorphism regarding HbA1c values. (B) Correlation between dietary calcium and HbA1c values within risk allele A carriers + metformin monotherapy adjusted by age, sex and energy intake.

Figure 2 Interaction and correlation between dietary potassium and OCT1 polymorphism regarding the TyG index. (A) Interaction between dietary Potassium and OCT1 polymorphism regarding the TyG index values. (B) Correlation between dietary potassium and TyG index values within risk allele A carriers + metformin monotherapy, adjusted by age, s ex and energy intake.

Glycemic control is one of the main goals in primary care for T2D patients. Lifestyle along with physical activity, an adjusted diet to nutritional needs, and the anti-hyperglycemic therapy integrated to the right behavioral health of the individual, are the basis for achieving glycemic control in institutional programs such as DIABETIMSS.21,22

In this study, the group of patients who had metformin monotherapy had significantly fewer years with T2D, and consequently, less time with pharmacological therapy than patients with dual or triple therapy. This can be explained by the therapeutic approach according to the international treatment guidelines in which metformin is proposed as a pharmacological therapy of initiation and insulin secretagogues are added when euglycemia is not achieved.23,24 In the natural course of the disease, gradual loss of pancreatic beta-cell function with decreased secretion of insulin have been demonstrated as the pathology progresses in many of the patients, which impact glycemic control.25,26 The best glycemic profile in the group of patients with metformin monotherapy showed a shorter duration with T2D, which is consistent with the Prospective Diabetes Study (UKPDS).25 An important aspect of all patients in this study is the initiation of the diet and pharmacological therapy, which begin technically once the diagnosis is established and as a result, differences in glycemic control and triglycerides were observed, as well a high percentage of patients who achieved the goal of HbA1c <7% and better TyG index in the metformin monotherapy group.

The nutritional analyses in study subjects reflect what previous urban diet studies of western Mexico have published: a high intake of refined sugars accompanied by low fiber intake, an unhealthy composition of dietary fats, as well as micronutrients such as calcium, magnesium, zinc and potassium.10,27,28 In the three anti-hyperglycemic therapy groups, the nutritional composition resembles the westernized diet, which is usually deleterious for carbohydrate and lipid metabolism, and is reflected in the BMI with higher frequency of overweight and obesity, total body fat and waist circumference, independently of anti-hyperglycemic therapy.28 In addition, this high dietary fat intake and excessive total body fat could downregulate SLC22A1/OCT1 gene expression as shown by study of Lu et al, and consequently, the pharmacokinetics of metformin and its therapeutic effect.7

The genotypic and allelic frequencies shown in this study are similar to those reported by Resndiz-Abarca et al, in another group of Mexican patients with T2D where the risk allele A was 16.9%, which is in accordance with the allele A frequency observed in our population.32 In the 1000 Genomes Project Phase 3, the reported global frequency of this polymorphism (rs628031) for the risk allele A is 31%, with Europe being the geographical region where it reaches the highest frequency (41%), followed by Southeast Asia (39%), Africa (27%), East Asia (26%) and the lowest frequency of 22% is reported in America.29

The risk allele A of the Met408Val (rs628031) polymorphism in the SLC22A1/OCT1 gene has been associated with decreased therapeutic efficacy of metformin in several populations worldwide, and recently with a significant increase of %HbA1c in patients with T2D from Mexico, a country that belongs to the North American region.8,29,30 With this low frequency of the A allele in the Mexican population (13% 17%) and probably in other Latin American countries like Brazil where the prevalence of T2D is high,31 it would be expected that more subjects achieve the goal of glycemic control %HbA1c <7 with metformin therapy. In contrast, the high frequency of this risk allele in Europe and United States of America, could be of clinical consideration in those who do not achieve the glycemic goal of HbA1c <7% with metformin as monotherapy.31,32 However, allele analysis showed that despite the fact that carriers of the risk A allele have significantly less time with T2D and anti-hyperglycemic therapy, they do not shower better glycemic control than carriers of the G allele as it could be expected for a shorter period of time with T2D, which is consistent with a decreased anti-hyperglycemic effect in these carriers as shown in other studies.8,9

A relevant nutrigenetic finding of this study was the interactions between the Met408Val polymorphism (rs628031) of SLC22A1/OCT1 gene and the dietary intakes of calcium and potassium regarding glycemic outcomes as statistically significant differences were found. This data highlights the importance of gene-micronutrient interactions and status monitoring in T2D patients, particularly for SLC22A1/OCT1 (rs628031) risk allele A carriers, to achieve an improved metabolic control within a new metabolic approach that entails personalized medicine. Moreover, our results are consistent with previous reports analyzing the role of DRD2 and APOE gene variants on glycemic outcomes in T2D patients through nutritional interactions.10,33 This association between higher calcium and potassium consumption with the increase in %HbA1c and TyG index in T2D patients carrying the risk allele A of polymorphism of SLC22A1/OCT1 gene (rs628031) has an important clinical significance because there are populations such as the Caucasian European whose prevalence of this risk allele A is close to 50% and the prevalence of osteoporosis after 60 years of age is greater than 10%, and in these adult patients, the recommended calcium daily intake is between 800 and 1200 mg, which could affect glycemic control.34,35

It should be noted that there is a wide acknowledgement on the effect of metformin on the 5 adenosine monophosphate-activated protein kinase/sirtuin1 (AMPK/Sirt1) pathway activation to modulate blood glucose levels and hepatic glucose production.21,36,37 In type 2 diabetes, obesity and insulin resistance, AMPK and Sirt1 become important targets since they decrease hyperglycemia and show similar metabolic outcomes.3840

Furthermore, Fu et al, reported synergistic activity between metformin administration and the branched-chain amino acid (BCAA) leucine intake on glycemic control as leucine may activate AMPK/Sirt1 pathway in diet-induced obese mice.41 In this sense, we also suggested possible synergistic activity between calcium intake and metformin in the monotherapy group, since intracellular calcium through calcium/calmodulin-dependent kinase II (CaMKII) increases the AMP/ADP ratio, and consequently activates the AMPK pathway.4244 This could explain, in part why the individuals with metformin as monotherapy had better glycemic control compared with dual or triple therapy.

Besides, other authors have suggested a possible interaction between the co-administration of metformin. Shibata, et al, reported that peficitinib inhibited Metformin uptake in OCT1 and MATE1/2-K-expressing cells.45 Therefore, we suspect a drugdrug interaction on glycemic control, due to the metformin monotherapy effect, which was not found in the other study groups, but more studies are necessary. Moreover, our findings suggest that polymorphism SLC22A1/OCT1 (rs628031) and the effect of metformin may have modified the expected response between glycemic control and micronutrient intake, since the group with A risk allele + metformin drug and higher calcium intake showed a low diabetes control. From the clinical point of view, it is worth considering that a subject with metformin monotherapy who does not achieve the glycemic control goal of %HbA1c <7 in the early stages of T2D, could be a carrier of the risk allele A with a higher dietary intake of calcium or potassium than the recommended dosage.

A limitation of this study is the population studied as extrapolation to a larger population and the blood concentration of metformin as the main endpoint are needed because other factors in glycemic control might intervene, such as insulin secretion capacity, resistance to the action of this hormone, adiposity, diet, and physical activity. Moreover, although interaction studies are very reliable, type I and type II statistical errors cannot be completely ruled out.

This study reports a relevant interaction between the micronutrient intake of calcium and potassium with the Met408Val (rs628031) polymorphism of the SLC22A1/OCT1 gene regarding the glycemic control of patients with T2D from western Mexico. Subjects who received metformin as monotherapy and are carriers of the risk allele A of the Met408Val (rs628031) polymorphism showed a significant positive correlation between calcium intake and %HbA1c, as well as potassium with the TyG index. These findings suggest a differential effect of metformin on glycemic control depending on calcium and potassium intake regarding the Met408Val (rs628031) polymorphism of the SLC22A1/OCT1 gene in patients with T2D. One perspective to consider with these findings is the relevance of micronutrient interactions for new therapeutic approaches in primary care to contribute to glycemic control.

The authors express their gratitude to participants of this cohort study for their enthusiastic support and the staff of Family Medicine Unit No. 24 of Mexican Institute of Social Security for their valuable help. We acknowledge students in Nutrition Luis Roberto Mejia Godoy and Ivette Xitlalli Eleuterio Salvador, as well as Pharmaceutical Chemists Fabiola B. Moreno Escalera, Kevin J, Fras Delgadillo and Sara A. Campos Huerta for their support in obtaining data of all patients in this study.

To the Interinstitutional Program for the Strengthening of Research and Graduate Studies of the Pacific (Dolphin Program) for promoting the collegiate work that led to the creation of the Dolphin Research Networks within the mobility subprogram of professors and researchers.

The laboratory infrastructure was supported by The National Council for Science and Technology (CONACyT), Mxico (grant number: INFR-2016-01-268517) and material by The Secretary of Public Education (SEP), Mxico (grant number: P/PFCE-2018-18MSU0019M-04). Part of this project was carried out with resources from the special tax destined to the Autonomous University of Nayarit (Article Publishing Charge) Both sources did not participate in the collection, analysis and interpretation of data; neither in the writing and/or in the decision to submit this article.

The authors report no conflicts of interest in this work.

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